Diagnostic Expectations and Stock Returns

Bordalo, Pedro; Gennaioli, Nicola; Porta, Rafael La; Shleifer, Andrei

doi:10.1111/jofi.12833

Cited by 270 publications

(43 citation statements)

References 76 publications

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“…The solid orange line represents the observed male advantage in performance in each category. 11 Categories perceived to be male-typed according to the slider scale measure tend to also display a male advantage in performance. Female performance significantly exceeds male performance in Kardashians and Disney movies.…”

Section: A Look At the Datamentioning

confidence: 99%

Beliefs about Gender

Bordalo

Coffman²,

Gennaioli

et al. 2019

American Economic Review

Self Cite

355

141

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We conduct laboratory experiments that explore how gender stereotypes shape beliefs about ability of oneself and others in different categories of knowledge. The data reveal two patterns. First, men’s and women’s beliefs about both oneself and others exceed observed ability on average, particularly in difficult tasks. Second, overestimation of ability by both men and women varies across categories. To understand these patterns, we develop a model that separates gender stereotypes from misestimation of ability related to the difficulty of the task. We find that stereotypes contribute to gender gaps in self-confidence, assessments of others, and behavior in a cooperative game. (JEL C92, D83, D91, J16)

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Section: A Look At the Datamentioning

confidence: 99%

Beliefs about Gender

Bordalo

Coffman²,

Gennaioli

et al. 2019

American Economic Review

Self Cite

355

141

View full text Add to dashboard Cite

show abstract

“…3 Recent theoretical models (e.g., Barberis et al (2015), Adam, Marcet, and Beutel (2017)) have been proposed to reconcile survey data on expectations with price volatility. With some exceptions (e.g., Bordalo et al (2019)), these papers focus primarily on explaining the behavior of subjective return expectations. The main force driving price ratio movements in these models is typically expectations of future price growth.…”

mentioning

confidence: 99%

Subjective Cash Flow and Discount Rate Expectations

O¹,

Myers²

2021

The Journal of Finance

133

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Why do stock prices vary? Using survey forecasts, we find that cash flow growth expectations explain most movements in the S&P 500 price-dividend and price-earnings ratios, accounting for at least 93% and 63% of their variation. These expectations comove strongly with price ratios, even when price ratios do not predict future cash flow growth. In comparison, return expectations have low volatility and small comovement with price ratios. Short-term, rather than long-term, expectations account for most price ratio variation. We propose an asset pricing model with beliefs about earnings growth reversal that accurately replicates these cash flow growth expectations and dynamics.A CENTRAL QUESTION IN FINANCE IS WHAT drives stock price movements. Specifically, researchers want to know what explains the large movements in the aggregate price-dividend ratio, a measure of how cheap or expensive stocks are at a given time. Based on the present value approach, for any investor that prices the stock, the stock's price should equal her expected discounted value of future dividends. This is true whether her expectations match an objective probability distribution or they come from a subjective distribution. Price changes should therefore be due to changes in her dividend expectations or her return expectations, and changes in the price-dividend ratio should be due to changes in her dividend growth expectations or return expectations.The challenge is determining the expectations of market participants. If investors have rational expectations, then we can infer the importance of

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“…The authors point out that tree-based classifier algorithms are more effective tools for predicting stock market behavior. Bordalo et al (2019) investigate the dynamics of fundamentals, expectations, and stock returns using different forecasting techniques in the theoretical framework. Unlike the adaptive expectations theory, the results indicate that the investors are forward-looking in forming their belief in the light of observed stock earning growth.…”

Section: Predicting Stock Market Returns: Rational or Adaptive Expect...mentioning

confidence: 99%

Comparing Decision Trees and Association Rules for Stock Market Expectations in BIST100 and BIST30

Ataman

Kahraman

2022

Sci. Ann. Econ. Bus.

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With the increased financial fragility, methods have been needed to predict financial data effectively. In this study, two leading data mining technologies, classification analysis and association rule mining, are implemented for modeling potentially successful and risky stocks on the BIST 30 index and BIST 100 Index based on the key variables of index name, index value, and stock price. Classification and Regression Tree (CART) is used for classification, and Apriori is applied for association analysis. The study data set covered monthly closing values during 2013-2019. The Apriori algorithm also obtained almost all of the classification rules generated with the CART algorithm. Validated by two promising data mining techniques, proposed rules guide decision-makers in their investment decisions. By providing early warning signals of risky stocks, these rules can be used to minimize risk levels and protect decision-makers from making risky decisions.

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Diagnostic Expectations and Stock Returns

Cited by 270 publications

References 76 publications

Beliefs about Gender

Beliefs about Gender

Subjective Cash Flow and Discount Rate Expectations

Comparing Decision Trees and Association Rules for Stock Market Expectations in BIST100 and BIST30

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