This paper examines long memory volatility in international stock markets. We show that long memory volatility is widespread in a panel dataset of eighty-two countries and that the degree of memory in the panel can be related to macroeconomic variables such as short- and long-run interest rates...

In this work we study a variant of the GARCH model when we consider the arrival of heterogeneous information in high-frequency data. This model is known as HARCH(n). We modify the HARCH(n) model when taking into consideration some market components that we consider important to the modeling...

In this paper, we modify Duan’s (1995) local risk-neutral valuation relationship (mLRNVR) for the GARCH option-pricing models. In our mLRNVR, the conditional variances under two measures are designed to be different and the variance process is more persistent in the risk-neutral measure than...

This paper focuses on three "safe haven" assets (gold, oil, and the Swiss Franc) and examines the impact of recent financial crises and some macroeconomic variables on their return co-movements during the last two decades. All financial crises produced significant increases in conditional...

Purpose The purpose of this paper is to examine the conditional correlations and spillovers of volatilities across CEE markets, namely, Hungary, Poland, the Czech Republic, Romania and Croatia, in the post-2007 financial crisis period. Design/methodology/approach The authors use five-dimensional...

An increase in the return of an asset in the financial markets may cause the returns of the remaining assets to fluctuate over time because of the arbitrage conditions. This may also create a spillover or contagion between the volatilities of the assets in the financial markets. This study aimed...

This paper aims at identifying a validated risk model for the cryptocurrency market. We propose a stochastic volatility model with co-jumps in return and volatility (SVCJ) to highlight the role of jumps in returns and volatility in affecting Value-at-Risk (VaR) and Expected Shortfall (ES) in...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying....

Volatility is one of the most important factors of investment decisions. Unexpected information forces the investor to trade abnormally in the market which in turn affects the volatility of the market. But this kind of trading behavior has a different impact on the different market segments....

This article investigates the exchange rate volatility spillover and dynamic conditional correlation between the euro and the South African rand following the Eurozone sovereign debt crisis. It employs two multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models,...

An accurate weather forecast is the basis for the valuation of weather derivatives, securities that partially compensate for financial losses to holders in case of, from their perspective, adverse outside temperature. The paper analyses precision of two forecast models of average daily...

Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did not perform well in large dimensions due to the...

This paper studies the volatility spillover between oil price and conventional and Islamic stock markets. We use a sample of five standard MSCI indexes and their Islamic counterparts from five countries from the Gulf region (Jordan, Kuwait, Oman, Qatar, UAE) and Brent crude oil price index,...

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV) of FTSE sampled at 5 min intervals taken...

This paper provides an exact algorithm for efficient computation of the time series of conditional variances, and hence the likelihood function, of models that have an ARCH(∞) representation. This class of models includes, e.g., the fractionally integrated generalized autoregressive...

In this paper, we employ 99% intraday value-at-risk (VaR) and intraday expected shortfall (ES) as risk metrics to assess the competency of the Multiplicative Component Generalised Autoregressive Heteroskedasticity (MC-GARCH) models based on the 1-min EUR/USD exchange rate returns. Five...

This study investigates the impact of commodity price volatility spillovers on financial sector stability. Specifically, the study investigates the spillover effects between oil and food price volatility and the volatility of a key macroeconomic indicator of importance to financial stability:...

This article explores the fitting of Autoregressive (AR) and Threshold AR (TAR) models with a non-Gaussian error structure. This is motivated by the problem of finding a possible probabilistic model for the realized volatility. A Gamma random error is proposed to cater for the non-negativity of...

We studied the dependence structure between West Texas Intermediate (WTI) oil prices and the exchange rates of BRICS1 countries, using copula models. We used the Normal, Plackett, rotated-Gumbel, and Student's t copulas to measure the constant dependence, and we captured the dynamic dependence...

The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia,...

This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and...

Volatility is an important component of asset pricing; an increase in volatility on markets can trigger changes in the risk distribution of financial assets. In conventional financial theory, investors are considered to be rational and any changes in relevant risk are assumed to be a result of...

A predictable pattern of stock market return is the violation of the efficient market hypothesis (EMH). It is well studied and evident in financial literature that stock markets around the world have predictable patterns, e.g. calendar effect, behavioural effect, and Religious festival effect....

Purpose - Actions of incumbent politicians and firms' managers during election years have been cited as sources of many problems that afflict economies and business entities. Given the controversies surrounding the impact of elections on firms' soundness, this paper poses a question of whether...

This paper compares volatility forecasts for the RTS Index (the main index for the Russian stock market) generated by alternative models, specifically option-implied volatility forecasts based on the Black-Scholes model, ARCH/GARCH-type model forecasts, and forecasts combining those two using a...

It is well-known that interest rates are extremely persistent, yet they are best modeled and understood as stationary processes. These properties are contradictory in the workhorse Gaussian affine term structure model in which persistent data often result in unit roots that imply...