In this study, we explore the research published from 2009 to 2021 and summarize what
extant literature has contributed in the last decade to the analysis of volatility and risk …

This study is an integrated survey of GARCH methodologies applications on 67 empirical
papers that focus on cryptocurrencies. More sophisticated GARCH models are found to …

In recent years, investors, corporations, and enterprises have shown great interest in the
Bitcoin network; thus, promoting its products and services is crucial. This study utilizes an …

This study examines the dependence structure and estimates the Value at Risk (V a R) and
risk spillover between cryptocurrencies, oil, and Gold market data. In this paper, we estimate …

Abstract We forecast the Range Value at Risk (RVaR) of main cryptocurrencies using the
GARCH model with different error distributions. We compare the performance of the different …

Several procedures to forecast daily risk measures in cryptocurrency markets have been
recently implemented in the literature. Among them, long‐memory processes, procedures …

This paper introduces a semi-nonparametric approach for modeling Bitcoin risk relatively to
other parametric distributions and volatility models. Model performance is assessed through …

The cryptocurrency market offers significant investment opportunities but also entails higher
risks as compared to other asset classes. This article aims to analyse the financial risk …

In this paper, we compare the predictions on the market liquidity in crypto and fiat currencies
between two traditional time series methods, the autoregressive moving average (ARMA) …

We propose a neural networks method to estimate extreme Expected Shortfall, and even
more generally, extreme conditional tail moments as functions of confidence levels, in heavy …