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Kris Boudt

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.

    Cited by:

    1. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
    2. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 21-18, Federal Reserve Bank of Philadelphia.
    3. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
    4. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," Working Papers 2022-06, Joint Research Centre, European Commission.

  2. David Ardia & Keven Bluteau & Kris Boudt, 2021. "Media abnormal tone, earnings announcements, and the stock market," Papers 2110.10800, arXiv.org.

    Cited by:

    1. Perico Ortiz, Daniel & Schnaubelt, Matthias & Seifert, Oleg, 2023. "A topic modeling perspective on investor uncertainty," FAU Discussion Papers in Economics 04/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

  3. David Ardia & Keven Bluteau & Kris Boudt & Koen Inghelbrecht, 2020. "Climate change concerns and the performance of green versus brown stocks," Working Paper Research 395, National Bank of Belgium.

    Cited by:

    1. Bua, Giovanna & Kapp, Daniel & Ramella, Federico & Rognone, Lavinia, 2022. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," Working Paper Series 2677, European Central Bank.
    2. Meinerding, Christoph & Schüler, Yves S. & Zhang, Philipp, 2023. "Shocks to transition risk," Discussion Papers 04/2023, Deutsche Bundesbank.
    3. Apel, Matthias & Betzer, André & Scherer, Bernd, 2023. "Real-time transition risk," Finance Research Letters, Elsevier, vol. 53(C).
    4. Inessa BENCHORA & Aurélien LEROY & Louis RAFFESTIN, 2023. "Is Monetary Policy Transmission Green?," Bordeaux Economics Working Papers 2023-08, Bordeaux School of Economics (BSE).
    5. Tiziano De Angelis & Peter Tankov & Olivier David Zerbib, 2022. "Climate Impact Investing," Carlo Alberto Notebooks 676 JEL Classification: G, Collegio Carlo Alberto.
    6. Ardia, David & Bluteau, Keven & Tran, Thien Duy, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Finance Research Letters, Elsevier, vol. 48(C).
    7. Pástor, Luboš & Stambaugh, Robert F. & Taylor, Lucian, 2022. "Dissecting Green Returns," CEPR Discussion Papers 16260, C.E.P.R. Discussion Papers.
    8. Joost Bats & Giovanna Bua & Daniel Kapp, 2023. "Physical and transition risk premiums in euro area corporate bond markets," Working Papers 761, DNB.
    9. Bats, Joost Victor & Bua, Giovanna & Kapp, Daniel, 2024. "Physical and transition risk premiums in euro area corporate bond markets," Working Paper Series 2899, European Central Bank.
    10. Ho, Kelvin & Wong, Andrew, 2023. "Effect of climate-related risk on the costs of bank loans: Evidence from syndicated loan markets in emerging economies," Emerging Markets Review, Elsevier, vol. 55(C).
    11. Rabeh Khalfaoui & Salma Mefteh-Wali & Jean-Laurent Viviani & Sami Ben Jabeur & Mohammad Zoynul Abedin & Brian Lucey, 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Post-Print hal-03797937, HAL.
    12. Venturini, Alessio, 2022. "Climate change, risk factors and stock returns: A review of the literature," International Review of Financial Analysis, Elsevier, vol. 79(C).
    13. Milot Hasaj & Bernd Scherer, 2021. "Covid-19 and smart beta," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 515-532, December.
    14. Iulia Lupu & Adina Criste, 2022. "Tendencies In Green Finance," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 3, pages 57-63, June.
    15. Du, Qianqian & Su, Wanxuan & Liang, Dawei & Wang, Luying, 2023. "How does green preference impact sustainability-based investment strategy? Evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 124(C).
    16. Zhang, Si Ying, 2022. "Are investors sensitive to climate-related transition and physical risks? Evidence from global stock markets," Research in International Business and Finance, Elsevier, vol. 62(C).
    17. Olivier David Zerbib, 2022. "A Sustainable Capital Asset Pricing Model (S-CAPM): Evidence from Environmental Integration and Sin Stock Exclusion [Asset pricing with liquidity risk]," Review of Finance, European Finance Association, vol. 26(6), pages 1345-1388.
    18. Borghesi, S. & Castellini, M. & Comincioli, N. & Donadelli, M. & Gufler, I. & Vergalli, S., 2022. "European green policy announcements and sectoral stock returns," Energy Policy, Elsevier, vol. 166(C).

  4. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.

    Cited by:

    1. Lassance, Nathan & Vrins, Frédéric, 2020. "Robust portfolio selection using sparse estimation of comoment tensors," LIDAM Discussion Papers LFIN 2020003, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," LIDAM Reprints LFIN 2021005, Université catholique de Louvain, Louvain Finance (LFIN).

  5. David Ardia & Kris Boudt & Giang Nguyen, 2018. "Beyond risk-based portfolios: balancing performance and risk contributions in asset allocation," ULB Institutional Repository 2013/286494, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Monica Billio & Bertrand Maillet & Loriana Pelizzon, 2022. "A meta-measure of performance related to both investors and investments characteristics," Annals of Operations Research, Springer, vol. 313(2), pages 1405-1447, June.
    2. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
    3. Fays, Boris & Papageorgiou, Nicolas & Lambert, Marie, 2021. "Risk optimizations on basis portfolios: The role of sorting," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 136-163.

  6. Thewissen, James & Torsin, Wouter & Boudt, Kris, 2018. "When does the tone of earnings press releases matter?," LIDAM Reprints LFIN 2018001, Université catholique de Louvain, Louvain Finance (LFIN).

    Cited by:

    1. Mather, Paul & Ranasinghe, Dinithi & Unda, Luisa A., 2021. "Are gender diverse boards more cautious? The impact of board gender diversity on sentiment in earnings press releases," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(3).
    2. Hesham Bassyouny & Tarek Abdelfattah, 2022. "Executives vs. governance: Who has the predictive power? Evidence from narrative tone," Review of Quantitative Finance and Accounting, Springer, vol. 58(1), pages 361-382, January.
    3. Bassyouny, Hesham & Abdelfattah, Tarek & Tao, Lei, 2020. "Beyond narrative disclosure tone: The upper echelons theory perspective," International Review of Financial Analysis, Elsevier, vol. 70(C).
    4. Bassyouny, Hesham & Abdelfattah, Tarek & Tao, Lei, 2022. "Narrative disclosure tone: A review and areas for future research," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 49(C).
    5. Henry, Elaine & Thewissen, James & Torsin, Wouter, 2021. "International Earnings Announcements: Tone, Forward-looking Statements, and Informativeness," LIDAM Discussion Papers LFIN 2021016, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    7. Khine Kyaw & Mojisola Olugbode & Barbara Petracci, 2020. "Is the market surprised by the surprise?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(1), pages 20-29, March.
    8. Arslan-Ayaydin, Özgür & Bishara, Norman & Thewissen, James & Torsin, Wouter, 2020. "Managerial career concerns and the content of corporate disclosures: An analysis of the tone of earnings press releases," International Review of Financial Analysis, Elsevier, vol. 72(C).
    9. Özgür Arslan‐Ayaydin & James Thewissen & Wouter Torsin, 2021. "Disclosure tone management and labor unions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 102-147, January.
    10. Baker, H. Kent & Kumar, Satish & Goyal, Kirti & Sharma, Anuj, 2021. "International review of financial analysis: A retrospective evaluation between 1992 and 2020," International Review of Financial Analysis, Elsevier, vol. 78(C).

  7. Kris Boudt & Christopher J. Neely & Piet Sercu & Marjan Wauters, 2017. "The response of multinationals’ foreign exchange rate exposure to macroeconomic news," Working Papers 2017-20, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Fuchs, Fabian U., 2022. "Macroeconomic determinants of foreign exchange rate exposure," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 77-102.
    2. Yi-Chen Chung & Hsien-Ming Chou & Chih-Neng Hung & Chihli Hung, 2021. "Using Textual and Economic Features to Predict the RMB Exchange Rate," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-8.
    3. Sikarwar, Ekta, 2022. "Board attributes, hedging activities and exchange rate risk: Multi-country firm-level evidence," Economic Modelling, Elsevier, vol. 110(C).
    4. Sikarwar, Ekta, 2020. "Forex interventions and exchange rate exposure: Evidence from emerging market firms," Economic Modelling, Elsevier, vol. 93(C), pages 69-81.
    5. Munazza Jabeen & Abdul Rashid, 2022. "Macroeconomic News and Exchange Rates: Exploring the Role of Order Flow," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 14(2), pages 222-245, May.
    6. Munazza Jabeen & Abdul Rashid & Hajra Ihsan, 2022. "The news effects on exchange rate returns and volatility: Evidence from Pakistan," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 745-769, January.
    7. Yu Ma & Xinqian Du, 2022. "Exchange rate factors, income levels, and investment abroad: An empirical study based on a sample of emerging economies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1711-1730, April.

  8. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.

    Cited by:

    1. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
    2. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    3. Mohamed El Ghourabi & Asma Nani & Imed Gammoudi, 2021. "A value‐at‐risk computation based on heavy‐tailed distribution for dynamic conditional score models," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2790-2799, April.
    4. Tobias Fissler & Yannick Hoga, 2021. "Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability," Papers 2104.10673, arXiv.org, revised Feb 2022.
    5. Ghufran Ahmad & Muhammad Suhail Rizwan & Dawood Ashraf, 2021. "Systemic risk and macroeconomic forecasting: A globally applicable copula‐based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1420-1443, December.
    6. Lööf, Hans & Sahamkhadam, Maziar & Stephan, Andreas, 2021. "Is Corporate Social Responsibility investing a free lunch? The relationship between ESG, tail risk, and upside potential of stocks before and during the COVID-19 crisis," Working Paper Series in Economics and Institutions of Innovation 488, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    7. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
    8. Owusu Junior, Peterson & Alagidede, Imhotep, 2020. "Risks in emerging markets equities: Time-varying versus spatial risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    9. Dennis Umlandt, 2020. "Likelihood-based Dynamic Asset Pricing: Learning Time-varying Risk Premia from Cross-Sectional Models," Working Paper Series 2020-06, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    10. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.

  9. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Value-at-Risk Prediction in R with the GAS Package," Papers 1611.06010, arXiv.org.

    Cited by:

    1. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    2. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    3. Dodo Natatou Moutari & Hassane Abba Mallam & Diakarya Barro & Bisso Saley, 2021. "Dependence Modeling and Risk Assessment of a Financial Portfolio with ARMA-APARCH-EVT models based on HACs," Papers 2105.09473, arXiv.org.

