Report NEP-FMK-2023-07-31

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-FMK

The following items were announced in this report:

• Jiong Liu & M. Dashti Moghaddam & R. A. Serota, 2023. "Are there Dragon Kings in the Stock Market?," Papers 2307.03693, arXiv.org.
• Domonkos F. Vamossy, 2023. "Social Media Emotions and IPO Returns," Papers 2306.12602, arXiv.org, revised Apr 2024.
• Lee, David, 2023. "An Analytic Solution for Valuing Guaranteed Equity Securities," MPRA Paper 117775, University Library of Munich, Germany.
• Massimo Guidolin & Erwin Hansen & Gabriel Cabrera, 2023. "Time-Varying Risk Aversion and International Stock Returns," BAFFI CAREFIN Working Papers 23203, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Matthias Fleckenstein & Francis A. Longstaff, 2023. "Do Municipal Bond Investors Pay a Convenience Premium to Avoid Taxes?," NBER Working Papers 31389, National Bureau of Economic Research, Inc.
• Eugene W. Park, 2023. "Principal Component Analysis and Hidden Markov Model for Forecasting Stock Returns," Papers 2307.00459, arXiv.org.
• Yang Qiao & Yiping Xia & Xiang Li & Zheng Li & Yan Ge, 2023. "Higher-order Graph Attention Network for Stock Selection with Joint Analysis," Papers 2306.15526, arXiv.org.
• Marc Velay & Bich-Li^en Doan & Arpad Rimmel & Fabrice Popineau & Fabrice Daniel, 2023. "Benchmarking Robustness of Deep Reinforcement Learning approaches to Online Portfolio Management," Papers 2306.10950, arXiv.org.
• Mingxiao Song & Yunsong Liu & Agam Shah & Sudheer Chava, 2023. "Abnormal Trading Detection in the NFT Market," Papers 2306.04643, arXiv.org, revised Aug 2023.
• Joel Ong & Dorien Herremans, 2023. "Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning," Papers 2306.13661, arXiv.org.
• David Noel, 2023. "Stock Price Prediction using Dynamic Neural Networks," Papers 2306.12969, arXiv.org.
• Haohan Zhang & Fengrui Hua & Chengjin Xu & Hao Kong & Ruiting Zuo & Jian Guo, 2023. "Unveiling the Potential of Sentiment: Can Large Language Models Predict Chinese Stock Price Movements?," Papers 2306.14222, arXiv.org, revised May 2024.
• Abramov Alexander & Radygin Alexander & Chernova Maria, 2023. "Russian financial market in 2022," Published Papers ppaper-2023-1275, Gaidar Institute for Economic Policy, revised 2023.