In this paper, a local 𝑀-estimation for the conditional variance function in heteroscedastic regression models under stationary α-mixing dependent samples is developed. The local 𝑀-estimator is ...
The exponentially weighted moving average (EWMA) estimator is widely used to forecast the conditional volatility of short-horizon asset returns. The EWMA estimator is appropriate when returns are ...
description [NeurIPS 2025][Active Measurement] This paper proposes the Active Measurement framework, which uses AI model predictions as an importance sampling proposal distribution and achieves ...
ABSTRACT: In many applications a heterogeneous population consists of several subpopulations. When each subpopulation can be adequately modeled by a heteroscedastic single-index model, the whole ...
It leverages the conditional front-door adjustment (CFD), which theoretically gaurantees lower variance estimates than the commonly used standard backdoor adjustment (CFD) when the true treatment ...
There are several approaches to dealing with heteroscedasticity. If the error variance at different times is known, weighted regression is a good method. If, as is ...
In addition, you can consider the model with disturbances following an autoregressive process and with the GARCH errors. The AR(m)-GARCH(p,q) regression model is denoted Nelson and Cao (1992) proposed ...
This issue of the Journal of Risk contains four long papers dealing with market risk management. The first paper, “Risk estimation using the normal inverse Gaussian distribution”, by P. J. de Jongh ...
ABSTRACT: This study investigated the performance of eleven competing time series GARCH models for fitting the rate of returns data, monthly observations on the index returns series of the market over ...
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