The costs of suboptimal dynamic asset allocation: General results and applications to interest rate risk, stock volatility risk, and growth/value tilts

Larsen, Linda Sandris; Munk, Claus

doi:10.1016/j.jedc.2011.09.009

Cited by 62 publications

(28 citation statements)

References 66 publications

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“…As we will see later on, the general case is more involved. Given the results of Larsen and Munk (2012), who study sub-optimal strategies with misspecified hedge terms, this is not surprising. The following propositions give various bounds on the optimal strategy π * .…”

Section: Bounds On Optimal Strategymentioning

confidence: 99%

When Do Jumps Matter for Portfolio Optimization?

Ascheberg¹,

Branger²,

Kraft³

2013

SSRN Journal

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We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on quantities known only in the true model. We apply our method to a calibrated affine model. Our findings are threefold: Jumps matter more, i.e. our approximation is less accurate, if (i) the expected jump size or (ii) the jump intensity is large. Fixing the average impact of jumps, we find that (iii) rare, but severe jumps matter more than frequent, but small jumps. JEL-Classification AbstractWe consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on quantities known only in the true model. We apply our method to a calibrated affine model. Our findings are threefold: Jumps matter more, i.e. our approximation is less accurate, if (i) the expected jump size or (ii) the jump intensity is large. Fixing the average impact of jumps, we find that (iii) rare, but severe jumps matter more than frequent, but small jumps. JEL-Classification: G11; C63

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Section: Bounds On Optimal Strategymentioning

confidence: 99%

When Do Jumps Matter for Portfolio Optimization?

Ascheberg¹,

Branger²,

Kraft³

2013

SSRN Journal

View full text Add to dashboard Cite

show abstract

Section: Bounds On Optimal Strategymentioning

confidence: 99%

When Do Jumps Matter for Portfolio Optimization?

Ascheberg

Branger²,

Kraft

et al. 2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on results from the true model. We apply our method to a calibrated affine model and find that relative wealth equivalent losses are below 1.16% if the jump size is stochastic and below 1% if the jump size is constant and γ ≥ 5. We perform robustness checks for various levels of risk-aversion, expected jump size, and jump intensity. Terms of use: Documents in AbstractWe consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on results from the true model. We apply our method to a calibrated affine model and find that relative wealth equivalent losses are below 1.16% if the jump size is stochastic and below 1% if the jump size is constant and γ ≥ 5. We perform robustness checks for various levels of risk-aversion, expected jump size, and jump intensity.JEL-Classification: G11; C63

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“…The finding is that the degree of suboptimality due to the restriction of discrete portfolio revisions is of minor importance, whereas the uncertainty about the rate of return can be substantial. In recent papers, Larsen and Munk (2012) address the issue of incomplete information and incomplete menu of assets in a rather general setting for a single investor with a focus on the importance of the hedging term for a stochastically varying investment opportunity set; and Flor and Larsen (2014) address the issue of ambiguity aversion when the investor does not know the true return distributions. We refer to the rather elaborate list of references in these papers for a broad variety of contributions dealing with various issues of timevarying risk premia and investment opportunity sets as well as incomplete information about return distributions.…”

Section: Investment Made By Multiple Investors In Common Is Distributmentioning

confidence: 99%

How suboptimal are linear sharing rules?

Jensen

Nielsen

2016

Ann Finance

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The objective of this paper is to analyze criteria for portfolio choice when two investors are forced to invest in a common portfolio and share the proceeds by a linear sharing rule. A similar situation with many investors is typical for defined contribution pension schemes. The restriction implies two sources of suboptimal investment decisions as seen from each of the two investors individually. One is the suboptimal choice of portfolio, the other is the forced linear sharing rule. We measure the combined consequence for each investor by their respective loss in wealth equivalent. We show that significant losses can arise when investors are diverse in their risk attitude. We also show that an investor with a low degree of risk aversion, like the logarithmic or the square root investor, often applied in portfolio choice models, can either inflict or be subject to severe losses when being forced to participate in such a common investment pool.

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The costs of suboptimal dynamic asset allocation: General results and applications to interest rate risk, stock volatility risk, and growth/value tilts

Cited by 62 publications

References 66 publications

When Do Jumps Matter for Portfolio Optimization?

When Do Jumps Matter for Portfolio Optimization?

When Do Jumps Matter for Portfolio Optimization?

How suboptimal are linear sharing rules?

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