Modeling Mediterranean Stock Markets Volatility with Univariate and Multivariate Approaches

In our study we use the univariate and multivariate GARCH models to analyze the volatility behavior of the daily data of four Mediterranean stock markets (Morocco, Turkey, Spain, and France) spanning the period 2000-2020. We find a strong evidence of persisting of volatility in each of these markets. Results also indicate that both the univariate and the multivariate approaches capture well the ARCH and GARCH effects. We analyze the conditional covariances, and co-volatility spillovers between the Moroccan stock market and the three other Mediterranean stock markets. In order to study co-volatility spillovers, our work is built on the diagonal BEKK model especially the conditional covariances.

Univariate and Multivariate GARCH Models Applied to Bitcoin Futures Option Pricing

In this paper, the Heston–Nandi futures option pricing model is applied to Bitcoin futures options. The model prices are compared to market prices to give an indication of the pricing performance. In addition, a multivariate Bitcoin futures option pricing methodology based on a multivatiate GARCH model is developed. The empirical results show that a symmetric model is a better fit when applied to Bitcoin futures returns, and also produces more accurate option prices compared to market prices for two out of three expiry dates considered.

Hedging stock market prices with WTI, Gold, VIX and cryptocurrencies: a comparison between DCC, ADCC and GO-GARCH models

PurposeIn a first place, the present paper is designed to examine the dynamic correlations persistent between five cryptocurrencies, WTI, Gold, VIX and four stock markets (SP500, FTSE, NIKKEI and MSCIEM). In a second place, it investigates the relevant optimal hedging strategy.Design/methodology/approachEmpirically, the authors examine how WTI, Gold, VIX and five cryptocurrencies can be applicable to hedge the four stock markets. Three variants of multivariate GARCH models (DCC, ADCC and GO-GARCH) are implemented to estimate dynamic optimal hedge ratios.FindingsThe reached findings prove that both of the Bitcoin and Gold turn out to display remarkable hedging commodity features, while the other assets appear to demonstrate a rather noticeable disposition to act as diversifiers. Moreover, the results show that the VIX turns out to stand as the most effectively appropriate instrument, fit for hedging the stock market indices various related refits. Furthermore, the results prove that the hedging strategy instrument was indifferent for FTSE and NIKKEI stock while for the American and emerging markets, the hedging strategy was reversed from the pre-cryptocurrency crash to the during cryptocurrency crash period.Originality/valueThe first paper's empirical contribution lies in analyzing emerging cross-hedge ratios with financial assets and compare hedging effectiveness within the period of crash and the period before Bitcoin crash as well as the sensitivity of results to refits choose to compare between short term hedging strategy and long-term one.

Risk Spillover during the COVID-19 Global Pandemic and Portfolio Management

This paper aims to examine the volatility spillover, diversification benefits, and hedge ratios between U.S. stock markets and different financial variables and commodities during the pre-COVID-19 and COVID-19 crisis, using daily data and multivariate GARCH models. Our results indicate that the risk spillover has reached the highest level during the COVID-19 period, compared to the pre-COVID period, which means that the COVID-19 pandemic enforced the risk spillover between U.S. stock markets and the remains assets. We confirm the economic benefit of diversification in both tranquil and crisis periods (e.g., a negative dynamic conditional correlation between the VIX and SP500). Moreover, the hedging analysis exhibits that the Dow Jones Islamic has the highest hedging effectiveness either before or during the recent COVID19 crisis, offering better resistance to uncertainty caused by unpredictable turmoil such as the COVID19 outbreak. Our finding may have some implications for portfolio managers and investors to reduce their exposure to the risk in their portfolio construction.

Stock Markets of the Visegrad Countries after Their Accession to the European Union

In this chapter, interlinkages between stock markets in CEE-4 countries and capital markets in developed countries are analyzed. Changes of variance on stock markets in Poland, the Czech Republic, Slovakia, and Hungary are identified. Differences among countries are analyzed. Capital markets of these countries are compared in terms of market efficiency. Moreover, co-movements of stock markets in Visegrad countries with capital markets in developed countries are studied. Different specifications of multivariate GARCH models are studied. Asymmetric GARCH-BEKK model and Asymmetric Generalized Dynamic Conditional Correlation model are considered.

Bayesian Multivariate GARCH Models for Within-Person Variance Forecasting

We present a multivariate GARCH (MGARCH) model to forecast model averaged (co-)variances, correlations, and means in behavioral data for single individuals. We consider four MGARCH model parameterizations; three classic models (CCC, DCC, andBEKK) as well as a recently introduced model (pdBEKK) optimized for behavioral research. To obtain the averaged forecasts across the four models, we will first need to compute the model weights, obtained from a model stacking method. To do so, we need to approximate the expected log predictive density via a fully Bayesian leave-future-out cross validation technique. This approach has not been described so far in the literature. We provide an illustrative implementation using real data on two individuals from the longitudinal Intelligent Systems for Assessing Aging Change (ISAAC) study covering up to 4 years of daily measurements on individual computer use and walking speed. The individual participants show distinct patterns in the model weights, suggesting that individuals differ in the parameterizations that best capture their behavior. We generate weighted forecasts for up to 5 consecutive two-week periods for both individuals. These foreceast are compared to forecasts from the single best model. The resulting predictions are shown to be superior or at least equivalent to the forecasts from the single best model. We close with a discussion on limitations and an outlook. We provide an R package

Hedging the Brazilian stock index in the era of low interest rates: What has changed?

<p>In this paper we analyze the ability of different asset classes to hedge the Brazilian stock index in periods of high and low interest rates in the Brazilian economy, using two multivariate GARCH models. Our analysis includes two categories of assets: those traded in domestic currency and those traded in U.S. dollars. From the perspective of a local investor, we find that the exchange rate (R$/US$) and gold are the assets least correlated with equities. From the standpoint of a foreign investor, commodity index and fixed-income assets are the most useful. These results prevail in the low- and high-interest-rate periods. Moreover, in the period of low interest rates, the standard deviation of the estimated conditional correlation time series decreases, suggesting that in this period investors are more confident about macroeconomic policies.</p>