Analysis of the bitcoin stock market indexes using comparative study of two
models SV with MCMC algorithm
#MMPMIDC7338123
Hachicha A
; Hachicha F
?-/-? 2021[]; 56
(2
): 647-73
PMIDC7338123
show ga
The purpose of this article is to find a better technique for estimating the
volatility of the price of bitcoin on the one hand and to check if this special
kind of asset called cryptocurrency behaves like other stock market indices. We
include five stock market indexes for different countries such as Standard and
Poor?s 500 composite Index (S&P), Nasdaq, Nikkei, Stoxx, and DowJones. Using
daily data over the period 2010?2019. We examine two asymmetric stochastic
volatility models used to describe the volatility dependencies found in most
financial returns. Two models are compared, the first is the autoregressive
stochastic volatility model with Student?s t-distribution (ARSV-t), and the
second is the basic SVOL. To estimate these models, our analysis is based on the
Markov Chain Monte-Carlo method. Therefore, the technique used is a
Metropolis?Hastings (Hastings in Biometrika 57:97?109, 1970), and the Gibbs
sampler (Casella and George in Am Stat 46:167?174, 1992; Gelfand and Smith in J
Am Stat Assoc 85:398?409, 1990; Gilks and Wild in 41:337?348, 1992). Model
comparisons illustrate that the ARSV-t model performs better performances. We
conclude that this model is better than the SVOL model on the MSE and AIC
function. This result concerns bitcoin as well as the other stock market indices.
Without forgetting that our finding proves the efficiency of Markov Chain for our
sample and the convergence and stability for all parameters to a certain level.
On the whole, it seems that permanent shocks have an effect on the volatility of
the price of the bitcoin and also on the other stock market. Our results will
help investors better diversify their portfolio by adding this cryptocurrency.
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