Long Memory Volatility and Bernoulli Jumps in Daily Crypto Currency Prices
DOI :10.23842/jif.2019.30.3.004
Publisher : Korea Insurance Research Institute
Research Area : Business Management
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This paper investigates the intrinsic time series properties of daily crypto currency prices, the long memory volatility and the jumps. For the purpose, this paper first adopts the simple FIGARCH model to analyze the long memory volatility process of the crypto currency prices and finds that there exists the long memory volatility in the daily returns. But, the jumps are found to be significant in the daily returns so that the simple FIGARCH model appears to be inadequate. Thus, this paper uses a normal mixture distribution which includes the Bernoulli jumps in the daily returns. In particular, the jumps appear to make the long memory volatility more significant in the daily returns. The results imply that using simple FIGARCH model without the jumps may yield the incorrect long memory volatility process of the crypto currencies and result in ineffective risk management and portfolio optimization in the markets. Thus, the FIGARCH model with allowing for the jump process could be more appropriate in the aspects of risk management and investment purpose forecasting the risk in such an investment as this market attracts increasing attractions from regulators and investors.
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[journal] Andersen, T. / 2002 / Micro effects of macro announcements: Real-time price discovery in foreign exchange / American Economic Reviews 93 : 38~62
[journal] Andersen, T. / 2006 / Volatility and correlation forecasting / Handbook of economic forecasting 1 : 777~878
[journal] Baek, C. / 2015 / Bitcoin as an investment or speculative vehicle? A first look / Applied Economic Letter 22 : 30~34
[journal] Baillie, R. / 1996 / Long memory processes and fractional integration in Econometrics / Journal of Econometrics 73 : 5~59
[journal] Baillie, R. / 1996 / Fractionally integrated generalized autoregressive conditional heteroskedasticity / Journal of Econometrics 74 : 3~30
[journal] Baillie, R. / 2001 / Testing Target Zone Models Using Efficient Methods of Moments / Journal of Business and Economic Statistics 19 : 273~277
[journal] Bariviera, A. / 2017 / The Inefficiency of Bitcoin Revisited: A Dynamic Approach / Economics Letters 161 : 1~4
[journal] Bariviera, A / 2017 / Some stylized facts of the Bitcoin market / Physica A: Statistical Mechanics and its Applications 484 : 82~90
[journal] Beine, M. / 2003 / Central bank interventions and jumps in double long memory models of daily exchange rates / Journal of Empirical Finance 10 : 641~660
[journal] Bollerslev, T. / 1992 / Quasi-maximum likelihood estimation of dynamic models with time varying covariances / Econometric Reviews 11 : 143~172
[report] Bouri, E. / 2016 / On the return-volatility relationship in the Bitcoin market around the price crash of 2013 / Kiel Institute for the World Economy
[journal] Breidt, F. / 1998 / The detection and estimation of long memory in stochastic volatility / Journal of Econometrics 83 : 325~348
[report] Caporale, G. / 2017 / Persistence in the cryptocurrency market / DIW
[report] Caporale, G. / 2017 / The day of the week effect in the crypto currency market / CESifo
[journal] Caporale, G. / 2019 / Modelling Volatility of Cryptocurrencies Using Markov-Switching GARCH Models / Research in International Business and Finance 48 : 143~155
[journal] Carrick, J. / 2016 / Bitcoin as a complement to emerging market currencies / Emerging Markets Finance and Trade 52 : 2321~2334
[report] Catania, L. / 2017 / Modelling crypto-currencies financial time-series / Department of Economics and Finance, University of Rome
[journal] Choi, K. / 2007 / Long memory and structural changes in the forward discount: An empirical investigation / Journal of International Money and Finance 26 : 342~363
[journal] Chou, J. / 2017 / GARCH modelling of cryptocurrencies / Journal of Risk and Financial Management 10 : 17~30
[journal] Corsi, F. / 2009 / A simple approximate long-memory model of realized volatility / Journal of Financial Econometrics 7 : 174~196
[journal] Diebold, F. / 1986 / Modelling the persistence of conditional variances: a comment / Econometric Reviews 5 : 51~56
[journal] Dwyer, G. / 2014 / The economics of Bitcoin and similar private digital currencies / Journal of Financial Stability 17 : 81~91
[web] ElBahrawy, A / 2017 / Evolutionary dynamics of the crypto currency market / https://arxiv.org/abs/1705.05334
[journal] Granger, C. / 1996 / Some properties of absolute returns: an alternative measure of Risk / Annales d'Economie et de Statistique 40 : 67~92
[journal] Granger, C. / 2004 / Occasional structural breaks and long memory with an application to the S&P500 absolute stock returns / Journal of Empirical Finance 11 : 399~421
[report] Gronwald, M / 2015 / The economics of Bitcoin- market characteristics and price jumps / CESifo
[journal] 한영욱 / 2007 / Poisson Jumps and Long Memory Volatility Process in High Frequency European Exchange Rates / Seoul Journal of Economics / 경제연구소 20 (2) : 201~222
[journal] 한영욱 / 2011 / Potential Sources of the Long Memory Property in the Volatility Process of Daily KRW-USD Exchange Rates : Jumps and Structural Breaks / 보험금융연구 / 보험연구원 22 (1) : 137~163
[thesis] Hotta, L. / 1988 / Outliers in GARCH process / University of Chicago
[journal] Jarque, C. / 1987 / Test for normality of observations and regression residuals / International Statistical Review 55 : 163~172
[journal] Koedijk, K. / 1990 / The tail index of exchange rate returns / Journal of International Economics 29 : 93~108
[journal] 권용재 / 2010 / Long Memory and Structural Breaks in Extreme Value Estimators - The Case of the U.S. Stock Indexes - / 보험금융연구 / 보험연구원 21 (1) : 187~237
[report] Mensi, W. / 2019 / Structural Breaks and Double Long Memory of Cryptocurrency Prices: A Comparative Analysis from Bitcoin and Ethereum
[journal] Nimalendran, M. / 1994 / Estimating the effects of information surprises and trading on stock returns using a mixed jump diffusion model / Review of Financial Studies 7 : 451~473
[journal] Press, J. / 1967 / A compound events model for security prices / Journal of Business 40 : 317~335
[report] Scaillet, O. / 2017 / High-frequency jump analysis of Bitcoin market / Swiss Finance Institute Research
[report] Shaw, C. / 2017 / Conditional heteroscedasticity in crypto-asset returns: a response to Chu et al. (2017) / Department of Economics, Mathematics and Statistics, Birkbeck College, University of London
[report] Starcia, C. / 2004 / Non-stationarities in stock returns / University of California San Diego
[journal] Vlaar, P. / 1993 / The message in weekly exchange rates in the European Monetary System: mean reversion, conditional heteroskedasticity and jumps / Journal of Business and Economic Statistics 11 : 351~360
[journal] Yonghong, J. / 2018 / Time-Varying Long-Term Memory in Bitcoin Market / Finance Research Letters 25 : 280~284
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