Research classified by Journal of Economic Literature (JEL) codes

2022

• Wang, Gang-Jin & Xiong, Lu & Zhu, You & Xie, Chi & Foglia, Matteo, 2022, "Multilayer network analysis of investor sentiment and stock returns," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101707.
• Aloui, Riadh & Ben Jabeur, Sami & Mefteh-Wali, Salma, 2022, "Tail-risk spillovers from China to G7 stock market returns during the COVID-19 outbreak: A market and sectoral analysis," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101709.
• Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022, "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101723.
• Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022, "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101734.
• Carvajal-Patiño, Daniel & Ramos-Pollán, Raul, 2022, "Synthetic data generation with deep generative models to enhance predictive tasks in trading strategies," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101747.
• Bai, Chenjiang & Duan, Yuejiao & Liu, Congya & Qiu, Leiju, 2022, "International taxation sentiment and COVID-19 crisis," Research in International Business and Finance, Elsevier, volume 63, issue C, DOI: 10.1016/j.ribaf.2022.101783.
• Foster, Joshua & Haley, M. Ryan, 2022, "Charity auctions as assets: Theory and simulations of fundraising risk management in mean-variance space," Socio-Economic Planning Sciences, Elsevier, volume 83, issue C, DOI: 10.1016/j.seps.2022.101319.
• Yu, Baojun & Li, Changming & Mirza, Nawazish & Umar, Muhammad, 2022, "Forecasting credit ratings of decarbonized firms: Comparative assessment of machine learning models," Technological Forecasting and Social Change, Elsevier, volume 174, issue C, DOI: 10.1016/j.techfore.2021.121255.
• Yan, Lei & Mirza, Nawazish & Umar, Muhammad, 2022, "The cryptocurrency uncertainties and investment transitions: Evidence from high and low carbon energy funds in China," Technological Forecasting and Social Change, Elsevier, volume 175, issue C, DOI: 10.1016/j.techfore.2021.121326.
• Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022, "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, volume 182, issue C, DOI: 10.1016/j.techfore.2022.121810.
• Edson Z. Monte & Lucas B. Defanti, 2022, "Dynamic Interdependence and Volatility Transmission from the American to the Brazilian Stock Market," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 65, issue 1, pages 52-73.
• Fabio Calonaci & George Kapetanios & Simon Price, 2022, "Stock Returns Predictability with Unstable Predictors," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-04, Jan.
• Huy Viet Hoang & Son Tung Ha & Manh Linh Tran & Thi Thu Trang Nguyen, 2022, "Is auditor tolerant of earnings management in socially responsible firms? Evidence from China," Asian Review of Accounting, Emerald Group Publishing Limited, volume 30, issue 5, pages 669-690, October, DOI: 10.1108/ARA-01-2022-0001.
• Ender Baykut & Ercan Özen, 2022, "An Assessment of the Borsa Istanbul Insurance Index Return Structure: The Markov Regime Switching Model," Contemporary Studies in Economic and Financial Analysis, Emerald Group Publishing Limited, "Managing Risk and Decision Making in Times of Economic Distress, Part B", DOI: 10.1108/S1569-37592022000108B042.
• Serdar Simonyan & Sema Bayraktar, 2022, "Asymmetric dynamics in sovereign credit default swaps pricing: evidence from emerging countries," International Journal of Emerging Markets, Emerald Group Publishing Limited, volume 18, issue 12, pages 5607-5629, March, DOI: 10.1108/IJOEM-03-2021-0469.
• Sumaira Chamadia & Mobeen Ur Rehman & Muhammad Kashif, 2022, "Do average higher moments predict aggregate returns in emerging stock markets?," Journal of Asian Business and Economic Studies, Emerald Group Publishing Limited, volume 29, issue 2, pages 120-145, January, DOI: 10.1108/JABES-08-2021-0140.
• Hakan Yildirim & Saffet Akdag & Andrew Adewale Alola, 2022, "Is there a price bubble in the exchange rates of the developing countries? The case of BRICS and Turkey," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, volume 27, issue 54, pages 247-261, May, DOI: 10.1108/JEFAS-04-2021-0025.
• Clio Ciaschini & Maria Cristina Recchioni, 2022, "A market sentiment indicator, behaviourally grounded, for the analysis and forecast of volatility and bubbles," Review of Behavioral Finance, Emerald Group Publishing Limited, volume 16, issue 1, pages 17-38, November, DOI: 10.1108/RBF-07-2021-0128.
• Gil Cohen, 2022, "Artificial Intelligence in Trading the Financial Markets," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), volume 0, issue 1, pages 101-110.
• Demetrescu, Matei & Rodrigues, Paulo MM & Taylor, AM Robert, 2022, "Transformed Regression-based Long-Horizon Predictability Tests," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 30620, Jul.
• Calonaci, Fabio & Kapetanios, George & Price, Simon, 2022, "Stock returns predictability with unstable predictors," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 32331, Feb.
• Alexander Golub & Jon Anda & Anil Markandya & Michael Brody & Aldin Celovic & Angele Kedaitiene, 2022, "Climate alpha and the global capital market," Working Papers, Fondazione Eni Enrico Mattei, number 2022.19, Aug.
• Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2022, "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2022-16, Nov, DOI: 10.29338/wp2022-16.
• Filippo Ferroni, 2022, "How Interconnected Are Cryptocurrencies and What Does This Mean for Risk Management," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue 466, pages 1-5, March.
• Cagri HAMURCU, 2022, "Can Elon Mask's Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias?," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 1, DOI: 10.25295/fsecon.1028730.
• Yavuz ÖZEK & Halil OÄŸuzhan ERGÃœR, 2022, "The Effect Of Exchange Market Pressure On Output In Turkey," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 2, DOI: 10.25295/fsecon.1073333.
• Elena V. Ryabova & Natalia V. Feruleva & Olga A. Zamotaeva, 2022, "Assessing the Investment Attractiveness of Oil Field Development Projects under the Tax Maneuver: The Evidence from West Siberia," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 86-101, June, DOI: 10.31107/2075-1990-2022-3-86-101.
• Andrey V. Zubarev & Kirill D. Shilov, 2022, "Stress Test of the Russian Banking System: The Case of an Increase in Overdue Debt
  [Стресс-Тест Российской Банковской Системы: Случай Роста Просроченной Задолженности]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 52-62, December.
• Andrey V. Zubarev & Kirill D. Shilov, 2022, "Стресс-Тест Российской Банковской Системы: Случай Роста Просроченной Задолженности," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 52-62, December.
• Sisa Shiba & Juncal Cunado & Rangan Gupta, 2022, "Predictability of the Realised Volatility of International Stock Markets Amid Uncertainty Related to Infectious Diseases," JRFM, MDPI, volume 15, issue 1, pages 1-18, January.
• Dean Fantazzini, 2022, "Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death," JRFM, MDPI, volume 15, issue 7, pages 1-34, July.
• Christian Gourieroux & Alain Monfort & Jean-Paul Renne, 2022, "Required Capital for Long-Run Risks," Post-Print, HAL, number hal-03865173, Nov, DOI: 10.1016/j.jedc.2022.104502.
• Mohamad Hassan Shahrour & Mostafa Dekmak, 2022, "Intelligent Stock Prediction: A Neural Network Approach," Post-Print, HAL, number hal-03884171, Jun, DOI: 10.1142/S2424786322500165.
• 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," Post-Print, HAL, number hal-04021587, Mar, DOI: 10.1007/s42521-021-00045-3.
• Brice Corgnet & Cary Deck & Mark Desantis & David Porter, 2022, "Forecasting Skills in Experimental Market : Illusion or Reality?," Post-Print, HAL, number hal-04325544, Jul, DOI: 10.1287/mnsc.2021.4160.
• Olivier Dessaint & Thierry Foucault & Laurent Frésard, 2022, "The Horizon of Investors' Information and Corporate Investment," Working Papers, HAL, number hal-03890720, Nov, DOI: 10.2139/ssrn.4276832.
• Lööf, Hans & Sahamkhadam, Maziar & Stephan, Andreas, 2022, "Incorporating ESG into optimal stock portfolios for the global timber & forestry industry," Working Paper Series in Economics and Institutions of Innovation, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, number 490, Feb.
• Kladívko, Kamil & Österholm, Pär, 2022, "Analysts versus the Random Walk in Financial Forecasting: Evidence from the Czech National Bank’s Financial Market Inflation Expectations Survey," Working Papers, Örebro University, School of Business, number 2022:14, Nov.
• Bianchi, Daniele & Babiak, Mykola & Dickerson, Alexander, 2022, "Trading volume and liquidity provision in cryptocurrency markets," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 413, May.
• Alexander Sorokin, 2022, "Modeling of Optimal Credit Limits in Microfinance Organizations," HSE Economic Journal, National Research University Higher School of Economics, volume 26, issue 2, pages 285-306.
• Watanabe, Toshiaki & Nakajima, Jouchi, 2022, "Realized Volatility: Survey with Application to Nikkei 225 Stock Index," Economic Review, Hitotsubashi University, volume 73, issue 3, pages 254-280, July, DOI: 10.15057/74220.
• Sophia L. Zhou, 2022, "Real Estate Trend Prediction Using Linear Regression And Artificial Neural Network Techniques," Global Journal of Business Research, The Institute for Business and Finance Research, volume 16, issue 1, pages 1-16.
• Terrance Jalbert & Jonathan D. Stewart, 2022, "A Comprehensive Retirement Financial Planning Tool," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, volume 15, issue 1, pages 47-76.
• Montserrat Reyna Miranda & Ricardo Massa Roldán & Vicente Gómez Salcido, 2022, "Neuro-wavelet Model for price prediction in high-frequency data in the Mexican Stock market," 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 17, issue 1, pages 1-23, Enero - M.
• Nicolás Magner Pulgar & Esteban José Antonio Terán Sánchez & Vicente Alfonso Guzmán Muñoz, 2022, "Stock Market Synchronization and Stock Volatility: The Case of an Emerging Market," 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 17, issue 3, pages 1-22, Julio - S.
