Research classified by Journal of Economic Literature (JEL) codes

2020

• Rey Francisco Ayala Castrejon & Christian Bucio Pacheco, 2020, "Modelo ARIMA aplicado al tipo de cambio peso-dólar en el periodo 2016-2017 mediante ventanas temporales deslizantes," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 15, issue 3, pages 331-354, Julio - S.
• Joana Almeida & Raquel M. Gaspar, 2020, "Accuracy of European Stock Target Prices," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2020/0115, Jan.
• Raquel M. Gaspar & Sara D. Lopes & Bernardo Sequeira, 2020, "Neural Network pricing of American put options," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2020/0122, Apr.
• Amparo Soler-Domínguez & Juan Carlos Matallín-Sáez & Diego Víctor de Mingo-López & Emili Tortosa-Ausina, 2020, "Social responsible mutual funds and lowcarbon economy," Working Papers, Economics Department, Universitat Jaume I, Castellón (Spain), number 2020/15.
• Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020, "Artificial intelligence in asset management," Working Papers, Cambridge Judge Business School, University of Cambridge, number 20202001, Mar.
• Prasenjit Chakrabarti & K Kiran Kumar, 2020, "High-Frequency Return-Implied Volatility Relationship: Empirical Evidence from Nifty and India VIX," Journal of Developing Areas, Tennessee State University, College of Business, volume 54, issue 3, pages 53-68, July-Sept.
• Jochen Güntner & Benjamin Karner, 2020, "Hedging with commodity futures and the end of normal Backwardation," Economics working papers, Department of Economics, Johannes Kepler University Linz, Austria, number 2020-21, Nov.
• Hatıra SADEGHZADEH EMSEN & Ömer Selçuk EMSEN & Ömer YALÇINKAYA, 2020, "An Effort To Construct A Mechanism Similar To The Taylor Rule Mechanism: Tests On Bist-100," JOURNAL OF LIFE ECONOMICS, Holistence Publications, volume 7, issue 1, pages 79-102, January, DOI: 10.15637/jlecon.7.006.
• Caio Vigo Pereira, 2020, "Portfolio Efficiency with High-Dimensional Data as Conditioning Information," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202015, Sep, revised Sep 2020.
• Mario Maggi & Maria-Laura Torrente & Pierpaolo Uberti, 2020, "Proper measures of connectedness," Annals of Finance, Springer, volume 16, issue 4, pages 547-571, December, DOI: 10.1007/s10436-020-00363-3.
• Polin Wu & Wasin Siwasarit, 2020, "Capturing the Order Imbalance with Hidden Markov Model: A Case of SET50 and KOSPI50," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, volume 27, issue 1, pages 115-144, March, DOI: 10.1007/s10690-019-09285-1.
• Hyeong-Ohk Bae & Seung-Yeal Ha & Yongsik Kim & Hyuncheul Lim & Jane Yoo, 2020, "Volatility Flocking by Cucker–Smale Mechanism in Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, volume 27, issue 3, pages 387-414, September, DOI: 10.1007/s10690-019-09299-9.
• Parthajit Kayal & Sayanti Mondal, 2020, "Speed of Price Adjustment in Indian Stock Market: A Paradox," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, volume 27, issue 4, pages 453-476, December, DOI: 10.1007/s10690-020-09303-7.
• Alexandru Mandes, 2020, "Impact of Electronic Liquidity Providers Within a High-Frequency Agent-Based Modeling Framework," Computational Economics, Springer;Society for Computational Economics, volume 55, issue 2, pages 407-450, February, DOI: 10.1007/s10614-019-09891-1.
• Jules Clement Mba & Sutene Mwambi, 2020, "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, volume 34, issue 2, pages 199-214, June, DOI: 10.1007/s11408-020-00346-4.
• Tania Morris & Jules Comeau, 2020, "Portfolio creation using artificial neural networks and classification probabilities: a Canadian study," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, volume 34, issue 2, pages 133-163, June, DOI: 10.1007/s11408-020-00350-8.
• Guglielmo Maria Caporale & Alex Plastun, 2020, "Momentum effects in the cryptocurrency market after one-day abnormal returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, volume 34, issue 3, pages 251-266, September, DOI: 10.1007/s11408-020-00357-1.

2019

• Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2019, "Forecasting Financial Stress Indices in Korea: A Factor Model Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-02, Mar.
• Hyeongwoo Kim & Kyunghwan Ko, 2019, "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-03, Apr.
• Sarthak Behera & Hyeongwoo Kim, 2019, "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-04, Oct.
• T. Bazhenov & D. Fantazzini, 2019, "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, volume 12, issue 1, DOI: 10.17073/2072-1633-2019-1-79-88.
• Daniel J. Wilson, 2019, "Clearing the Fog: The Predictive Power of Weather for Employment Reports and Their Asset Price Responses," American Economic Review: Insights, American Economic Association, volume 1, issue 3, pages 373-388, December.
• Mohamed Chikhi & Claude Diebolt, 2019, "Testing Nonlinearity through a Logistic Smooth Transition AR Model with Logistic Smooth Transition GARCH Errors," Working Papers, Association Française de Cliométrie (AFC), number 03-19.
• Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019, "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers, Association Française de Cliométrie (AFC), number 07-19.
