Report NEP-FMK-2023-07-24
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:
- Marco Di Maggio & Francesco Franzoni & Shimon Kogan & Ran Xing, 2023. "Avoiding Idiosyncratic Volatility: Flow Sensitivity to Individual Stock Returns," NBER Working Papers 31360, National Bureau of Economic Research, Inc.
- Alex Kim & Maximilian Muhn & Valeri Nikolaev, 2023. "Bloated Disclosures: Can ChatGPT Help Investors Process Information?," Papers 2306.10224, arXiv.org, revised Feb 2024.
- Ian Berk & Massimo Guidolin & Monia Magnani, 2023. "Strong vs. Stable: The Impact of ESG Ratings Momentum and their Volatility on the Cost of Equity Capital," BAFFI CAREFIN Working Papers 23202, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
- Cassidy K. Buhler & Hande Y. Benson, 2023. "Efficient Solution of Portfolio Optimization Problems via Dimension Reduction and Sparsification," Papers 2306.12639, arXiv.org.
- Sander Lammers & Massimo Giuliodori & Robert Schmitz & Adam Elbourne, 2023. "Bank Funding, SME lending and Risk Taking," CPB Discussion Paper 447, CPB Netherlands Bureau for Economic Policy Analysis.
- Guglielmo Maria Caporale & Kyriacos Kyriacou & Nicola Spagnolo, 2023. "Aggregate Insider Trading and Stock Market Volatility in the UK," CESifo Working Paper Series 10511, CESifo.
- Karol Chojnacki & Robert Ćlepaczuk, 2023. "This study compares well-known tools of technical analysis (Moving Average Crossover MAC) with Machine Learning based strategies (LSTM and XGBoost) and Ensembled Machine Learning Strategies (LSTM ense," Working Papers 2023-15, Faculty of Economic Sciences, University of Warsaw.