We analyse the dynamic behavior of conditional volatility in commodity markets using a novel, manually collected dataset of daily price ranges over a time span of more than 140 years, which allows more precise daily volatility estimates than are otherwise prevalent in the commodity literature....

The results of Lettau and Ludvigson (2001) show that Cay-LL has a significant predictive power both in the in-sample and the out-of-sample forecast of excess return. Our study departs from Lettau and Ludvigson (2001) in adding and comparing other two estimates of cay namely cay-OLS and cay-DLS...

In this paper new semiparametric GARCH models with long memory are introduced. The estimation of the nonparametric scale function is carried out by an adapted version of the SEMIFAR algorithm (Beran et al., 2002). Recurring on the revised recommendations by the Basel Committee to measure market...

We propose a score-driven extension to the well-known dynamic conditional correlation (DCC) model. The p-range DCC model provides means to capture the time-varying influence from news on correlation dynamics. The recursion to update the news parameter over time is based on the observations of...

The paper develops a tail risk forecasting model that incorporates the wealth of economic and financial information available to risk managers. The approach can be viewed as a regularized extension of the two-stage GARCH-EVT model of McNeil and Frey (2000) where we permit a time-varying...

We propose a new class of conditional heteroskedasticity in the volatility (CH-V) models which allows for time-varying volatility of volatility in the volatility of asset returns. This class nests a variety of GARCH-type models and the SHARV model of Ding (2021b). CH-V models can be seen as a...

We study the asymptotic normality of two estimators of the integrated volatility of volatility based on the Fourier methodology, which does not require the pre-estimation of the spot volatility.We show that the bias-corrected estimator reaches the optimal rate 1/4, while the estimator without...

This paper introduces a novel quantile approach to harness the high-frequency information and improve the daily conditional quantile estimation. Specifically, we model the conditional standard deviation as a realized GARCH model and employ conditional standard deviation, realized volatility,...

The aim of this study is to examine the daily return spillover among 18 cryptocurrencies under low and high volatility regimes, while considering three pricing factors and the effect of the COVID-19 outbreak. To do so, we apply a Markov regime-switching (MS) vector autoregressive with exogenous...