• Niyazi TELÇEKEN & Murat KIYILAR & Eyüp KADIOĞLU, 2019, "Volatilite Endeksleri: Gelişimi, Türleri, Uygulamaları ve TRVIX Önerisi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 4, issue 2, pages 204-228, DOI: 10.30784/epfad.534052.
• Stanimir Ivanov Kabaivanov & Veneta Markovska, 2019, "Making a Difference: Accounting for the Impact of Management Decisions in Environmental Management," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, volume 66, issue 2, pages 131-139, June.
• Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019, "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali, number 440, Oct.
• Claudia Pigini, 2019, "Penalized Maximum Likelihood Estimation Of Logit-Based Early Warning Systems," Working Papers, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali, number 441, Nov.
• Jean Paul Rabanal & Aleksei Chernulich & John Horowitz & Olga A. Rud & Manizha Sharifova, 2019, "Market timing under public and private information," Working Papers, Peruvian Economic Association, number 151, Aug.
• Jozef Barunik & Pavel Fiser, 2019, "Co-jumping of Treasury Yield Curve Rates," Papers, arXiv.org, number 1905.01541, May.
• Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2019, "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Papers, arXiv.org, number 1906.05545, Jun.
• Tim Leung & Brian Ward, 2019, "Tracking VIX with VIX Futures: Portfolio Construction and Performance," Papers, arXiv.org, number 1907.00293, Jun.
• Kyungsub Lee & Byoung Ki Seo, 2019, "Marked Hawkes process modeling of price dynamics and volatility estimation," Papers, arXiv.org, number 1907.12025, Jul.
• Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019, "Implied volatility surface predictability: the case of commodity markets," Papers, arXiv.org, number 1909.11009, Sep.
• Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019, "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers, arXiv.org, number 1912.05228, Dec, revised Dec 2021.
• Gergana Taneva, 2019, "An analysis and a forecast of the cryptomarket based on the ARIMA model," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 66-84.
• Pablo Aguilar & Samuel Hurtado & Stephan Fahr & Eddie Gerba, 2019, "Quest for robust optimal macroprudential policy," Working Papers, Banco de España, number 1916, Jul.
• Wilmar Cabrera-Rodríguez & Santiago Segovia-Baquero & Juan Sebastián Mariño-Montaña & Eduardo Yanquen, 2019, "Probabilidad de incumplimiento de entidades financieras colombianas: una aproximación estructural," Borradores de Economia, Banco de la Republica de Colombia, number 1097, Nov, DOI: https://doi.org/10.32468/be.1097.
• Pei Kuang & Renbin Zhang & Tongbin Zhang, 2019, "New Tests of Expectation Formation with Applications to Asset Pricing Models," Discussion Papers, Department of Economics, University of Birmingham, number 19-05, May.
• Ingo Fender & Mike McMorrow & Vahe Sahakyan & Omar Zulaica, 2019, "Green bonds: the reserve management perspective," BIS Quarterly Review, Bank for International Settlements, September.
• Leonardo Gambacorta & Yiping Huang & Han Qiu & Jingyi Wang, 2019, "How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm," BIS Working Papers, Bank for International Settlements, number 834, Dec.
• Koresh Galil & Neta Gilat, 2019, "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., volume 19, issue 4, pages 731-758, December, DOI: 10.1111/irfi.12197.
• Jean‐Philippe Bouchaud & Philipp Krüger & Augustin Landier & David Thesmar, 2019, "Sticky Expectations and the Profitability Anomaly," Journal of Finance, American Finance Association, volume 74, issue 2, pages 639-674, April, DOI: 10.1111/jofi.12734.
• Ian W. R. Martin & Christian Wagner, 2019, "What Is the Expected Return on a Stock?," Journal of Finance, American Finance Association, volume 74, issue 4, pages 1887-1929, August, DOI: 10.1111/jofi.12778.
• Tobias Adrian & Richard K. Crump & Erik Vogt, 2019, "Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds," Journal of Finance, American Finance Association, volume 74, issue 4, pages 1931-1973, August, DOI: 10.1111/jofi.12776.
• Senarathne Chamil W., 2019, "The Impact of Internet Information Flow Regarding ‘Innovation’ on Common Stock Returns: Volume vs Google Search Quarries," Management of Sustainable Development, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, volume 11, issue 1, pages 43-49, June.
• Sun-Joong Yoon, 2019, "Determinants of Variance Risk Premium (in Korean)," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, volume 25, issue 1, pages 1-33, March.
• René Garcia & Nour Meddahi, 2019, "Prime de risque et prix du risque sur les actions," Revue d'économie financière, Association d'économie financière, volume 0, issue 1, pages 199-211.
• Cheng, T. & Gao, J. & Linton, O., 2019, "Nonparametric Predictive Regressions for Stock Return Prediction," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1932, Mar.
• Bauwens, Luc & Xu, Yongdeng, 2019, "DCC and DECO-HEAVY: a multivariate GARCH model based on realized variances and correlations," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2019/5, Feb, revised Aug 2021.
• Guglielmo Maria Caporale & Alex Plastun, 2019, "Momentum Effects in the Cryptocurrency Market After One-Day Abnormal Returns," CESifo Working Paper Series, CESifo, number 7917.
