Bitcoin Returns and the Frequency of Daily Abnormal Returns

22 Pages Posted: 23 Jun 2020

See all articles by Guglielmo Maria Caporale

Guglielmo Maria Caporale

Brunel University London - Department of Economics and Finance; London South Bank University; CESifo (Center for Economic Studies and Ifo Institute); German Institute for Economic Research (DIW Berlin)

Oleksiy Plastun

Sumy State University

Viktor Oliinyk

Sumy State University

Date Written: May 25, 2020

Abstract

This paper investigates the relationship between Bitcoin returns and the frequency of daily abnormal returns over the period from June 2013 to February 2020 using a number of regression techniques and model specifications including standard OLS, weighted least squares (WLS), ARMA and ARMAX models, quantile regressions, Logit and Probit regressions, piecewise linear regressions and non-linear regressions. Both the in-sample and out-of-sample performance of the various models are compared by means of appropriate selection criteria and statistical tests. These suggest that on the whole the piecewise linear models are the best but in terms of forecasting accuracy they are outperformed by a model that combines the top five to produce “consensus” forecasts. The finding that there exist price patterns that can be exploited to predict future price movements and design profitable trading strategies is of interest both to academics (since it represents evidence against the EMH) and to practitioners (who can use this information for their investment decisions).

Keywords: cryptocurrency, Bitcoin, anomalies, abnormal returns, frequency of abnormal returns, regression analysis

JEL Classification: G12, G17, C63

Suggested Citation

Caporale, Guglielmo Maria and Plastun, Oleksiy and Oliinyk, Viktor, Bitcoin Returns and the Frequency of Daily Abnormal Returns (May 25, 2020). Available at SSRN: https://ssrn.com/abstract=3614279 or http://dx.doi.org/10.2139/ssrn.3614279

Guglielmo Maria Caporale

Brunel University London - Department of Economics and Finance ( email )

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HOME PAGE: http://www.brunel.ac.uk/about/acad/bbs/bbsstaff/ef_staff/guglielmocaporale/

London South Bank University ( email )

Centre for Monetary and Financial Economics
London
United Kingdom

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstraße 58
Berlin, 10117
Germany

Oleksiy Plastun (Contact Author)

Sumy State University ( email )

Rymskyi-Korsakov str., 2
Sumy, 40000
Ukraine

Viktor Oliinyk

Sumy State University ( email )

Rymskyi-Korsakov str., 2
Sumy, 40000
Ukraine

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