Cross-Sectional Estimation Biases in Risk Premia and Zero-Beta Excess Returns

2009 ◽  
Author(s):  
Jianhua Yuan ◽  
Robert Savickas
Keyword(s):  
Risk Premia ◽  
Excess Returns ◽  
Cross Sectional

scholarly journals Cross-Sectional Estimation Biases in Risk Premia and Ze-ro-Beta Excess Returns

2013 ◽  
Vol 04 (01) ◽  
pp. 54-66
Author(s):  
Jianhua Yuan ◽  
Robert Savickas
Keyword(s):  
Risk Premia ◽  
Excess Returns ◽  
Cross Sectional

Dividend Risk Premia

2019 ◽  
Vol 55 (4) ◽  
pp. 1199-1242
Author(s):  
Georg Cejnek ◽  
Otto Randl
Keyword(s):  
United States ◽  
Risk Factor ◽  
United Kingdom ◽  
Time Variation ◽  
Factor Model ◽  
International Markets ◽  
Risk Premia ◽  
Excess Returns ◽  
Stock Indices ◽  
Bond Risk

This article studies time variation in the expected excess returns of traded claims on dividends, bonds, and stock indices for international markets. We introduce a novel dividend risk factor that complements the bond risk factor of Cochrane and Piazzesi (2005). By aggregating over 4 regions (United States, United Kingdom, Eurozone, and Japan), we create global dividend and bond factors. Our global 2-factor model captures the excess returns of most Morgan Stanley Capital International (MSCI) country indices, as well as a variety of other test assets. Our findings highlight the value of the information contained in dividend and bond forward curves and suggest substantial comovement in international risk premia.

Evidence for Some Underlying Time Series Momentum

2014 ◽  
pp. 205-217
Author(s):  
Faten Zoghlami
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Returns ◽  
Excess Returns ◽  
Momentum Strategy ◽  
Cross Sectional ◽  
Times Series ◽  
Before And After ◽  
Main Driver ◽  
Full Rationality

The chapter documents significant and momentary momentum pattern in stock returns times series. Moreover, the chapter gives evidence that this time series momentum is the main driver of the cross-sectional momentum pattern. The temporary time series momentum pattern is midway between the behavioural and rational financial theories. Given the strong and positive autocorrelation in stock returns time series, the authors argue that investors are temporary under reacting, and they progressively find their full rationality. Using monthly returns inherent to all stocks listed on Tunisian stock market, from January 2000 to December 2009, the authors examine momentum strategy’s excess returns before and after considering time series momentum in stocks returns. Results show that momentum strategy is still profitable, but no longer puzzling. Furthermore, the chapter aims to reconcile between the behavioural and the rational financial theories, through the introduction of the progressive investors rationality.

scholarly journals Testing Beta-Pricing Models Using Large Cross-Sections

2019 ◽  
Vol 33 (6) ◽  
pp. 2796-2842 ◽  
Author(s):  
Valentina Raponi ◽  
Cesare Robotti ◽  
Paolo Zaffaroni
Keyword(s):  
Cross Sections ◽  
Risk Premia ◽  
Expected Returns ◽  
Firm Characteristics ◽  
Pricing Models ◽  
Cross Sectional ◽  
Misspecified Models ◽  
Oxford University ◽  
Fama French Factors ◽  
Published Paper

Abstract We propose a methodology for estimating and testing beta-pricing models when a large number of assets is available for investment but the number of time-series observations is fixed. We first consider the case of correctly specified models with constant risk premia, and then extend our framework to deal with time-varying risk premia, potentially misspecified models, firm characteristics, and unbalanced panels. We show that our large cross-sectional framework poses a serious challenge to common empirical findings regarding the validity of beta-pricing models. In the context of pricing models with Fama-French factors, firm characteristics are found to explain a much larger proportion of variation in estimated expected returns than betas. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Using Stocks or Portfolios in Tests of Factor Models

2019 ◽  
Vol 55 (3) ◽  
pp. 709-750 ◽  
Author(s):  
Andrew Ang ◽  
Jun Liu ◽  
Krista Schwarz
Keyword(s):  
Asset Pricing ◽  
Risk Premia ◽  
Factor Models ◽  
Idiosyncratic Volatility ◽  
Standard Errors ◽  
Coefficient Estimates ◽  
Pricing Models ◽  
Cross Sectional ◽  
Factor Loadings ◽  
Asset Pricing Models