• Roni Michaely & Amir Rubin & Dan Segal & Alexander Vedrashko, 2019, "Lured by the Consensus," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-06, Mar, revised Mar 2019.
• Paul Schneider, 2019, "A Theory of Scenario Generation," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-17, Mar.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019, "A Flexible Regime Switching Model for Asset Returns," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-27, May, revised May 2019.
• Rebecca Westphal & Didier Sornette, 2019, "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-29, Jun.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019, "A Non-Elliptical Orthogonal GARCH Model for Portfolio Selection under Transaction Costs," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-51, Sep.
• Altan Pazarbasi & Paul Schneider & Grigory Vilkov, 2019, "Sentimental Recovery," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-57, Oct.
• Germ√°n Eduardo Gonz√°lez, 2019, "An√°lisis de sentimientos de noticias e inversionistas en el mercado burs√°til," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 17375, Aug.
• Xiomara Esther Vazquez Carrazana & Gilberto Jos� Miranda, 2019, "Relación entre indicadores económicos y precio de acciones en empresas brasilenas," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, volume 27, issue 2, pages 51-66, DOI: 10.18359/rfce.3510.
• Edwin Alexander Veloza Moreno, 2019, "Aplicación del modelo estocástico de difusion -salto de merton para la simulación del valor del índice colcap," Vniversitas Económica, Universidad Javeriana - Bogotá, volume 0, issue 0, pages 1-23.
• BAUWENS Luc, & XU Yongdeng,, 2019, "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), number 2019025, Dec.
• Tomasz Sosnowski & Anna Wawryszuk-Misztal, 2019, "Diversity on management and supervisory board and accuracy of management earnings forecasts in IPO prospectuses," Ekonomia i Prawo, Uniwersytet Mikolaja Kopernika, volume 18, issue 3, pages 347-363, September, DOI: 10.12775/EiP.2019.024.
• Sentana, Enrique & Fiorentini, Gabriele, 2019, "New testing approaches for mean-variance predictability," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13426, Jan.
• Adrian, Tobias & Vogt, Erik & Stackman, Daniel, 2019, "Global Price of Risk and Stabilization Policies," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13435, Jan.
• Mele, Antonio & Distaso, Walter & Vilkov, Grigory, 2019, "Correlation Risk, Strings and Asset Prices," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13873, Jul.
• Taylor, Alan M. & Davis, Josh, 2019, "The Leverage Factor: Credit Cycles and Asset Returns," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14115, Nov.
• Lettau, Martin & Ludvigson, Sydney & Greenwald, Dan, 2019, "How the Wealth Was Won: Factor Shares as Market Fundamentals," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14200, Dec.
• Gambacorta, Leonardo & Huang, Yiping & Qiu, Han & Wang, Jingyi, 2019, "How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14259, Dec.
• Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019, "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 29291, Nov.
• Kuo-Hwa Chang & Michael Nayat Young, 2019, "Portfolios Optimizations of Behavioral Stocks with Perception Probability Weightings," Annals of Economics and Finance, Society for AEF, volume 20, issue 2, pages 817-845, November.
• Fuwei Jiang & Joshua Lee & Xiumin Martin & Guofu Zhou, 2019, "Manager sentiment and stock returns," CEMA Working Papers, China Economics and Management Academy, Central University of Finance and Economics, number 677.
• Barnett, William A. & Su, Liting, 2019, "Risk Adjustment Of The Credit-Card Augmented Divisia Monetary Aggregates," Macroeconomic Dynamics, Cambridge University Press, volume 23, issue S1, pages 90-114, September.
• Karlo Kauko & Eero Tölö, 2019, "Banking Crisis Prediction with Differenced Relative Credit," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, volume 65, issue 4, pages 277-297, DOI: 10.3790/aeq.65.4.277.
• Михаела Монова, 2019, "Новите Законодателните Промени По Застраховка „Гражданска Отговорност” На Автомобилистите И Влиянието Им Върху Финансовата Стабилност На Българския Застрахователен Пазар," Almanac of PhD Students, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, volume 15, issue 15 Year 2, pages 125-154.
• Анелия Пенева, 2019, "Анализ На Взаимовръзките Между Капиталовите И Валутните Пазари," Almanac of PhD Students, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, volume 15, issue 15 Year 2, pages 29-50.
• Стефан Симеонов & Теодор Тодоров & Даниел Николаев, 2019, "Развитие На Честотния Анализ На Променливостта В Модел За Прогнозиране Тренда На Финансовите Пазари И Сравнителна Емпирична Оценка С Техническия Анализ," Electronic magazine "Dialogue", D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 1 Year 20, pages 37-70.
• Lang, Jan Hannes & Forletta, Marco, 2019, "Bank capital-at-risk: measuring the impact of cyclical systemic risk on future bank losses," Macroprudential Bulletin, European Central Bank, volume 9.
• Lang, Jan Hannes & Izzo, Cosimo & Fahr, Stephan & Ruzicka, Josef, 2019, "Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises," Occasional Paper Series, European Central Bank, number 219, Feb.
• Covi, Giovanni & Gorpe, Mehmet Ziya & Kok, Christoffer, 2019, "CoMap: mapping contagion in the euro area banking sector," Working Paper Series, European Central Bank, number 2224, Jan.
