Portfolio Optimization Under Tracking Error and Weights Constraints

Bajeux‐Besnainou, Isabelle; Belhaj, Riadh; Maillard, Didier; Portait, Roland

doi:10.2139/ssrn.963997

Cited by 7 publications

(9 citation statements)

References 18 publications

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“…By using market data, Ammann and Zimmermann (2001) found that imposing large tactical asset allocation ranges implied surprisingly small TEs. More recently, Bajeux-Besnainou et al (2011) considered portfolio performance under simultaneous TE and weight constraints compliance.…”

Section: Literature Reviewmentioning

confidence: 99%

Portfolio performance under tracking error and asset weight constraints

Daly

Vuuren

2020

Journal of Economic and Financial Sciences

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Research purpose: Determining the range of possible risk and returns attainable by such constrained portfolios is of interest to active portfolio managers. Weight restrictions reduce the range of achievable returns. This work demonstrates the magnitude of these reductions.Motivation for the study: This research installs and augments an approach that ascertains the effect on a TR (active) constrained portfolio in absolute risk-return space. The effects are displayed in risk-return space, demonstrating the impact on such constraints.Research approach/design and method: A theoretical approach to plot the constant TR frontier was used. Theoretical and quantitative analytical approaches to establish changes in the constant TR frontier on a simulated (but highly stylistic) market portfolios were also employed.Main findings: Considerable reduction is observed in possible investable portfolios, even for limited asset weight restrictions. This effect is amplified if multiple restrictions are imposed simultaneously, driven by both a reduced area in risk-return space enclosed by the constant TR frontier and changes in the frontier long-axis slope.Practical/managerial implications: The change in the long-axis slope sign is also a feature of changing economic conditions, thereby acting as an early warning signal with associated ramifications for asset managers. Contribution/value add:The combined effects on active portfolio performance of TR and asset weight constraints have not been investigated and demonstrated before.

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Section: Literature Reviewmentioning

confidence: 99%

Portfolio performance under tracking error and asset weight constraints

Daly

Vuuren

2020

Journal of Economic and Financial Sciences

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“…In the static framework, assuming that the zero-coupon bond maturity T is traded (there is a risk-free asset), the optimal static terminal wealth denoted W s T is given by W s T ¼ I T þ (M T À 1/B T (0)), where M T is a Static Markowitz tangent efficient portfolio (Roll 1992, Jorion 2003, Bajeux-Besnainou et al 2011)z and is a parameter associated with the risk tolerance of the investor. As noted by Roll (1992), since M T is efficient, W s T is efficient if and only if the benchmark I T is efficient.…”

Section: Proposition 31: Under Complete Marketsmentioning

confidence: 99%

Optimal portfolio allocations with tracking error volatility and stochastic hedging constraints

Bajeux‐Besnainou

Portait

Tergny

2013

Quantitative Finance

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The performance of mutual fund or pension fund managers is often evaluated by comparing the returns of managed portfolios with those of a benchmark. As most portfolio managers use dynamic rules for rebalancing their portfolios, we use a dynamic framework to study the optimization of the tracking error-return trade-off. Following these observations, we assume that the manager minimizes the tracking error under an expected return goal (or, equivalently, maximizes the information ratio). Moreover, we assume that he/she complies with a stochastic hedging constraint whereby the terminal value of the portfolio is (almost surely) higher than a given stochastic payoff. This general setting includes the case of a minimum wealth level at the horizon date and the case of a performance constraint on terminal wealth as measured by the benchmark (i.e. terminal portfolio wealth should be at least equal to a given proportion of the index). When the manager cares about absolute returns and relative returns as well, the risk-return trade-off acquires an extra dimension since risk comprises two components. This extra risk dimension substantially modifies the characteristics of portfolio strategies. The optimal solutions involve pricing and duplication of spread options. Optimal terminal wealth profiles are derived in a general setting, and optimal strategies are determined when security prices follow geometric Brownian motions and interest rates remain constant. A numerical example illustrates the type of strategies generated by the model.

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“…We call these constraints multiple weights constraints. When p = 1, it is a single weights constraint [10]. In the rest of paper, we only consider the cases of multiple equalities weights constraints.…”

Section: The Model and Its Solutionsmentioning

confidence: 99%

“…We call this type of restriction weights constraints of a portfolio. However, it is to be regretted that weights constraint rarely used in the current (robust) tracking error portfolio literature with the exception of only Bajeux-Besnainou et al (2007) [10] in which they first introduced this kind of constraint into a mean-variance index tracking portfolio model.…”

Section: Introductionmentioning

confidence: 99%

Tracking Error Portfolio Problem with WCPLM1 and Weights Constraints

Ling

2011

2011 International Conference on Computer and Management (CAMAN)

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Motivated by the topics of active portfolio management payed close attention by many researchers and the fact that there exists rare explicit approach in robust portfolio literature. We propose a robust expectation maximization active portfolio model subject to the worst-case 1-order lower partial moment risk and multiple weights constraints in this paper. We first explore the explicit solution of the proposed model. And then we compare the efficient frontier of the proposed model with the classical mean-variance tracking error model. Some new and interesting results are found in the comparisons.

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Portfolio Optimization Under Tracking Error and Weights Constraints

Cited by 7 publications

References 18 publications

Portfolio performance under tracking error and asset weight constraints

Portfolio performance under tracking error and asset weight constraints

Optimal portfolio allocations with tracking error volatility and stochastic hedging constraints

Tracking Error Portfolio Problem with WCPLM1 and Weights Constraints

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