Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance

This paper develops a method informed by data and models to recover information about investor beliefs. Our approach uses information embedded in forward-looking asset prices in conjunction with asset pricing models. We step back from presuming rational expectations and entertain potential belief distortions bounded by a statistical measure of discrepancy. Additionally, our method allows for the direct use of sparse survey evidence to make these bounds more informative. Within our framework, market-implied beliefs may differ from those implied by rational expectations due to behavioral/psychological biases of investors, ambiguity aversion, or omitted permanent components to valuation. Formally, we represent evidence about investor beliefs using a nonlinear expectation function deduced using model-implied moment conditions and bounds on statistical divergence. We illustrate our method with a prototypical example from macrofinance using asset market data to infer belief restrictions for macroeconomic growth rates.

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“…Refs. 20 and 21 give extensions of the measure of model misspecification proposed by ref. 22 to accommodate conditioning information.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust identification of investor beliefs

Chen

Hansen

Hansen³

2020

Proc. Natl. Acad. Sci. U.S.A.

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“…In fact, this bound has the same form as the celebrated Hansen-Jagannathan (HJ) bound in theoretical finance [40][41][42]. The HJ bound is a fundamental relation in theoretical finance because it applies to all models of the market, and there have been many applications of it besides upper bounding the Sharpe ratio [43][44][45][46]. While the original HJ bound can only be applied to the case in which Q is a martingale distribution, our result applies to an arbitrary distribution Q such that R Q = r f .…”

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confidence: 92%

Universal Thermodynamic Uncertainty Relation in Non-Equilibrium Dynamics

Ziyin¹,

Ueda²

2022

Preprint

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We derive a universal thermodynamic uncertainty relation (TUR) that applies to an arbitrary observable in a general Markovian system. The generality of our result allows us to make two findings:(1) for an arbitrary out-of-equilibrium system, the imbalance between the entropy production and the degree of non-stationarity is required to bound the strength of a thermodynamic current; (2) by removing the antisymmetric constraint on observables, the TUR in physics and a fundamental inequality in theoretical finance can be unified in a single framework.

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Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance

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Cited by 2 publications

References 6 publications

Robust identification of investor beliefs

Robust identification of investor beliefs

Universal Thermodynamic Uncertainty Relation in Non-Equilibrium Dynamics

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