  10. Boudt, Kris & de Goeij, Peter & Thewissen, James & Van Campenhout, Geert, 2015. "Analysts' forecast error: a robust prediction model and its short-term trading profitability," LIDAM Reprints LFIN 2015008, Université catholique de Louvain, Louvain Finance (LFIN).

    Cited by:

    1. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.
    2. Mamatzakis, Emmanuel, 2022. "An international study on the impact of corruption on analysts’ forecasts," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 48(C).
    3. Emmanuel Mamatzakis & Anna Bagntasarian, 2021. "The nexus between CEO incentives and analysts' earnings forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6205-6248, October.
    4. Qin Zhang & He Ni & Hao Xu, 2023. "Forecasting models for the Chinese macroeconomy in a data‐rich environment: Evidence from large dimensional approximate factor models with mixed‐frequency data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 719-767, March.
    5. Hu, Jun & Long, Wenbin & Luo, Le & Peng, Yuanhuai, 2021. "Share pledging and optimism in analyst earnings forecasts: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 132(C).

  11. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," LIDAM Reprints LFIN 2014006, Université catholique de Louvain, Louvain Finance (LFIN).

    Cited by:

    1. Ding, Shusheng & Cui, Tianxiang & Zhang, Yongmin, 2022. "Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect," International Review of Financial Analysis, Elsevier, vol. 83(C).
    2. Paolo Mazza & Mikael Petitjean, 2016. "On the usefulness of intraday price ranges to gauge liquidity in cap-based portfolios," Post-Print hal-01562991, HAL.
    3. George Kapetanios & Michael Neumann & George Skiadopoulos, 2014. "Jumps in Option Prices and Their Determinants: Real-time Evidence from the E-mini S&P 500 Option Market," Working Papers 730, Queen Mary University of London, School of Economics and Finance.
    4. Będowska-Sójka, Barbara & Kliber, Agata, 2019. "The causality between liquidity and volatility in the Polish stock market," Finance Research Letters, Elsevier, vol. 30(C), pages 110-115.
    5. Qingfu Liu & Yiuman Tse & Kaixin Zheng, 2021. "The impact of trading behavioral biases on market liquidity under different volatility levels: Evidence from the Chinese commodity futures market," The Financial Review, Eastern Finance Association, vol. 56(4), pages 671-692, November.
    6. Seok, Sangik & Cho, Hoon & Ryu, Doojin, 2022. "Scheduled macroeconomic news announcements and intraday market sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    8. Sevcan Uzun & Ahmet Sensoy & Duc Khuong Nguyen, 2023. "Jump forecasting in foreign exchange markets: A high‐frequency analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 578-624, April.
    9. Będowska-Sójka, Barbara, 2018. "The coherence of liquidity measures. The evidence from the emerging market," Finance Research Letters, Elsevier, vol. 27(C), pages 118-123.
    10. Ghadhab, Imen, 2018. "Arbitrage opportunities and liquidity: An intraday event study on cross-listed stocks," Journal of Multinational Financial Management, Elsevier, vol. 46(C), pages 1-10.
    11. Dion Bongaerts & Richard Roll & Dominik Rösch & Mathijs van Dijk & Darya Yuferova, 2022. "How Do Shocks Arise and Spread Across Stock Markets? A Microstructure Perspective," Management Science, INFORMS, vol. 68(4), pages 3071-3089, April.
    12. Będowska-Sójka, Barbara, 2020. "Do aggressive orders affect liquidity? An evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 54(C).
    13. Tim Bollerslev & Jia Li & Yuan Xue, 2018. "Volume, Volatility, and Public News Announcements," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2005-2041.
    14. Elaut, Gert & Frömmel, Michael & Lampaert, Kevin, 2018. "Intraday momentum in FX markets: Disentangling informed trading from liquidity provision," Journal of Financial Markets, Elsevier, vol. 37(C), pages 35-51.
    15. Będowska-Sójka, Barbara & Echaust, Krzysztof, 2020. "What is the best proxy for liquidity in the presence of extreme illiquidity?," Emerging Markets Review, Elsevier, vol. 43(C).
    16. Barbara Będowska-Sójka, 2021. "Is liquidity wasted? The zero-returns on the Warsaw Stock Exchange," Annals of Operations Research, Springer, vol. 297(1), pages 37-51, February.
    17. Jian, Zhihong & Zhu, Zhican & Zhou, Jie & Wu, Shuai, 2020. "Intraday price jumps, market liquidity, and the magnet effect of circuit breakers," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 168-186.
    18. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    19. Kam Fong Chan & Phil Gray & Zheyao Pan, 2021. "The profitability of trading on large Lévy jumps," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 627-635, June.
    20. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
    21. Prodromou, Tina & Westerholm, P. Joakim, 2022. "Are high frequency traders responsible for extreme price movements?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 94-111.
    22. Andor, György & Bohák, András, 2017. "Identifying events in financial time series – A new approach with bipower variation," Finance Research Letters, Elsevier, vol. 22(C), pages 42-48.
    23. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market Instability and Technical Trading at High Frequency: Evidence from NASDAQ Stocks," LIDAM Reprints LFIN 2021016, Université catholique de Louvain, Louvain Finance (LFIN).
    24. Ahdi Noomen Ajmi & Roula Inglesi-Lotz, 2021. "Revisiting the Kuznets Curve Hypothesis for Tunisia: Carbon Dioxide vs. Ecological Footprint," Working Papers 202171, University of Pretoria, Department of Economics.
    25. Rangan Gupta & Chi Keung Marco Lau & Seong-Min Yoon, 2017. "OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration," Working Papers 201754, University of Pretoria, Department of Economics.
    26. Sensoy, Ahmet & Serdengeçti, Süleyman, 2020. "Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 68(C).
    27. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    28. Novotný, Jan & Petrov, Dmitri & Urga, Giovanni, 2015. "Trading price jump clusters in foreign exchange markets," Journal of Financial Markets, Elsevier, vol. 24(C), pages 66-92.
    29. Su, Zhifang & Bao, Haohua & Li, Qifang & Xu, Boyu & Cui, Xin, 2022. "The prediction of price gap anomaly in Chinese stock market: Evidence from the dependent functional logit model," Finance Research Letters, Elsevier, vol. 47(PB).
    30. Sun, Bianxia & Gao, Yang, 2020. "Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    31. Mazza, Paolo & Petitjean, Mikael, 2019. "Testing the effect of technical analysis on market quality and order book dynamics," LIDAM Reprints LFIN 2019006, Université catholique de Louvain, Louvain Finance (LFIN).
    32. Doojin Ryu & Robert I. Webb & Jinyoung Yu, 2023. "Who pays the liquidity cost? Central bank announcements and adverse selection," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(7), pages 904-924, July.
    33. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    34. Dinesh Gajurel & Biplob Chowdhury, 2021. "Realized Volatility, Jump and Beta: evidence from Canadian Stock Market," Applied Economics, Taylor & Francis Journals, vol. 53(55), pages 6376-6397, November.
    35. Srivastava, Pranjal & Jacob, Joshy, 2022. "Arbitrage constraints and behaviour of volatility components: Evidence from a natural experiment," IIMA Working Papers WP 2022-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    36. Ao Kong & Hongliang Zhu & Robert Azencott, 2021. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 416-438, April.
    37. Yu Shi & Qixuan Luo & Handong Li, 2019. "An Agent-Based Model of a Pricing Process with Power Law, Volatility Clustering, and Jumps," Complexity, Hindawi, vol. 2019, pages 1-10, February.
    38. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    39. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.
    40. Anabelle Couleau & Teresa Serra & Philip Garcia, 2020. "Are Corn Futures Prices Getting “Jumpy”?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 569-588, March.
    41. Qian, Ya & Tu, Jun & Härdle, Wolfgang Karl, 2019. "Information Arrival, News Sentiment, Volatilities and Jumps of Intraday Returns," IRTG 1792 Discussion Papers 2019-002, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    42. Ao Kong & Robert Azencott & Hongliang Zhu & Xindan Li, 2020. "Pattern recognition in micro-trading behaviors before stock price jumps: A framework based on multivariate time series analysis," Papers 2011.04939, arXiv.org, revised Feb 2021.
    43. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    44. Zhihong Jian & Zhican Zhu & Jie Zhou & Shuai Wu, 2018. "The Magnet Effect of Circuit Breakers: A role of price jumps and market liquidity," Departmental Working Papers 2018-01, The University of Winnipeg, Department of Economics.

  12. Kris Boudt & Ellen C.S. Paulus & Dale W.R. Rosenthal, 2013. "Funding liquidity, market liquidity and TED spread : A two-regime model," Working Paper Research 244, National Bank of Belgium.

    Cited by:

