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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. Erik Schlogl 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, arXiv.org, number 2307.03693, Jul.
- Domonkos F. Vamossy, 2023, "Social Media Emotions and IPO Returns," Papers, arXiv.org, number 2306.12602, Jun, revised Apr 2024.
- Lee, David, 2023, "An Analytic Solution for Valuing Guaranteed Equity Securities," MPRA Paper, University Library of Munich, Germany, number 117775, Jun.
- Massimo Guidolin & Erwin Hansen & Gabriel Cabrera, 2023, "Time-Varying Risk Aversion and International Stock Returns," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 23203.
- Matthias Fleckenstein & Francis A. Longstaff, 2023, "Do Municipal Bond Investors Pay a Convenience Premium to Avoid Taxes?," NBER Working Papers, National Bureau of Economic Research, Inc, number 31389, Jun.
- Eugene W. Park, 2023, "Principal Component Analysis and Hidden Markov Model for Forecasting Stock Returns," Papers, arXiv.org, number 2307.00459, Jul.
- Yang Qiao & Yiping Xia & Xiang Li & Zheng Li & Yan Ge, 2023, "Higher-order Graph Attention Network for Stock Selection with Joint Analysis," Papers, arXiv.org, number 2306.15526, Jun.
- 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, arXiv.org, number 2306.10950, Jun.
- Mingxiao Song & Yunsong Liu & Agam Shah & Sudheer Chava, 2023, "Abnormal Trading Detection in the NFT Market," Papers, arXiv.org, number 2306.04643, May, revised Aug 2023.
- Joel Ong & Dorien Herremans, 2023, "Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning," Papers, arXiv.org, number 2306.13661, Jun.
- David Noel, 2023, "Stock Price Prediction using Dynamic Neural Networks," Papers, arXiv.org, number 2306.12969, Jun.
- 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, arXiv.org, number 2306.14222, Jun, revised May 2024.
- Abramov Alexander & Radygin Alexander & Chernova Maria, 2023, "Russian financial market in 2022," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2023-1275, revised 2023.