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Bootstrap tests for multivariate event studies
Pin Huang Chou
Department of Finance
Research output
:
Contribution to journal
›
Article
›
peer-review
21
Scopus citations
Overview
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Dive into the research topics of 'Bootstrap tests for multivariate event studies'. Together they form a unique fingerprint.
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Mathematics
Asymptotics
100%
Monte Carlo
100%
Test Statistic
100%
Bootstrap Method
100%
Sampling Distribution
100%
Nominal Significance Level
100%
Distributional Assumption
100%
Statistical Test
100%
Keyphrases
Bootstrap Test
100%
Daily Returns
100%
Sampling Distribution
50%
Statistical Test
50%
Stock Returns
50%
Monte Carlo Experiment
50%
Test Statistic
50%
Bootstrap Method
50%
Better Approximation
50%
Distributional Hypothesis
50%
Experiment-based
50%
Multivariate Normality
50%
Rejection Rate
50%
Computer Science
Approximation (Algorithm)
100%
Sampling Distribution
100%
Significance Level
100%
Bootstrap Method
100%
Economics, Econometrics and Finance
Event Study
100%
Capital Market Returns
33%