• Josh Davis & Alan M. Taylor, 2022, "The Leverage Factor: Credit Cycles and Asset Returns," Management Science, INFORMS, volume 68, issue 10, pages 7350-7361, October, DOI: 10.1287/mnsc.2022.4508.
• Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022, "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, volume 68, issue 7, pages 5216-5232, July, DOI: 10.1287/mnsc.2021.4160.

2021

• Mikkel Bennedsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2021, "Inference and forecasting for continuous-time integer-valued trawl processes and their use in financial economics," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2021-12, Jul.
• Rojo-Ramírez, Alfonso A., 2021, "Rendimiento mínimo del inversor-propietario. El caso de la empresa pyme familiar," Small Business International Review, Asociación Española de Contabilidad y Administración de Empresas - AECA, volume 5, issue 1, pages 287-287, January, DOI: 10.26784/sbir.v5i1.287.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021, "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2021-03, Jul.
• Barış Aksoy, 2021, "Predicting Financial Statement Frauds Using Machine Learning Methods and Logistic Regression: The Case of Borsa Istanbul," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., volume 36, issue 115, pages 27-58, April, DOI: https://doi.org/10.33203/mfy.733855.
• Mehmet Mete Karadağ, 2021, "Analysis of the Deposit Banks Quoted in BIST With Topsis and Entropy Methods in Terms of IMF Financial Soundness Indicators," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., volume 36, issue 116, pages 119-142, October, DOI: https://doi.org/10.33203/mfy.970497.
• Sonat Bayram, 2021, "Estimation of the Future Values of BIST 30 Shares with Geometric Brownian Motion and Volatility Analysis with ARIMA, SARIMA, GARCH, EGARCH, GJR Models," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., volume 36, issue Special2, pages 191-218, January, DOI: https://doi.org/10.33203/mfy.844861.
• Bogdan Cosmin GOMOI & Mioara Florina PANTEA & Lavinia Denisia CUC, 2021, "Brief Financial Diagnosis of a Transnational Company," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 1, issue 12, pages 19-28, December , DOI: 10.37945/cbr.2020.12.03.
• Elena Cristina DORNEANU, 2021, "Practical Solutions to Increase Business’ Resilience. Diagnostic Analysis of the Company’s Financial Position and Performance," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 10, pages 18-28, October, DOI: 10.37945/cbr.2021.10.03.
• Elena Cristina DORNEANU, 2021, "Practical Solutions to Increase Business’ Resilience. Diagnostic Analysis of the Company’s Financial Position and Performance," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 11, pages 62-72, November, DOI: 10.37945/cbr.2021.11.08.
• Bogdan Cosmin GOMOI & Natalia Ioana PANTELIMON, 2021, "SIG and CAF – Methods of Tracking and Analysing the Financial Performances of Economic Entities," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 1, pages 20-31, January, DOI: 10.37945/cbr.2021.01.03.
• Delia Andreea FLOREA & Diana Iulia OPRIȘ, 2021, "Stock Valuation Methods," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 1, pages 32-38, January, DOI: 10.37945/cbr.2021.01.04.
• Bogdan Cosmin GOMOI, 2021, "Management and Profitability Ratios – The Connection Between the Financial Position and the Performance of the Economic Entities," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 4, pages 39-46, April, DOI: 10.37945/cbr.2021.04.05.
• Bogdan Cosmin GOMOI, 2021, "Study Regarding the Development of an Investment Project. (I) – Identifying the Main Suppliers and Customers," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 5, pages 35-43, May, DOI: 10.37945/cbr.2021.05.04.
• Corina-Graziella BÂTCĂ-DUMITRU & Daniela-Nicoleta SAHLIAN & Cleopatra ȘENDROIU & Ioan-Codruț ȚURLEA, 2021, "Approaches to Setting Sales Prices," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 6, pages 18-25, June, DOI: 10.37945/cbr.2021.06.03.
• Bogdan Cosmin GOMOI, 2021, "Study Regarding the Development of an Investment Project. (II) – Estimating the Cost of Project and Identifying the Main Income and Expense Flows," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 6, pages 26-37, June, DOI: 10.37945/cbr.2021.06.04.
• Corina-Graziella BÂTCĂ-DUMITRU & Daniela-Nicoleta SAHLIAN & Cleopatra ȘENDROIU, 2021, "The Budgetary Management of Sales," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 7, pages 14-24, July, DOI: 10.37945/cbr.2021.07.02.
• Bogdan Cosmin GOMOI, 2021, "Study Regarding the Development of an Investment Project. (III) – Project Evaluation," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 7, pages 25-34, July, DOI: 10.37945/cbr.2021.07.03.
• Bogdan Cosmin GOMOI, 2021, "Short Financial Diagnosis for a Transport Entity," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 8, pages 18-27, August, DOI: 10.37945/cbr.2021.08.03.
• Bogdan Cosmin GOMOI, 2021, "The Financial Analyses of an Entity from the Tourism Field – Between Normality and the COVID-19 Pandemic," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), volume 2, issue 9, pages 12-21, September, DOI: 10.37945/cbr.2021.09.02.