We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.

scholarly journals The Cross Section of Foreign Currency Risk Premia and Consumption Growth Risk: Comment

2011 ◽  
Vol 101 (7) ◽  
pp. 3456-3476 ◽  
Author(s):  
Craig Burnside
Keyword(s):  
Foreign Currency ◽  
Risk Premia ◽  
Expected Returns ◽  
Stochastic Discount Factor ◽  
Forward Premium Puzzle ◽  
Cross Sectional ◽  
Consumption Growth ◽  
Forward Premium ◽  
The Cross ◽  
Premium Puzzle

Lustig and Verdelhan (2007) argue that the excess returns to borrowing US dollars and lending in foreign currency “compensate US investors for taking on more US consumption growth risk,” yet the stochastic discount factor corresponding to their benchmark model is approximately uncorrelated with the returns they study. Hence, one cannot reject the null hypothesis that their model explains none of the cross sectional variation of the expected returns. Given this finding, and other evidence, I argue that the forward premium puzzle remains a puzzle. JEL: C58, E21, F31, G11, G12

scholarly journals Mood Sensitive Stocks and Sustainable Cross-Sectional Returns During the COVID-19 Pandemic: An Analysis of Day of the Week Effect in the Chinese A-Share Market

2021 ◽  
Vol 12 ◽  
Author(s):  
Qurat ul Ain ◽  
Tamoor Azam ◽  
Tahir Yousaf ◽  
Muhammad Zeeshan Zafar ◽  
Yasmeen Akhtar
Keyword(s):  
Stock Returns ◽  
Investor Sentiment ◽  
Excess Returns ◽  
Chinese Market ◽  
Market Anomalies ◽  
Cross Sectional ◽  
Day Of The Week ◽  
Stock Market Anomalies ◽  
New Evidence ◽  
A Share

This study examines two stock market anomalies and provides strong evidence of the day-of-the-week effect in the Chinese A-share market during the COVID-19 pandemic. Specifically, we examined the Quality minus Junk (QMJ) strategy return on Monday and FridayQuality stocks mean portfolio deciles that earn higher excess returns. As historical evidences suggest that less distressed/safe stocks earn higher excess returns (Dichev, 1998).. The QMJ factor is similar to the division of speculative and non-speculative stocks described by Birru (2018). Our findings provide evidence that the QMJ strategy gains negative returns on Fridays for both anomalies because the junk side is sensitive to an elevated mood and, thus, performs better than the quality side of portfolios on Friday. Our findings are also consistent with the theory of investor sentiment which asserts that investors are more optimistic when their mood is elevated, and generally individual mood is better on Friday than on other days of the week. Therefore, the speculative stocks earned higher sustainable stock returns during higher volatility in Chinese market due to COVID-19. Intrinsically, new evidence emerges on an inclined strategy to invest in speculative stocks on Fridays during the COVID-19 pandemic to gain sustainable excess returns in the Chinese A-share market.

ICAPM and the Accruals Anomaly

2020 ◽  
Vol 10 (03) ◽  
pp. 2050014 ◽  
Author(s):  
Hui Guo ◽  
Paulo Maio
Keyword(s):  
Business Cycle ◽  
Explanatory Power ◽  
Risk Premia ◽  
Key Factors ◽  
Baseline Model ◽  
Cross Sectional ◽  
Multifactor Models ◽  
Accruals Anomaly ◽  
The Business Cycle

We propose new multifactor models to explain the accruals anomaly. Our baseline model represents an application of Merton’s ICAPM in which the key factors represent (innovations on) the term and small-value spreads. The model shows large explanatory power for cross-sectional risking premia associated with three accruals portfolio groups. A scaled version of the model shows better performance, suggesting that accruals risk premia are related with the business cycle. Both models compare favorably with popular multifactor models used in the literature, and also perform well in pricing other important anomalies. The risk price estimates of the hedging factors are consistent with the ICAPM framework.

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