We are introducing the Unit Invariant Knee (UIK) point as an objective estimator for using elbow criterion in multivariate data analysis and especially in PCA, FA, AA and CA. Our computation is based on Extremum Distance Estimator (EDE) which is used for inflection and knee point identification....

We propose a new multivariate model to capture the presence of jumps in mean and conditional variance in the returns of oil prices and companies in this sector. The model is based on the presence of common factors associated with jumps in mean and variance, as it performs a decomposition of the...

In this paper, we propose a model based on multivariate decomposition of multiplicative—absolute values and signs—components of several returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional...

Asset prices exhibit characteristics that significantly deviate from log-normality and display time-varying stochastics. There is ample evidence of jumps in one asset price or market leading to jumps in other assets' prices or markets. We propose a multivariate jump diffusion model with...

Half-lives are summary measures of persistence, and are usually characterized from impulse response functions (IRFs) of univariate time series models. Two issues which occur with half-life characterization in multivariate time series are IRFs become conditional on specific shocks and are often...

Objective - Trade credit is the most important source of external finance for many companies. It appears on every balance sheet and represents more than 50 percent of company's short-term liabilities and a third of all company's total liabilities in OECD countries. Late payment of invoices may...

In this paper, we consider Sarmanov's multivariate discrete distribution as counting distribution in two multivariate compound models: the First model assumes different types of independent claim sizes (corresponding to, e.g., different types of insurance policies), while in the second model, we...

This paper considers smooth principle component analysis for high dimensional data with very large dimensional observations p and moderate number of individuals N. Our setting is similar to traditional PCA, but we assume the factors are smooth and design a new approach to estimate them. By...