This study attempts analyse the different indices of ‘Bombay Stock Exchange' (BSE) of India, in terms of risk return characteristics and their relatedness and predictibility to address the relavite neglect of past studies. Further it investigates the volatility impact of different sub indices...

In this paper, we used the GARCH (1,1) and GARCH-M (1,1) models to investigate volatility and persistence at daily frequency for European and US financial markets. In the study we included fourteen stock indices (twelve Europeans and two Americans), during March 2013 - January 2017. The results...

The purpose of this paper is to investigate the volatility spillovers between the returns on crude oil futures and oil company stocks using alternative multivariate GARCH models, namely the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), and VARMA-AGARCH model of...

We propose a new approach to model high and low frequency components of equity correlations. Our framework combines a factor asset pricing structure with other specifications capturing dynamic properties of volatilities and covariances between a single common factor and idiosyncratic returns....

Using a CCAPM-based risk-adjustment model, we perform yearly valuations of a large sample of stocks listed on NYSE, AMEX and NASDAQ over a thirty-year period. The model differs from standard valuation models in the sense that it adjusts forecasted residual income for risk in the numerator rather...

Examinations of the dynamics of daily returns and volatility in stock markets of the US, Hong Kong and mainland China (Shanghai and Shenzhen) over 2 January 2001 to 8 February 2013 suggest: (1) evidence of unidirectional return spillovers from the US to the other three markets; but no spillover...

A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted to the VIX price history from 1990 to 2022. Using a growing window of training data, the price of the S&P500 is predicted and two trading algorithms are presented, based on the...

This paper investigates whether augmenting models with the variance risk premium (VRP) and Google search data improves the quality of the forecasts for real oil prices. We considered a time sample of monthly data from 2007 to 2019 that includes several episodes of high volatility in the oil...

This study investigates the cross-country impact of U.S. equity market skewness risk. We find that a large decrease in the U.S. market skewness significantly predicts high future returns on international equity markets. The predictability remains significant after controlling for a set of U.S....