    1. Chiu, Junmao & Lien, Donald & Tsai, Wei-Che, 2023. "Global financial crisis, funding constraints, and liquidity of VIX futures," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    2. Syed Abul Basher & Alfred Haug & Perry Sadorsky, 2017. "The impact of oil-market shocks on stock returns in major oil-exporting countries: A Markov-switching approach," Working Papers 1710, University of Otago, Department of Economics, revised Oct 2017.
    3. Doojin Ryu & Jinyoung Yu, 2022. "Sentiment‐dependent impact of funding liquidity shocks on futures market liquidity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 61-76, January.
    4. Adeel Riaz & Assad Ullah & Li Xingong, 2024. "Does trade policy uncertainty in China and USA matter for key financial markets?," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-30, April.
    5. Sifat, Imtiaz & Zarei, Alireza & Hosseini, Seyedmehdi & Bouri, Elie, 2022. "Interbank liquidity risk transmission to large emerging markets in crisis periods," International Review of Financial Analysis, Elsevier, vol. 82(C).
    6. Xu, Yanyan & Huang, Dengshi & Ma, Feng & Qiao, Gaoxiu, 2019. "Liquidity and realized range-based volatility forecasting: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1102-1113.
    7. Gunay, Samet, 2020. "Seeking causality between liquidity risk and credit risk: TED-OIS spreads and CDS indexes," Research in International Business and Finance, Elsevier, vol. 52(C).
    8. Louisa Chen & Liya Shen & Zhiping Zhou, 2023. "Understand funding liquidity and market liquidity in a regime‐switching model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 589-605, January.
    9. Mansour Ishrakieh, Layal & Dagher, Leila & El Hariri, Sadika, 2018. "The Institute of Financial Economics Financial Stress Index (IFEFSI) for Lebanon," MPRA Paper 116054, University Library of Munich, Germany.
    10. Enoksen, F.A. & Landsnes, Ch.J. & Lučivjanská, K. & Molnár, P., 2020. "Understanding risk of bubbles in cryptocurrencies," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 129-144.
    11. Moinas, Sophie & Nguyen, Minh & Valente, Giorgio, 2017. "Funding Constraints and Market Illiquidity in the European Treasury Bond Market," TSE Working Papers 17-814, Toulouse School of Economics (TSE).
    12. Layal MansourIshrakieh & Leila Dagher & Sadika El Hariri, 2020. "A financial stress index for a highly dollarized developing country : The case of Lebanon," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 20(2), pages 43-52.
    13. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2018. "The impact of oil-market shocks on stock returns in major oil-exporting countries," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 264-280.
    14. O’Donnell, Niall & Shannon, Darren & Sheehan, Barry, 2021. "Immune or at-risk? Stock markets and the significance of the COVID-19 pandemic," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    15. Gian Piero Aielli & Davide Pirino, 2023. "Funding Liquidity and Stocks’ Market Liquidity: Structural Estimation From High-Frequency Data," CEIS Research Paper 568, Tor Vergata University, CEIS, revised 28 Nov 2023.
    16. Rosenthal, Dale W.R., 2009. "Market structure, counterparty risk, and systemic risk," MPRA Paper 36786, University Library of Munich, Germany, revised 19 Dec 2011.
    17. Wang, Yu-Min & Lin, Che-Chun & Tsai, I-Chun, 2023. "State transformation of information spillover in asset markets and effective dynamic hedging strategies," International Review of Financial Analysis, Elsevier, vol. 89(C).
    18. The Editors, 2018. "Reviews of Books and Teaching Materials," The American Statistician, Taylor & Francis Journals, vol. 72(2), pages 206-212, April.
    19. Weijie Pang & Stephan Sturm, 2020. "XVA Valuation under Market Illiquidity," Papers 2011.03543, arXiv.org.
    20. Socaciu, Erzsébet-Mirjám & Nagy, Bálint-Zsolt & Benedek, Botond, 2023. "No place like home: Home bias and flight-to-quality in Group of Seven countries," Economic Modelling, Elsevier, vol. 129(C).
    21. Jakub Jakl, 2019. "The SER Spread Under the ECB Quantitative Easing," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2019(2), pages 43-70.
    22. Marta Gómez-Puig & Mary Pieterse-Bloem & Simón Sosvilla-Rivero, 2022. ""Dynamic connectedness between credit and liquidity risks in EMU sovereign debt markets"," IREA Working Papers 202217, University of Barcelona, Research Institute of Applied Economics, revised Oct 2022.
    23. Dudek, Jérémy, 2013. "Illiquidité, contagion et risque systémique," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/13236 edited by Le Fol, Gaëlle.
    24. Zhang, Dayong & Lei, Lei & Ji, Qiang & Kutan, Ali M., 2019. "Economic policy uncertainty in the US and China and their impact on the global markets," Economic Modelling, Elsevier, vol. 79(C), pages 47-56.

  13. David Ardia & Kris Boudt, 2013. "Implied Expected Returns and the Choice of a Mean-Variance Efficient Portfolio Proxy," Cahiers de recherche 1328, CIRPEE.

    Cited by:

    1. David Ardia & Guido Bolliger & Kris Boudt & Jean-Philippe Gagnon-Fleury, 2017. "The impact of covariance misspecification in risk-based portfolios," Annals of Operations Research, Springer, vol. 254(1), pages 1-16, July.

  14. Kris Boudt & Jon Danielsson & Siem Jan Koopman & Andre Lucas, 2012. "Regime switches in the volatility and correlation of financial institutions," Working Paper Research 227, National Bank of Belgium.

    Cited by:

    1. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    3. H. Dewachter & G. de Walque & M. Emiris & P. Ilbas & J. Mitchell & R. Wouters, 2012. "Endogenous financial risk : The seventh international conference of the NBB," Economic Review, National Bank of Belgium, issue iii, pages 135-146, December.
    4. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.

  15. BOUDT, Kris & CROUX, Christophe & LAURENT, Sébastien, 2011. "Outlyingness weighted covariation," LIDAM Reprints CORE 2443, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    2. Chan, Kam Fong & Bowman, Robert G. & Neely, Christopher J., 2017. "Systematic cojumps, market component portfolios and scheduled macroeconomic announcements," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 43-58.
    3. Kim Christensen & Silja Kinnebrock & Mark Podolskij, 2010. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," Post-Print hal-00732537, HAL.
    4. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    5. Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
    6. Gnabo, Jean-Yves & Hvozdyk, Lyudmyla & Lahaye, Jérôme, 2014. "System-wide tail comovements: A bootstrap test for cojump identification on the S&P 500, US bonds and currencies," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 147-174.
    7. Cecilia Mancini & Vanessa Mattiussi & Roberto Reno', 2012. "Spot Volatility Estimation Using Delta Sequences," Working Papers - Mathematical Economics 2012-10, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    8. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2015. "Which continuous-time model is most appropriate for exchange rates?," Post-Print hal-01457402, HAL.
    9. Kim, Jihyun & Park, Joon & Wang, Bin, 2020. "Estimation of Volatility Functions in Jump Diffusions Using Truncated Bipower Increments," TSE Working Papers 20-1096, Toulouse School of Economics (TSE).
    10. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    11. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    12. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2010. "Jump-robust volatility estimation using nearest neighbor truncation," Staff Reports 465, Federal Reserve Bank of New York.
    13. Yaojie Zhang & Yu Wei & Li Liu, 2019. "Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1425-1438, September.
    14. Liu, Qiang & Liu, Yiqi & Liu, Zhi, 2018. "Estimating spot volatility in the presence of infinite variation jumps," Stochastic Processes and their Applications, Elsevier, vol. 128(6), pages 1958-1987.
    15. Iulia LUPU & Gheorghe HURDUZEU & Mariana NICOLAE, 2016. "Connections Between Sentiment Indices And Reduced Volatilities Of Sustainability Stock Market Indices," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 157-174.
    16. Vander Elst, Harry & Veredas, David, 2014. "Disentangled jump-robust realized covariances and correlations with non-synchronous prices," DES - Working Papers. Statistics and Econometrics. WS ws142416, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    18. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    19. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    20. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    21. Cecilia Mancini & Fabio Gobbi, 2010. "Identifying the Brownian Covariation from the Co-Jumps Given Discrete Observations," Working Papers - Mathematical Economics 2010-05, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    22. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    23. Michael Ho & Jack Xin, 2016. "Sparse Kalman Filtering Approaches to Covariance Estimation from High Frequency Data in the Presence of Jumps," Papers 1602.02185, arXiv.org, revised Apr 2016.
    24. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    25. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    26. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    27. YI, Chae-Deug, 2023. "Exchange rate volatility and intraday jump probability with periodicity filters using a local robust variance," Finance Research Letters, Elsevier, vol. 55(PA).

