Essays on Estimating and Testing Asset Pricing Models PDF Download
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Languages : en
Pages : 275
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Author:
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Languages : en
Pages : 275
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Author: Jun Xu
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Category :
Languages : en
Pages : 90
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Essay One: A New Estimate of BetaThis essay examines a new method of estimating systematic risk, or "beta". Due to market imperfection, stock prices, especially those of small firms, do not move with the market index synchronously. Because of nonsynchronous or delayed reaction in price for small firms, the traditional beta estimated from the market model may not be a true reflection of systematic risk. In other words, since stock prices do not fully respond to the market in a single period, the contemporary beta may only reflect the partial systematic risk. As a result, the beta estimated from the market model is underestimated for small firms and overestimated for large firms. The same problem also causes betas estimated from the market model to vary greatly across different estimation horizons. I develop a model of delay/lead price reactions for small/large firms. Based on this model I derive a multiple-period regression equation for the new estimation of beta.^We then estimate the equation for each of the ten size-ranked decile portfolios at different estimation horizons, using monthly, weekly and daily returns. Betas estimated from the optimal estimation horizons for monthly, weekly, and daily returns are discussed. Our results show that, betas estimated at similar horizons, using monthly, weekly, and daily returns, are consistent with each other. Betas estimated for the ten size-decile portfolios from monthly, weekly, and daily average returns are positively related to those returns, respectively. Essay Two: Test of Capital Asset Pricing Model Based on a New Estimate of BetaThis essay tests the Capital Asset Pricing Model (CAPM), based on a new estimate of beta. The test methodology follows the classic Fama-MacBeth (1973) approach, using updated data from 1926-2010.^I ran each test on eleven different periods based on three different estimates of beta: the Ordinary Least Square (OLS) beta, the Scholes-Williams (1977) beta, and a new estimate of beta. From three long testing periods, 1935-1968, 1969-2010, and 1935-2010, all three hypotheses are confirmed based on the new estimate of beta. In other words there is a positive trade-off between average return and risk, and non-linearity and non-beta risk do not play a significant role in explaining the cross section of expected return. Test results from the three long periods based on the OLS beta and the Scholes-Williams beta are mixed and less supportive to CAPM. Our test results from the eight shorter periods do not confirm the CAPM. However, this may be due to the lack of power and efficiency of the test methodology when applied to short periods.^Overall, our results from long periods show that tests based on the new estimate of beta perform better than those based on the OLS beta and the Scholes-Williams beta in terms of supporting CAPM.
Author: Jeroen Wilhelmus Paulus Dalderop
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Category :
Languages : en
Pages :
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Author: Pooya Nazeran
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Category :
Languages : en
Pages : 138
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Abstract: A considerable portion of the asset pricing literature considers the demand schedule for asset prices to be perfectly elastic (flat). As argued, asset prices are determined using information about future payoff distribution, as well as the discount rate; consequently, an asset would be priced independent of its available supply. Furthermore, such a flat demand curve is considered to be a consequence of the Efficient Market Hypothesis. My dissertation evaluates and questions the factuality of these assertions. I approach this problem from both an empirical and a theoretical perspective. The general argument is that asset prices do respond to supply-shocks; and changes in aggregate demand, stemming from preference changes, new international investments, or quantitative easing by the Fed, can result in price changes. Hence, asset prices are determined by both demand and supply factors. In the first essay, "Downward Sloping Asset Demand: Evidence from the Treasury Bills Market," I report on my empirical study which establishes the existence of a downward sloping demand curve (DSDC) in the T-bill market. In the second essay, "Asset Pricing: Inelastic Supply," I examine the theoretical issues concerning a downward sloping demand curve. I begin by clarifying a common confusion in the literature, namely, that many asset pricing models imply a flat demand curve. I show that the prominent asset pricing models, including Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT) and Consumption Capital Asset Pricing Model (CCAPM), all have an underlying DSDC. I further show that, while these models imply the relevance of supply, they are inconvenient as a vehicle for the estimation and analysis of the DSDC in the data. For those purposes, I develop an asset pricing framework based on the stochastic discount factor framework, specifically designed with a DSDC at its heart. I end the essay with a discussion of the framework's implications and applications. In the third essay I develop on the Factor-Augmented Vector-Autoregression (FAVAR) literature, proposing a bias-corrected method. As implemented in the literature, the Principal Component Analysis stage of FAVAR introduces a classical-error-in-variable problem which leads to bias. I propose an instrument-based method for bias correction.
