Mean-Variance Portfolio Rebalancing with Transaction Costs

Dybvig, Philip H.

doi:10.2139/ssrn.3373329

Cited by 11 publications

(3 citation statements)

References 39 publications

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“…Brauneis and Mestel [20] applied Markowitz' mean-variance framework to evaluate the return risk of cryptocurrency portfolios. Dybvig and Pezzo [21]studied the mean-variance portfolio rebalancing problem of transaction costs. Pandolfo et al [22] used the concept of a weighted Lp depth function to obtain a robust estimate of the mean and covariance matrix of asset returns, which has the advantage of not being affected by parameter assumptions.…”

Section: Return-risk Modelmentioning

confidence: 99%

Portfolio optimization model with uncertain returns based on prospect theory

Zhou

Tan

2021

Complex Intell. Syst.

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When investing in new stocks, it is difficult to predict returns and risks in a general way without the support of historical data. Therefore, a portfolio optimization model with an uncertain rate of return is proposed. On this basis, prospect theory is used for reference, and then the uncertain return portfolio optimization model is established from the perspective of expected utility maximization. An improved gray wolf optimization (GWO) algorithm is designed because of the complex nonsmooth and nonconcave characteristics of the model. The results show that the GWO algorithm is superior to the traditional particle swarm optimization algorithm and genetic algorithm.

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Section: Return-risk Modelmentioning

confidence: 99%

Portfolio optimization model with uncertain returns based on prospect theory

Zhou

Tan

2021

Complex Intell. Syst.

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“…The complementarity constraint (18) and the nonnegative constraint (20) prevent the possibility of simultaneous sales and purchases. Practically, concurrently selling and buying is seen as not optimal because making the allocation to one asset or security decreases and increases at the same time, thus being subjected to unnecessary transaction costs (Dybvig 2005). Constraint (19) helps to alleviate the estimation risk problem in the mean estimate (DeMiguel et al 2009).…”

Section: Regularized Mean-variance-evar Modelmentioning

confidence: 99%

Scaled and Stable Mean-Variance-Evar Portfolio Selection Strategy With Proportional Transaction Costs

Mills

2017

Journal of Business Economics and Management

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This paper studies a portfolio optimization problem with variance and Entropic Value-at-Risk (evar) as risk measures. As the variance measures the deviation around the expected return, the introduction of evar in the mean-variance framework helps to control the downside risk of portfolio returns. This study utilized the squared l2-norm to alleviate estimation risk problems arising from the mean estimate of random returns. To adequately represent the variance-evar risk measure of the resulting portfolio, this study pursues rescaling by the capital accessible after payment of transaction costs. The results of this paper extend the classical Markowitz model to the case of proportional transaction costs and enhance the efficiency of portfolio selection by alleviating estimation risk and controlling the downside risk of portfolio returns. The model seeks to meet the requirements of regulators and fund managers as it represents a balance between short tails and variance. The practical implications of the findings of this study are that the model when applied, will increase the amount of capital for investment, lower transaction cost and minimize risk associated with the deviation around the expected return at the expense of a small additional risk in short tails.

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“…With the same objective functional, Mei et al (2016) investigates a general form of transaction costs. In a single-period setting, a recent study Dybvig and Pezzo (2020) shows how to improve on traditional symmetric futures overlay strategies, which is inspirational to the dynamic setting.…”

Section: Classical Portfolio Selection: Modern Portfolio Theorymentioning

confidence: 99%

Dynamically optimal portfolio selection with frictions and portfolio constraints

Ye¹

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costs and initial wealth allocations. Our numerical example shows that the initial wealth allocation between the risk-free and risky assets affects the efficient frontier and the efficient frontier is distorted by the transaction costs. Moreover, the buying and selling rates have different impacts on the efficient frontier for different regions. We also examine how the width of the no-transaction region varies with different transaction cost rates.Second, we study the behavioural portfolio optimization. Beyond the meanvariance portfolio theory, prospect theory has been proposed as a descriptive model of economic behaviour under risk. We formulate the S-shaped utility maximization model under prospect theory and consider multi-period behavioural portfolio selection problem in a cone-constrained market. We consider the following two cases: (1) the case with one risky asset and no shorting constraint; and (2) the case with multiple elliptically distributed risky assets and cone constraints. We derive semi-closed form solutions of the optimal investment policy for both cases. Numerically, we illustrate the properties of the optimal policy by depicting the corresponding S-shaped utility curves, from which we investigate how the constraints in the market affect the investor's behaviour.Finally, the thesis is concluded, together with the discussion on promising future research directions. AcknowledgementFinally, thank my parents for their unconditional love and support. I could not get through the tough time and complete the thesis without them, especially during the coronavirus pandemic. This thesis is dedicated to my family. I am glad I made this decision to start this candidature. Definitely, I have grown to become a better version of myself in more ways than one.

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Mean-Variance Portfolio Rebalancing with Transaction Costs

Cited by 11 publications

References 39 publications

Portfolio optimization model with uncertain returns based on prospect theory

Portfolio optimization model with uncertain returns based on prospect theory

Scaled and Stable Mean-Variance-Evar Portfolio Selection Strategy With Proportional Transaction Costs

Dynamically optimal portfolio selection with frictions and portfolio constraints

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