Smart Beta and Statistical Significance

The Journal of Wealth Management 22 (2), 30-36

12 Pages Posted: 25 Feb 2020

See all articles by Paskalis Glabadanidis

Paskalis Glabadanidis

University of Adelaide Business School; Financial Research Network (FIRN)

Date Written: December 14, 2018


I propose an alternative weighting mechanism for equity mandates based on the statistical significance of the factor loading on the benchmark. Specifically, the weight of each security entering the active portfolio is directly proportional to the t-statistic of the factor loading ($\beta$) with the benchmark. I show that this amounts to overweighting securities with high correlations with the benchmark and vice versa. The t-statistic of market beta within a single-factor model is a monotonic transformation of its correlation with the benchmark. I test the out-of-sample performance of this alternative weighing scheme with industry portfolios as well as individual US stocks. I find that this strategy has higher correlations with the benchmark compared to other popular alternatives, has lower tracking error, unitary exposure to the benchmark, very good Sharpe ratios and substantial ex-post realized returns relative to the underlying benchmark.

Keywords: smart beta, statistical significance, alternative indexation

JEL Classification: G11, G10

Suggested Citation

Glabadanidis, Paskalis, Smart Beta and Statistical Significance (December 14, 2018). The Journal of Wealth Management 22 (2), 30-36, Available at SSRN:

Paskalis Glabadanidis (Contact Author)

University of Adelaide Business School ( email )

10 Pulteney Street
Adelaide, South Australia 5005

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane

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