• Kelly, Jane & Le Blanc, Julia & Lydon, Reamonn, 2019, "Pockets of risk in European housing markets: then and now," Working Paper Series, European Central Bank, number 2277, May.
• Maqui, Eduardo & Sydow, Matthias & Gourdel, Régis, 2019, "Investment funds under stress," Working Paper Series, European Central Bank, number 2323, Oct.
• Ma, Sai & Zhang, Shaojun, 2019, "Housing Cycle and Exchange Rates," Working Paper Series, Ohio State University, Charles A. Dice Center for Research in Financial Economics, number 2019-14, May.
• Stulz, Rene M., 2019, "Public versus Private Equity," Working Paper Series, Ohio State University, Charles A. Dice Center for Research in Financial Economics, number 2019-27, Nov.
• Kalai Lamia & Kasraoui Naziha, 2019, "Financial Cointegration and the Vector Error Correction Model: The Case of MENA Countries," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 1, pages 160-168.
• Chin-Sheng Huang & Yi-Sheng Liu, 2019, "Machine Learning on Stock Price Movement Forecast: The Sample of the Taiwan Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 2, pages 189-201.
• Ra l de Jes s-Guti rrez & Roberto J. Santill n-Salgado, 2019, "Conditional Extreme Values Theory and Tail-related Risk Measures: Evidence from Latin American Stock Markets," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 3, pages 127-141.
• Arindam Banerjee, 2019, "Forecasting of India VIX as a Measure of Sentiment," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 3, pages 268-276.
• Rama Krishna Yelamanchili, 2019, "Impact of Consumer Sentiment on Defensive and Aggressive Stock Returns: Indian Evidence," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 4, pages 109-114.
• Nidhi Malhotra & Saumya Gupta, 2019, "Volatility Spillovers and Correlation Between Cryptocurrencies and Asian Equity Market," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 6, pages 208-215.
• Onder Buberkoku, 2019, "Do Long-memory GARCH-type-Value-at-Risk Models Outperform None-and Semi-parametric Value-at-Risk Models?," International Journal of Energy Economics and Policy, Econjournals, volume 9, issue 2, pages 199-215.
• Akono, Henri & Karim, Khondkar & Nwaeze, Emeka, 2019, "Analyst rounding of EPS forecasts and stock recommendations," Advances in accounting, Elsevier, volume 44, issue C, pages 68-80, DOI: 10.1016/j.adiac.2018.10.002.
• Filiz, Ibrahim & Nahmer, Thomas & Spiwoks, Markus, 2019, "Herd behavior and mood: An experimental study on the forecasting of share prices," Journal of Behavioral and Experimental Finance, Elsevier, volume 24, issue C, DOI: 10.1016/j.jbef.2019.07.004.
• Frank, Murray Z. & Nezafat, Mahdi, 2019, "Testing the credit-market-timing hypothesis using counterfactual issuing dates," Journal of Corporate Finance, Elsevier, volume 58, issue C, pages 187-207, DOI: 10.1016/j.jcorpfin.2019.05.005.
• Mazzarisi, Piero & Lillo, Fabrizio & Marmi, Stefano, 2019, "When panic makes you blind: A chaotic route to systemic risk," Journal of Economic Dynamics and Control, Elsevier, volume 100, issue C, pages 176-199, DOI: 10.1016/j.jedc.2018.12.009.
• Fiszeder, Piotr & Fałdziński, Marcin, 2019, "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, volume 108, issue C, DOI: 10.1016/j.jedc.2019.103736.
• Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019, "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, volume 109, issue C, DOI: 10.1016/j.jedc.2019.103777.
• Oh, Sekyung & Kee, Hyukdo & Park, Kinam, 2019, "Tail risk under price limits," Economic Modelling, Elsevier, volume 77, issue C, pages 113-123, DOI: 10.1016/j.econmod.2018.12.002.
• Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019, "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, volume 78, issue C, pages 32-39, DOI: 10.1016/j.econmod.2018.09.014.
• Koubaa, Yosra & Slim, Skander, 2019, "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, volume 82, issue C, pages 168-184, DOI: 10.1016/j.econmod.2019.01.003.
• Chen, An-Sing & Chang, Hung-Chou & Cheng, Lee-Young, 2019, "Time-varying Variance Scaling: Application of the Fractionally Integrated ARMA Model," The North American Journal of Economics and Finance, Elsevier, volume 47, issue C, pages 1-12, DOI: 10.1016/j.najef.2018.11.007.
• 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, volume 47, issue C, pages 568-596, DOI: 10.1016/j.najef.2018.06.012.
• Tissaoui, Kais & Azibi, Jamel, 2019, "International implied volatility risk indexes and Saudi stock return-volatility predictabilities," The North American Journal of Economics and Finance, Elsevier, volume 47, issue C, pages 65-84, DOI: 10.1016/j.najef.2018.11.016.
• Kang, Hankil & Ryu, Doojin, 2019, "Information in mispricing factors for future investment opportunities," The North American Journal of Economics and Finance, Elsevier, volume 47, issue C, pages 657-668, DOI: 10.1016/j.najef.2018.07.006.
• Meng, Xiangcai & Huang, Chia-Hsing, 2019, "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, volume 48, issue C, pages 131-148, DOI: 10.1016/j.najef.2019.01.009.