• Osman Yavuz Akbulut & Ali Hepşen, 2021, "Finansal Performans ve Pay Senedi Getirileri Arasındaki İlişkinin Entropi ve CoCoSo ÇKKV Teknikleriyle Analiz Edilmesi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 6, issue 3, pages 681-709, DOI: 10.30784/epfad.945770.
• Leyla Ar & Reşat Sakur, 2021, "Modern Sermaye Yapısı Teorilerinin Geçerliliğinin Test Edilmesi: BIST 30 Endeksi Firmaları Üzerine Bir Araştırma," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 6, issue 3, pages 748-773, DOI: 10.30784/epfad.926187.
• Yan, Beibei & Arslan-Ayaydin, Özgür & Thewissen, James & Torsin, Wouter, 2021, "Does managerial ability affect disclosure? Evidence from earnings press releases," LIDAM Reprints LFIN, Université catholique de Louvain, Louvain Finance (LFIN), number 2021006, Jan, DOI: https://doi.org/10.1108/ARA-03-2020.
• Kyle Hampton & Paul Johnson, 2021, "Kaivik: A Free Online Asset Market Cellphone Interface Experiment with Financial Bubbles," Working Papers, University of Alaska Anchorage, Department of Economics, number 2021-04, Nov.
• Victor Olkhov, 2021, "To VaR, or Not to VaR, That is the Question," Papers, arXiv.org, number 2101.08559, Jan, revised Apr 2024.
• Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021, "Deep Structural Estimation: With an Application to Option Pricing," Papers, arXiv.org, number 2102.09209, Feb.
• Sergio Consoli & Luca Tiozzo Pezzoli & Elisa Tosetti, 2021, "Emotions in Macroeconomic News and their Impact on the European Bond Market," Papers, arXiv.org, number 2106.15698, Jun.
• Qihui Chen & Nikolai Roussanov & Xiaoliang Wang, 2021, "Semiparametric Conditional Factor Models in Asset Pricing," Papers, arXiv.org, number 2112.07121, Dec, revised Apr 2025.
• Osoolian, Mohammad & Koushki, Ali, 2021, "Prediction of Crisis in Tehran Stock Exchange with Entropy and Analyzing the Identified Crises such as Covid-19 (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, volume 26, issue 2, pages 133-152, September.
• Neluka Devpura, 2021, "Can Oil Prices Predict Japanese Yen?," Asian Economics Letters, Asia-Pacific Applied Economics Association, volume 1, issue 3, pages 1-5, DOI: 2021/06/27.
• Afees A. Salisu & Abdulsalam Abidemi Sikiru, 2021, "Pandemics and the Asia-Pacific Islamic Stocks," Asian Economics Letters, Asia-Pacific Applied Economics Association, volume 1, issue 1, pages 1-5, DOI: 2021/06/27.
• Manuela Pedio, 2021, "Option-Implied Network Measures of Tail Contagion and Stock Return Predictability," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 21154.
• Dariia Vasylieva, 2021, "Corporate Bond Markets In Eastern Europe: Trends And Prospects," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", volume 7, issue 1, DOI: 10.30525/2256-0742/2021-7-1-10-18.
• Rodolfo Méndez-Marcano, 2021, "Global | A vector autoregressive model for banking stress testing," Working Papers, BBVA Bank, Economic Research Department, number 21/08, Jul.
• Ali CELÝK, 2021, "Volatility of BIST 100 Returns After 2020, Calendar Anomalies and COVID-19 Effect," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 15, issue 1, pages 61-81.
• Roberto Pascual, 2021, "Do analysts forecast differently in periods of uncertainty? An empirical analysis of target prices for Spanish banks," Working Papers, Banco de España, number 2144, Dec.
• Davide Di Zio & Marco Fanari & Simone Letta & Tommaso Perez & Giovanni Secondin, 2021, "The strategic allocation and sustainability of central banks' investment," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems), Bank of Italy, Directorate General for Markets and Payment System, number 14, Dec.
• Fredy Gamboa-Estrada & Jose Vicente Romero, 2021, "Common and idiosyncratic movements in Latin-American Exchange Rates," Borradores de Economia, Banco de la Republica de Colombia, number 1158, Apr, DOI: https://doi.org/10.32468/be.1158.
• Florens Odendahl & Tatevik Sekhposyan & Barbara Rossi, 2021, "Evaluating Forecast Performance with State Dependence," Working Papers, Barcelona School of Economics, number 1295, Oct.
• Mikael Juselius & Nikola Tarashev, 2021, "Could corporate credit losses turn out higher than expected?," BIS Bulletins, Bank for International Settlements, number 46, Aug.
• Sebastian Doerr & Leonardo Gambacorta & José María Serena Garralda, 2021, "Big data and machine learning in central banking," BIS Working Papers, Bank for International Settlements, number 930, Mar.
• Nguyen Xuan-Huynh & Luu Quoc Chien, 2021, "Performance Measurement of Vietnamese Publishing Firms by the Integration of the GM (1,1) Model and the Malmquist Model," Business Systems Research, Paradigm, volume 12, issue 1, pages 17-33, May, DOI: 10.2478/bsrj-2021-0002.
