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Report NEP-MST-2022-09-26
This is the archive for NEP-MST, a report on new working papers in the area of Market Microstructure. Thanos Verousis issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-MST
The following items were announced in this report:
- Kang Gao & Perukrishnen Vytelingum & Stephen Weston & Wayne Luk & Ce Guo, 2022, "High-frequency financial market simulation and flash crash scenarios analysis: an agent-based modelling approach," Papers, arXiv.org, number 2208.13654, Aug.
- Yacine Aït-Sahalia & Jianqing Fan & Lirong Xue & Yifeng Zhou, 2022, "How and When are High-Frequency Stock Returns Predictable?," NBER Working Papers, National Bureau of Economic Research, Inc, number 30366, Aug.
- Taylan Kabbani & Ekrem Duman, 2022, "Deep Reinforcement Learning Approach for Trading Automation in The Stock Market," Papers, arXiv.org, number 2208.07165, Jul.
- Kang Gao & Perukrishnen Vytelingum & Stephen Weston & Wayne Luk & Ce Guo, 2022, "Understanding intra-day price formation process by agent-based financial market simulation: calibrating the extended chiarella model," Papers, arXiv.org, number 2208.14207, Aug.
- Ben Duan & Yutian Li & Dawei Lu & Yang Lu & Ran Zhang, 2022, "Pricing Stocks with Trading Volumes," Papers, arXiv.org, number 2208.12067, Aug, revised Oct 2022.