Asset pricing with return extrapolation

Jin, Lawrence; Sui, Pengfei

doi:10.1016/j.jfineco.2021.10.009

Cited by 61 publications

(6 citation statements)

References 62 publications

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“…For example, in models in which investors learn through Bayesian inference (e.g., Veronesi (1999), Johannes, Lochstoer, and Mou (2016), Ghaderi, Kilic, and Seo (2022)), our results suggest that beliefs should be strongly transmitted into actions. On the other hand, in models where learning departs from Bayesian inference or investors hold perpetually misspecified models (e.g., Jin and Sui (2022), Nagel and Xu (2022)), our results suggest that investor beliefs will be transmitted weakly into actions. 20…”

Section: A1 Incorporating Weak Transmission Into Investor Decisionsmentioning

confidence: 68%

“…Over the past decade, there has been an enormous amount of theoretical and empirical work on expectation formation in finance (Adam and Nagel (2023)). Several researchers have proposed models with the goal of jointly explaining asset prices and survey expectations (e.g., Barberis et al (2015), Hirshleifer, Li, and Yu (2015), Jin and Sui (2022)). While these models formalize the subjective expectation formation process in a psychologically grounded manner, they retain the standard assumption that investors fully act on their subjective beliefs.…”

Section: A1 Incorporating Weak Transmission Into Investor Decisionsmentioning

confidence: 99%

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Insensitive Investors

CHARLES,

FRYDMAN,

KILIC

2024

The Journal of Finance

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We experimentally study the transmission of subjective expectations into actions. Subjects in our experiment report valuations that are far too insensitive to their expectations, relative to the prediction from a frictionless model. We propose that the insensitivity is driven by a noisy cognitive process that prevents subjects from precisely computing asset valuations. The empirical link between subjective expectations and actions becomes stronger as subjective expectations approach rational expectations. Our results highlight the importance of incorporating weak transmission into belief‐based asset pricing models. Finally, we discuss how cognitive noise can provide a microfoundation for inelastic demand in the stock market.

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Section: A1 Incorporating Weak Transmission Into Investor Decisionsmentioning

confidence: 68%

Section: A1 Incorporating Weak Transmission Into Investor Decisionsmentioning

confidence: 99%

Insensitive Investors

CHARLES,

FRYDMAN,

KILIC

2024

The Journal of Finance

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“…Some researchers combine it with traditional models, and some have used it to answer the question about anomalies [4,5,[6][7][8]. Some people mix it with preference [9]. But recent research mainly focuses on the application, and less research is concerned with operating principles.…”

Section: Introductionmentioning

confidence: 99%

Simple Review of Extrapolation Bias

Guo

2023

AEMPS

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Extrapolation bias is a popular topic recently in economics and finance. Many researchers have become interested in this bias because it can explain many anomalies that a rational model cannot. This paper is a simple review of extrapolation bias, including its definition and bias. After reviewing past research on extrapolation, this paper selects a comprehensible definition, and three applications that can represent the recent research on extrapolation: the investor behavior model, the bubble model, and the house price model from three different top papers. After the review, it can be concluded that extrapolation bias has a wide applied range especially, in the financial market and asset pricing, and can explain many financial anomalies.

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“…Our paper also contributes to the growing theoretical literature studying the asset pricing implications of extrapolating past stock prices when forming future stock price expectations. In this literature, Barberis et al (2015) develop a heterogeneous agent model with two types of investors, the rational investors and extrapolators, whereas Jin and Sui (2022), Li and Liu (2020), and Atmaz (2021) develop homogeneous agent models in which the representative agent is an extrapolator. 3 Although these works capture various features of actual stock market returns, they typically generate only reversal, that is, a negative autocorrelation for all horizons.…”

Section: Introductionmentioning

confidence: 99%

Contrarians, Extrapolators, and Stock Market Momentum and Reversal

Atmaz,

Gulen,

Cassella

et al. 2023

Management Science

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We document considerable cross-investor variation in survey expectations about aggregate stock market returns. Although most investors are extrapolators who expect higher returns after a good market performance, some are contrarians who expect lower returns after a good performance. More notably, compared with extrapolators, contrarians have less persistent expectations that are corrected more quickly. We then develop a dynamic equilibrium model accounting for these differences in expectations and find that the equilibrium stock price exhibits short-term momentum and long-term reversal as in the data. Furthermore, we test the key predictions of our model linking the observable differences in extrapolators’ and contrarians’ expectations to aggregate stock market momentum and future stock performance and find supportive evidence for our model mechanism. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4960 .

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Asset pricing with return extrapolation

Cited by 61 publications

References 62 publications

Insensitive Investors

Insensitive Investors

Simple Review of Extrapolation Bias

Contrarians, Extrapolators, and Stock Market Momentum and Reversal

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