Showing 1 - 10 of 52,598
This paper characterizes the impact of serial dependence on the non-asymptotic estimation error bound of penalized regressions (PRs). Focusing on the direct relationship between the degree of cross-correlation of covariates and the estimation error bound of PRs, we show that orthogonal or weakly...
Persistent link: https://www.econbiz.de/10013336165
We propose a jump robust positive semidefinite rank-based estimator for the daily covariance matrix based on high …-frequency intraday returns. It disentangles covariance estimation into variance and correlation components. This allows to estimate … covariance estimation and the jump robustness of the estimator are illustrated in a simulation study. In an application to the …
Persistent link: https://www.econbiz.de/10013115577
We estimate the daily integrated variance and covariance of stock returns using high-frequency data in the presence of … jumps, market microstructure noise and non-synchronous trading. For this we propose jump robust two time scale (co)variance …
Persistent link: https://www.econbiz.de/10012976316
The purpose of this paper is to introduce the Gerber statistic, a robust co-movement measure for covariance matrix … for estimating the covariance matrix of stock returns: the sample covariance matrix (also called the historical covariance … matrix) and shrinkage of the sample covariance matrix as formulated in Ledoit and Wolf (2004). Using a well …
Persistent link: https://www.econbiz.de/10013219149
This paper investigates whether the use of robust covariance improves portfolio performance and, in the presence of … uncertainty, whether the 1/N strategy is as good as you think. In addition to sample covariance, we use a battery of robust … covariance matrix. Our empirical evidence has two findings: First, the range of in-sample estimation horizon and out …
Persistent link: https://www.econbiz.de/10013035481
the relation between all the variables. The mean, quantile (including median) and mode re-gression estimators are proposed …
Persistent link: https://www.econbiz.de/10008622247
In this study we present a closed form solution to the moments and, in particular, correlation of two log-normally distributed random variables, when the underlying log-normal distribution is potentially truncated or censored at both tails. The closed form solution that we derive also covers the...
Persistent link: https://www.econbiz.de/10013075564
Propensity score based-estimators are commonly used to estimate causal effects in evaluation research. To reduce bias in observational studies researchers might be tempted to include many, perhaps correlated, covariates when estimating the propensity score model. Taking into account that the...
Persistent link: https://www.econbiz.de/10010479992
weights are all direct functions of the estimated covariance matrix. We perform a Monte Carlo study to assess the impact of … covariance matrix misspecification to these risk-based portfolios. Our results show that the equal-risk-contribution and inverse …-volatility weighted portfolio weights are relatively robust to covariance misspecification, but that the minimum-variance and maximum …
Persistent link: https://www.econbiz.de/10012971143
This paper presents how the most recent improvements made on covariance matrix estimation and model order selection can … Random Matrix Theory and robust covariance matrix estimation. The proposed procedure will be explained through synthetic data …
Persistent link: https://www.econbiz.de/10012918912