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Academic Research Spotlight: Replicating Anomalies by Lu Zhang, Chen Xue and Kewei Hou

Academic Research Spotlight: Replicating Anomalies by Lu Zhang, Chen Xue and Kewei Hou

FromExcess Returns


Academic Research Spotlight: Replicating Anomalies by Lu Zhang, Chen Xue and Kewei Hou

FromExcess Returns

ratings:
Length:
20 minutes
Released:
Feb 28, 2021
Format:
Podcast episode

Description

In this episode, we are trying something new. There is so much academic research out there about markets, and what drives their returns over time, that it can be very difficult for investors to keep up with all of it. So we are going to start highlighting some of our favorite academic papers each month and breaking down their key lessons. 
We start with paper Replicating Anomalies by Lu Zhang, Chen Xue and Kewei Hou. In this paper, the authors examined 452 stock market anomalies to see how they held up once the impact of micro-cap stocks was reduced. We summarize the findings from the paper and what they mean for investors. 
We hope you enjoy the discussion. 
DIRECT LINK TO REPLICATING ANOMALIES PAPER
Replicating Anomalies by Kewei Hou, Chen Xue, Lu Zhang :: SSRN
ABOUT THE PODCAST
Excess Returns is an investing podcast hosted by Jack Forehand (@practicalquant) and Justin Carbonneau (@jjcarbonneau), partners at Validea. Justin and Jack discuss a wide range of investing topics including factor investing, value investing, momentum investing, multi-factor investing, trend following, market valuation and more with the goal of helping those who watch and listen become better long term investors.
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Released:
Feb 28, 2021
Format:
Podcast episode

Titles in the series (100)

Excess Returns is an investing podcast hosted by Jack Forehand and Justin Carbonneau, partners at Validea. Justin and Jack discuss a wide range of investing topics, including factor investing, value investing, momentum investing and behavioral finance, with the goal of helping those who watch and listen become better long term investors, all in twenty minutes or less per episode.