Over the past two decades, the Black Sea region has exhibited significantly growing wheat production and exports. In 2017/18, Russia ultimately became the world’s largest wheat exporter, a position that was held by the USA for decades. Mostly serving destination markets in the Middle East and...

According to portfolio theory, diversifying investment to several stocks with negative correlations may reduce portfolio risk. In contrast, combining stocks with similar movement (co-movement) has no impact on portfolio risk reduction. This study aims to examine state-owned enterprise stock...

The research in this paper is focused on the innovative range-based volatility models introduced in Alizadeh, Brandt, and Diebold (2002) (hereafter ABD). We develop new option pricing models using multi-factor diffusion approximations couched within this theoretical framework and examine their...

The volatility of equity returns for two beverages traded on the Nigerian stock exchange is the subject of this study. The ARCH effect test demonstrated that the two beverages disprove the claim that there is no ARCH effect. According to the preliminary analysis, both beverages were volatile....

The great majority of empirical studies have focused on asset markets in the US and other developed economies. The purpose of this research is to determine to what extent the findings of other researchers in relation to the characteristics of asset volatility in developed economies applies also...

In this study, we investigate a sequential procedure for the early detection of parameter changes in conditionally heteroscedastic time series models. We introduce the detectors based on the cumulative sum of score vectors and residuals for this procedure. The asymptotic properties of the...

Conditional heteroskedasticity of the error terms is a common occurrence in financial factor models, such as the CAPM and Fama-French factor models. This feature necessitates the use of heteroskedasticity consistent (HC) standard errors to make valid inference for regression coefficients. In...

Metaverses have been evolving following the popularity of blockchain technology. They build their own cryptocurrencies for transactions inside their platforms. These new cryptocurrencies are, however, still highly speculative, volatile, and risky, motivating us to manage their risk. In this...

Evidence that cryptocurrencies exhibit speculative bubble behavior is well documented. This evidence could trigger global financial instability leading to systemic risk. It is therefore crucial to quantify systemic risk and investigate its transmission mechanism across crypto markets and other...

The results of the research presented in the article regard the importance of publication of macroeconomic data from the United States for the short-term USD/PLN currency pair exchange rate volatility. The main purpose of the research was to indicate what macroeconomic data is important for the...

The development of technology and the globalization of financial markets have increased the volatility in financial markets and caused the emergence of risks and uncertainties that have not been previously encountered. Since traditional econometric models cannot fully explain this vol- atility,...

Purpose: This study focuses on forecasting the price of the most important export crops of vegetables and fruits in Egypt from 2016 to 2030. Design/methodology/approach: The study applied generalized autoregressive conditional heteroskedasticity (GARCH) model and autoregressive integrated moving...

The rapid growth of BRICS has increasingly integrated their markets into the global economy. Thus, making their financial markets more vulnerable to external shocks such as global economic policy uncertainties. In this light, this study examines BRICS stock markets’ response to global economic...

This study proposes a GARCH copula quantile regression model to capture the downside and upside tail dependence between oil price change and stock market returns at different risk levels. In the model, ten copulas are provided to measure the nonlinearity of the tail dependence with the marginal...

We propose a new clustering approach for comparing financial time series and employ it to study how the COVID-19 pandemic affected the U.S. stock market. Essentially, we compute the forecast accuracy of asymmetric GARCH models applied to S&P500 industries and use the model forecast errors for...

In this study, we document interesting properties of cryptoassets and empirically investigate the dynamic correlations between six major stablecoins and Bitcoin. It is evident that volatilities of Bitcoin and stablecoin returns exhibit asymmetric responses to good and bad news. We evaluate...

This article examines the asymmetric volatility spillover effects between Bitcoin and alternative coin markets at the disaggregate level. We apply a frequency connectedness approach to the daily data of 11 major cryptocurrencies for the period from 1 September 2017 to 2 March 2022. We try to...

This study aimed to investigate the interactions between Bitcoin to euro, gold, and STOXX50 during the period of COVID-19. First, a bibliometric analysis based on the R package was applied to highlight the research trends in the field during the period of the COVID-19 pandemic. While...

