This study investigates the volatility spillover dynamics between the VIX fear index and the Magnificent Seven technology stocks - namely Microsoft, Apple, Nvidia, Amazon, Alphabet, Meta Platforms, and Tesla - over the period of June 2012 to March 2024. To achieve this objective, the variance...

This study explores how the volatility spillover mechanism and dynamic dependence among the founding BRICS equity markets, namely IBOVESPA, MICEX, Nifty 50, SSE, and JSE, have evolved over time using a multivariate DCC-GARCH model. The analysis is conducted across three distinct regimes: the...

This study examines the role of volatility mean reversion in option pricing and evaluates the performance of commonly used volatility estimators within a broad market context. Using a comprehensive dataset of end-of-day option chains for the 100 most actively traded U.S. equities from 2018 to...

This paper examines the asymmetric impact of economic policy uncertainty (EPU) on exchange rate volatility across a sample of developed and emerging economies. Using an asymmetric GARCH-MIDAS model, volatility is decomposed into short-term and long-term components, with the latter associated...

This paper compares the daily return volatility by four leading international indices: JSE Top 40, FTSE 100, Nikkei 225 and S&P/ASX 200. The return series are modelled in ARMA process, where ARMA(1,3) values are taken for JSE Top 40 and S&P/ASX 200, ARMA(0,0) for FTSE 100, and ARMA(1,2) for...

This study examines the asymmetric responses of stock market indices in Türkiye and Kazakhstan to oil price shocks during the 2010-2025 period. Using the Nonlinear Autoregressive Distributed Lag (NARDL) model, the study decomposes the nonlinear effects of oil price fluctuations on financial...

This study examines dynamic interdependencies and risk transmission among major cryptocurrencies and traditional financial assets, including Bitcoin, Ethereum, U.S. equities, and gold, over the period 2017-2024. Particular attention is given to the structural shift associated with the 2024 U.S....

This paper evaluates an Adaptive LASSO-MGARCH model for multivariate volatility forecasting, with an application to green and conventional bonds, equities, energy commodities, and EU carbon allowances. By introducing coefficient-specific adaptive penalisation directly into the multivariate GARCH...

This research explores the application of extreme value theory in modelling and quantifying tail risks across different economic equity markets, with focus on the Nairobi Securities Exchange (NSE20), the South African Equity Market (FTSE/JSE Top40) and the US Equity Index (S&P500). The study...

We propose a robust semi-parametric framework for persistent time-varying extreme tail behavior, including extreme Value-at-Risk (VaR) and Expected Shortfall (ES). The framework builds on Extreme Value Theory and uses a conditional version of the Generalized Pareto Distribution (GPD) for...

Examining the economies of the European Union from 2000 to 2023, we have found no strong evidence that the inflation rate has a negative impact on economic growth. In contrast, in line with conventional economic theory, higher interest rates are associated with lower economic growth. The results...

European electricity markets are in the midst of unprecedented changes-caused by Russia's invasion of Ukraine and the rise of renewable sources of energy. Using high-frequency data, this paper investigates volatility spillovers across 24 countries in the European Union (EU) during the period...

In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data, taking the logarithm of the squared returns to obtain a linear state space model. A well-known series representation links the correlations between elements of the observation...

To address a key issue in functional time series analysis on testing the randomness of an observed series, we propose an IID test for functional time series by generalizing the Brock-Dechert-Scheinkman (BDS) test, which is commonly used for testing nonlinear independence. Similarly to the BDS...

In this paper, we carry out a comprehensive comparison of Gaussian generalized autoregressive conditional heteroskedasticity (GARCH) and autoregressive stochastic volatility (ARSV) models for volatility forecasting using the S&P 500 Index. In particular, we investigate their performance using...

The transition to a cleaner energy mix, essential for achieving net-zero greenhouse gas emissions by 2050, will significantly increase demand for metals critical to renewable energy technologies. Energy Transition Metals (ETMs), including copper, lithium, nickel, cobalt, and rare earth elements,...

Foreign exchange (FX) trading volume is a key factor in exchange rate volatility. Given the important role of volatility in economic growth and stability, this paper investigates the dynamic nature of exchange trading volume on exchange rate volatility using hourly high-frequency data. The...

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...