  16. BOUDT, Kris & CROUX, Christophe & LAURENT, Sabéastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," LIDAM Reprints CORE 2411, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Christian Walter, 2020. "Sustainable Financial Risk Modelling Fitting the SDGs: Some Reflections," Sustainability, MDPI, vol. 12(18), pages 1-28, September.
    2. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    3. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    4. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    5. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    6. Dette, Holger & Golosnoy, Vasyl & Kellermann, Janosch, 2022. "Correcting Intraday Periodicity Bias in Realized Volatility Measures," Econometrics and Statistics, Elsevier, vol. 23(C), pages 36-52.
    7. Deniz Erdemlioglu & Nikola Gradojevic, 2020. "Heterogeneous investment horizons, risk regimes, and realized jumps," Post-Print hal-02995997, HAL.
    8. Machin, Stephen & Marie, Olivier & Vujic, Suncica, 2012. "Youth Crime and Education Expansion," IZA Discussion Papers 6582, Institute of Labor Economics (IZA).
    9. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    10. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    11. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    12. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Documentos de Trabajo del ICAE 2016-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    13. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    14. Jean-Yves Gnabo & J�rôme Lahaye & S�bastien Laurent & Christelle Lecourt, 2012. "Do jumps mislead the FX market?," Quantitative Finance, Taylor & Francis Journals, vol. 12(10), pages 1521-1532, October.
    15. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," AMSE Working Papers 1843, Aix-Marseille School of Economics, France.
    16. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    17. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.
    18. Halbleib, Roxana & Dimitriadis, Timo, 2019. "How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203669, Verein für Socialpolitik / German Economic Association.
    19. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    20. Turiel, Jeremy D. & Aste, Tomaso, 2022. "Heterogeneous criticality in high frequency finance: a phase transition in flash crashes," LSE Research Online Documents on Economics 113892, London School of Economics and Political Science, LSE Library.
    21. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    22. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    23. Piccotti, Louis R., 2018. "Jumps, cojumps, and efficiency in the spot foreign exchange market," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 49-67.
    24. Sevcan Uzun & Ahmet Sensoy & Duc Khuong Nguyen, 2023. "Jump forecasting in foreign exchange markets: A high‐frequency analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 578-624, April.
    25. Gnabo, Jean-Yves & Hvozdyk, Lyudmyla & Lahaye, Jérôme, 2014. "System-wide tail comovements: A bootstrap test for cojump identification on the S&P 500, US bonds and currencies," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 147-174.
    26. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    27. Będowska-Sójka, Barbara, 2020. "Do aggressive orders affect liquidity? An evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 54(C).
    28. Kris Boudt & Koen Schoors & Milan van den Heuvel & Johannes Weytjens, 2023. "The Consumption Response to Labour Income Changes," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1067, Ghent University, Faculty of Economics and Business Administration.
    29. Eichler, M. & Türk, D., 2013. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Energy Economics, Elsevier, vol. 36(C), pages 614-624.
    30. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2015. "Which continuous-time model is most appropriate for exchange rates?," Post-Print hal-01457402, HAL.
    31. Barbara Będowska-Sójka, 2021. "Is liquidity wasted? The zero-returns on the Warsaw Stock Exchange," Annals of Operations Research, Springer, vol. 297(1), pages 37-51, February.
    32. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    33. Michael C. Tseng & Soheil Mahmoodzadeh, 2022. "Information Jumps, Liquidity Jumps, and Market Efficiency," JRFM, MDPI, vol. 15(3), pages 1-21, February.
    34. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
    35. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    36. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    37. Prodromou, Tina & Westerholm, P. Joakim, 2022. "Are high frequency traders responsible for extreme price movements?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 94-111.
    38. Dovonon, Prosper & Goncalves, Silvia & Hounyo, Ulrich & Meddahi, Nour, 2017. "Bootstrapping high-frequency jump tests," IDEI Working Papers 870, Institut d'Économie Industrielle (IDEI), Toulouse.
    39. Tao Chen & Kam C. Chan & Haodong Chang, 2022. "Periodicity of trading activity in foreign exchange markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(2), pages 445-465, June.
    40. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," Journal of Financial Markets, Elsevier, vol. 17(C), pages 121-149.
    41. Chao YU & Xujie ZHAO, 2021. "Measuring the Jump Risk Contribution under Market Microstructure Noise – Evidence from Chinese Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, December.
    42. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    43. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    44. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market Instability and Technical Trading at High Frequency: Evidence from NASDAQ Stocks," LIDAM Reprints LFIN 2021016, Université catholique de Louvain, Louvain Finance (LFIN).
    45. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
    46. Wu, Fan & Wang, Guan-jun & Kong, Xin-bing, 2022. "Inference on common intraday periodicity at high frequencies," Statistics & Probability Letters, Elsevier, vol. 191(C).
    47. Iulia LUPU & Gheorghe HURDUZEU & Mariana NICOLAE, 2016. "Connections Between Sentiment Indices And Reduced Volatilities Of Sustainability Stock Market Indices," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 157-174.
    48. Fried, Roland, 2012. "On the online estimation of local constant volatilities," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3080-3090.
    49. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    50. Sensoy, Ahmet & Serdengeçti, Süleyman, 2020. "Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 68(C).
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    52. Novotný, Jan & Petrov, Dmitri & Urga, Giovanni, 2015. "Trading price jump clusters in foreign exchange markets," Journal of Financial Markets, Elsevier, vol. 24(C), pages 66-92.
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    54. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    55. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    56. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    57. Sun, Bianxia & Gao, Yang, 2020. "Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    58. Adrian Cantemir CĂLIN & Radu LUPU, 2016. "The Effects Of Labor Market News On International Financial Markets," Romanian Economic Business Review, Romanian-American University, vol. 11(2), pages 207-215, June.
    59. Jérôme Lahaye & Christopher Neely, 2020. "The Role of Jumps in Volatility Spillovers in Foreign Exchange Markets: Meteor Shower and Heat Waves Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 410-427, April.
    60. Eichler, M. & Türk, D.D.T., 2012. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Research Memorandum 035, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    61. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.
    62. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    63. Seema REHMAN & Saqib SHARIF & Wali ULLAH, 2023. "Relative Signed Jump and Future Stock Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 25-45, March.
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    65. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
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    74. Jan Hanousek & Jan Novotný, 2014. "Cenové skoky během finanční nejistoty: od intuice k regulační perspektivě [Price Jumps during Financial Crisis: From Intuition to Financial Regulation]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 32-48.
    75. Yingjie Dong & Yiu-Kuen Tse, 2017. "Business Time Sampling Scheme with Applications to Testing Semi-Martingale Hypothesis and Estimating Integrated Volatility," Econometrics, MDPI, vol. 5(4), pages 1-19, November.
    76. Lucian Liviu Albu & Radu Lupu & Adrian Cantemir Călin, 2016. "Impact Of FOMC Official Speeches on the Intraday Dynamics of CDS Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-12, June.
    77. Lee, Suzanne S. & Wang, Minho, 2020. "Tales of tails: Jumps in currency markets," Journal of Financial Markets, Elsevier, vol. 48(C).
    78. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    79. Noemi Nava & Tiziana Di Matteo & Tomaso Aste, 2015. "Time-dependent scaling patterns in high frequency financial data," Papers 1508.07428, arXiv.org, revised Dec 2015.
    80. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    81. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
    82. Boffelli, Simona & Urga, Giovanni, 2015. "Macroannouncements, bond auctions and rating actions in the European government bond spreads," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 148-173.
    83. YI, Chae-Deug, 2023. "Exchange rate volatility and intraday jump probability with periodicity filters using a local robust variance," Finance Research Letters, Elsevier, vol. 55(PA).

  17. Ardia, David & Boudt, Kris & Carl, Peter & Mullen, Katharine M. & Peterson, Brian, 2010. "Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization," MPRA Paper 22135, University Library of Munich, Germany.

    Cited by:

    1. Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2009. "DEoptim: An R Package for Global Optimization by Differential Evolution," MPRA Paper 21743, University Library of Munich, Germany, revised 26 Dec 2010.
    2. Ankit Dangi, 2013. "Financial Portfolio Optimization: Computationally guided agents to investigate, analyse and invest!?," Papers 1301.4194, arXiv.org.
    3. Ryś Przemysław & Ślepaczuk Robert, 2018. "Machine Learning Methods in Algorithmic Trading Strategy Optimization – Design and Time Efficiency," Central European Economic Journal, Sciendo, vol. 5(52), pages 206-229, January.
    4. Bilel JARRAYA, 2013. "Asset Allocation And Portfolio Optimization Problems With Metaheuristics: A Literature Survey," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 3(4), pages 38-56, December.
    5. Przemysław Ryś & Robert Ślepaczuk, 2018. "Machine learning in algorithmic trading strategy optimization - implementation and efficiency," Working Papers 2018-25, Faculty of Economic Sciences, University of Warsaw.
    6. Ardia, David & Ospina, Juan & Giraldo, Giraldo, 2010. "Jump-Diffusion Calibration using Differential Evolution," MPRA Paper 26184, University Library of Munich, Germany, revised 25 Oct 2010.

Articles

  1. Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
    See citations under working paper version above.
  2. Ardia, David & Bluteau, Keven & Boudt, Kris, 2022. "Media abnormal tone, earnings announcements, and the stock market," Journal of Financial Markets, Elsevier, vol. 61(C).
    See citations under working paper version above.
  3. K. Boudt & K. Dragun & S. Vanduffel, 2022. "The optimal payoff for a Yaari investor," Quantitative Finance, Taylor & Francis Journals, vol. 22(10), pages 1839-1852, October.

    Cited by:

    1. Lauzier, Jean-Gabriel & Lin, Liyuan & Wang, Ruodu, 2023. "Pairwise counter-monotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 279-287.

  4. Kris Boudt & Valentin Todorov & Wenjing Wang, 2020. "Robust Distribution-Based Winsorization in Composite Indicators Construction," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(2), pages 375-397, June.

    Cited by:

    1. Khan, Muhammad Tariq Iqbal & Anwar, Sofia, 2022. "Natural disasters and foreign exchange reserves: The role of renewable energy and human capital," Renewable Energy, Elsevier, vol. 192(C), pages 838-848.
    2. Halkos, George & Moll de Alba, Jaime & Todorov, Valentin, 2021. "Analyzing manufacturing sector and selected development challenges: A panel data analysis," Energy, Elsevier, vol. 235(C).
    3. Kehinde Oni & Mukaila Ayanda Aremu & Taiwo Ogunniran, 2022. "Impact of Corporate Social Responsibility on Microfinance Banks' Performance in Ogbomoso, Oyo State, Nigeria," Technium Social Sciences Journal, Technium Science, vol. 31(1), pages 553-574, May.

  5. Boudt, Kris & Cornilly, Dries & Verdonck, Tim, 2020. "Nearest comoment estimation with unobserved factors," Journal of Econometrics, Elsevier, vol. 217(2), pages 381-397.
    See citations under working paper version above.
  6. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.

    Cited by:

    1. Ardia, David & Bluteau, Keven & Boudt, Kris, 2022. "Media abnormal tone, earnings announcements, and the stock market," Journal of Financial Markets, Elsevier, vol. 61(C).
    2. de Medeiros, Rennan Kertlly & da Silva Bejarano Aragón, Edilean Kleber & Besarria, Cássio da Nóbrega, 2023. "Effects of oil market sentiment on macroeconomic variables," Resources Policy, Elsevier, vol. 83(C).
    3. Peter A.G. van Bergeijk, 2021. "Pandemic Economics," Books, Edward Elgar Publishing, number 20401.
    4. Robert Lehmann, 2020. "The Forecasting Power of the ifo Business Survey," CESifo Working Paper Series 8291, CESifo.
    5. VAN DER WIELEN Wouter & BARRIOS Salvador, 2020. "Fear and Employment During the COVID Pandemic: Evidence from Search Behaviour in the EU," JRC Working Papers on Taxation & Structural Reforms 2020-08, Joint Research Centre.
    6. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
    7. Karol Szafranek & Michał Rubaszek & Gazi Salah Uddin, 2023. "The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets," KAE Working Papers 2023-095, Warsaw School of Economics, Collegium of Economic Analysis.
    8. Mikhail Stolbov & Maria Shchepeleva, 2023. "Sentiment-based indicators of real estate market stress and systemic risk: international evidence," Annals of Finance, Springer, vol. 19(3), pages 355-382, September.
    9. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    10. Mazzotta, Stefano, 2022. "Immigration narrative sentiment from TV news and the stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    11. Aakriti Mathur & Rajeswari Sengupta & Bhanu Pratap, 2022. "Saved by the bell? Equity market responses to surprise Covid-19 lockdowns and central bank interventions," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2022-001, Indira Gandhi Institute of Development Research, Mumbai, India.
    12. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    13. Ballandonne, Matthieu & Cersosimo, Igor, 2022. "Towards a “Text as Data” Approach in the History of Economics: An Application to Adam Smith’s Classics," OSF Preprints mg3zb, Center for Open Science.
    14. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    15. Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
    16. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    17. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
    18. Aktham Maghyereh & Hussein Abdoh, 2022. "Can news-based economic sentiment predict bubbles in precious metal markets?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    19. Antón Sarabia Arturo & Bazdresch Santiago & Lelo-de-Larrea Alejandra, 2023. "The Influence of Central Bank's Projections and Economic Narrative on Professional Forecasters' Expectations: Evidence from Mexico," Working Papers 2023-21, Banco de México.
    20. khan Feroz, Noushad & Hassan, Gazi & Cameron, Michael P., 2022. "To what extent do network effects moderate the relationship between social media propagated news and investors’ perceptions?," Research in Economics, Elsevier, vol. 76(3), pages 170-188.
    21. Gerardin Mathilde, & Ranvier Martial., 2021. "Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments," Working papers 821, Banque de France.
    22. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    23. Danilo Vassallo & Giacomo Bormetti & Fabrizio Lillo, 2019. "A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics," Papers 1910.01407, arXiv.org, revised Sep 2020.
    24. Kishor, N. Kundan & Pratap, Bhanu, 2023. "The Role of Inflation Targeting in Anchoring Long-Run Inflation Expectations: Evidence from India," MPRA Paper 118951, University Library of Munich, Germany.
    25. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    26. Gianni La Cava, 2021. "Smells Like Animal Spirits: The Effect of Corporate Sentiment on Investment," RBA Research Discussion Papers rdp2021-11, Reserve Bank of Australia.
    27. Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
    28. Yu, Zhen & Liu, Wei & Yang, Fuyu, 2023. "A central bankers’ sentiment index of global financial cycle," Finance Research Letters, Elsevier, vol. 57(C).
    29. Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
    30. Łukasz Baszczak, 2023. "Ekonomia narracji – początki nowego nurtu," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1, pages 66-81.
    31. Christoph Kronenberg, 2021. "A New Measure of 19th Century US Suicides," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 803-815, September.
    32. Fabozzi, Francesco A. & Nazemi, Abdolreza, 2023. "News-based sentiment and the value premium," Journal of International Money and Finance, Elsevier, vol. 136(C).
    33. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).

