This paper is inspired by medical studies in which the same patients with multiple sclerosis are examined at several successive visits (doctor's appointments) and described by fractional anisotropy tract profiles, which can be represented as f unctions. Since the observations for each patient...

Bessel's correction adjusts the denominator in the sample variance formula from n to n − 1 to produce an unbiased estimator for the population variance. This paper includes rigorous derivations, geometric interpretations, and visualizations. It then introduces the concept of "bariance," an...

This paper studies covariate adjusted estimation of the average treatment effect in stratified experiments. We work in a general framework that includes matched tuples designs, coarse stratification, and complete randomization as special cases. Regression adjustment with treatment‐covariate...

We investigate portfolio selection performance as in Markowitz by evaluating variance matrix estimation criteria in the currency market. This study challenges theoretically rigorous shrinkage covariance estimators using multiple evaluation metrics: systematic loss function, risk profile of...

This paper reviews the literature on firm wage differences and the fixed effects methods typically used to measure these differences. High wage firms tend to be more productive, larger, more sought after by workers, and to employ more credentialed and higher wage workers. The latest evidence...

Gaussian Structured Additive Regression provides a flexible framework for additive decomposition of the expected value with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity, and complex interactions between covariates of different types....

We examine two major topics in the field of cryptocurrencies. On the one hand, we investigate possible long-run equilibrium relationships among ten major cryptocurrencies by applying two different cointegration tests. This analysis aims at constructing cointegrated portfolios that enable...

This paper examines optimal portfolio selection using quantile-based risk measures such as Valueat-Risk (VaR) and Conditional Value-at-Risk (CVaR). We address the case of a singular covariance matrix of asset returns, which leads to an optimization problem with infinitely many solutions. An...

Modeling policy effects in the context of high-dimensional data requires a balanced consideration of omitted interaction bias and overfitting problems. This paper investigates the role of machine learning algorithms in stabilizing estimates and demonstrates the possible regularization bias...

This paper disentangles the added value of using high-frequency-based (realized) covariance measures on multivariate volatility forecasting into two pillars: the realized variances and realized correlations and quantifies the corresponding economic gains using a broad set of portfolio...

In diesem Beitrag werden Arbeitsanforderungen, Ressourcen und Gesundheit von Basisarbeitenden in den Dienstleistungssektoren Handel, Finanzwesen und öffentliche Dienstleistungen untersucht. Als Datengrundlage dient die aktuelle Erhebung der BIBB/BAuA-Erwerbstätigenbefragung 2018, eine...

In this study, we examine the nexus between oil tail risks and the realized variance of consumer prices in six advanced economies, namely, Canada, France, Germany, Japan, the United Kingdom, and the United States. Importantly, we estimate the oil tail risks following the Conditional...

The aim of this study is to analyze different forecasting approaches for the variance of future earnings, compare the respective forecast accuracy and test whether the forecasted information are relevant to equity or debt markets. The results, in line with former research, indicate that...

Covariates selection is essential when faced with many variables in modern causal inference in a data-rich environment. Particularly, the efficiency of the average causal effect (ACE) can be improved by including covariates only related to the outcome and reduced by including covariates related...

The main problem in pricing variance, volatility, and correlation swaps is how to determine the evolution of the stochastic processes for the underlying assets and their volatilities. Thus, sometimes it is simpler to consider pricing of swaps by so-called pseudo-statistics, namely, the...

This study examines the ways in which firms recover from stagnation or sales decline, with a focus on two key aspects: traditional high‑growth companies and growth restarts within the framework of organizational life cycle theory. Analyzing a dataset of 1883 Russian firms from 2013 to 2021,...

This study develops a flexible and efficient generalized ratio-product cum regression-type estimator of population variance utilizing auxiliary variable in two-phase sampling that incorporates the properties of ratio-type and product-type estimators. The properties of the estimator were derived...

Despite the popularity of factor models with simple loading matrices, little attention has been given to formally address the identifiability of these models beyond standard rotation-based identification such as the positive lower triangular (PLT) constraint. To fill this gap, we review the...

Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs. Certificates can be modeled using a bond component and a derivative component, typically an options strategy. The pricing of certificates is typically performed...

In this paper, we investigate the calibration of the smoothing parameter in an exponentially weighted moving average (EWMA) for realized covariance matrices. Although it is the crucial determinant in steering the dynamics of the EWMA, little attention is drawn on its calibration in many...

This paper will outline the functionality available in the CovRegpy package for actuarial practitioners, wealth managers, fund managers, and portfolio analysts written in Python 3.7. The major contributions of CovRegpy can be found in the CovRegpy_DCC.py, CovRegpy_IFF.py, CovRegpy_RCR.py,...