This study examines the use of Filtered Historical Simulation (FHS) to estimate tail risk in cryptocurrency markets for the optimization of robustness in this area under model misspecification. An ARMA-GARCH model is employed on the daily returns on Binance Coin and Litecoin in order to compare...

In a stage of more and more complex and high-frequency financial markets, the volatility analysis is a cornerstone of modern financial econometrics with practical applications in portfolio optimization, derivative pricing, and systematic risk assessment. This paper introduces a novel Bayesian...

Financial time-series data often exhibit statistically significant skewness and heavy tails, and numerous flexible distributions have been proposed to model them. In the context of the Log-linear Realized GARCH model with Skew-t (ST) distributions, our objective is to explore how the choice of...

The energy sector, as a major source of carbon emissions, has a significant impact on the operation of the carbon market and the management of carbon emissions. With the introduction of the "dual carbon" goals, the Chinese government has actively implemented measures to reduce carbon emissions,...

This paper proposes a mixed-frequency stochastic volatility model for intraday returns that captures fast and slow level shifts in the volatility level induced by news from both low-frequency variables and scheduled announcements. A MIDAS component describes slow-moving changes in volatility...

This study investigates the volatility of the Israeli corporate bond market, where corporate bonds are traded on a Limit Order Book (LOB) exchange with high retail trading activity. Using data from the Tel-Bond 20 and Tel-Bond 60 indices, we estimate various asymmetric GARCH models to capture...

This paper introduces a new hybrid model, HAR-RV-CARMA, which combines the Heterogeneous Autoregressive model for Realized Volatility (HAR-RV) with the Continuous Autoregressive Moving Average (CARMA) model. The key innovation of this study lies in the use of a Kalman filter-based dynamic state...

This study investigates the leverage effect and realized volatility (RV) of stocks in the presence of asymmetric jumps across economic expansions and contractions. We extend the heterogeneous autoregressive-realized volatility (HAR-RV) model by incorporating a two-period Markov regime-switching...

This study evaluates the predictive accuracy of traditional time series (TS) models versus machine learning (ML) methods in forecasting realized volatility across major cryptocurrencies-Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), and Ripple (XRP). Employing high-frequency data, we analyze...

This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses. We examine the contemporaneous relationships using correlation coefficient analysis,...

We develop a test for mean stationarity of latent volatility curves using high-frequency data. To derive the asymptotic test size and power, we establish a functional invariance principle for semimartingales under a strong mixing condition. The power properties are analyzed under alternatives...

We develop a data-driven procedure to identify which correlations in high-dimensional dynamic systems should be time-varying, constant, or zero. The method integrates a vine-based multivariate partial correlation model with sequential penalized estimation. Applied to 50 US equities and...

Examining the persistence of volatility transmission over an extended timeframe, regardless of specific events, reveals significant importance, as it uncovers the inherent fundamental and structural drivers that give rise to volatility. However, previous research in South Asia is minimal and has...

Noise traders' propensity to emotionally react to market fluctuations, news, rumours, or other non-fundamental factors influences the irrational investor's financial decisions. This ultimately impacts the stock market return and volatility. To measure the irrational traders' sentiments, the...

The South African exchange rate has been volatile in recent years affecting the competitiveness of commodities in the market. Consequently, South African agricultural exporters have faced lower profitability or entire losses. More South Africa is among the top agricultural exporters in Africa....

If intraday price data are unavailable, then using daily returns to construct realized measures of the variances of lower-frequency returns is a natural substitute for using high-frequency returns in this context. Notably, a suitable application of this approach yields realized measures that are...