  7. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.

    Cited by:

    1. Qian Wang & Duowen Wu & Lina Yan, 2021. "Effect of positive tone in MD&A disclosure on capital structure adjustment speed: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5809-5845, December.
    2. Harrison, Joseph S. & Josefy, Matthew A. & Kalm, Matias & Krause, Ryan, 2022. "Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context," Other publications TiSEM abc9f83d-960e-40c5-ae40-3, Tilburg University, School of Economics and Management.
    3. Shuangyan Li & Guangrui Wang & Yongli Luo, 2022. "Tone of language, financial disclosure, and earnings management: a textual analysis of form 20-F," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    4. Liu, Pu & Nguyen, Hazel T., 2020. "CEO characteristics and tone at the top inconsistency," Journal of Economics and Business, Elsevier, vol. 108(C).
    5. Fiset, John & Oldford, Erin & Chu, Shaner, 2021. "Market signaling capacity of written and visual charismatic leadership tactics," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    6. Enrique Bonson & David Perea & Graca Azevedo, 2021. "Tone and content analysis in the president’s letters to shareholders: Spanish evidence," Upravlenets, Ural State University of Economics, vol. 12(1), pages 78-90, March.
    7. Elena Fedorova & Nadezhda Lapshina & Mikhail Lazarev & Alexandr Bobrodin, 2021. "Impact of Information in Press Releases on the Financial Performance of Russian Companies [Влияние Информации В Пресс-Релизах На Финансовые Показатели Российских Компаний]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, pages 138-157, June.
    8. Michele Gendelsky de Oliveira & Graça Azevedo & Jonas Oliveira, 2021. "The Relationship between the Company’s Value and the Tone of the Risk-Related Narratives: The Case of Portugal," Economies, MDPI, vol. 9(2), pages 1-28, May.
    9. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    10. Javid Iqbal & Muhammad Khalid Sohail & Aymen Irshad & Rao Aamir Khan, 2024. "Risk management disclosures and banks financial performance: evidence from emerging markets," Risk Management, Palgrave Macmillan, vol. 26(1), pages 1-21, February.
    11. Isabel-María García-Sánchez & Víctor Amor-Esteban & Alejandra García-Sánchez, 2021. "Different Leaders in a COVID-19 Scenario: CEO Altruism and Generous Discourse," Sustainability, MDPI, vol. 13(7), pages 1-19, March.
    12. Arslan-Ayaydin, Özgür & Bishara, Norman & Thewissen, James & Torsin, Wouter, 2020. "Managerial career concerns and the content of corporate disclosures: An analysis of the tone of earnings press releases," International Review of Financial Analysis, Elsevier, vol. 72(C).
    13. Liu, Yifan & Popova, Ivilina, 2023. "Threats to central bank independence and exchange rate volatility: High-frequency identification with Trump’s Fed tweets," Finance Research Letters, Elsevier, vol. 53(C).
    14. Javid Iqbal & Khalid Riaz, 2022. "Predicting future financial performance of banks from management’s tone in the textual disclosures," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2691-2721, August.
    15. Iqbal, Javid & Saeed, Abubakr, 2023. "Managerial sentiments, non-performing loans, and banks financial performance: A causal mediation approach," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    16. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
    17. Joseph S. Harrison & Matthew A. Josefy & Matias Kalm & Ryan Krause, 2023. "Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context," Strategic Management Journal, Wiley Blackwell, vol. 44(7), pages 1780-1802, July.
    18. Özgür Arslan‐Ayaydin & James Thewissen & Wouter Torsin, 2021. "Disclosure tone management and labor unions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 102-147, January.

  8. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.

    Cited by:

    1. Nyman, Rickard & Kapadia, Sujit & Tuckett, David & Gregory, David & Ormerod, Paul & Smith, Robert, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
    2. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    3. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
    4. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
    5. Ksenia Yakovleva, 2018. "Text Mining-based Economic Activity Estimation," Russian Journal of Money and Finance, Bank of Russia, vol. 77(4), pages 26-41, December.
    6. Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
    7. Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022. "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, vol. 4(1), pages 17-61, March.
    8. Diana Gabrielyan & Lenno Uusküla, 2022. "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 142, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    9. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
    10. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    11. Paul Hubert & Fabien Labondance, 2020. "Central Bank Tone and the Dispersion of Views within Monetary Policy Committees," Sciences Po publications 02/2020, Sciences Po.
    12. Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023. "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 415-438, June.
    13. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
    14. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    15. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    16. Erik Andres-Escayola & Corinna Ghirelli & Luis Molina & Javier J. Pérez & Elena Vidal, 2022. "Using newspapers for textual indicators: which and how many?," Working Papers 2235, Banco de España.
    17. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
    18. Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
    19. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    20. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    21. Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
    22. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    23. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
    24. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
    25. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
    26. Gerardin Mathilde, & Ranvier Martial., 2021. "Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments," Working papers 821, Banque de France.
    27. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    28. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    29. Zhang, Yulian & Hamori, Shigeyuki, 2021. "Do news sentiment and the economic uncertainty caused by public health events impact macroeconomic indicators? Evidence from a TVP-VAR decomposition approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 145-162.
    30. Bai, Xiwen & Lam, Jasmine Siu Lee & Jakher, Astha, 2021. "Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    31. Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
    32. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).
    33. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    34. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.

  9. Boudt, Kris & Raza, Muhammad Wajid & Wauters, Marjan, 2019. "Evaluating the Shariah-compliance of equity portfolios: The weighting method matters," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 406-417.

    Cited by:

    1. Pirgaip, Burak & Arslan-Ayaydin, Özgür & Karan, Mehmet Baha, 2021. "Do Sukuk provide diversification benefits to conventional bond investors? Evidence from Turkey," Global Finance Journal, Elsevier, vol. 50(C).
    2. Cheong, Calvin W.H., 2021. "Risk, resilience, and Shariah-compliance," Research in International Business and Finance, Elsevier, vol. 55(C).
    3. Khan, Abdullah & Rizvi, Syed Aun R. & Ali, Mohsin & Haroon, Omair, 2021. "A survey of Islamic finance research – Influences and influencers," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    4. Rasha Tawfiq Abadi & Florinda Silva, 2022. "Do Islamic fundamental weighted indices outperform their conventional counterparts? An empirical investigation during the crises in the MENA region," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(2), pages 241-266, June.

  10. Boudt, Kris & Neely, Christopher J. & Sercu, Piet & Wauters, Marjan, 2019. "The response of multinationals’ foreign exchange rate exposure to macroeconomic news," Journal of International Money and Finance, Elsevier, vol. 94(C), pages 32-47.
    See citations under working paper version above.
  11. Boudt, Kris & Raza, Muhammad Wajid & Ashraf, Dawood, 2019. "Macro-financial regimes and performance of Shariah-compliant equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 60(C), pages 252-266.

    Cited by:

    1. Khan, Abdullah & Rizvi, Syed Aun R. & Ali, Mohsin & Haroon, Omair, 2021. "A survey of Islamic finance research – Influences and influencers," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    2. Hasan, Md. Bokhtiar & Rashid, Md. Mamunur & Shafiullah, Muhammad & Sarker, Tapan, 2022. "How resilient are Islamic financial markets during the COVID-19 pandemic?," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    3. María de la O González & Francisco Jareño & Camalea El Haddouti, 2019. "Sector Portfolio Performance Comparison between Islamic and Conventional Stock Markets," Sustainability, MDPI, vol. 11(17), pages 1-23, August.
    4. Kok, Seng Kiong & Giorgioni, Gianluigi & Farquhar, Stuart, 2022. "The trade-off between knowledge accumulation and independence: The case of the Shariah supervisory board within the Shariah governance and firm performance nexus," Research in International Business and Finance, Elsevier, vol. 59(C).
    5. Wang, Lu, 2021. "Time-varying conditional beta, return spillovers, and dynamic bank diversification strategies," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 272-280.
    6. Boudt, Kris & Khokhar, Mulazim-Ali, 2021. "Performance-sharing optimization by risk-constrained equity investors," Finance Research Letters, Elsevier, vol. 38(C).

  12. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.

    Cited by:

    1. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    2. R. Rajesh, 2023. "Grey Markov Models for Predicting the Social Sustainability Performances of Firms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 297-351, August.
    3. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
    5. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    6. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    7. Urom, Christian & Onwuka, Kevin O. & Uma, Kalu E. & Yuni, Denis N., 2020. "Regime dependent effects and cyclical volatility spillover between crude oil price movements and stock returns," International Economics, Elsevier, vol. 161(C), pages 10-29.
    8. Abdulkadir Kaya & İkram Yusuf Yarbaşı, 2021. "Forecasting of Volatility in Stock Exchange Markets by MS-GARCH Approach: An Application of Borsa Istanbul," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 6(1), pages 16-35.
    9. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    10. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    11. Ibrahim, Omar, 2019. "Modelling Risk on the Egyptian Stock Market: Evidence from a Markov-Regime Switching GARCH Process," MPRA Paper 98091, University Library of Munich, Germany.
    12. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2019. "Non-Linearities, Cyber Attacks and Cryptocurrencies," CESifo Working Paper Series 7692, CESifo.
    13. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    14. Lu-Tao Zhao & Li-Na Liu & Zi-Jie Wang & Ling-Yun He, 2019. "Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
    15. John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
    16. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    17. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.
    18. Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
    19. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2019. "A Test of Using Markov-Switching GARCH Models in Oil and Natural Gas Trading," Energies, MDPI, vol. 13(1), pages 1-24, December.
    20. Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
    21. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    22. Abdessamad Ouchen, 2022. "Is the ESG portfolio less turbulent than a market benchmark portfolio?," Risk Management, Palgrave Macmillan, vol. 24(1), pages 1-33, March.
    23. Olofsson, Petter & Råholm, Anna & Uddin, Gazi Salah & Troster, Victor & Kang, Sang Hoon, 2021. "Ethical and unethical investments under extreme market conditions," International Review of Financial Analysis, Elsevier, vol. 78(C).
    24. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Do Islamic stocks outperform conventional stock sectors during normal and crisis periods? Extreme co-movements and portfolio management analysis," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    25. Achraf Ghorbel & Ahmed Jeribi, 2021. "Volatility spillovers and contagion between energy sector and financial assets during COVID-19 crisis period," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 449-467, September.
    26. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    27. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.
    28. Yu, Xing & Li, Yanyan & Lu, Junli & Shen, Xilin, 2023. "Futures hedging in crude oil markets: A trade-off between risk and return," Resources Policy, Elsevier, vol. 80(C).
    29. Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf & Al-Freedi, Ajab, 2020. "Forecasting volatility in the petroleum futures markets: A re-examination and extension," Energy Economics, Elsevier, vol. 86(C).
    30. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    31. Arian, Hamid & Moghimi, Mehrdad & Tabatabaei, Ehsan & Zamani, Shiva, 2022. "Encoded Value-at-Risk: A machine learning approach for portfolio risk measurement," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 500-525.
    32. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    33. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    34. Guo, Xiaozhu & Huang, Yisu & Liang, Chao & Umar, Muhammad, 2022. "Forecasting volatility of EUA futures: New evidence," Energy Economics, Elsevier, vol. 110(C).
    35. Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    36. Leopoldo Catania & Mads Sandholdt, 2019. "Bitcoin at High Frequency," JRFM, MDPI, vol. 12(1), pages 1-20, February.
    37. Abdollahi, Hooman, 2020. "A novel hybrid model for forecasting crude oil price based on time series decomposition," Applied Energy, Elsevier, vol. 267(C).
    38. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.
    39. Chon, Sora & Kim, Jaeho, 2021. "Does the Financial Leverage Effect Depend on Volatility Regimes?," Finance Research Letters, Elsevier, vol. 39(C).

  13. Kris Boudt & Edgars Jakobsons & Steven Vanduffel, 2018. "Block rearranging elements within matrix columns to minimize the variability of the row sums," 4OR, Springer, vol. 16(1), pages 31-50, March.

    Cited by:

    1. Nabil Bouamara & Kris Boudt & Sebastien Laurent & Christopher J. Neely, 2024. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Working Papers 2024-006, Federal Reserve Bank of St. Louis.
    2. Carole Bernard & Oleg Bondarenko & Steven Vanduffel, 2021. "A model-free approach to multivariate option pricing," Review of Derivatives Research, Springer, vol. 24(2), pages 135-155, July.
    3. Bernard, Carole & Kazzi, Rodrigue & Vanduffel, Steven, 2020. "Range Value-at-Risk bounds for unimodal distributions under partial information," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 9-24.
    4. Jose Blanchet & Henry Lam & Yang Liu & Ruodu Wang, 2020. "Convolution Bounds on Quantile Aggregation," Papers 2007.09320, arXiv.org, revised May 2023.

  14. David Ardia & Kris Boudt & Giang Nguyen, 2018. "Beyond risk-based portfolios: balancing performance and risk contributions in asset allocation," Quantitative Finance, Taylor & Francis Journals, vol. 18(8), pages 1249-1259, August.
    See citations under working paper version above.
  15. Ardia, David & Boudt, Kris, 2018. "The peer performance ratios of hedge funds," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 351-368.

    Cited by:

    1. Candelon, Bertrand & Fuerst, Franz & Hasse, Jean-Baptiste, 2021. "Diversification Potential in Real Estate Portfolios," LIDAM Discussion Papers LFIN 2021001, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Silvio John Camilleri & Ritienne Farrugia, 2018. "The Risk-Adjusted Performance of Alternative Investment Funds and UCITS: A Comparative Analysis," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(7), pages 1-23, July.
    3. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
    4. Giulio Bottazzi & Francesco Cordoni & Giulia Livieri & Stefano Marmi, 2020. "Uncertainty in Firm Valuation and a Cross-Sectional Misvaluation Measure," LEM Papers Series 2020/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Monica Billio & Bertrand Maillet & Loriana Pelizzon, 2022. "A meta-measure of performance related to both investors and investments characteristics," Annals of Operations Research, Springer, vol. 313(2), pages 1405-1447, June.
    6. Ardia, David & Bluteau, Keven & Tran, Thien Duy, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Finance Research Letters, Elsevier, vol. 48(C).
    7. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    8. Elias Cavalcante Junior & Fernando Moraes & Rodrigo De Losso, 2020. "Unskilled Fund Managers: Replicating Active Fund Performance With Few ETFs," Working Papers, Department of Economics 2020_14, University of São Paulo (FEA-USP), revised 15 Sep 2020.
    9. Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.
    10. Quaye, Enoch & Tunaru, Radu, 2022. "The stock implied volatility and the implied dividend volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    11. Giulio Bottazzi & Francesco Cordoni & Giulia Livieri & Stefano Marmi, 2020. "Stock Recommendations from Stochastic Discounted Cash Flows," LEM Papers Series 2020/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    12. Ardia, David & Bluteau, Keven & Lortie-Cloutier, Gabriel & Duy Tran, Thien, 2023. "Factor exposure heterogeneity in green and brown stocks," Finance Research Letters, Elsevier, vol. 55(PA).

  16. Boudt, Kris & Thewissen, James & Torsin, Wouter, 2018. "When does the tone of earnings press releases matter?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 231-245.
    See citations under working paper version above.
  17. Boudt, Kris & Laurent, Sébastien & Lunde, Asger & Quaedvlieg, Rogier & Sauri, Orimar, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Journal of Econometrics, Elsevier, vol. 196(2), pages 347-367.

    Cited by:

    1. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    3. Sébastien Laurent & Shuping Shi, 2018. "Volatility Estimation and Jump Detection for drift-diffusion Processes," AMSE Working Papers 1843, Aix-Marseille School of Economics, France.
    4. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    6. Nabil Bouamara & Kris Boudt & Sebastien Laurent & Christopher J. Neely, 2024. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Working Papers 2024-006, Federal Reserve Bank of St. Louis.
    7. Christian Francq & Jean-Michel Zakoian, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," Papers 1909.04661, arXiv.org.
    8. Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
    9. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    10. Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
    11. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    12. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.

  18. Boudt, Kris & Paulus, Ellen C.S. & Rosenthal, Dale W.R., 2017. "Funding liquidity, market liquidity and TED spread: A two-regime model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 143-158.
    See citations under working paper version above.
  19. David Ardia & Guido Bolliger & Kris Boudt & Jean-Philippe Gagnon-Fleury, 2017. "The impact of covariance misspecification in risk-based portfolios," Annals of Operations Research, Springer, vol. 254(1), pages 1-16, July.

    Cited by:

    1. Olessia Caillé & Daria Onori, 2018. "Conditional Risk-Based Portfolio," Working Papers hal-01973115, HAL.
    2. Muhinyuza, Stanislas & Bodnar, Taras & Lindholm, Mathias, 2020. "A test on the location of the tangency portfolio on the set of feasible portfolios," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    3. Nathan Lassance & Frédéric Vrins, 2019. "Minimum Rényi entropy portfolios," LIDAM Reprints CORE 3062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Kei Nakagawa & Shuhei Noma & Masaya Abe, 2020. "RM-CVaR: Regularized Multiple $\beta$-CVaR Portfolio," Papers 2004.13347, arXiv.org, revised May 2020.
    5. Zhang, Xi & Li, Jian, 2018. "Credit and market risks measurement in carbon financing for Chinese banks," Energy Economics, Elsevier, vol. 76(C), pages 549-557.
    6. Prayut Jain & Shashi Jain, 2019. "Can Machine Learning-Based Portfolios Outperform Traditional Risk-Based Portfolios? The Need to Account for Covariance Misspecification," Risks, MDPI, vol. 7(3), pages 1-27, July.
    7. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    8. Li, Xiaoyue & Uysal, A. Sinem & Mulvey, John M., 2022. "Multi-period portfolio optimization using model predictive control with mean-variance and risk parity frameworks," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1158-1176.
    9. Ardia, David & Boudt, Kris & Hartmann, Stefan & Nguyen, Giang, 2022. "Properties of the Margrabe Best-of-two strategy to tactical asset allocation," International Review of Financial Analysis, Elsevier, vol. 81(C).
    10. Giorgio Costa & Roy Kwon, 2020. "A robust framework for risk parity portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 447-466, September.
    11. Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    12. Ayse Sinem Uysal & Xiaoyue Li & John M. Mulvey, 2021. "End-to-End Risk Budgeting Portfolio Optimization with Neural Networks," Papers 2107.04636, arXiv.org.
    13. Peter Nystrup & Stephen Boyd & Erik Lindström & Henrik Madsen, 2019. "Multi-period portfolio selection with drawdown control," Annals of Operations Research, Springer, vol. 282(1), pages 245-271, November.
    14. Kei Nakagawa & Mitsuyoshi Imamura & Kenichi Yoshida, 2018. "Risk-Based Portfolios with Large Dynamic Covariance Matrices," IJFS, MDPI, vol. 6(2), pages 1-14, May.
    15. Marco Neffelli, 2018. "Target Matrix Estimators in Risk-Based Portfolios," Risks, MDPI, vol. 6(4), pages 1-20, November.
    16. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    17. Debjani Palit & Victor R. Prybutok, 2024. "A Study of Hierarchical Risk Parity in Portfolio Construction," Journal of Economic Analysis, Anser Press, vol. 3(3), pages 106-125, September.