• Henry Penikas & Anastasia Skarednova & Mikhail Surkov, 2021, "How Do Investors Prefer Banks to Transit to Basel Internal Models: Mandatorily or Voluntarily?," Bank of Russia Working Paper Series, Bank of Russia, number wps74, Jul.
• J. James Reade & Carl Singleton & Alasdair Brown, 2021, "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, volume 68, issue 2, pages 261-285, May, DOI: 10.1111/sjpe.12264.
• BOTOROGA Cosmin-Alin & HOROBET Alexandra & BELASCU Lucian, 2021, "Assessing Market Risk During Financial Crises - An Applicable Method Of Using Value At Risk And Expected Shortfall In Investments," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, volume 73, issue 3, pages 51-74, October.
• Mattia Montagna & Gabriele Torri & Giovanni Covi, 2021, "On the origin of systemic risk," Bank of England Staff Working Paper series, Bank of England, number 906, Jan.
• David Murphy & Nicholas Vause, 2021, "A CBA of APC: analysing approaches to procyclicality reduction in CCP initial margin models," Bank of England Staff Working Paper series, Bank of England, number 950, Nov.
• Panagiotis Lazaris & Anastasios Petropoulos & Vasileios Siakoulis & Evangelos Stavroulakis & Nikolaos Vlachogiannakis, 2021, "Interest rate pass through in the deposit and loan products provided by Greek banks," Working Papers, Bank of Greece, number 287, Feb.
• Chang Carolyn W. & Feng Yalan, 2021, "Hurricane Bond Price Dependency on Underlying Hurricane Parameters," Asia-Pacific Journal of Risk and Insurance, De Gruyter, volume 15, issue 1, pages 1-21, January, DOI: 10.1515/apjri-2020-0017.
• Tripathi Manas & Kumar Saurabh & Inani Sarveshwar Kumar, 2021, "Exchange Rate Forecasting Using Ensemble Modeling for Better Policy Implications," Journal of Time Series Econometrics, De Gruyter, volume 13, issue 1, pages 43-71, January, DOI: 10.1515/jtse-2020-0013.
• Otilia P. MANTA, 2021, "The Impact Of Population Financial Indicators On The National Economy," Contemporary Economy Journal, Constantin Brancoveanu University, volume 6, issue 4, pages 49-59.
• Ding, Y., 2021, "Conditional Heteroskedasticity in the Volatility of Asset Returns," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2179, Nov.
• Nenad Milojević & Srdjan Redzepagic, 2021, "Prospects of Artificial Intelligence and Machine Learning Application in Banking Risk Management," Journal of Central Banking Theory and Practice, Central bank of Montenegro, volume 10, issue 3, pages 41-57.
• Scott R. Baker & Nicholas Bloom & Steven J. Davis & Marco Sammon, 2021, "What triggers stock market jumps?," CEP Discussion Papers, Centre for Economic Performance, LSE, number dp1789, Aug.
• Scott R. Baker & Nicholas Bloom & Steven J. Davis & Marco Sammon, 2021, "What triggers stock market jumps?," POID Working Papers, Centre for Economic Performance, LSE, number 010, Aug.
• Daniele Bianchi & Mykola Babiak, 2021, "A Factor Model for Cryptocurrency Returns," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp710, Nov.
• Felix Haase & Matthias Neuenkirch, 2021, "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series, CESifo, number 8828.
• Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021, "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-09, Jan.
• Alexander Wehrli & Didier Sornette, 2021, "Excess financial volatility explained by endogenous excitations revealed by EM calibrations of a generalized Hawkes point process," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-35, Apr.
• Davide Cividino & Rebecca Westphal & Didier Sornette, 2021, "Multi-asset financial bubbles in an agent-based model with noise traders’ herding described by an n-vector Ising model," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-76, Nov.
• Dongshuai Zhao, CFA & Didier Sornette, 2021, "Bubbles for Fama from Sornette," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-94, Dec.
• Damir Filipović & Amir Khalilzadeh, 2021, "Machine Learning for Predicting Stock Return Volatility," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-95, Dec.
• Yannick Malevergne & Didier Sornette & Ran Wei, 2021, "A model of financial bubbles and drawdowns with non-local behavioral self-referencing," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-96, Dec.
• Christian Urom & Gideon Ndubuisi & Jude Ozor, 2021, "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, CEPII research center, issue 165, pages 51-66.
• Dessaint, Olivier & Foucault, Thierry & Frésard, Laurent, 2021, "Does Alternative Data Improve Financial Forecasting? The Horizon Effect," CEPR Discussion Papers, Centre for Economic Policy Research, number 15786, Feb.
• Moench, Emanuel & Stein, Tobias, 2021, "Equity premium predictability over the business cycle," CEPR Discussion Papers, Centre for Economic Policy Research, number 16357, Jul.
• Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021, "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, volume 37, issue 4, pages 794-816, August.
• Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021, "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, volume 56, issue 1, pages 65-91, February.
• Doan, Minh Phuong & Sercu, Piet, 2021, "Merging One's Way to the Top: AB Inbev versus Heineken," Journal of Wine Economics, Cambridge University Press, volume 16, issue 1, pages 32-55, February.
