The predictive power of Bitcoin prices for the realized volatility of US stock sector returns

Elie Bouri (), Afees Salisu and Rangan Gupta
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Elie Bouri: Lebanese American University

Financial Innovation, 2023, vol. 9, issue 1, 1-22

Abstract: Abstract This paper is motivated by Bitcoin’s rapid ascension into mainstream finance and recent evidence of a strong relationship between Bitcoin and US stock markets. It is also motivated by a lack of empirical studies on whether Bitcoin prices contain useful information for the volatility of US stock returns, particularly at the sectoral level of data. We specifically assess Bitcoin prices’ ability to predict the volatility of US composite and sectoral stock indices using both in-sample and out-of-sample analyses over multiple forecast horizons, based on daily data from November 22, 2017, to December, 30, 2021. The findings show that Bitcoin prices have significant predictive power for US stock volatility, with an inverse relationship between Bitcoin prices and stock sector volatility. Regardless of the stock sectors or number of forecast horizons, the model that includes Bitcoin prices consistently outperforms the benchmark historical average model. These findings are independent of the volatility measure used. Using Bitcoin prices as a predictor yields higher economic gains. These findings emphasize the importance and utility of tracking Bitcoin prices when forecasting the volatility of US stock sectors, which is important for practitioners and policymakers.

Keywords: Bitcoin prices; S&P 500 index; US sectoral indices; Realized volatility prediction; Economic gains (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (9)

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DOI: 10.1186/s40854-023-00464-8

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