Half a century of measuring culture: Review of approaches,challenges, and limitations based on the analysis of 121 instruments for quantifying culture

After examining 121 instruments for measuring culture, we provide a historical overview and analyze how culture has been operationalized over the last half a century. Our study focuses on the topics of culture definition, dimensionality of culture models, collection and analysis of data for measuring culture, levels of culture measurement, issues of cross-cultural survey equivalence and the reliability and validity of culture measures. For each of these topics, we provide a review of existing approaches, discuss the challenges, and suggest best practices. Based on our analysis, we identify gaps in the field of culture measurement and offer directions for future research.     

Multivariate autoregressive extreme value process and its application for modeling the time series properties of the extreme daily asset prices

Abstract

In this article we suggest a new multivariate autoregressive process for modeling time-dependent extreme value distributed observations. The idea behind the approach is to transform the original observations to latent variables that are univariate normally distributed. Then the vector autoregressive DCC model is fitted to the multivariate latent process. The distributional properties of the suggested model are extensively studied. The process parameters are estimated by applying a two-stage estimation procedure. We derive a prediction interval for future values of the suggested process. The results are applied in an empirically study by modeling the behavior of extreme daily stock prices.     

Correction to: Comparison of joint control schemes for multivariate normal i.i.d. output

AStA Advances in Statistical Analysis - In the original paper, we incorrectly stated that...     

CUSUM control schemes for monitoring the covariance matrix of multivariate time series

Modified cumulative sum (CUSUM) control charts and CUSUM schemes for residuals are suggested to detect changes in the covariance matrix of multivariate time series. Several properties of these schemes are derived when the in-control process is a stationary Gaussian process. A Monte Carlo study reveals that the proposed approaches show similar or even better performance than the schemes based on the multivariate exponentially weighted moving average (MEWMA) recursion. We illustrate how the control procedures can be applied to monitor the covariance structure of developed stock market indices.     

Central limit theorems for functionals of large sample covariance matrix and mean vector in matrix‐variate location mixture of normal distributions

In this paper, we consider the asymptotic distributions of functionals of the sample covariance matrix and the sample mean vector obtained under the assumption that the matrix of observations has a matrix‐variate location mixture of normal distributions. The central limit theorem is derived for the product of the sample covariance matrix and the sample mean vector. Moreover, we consider the product of the inverse sample covariance matrix and the mean vector for which the central limit theorem is established as well. All results are obtained under the large‐dimensional asymptotic regime, where the dimension p and the sample size n approach infinity such that p/n→c ∈ [0, + ∞) when the sample covariance matrix does not need to be invertible and p/n→c ∈ [0,1) otherwise.     

Goodness-of-fit tests for centralized Wishart processes

Abstract

In this paper we present several goodness-of-fit tests for the centralized Wishart process, a popular matrix-variate time series model used to capture the stochastic properties of realized covariance matrices. The new test procedures are based on the extended Bartlett decomposition derived from the properties of the Wishart distribution and allows to obtain sets of independently and standard normally distributed random variables under the null hypothesis. Several tests for normality and independence are then applied to these variables in order to support or to reject the underlying assumption of a centralized Wishart process. In order to investigate the influence of estimated parameters on the suggested testing procedures in the finite-sample case, a simulation study is conducted. Finally, the new test methods are applied to real data consisting of realized covariance matrices computed for the returns on six assets traded on the New York Stock Exchange.     

Distinguishing Between Mastery and Domination: Response to Discussants

Therapeutic impasse, while often heralding the destruction of the analytical treatment process, may provide an unexpected opportunity for setting it back into motion. While not deliberately sought after, the impasse sets the stage for both patient and analyst to shift sufficiently to forge a more meaningful dialogue and connection. Pizer's discussion highlighted the analyst's struggle to keep his patient in mind while maintaining a working grasp on his capacity for reflective, analytical thought. Ringstrom's contributions offered the framework of improvisational drama, allowing a greater range of experimentation and play between patient and analyst, facilitating their collaborative creation of new ways of connecting, while exploring what is mutually safe and manageable. Harris's thoughts on phallic potency provided clinically valuable insights into the patient's undercurrent of conflict between desire and dread/hatred, in his strivings for master y and a meaningful connection. The discussants' contributions also allowed a deeper understanding of the analyst's own conflicts over mastery and the self-protective urge to retreat.     

Statistical inference procedure for the mean–variance efficient frontier with estimated parameters

We suggest finite sample tests for the location of the efficient frontier with the estimated parameters in mean–variance space. The exact densities of the test statistics are derived. We implement the introduced testing procedure empirically by considering monthly returns of ten developed stock markets. It is shown that ignoring the uncertainty about the estimated parameters leads to a more frequent reconstruction of the efficient frontier.