Robust portfolio choice with derivative trading under stochastic volatility

Escobar, Marcos; Ferrando, Sebastian; Rubtsov, Alexey

doi:10.1016/j.jbankfin.2015.08.033

Cited by 61 publications

(49 citation statements)

References 42 publications

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“…Maenhout [24] provided the "homogeneous robustness", and Maenhout [23] presented a method to calculate detection-error probabilities. Later, Escobar et al [9] studied the robust optimal problem with derivatives under stochastic volatility. Yi et al [31] and Zheng et al [36] studied the optimal reinsuranceinvestment strategies with ambiguity-averse insurers under the Heston's SV model and the CEV model respectively.…”

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confidence: 99%

“…Notice that the alternative models in class Q only differ in the drift terms, as it should. Inserting (8) and (9) into (6), the wealth process can be rewritten as…”

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confidence: 99%

“…Assume that an AAM aims to seek an optimal strategy π (t) ∈ Γ, such that the variance of terminal wealth can be minimized under the worst-case alternative measure for a given expected level of wealth. Thus, inspired by Anderson et al [1] and Escobar et al [9], we modify the problem (7) as follows:…”

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confidence: 99%

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Robust optimal strategies of DC pension plans with stochastic volatility and stochastic income under mean-variance criteria

Chang¹,

Li²,

Zhao³

2022

JIMO

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This paper studies a robust optimal investment problem under the mean-variance criterion for a defined contribution (DC) pension plan with an ambiguity-averse member (AAM), who worries about model misspecification and aims to find robust optimal strategy. The member has access to a risk-free asset (i.e., cash or bank account) and a risky asset (i.e., the stock) in a financial market. In order to get closer to the actual environment, we assume that both the income level and stock price are driven by Heston's stochastic volatility model. A continuous-time mean-variance model with ambiguity aversion for a DC pension plan is established. By using the Lagrangian multiplier method and stochastic optimal control theory, the closed-form expressions for robust efficient strategy and efficient frontier are derived. In addition, some special cases are derived in detail. Finally, a numerical example is presented to illustrate the effects of model parameters on the robust efficient strategy and the efficient frontier, and some economic implications have been revealed.

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confidence: 99%

“…Notice that the alternative models in class Q only differ in the drift terms, as it should. Inserting (8) and (9) into (6), the wealth process can be rewritten as…”

mentioning

confidence: 99%

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Robust optimal strategies of DC pension plans with stochastic volatility and stochastic income under mean-variance criteria

Chang¹,

Li²,

Zhao³

2022

JIMO

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“…Such analysis sheds light on the benefits of learning more about the distribution of losses. The suboptimal analysis originates from the financial literature, see Liu and Pan (2003) for a pioneer use in portfolio optimization, and more recently Branger et al (2013) and Escobar et al (2015). The type of analysis and framework proposed here shed light on the financial implications of using suboptimal contracts, therefore helping the DM to better understand and measure the influence of its prior belief.…”

Section: Analyzing Suboptimality Of the Insurance Contractsmentioning

confidence: 99%

Optimal Insurance Contracts Under Distortion Risk Measures With Ambiguity Aversion

Jiang¹,

Escobar‐Anel

Ren

2020

ASTIN Bull.

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This paper presents analytical representations for an optimal insurance contract under distortion risk measure and in the presence of model uncertainty. We incorporate ambiguity aversion and distortion risk measure through the model of Robert and Therond [(2014) ASTIN Bulletin: The Journal of the IAA, 44(2), 277–302.] as per the framework of Klibanoff et al. [(2005) A smooth model of decision making under ambiguity. Econometrica, 73(6), 1849–1892.]. Explicit optimal insurance indemnity functions are derived when the decision maker (DM) applies Value-at-Risk as risk measure and is ambiguous about the loss distribution. Our results show that: (1) under model uncertainty, ambiguity aversion results in a distorted probability distribution over the set of possible models with a bias in favor of the model which yields a larger risk; (2) a more ambiguity-averse DM would demand more insurance coverage; (3) for a given budget, uncertainties about the loss distribution result in higher risk level for the DM.

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“…Finally, Escobar et al. ( 2015 ) and Bergen et al. ( 2018 ) studied ambiguity aversion in relation to stochastic volatility and stochastic covariance respectively.…”

Section: Introductionmentioning

confidence: 99%

Model uncertainty on commodity portfolios, the role of convenience yield

Chen

Escobar‐Anel

2021

Ann Finance

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This paper investigates the effect of model uncertainty on the performance of commodity-based portfolios. We consider a constant relative risk aversion (CRRA) utility maximizer investor in a complete market, with independent ambiguity-aversion levels for the three factors explaining the term structure of future prices, namely, spot prices, convenience yield (CY) and interest rates (IRs), as proposed in the seminal work of Schwartz (J Finance 52(3): 923–973, 1997). This generic investor is interested in the speculative component of the investment rather than possessing/consuming the physical commodity. We obtain closed-form solutions for optimal investments, optimal perturbations (alternative model) and value functions in line with the robust portfolio setting of Maenhout (Rev Financial Stud 17(4): 951–983, 2004). Our main focus is on the effect of convenience yield’s uncertainty on the optimal analysis. We estimate the model by applying a combination of maximum likelihood estimation (MLE) and Kalman Filter (KF) techniques, to two commodities: West Texas Intermediate (WTI) and copper future prices. The analysis demonstrates that uncertainty on the CY factor could be the largest contributor to the under-performance of a commodities portfolio, with wealth equivalent losses (WELs) in the ranges of 33% to 88% (WTI), and 7% to 31% (copper). Moreover, small variations, of up 25%, on CY’s covariance parameters could lead to a WEL of up to 40% (WTI, lesser volatility of CY).

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Robust portfolio choice with derivative trading under stochastic volatility

Cited by 61 publications

References 42 publications

Robust optimal strategies of DC pension plans with stochastic volatility and stochastic income under mean-variance criteria

Robust optimal strategies of DC pension plans with stochastic volatility and stochastic income under mean-variance criteria

Optimal Insurance Contracts Under Distortion Risk Measures With Ambiguity Aversion

Model uncertainty on commodity portfolios, the role of convenience yield

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