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Hidden Markov model for stock selection
Nguyen, Nguyet; Nguyen, Dung - In: Risks : open access journal 3 (2015) 4, pp. 455-473
of the S&P 500 stocks to identify which stock characteristics have been well rewarded during the time periods and assign … on the scores and weights of its features. Based on this algorithm, we choose the 50 top ranking stocks to buy. We …
Persistent link: https://www.econbiz.de/10011402656
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Is gold a hedge against stock price risk in U.S. or Indian markets?
Manuj, Hemant - In: Risks : open access journal 9 (2021) 10, pp. 1-15
We study whether gold acts as a hedge or a safe haven in U.S. and the Indian stock markets. These two stock markets have been chosen as representatives of the developed markets and the emerging markets, respectively, and are of significant interest to long-term investors. We apply a linear...
Persistent link: https://www.econbiz.de/10012632191
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Quantum computing approach to realistic esg-friendly stock portfolios
Catalano, Francesco; Nasello, Laura; Guterding, Daniel - In: Risks : open access journal 12 (2024) 4, pp. 1-20
a continuous fashion, as if stocks could be bought in fractional increments, practical implementations often resort to … approximations, as fractional stocks are typically not tradeable. While these approximations are effective for large investment … portfolio optimization with ESG (environmental, social, governance) ratings for EURO STOXX 50 index stocks. We introduce a …
Persistent link: https://www.econbiz.de/10014636503