  20. Algaba, Andres & Boudt, Kris, 2017. "Generalized financial ratios to predict the equity premium," Economic Modelling, Elsevier, vol. 66(C), pages 244-257.

    Cited by:

    1. Jonathan A. Batten & Harald Kinateder & Niklas Wagner, 2022. "Beating the Average: Equity Premium Variations, Uncertainty, and Liquidity," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 567-588, September.
    2. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.

  21. Kris Boudt & Fang Liu & Piet Sercu, 2016. "Exporters’ Exposures to Currencies: Beyond the Loglinear Model," Review of Finance, European Finance Association, vol. 20(4), pages 1631-1657.

    Cited by:

    1. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.

  22. Ardia, David & Boudt, Kris & Wauters, Marjan, 2016. "The economic benefits of market timing the style allocation of characteristic-based portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 38-62.

    Cited by:

    1. Boudt, Kris & Raza, Muhammad Wajid & Wauters, Marjan, 2019. "Evaluating the Shariah-compliance of equity portfolios: The weighting method matters," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 406-417.
    2. Naqvi, Bushra & Mirza, Nawazish & Rizvi, Syed Kumail Abbas & Porada-Rochoń, Małgorzata & Itani, Rania, 2021. "Is there a green fund premium? Evidence from twenty seven emerging markets," Global Finance Journal, Elsevier, vol. 50(C).
    3. Algaba, Andres & Boudt, Kris, 2017. "Generalized financial ratios to predict the equity premium," Economic Modelling, Elsevier, vol. 66(C), pages 244-257.
    4. Rahat, Birjees & Nguyen, Pascal, 2022. "Risk-adjusted investment performance of green and black portfolios and impact of toxic divestments in emerging markets," Energy Economics, Elsevier, vol. 116(C).

  23. Arslan-Ayaydin, Özgür & Boudt, Kris & Thewissen, James, 2016. "Managers set the tone: Equity incentives and the tone of earnings press releases," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 132-147.

    Cited by:

    1. Xi Wu & Xinle Tong & Yudong Wang, 2022. "Managerial ability and idiosyncratic volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2566-2581, April.
    2. Ardia, David & Bluteau, Keven & Boudt, Kris, 2022. "Media abnormal tone, earnings announcements, and the stock market," Journal of Financial Markets, Elsevier, vol. 61(C).
    3. Baochen Yang & Yifang Liu & Yunpeng Su, 2023. "Earnings communication conferences and post‐earnings‐announcement drift: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(2), pages 2145-2185, June.
    4. Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
    5. Jiao Ji & Oleksandr Talavera & Shuxing Yin, 2018. "The Hidden Information Content: Evidence from the Tone of Independent Director Reports," Working Papers 2018-28, Swansea University, School of Management.
    6. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.
    7. Azam Pouryousof & Farzaneh Nassirzadeh & Reza Hesarzadeh & Davood Askarany, 2022. "The Relationship between Managers’ Disclosure Tone and the Trading Volume of Investors," JRFM, MDPI, vol. 15(12), pages 1-16, December.
    8. Zhao, Wanlong & Zhang, Wei & Xiong, Xiong & Zou, Gaofeng, 2021. "How insiders utilize their information advantages in their trading: Evidence from China," Finance Research Letters, Elsevier, vol. 42(C).
    9. Qian Wang & Duowen Wu & Lina Yan, 2021. "Effect of positive tone in MD&A disclosure on capital structure adjustment speed: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5809-5845, December.
    10. Xi Fu & Xiaoxi Wu & Zhifang Zhang, 2021. "The Information Role of Earnings Conference Call Tone: Evidence from Stock Price Crash Risk," Journal of Business Ethics, Springer, vol. 173(3), pages 643-660, October.
    11. Diana Gabrielyan & Lenno Uusküla, 2022. "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 142, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    12. Bannier, Christina E. & Pauls, Thomas & Walter, Andreas, 2017. "CEO-speeches and stock returns," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168192, Verein für Socialpolitik / German Economic Association.
    13. Miwa, Kotaro, 2023. "Divergent opinions on social media," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 182-196.
    14. Boudt, Kris & Thewissen, James & Torsin, Wouter, 2018. "When does the tone of earnings press releases matter?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 231-245.
    15. Gilberto Marquez-Illescas & Allan A. Zebedee & Linying Zhou, 2019. "Hear Me Write: Does CEO Narcissism Affect Disclosure?," Journal of Business Ethics, Springer, vol. 159(2), pages 401-417, October.
    16. Liu, Pu & Nguyen, Hazel T., 2020. "CEO characteristics and tone at the top inconsistency," Journal of Economics and Business, Elsevier, vol. 108(C).
    17. Ankit Jain & Hariom Manchiraju & Shyam V. Sunder, 2023. "Institutional ownership and the informativeness of disclosure tone," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 50(1-2), pages 61-90, January.
    18. Rahman, Dewan & Oliver, Barry & Faff, Robert, 2020. "Evidence of strategic information uncertainty around opportunistic insider purchases," Journal of Banking & Finance, Elsevier, vol. 117(C).
    19. Bassyouny, Hesham & Abdelfattah, Tarek & Tao, Lei, 2020. "Beyond narrative disclosure tone: The upper echelons theory perspective," International Review of Financial Analysis, Elsevier, vol. 70(C).
    20. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
    21. Sarel, Roee & Demirtas, Melanie, 2021. "Delegation in a multi-tier court system: Are remands in the U.S. federal courts driven by moral hazard?," European Journal of Political Economy, Elsevier, vol. 68(C).
    22. Kim, Jongkyum & Lim, Jee-Hae & Yoon, Kyunghee, 2022. "How do the content, format, and tone of Twitter-based corporate disclosure vary depending on earnings performance?," International Journal of Accounting Information Systems, Elsevier, vol. 47(C).
    23. Miwa, Kotaro, 2022. "The informational role of analysts’ textual statements," Research in International Business and Finance, Elsevier, vol. 59(C).
    24. Elena Fedorova & Nadezhda Lapshina & Mikhail Lazarev & Alexandr Bobrodin, 2021. "Impact of Information in Press Releases on the Financial Performance of Russian Companies [Влияние Информации В Пресс-Релизах На Финансовые Показатели Российских Компаний]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, pages 138-157, June.
    25. Boulland, Romain & Dessaint, Olivier, 2017. "Announcing the announcement," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 59-79.
    26. Rong Gong, 2023. "CEO overconfidence and the tone of press release," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(2), pages 2081-2108, June.
    27. D. G. DeBoskey & Yan Luo & Linying Zhou, 2019. "CEO power, board oversight, and earnings announcement tone," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 657-680, February.
    28. Xiao Wu, Dong & Yao, Xiao & Luan Guo, Jian, 2021. "Is Textual Tone Informative or Inflated for Firm’s Future Value? Evidence from Chinese Listed Firms," Economic Modelling, Elsevier, vol. 94(C), pages 513-525.
    29. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    30. Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.
    31. Florian Kiesel, 2021. "It's the tone, stupid! Soft information in credit rating reports and financial markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(3), pages 553-585, September.
    32. Eddy Cardinaels & Stephan Hollander & Brian J. White, 2019. "Automatic summarization of earnings releases: attributes and effects on investors’ judgments," Review of Accounting Studies, Springer, vol. 24(3), pages 860-890, September.
    33. Cardinaels, Eddy & Hollander, Stephan & White, Brian, 2019. "Automatic summarization of earnings releases : Attributes and effects on investors’ judgments," Other publications TiSEM 721f64f4-033e-453b-a3e7-2, Tilburg University, School of Economics and Management.
    34. Miwa, Kotaro, 2021. "Language barriers in analyst reports," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 223-236.
    35. Kothari, Pratik & Chance, Don M. & Ferris, Stephen P., 2021. "Bragging rights: Does corporate boasting imply value creation?," Journal of Corporate Finance, Elsevier, vol. 67(C).
    36. Arslan-Ayaydin, Özgür & Bishara, Norman & Thewissen, James & Torsin, Wouter, 2020. "Managerial career concerns and the content of corporate disclosures: An analysis of the tone of earnings press releases," International Review of Financial Analysis, Elsevier, vol. 72(C).
    37. Shuyu Zhang & Walter Aerts & Dunli Zhang & Zishan Chen, 2022. "Positive tone and initial coin offering," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(2), pages 2237-2266, June.
    38. Jin, Xianzhe & Li, Jingnan & Gao, Jijun, 2022. "Joint effect of linguistic style and ethnicity on entrepreneurial fundraising: Evidence from equity crowdfunding," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    39. Özgür Arslan‐Ayaydin & James Thewissen & Wouter Torsin, 2021. "Disclosure tone management and labor unions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 102-147, January.

  24. David Ardia & Kris Boudt & Marjan Wauters, 2016. "Smart beta and CPPI performance," Finance, Presses universitaires de Grenoble, vol. 37(3), pages 31-65.

    Cited by:

    1. Ardia, David & Boudt, Kris & Hartmann, Stefan & Nguyen, Giang, 2022. "Properties of the Margrabe Best-of-two strategy to tactical asset allocation," International Review of Financial Analysis, Elsevier, vol. 81(C).
    2. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.

  25. Boudt, Kris & Lu, Wanbo & Peeters, Benedict, 2015. "Higher order comoments of multifactor models and asset allocation," Finance Research Letters, Elsevier, vol. 13(C), pages 225-233.

    Cited by:

    1. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    2. Rui Zhou & Daniel P. Palomar, 2020. "Solving High-Order Portfolios via Successive Convex Approximation Algorithms," Papers 2008.00863, arXiv.org.
    3. M. Barkhagen & S. García & J. Gondzio & J. Kalcsics & J. Kroeske & S. Sabanis & A. Staal, 2023. "Optimising portfolio diversification and dimensionality," Journal of Global Optimization, Springer, vol. 85(1), pages 185-234, January.
    4. Jinxin Wang & Zengde Deng & Taoli Zheng & Anthony Man-Cho So, 2020. "Sparse High-Order Portfolios via Proximal DCA and SCA," Papers 2008.12953, arXiv.org, revised Jun 2021.
    5. Yue, Wei & Wang, Yuping, 2017. "A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 124-140.
    6. Mihovil Anðelinoviæ & Filip Škunca, 2023. "Optimizing insurers investment portfolios: incorporating alternative investments," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 41(2), pages 361-389.
    7. M. D. Braga & C. R. Nava & M. G. Zoia, 2023. "Kurtosis-based risk parity: methodology and portfolio effects," Quantitative Finance, Taylor & Francis Journals, vol. 23(3), pages 453-469, March.
    8. Kris Boudt & Dries Cornilly & Tim Verdonck, 2019. "Nearest Comoment Estimation With Unobserved Factors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/970, Ghent University, Faculty of Economics and Business Administration.
    9. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    10. Lassance, Nathan & Vrins, Frédéric, 2020. "Robust portfolio selection using sparse estimation of comoment tensors," LIDAM Discussion Papers LFIN 2020003, Université catholique de Louvain, Louvain Finance (LFIN).
    11. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," LIDAM Reprints LFIN 2021005, Université catholique de Louvain, Louvain Finance (LFIN).

