Report NEP-FMK-2020-10-26

This is the archive for NEP-FMK, a report on new working papers in the area of Financial Markets. Kwang Soo Cheong issued this report. It is usually issued weekly.

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Other reports in NEP-FMK

The following items were announced in this report:

• Zhifeng Liu & Toan Luu Duc Huynh & Peng-Fei Dai, 2020. "The impact of COVID-19 on the stock market crash risk in China," Papers 2009.08030, arXiv.org, revised Aug 2021.
• Steven J. Davis & Stephen Hansen & Cristhian Seminario-Amez, 2020. "Firm-Level Risk Exposures and Stock Returns in the Wake of Covid-19," CESifo Working Paper Series 8594, CESifo.
• Frederik P. Schlingemann & René M. Stulz, 2020. "Have Exchange-Listed Firms Become Less Important for the Economy?," NBER Working Papers 27942, National Bureau of Economic Research, Inc.
• Paul Glasserman & Kriste Krstovski & Paul Laliberte & Harry Mamaysky, 2020. "Choosing News Topics to Explain Stock Market Returns," Papers 2010.07289, arXiv.org.
• Junni L. Zhang & Wolfgang Karl Hardle & Cathy Y. Chen & Elisabeth Bommes, 2020. "Distillation of News Flow into Analysis of Stock Reactions," Papers 2009.10392, arXiv.org.
• Bruce Knuteson, 2020. "Strikingly Suspicious Overnight and Intraday Returns," Papers 2010.01727, arXiv.org.
• Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020. "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers 305661169, Lancaster University Management School, Economics Department.
• Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
• Thomas Dierckx & Jesse Davis & Wim Schoutens, 2020. "Using Machine Learning and Alternative Data to Predict Movements in Market Risk," Papers 2009.07947, arXiv.org.
• Qi Zhao, 2020. "A Deep Learning Framework for Predicting Digital Asset Price Movement from Trade-by-trade Data," Papers 2010.07404, arXiv.org.
• Artur Sokolovsky & Luca Arnaboldi, 2020. "A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components," Papers 2009.09993, arXiv.org, revised Jun 2022.
• Sidra Mehtab & Jaydip Sen & Abhishek Dutta, 2020. "Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models," Papers 2009.10819, arXiv.org.
• Xing Wang & Yijun Wang & Bin Weng & Aleksandr Vinel, 2020. "Stock2Vec: A Hybrid Deep Learning Framework for Stock Market Prediction with Representation Learning and Temporal Convolutional Network," Papers 2010.01197, arXiv.org.
• Cheng Peng & Young Shin Kim & Stefan Mittnik, 2020. "Portfolio Optimization on Multivariate Regime Switching GARCH Model with Normal Tempered Stable Innovation," Papers 2009.11367, arXiv.org, revised Feb 2023.
• Bampinas, Georgios & Panagiotidis, Theodore & Politsidis, Panagiotis, 2020. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," MPRA Paper 102846, University Library of Munich, Germany.
• neifar, malika, 2020. "Efficient Markets Hypothesis in Canada:‎ a comparative study between Islamic and Conventional stock markets ‎," MPRA Paper 103175, University Library of Munich, Germany.
• neifar, malika, 2020. "Efficiency-Market Hypothesis: case of Tunisian and 6 ‎Asian stock markets ‎," MPRA Paper 103232, University Library of Munich, Germany.
• Musaeva, Gulzhan & Masih, Mansur, 2018. "Granger-causal relationship between islamic stock markets and oil prices: a case study of Malaysia," MPRA Paper 102862, University Library of Munich, Germany.