Report NEP-FMK-2021-01-25

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:

• Ruiqiang Song & Min Shu & Wei Zhu, 2021. "The 2020 Global Stock Market Crash: Endogenous or Exogenous?," Papers 2101.00327, arXiv.org.
• Tinic, Murat & Sensoy, Ahmet & Demir, Muge & Nguyen, Duc Khuong, 2020. "Broker Network Connectivity and the Cross-Section of Expected Stock Returns," MPRA Paper 104719, University Library of Munich, Germany.
• Nina Boyarchenko & Richard K. Crump & Anna Kovner & Or Shachar, 2021. "Corporate Bond Market Distress," Staff Reports 957, Federal Reserve Bank of New York.
• Yvo Mudde & Anna Samarina & Robert Vermeulen, 2021. "Spillover effects of sovereign bond purchases in the euro area," Working Papers 706, DNB.
• Alexis Marchal, 2020. "Risk & returns around FOMC press conferences: a novel perspective from computer vision," Papers 2012.06573, arXiv.org, revised Jan 2021.
• Paweł Sakowski & Anna Turovtseva, 2020. "Verification of Investment Opportunities on the Cryptocurrency Market within the Markowitz Framework," Working Papers 2020-41, Faculty of Economic Sciences, University of Warsaw.
• Kentaro Imajo & Kentaro Minami & Katsuya Ito & Kei Nakagawa, 2020. "Deep Portfolio Optimization via Distributional Prediction of Residual Factors," Papers 2012.07245, arXiv.org.
• Xavier Warin, 2021. "Deep learning for efficient frontier calculation in finance," Papers 2101.02044, arXiv.org, revised Feb 2022.
• Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
• Le Trung Hieu, 2020. "Deep Reinforcement Learning for Stock Portfolio Optimization," Papers 2012.06325, arXiv.org.