Printed from https://ideas.repec.org/n/nep-fmk/2019-07-22.html
Report NEP-FMK-2019-07-22
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:
- Birru, Justin & Gokkaya, Sinan & Liu, Xi & Stulz, Rene M., 2019, "Are Analyst Trade Ideas Valuable?," Working Paper Series, Ohio State University, Charles A. Dice Center for Research in Financial Economics, number 2019-15, Jul.
- Abhin Kakkad & Harsh Vasoya & Arnab K. Ray, 2019, "Regularities in stock markets," Papers, arXiv.org, number 1907.00371, Jun, revised Dec 2020.
- Carlo A. Favero & Alessandro Melone, 2019, "Asset Pricing vs Asset Expected Returning in Factor Models," Working Papers, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University, number 651.
- Ajit Mahata & Md Nurujjaman, 2019, "Time scales in stock markets," Papers, arXiv.org, number 1906.05494, Jun.
- Tim Leung & Brian Ward, 2019, "Tracking VIX with VIX Futures: Portfolio Construction and Performance," Papers, arXiv.org, number 1907.00293, Jun.
- Ajit Mahata & Debi Prasad Bal & Md Nurujjaman, 2019, "Identification of short-term and long-term time scales in stock markets and effect of structural break," Papers, arXiv.org, number 1907.03009, Jul.
- Efthymios Pavlidis & Konstantinos Vasilopoulos, 2019, "Speculative Bubbles in Segmented Markets," Working Papers, Lancaster University Management School, Economics Department, number 268640661.
- Xinyi Li & Yinchuan Li & Yuancheng Zhan & Xiao-Yang Liu, 2019, "Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation," Papers, arXiv.org, number 1907.01503, Jun.
- Filippo Curti & Marco Migueis & Rob T. Stewart, 2019, "Benchmarking Operational Risk Stress Testing Models," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2019-038, May, DOI: 10.17016/FEDS.2019.038.
- Matthias Feiler & Thibaut Ajdler, 2019, "Learning from Others in the Financial Market," Papers, arXiv.org, number 1906.03201, Jun, revised Aug 2019.
- Trong-Nghia Nguyen & Minh-Ngoc Tran & David Gunawan & R. Kohn, 2019, "A Statistical Recurrent Stochastic Volatility Model for Stock Markets," Papers, arXiv.org, number 1906.02884, Jun, revised Jan 2022.
- Pierre-Alain Reigneron & Vincent Nguyen & Stefano Ciliberti & Philip Seager & Jean-Philippe Bouchaud, 2019, "The Case for Long-Only Agnostic Allocation Portfolios," Papers, arXiv.org, number 1906.05187, Jun.
- Das, Mahamitra & Kundu, Srikanta & Sarkar, Nityananda, 2019, "Mean and Volatility Spillovers between REIT and Stocks Returns A STVAR-BTGARCH-M Model," MPRA Paper, University Library of Munich, Germany, number 94707, Jul.
- Wonse Kim & Junseok Lee & Kyungwon Kang, 2019, "The Effects of the Introduction of Bitcoin Futures on the Volatility of Bitcoin Returns," Papers, arXiv.org, number 1906.03430, Jun.
- Omar Masood & Manuela Tvaronavičienė & Kiran Javaria, 2019, "Impact of oil prices on stock return: evidence from G7 countries," Post-Print, HAL, number hal-02163013, Jun, DOI: 10.9770/ird.2019.1.2(4).
- A Itkin, 2019, "Deep learning calibration of option pricing models: some pitfalls and solutions," Papers, arXiv.org, number 1906.03507, Jun.
- Kenechukwu E. Anadu & James Bohn & Lina Lu & Matthew Pritsker & Andrei Zlate, 2019, "Reach for Yield by U.S. Public Pension Funds," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2019-048, Jun, DOI: 10.17016/FEDS.2019.049.