What Does the Cross-Section Tell About Itself? An Asset Pricing Model with Cross-Sectional Moments

2007 ◽  
Author(s):  
Paulo F. Maio
2014 ◽  
Vol 49 (2) ◽  
pp. 483-511 ◽  
Author(s):  
Abraham Lioui ◽  
Paulo Maio

AbstractWe derive a macroeconomic asset pricing model in which the key factor is the opportunity cost of money. The model explains well the cross section of stock returns in addition to the excess market return. The interest rate factor is priced and seems to drive most of the explanatory power of the model. In this model, both value stocks and past long-term losers enjoy higher average (excess) returns because they have higher interest rate risk than growth/past winner stocks. The model significantly outperforms the nested models (capital asset pricing model (CAPM) and consumption CAPM (CCAPM)) and compares favorably with alternative macroeconomic models.


2013 ◽  
Vol 11 (1) ◽  
pp. 295-303
Author(s):  
Qi Shi ◽  
Ali F. Darrat ◽  
Bin Li ◽  
Richard Chung

We examine the link between technology prospect and stock returns in the Australian market. Our results suggest that the technology-based asset pricing model outperforms the CAPM and Fama-French three-factor models in explaining the cross-section of the Australian Fama-French 25 size/book-to-market portfolios. The results prove robust to using alternative estimation methods and continue to supports the importance of the technology factor for shaping the cross section of the Fama-French portfolios returns.


2019 ◽  
Vol 16 (4) ◽  
pp. 545
Author(s):  
Verônica De Fátima Santana ◽  
Alex Augusto Timm Rathke

This research aims to compare the performance of a statistical factor asset pricing model with the Fama-French-Carhart 4-factor model. We perform a Principal Component Analysis (PCA) to extract latent risk factors using data of stocks listed on B3 from 2001 to 2015. We test the abilities of the two models to explain assets' returns both in the time-series and in the cross-section dimension. We found that the statistical factor models generates statistically significant abnormal returns in the time-series analysis while the 4-factor model does not. In the cross section dimension, neither model generates significant abnormal returns but they also are not able to generate positive risk premia. Similar results are found if we consider different sets of time and assets. Therefore, although the 4-factor model performs slightly better in the set of tests, neither of the models can be considered fully adequate to explain expected returns of assets in the Brazilian stock market.


Author(s):  
Adriano Mussa ◽  
Pablo Rogers ◽  
José Roberto Securato

Metodologias preditivas para teste de modelos de retornos esperados são amplamente difundidas no meio acadêmico internacional, entretanto, não têm sido sistematicamente aplicadas no Brasil. Geralmente, os estudos empíricos procedidos com dados do mercado acionário brasileiro concentram-se apenas na primeira etapa dessas metodologias. O objetivo deste artigo foi testar e comparar os modelos CAPM (Capital Asset Pricing Model), 3-fatores e 4-fatores a partir de uma metodologia de teste preditivo, utilizando duas etapas – regressões em séries temporais e cross-section – com erros-padrão calculados pela técnica de Fama e Macbeth (1973). Apesar dos resultados indicarem a superioridade do modelo 4- fatores em relação ao modelo 3-fatores, e esse em relação ao CAPM, nenhum dos modelos testados foram suficientes na explicação das variações dos retornos das ações do mercado brasileiro. Contrário a algumas evidências empíricas que não utilizam a metodologia preditiva, os efeitos tamanho e momento parecem não estar presentes no mercado de capitais brasileiro, enquanto há indícios da presença do efeito valor e relevância do mercado em explicar retornos esperados. Os achados dessa pesquisa levantaram alguns questionamentos, principalmente, devido à originalidade metodológica no mercado nacional e o tema ser ainda incipiente e polêmico no meio acadêmico brasileiro.


2019 ◽  
Vol 12 (4) ◽  
pp. 165 ◽  
Author(s):  
Zaremba

The last three decades brought mounting evidence regarding the cross-sectional predictability of country equity returns. The studies not only documented country-level counterparts of well-established stock-level anomalies, such as size, value, or momentum, but also demonstrated some unique return-predicting signals such as fund flows or political regimes. Nonetheless, the different studies vary remarkably in terms of their dataset and methods employed. This study aims to provide a comprehensive review of the current literature on the cross-section of country equity returns. We focus on three particular aspects of the asset pricing literature. First, we study the choice of dataset and sample preparation methods. Second, we survey different aspects of the methodological approaches. Last but not least, we review the country-level equity anomalies discovered so far. The discussed cross-sectional return patterns not only provide new insights into international asset pricing but can also be potentially translated into effective country allocation strategies.


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