Second moments of asset returns are important for risk management and portfolio selection. The problem of estimating second moments can be approached from two angles: time series and the cross-section. In time series, the key is to account for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH/GARCH family started by Engle (1982). In ...

This study examines investor sentiment which may trigger contagion in financial markets during the recent Covid-19 outbreak within a DCC-GARCH model. The results show that most of time-varying correlations have risen after until WHO declared disease as global pandemic and rise occurs each group countries/regions where least deaths took place. There is evidence cases. Overall, seems to give betw...

The cryptocurrency market has experienced stunning growth, with value exceeding USD 1.5 trillion. We use a DCC-MGARCH model to examine the return and volatility spillovers across three distinct classes of cryptocurrencies: coins, tokens, stablecoins. Our results demonstrate that conditional correlations are time-varying, peaking during COVID-19 pandemic sell-off March 2020, both ARCH GARCH effe...

Recently, the world of cryptocurrencies has experienced an undoubted increase in interest. Since first cryptocurrency appeared 2009 aftermath Great Recession, popularity digital currencies has, year by year, risen continuously. As February 2021, there are more than 8525 with a market value approximately USD 1676 billion. These particular assets can be used to diversify portfolio as well for spe...

This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly we...

We focus on the pairwise correlations of Japanese stock returns to study their correlation dynamics empirically. Two types of reduced size sample portfolios are created to observe the changes in conditional correlation: a set of individual stock portfolios created by using a network-based clustering algorithm and a single portfolio created from the mean return indexes of the individual sample p...

Forecasting Value-at-Risk (VaR) for financial portfolios is a staggering task in financial risk management. The turmoil in financial markets as observed since September 2008 called for more complex VaR models, as ”standard” VaR approaches failed to anticipate the collective market movements faced during the financial crisis. Hence, recent research on portfolio management mainly focussed on mode...

The extraordinary conditions in the financial world of late 2008 caused severe market dislocations and consequently many asset managers experienced significant portfolio losses, partly due to ineffective hedging techniques. In order to examine the effect of the credit crisis on investment strategies, we create a diverse set of long-short equity portfolios with domestic equity sectors and an arr...