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Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

机译:模拟比特币和LiteCoin的动态:GARCH与随机波动模型

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摘要

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.
机译:我们检查并比较了大量的广义自回归条件异源性(GARCH)和随机挥发性(SV)模型使用一系列比特币和LiteCoin价格返回,以评估这些加密货价返回系列的动态的型号。检查的各种型号包括标准GARCH(1,1)和SV,具有AR(1)对数波动过程,以及具有跳跃,平均值,杠杆效果,T分布式和移动平均创新的更灵活的模型。我们报告说,比特币的最佳型号是SV-T,而LiteCoin是GARCH-T。总的来说,T级模型比两个加密货币的其他类更好。对于比特币,SV型号始终优于GARCH模型,并且在大多数情况下,LiteCoin的相同保持真实。最后,使用GARCH-GJR模型的GARCH模型的比较揭示了杠杆效应对于加密货币不显着,这表明这些不像股票价格。

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