Portfolio Optimization Constrained by Performance Attribution

Yuan Hu, W. Brent Lindquist and Svetlozar T. Rachev
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Yuan Hu: Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA
W. Brent Lindquist: Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA
Svetlozar T. Rachev: Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA

JRFM, 2021, vol. 14, issue 5, 1-12

Abstract: This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize conditional value-at-risk and investigate two performance attributes, asset allocation (AA) and the selection effect (SE), as constraints on asset weights. The test portfolio consists of stocks from the Dow Jones Industrial Average index. Values for the performance attributes are established relative to two benchmarks, equi-weighted and price-weighted portfolios of the same stocks. Performance of the optimized portfolios is judged using comparisons of cumulative price and the risk-measures: maximum drawdown, Sharpe ratio, Sortino–Satchell ratio and Rachev ratio. The results suggest that achieving SE performance thresholds requires larger turnover values than that required for achieving comparable AA thresholds. The results also suggest a positive role in price and risk-measure performance for the imposition of constraints on AA and SE.

Keywords: portfolio optimization; performance attribution; asset allocation; selection effect (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
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