Using Stocks or Portfolios in Tests of Factor Models

Ang, Andrew; Li, Jun; Schwarz, Krista

doi:10.1017/s0022109019000255

Cited by 119 publications

(70 citation statements)

References 72 publications

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“…The overall results suggest the rejection of the joint null hypothesis across periods and test statistics, however, it is worth noting that the corrected versions of Ando and Bai's (2015) test for both R = 2, 5 and the three asset pricing equations do not reject the null hypothesis of correct specification of the asset pricing equation over the period 1973-1993. In summary, our empirical results for a cross-section of 47 industry portfolios excluding Health and Computer Software sectors are similar to other recent empirical studies testing the validity of empirical asset pricing models. Thus Ang, Liu, and Schwarz (2017) using two-pass asset pricing regression models reject the hypothesis that the cross-sectional risk premia are equal to the mean factor portfolio returns using a dataset of portfolios. Our results are also similar to the empirical findings in Gagliardini et al (2016) that reject the empirical validity of different factor models to price the cross-section of industry portfolios using a novel test in a conditional asset pricing setting, and also the standard Gibbons et al (1989) F-statistic.…”

Section: Test Resultsmentioning

confidence: 84%

“…In summary, our empirical results for a cross‐section of 47 industry portfolios excluding Health and Computer Software sectors are similar to other recent empirical studies testing the validity of empirical asset pricing models. Thus Ang, Liu, and Schwarz () using two‐pass asset pricing regression models reject the hypothesis that the cross‐sectional risk premia are equal to the mean factor portfolio returns using a dataset of portfolios. Our results are also similar to the empirical findings in Gagliardini et al () that reject the empirical validity of different factor models to price the cross‐section of industry portfolios using a novel test in a conditional asset pricing setting, and also the standard Gibbons et al () F ‐statistic.…”

Section: Empirical Applicationmentioning

confidence: 90%

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Tests of asset pricing with time‐varying factor loads

Galvao

Montes‐Rojas

Olmo

2019

J of Applied Econometrics

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Summary This paper proposes an empirical asset pricing test based on the homogeneity of the factor risk premia across risky assets. Factor loadings are considered to be dynamic and estimated from data at higher frequencies. The factor risk premia are obtained as estimates from time series regressions applied to each risky asset. We propose Swamy‐type tests robust to the presence of generated regressors and dependence between the pricing errors to assess the homogeneity of the factor risk premia and the zero intercept hypothesis. An application to US industry portfolios shows overwhelming evidence rejecting the capital asset pricing model, and the three and five factor models developed by Fama and French (Journal of Financial Economics, 1993, 33, 3–56; Journal of Financial Economics, 2015, 116, 1–22). In particular, we reject the null hypotheses of a zero intercept, homogeneous factor risk premia across risky assets, and the joint test involving both hypotheses.

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Section: Test Resultsmentioning

confidence: 84%

Section: Empirical Applicationmentioning

confidence: 90%

Tests of asset pricing with time‐varying factor loads

Galvao

Montes‐Rojas

Olmo

2019

J of Applied Econometrics

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“…However, several potential problems arise from using portfolios. Litzenberger and Ramaswamy (1979) and Ang, Liu, and Schwarz (2010a) argue that valuable information is lost when forming portfolios, leading to lower power in asset-pricing tests. Further, information about firm-level returns can be distorted when forming portfolios, potentially resulting in poor inferences about a model (e.g., Roll (1977), , and Fama and French (2008)).…”

Section: Model Discussionmentioning

confidence: 99%

“…1 One way to avoid the concerns with portfolios is to use firm-level data. To examine anomalies at the firm level, however, the 1 For example, Litzenberger and Ramaswamy (1979) and Ang, Liu, and Schwarz (2010b) consider the loss in efficiency from using portfolios rather than individual firms in assetpricing tests, while Roll (1977), , and Fama and French (2008) discuss how patterns in firm-level pricing errors can be distorted at the portfolio level. Lo and MacKinlay (1990) highlight the data-snooping biases inherent in portfoliobased asset-pricing tests.…”

