Your search

× We're adding references and refining topic classifications. The platform is under construction, and we're looking for maintainers to help. Interested in contributing? Get in touch!
In authors or contributors
  • FT50 UTD24 A*

    ABSTRACT We present a model of credit cycles arising from diagnostic expectations?a belief formation mechanism based on Kahneman and Tversky's representativeness heuristic. Diagnostic expectations overweight future outcomes that become more likely in light of incoming data. The expectations formation rule is forward looking and depends on the underlying stochastic process, and thus is immune to the Lucas critique. Diagnostic expectations reconcile extrapolation and neglect of risk in a unified framework. In our model, credit spreads are excessively volatile, overreact to news, and are subject to predictable reversals. These dynamics can account for several features of credit cycles and macroeconomic volatility.

  • FT50 UTD24 A*

    ABSTRACT We revisit La Porta's finding that returns on stocks with the most optimistic analyst long-term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.

  • FT50 A*

    We construct an index of long-term expected earnings growth for S&P 500 firms and show that it has remarkable power to jointly predict future errors in expectations and stock returns, in both the aggregate market and the cross section. The evidence supports a mechanism whereby good news causes investors to become too optimistic about long-term earnings growth. This leads to inflated stock prices and, as beliefs are systematically disappointed, subsequent low returns in the aggregate market. Overreaction of long-term expectations helps resolve major asset-pricing puzzles without time-series or cross-sectional variation in required returns.

  • FT50 UTD24 A*

    We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with learning from prices and speculation (buying for resale). With diagnostic (but not with rational) expectations, these mechanisms lead to price paths exhibiting three phases: initial underreaction, then overshooting (the bubble), and finally a crash. With learning from prices, the model generates price extrapolation as a by-product of beliefs about fundamentals, lasting only as the bubble builds up. When investors speculate, even mild diagnostic distortions generate substantial bubbles.

Last update from database: 9/16/24, 10:02 PM (AEST)