A Simple Consumption-Based Asset Pricing Model and the Cross-Section of Equity Returns

2013 ◽  
Author(s):  
Robert F. Dittmar ◽  
Christian T. Lundblad
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.


Author(s):  
Ume Salma Akbar ◽  
Niaz Ahmed Bhutto ◽  
Suresh Kumar Oad Rajput

In this study, I extend the Fama and French five-factor asset pricing model with a sixth factor, namely, carbon risk, to investigate its impact on equity returns. To measure carbon risk, a new factor ‘pollutant minus green,’ is developed using the difference between the weighted average returns of pollutant and green firms across 51 developed and emerging countries across four categories—North America, Europe, Emerging Markets, and the Asia Pacific. The results reveal that North America, Europe, and Asia Pacific markets have a carbon risk premium that gets eliminated in small-cap firms. The carbon risk factor is further tested in left-hand side (LHS) test asset portfolios and found to be more pronounced with size-effect anomaly; specifically, small stock firms report greater declining average returns because of more exposure than the mega-cap stocks to carbon dioxide emissions. Furthermore, size-effect anomaly prevails with profitability and investment factors across firms. Therefore, high profitability, as well as high investment small firms, show a greater decline than the big stock firms in average returns when their carbon dioxide emissions increase. The asset pricing model evaluation is carried out through the Gibbons, Ross, and Shanken test. The six-factor model directed at capturing carbon risk patterns in average equity returns performs better than the three-factor and five-factor models of Fama and French (1993 and 2015) in the majority of categories under 3x3 sorting and compete with both Fama and French model under 2x4x4 sorted LHS portfolios. The finding of this study offers various useful applications for investors, policymakers, brokers, corporations, governmental pollution abatement institutions, and other stakeholders who wish to obtain carbon risk premium.


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