  26. Kris Boudt & Peter Goeij & James Thewissen & Geert Van Campenhout & Anne Wyatt, 2015. "Analysts' forecast error: a robust prediction model and its short-term trading profitability," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 55(3), pages 683-715, September.
    See citations under working paper version above.
  27. Ardia, David & Boudt, Kris, 2015. "Testing equality of modified Sharpe ratios," Finance Research Letters, Elsevier, vol. 13(C), pages 97-104.

    Cited by:

    1. Candelon, Bertrand & Fuerst, Franz & Hasse, Jean-Baptiste, 2021. "Diversification Potential in Real Estate Portfolios," LIDAM Discussion Papers LFIN 2021001, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
    3. Gireesh Shrimali, 2021. "Financial Performance of Renewable and Fossil Power Sources in India," Sustainability, MDPI, vol. 13(5), pages 1-23, February.
    4. DeMiguel, Victor & Lassance, Nathan & Vrins, Frédéric, 2021. "Optimal Portfolio Diversification via Independent Component Analysis," LIDAM Discussion Papers LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
    5. Ardia, David & Boudt, Kris, 2018. "The peer performance ratios of hedge funds," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 351-368.
    6. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    7. Nabil Bouamara & Kris Boudt & Sebastien Laurent & Christopher J. Neely, 2024. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Working Papers 2024-006, Federal Reserve Bank of St. Louis.
    8. Owen Davis & Siavash Radpour, 2022. "Older Workers’ Wages Are Growing—But Not Fast Enough," SCEPA publication series. 2022-02, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    9. Adlane Haffar & Éric Le Fur, 2022. "Dependence structure of CAT bonds and portfolio diversification: a copula-GARCH approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 297-309, July.
    10. Andreas Lichtenberger & Joao Paulo Braga & Willi Semmler, 2022. "Green Bonds for the Transition to a Low-Carbon Economy," SCEPA working paper series. 2022-02, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    11. Jean-Baptiste Hasse & Christelle Lecourt & Souhila Siagh, 2023. "Institutional Stock-Bond Portfolios Rebalancing and Financial Stability," AMSE Working Papers 2322, Aix-Marseille School of Economics, France.
    12. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," LIDAM Reprints LFIN 2021005, Université catholique de Louvain, Louvain Finance (LFIN).
    13. Andreas Lichtenberger & Joao Paulo Braga & Willi Semmler, 2022. "Green Bonds for the Transition to a Low-Carbon Economy," Econometrics, MDPI, vol. 10(1), pages 1-31, March.
    14. La Monaca, Sarah & Assereto, Martina & Byrne, Julie, 2018. "Clean energy investing in public capital markets: Portfolio benefits of yieldcos," Energy Policy, Elsevier, vol. 121(C), pages 383-393.

  28. Kris Boudt & Jin Zhang, 2015. "Jump robust two time scale covariance estimation and realized volatility budgets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1041-1054, June.

    Cited by:

    1. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    2. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    3. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    4. Yaojie Zhang & Yu Wei & Li Liu, 2019. "Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1425-1438, September.
    5. Aida Karmous & Heni Boubaker & Lotfi Belkacem, 2021. "Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 461-482, August.
    6. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    7. Karmous, Aida & Boubaker, Heni & Belkacem, Lotfi, 2019. "A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    8. Michael Ho & Jack Xin, 2016. "Sparse Kalman Filtering Approaches to Covariance Estimation from High Frequency Data in the Presence of Jumps," Papers 1602.02185, arXiv.org, revised Apr 2016.
    9. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    10. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.

  29. Boudt, Kris & Petitjean, Mikael, 2014. "Intraday liquidity dynamics and news releases around price jumps: Evidence from the DJIA stocks," Journal of Financial Markets, Elsevier, vol. 17(C), pages 121-149.
    See citations under working paper version above.
  30. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.

    Cited by:

    1. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    2. Yilmaz, Mustafa K. & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2015. "Cross-sectoral interactions in Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 1-20.
    3. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    4. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    5. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    6. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    8. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 353-382.
    9. Souhir, Ben Amor & Heni, Boubaker & Lotfi, Belkacem, 2019. "Price risk and hedging strategies in Nord Pool electricity market evidence with sector indexes," Energy Economics, Elsevier, vol. 80(C), pages 635-655.
    10. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    12. Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 499-512, October.
    13. Sébastien Laurent & Christelle Lecourt & Franz C. Palm, 2016. "Testing for jumps in conditionally Gaussian ARMA-GARCH models, a robust approach," Post-Print hal-01447861, HAL.
    14. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    15. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
    16. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    17. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    18. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    19. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    20. Amélie Charles & Olivier Darné, 0. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 0, pages 1-24.
    21. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    22. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the Pernicious Effects of Oil Price Uncertainty on U.S. Real Economic Activities," Post-Print hal-03040689, HAL.
    23. Sla{dj}ana Babi'c & Christophe Ley & Lorenzo Ricci & David Veredas, 2020. "TailCoR," Papers 2011.14817, arXiv.org.
    24. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    25. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    26. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    27. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    28. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    29. Grané, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    30. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    31. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for Bitcoin: Replication and robustness," International Economics, CEPII research center, issue 157, pages 23-32.
    32. Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
    33. Abdul Aziz, Nor Syahilla & Vrontos, Spyridon & M. Hasim, Haslifah, 2019. "Evaluation of multivariate GARCH models in an optimal asset allocation framework," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 568-596.
    34. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    35. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    36. Ewa Ratuszny, 2013. "Robust Estimation in VaR Modelling - Univariate Approaches using Bounded Innovation Propagation and Regression Quantiles Methodology," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(1), pages 35-63, March.
    37. Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2019. "Tales from tails: On the empirical distributions of forecasting errors and their implication to risk," International Journal of Forecasting, Elsevier, vol. 35(2), pages 687-698.
    38. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    39. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.

  31. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2013. "The impact of a sustainability constraint on the mean-tracking error efficient frontier," Economics Letters, Elsevier, vol. 119(3), pages 255-260.

    Cited by:

    1. Víctor Amor-Esteban & Mª-Purificación Galindo-Villardón & Fátima David, 2018. "Study of the Importance of National Identity in the Development of Corporate Social Responsibility Practices: A Multivariate Vision," Administrative Sciences, MDPI, vol. 8(3), pages 1-33, August.
    2. Víctor Amor‐Esteban & Ma‐Purificación Galindo‐Villardón & Isabel‐María García‐Sánchez & Fátima David, 2019. "An extension of the industrial corporate social responsibility practices index: New information for stakeholder engagement under a multivariate approach," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 26(1), pages 127-140, January.
    3. Víctor Amor-Esteban & Mª-Purificación Galindo-Villardón & Isabel-María García-Sánchez, 2019. "A Multivariate Proposal for a National Corporate Social Responsibility Practices Index (NCSRPI) for International Settings," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(2), pages 525-560, June.
    4. Apostolakis, George & van Dijk, Gert & Kraanen, Frido & Blomme, Robert J., 2018. "Examining socially responsible investment preferences: A discrete choice conjoint experiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 83-96.
    5. Maike van Dijk-de Groot & Andre H.J. Nijhof, 2015. "Socially Responsible Investment Funds: a review of research priorities and strategic options," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 5(3), pages 178-204, July.

  32. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.

    Cited by:

    1. Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
    2. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    3. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    4. Wenjing Wang & Minjing Tao, 2020. "Forecasting Realized Volatility Matrix With Copula-Based Models," Papers 2002.08849, arXiv.org.
    5. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    6. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    7. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.

  33. Boudt, Kris & Croux, Christophe & Laurent, Sébastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 353-367, March.
    See citations under working paper version above.
  34. Kris Boudt & Derya Caliskan & Christophe Croux, 2011. "Robust explicit estimators of Weibull parameters," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 187-209, March.

    Cited by:

    1. Shahzad Hussain & Sajjad Haider Bhatti & Tanvir Ahmad & Muhammad Ahmed Shehzad, 2021. "Parameter estimation of the Pareto distribution using least squares approaches blended with different rank methods and its applications in modeling natural catastrophes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(2), pages 1693-1708, June.
    2. Kris Boudt & Valentin Todorov & Wenjing Wang, 2020. "Robust Distribution-Based Winsorization in Composite Indicators Construction," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(2), pages 375-397, June.
    3. Colombo, Danilo & Lima, Gilson Brito Alves & Pereira, Danillo Roberto & Papa, João P., 2020. "Regression-based finite element machines for reliability modeling of downhole safety valves," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    4. Peter Ruckdeschel & Nataliya Horbenko, 2012. "Yet another breakdown point notion: EFSBP," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1025-1047, November.
    5. Asimit, Alexandru V. & Badescu, Alexandru M. & Verdonck, Tim, 2013. "Optimal risk transfer under quantile-based risk measurers," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 252-265.
    6. Liesa Denecke & Christine Müller, 2014. "New robust tests for the parameters of the Weibull distribution for complete and censored data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(5), pages 585-607, July.
    7. Toma, Aida & Leoni-Aubin, Samuela, 2013. "Optimal robust M-estimators using Rényi pseudodistances," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 359-373.
    8. Muhammad Aslam Mohd Safari & Nurulkamal Masseran & Muhammad Hilmi Abdul Majid, 2020. "Robust Reliability Estimation for Lindley Distribution—A Probability Integral Transform Statistical Approach," Mathematics, MDPI, vol. 8(9), pages 1-21, September.

  35. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.

    Cited by:

    1. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    2. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    3. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    4. Sébastien Laurent & Christelle Lecourt & Franz C. Palm, 2016. "Testing for jumps in conditionally Gaussian ARMA-GARCH models, a robust approach," Post-Print hal-01447861, HAL.
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