Expectations and Investment

By N. Gennaioli, Yueran Ma, A. Shleifer. NBER macroeconomics annual, 2015

355 citations recorded by the source corpus.

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/48a9f7cb4c75f70f3ff40156a285e4d47e860fc4

Citations in the corpus

• More is different ... and complex! the case for agent-based macroeconomics (2019, neutral): “Conversely, given such premises, no wonder that empirical tests usually reject the full-information, rational expectation hypothesis (see e.g. Coibion and Gorodnichenko, 2015; Gennaioli et al., 2015).”
• New Experimental Evidence on Expectations Formation (2017, neutral): “2 1For instance, Lakonishok et al. (1994) and Laporta (1996) argue that the value premium is related to extrapolative bias.”
• Imperfect Macroeconomic Expectations: Evidence and Theory (2020, neutral): “More recently, Greenwood and Shleifer (2014) and Gennaioli, Ma, and Shleifer (2015b) demonstrate patters in survey expectations of stock returns and firm earnings that are also suggestive of over-extrapolation.”
• Sticky Expectations and the Profitability Anomaly (2018, neutral): “This framework accommodates patterns of both under-reaction (0 < λ < 1) and overreaction (λ < 0) (shown for instance in Gennaioli et al. (2015) and Greenwood and Shleifer (2014)).”
• Diagnostic Expectations and Credit Cycles (2018, neutral): “…dynamics of forecasts that we document here are in line with other studies, such as evidence of systematic reversal in bond spreads (Greenwood and Hanson (2013)) and the extrapolative nature of a CFO’s expectations about their company’s earnings growth (Gennaioli, Ma, and Shleifer (2016)).”
• Psychology-based Models of Asset Prices and Trading Volume (2018, neutral): “Aside from excess volatility and time-series predictability, the model also captures an idea emphasized by Marks (2011) and Gennaioli et al. (2012), namely that the risk of a crash is greatest following a long quiet period with no significant downturns: at such a moment, the availability heuristic l”
• Diagnostic Expectations and Stock Returns (2019, neutral): “We use expectations data not only to predict returns, but also as a central element of the model and its empirical estimation.2 Such data are becoming increasingly common in recent work (Ben David, Graham, and Harvey (2013), Greenwood and Shleifer (2014), Gennaioli, Ma, and Shleifer (2016)).”