Stock price volatility and equity premium

By Michael J. Brennan, Yihong Xia. 2001

276 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/909079884cba9f75106d0d724943c3a55d627637

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Citations in the corpus

Equilibrium Portfolio Strategies in the Presence of Sentiment Risk and Excess Volatility (2009, unknown): “…in the data, we would like to work with parameter values that are reasonable.23 The parameter values that we specify are based on the estimation undertaken in Brennan and Xia (2001) for a model similar to ours.24 We limit ourselves to the case in which risk aversion is greater than one (α 0).”
Heterogeneous Beliefs, Speculation, and the Equity Premium (2008, background): “Following Cecchetti, Lam, and Mark (1990) and Brennan and Xia (2001), dividends are modeled as a part of the entire output of the economy.”
Investor Attention and Stock Market Volatility (2015, background): “Our paper is related to the broad literature of learning and uncertainty in finance (Detemple 1986, Gennotte 1986, Dothan and Feldman 1986, David 1997, Veronesi 1999, 2000, Brennan and Xia 2001).”
Mental Accounting, Loss Aversion, and Individual Stock Returns (2001, background): “…such as Barberis, Shleifer and Vishny (1998), Daniel, Hirshleifer, and Subrahmanyam (2001), and Hong and Stein (1999); models based on learning, such as Brennan and Xia (2001); and models based on corporate growth options such as Berk, Green and Naik (1999) and Gomes, Kogan, and Zhang (2001).”
Deja Vol: Predictive Regressions for Aggregate Stock Market Volatility Using Macroeconomic Variables (2012, unknown): “Brunnermeier and Pedersen (2009) study the interrelationship between traders’ funding liquidity and asset market liquidity.”
Optimal Decentralized Investment Management (2008, unknown): “Alternatively, limited knowledge of the managers’ risk attitudes can be interpreted as a form of Bayesian parameter uncertainty (see, for example, Barberis (2000), Brennan and Xia (2001)).”
Learning in Financial Markets (2009, background): “Brennan and Xia (2001b) assess the importance of the value and size anomalies from the perspective of an investor who is uncertain whether the anomalies are genuine.”
Style Effects in the Cross-Section of Stock Returns (2004, unknown): “This allows us to separate from the learning models proposed by Brennan and Xia (2001) , Veronesi (1999), and Lewellen and Shanken (2002).”
Parameter Learning in General Equilibrium: The Asset Pricing Implications (2016, background): “In the learning case, the two shocks are perfectly positively correlated (see Equations (10) and (11)).”
Investor Attention and FX Market Volatility (2015, unknown): “Attempts to resolve this puzzle draw on explanations such as Bayesian learning (Brennan and Xia, 2001) or adaptive learning (Adam et al., 2009) on the part of homogeneous investors, di ﬀ erences of opinions (Scheinkman and Xiong, 2003; Buraschi and Jiltsov, 2006), and Knightian uncertainty (Cagetti…”
Fragile beliefs and the price of uncertainty (2010, methodology): “…(2000) applied, we introduce an additional one, taken from Hansen and Sargent (2007), that adjusts the probability distribution of hidden Markov states for model uncertainty.5 We interpret both risk-sensitivity operators as capturing the representative consumer’s concerns about robustness instead…”
Investor Attention and Time-Varying Comovements (2007, unknown): “…typically adopt C© 2007 The Authors Journal compilation C© 2007 Blackwell Publishing Ltd, 2007 Bayesian learning frameworks to model investors’ learning processes under uncertainty, e.g., Epstein and Turnbull (1980), Detemple (1986), Gennotte (1986), Veronesi (1999), and Brennan and Xia (2001).”
Stock Market Volatility and Learning (2008, unknown): “21For example, Timmermann (1993, 1996), Brennan and Xia (2001), Cogley and Sargent (2006).”
Multifrequency News and Stock Returns (2007, background): “For example, Campbell and Hentschel (1992) focus on how fluctuations in dividend news volatility impact endogenous stock prices, and show that innovations with a half-life of about six months contribute to matching daily returns.”