Y
Yan Li
Researcher at Temple University
Publications - 14
Citations - 727
Yan Li is an academic researcher from Temple University. The author has contributed to research in topics: Nonparametric statistics & Equity premium puzzle. The author has an hindex of 10, co-authored 14 publications receiving 642 citations.
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Journal ArticleDOI
Predicting Market Returns Using Aggregate Implied Cost of Capital
TL;DR: This article found that implied cost of capital (ICC) is a good proxy for time-varying expected returns, and that aggregate ICC strongly predicts future excess market returns at horizons ranging from one month to four years.
Journal ArticleDOI
Prospect Theory, the Disposition Effect, and Asset Prices
Yan Li,Liyan Yang +1 more
TL;DR: In this article, a general equilibrium model is proposed to examine the implications of prospect theory for the disposition effect, asset prices, and trading volume of the stock market, which is helpful for understanding a wide range of financial phenomena and also suggests new testable predictions.
Journal ArticleDOI
Predicting market returns using aggregate implied cost of capital
TL;DR: This paper found that implied cost of capital (ICC) is a good proxy for time-varying expected returns, and that aggregate ICC strongly predicts future excess market returns at horizons ranging from one month to four years.
Journal ArticleDOI
Speculation and Hedging in Segmented Markets
Itay Goldstein,Yan Li,Liyan Yang +2 more
TL;DR: In this paper, the authors analyze a model where traders have different trading opportunities and learn information from prices, and suggest that adding more informed traders may reduce price informativeness and therefore provide a source for learning complementarities leading to multiple equilibria and price jumps.
Journal ArticleDOI
Prospect theory, the disposition effect, and asset prices
Yan Li,Liyan Yang +1 more
TL;DR: In this paper, a general equilibrium model is proposed to examine the implications of prospect theory for the disposition effect, asset prices, and trading volume of the stock market, which is helpful for understanding a wide range of financial phenomena and also suggests new testable predictions.