Stock Return Predictability and Model Uncertainty

By Doron Avramov. 2002

630 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/57ed40f3e9cff9a8ea12e41db903189eea4bc808

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Citations in the corpus

A Comprehensive Look at the Empirical Performance ofEquity Premium Prediction II (2008, positive): “This selection model also shares a certain flavor with our encompassing tests in Section 7, where we seek to find an optimal rolling combination between each model and an unconditional historical equity premium average, and with the Bayesian model selection approach in Avramov (2002). The latter two”
Predictability of stock returns and asset allocation under structural breaks (2011, methodology): “This point has been emphasized by Pesaran and Timmermann (1995) and, more recently in a Bayesian setting, investigated by Avramov (2002) and Cremers (2002). The analysis of Avramov and Cremers treats model uncertainty by considering all possible combinations of a large range of predictor variables.”
Forecasting with Many Predictors (2006, methodology): “Avramov (2002) applied BMA to the problem of forecasting monthly and quarterly returns on six different portfolios of U.S. stocks using n = 14 traditional predictors (the dividend yield, the default risk spread, the 90-day Treasury bill rate, etc.).”
A Model-Averaging Approach for High-Dimensional Regression (2014, background): “In the fields of economics, finance, and business, there is a wide body of literature on model averaging for applications such as stock returns (Avramov 2002), exchange rates (Wright 2008), output growth (Garratt et al. 2003), portfolio management (Pesaran, Schleicher, and Zaffaroni 2009), currency…”
Forecasting the European carbon market (2013, methodology): “Avramov (2002)), the number of potential variables that may affect carbon prices is large.”
Bayesian Model Averaging and exchange rate forecasts (2003, neutral): “Sala-i-Martin (2000) and Fernandez, Ley and Steel (2001)) and stock return prediction ( Avramov (2002) and Cremers (2002)).”
Least Squares Model Averaging (2007, neutral): “In the m0th approximating model (5), let μm = XmΘm so that μ = μm + bm where μ = (μ1, .”
Complete subset regressions (2013, methodology): “Predictability of US stock returns by means of combinations of models based on different sets of predictors has been considered by studies such as Avramov (2002), Cremers (2002), and Rapach et al. (2010).”
Asset Allocation With a High Dimensional Latent Factor Stochastic Volatility Model (2006, neutral): “Some recent examples are Lettau and Ludvigson (2001), Cremers (2002), Avramov (2002), and Goyal and Welch (2003).”
Predicting stock returns (2006, positive): “Moreover, Lettau and Ludvigson (2001) and Avramov and Chordia (2006), among others, demonstrate that asset pricing models with time varying market premium or risk are reasonably successful relative to their unconditional counterparts.”
tay's as good as cay (2005, background): “6 In an independent study,Avromov (2002)also finds thatcaydisplays an impressive predictive power on when the shares of asset wealth and labor income (in total wealth) are based on data realized subs the prediction period, and that when constructed using quantities available at the time of…”
Portfolio Choice Problems (2010, background): “Further extensions and applications are pursued by Pastor and Stambaugh (2000,2002) and Avramov (2004)”