• Ali Trabelsi Karoui & Aida Kammoun, 2021, "Exchange Rate Determination: Mixed Microstructural and Macroeconomic Approach," International Journal of Economics and Financial Issues, International Journal of Economics and Financial Issues, volume 11, issue 3, pages 89-106.
• Ikhlaas Gurrib & Firuz Kamalov & Elgilani Elshareif, 2021, "Can the Leading US Energy Stock Prices be Predicted using the Ichimoku Cloud?," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 11, issue 1, pages 41-51.
• Evaristo Navarro Manotas & Remedios Pitre Redondo & Janeka L pez Contreras & Meredith Jim nez Cardenas & Hugo Hernandez Palma, 2021, "Renewable Energies and their Advantages for the Sustainability of Companies in the Health Sector," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 11, issue 5, pages 531-537.
• Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021, "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 11, issue 6, pages 489-502.
• Prasad, Mason & Bakry, Walid & Varua, Maria Estela, 2021, "Abnormal volatility in seasoned equity offerings during economic disruptions," Journal of Behavioral and Experimental Finance, Elsevier, volume 30, issue C, DOI: 10.1016/j.jbef.2021.100509.
• Filiz, Ibrahim & Judek, Jan René & Lorenz, Marco & Spiwoks, Markus, 2021, "Reducing algorithm aversion through experience," Journal of Behavioral and Experimental Finance, Elsevier, volume 31, issue C, DOI: 10.1016/j.jbef.2021.100524.
• Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021, "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, volume 32, issue C, DOI: 10.1016/j.jbef.2021.100591.
• Amini, Shahram & Elmore, Ryan & Öztekin, Özde & Strauss, Jack, 2021, "Can machines learn capital structure dynamics?," Journal of Corporate Finance, Elsevier, volume 70, issue C, DOI: 10.1016/j.jcorpfin.2021.102073.
• Georges, Christophre & Pereira, Javier, 2021, "Market stability with machine learning agents," Journal of Economic Dynamics and Control, Elsevier, volume 122, issue C, DOI: 10.1016/j.jedc.2020.104032.
• Bianchi, Daniele, 2021, "Adaptive expectations and commodity risk premiums," Journal of Economic Dynamics and Control, Elsevier, volume 124, issue C, DOI: 10.1016/j.jedc.2021.104078.
• Nyman, Rickard & Kapadia, Sujit & Tuckett, David, 2021, "News and narratives in financial systems: Exploiting big data for systemic risk assessment," Journal of Economic Dynamics and Control, Elsevier, volume 127, issue C, DOI: 10.1016/j.jedc.2021.104119.
• Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021, "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, volume 69, issue C, pages 208-224, DOI: 10.1016/j.eap.2020.12.008.
• Lehrer, Steven & Xie, Tian & Zhang, Xinyu, 2021, "Social media sentiment, model uncertainty, and volatility forecasting," Economic Modelling, Elsevier, volume 102, issue C, DOI: 10.1016/j.econmod.2021.105556.
• Shang, Yuhuang & Zheng, Tingguo, 2021, "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, volume 95, issue C, pages 462-472, DOI: 10.1016/j.econmod.2020.03.013.
• Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021, "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, volume 96, issue C, pages 209-219, DOI: 10.1016/j.econmod.2021.01.005.
• Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021, "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, volume 98, issue C, pages 361-370, DOI: 10.1016/j.econmod.2020.11.005.
• Nonejad, Nima, 2021, "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, volume 57, issue C, DOI: 10.1016/j.najef.2021.101442.
• Shu, Min & Song, Ruiqiang & Zhu, Wei, 2021, "The ‘COVID’ crash of the 2020 U.S. Stock market," The North American Journal of Economics and Finance, Elsevier, volume 58, issue C, DOI: 10.1016/j.najef.2021.101497.
• Chen, Zilin & Gang, Jianhua & Qian, Zongxin, 2021, "Stock returns and carry trades," The North American Journal of Economics and Finance, Elsevier, volume 58, issue C, DOI: 10.1016/j.najef.2021.101507.
• Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021, "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, volume 58, issue C, DOI: 10.1016/j.najef.2021.101525.
• Qiu, Yue, 2021, "Complete subset least squares support vector regression," Economics Letters, Elsevier, volume 200, issue C, DOI: 10.1016/j.econlet.2021.109737.
• Gross, Christian & Jarmuzek, Mariusz & Pancaro, Cosimo, 2021, "Macro-stress testing dividend income. Evidence from euro area banks," Economics Letters, Elsevier, volume 201, issue C, DOI: 10.1016/j.econlet.2021.109763.
• Akyildirim, Erdinc & Aysan, Ahmet Faruk & Cepni, Oguzhan & Darendeli, S. Pinar Ceyhan, 2021, "Do investor sentiments drive cryptocurrency prices?," Economics Letters, Elsevier, volume 206, issue C, DOI: 10.1016/j.econlet.2021.109980.
• Qiu, Yue & Wang, Yifan & Xie, Tian, 2021, "Forecasting Bitcoin realized volatility by measuring the spillover effect among cryptocurrencies," Economics Letters, Elsevier, volume 208, issue C, DOI: 10.1016/j.econlet.2021.110092.
