Betas, Benchmarks and Beating the Market

The Journal of Trading 13(3) (2018) 44-66

36 Pages Posted: 5 Jun 2018 Last revised: 14 Jun 2019

See all articles by Zura Kakushadze

Zura Kakushadze

Quantigic Solutions LLC; Free University of Tbilisi

Willie Yu

Duke-NUS Medical School - Centre for Computational Biology

Date Written: May 30, 2018


We give an explicit formulaic algorithm and source code for building long-only benchmark portfolios and then using these benchmarks in long-only market outperformance strategies. The benchmarks (or the corresponding betas) do not involve any principal components, nor do they require iterations. Instead, we use a multifactor risk model (which utilizes multilevel industry classification or clustering) specifically tailored to long-only benchmark portfolios to compute their weights, which are explicitly positive in our construction.

Keywords: Market, Beta, Benchmark, Alpha, Trading, Portfolio, Stock, Equity, Optimization, Sharpe Ratio, Risk, Return, Expected, Factor, Loading, Specific, Idiosyncratic, Volatility, Variance, Covariance, Correlation, Matrix, Bound, Cost, Constraint, Regression, Weight, Source Code, Index, Investment, Long

JEL Classification: G00, G10, G11, G12, G23

Suggested Citation

Kakushadze, Zura and Yu, Willie, Betas, Benchmarks and Beating the Market (May 30, 2018). The Journal of Trading 13(3) (2018) 44-66, Available at SSRN: or

Zura Kakushadze (Contact Author)

Quantigic Solutions LLC ( email )

680 E Main St #543
Stamford, CT 06901
United States
6462210440 (Phone)
6467923264 (Fax)


Free University of Tbilisi ( email )

Business School and School of Physics
240, David Agmashenebeli Alley
Tbilisi, 0159

Willie Yu

Duke-NUS Medical School - Centre for Computational Biology ( email )

8 College Road
Singapore, 169857

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
PlumX Metrics