Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning 2020
DOI: 10.1142/9789811202391_0055
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A Time-Series Bootstrapping Simulation Method to Distinguish Sell-Side Analysts’ Skill from Luck

Abstract: This is a repository copy of A time-series bootstrapping simulation method to distinguish sell-side analysts' skill from luck.

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“… In contrast, Su et al (2019) develop a rolling window‐based time‐series bootstrap simulation method, producing simulated results for the up/downgrade portfolio including all stocks recommended by Top 5 BHs in a total of 4,420 one‐year rolling windows over the whole sample period January 1995 to June 2013 (see, also., Su & Zhang, 2020). The objective of the time‐series bootstrap simulations is to test whether Top 5 BHs are able to generate superior recommendation performance in certain time periods. …”
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confidence: 99%
“… In contrast, Su et al (2019) develop a rolling window‐based time‐series bootstrap simulation method, producing simulated results for the up/downgrade portfolio including all stocks recommended by Top 5 BHs in a total of 4,420 one‐year rolling windows over the whole sample period January 1995 to June 2013 (see, also., Su & Zhang, 2020). The objective of the time‐series bootstrap simulations is to test whether Top 5 BHs are able to generate superior recommendation performance in certain time periods. …”
mentioning
confidence: 99%