The extraordinary growth of short volatility strategies creates risks that may trigger the next serious market crash. A low yield, low volatility environment has drawn various market participants into essentially similar short volatility-contingent strategies with a common non-linear risk...

Stock and oil relationship is usually time-varying and depends on the current economic conditions. In this study, we propose a new Dynamic Stochastic Mixed data frequency sampling (DSM) copula model, that decomposes the stock-oil relationship into a short-run dynamic stochastic component and a...

The importance of modelling correlation has long been recognised in the field of portfolio management with large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of...

Forecasts of asset return volatility are necessary for many financial applications, including portfolio allocation. Traditionally, the parameters of econometric models used to generate volatility forecasts are estimated in a statistical setting and subsequently used in an economic setting such...

The importance of covariance modelling has long been recognised in the field of portfolio management and large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating whether simpler...

Within the context of volatility timing and portfolio selection this paper considers how best to estimate a volatility model. Two issues are dealt with, namely the frequency of data used to construct volatility estimates, and the loss function used to estimate the parameters of a volatility...

This paper investigates how best to forecast optimal portfolio weights in the context of a volatility timing strategy. It measures the economic value of a number of methods for forming optimal portfolios on the basis of realized volatility. These include the traditional econometric approach of...

Recent advances in the measurement of volatility have utilized high frequency intraday data to produce what are generally known as realised volatility estimates. It has been shown that forecasts generated from such estimates are of positive economic value in the context of portfolio allocation....

This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns. We study trading quantitatives such as returns, traded volumes, volatility periodicity, and provide summary statistics of return correlations to CRIX (CRyptocurrency IndeX), as well...

The real estate investment trust (REIT) industry experienced a liquidity crisis resulting from reduced access to credit commitments as banks were restoring their balance sheets during the 2007-2009 financial crisis. Employing generalized autoregressive conditional heteroscedasticity (GARCH)...