Asset Allocation Strategies, Data Snooping, and the 1/N Rule

43 Pages Posted: 23 Dec 2016 Last revised: 6 Oct 2018

See all articles by Po-Hsuan Hsu

Po-Hsuan Hsu

National Tsing Hua University - Department of Quantitative Finance

Han heng

Hefei University of Technology

Wu sheng

Hefei University of Technology

Zhiguang Cao

Shanghai University of Finance and Economics

Date Written: December 23, 2016

Abstract

Using a series of advanced tests from White’s (2000) “Reality Check” to correct for data-snooping bias, we assess the out-of-sample performance of various portfolio strategies relative to the naive 1/N rule. When we analyze 16 basic portfolio strategies, 126 learning strategies, and nearly 2,000 extended strategies, we find that some strategies outperform the 1/N rule in conventional tests that do not account for data-snooping bias. However, after we use the new tests that control for such bias, we find that none or very few of these strategies outperform the 1/N rule. Thus, our finding underscores the necessity to control for data-snooping bias when making asset allocation decisions.

Keywords: Portfolio strategies, Data snooping, Reality Check, Predictability

JEL Classification: G11, G14

Suggested Citation

Hsu, Po-Hsuan and heng, Han and Wensheng, Wu and Cao, Zhiguang, Asset Allocation Strategies, Data Snooping, and the 1/N Rule (December 23, 2016). Available at SSRN: https://ssrn.com/abstract=2889279 or http://dx.doi.org/10.2139/ssrn.2889279

Po-Hsuan Hsu

National Tsing Hua University - Department of Quantitative Finance ( email )

101, Section 2, Kuang-Fu Road
Hsinchu, Taiwan 300
China

Han Heng

Hefei University of Technology ( email )

193 Tunxi Rd
Baohe
Hefei, Anhui
China

Wu Wensheng (Contact Author)

Hefei University of Technology ( email )

193 Tunxi Rd
Baohe
Hefei, Anhui
China

Zhiguang Cao

Shanghai University of Finance and Economics ( email )

Shanghai, AK Shanghai
China

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