The Hidden Predictive Power of Cryptocurrencies: Evidence from US Stock Market
Kazeem Isah () and
Ibrahim Raheem ()
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Ibrahim Raheem: School of Economics, University of Kent, Canterbury, UK
No 56, Working Papers from Centre for Econometric and Allied Research, University of Ibadan
This paper is motivated by the news that the surge in cryptocurrencies is an important candidate to in explaining the plummeting stock markets. To validate this believe, we construct a predictive model in which cryptocurrencies are identified as the predictors of US stock returns. The inherent statistical properties of cryptocurrencies such as persistence, endogeneity, and conditional heteroscedasticity are being accounted for in the Westerlund and Narayan (2015) estimator. Three salient results emanated from our estimations. First, we validated the importance of cryptocurrencies in predicting US stock prices; second, the cryptocurrencies predictive model outperforms the conventional time-series models such as Autoregressive Integrated Moving Average (ARIMA) model and the Autoregressive Fractionally Integrated Moving Average (ARFIMA); third, our results are robust to different method of forecast performance evaluation measures and different sub-sample periods. These results have important policy implications for the investors and policymakers.
Keywords: Stock Prices; Cryptocurrency; Digital Asset Prices; Predictive Model; Forecast Evaluation (search for similar items in EconPapers)
JEL-codes: C52 C53 G11 G14 G17 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-fmk, nep-for, nep-ore, nep-pay and nep-rmg
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