• Fiorentini, Gabriele & Sentana, Enrique, 2021, "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 516-538, DOI: 10.1016/j.jeconom.2020.07.014.
• Jaskowski, Marcin & McAleer, Michael, 2021, "Spurious cross-sectional dependence in credit spread changes," Econometrics and Statistics, Elsevier, volume 18, issue C, pages 12-27, DOI: 10.1016/j.ecosta.2019.09.001.
• Leung, Melvern & Li, Youwei & Pantelous, Athanasios A. & Vigne, Samuel A., 2021, "Bayesian Value-at-Risk backtesting: The case of annuity pricing," European Journal of Operational Research, Elsevier, volume 293, issue 2, pages 786-801, DOI: 10.1016/j.ejor.2020.12.051.
• Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021, "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, volume 62, issue C, pages 179-201, DOI: 10.1016/j.jempfin.2021.03.003.
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021, "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, volume 63, issue C, pages 252-269, DOI: 10.1016/j.jempfin.2021.07.009.
• Calice, Giovanni & Lin, Ming-Tsung, 2021, "Exploring risk premium factors for country equity returns," Journal of Empirical Finance, Elsevier, volume 63, issue C, pages 294-322, DOI: 10.1016/j.jempfin.2021.07.003.
• Ewald, Christian & Zou, Yihan, 2021, "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, volume 64, issue C, pages 37-52, DOI: 10.1016/j.jempfin.2021.08.006.
• Han, Yang & Jiao, Anqi & Ma, Jun, 2021, "The predictive power of Nelson–Siegel factor loadings for the real economy," Journal of Empirical Finance, Elsevier, volume 64, issue C, pages 95-127, DOI: 10.1016/j.jempfin.2021.04.008.
• Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021, "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, volume 100, issue C, DOI: 10.1016/j.eneco.2021.105300.
• Lyócsa, Štefan & Todorova, Neda, 2021, "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, volume 100, issue C, DOI: 10.1016/j.eneco.2021.105367.
• Ladokhin, Sergiy & Borovkova, Svetlana, 2021, "Three-factor commodity forward curve model and its joint P and Q dynamics," Energy Economics, Elsevier, volume 101, issue C, DOI: 10.1016/j.eneco.2021.105418.
• Patra, Saswat, 2021, "Revisiting value-at-risk and expected shortfall in oil markets under structural breaks: The role of fat-tailed distributions," Energy Economics, Elsevier, volume 101, issue C, DOI: 10.1016/j.eneco.2021.105452.
• Baum, Christopher F. & Zerilli, Paola & Chen, Liyuan, 2021, "Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data," Energy Economics, Elsevier, volume 93, issue C, DOI: 10.1016/j.eneco.2019.104481.
• Iyke, Bernard Njindan & Tran, Vuong Thao & Narayan, Paresh Kumar, 2021, "Can energy security predict energy stock returns?," Energy Economics, Elsevier, volume 94, issue C, DOI: 10.1016/j.eneco.2020.105052.
• Dai, Zhifeng & Zhou, Huiting & Kang, Jie & Wen, Fenghua, 2021, "The skewness of oil price returns and equity premium predictability," Energy Economics, Elsevier, volume 94, issue C, DOI: 10.1016/j.eneco.2020.105069.
• Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2021, "Predicting corporate carbon footprints for climate finance risk analyses: A machine learning approach," Energy Economics, Elsevier, volume 95, issue C, DOI: 10.1016/j.eneco.2021.105129.
• He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021, "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, volume 97, issue C, DOI: 10.1016/j.eneco.2021.105189.
• Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2021, "Investor heterogeneity and momentum-based trading strategies in China," International Review of Financial Analysis, Elsevier, volume 74, issue C, DOI: 10.1016/j.irfa.2020.101654.
• Lartey, Theophilus & James, Gregory A. & Danso, Albert, 2021, "Interbank funding, bank risk exposure and performance in the UK: A three-stage network DEA approach," International Review of Financial Analysis, Elsevier, volume 75, issue C, DOI: 10.1016/j.irfa.2021.101753.
• Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021, "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, volume 76, issue C, DOI: 10.1016/j.irfa.2021.101776.
• Vigo Pereira, Caio, 2021, "Portfolio efficiency with high-dimensional data as conditioning information," International Review of Financial Analysis, Elsevier, volume 77, issue C, DOI: 10.1016/j.irfa.2021.101811.
• Nonejad, Nima, 2021, "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, volume 77, issue C, DOI: 10.1016/j.irfa.2021.101818.
• Doan, Minh Phuong & Sercu, Piet, 2021, "Modelling multiperiod patterns in stock-market reactions to events, with an application to serial acquisitions," International Review of Financial Analysis, Elsevier, volume 77, issue C, DOI: 10.1016/j.irfa.2021.101854.
• Fei, Tianlun & Liu, Xiaoquan, 2021, "Herding and market volatility," International Review of Financial Analysis, Elsevier, volume 78, issue C, DOI: 10.1016/j.irfa.2021.101880.
• Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021, "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, volume 78, issue C, DOI: 10.1016/j.irfa.2021.101908.