• Su, Zhi & Fang, Tong & Yin, Libo, 2019, "Understanding stock market volatility: What is the role of U.S. uncertainty?," The North American Journal of Economics and Finance, Elsevier, volume 48, issue C, pages 582-590, DOI: 10.1016/j.najef.2018.07.014.
• Wang, Ximei & Zhao, Yanlong & Bao, Ying, 2019, "Arbitrage-free conditions for implied volatility surface by Delta," The North American Journal of Economics and Finance, Elsevier, volume 48, issue C, pages 819-834, DOI: 10.1016/j.najef.2018.08.011.
• Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019, "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, volume 48, issue C, pages 857-867, DOI: 10.1016/j.najef.2018.08.010.
• Haas Ornelas, José Renato, 2019, "Expected currency returns and volatility risk premia," The North American Journal of Economics and Finance, Elsevier, volume 49, issue C, pages 206-234, DOI: 10.1016/j.najef.2019.03.015.
• Uddin, Gazi Salah & Gençay, Ramazan & Bekiros, Stelios & Sahamkhadam, Maziar, 2019, "Enhancing the predictability of crude oil markets with hybrid wavelet approaches," Economics Letters, Elsevier, volume 182, issue C, pages 50-54, DOI: 10.1016/j.econlet.2019.05.041.
• Delgado-Mohatar, Oscar & Felis-Rota, Marta & Fernández-Herraiz, Carlos, 2019, "The Bitcoin mining breakdown: Is mining still profitable?," Economics Letters, Elsevier, volume 184, issue C, DOI: 10.1016/j.econlet.2019.05.044.
• Bandi, F.M. & Perron, B. & Tamoni, A. & Tebaldi, C., 2019, "The scale of predictability," Journal of Econometrics, Elsevier, volume 208, issue 1, pages 120-140, DOI: 10.1016/j.jeconom.2018.09.008.
• Fisher, Mark & Jensen, Mark J., 2019, "Bayesian inference and prediction of a multiple-change-point panel model with nonparametric priors," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 187-202, DOI: 10.1016/j.jeconom.2018.11.012.
• Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019, "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, volume 211, issue 2, pages 388-413, DOI: 10.1016/j.jeconom.2018.10.008.
• Andreasen, Martin M. & Christensen, Jens H.E. & Rudebusch, Glenn D., 2019, "Term Structure Analysis with Big Data: One-Step Estimation Using Bond Prices," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 26-46, DOI: 10.1016/j.jeconom.2019.04.019.
• Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019, "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, volume 213, issue 2, pages 493-515, DOI: 10.1016/j.jeconom.2019.07.002.
• Ma, Xiaohan & Samaniego, Roberto, 2019, "Deconstructing uncertainty," European Economic Review, Elsevier, volume 119, issue C, pages 22-41, DOI: 10.1016/j.euroecorev.2019.06.004.
• Zhi, Tianhao & Li, Zhongfei & Jiang, Zhiqiang & Wei, Lijian & Sornette, Didier, 2019, "Is there a housing bubble in China?," Emerging Markets Review, Elsevier, volume 39, issue C, pages 120-132, DOI: 10.1016/j.ememar.2019.04.005.
• Trucíos, Carlos & Hotta, Luiz K. & Valls Pereira, Pedro L., 2019, "On the robustness of the principal volatility components," Journal of Empirical Finance, Elsevier, volume 52, issue C, pages 201-219, DOI: 10.1016/j.jempfin.2019.03.006.
• Kearney, Fearghal & Cummins, Mark & Murphy, Finbarr, 2019, "Using extracted forward rate term structure information to forecast foreign exchange rates," Journal of Empirical Finance, Elsevier, volume 53, issue C, pages 1-14, DOI: 10.1016/j.jempfin.2019.05.002.
• Díaz-Hernández, Adán & Constantinou, Nick, 2019, "A multiple regime extension to the Heston–Nandi GARCH(1,1) model," Journal of Empirical Finance, Elsevier, volume 53, issue C, pages 162-180, DOI: 10.1016/j.jempfin.2019.05.004.
• Panopoulou, Ekaterini & Souropanis, Ioannis, 2019, "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, volume 53, issue C, pages 197-221, DOI: 10.1016/j.jempfin.2019.07.004.
• Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019, "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, volume 53, issue C, pages 222-237, DOI: 10.1016/j.jempfin.2019.07.006.
• Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019, "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, volume 54, issue C, pages 97-117, DOI: 10.1016/j.jempfin.2019.08.007.
• Westerlund, Joakim & Sharma, Susan Sunila, 2019, "Panel evidence on the ability of oil returns to predict stock returns in the G7 area," Energy Economics, Elsevier, volume 77, issue C, pages 3-12, DOI: 10.1016/j.eneco.2018.05.007.
• Ji, Qiang & Liu, Bing-Yue & Fan, Ying, 2019, "Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model," Energy Economics, Elsevier, volume 77, issue C, pages 80-92, DOI: 10.1016/j.eneco.2018.07.012.
• Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019, "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, volume 78, issue C, pages 143-164, DOI: 10.1016/j.eneco.2018.10.034.
