Karl Pearson developed the correlation coefficient r(X,Y) in 1890s vastly underestimates dependence between two series …. Vinod(2014} develops new generalized correlation coefficients so that when r*(Y|X) > r*(X|Y) then X is the "kernel cause … latest rendering of the theory behind causal paths including theorems with proofs. The function 'causeSummBlk(.)' is …

noise model with correlation and volatility processes being constant over small intervals. The asymptotic equivalence of the …

distribution theory for a generalized multiscale estimator including a feasible central limit theorem with optimal convergence rate …

Karl Pearson developed the correlation coefficient r(X,Y) in 1890's. Vinod (2014) develops new generalized correlation …

We reformulate and decompose the Pearson and Spearman correlation coefficients into two components. We recommend the …-parallel line correlation, hidden, mixed, influenced, or weaker but significant relationships not recognized by standard …

average treatment effect of interest will typically fail. While the form of this measurement error varies across applications …, in many cases the measurement error structure is heterogeneous across different groups of observations. We develop a … novel measurement error correction procedure capable of addressing heterogeneous mismeasurement structures by leveraging …

Equity basket correlation is an important risk factor. It characterizes the strength of linear dependence between … propose several hedging schemes based on implied correlation (IC) forecasts. Modeling IC is a challenging task both in terms … of computational burden and estimation error. First the number of correlation coefficients to be estimated would grow …

covariance matrix eigenvalues, while for the Box-Cox dynamic correlation (BC-DC) specification the variances are transformed …

into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity …