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Report NEP-FMK-2023-05-29
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:
- Li Rong Wang & Hsuan Fu & Xiuyi Fan, 2023, "Stock Price Predictability and the Business Cycle via Machine Learning," Papers, arXiv.org, number 2304.09937, Apr.
- Rangan Gupta & Jacobus Nel & Joshua Nielsen & Christian Pierdzioch, 2023, "Stock Market Volatility and Multi-Scale Positive and Negative Bubbles," Working Papers, University of Pretoria, Department of Economics, number 202310, May.
- Sebastian Doerr & Sebastian Egemen Eren & Semyon Malamud, 2023, "Money market funds and the pricing of near-money assets," BIS Working Papers, Bank for International Settlements, number 1096, May.
- Sungwoo Kang & Jong-Kook Kim, 2023, "Using a Deep Learning Model to Simulate Human Stock Trader's Methods of Chart Analysis," Papers, arXiv.org, number 2304.14870, Apr, revised Apr 2024.
- Michael Kopp, 2023, "The impact of the AI revolution on asset management," Papers, arXiv.org, number 2304.10212, Apr, revised Apr 2023.
- Aayush Shah & Mann Doshi & Meet Parekh & Nirmit Deliwala & Pramila M. Chawan, 2023, "Identifying Trades Using Technical Analysis and ML/DL Models," Papers, arXiv.org, number 2304.09936, Apr.
- Philippe Goulet Coulombe & Maximilian Gobel, 2023, "Maximally Machine-Learnable Portfolios," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 23-01, Apr, revised Apr 2023.