Asset pricing with adaptive learning

Cárceles‐Poveda, Eva; Giannitsarou, Chryssi

doi:10.1016/j.red.2007.10.003

Cited by 63 publications

(37 citation statements)

References 26 publications

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“…Note of course that the value of g computed with annual data would be larger than the corresponding g if the data were converted to quarterly. values of t above 1, as we can see from equations (14)(15)(16). We expect lower , or fatter tails, as the support of t that lies above 1 gets larger.…”

Section: Model Simulations and Comparative Staticsmentioning

confidence: 62%

Learning, Large Deviations and Rare Events

Benhabib¹,

Dave²

2011

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We examine the role of generalized constant gain stochastic gradient (SGCG) learning in generating large deviations of an endogenous variable from its rational expectations value. We show analytically that these large deviations can occur with a frequency associated with a fat tailed distribution even though the model is driven by thin tailed exogenous stochastic processes. We characterize these large deviations that are driven by sequences of consistently low or consistently high shocks. We then apply our model to the canonical asset-pricing model. We demonstrate that the tails of the stationary distribution of the price-dividend ratio will follow a power law.

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Section: Model Simulations and Comparative Staticsmentioning

confidence: 62%

Learning, Large Deviations and Rare Events

Benhabib¹,

Dave²

2011

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“…In such a case, an alternative is provided by the ad-hoc initialization method, where the initials are hand-picked by the researcher. When taking the REE-based initials as a reference, this method provides a way to validate the sensitivity of results obtained under the former approach (e.g., Milani, 2007;Carceles-Poveda and Giannitsarou, 2008). In fact, one of the main uses of ad-hoc initials is to deal with the possibility of structural changes around the periods of the initials: when the changes affect the REE, agents may not be able to instantaneously adjust to the new equilibrium, and could therefore be forming expectations consistent with the previous equilibrium at the time of the initialization (see also Giannitsarou, 2007, p. 2679).…”

Section: Equilibrium-related Methodsmentioning

confidence: 99%

“…Examples are given by Carceles-Poveda and Giannitsarou (2008) for asset pricing models, Huang et al (2009) in a standard growth model, and Slobodyan and Wouters (2012) in a medium-scale dynamic stochastic general equilibrium (DSGE) model. Overall, these studies present results showing that whereas the introduction of learning has interesting effects on the dynamics and the fit of models to the data, a great portion of the improvements may be associated to transition dynamics from specific initial beliefs.…”

Section: Introductionmentioning

confidence: 99%

On the initialization of adaptive learning in macroeconomic models

Berardi

Galimberti

2017

Journal of Economic Dynamics and Control

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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. Terms of use: Documents in ETH Zurich AbstractWe review and evaluate methods previously adopted in the applied literature of adaptive learning in order to initialize agents' beliefs. Previous methods are classified into three broad classes: equilibrium-related, training sample-based, and estimation-based. We conduct several simulations comparing the accuracy of the initial estimates provided by these methods and how they affect the accuracy of other estimated model parameters. We find evidence against their joint estimation with standard moment conditions: as the accuracy of estimated initials tends to deteriorate with the sample size, spillover effects also deteriorate the accuracy of the estimates of the model's structural parameters. We show how this problem can be attenuated by penalizing the variance of estimation errors. Even so, the joint estimation of learning initials with other model parameters is still subject to severe distortions in small samples. We find that equilibrium-related and training sample-based initials are less prone to these issues. We also demonstrate the empirical relevance of our results by estimating a New Keynesian Phillips curve with learning, where we find that our estimation approach provides robustness to the initialization of learning. That allows us to conclude that under adaptive learning the degree of price stickiness is lower compared to inferences under rational expectations, whereas the fraction of backward looking price setters increases.

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“…Finally, the conditional normality ofĉ t+1 implies that marginal utility growth, t+1 ; in (24), and hence the log-SDF, m t+1 = ln + t+1 , are also conditionally normally distributed. Thus, R e t+1 (h) = e ln +r e t+1 (h) and M t+1 = e m t+1 are con…rmed to be conditionally lognormally distributed, as we assumed when going from (15) to (17).…”

Section: Model Solutionmentioning

confidence: 99%

“…As an additional robustness check, we also compare the multipliers obtained with our approximation to those obtained via standard …rst, second and third order log perturbations of the equilibrium condition that charac-terizes real stock prices, i.e. (15). For all equilibrium conditions apart from (15), we keep working with their log-linear approximations.…”

Section: Baseline Parameterizationmentioning

confidence: 99%

Stock Prices and Monetary Policy Shocks: A General Equilibrium Approach

Challe

Giannitsarou

2011

SSRN Journal

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Abstract. Recent empirical literature documents that unexpected changes in the nominal interest rates have a signi…cant e¤ect on real stock prices: a 25-basis point increase in the nominal interest rate is associated with an immediate decrease in broad real stock indices that may range from 0.6 to 2.2 percent, followed by a gradual decay as real stock prices revert towards their long-run expected value. In this paper, we assess the ability of a general equilibrium New Keynesian asset-pricing model to account for these facts. The model we consider is a production economy with elastic labor supply, staggered price and wage setting, as well as time-varying risk aversion through habit formation. We …nd that the model predicts a stock market response to policy shocks that matches empirical estimates, both qualitatively and quantitatively. Our …ndings are robust to a range of variations and parameterizations of the model.

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Asset pricing with adaptive learning

Cited by 63 publications

References 26 publications

Learning, Large Deviations and Rare Events

Learning, Large Deviations and Rare Events

On the initialization of adaptive learning in macroeconomic models

Stock Prices and Monetary Policy Shocks: A General Equilibrium Approach

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