Section: Introductionmentioning

confidence: 99%

“…returns, rather than testing among portfolios where results are known to be sensitive to the choice of test assets (e.g., Ahn, Conrad, and Dittmar (2009) and Lewellen, Nagel, and Shanken (2010)). Further, testing asset-pricing models among individual firms generally achieves higher power (Litzenberger and Ramaswamy (1979) and Ang, Liu, and Schwarz (2010a)) and avoids various problems that can occur when aggregating firm returns into portfolios, such as wasting or distorting information in firm returns. 3 Perhaps more importantly, I directly include estimated innovations in the market risk premium and real interest rate as additional factors while testing the ICAPM.…”

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confidence: 99%

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Essays in cross-sectional asset pricing

Cederburg¹

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In this dissertation, I study the performance of asset-pricing models in explaining the cross section of expected stock returns. The finance literature has uncovered several potential failings of the Capital Asset Pricing Model (CAPM).I investigate the ability of additional risk factors, which are not considered by the CAPM, to explain these problems. In particular, I examine intertemporal risk and long-run risk in the cross section of returns. In addition, I develop a firm-level test to refine and reassess the cross-sectional evidence against the CAPM.In the first chapter, I test the cross-sectional implications of the Intertemporal CAPM (ICAPM) of Merton (1973 using a new firm-level approach. I find that the ICAPM performs well in explaining returns.Consistent with theoretical predictions, investors require a large positive premium for taking on market risk and zero-beta assets earn the risk-free rate. Moreover, investors accept lower returns on assets that hedge against adverse shifts in the investment opportunity set. The ICAPM explains more cross-sectional variation in average returns than either the CAPM or Fama-French (1993) model. I also investigate whether the SMB and HML factors of the Fama-French model proxy for intertemporal risk and find little evidence in favor of this conjecture.In the second chapter, we propose an intertemporal asset-pricing model that simultaneously resolves the puzzling negative relations between expected stock return and analysts' forecast dispersion, idiosyncratic volatility, and credit risk. All three effects emerge in a long-run risk economy accommodating a formal cross sec-tion of firms characterized by mean-reverting expected dividend growth. Higher cash flow duration firms exhibit higher exposure to economic growth shocks while they are less sensitive to firm-specific news. Such firms command higher risk premiums but exhibit lower measures of idiosyncratic risk. Empirical evidence broadly supports our model's predictions, as higher dispersion, idiosyncratic volatility, and credit risk firms display lower exposure to long-run risk along with higher firm-specific risk.Lastly, in the third chapter, we examine asset-pricing anomalies at the firm level. Portfolio-level tests linking CAPM alphas to a large number of firm characteristics suggest that the CAPM fails across multiple dimensions. There are, however, concerns that underlying firm-level associations may be distorted at the portfolio level. In this paper we use a hierarchical Bayes approach to model conditional firmlevel alphas as a function of firm characteristics. Our empirical results indicate that much of the portfolio-based evidence against the CAPM is overstated. Anomalies are primarily confined to small stocks, few characteristics are robustly associated with CAPM alphas out of sample, and most firm characteristics do not contain unique information about abnormal returns. Abstract Approved: Thesis Supervisor ACKNOWLEDGEMENTS I would like to thank my advisor, Paul A. Weller, for his support and guidance. I also t...

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On the time‐varying relationship between coskewness and returns of banks

Bressan

Weissensteiner

2023

Rev Financ Econ

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For a sample of US commercial banks, we find that during the Global Financial Crisis of 2007–2009 and the COVID‐19 pandemic of February–December 2020, bank returns were positively related to their coskewness with the market return, while the relationship was negative during stable periods. The literature on non‐financial firms and global equity indices has shown that the relationship between coskewness and stock returns is time‐variant. The findings of this study extend that evidence to banks. The interpretation is that in normal times, investors show a preference for “lotteryness,” and therefore they are willing to pay a premium for bank stocks with a high coskewness (i.e., low expected return). In contrast, during crises, stocks with a high coskewness are more likely to suffer deep losses, and investors are reluctant to demand these risky high returns. These findings deliver important insights into how to interpret bank capital costs throughout the business cycle, as we suggest that during crises the issuance of equity capital becomes more costly for banks because investors demand higher coskewness risk premiums.

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Using Stocks or Portfolios in Tests of Factor Models

Cited by 119 publications

References 72 publications

Tests of asset pricing with time‐varying factor loads

Tests of asset pricing with time‐varying factor loads

Essays in cross-sectional asset pricing

On the time‐varying relationship between coskewness and returns of banks

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