Optimizing tracking error-constrained portfolios

2021

JEFAS

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Purpose Using a portfolio comprising liquid global stocks and bonds, this study aims to limit absolute risk to that of a standardised benchmark and determine whether this has a significant impact on expected return in both high volatility period (HV) and low volatility period (LV). Design/methodology/approach Using a traditional benchmark comprising 40% equity and 60% bonds, a constant tracking error (TE) frontier was constructed and implemented. Portfolio performance for different TE constraints and different economic periods (expansion and contraction) was explored. Findings Results indicate that during HV, replicating benchmark portfolio risk produces portfolios that outperform both the maximum return (MR) portfolio and the benchmark. MR portfolios outperform those with the same risk as that of the benchmark in LV. The MR portfolio weights assets to obtain the highest return on the TE frontier. During HV, the benchmark replicated risk portfolio obtained a higher absolute risk value than that of the MR portfolio because of an inefficient benchmark. In HV, the benchmark replicated risk portfolio favoured intermediate maturity treasury bills. Originality/value There is a dearth of literature exploring the performance of active portfolios subject to TE constraints. This work addresses this gap and demonstrates, for the first time, the relative portfolio performance of several standard portfolio choices on the frontier.

Section: Resultsmentioning

confidence: 93%

Section: Jefasmentioning

confidence: 99%

Portfolio performance under tracking error and benchmark volatility constraints

Hausner

2021

JEFAS

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“…The Ω -ratio -measured using as threshold the benchmark return -for each portfolio is then plotted on the same x-axis (risk) as the constant TE frontier (the solid black line in Figure 2 for TE = 6%). The unconstrained (universal) Ω -ratio, using the same threshold, is also shown in Figure 2, along with the efficient frontier and the capital market line (CML) for the constant TE frontier (Maxwell, Daly, Thomson, & Van Vuuren, 2018).…”

Section: Resultsmentioning

confidence: 99%

“…for the weights which generate the tangent portfolio (to the constant TE frontier) was shown byMaxwell, Daly, Thomson, and van Vuuren (2018) to involve solving for σ P using:…”

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confidence: 99%

Optimal omega-ratio portfolio performance constrained by tracking error

Gunning

Investment Management and Financial Innovations

2020

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The mean-variance framework coupled with the Sharpe ratio identifies optimal portfolios under the passive investment style. Optimal portfolio identification under active investment approaches, where performance is measured relative to a benchmark, is less well-known. Active portfolios subject to tracking error (TE) constraints lie on distorted elliptical frontiers in return/risk space. Identifying optimal active portfolios, however defined, have only recently begun to be explored. The Ω – ratio considers both down and upside portfolio potential. Recent work has established a technique to determine optimal Ω – ratio portfolios under the passive investment approach. The authors apply the identification of optimal Ω – ratio portfolios to the active arena (i.e., to portfolios constrained by a TE) and find that while passive managers should always invest in maximum Ω – ratio portfolios, active managers should first establish market conditions (which determine the sign of the main axis slope of the constant TE frontier). Maximum Sharpe ratio portfolios should be engaged when this slope is &gt; 0 and maximum Ω – ratios when &lt; 0.

“…Maximum Sharpe Ratio (MS): maximizing theSharpe ratio of TE-constrained portfolios generates maximally risk-adjusted portfolios, en-tirely analogous to similar portfolios on the efficient frontier(Maxwell, Daly, Thomson, & van Vuuren, 2018).…”

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confidence: 99%

Investment strategy performance under tracking error constraints

Evans

Investment Management and Financial Innovations

2019

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Recent (2018) evidence identifies the increased need for active managers to facilitate the exploitation of investment opportunities found in inefficient markets. Typically, active portfolios are subject to tracking error (TE) constraints. The risk-return relationship of such constrained portfolios is described by an ellipse in mean-variance space, known as the constant TE frontier. Although previous work assessed the performance of active portfolio strategies on the efficient frontier, this article uses several performance indicators to evaluate the outperformance of six active portfolio strategies over the benchmark – subject to various TE constraints – on the constant TE frontier.