Adaptive Testing for Alphas in Conditional Factor Models with High Dimensional Assets

07/18/2023
by   Huifang Ma, et al.
0

This paper focuses on testing for the presence of alpha in time-varying factor pricing models, specifically when the number of securities N is larger than the time dimension of the return series T. We introduce a maximum-type test that performs well in scenarios where the alternative hypothesis is sparse. We establish the limit null distribution of the proposed maximum-type test statistic and demonstrate its asymptotic independence from the sum-type test statistics proposed by Ma et al.(2020).Additionally, we propose an adaptive test by combining the maximum-type test and sum-type test, and we show its advantages under various alternative hypotheses through simulation studies and two real data applications.

READ FULL TEXT
research
05/03/2022

Asymptotic Independence of the Sum and Maximum of Dependent Random Variables with Applications to High-Dimensional Tests

For a set of dependent random variables, without stationary or the stron...
research
05/02/2022

Computationally efficient and data-adaptive changepoint inference in high dimension

High-dimensional changepoint inference that adapts to various change pat...
research
04/13/2023

Adaptive Testing for Alphas in High-dimensional Factor Pricing Models

This paper proposes a new procedure to validate the multi-factor pricing...
research
03/19/2023

Spatial-sign based High Dimensional White Noises Test

A spatial-sign based test procedure is proposed for high dimensional whi...
research
02/04/2019

Directional differentiability for supremum-type functionals: statistical applications

We show that various functionals related to the supremum of a real funct...
research
05/02/2021

A simple consistent Bayes factor for testing the Kendall rank correlation coefficient

In this paper, we propose a simple and easy-to-implement Bayesian hypoth...
research
08/09/2021

Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference

This work is motivated by learning the individualized minimal clinically...

Please sign up or login with your details

Forgot password? Click here to reset