• Christensen, Troels Sønderby & Pircalabu, Anca & Høg, Esben, 2019, "A seasonal copula mixture for hedging the clean spark spread with wind power futures," Energy Economics, Elsevier, volume 78, issue C, pages 64-80, DOI: 10.1016/j.eneco.2018.11.002.
• Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019, "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Energy Economics, Elsevier, volume 79, issue C, pages 111-129, DOI: 10.1016/j.eneco.2018.03.032.
• Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019, "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, volume 80, issue C, pages 423-433, DOI: 10.1016/j.eneco.2019.01.010.
• Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019, "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, volume 81, issue C, pages 1109-1120, DOI: 10.1016/j.eneco.2019.05.018.
• Chun, Dohyun & Cho, Hoon & Kim, Jihun, 2019, "Crude oil price shocks and hedging performance: A comparison of volatility models," Energy Economics, Elsevier, volume 81, issue C, pages 1132-1147, DOI: 10.1016/j.eneco.2019.06.002.
• Liu, Jingzhen & Kemp, Alexander, 2019, "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, volume 81, issue C, pages 672-686, DOI: 10.1016/j.eneco.2019.04.023.
• Kim, Jae H. & Rahman, Md Lutfur & Shamsuddin, Abul, 2019, "Can energy prices predict stock returns? An extreme bounds analysis," Energy Economics, Elsevier, volume 81, issue C, pages 822-834, DOI: 10.1016/j.eneco.2019.05.029.
• Singh, Vipul Kumar & Kumar, Pawan & Nishant, Shreyank, 2019, "Global connectedness of MSCI energy equity indices: A system-wide network approach," Energy Economics, Elsevier, volume 84, issue C, DOI: 10.1016/j.eneco.2019.104477.
• Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2019, "How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study," Energy Economics, Elsevier, volume 84, issue C, DOI: 10.1016/j.eneco.2019.104536.
• Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019, "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, volume 63, issue C, pages 1-9, DOI: 10.1016/j.irfa.2019.02.007.
• Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019, "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, volume 63, issue C, pages 257-272, DOI: 10.1016/j.irfa.2018.12.002.
• Shahzad, Syed Jawad Hussain & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2019, "Is Bitcoin a better safe-haven investment than gold and commodities?," International Review of Financial Analysis, Elsevier, volume 63, issue C, pages 322-330, DOI: 10.1016/j.irfa.2019.01.002.
• Tissaoui, Kais, 2019, "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, volume 64, issue C, pages 232-249, DOI: 10.1016/j.irfa.2019.06.001.
• Yin, Anwen, 2019, "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, volume 65, issue C, DOI: 10.1016/j.irfa.2019.101385.
• Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019, "Overnight momentum, informational shocks, and late informed trading in China," International Review of Financial Analysis, Elsevier, volume 66, issue C, DOI: 10.1016/j.irfa.2019.101394.
• Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019, "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, volume 29, issue C, pages 315-322, DOI: 10.1016/j.frl.2018.08.013.
• Wong, Alfred, 2019, "Currency jumps, Euribor-OIS spreads and the volatility skew: A study on the dollar-euro crash risk of 2007–2015," Finance Research Letters, Elsevier, volume 29, issue C, pages 7-16, DOI: 10.1016/j.frl.2019.03.001.
• Chu, Xiaojun & Gu, Zherong & Zhou, Haigang, 2019, "Intraday momentum and reversal in Chinese stock market," Finance Research Letters, Elsevier, volume 30, issue C, pages 83-88, DOI: 10.1016/j.frl.2019.04.002.
• Kaiser, Lars, 2019, "Seasonality in cryptocurrencies," Finance Research Letters, Elsevier, volume 31, issue C, DOI: 10.1016/j.frl.2018.11.007.
• Geuder, Julian & Kinateder, Harald & Wagner, Niklas F., 2019, "Cryptocurrencies as financial bubbles: The case of Bitcoin," Finance Research Letters, Elsevier, volume 31, issue C, DOI: 10.1016/j.frl.2018.11.011.
• Lim, Kian Guan & Chen, Ying & Yap, Nelson K.L., 2019, "Intraday information from S&P 500 Index futures options," Journal of Financial Markets, Elsevier, volume 42, issue C, pages 29-55, DOI: 10.1016/j.finmar.2018.10.001.
• BenSaïda, Ahmed, 2019, "Good and bad volatility spillovers: An asymmetric connectedness," Journal of Financial Markets, Elsevier, volume 43, issue C, pages 78-95, DOI: 10.1016/j.finmar.2018.12.005.
• Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019, "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, volume 44, issue C, pages 91-118, DOI: 10.1016/j.finmar.2019.03.001.
• Lanfear, Matthew G. & Lioui, Abraham & Siebert, Mark G., 2019, "Market anomalies and disaster risk: Evidence from extreme weather events," Journal of Financial Markets, Elsevier, volume 46, issue C, DOI: 10.1016/j.finmar.2018.10.003.
• Gonçalves, Rui & Ribeiro, Vitor Miguel & Pereira, Fernando Lobo & Rocha, Ana Paula, 2019, "Deep learning in exchange markets," Information Economics and Policy, Elsevier, volume 47, issue C, pages 38-51, DOI: 10.1016/j.infoecopol.2019.05.002.