• Liu, Zhenya & Lu, Shanglin & Wang, Shixuan, 2021, "Asymmetry, tail risk and time series momentum," International Review of Financial Analysis, Elsevier, volume 78, issue C, DOI: 10.1016/j.irfa.2021.101938.
• González-Sánchez, Mariano, 2021, "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2020.101510.
• Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021, "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2020.101453.
• Wu, Xinyu & Xie, Haibin, 2021, "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2019.101392.
• Bouri, Elie & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2021, "Gold, platinum and the predictability of bond risk premia," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2020.101490.
• Kinateder, Harald & Papavassiliou, Vassilios G., 2021, "Calendar effects in Bitcoin returns and volatility," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2019.101420.
• Silahli, Baykar & Dingec, Kemal Dincer & Cifter, Atilla & Aydin, Nezir, 2021, "Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2019.101425.
• Bonato, Matteo & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021, "A note on investor happiness and the predictability of realized volatility of gold," Finance Research Letters, Elsevier, volume 39, issue C, DOI: 10.1016/j.frl.2020.101614.
• Kladívko, Kamil & Österholm, Pär, 2021, "Do market participants’ forecasts of financial variables outperform the random-walk benchmark?," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101712.
• Apergis, Nicholas & Koutmos, Dimitrios & Payne, James E., 2021, "Convergence in cryptocurrency prices? the role of market microstructure," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101685.
• Madan, Dilip B. & Wang, King, 2021, "The structure of financial returns," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101665.
• Burggraf, Tobias & Rudolf, Markus, 2021, "Cryptocurrencies and the low volatility anomaly," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101683.
• Iyke, Bernard Njindan & Ho, Sin-Yu, 2021, "Stock return predictability over four centuries: The role of commodity returns," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101711.
• Taussig, Roi D., 2021, "Competition risk and expected stock returns," Finance Research Letters, Elsevier, volume 41, issue C, DOI: 10.1016/j.frl.2020.101860.
• Chang, Danting, 2021, "Fundamental anomalies and the size puzzle in China: A data mining approach," Finance Research Letters, Elsevier, volume 42, issue C, DOI: 10.1016/j.frl.2020.101907.
• Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021, "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, volume 42, issue C, DOI: 10.1016/j.frl.2021.101924.
• Boubaker, Sabri & Liu, Zhenya & Lu, Shanglin & Zhang, Yifan, 2021, "Trading signal, functional data analysis and time series momentum," Finance Research Letters, Elsevier, volume 42, issue C, DOI: 10.1016/j.frl.2021.101933.
• Guidolin, Massimo & Pedio, Manuela, 2021, "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," Finance Research Letters, Elsevier, volume 42, issue C, DOI: 10.1016/j.frl.2021.101943.
• Maheu, John M. & McCurdy, Thomas H. & Song, Yong, 2021, "Bull and bear markets during the COVID-19 pandemic," Finance Research Letters, Elsevier, volume 42, issue C, DOI: 10.1016/j.frl.2021.102091.
• Umar, Zaghum & Riaz, Yasir & Zaremba, Adam, 2021, "Patterns of Spillover in Energy, Agricultural, and Metal Markets: A Connectedness Analysis for Years 1780-2020," Finance Research Letters, Elsevier, volume 43, issue C, DOI: 10.1016/j.frl.2021.101999.
• Hou, Tony Chieh-Tse & Gao, Simon, 2021, "The impact of economic freedom on financial analysts' earnings forecast: Evidence from the Asia-Pacific region," Finance Research Letters, Elsevier, volume 43, issue C, DOI: 10.1016/j.frl.2021.102009.
• Castillo, Brenda & León, Ángel & Ñíguez, Trino-Manuel, 2021, "Backtesting VaR under the COVID-19 sudden changes in volatility," Finance Research Letters, Elsevier, volume 43, issue C, DOI: 10.1016/j.frl.2021.102024.
• Baruník, Jozef & Čech, František, 2021, "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, volume 52, issue C, DOI: 10.1016/j.finmar.2020.100562.
• Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021, "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, volume 53, issue C, DOI: 10.1016/j.finmar.2020.100568.
• Covi, Giovanni & Gorpe, Mehmet Ziya & Kok, Christoffer, 2021, "CoMap: Mapping Contagion in the Euro Area Banking Sector," Journal of Financial Stability, Elsevier, volume 53, issue C, DOI: 10.1016/j.jfs.2020.100814.
• Baker, H. Kent & Kumar, Satish & Pandey, Nitesh, 2021, "Thirty years of the Global Finance Journal: A bibliometric analysis," Global Finance Journal, Elsevier, volume 47, issue C, DOI: 10.1016/j.gfj.2019.100492.
• Park, Jin Suk & Newaz, Mohammad Khaleq, 2021, "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, volume 50, issue C, DOI: 10.1016/j.gfj.2021.100673.
• McGuinness, Paul B., 2021, "Board member age, stock seasoning and the evolution of capital structure in Chinese firms," International Business Review, Elsevier, volume 30, issue 3, DOI: 10.1016/j.ibusrev.2020.101769.
• Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021, "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, volume 132, issue C, DOI: 10.1016/j.jinteco.2021.103512.