Correlations among the asset returns are the main reason for the computational and statistical complexities of the full multivariate GARCH models. We rely on the variancecorrelation separation strategy and introduce a broad class of multivariate models in the spirit of Engle’s (2002) dynamic conditional correlation models, that is univariate GARCH models are used for variances of individual ass...

Predictability of Asset Returns and the Efficient Market Hypothesis This paper is concerned with empirical and theoretical basis of the Efficient Market Hypothesis (EMH). The paper begins with an overview of the statistical properties of asset returns at different frequencies (daily, weekly and monthly), and considers the evidence on return predictability, risk aversion and market efficiency. T...

Let {X,Xk,i; i ≥ 1, k ≥ 1} be a double array of nondegenerate i.i.d. random variables and let {pn; n ≥ 1} be a sequence of positive integers such that n/pn is bounded away from 0 and ∞. This work is devoted to the solution to an open problem posed in Li, Liu, and Rosalsky (2010) on the asymptotic distribution of the largest entry Ln = max1≤i<j≤pn ∣∣ρ̂(n) i,j ∣∣ of the sample correlation matrix Γ...

We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction m...

Correlations among the asset returns are the main reason for the computational and statistical complexities of the full multivariate GARCH models. We rely on the variancecorrelation separation strategy and introduce a broad class of multivariate models in the spirit of Engle’s (2002) dynamic conditional correlation models, that is univariate GARCH models are used for variances of individual ass...

In this study, we first build two empirical cross-correlationmatrices in the US stockmarket by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the twomatriceswith the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock m...

In order to undertake controlled investigations into perceptual effects that relate to the interaural cross-correlation coefficient, experiment stimuli that meet a tight set of criteria are required. The requirements of each stimulus are that it is narrow band, normally has a constant cross-correlation coefficient over time, and can be altered to cover the full range of values of cross-correlat...

One of the features of a financial market, the stock market, in particular, is the market sentiment which is the overall attitude of investors toward a particular security or financial market. Investors always seek to create a portfolio with minimum risk while maintaining the expected return level. Therefore, perceiving the relationship between the stock returns and markets returns can be helpf...

If returns on two assets share common volatility components, the prices of options on the assets should be interdependent and the implied volatility spread should mean revert. We first demonstrate, using the canonical correlation method, that there is a common component among the volatilities of the returns on S&P 100 and S&P 500 indexes. We then exploit this commonality by trading on the volat...