• Kok, Christoffer & Mirza, Harun & Pancaro, Cosimo, 2019, "Macro stress testing euro area banks’ fees and commissions," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 61, issue C, pages 97-119, DOI: 10.1016/j.intfin.2019.02.005.
• Kinateder, Harald & Papavassiliou, Vassilios G., 2019, "Sovereign bond return prediction with realized higher moments," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 62, issue C, pages 53-73, DOI: 10.1016/j.intfin.2019.05.002.
• Daly, Kevin & Batten, Jonathan A. & Mishra, Anil V. & Choudhury, Tonmoy, 2019, "Contagion risk in global banking sector," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 63, issue C, DOI: 10.1016/j.intfin.2019.101136.
• Buncic, Daniel & Stern, Cord, 2019, "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 63, issue C, DOI: 10.1016/j.intfin.2019.101138.
• Knotek, Edward S. & Zaman, Saeed, 2019, "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, volume 35, issue 4, pages 1708-1724, DOI: 10.1016/j.ijforecast.2018.10.012.
• Cont, Rama & Schaanning, Eric, 2019, "Monitoring indirect contagion," Journal of Banking & Finance, Elsevier, volume 104, issue C, pages 85-102, DOI: 10.1016/j.jbankfin.2019.04.007.
• Kearney, Fearghal & Shang, Han Lin & Sheenan, Lisa, 2019, "Implied volatility surface predictability: The case of commodity markets," Journal of Banking & Finance, Elsevier, volume 108, issue C, DOI: 10.1016/j.jbankfin.2019.105657.
• Gupta, Jairaj & Chaudhry, Sajid, 2019, "Mind the tail, or risk to fail," Journal of Business Research, Elsevier, volume 99, issue C, pages 167-185, DOI: 10.1016/j.jbusres.2019.02.037.
• Lu, Zhongjin & Murray, Scott, 2019, "Bear beta," Journal of Financial Economics, Elsevier, volume 131, issue 3, pages 736-760, DOI: 10.1016/j.jfineco.2018.09.006.
• Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019, "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, volume 132, issue 1, pages 126-149, DOI: 10.1016/j.jfineco.2018.10.001.
• Pyun, Sungjune, 2019, "Variance risk in aggregate stock returns and time-varying return predictability," Journal of Financial Economics, Elsevier, volume 132, issue 1, pages 150-174, DOI: 10.1016/j.jfineco.2018.10.002.
• Jensen, Christian Skov & Lando, David & Pedersen, Lasse Heje, 2019, "Generalized recovery," Journal of Financial Economics, Elsevier, volume 133, issue 1, pages 154-174, DOI: 10.1016/j.jfineco.2018.12.003.
• Calomiris, Charles W. & Mamaysky, Harry, 2019, "How news and its context drive risk and returns around the world," Journal of Financial Economics, Elsevier, volume 133, issue 2, pages 299-336, DOI: 10.1016/j.jfineco.2018.11.009.
• Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019, "Average skewness matters," Journal of Financial Economics, Elsevier, volume 134, issue 1, pages 29-47, DOI: 10.1016/j.jfineco.2019.03.003.
• Ederington, Louis & Guan, Wei & Yang, Lisa (Zongfei), 2019, "The impact of the U.S. employment report on exchange rates," Journal of International Money and Finance, Elsevier, volume 90, issue C, pages 257-267, DOI: 10.1016/j.jimonfin.2018.10.003.
• Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2019, "International tail risk and World Fear," Journal of International Money and Finance, Elsevier, volume 93, issue C, pages 244-259, DOI: 10.1016/j.jimonfin.2019.01.004.
• Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019, "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, volume 96, issue C, pages 210-227, DOI: 10.1016/j.jimonfin.2019.05.003.
• Ornelas, José Renato Haas & Mauad, Roberto Baltieri, 2019, "Volatility risk premia and future commodity returns," Journal of International Money and Finance, Elsevier, volume 96, issue C, pages 341-360, DOI: 10.1016/j.jimonfin.2017.07.008.
• Cronin, David & Dunne, Peter G., 2019, "How effective are sovereign bond-backed securities as a spillover prevention device?," Journal of International Money and Finance, Elsevier, volume 96, issue C, pages 49-66, DOI: 10.1016/j.jimonfin.2019.05.001.
• Xu, Zhongxiang & Chevapatrakul, Thanaset & Li, Xiafei, 2019, "Return asymmetry and the cross section of stock returns," Journal of International Money and Finance, Elsevier, volume 97, issue C, pages 93-110, DOI: 10.1016/j.jimonfin.2019.06.005.
• Khan, Mostafa Saidur Rahim & Kato, Hideaki Kiyoshi & Bremer, Marc, 2019, "Short sales constraints and stock returns: How do the regulations fare?," Journal of the Japanese and International Economies, Elsevier, volume 54, issue C, DOI: 10.1016/j.jjie.2019.101049.
• Spelta, A. & Pecora, N. & Rovira Kaltwasser, P., 2019, "Identifying Systemically Important Banks: A temporal approach for macroprudential policies," Journal of Policy Modeling, Elsevier, volume 41, issue 1, pages 197-218, DOI: 10.1016/j.jpolmod.2018.06.004.
