Exact Nonparametric Tests for a Random Walk with Unknown Drift under Conditional Heteroskedasticity

A Nonparametric Goodness-of-fit-based Test for Conditional Heteroskedasticity∗

In this paper we propose a nonparametric test for conditional heteroskedasticity based on a new measure of nonparametric goodness-of-fit (R2). In analogy with the ANOVA tools for classical linear regression models, the nonparametric R2 is obtained for the local polynomial regression of the residuals from a parametric regression on some covariates. It is close to 0 under the null hypothesis of c...

Testing for Reduction to Random Walk in Autoregressive Conditional Heteroskedasticity Models

RANDOM WALKS WITH DRIFT - A SEQUENTIAL APPROACH (Revision 07/04)

In this paper sequential monitoring schemes to detect nonparametric drifts are studied for the random walk case. The procedure is based on a kernel smoother. As a by-product we obtain the asymptotics of the Nadaraya-Watson estimator and its associated sequential partial sum process under non-standard sampling. The asymptotic behavior differs substantially from the stationary situation, if there...

Random Walks with Drift - a Sequential Approach

In this paper sequential monitoring schemes to detect nonparametric drifts are studied for the random walk case. The procedure is based on a kernel smoother. As a by-product we obtain the asymptotics of the Nadaraya-Watson estimator and its associated sequential partial sum process under non-standard sampling. The asymptotic behavior differs substantially from the stationary situation, if there...

The Random-Walk Hypothesis on the Indian Stock Market

This study tests the random walk hypothesis for the Indian stock market. Using 19 years of monthly data on six indices from the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE), this study applies three different unit root tests with two structural breaks to analyse the random walk hypothesis. We find that unit root tests that allow for two structural breaks alone are not able ...