Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation

By Ender Demir, Giray Gozgor, Chi Keung Marco Lau, Samuel A. Vigne. Finance Research Letters, 2018

612 citations recorded by the source corpus.

This paper analyzes the prediction power of the economic policy uncertainty (EPU) index on the daily Bitcoin returns. Using the Bayesian Graphical Structural Vector Autoregressive model as well as the Ordinary Least Squares and the Quantile-on-Quantile Regression estimations, the paper finds that the EPU has a predictive power on Bitcoin returns. Fundamentally, Bitcoin returns are negatively associated with the EPU. However, the effect is positive and significant at both lower and higher quantiles of Bitcoin returns and the EPU. In the light of these findings, the paper concludes that Bitcoin can serve as a hedging tool against uncertainty.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/1f0da8b2c92610df60118e41768fff7f4cbc7b72

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Citations in the corpus

COVID-19 and oil market crash: Revisiting the safe haven property of gold and Bitcoin (2020, methodology): “We resort to the DCC-GARCH approach proposed by Engle (2002), which has received considerable attention in prior literature investigating the time-varying correlation structure among the financial markets (Bouri et al.”
Event study on the reaction of the developed and emerging stock markets to the 2019-nCoV outbreak (2020, neutral): “While Dimson (1979) advocates the aggregated coefficient method, Brown andWarner (1980& 1985) supports the market model for estimating the abnormal performance.”
Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin? (2019, background): “In times of economic unrest and weak trust, the appeal of Bitcoin among investors and practitioners increases, making Bitcoin to shine (Bouri et al., 2017b; Luther and Salter, 2017; Demir et al., 2018).”
A three-factor pricing model for cryptocurrencies (2020, background): “Also, studies have shown that external variables through Google Trends data (Urquhart, 2018), the number of tweets (Shen et al, 2019) and Economic Policy Uncertainty (Demir et al., 2018) all have predictive power in the Bitcoin market.”
Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting (2019, background): “, 2018b), global and Chinese economic policy uncertainty (Demir et al., 2018), and crude oil (Hayes, 2017).”
Connectedness of cryptocurrencies and prevailing uncertainties (2020, background): “Demir et al. (2018) show that Bitcoin’s return is negatively associated with Economic Policy Uncertainty (EPU).”
Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance (2018, positive): “Ding et al. (1993) show that autocorrelation of |rt| of a time series rt with δ close to 1 is larger and longer than other values for δ and thus indicate the behavior of long memory in volatility.”
Effects of the geopolitical risks on Bitcoin returns and volatility (2019, background): “(2017b) and Demir et al. (2018), which illustrate that the effects of risk and uncertainty indicators on Bitcoin return are negative in the baseline findings; however, Bitcoin should be considered for hedging against geopolitical risks in the bull-market conditions.”
The asymmetric effect of bitcoin on altcoins: evidence from the nonlinear autoregressive distributed lag (NARDL) model (2020, neutral): “2017; Poyser, 2019) and against uncertainty (Demir et al. 2018; Gozgor et al. 2019).”