Report NEP-FMK-2023-07-10

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:

• Barry Quinn, 2023. "Explaining AI in Finance: Past, Present, Prospects," Papers 2306.02773, arXiv.org.
• Taeisha Nundlall & Terence L Van Zyl, 2023. "Machine Learning for Socially Responsible Portfolio Optimisation," Papers 2305.12364, arXiv.org.
• Harsimrat Kaeley & Ye Qiao & Nader Bagherzadeh, 2023. "Support for Stock Trend Prediction Using Transformers and Sentiment Analysis," Papers 2305.14368, arXiv.org.
• Ben Moews, 2023. "On random number generators and practical market efficiency," Papers 2305.17419, arXiv.org, revised Jul 2023.
• Hong Guo & Jianwu Lin & Fanlin Huang, 2023. "Market Making with Deep Reinforcement Learning from Limit Order Books," Papers 2305.15821, arXiv.org.
• David Ardia & Keven Bluteau, 2023. "The Role of Twitter in Cryptocurrency Pump-and-Dumps," Papers 2306.02148, arXiv.org.
• Noam Ben-Ze'ev, 2023. "Drivers of Flows-Performance Sensitivity in Mutual Funds," Bank of Israel Working Papers 2023.06, Bank of Israel.
• Aadhitya A & Rajapriya R & Vineetha R S & Anurag M Bagde, 2023. "Predicting Stock Market Time-Series Data using CNN-LSTM Neural Network Model," Papers 2305.14378, arXiv.org.
• Yuze Lu & Hailong Zhang & Qiwen Guo, 2023. "Stock and market index prediction using Informer network," Papers 2305.14382, arXiv.org.
• KANAGUCHI Takehisa & KAWAKAMI Takehito & HASEBE Akira & OGAWA Yoshiya, 2023. "The Overview and Risks of Fund Finance," Bank of Japan Review Series 23-E-5, Bank of Japan.
• Reza Nematirad & Amin Ahmadisharaf & Ali Lashgari, 2023. "Forecasting the Performance of US Stock Market Indices During COVID-19: RF vs LSTM," Papers 2306.03620, arXiv.org.
• Jaydip Sen & Aditya Jaiswal & Anshuman Pathak & Atish Kumar Majee & Kushagra Kumar & Manas Kumar Sarkar & Soubhik Maji, 2023. "A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Market," Papers 2305.17523, arXiv.org.