Learning from Prices and the Dispersion in Beliefs

By Snehal Banerjee. 2011

238 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/5b514cb4b443bb3bcaeeeb0014fdec0abd391cbb

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Citations in the corpus

Psychology-based Models of Asset Prices and Trading Volume (2018, background): “21See Banerjee and Kremer (2010) and Banerjee (2011) for other dismissiveness-based models of trading volume.”
Ratings Shopping and Asset Complexity: A Theory of Ratings Inflation (2009, unknown): “For more recent work on this topic, see Banerjee (2007).”
Individual Investor Perceptions and Behavior During the Financial Crisis (2013, unknown): “Changes in and divergence of perceptions are both expected to lead to higher trading activity: the first effect provides more reasons to trade, the second effect makes it more likely to find a trading counterpart (cf. Harris and Raviv, 1993; Banerjee, 2011).”
Reference-Dependent Preferences and the Risk-Return Trade-Off (2017, unknown): “7 These alternative measures of risk can be viewed, and have been used, as proxies for information uncertainty in Zhang (2006) , idiosyncratic parameter uncertainty or information risk in Johnson (2004) , divergence of opinion in Diether, Malloy, and Scherbina (2002) , parameter uncertainty over the”
Disagreement and asset prices. (2014, unknown): “As Banerjee (2011) highlights, investors may update their beliefs via a rational expectations mechanism or may agree to disagree, which results in persistent differences in opinion.”
Differences in herding: Individual vs. institutional investors (2017, unknown): “In testing the relationship between disagreement and stock return and volatility, Banerjee (2011) finds that using volume as proxies for disagreement provide empirical evidence that is consistent with investors using prices on average.”
Information Percolation, Momentum and Reversal (2014, unknown): “We therefore follow the convention introduced by Banerjee et al. (2009) and condition future returns on past returns, as opposed to the common information set F .”