Patterns in stock market movements tested as random number generators
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DOI: 10.1016/j.ejor.2012.11.057
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- Jozef Barunik & Tomas Krehlik & Lukas Vacha, 2012. "Modeling and forecasting exchange rate volatility in time-frequency domain," Papers 1204.1452, arXiv.org, revised Feb 2015.
- Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," FinMaP-Working Papers 55, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Ma, T. & Fraser-Mackenzie, P.A.F. & Sung, M. & Kansara, A.P. & Johnson, J.E.V., 2022. "Are the least successful traders those most likely to exit the market? A survival analysis contribution to the efficient market debate," European Journal of Operational Research, Elsevier, vol. 299(1), pages 330-345.
- Green, Lawrence & Sung, Ming-Chien & Ma, Tiejun & Johnson, Johnnie E. V., 2019. "To what extent can new web-based technology improve forecasts? Assessing the economic value of information derived from Virtual Globes and its rate of diffusion in a financial market," European Journal of Operational Research, Elsevier, vol. 278(1), pages 226-239.
- Michael A. Noakes & Kanshukan Rajaratnam, 2016. "Testing market efficiency on the Johannesburg Stock Exchange using the overlapping serial test," Annals of Operations Research, Springer, vol. 243(1), pages 273-300, August.
- Ben Moews, 2023. "On random number generators and practical market efficiency," Papers 2305.17419, arXiv.org, revised Jul 2023.
- Li-Chen Cheng & Yu-Hsiang Huang & Ming-Hua Hsieh & Mu-En Wu, 2021. "A Novel Trading Strategy Framework Based on Reinforcement Deep Learning for Financial Market Predictions," Mathematics, MDPI, vol. 9(23), pages 1-16, November.
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Keywords
Stock market time series; Financial data mining; Forecasting; Finance; Overlapping serial test;All these keywords.
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