Purpose: Modelling security prices seem to be an ending debate in finance literature due to no clear consensus on behavioral patterns, Knowledge of stock price movement has always been an important source of information that is much needed in asset pricing and trading strategies, The aim of this...

This paper proposes a methodology for building Multivariate Time-Varying STCC-GARCH models. The novel contributions in this area are the specification tests related to the correlation component, the extension of the general model to allow for additional correlation regimes, and a detailed...

We provide a comparison of several GARCH and stochastic volatility models for forecasting the risk of cryptocurrencies. It turns out that the widely used GARCH(1,1) does not provide accurate risk predictions. In contrast, adding t-distributed innovations or allowing for regime changes improves...

The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from the main financial markets of developed and...

The future of e-money is crypocurrencies, it is the decentralize digital and virtual currency that is secured by cryptography. It has become increasingly popular in recent years attracting the attention of the individual, investor, media, academia and governments worldwide. This study aims to...

This study investigates the intraday realized volatility (RV) forecasting of gold futures in China. To predict the RV in the last half an hour before the day trading close (LH), we decompose the whole trading period into several intervals. RVs in day trading intervals can predict the RV in LH,...

This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia. It contributes to the existing literature by (i) revisiting this question for the principal stock markets in the Middle East and North Africa (MENA) region and (ii) using the...

Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability, and the development of the artificial intelligence industry. To provide investors with a more reliable reference in terms of artificial intelligence index investment,...

Measurement errors and structural breaks are important factors affecting the forecasting accurancy of volatility in the oil futures market. To capture these key points in one uniform forecasting model, we propose the MRS-HARQ-type model by simultaneously introducing the modification of...

Modelling the volatility (or kurtosis) of the implied volatility is an important aspect of financial markets when analysing market consensus and risk strategies. The purpose of this study is to evaluate the ability of symmetric and asymmetric GARCH systems to model the volatility of the FTSE 100...

Gold has also been a store of value and hedge against economic shocks for citizens and even nations for centuries. This paper explores the unpredictable nature of exchange rate volatility and if any relationship or influence exists, on the price of gold on the world market. Using GARCH models we...

This paper proposes a novel extension of log and exponential GARCH models, where time-varying parameters are approximated by orthogonal polynomial systems. These expansions enable us to add and study the effects of market-wide and external international shocks on the volatility forecasts and...

Events such as pandemic, changes in government policies and wars result in structural breaks in many areas including oil markets. RS GARCH MIDAS models, which consider both structural changes and macroeconomic factors affecting the oil prices have been studied by very few authors where they...

This study investigates tail dependence among five major cryptocurrencies, namely Bitcoin, Ethereum, Litecoin, Ripple, and Bitcoin Cash, and uncertainties in the gold, oil, and equity markets. Using the cross-quantilogram method and quantile connectedness approach, we identify cross-quantile...

We implement multivariate, self-exciting Peaks-over-Threshold (POT) methods to measure extremal losses in high-frequency return series of cryptocurrencies. For that purpose, we implement trivariate Hawkes-POT and the autoregressive conditional intensity ACI-POT models for Bitcoin, Ethereum, and...

We evaluate the importance of nonlinear and interactive effects in implied volatility innovation forecasting by comparing the performance of machine learning models that can search for interactive effects relative to classical ones that cannot, measuring the economic significance of these...

The outbreak of the Covid-19 pandemic has led to a slowdown in the world’s energy trade and changes in the use of energy resources. Meanwhile, global conditions are confused and can affect fossil energy spot markets, including crude oil, gasoline, heating oil, and natural gas. In this paper,...

Across the globe, COVID-19 has disrupted the financial markets, making them more volatile. Thus, this paper examines the market volatility and asymmetric behavior of Bitcoin, EUR, S&P 500 index, Gold, Crude Oil, and Sugar during the COVID-19 pandemic. We applied the GARCH (1, 1), GJR-GARCH (1,...

We investigate whether range-based estimators contain information in forecasting realized volatility within a HAR-RV-X framework and applied to G7 stock markets. Using a rolling window approach and QLIKE, HMSE and MCS forecast criteria, overall findings suggest that while no single model...