Author: Bruce Neal Lehmann
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Category : Assets (Accounting)
Languages : en
Pages : 52
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This essay reviews the extensive literature on empirical testing of asset pricing models. It briefly describes the kinds of asset pricing models typically tested in the literature and explicates their econometric implications, both in terms of the estimation of relevant parameters and tests of their implied restrictions. Pertinent aspects of the available data on security prices and macroeconomic variables are discussed as well. The essay concludes with the examination of selected aspects of the current empirical state of asset pricing theory
Author: Michael Shane O'Doherty
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ISBN:
Category : Stock price forecasting
Languages : en
Pages : 159
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Using a variety of test portfolios, the optimal pool of models consistently outperforms the best individual model on both statistical and economic grounds.
Author: Irina Pimenova
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Category :
Languages : en
Pages : 206
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In this dissertation, I revisit two problems in empirical asset pricing. In Chapter 1, I propose a methodology to evaluate the validity of linear asset pricing factor models under short sale restrictions using a regression-based test. The test is based on the revised null hypothesis that intercepts obtained from regressing excess returns of test assets on factor returns, usually referred to as alphas, are non-positive. I show that under short sale restrictions a much larger set of models is supported by the data than without restrictions. In particular, the Fama-French five-factor model augmented with the momentum factor is rejected less often than other models. In Chapter 2, I investigate patterns of equity premium predictability in international capital markets and explore the robustness of common predictive variables. In particular, I focus on predictive regressions with multiple predictors: dividend-price ratio, four interest rate variables, and inflation. To obtain precise estimates, two estimation methods are employed. First, I consider all capital markets jointly as a system of regressions. Second, I take into account uncertainty about which potential predictors forecast excess returns by employing spike-and-slab prior. My results suggest evidence in favor of predictability is weak both in- and out-of-sample and limited to a few countries. The strong predictability observed on the U.S. market is rather exceptional. In addition, my analysis shows that considering model uncertainty is essential as it leads to a statistically significant increase of investors' welfare both in- and out-of-sample. On the other hand, the welfare increase associated with considering capital markets jointly is relatively modest. However, it leads to reconsider the relative importance of predictive variables because the variables that are statistically significant predictors in the country-specific regressions are insignificant when the capital markets are studied jointly. In particular, my results suggest that the in-sample evidence in favor of the interest rate variables, that are believed to be among the most robust predictors by the literature, is spurious and is mostly driven by ignoring the cross-country information. Conversely, the dividend-price ratio emerges as the only robust predictor of future stock returns.
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Languages : en
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Author: Hua Shang
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Category :
Languages : en
Pages : 129
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This disertation includes three essays on linear asset pricing models. The first chapter is concerned with the effects of including a low-variance factor which leads to a small signal-to-noise ratio in an asset pricing model. We rely on local asymptotics and define the low-variance as local-to-zero by being inversely related to the sample size. When a low-variance factor is present, the commonly applied Fama-Macbeth two-pass regression procedure yields misleading results. Local asymptotic analysis and simulation evidence indicate that the beta of the low-variance factor, risk premiums corresponding to all factors and the magnitude of associated variances are all unreliably estimated. Moreover, t- and F- statistics are unable to detect whether risk premiums are significantly different from zero. Additional simulation results also reveal that Kleibergen's statistic has some ability to detect the usefulness of different factors. In the second chapter, I investigate the finite sample properties of the two-pass regression, the t-statistic, statistics proposed by Kleibergen (2009) and the specification tests when the first-pass regression slope coefficients -- betas -- are large, small and zero. In particular, I explore the effect of the number of assets on the properties of the statistics. The results reveal that most of the statistics tend to reach a conclusion that the factor should be included in the model or the model is correct more often that it should, especially when betas are small and the number of assets is large. The diagnosis of the results shows that the source of the problem lies in the large bias of the estimated risk premiums and the poor estimation of the variance-covariance matrix of the error terms in the first-pass regression. The third chapter explores an economic explanation of commodity prices by considering the macro-economic exposure of commodity returns. Through estimating the stochastic discount factor representation of the linear asset pricing model, I find that investors are compensated for exchange-rate risk. The result is robust to different estimation methods, to different data sets and over longer periods of time.
Author: Yan Wang
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Category :
Languages : en
Pages :
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