• Nassios, Jason & Giesecke, James A. & Dixon, Peter B. & Rimmer, Maureen T., 2019, "Mandated superannuation contributions and the structure of the financial sector in Australia," Journal of Policy Modeling, Elsevier, volume 41, issue 5, pages 859-881, DOI: 10.1016/j.jpolmod.2019.05.004.
• Pincheira Brown, Pablo & Hardy, Nicolás, 2019, "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, volume 62, issue C, pages 256-281, DOI: 10.1016/j.resourpol.2019.02.019.
• Salisu, Afees A. & Isah, Kazeem O. & Raheem, Ibrahim D., 2019, "Testing the predictability of commodity prices in stock returns of G7 countries: Evidence from a new approach," Resources Policy, Elsevier, volume 64, issue C, DOI: 10.1016/j.resourpol.2019.101520.
• Alqahtani, Abdullah & Klein, Tony & Khalid, Ali, 2019, "The impact of oil price uncertainty on GCC stock markets," Resources Policy, Elsevier, volume 64, issue C, DOI: 10.1016/j.resourpol.2019.101526.
• Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019, "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, volume 54, issue C, pages 132-146, DOI: 10.1016/j.pacfin.2019.02.006.
• Bahrami, Afsaneh & Shamsuddin, Abul & Uylangco, Katherine, 2019, "Are advanced emerging market stock returns predictable? A regime-switching forecast combination approach," Pacific-Basin Finance Journal, Elsevier, volume 55, issue C, pages 142-160, DOI: 10.1016/j.pacfin.2019.02.003.
• Lai, Van Son & Ye, Xiaoxia & Zhao, Lu, 2019, "Are market views on banking industry useful for forecasting economic growth?," Pacific-Basin Finance Journal, Elsevier, volume 57, issue C, DOI: 10.1016/j.pacfin.2018.10.011.
• Hoang, Khoa & Cannavan, Damien & Gaunt, Clive & Huang, Ronghong, 2019, "Is that factor just lucky? Australian evidence," Pacific-Basin Finance Journal, Elsevier, volume 57, issue C, DOI: 10.1016/j.pacfin.2019.101191.
• Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019, "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, volume 58, issue C, DOI: 10.1016/j.pacfin.2019.101218.
• Shafique, Attayah & Ayub, Usman & Zakaria, Muhammad, 2019, "Don’t let the Greed catch you! Pleonexia rule applied to Pakistan stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 524, issue C, pages 157-168, DOI: 10.1016/j.physa.2019.04.048.
• Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019, "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 525, issue C, pages 466-477, DOI: 10.1016/j.physa.2019.03.097.
• Efremidze, Levan & Stanley, Darrol J. & Park, Abraham & Wasilewski, Nikolai, 2019, "Empirical implementation of entropy risk factor model: A test on Chilean peso," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 532, issue C, DOI: 10.1016/j.physa.2019.121836.
• Xiao, Binqing & Yang, Ye & Peng, Xuerong & Fang, Libing, 2019, "Measuring the connectedness of European electricity markets using the network topology of variance decompositions," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 535, issue C, DOI: 10.1016/j.physa.2019.122279.
• Isah, Kazeem O. & Raheem, Ibrahim D., 2019, "The hidden predictive power of cryptocurrencies and QE: Evidence from US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 536, issue C, DOI: 10.1016/j.physa.2019.04.268.
• Stoupos, Nikolaos & Kiohos, Apostolos, 2019, "Scandinavia: Towards the European Monetary Union?," The Quarterly Review of Economics and Finance, Elsevier, volume 74, issue C, pages 278-291, DOI: 10.1016/j.qref.2019.01.006.
• Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019, "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, volume 59, issue C, pages 150-163, DOI: 10.1016/j.iref.2018.08.016.
• Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019, "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, volume 59, issue C, pages 289-301, DOI: 10.1016/j.iref.2018.09.005.
• Gebka, Bartosz & Wohar, Mark E., 2019, "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, volume 60, issue C, pages 1-25, DOI: 10.1016/j.iref.2018.12.002.
• Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & Maasoumi, Esfandiar & McAleer, Michael & Pérez-Amaral, Teodosio, 2019, "Choosing expected shortfall over VaR in Basel III using stochastic dominance," International Review of Economics & Finance, Elsevier, volume 60, issue C, pages 95-113, DOI: 10.1016/j.iref.2018.12.016.
• Yen, Yu-Min, 2019, "Forward-looking information on growth and uncertainty implied by derivative securities: Evidence from an emerging market," International Review of Economics & Finance, Elsevier, volume 62, issue C, pages 240-266, DOI: 10.1016/j.iref.2019.03.008.
• Miwa, Kotaro, 2019, "Trading hours extension and intraday price behavior," International Review of Economics & Finance, Elsevier, volume 64, issue C, pages 572-585, DOI: 10.1016/j.iref.2019.07.007.
• Kusen, Alex & Rudolf, Markus, 2019, "Feedback trading: Strategies during day and night with global interconnectedness," Research in International Business and Finance, Elsevier, volume 48, issue C, pages 438-463, DOI: 10.1016/j.ribaf.2019.01.013.
• Pönkä, Harri & Zheng, Yi, 2019, "The role of oil prices on the Russian business cycle," Research in International Business and Finance, Elsevier, volume 50, issue C, pages 70-78, DOI: 10.1016/j.ribaf.2019.04.011.