Interest Rate Risk and the Cross Section of Stock Returns

2014 ◽  
Vol 49 (2) ◽  
pp. 483-511 ◽  
Author(s):  
Abraham Lioui ◽  
Paulo Maio
Keyword(s):  
Asset Pricing ◽  
Interest Rate ◽  
Stock Returns ◽  
Cross Section ◽  
Interest Rate Risk ◽  
Pricing Model ◽  
Nested Models ◽  
Asset Pricing Model ◽  
Rate Risk ◽  
The Cross

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.

scholarly journals Asset Pricing Model (CAPM) in Emerging Markets: Evidence in BRICS nations and comparisons with other G20

2019 ◽  
Vol 11 (2) ◽  
pp. 162-175
Author(s):  
Cláudio Francisco Rezende ◽  
Vinícius Silva Pereira ◽  
Antonio Sergio Torres Penedo
Keyword(s):  
Asset Pricing ◽  
Interest Rate ◽  
Risk Premium ◽  
Fixed Effects ◽  
Interest Rate Risk ◽  
Pricing Model ◽  
Risk Premiums ◽  
Asset Pricing Model ◽  
Rate Risk ◽  
The Interest Rate

The objective of this paper is to empirically investigate the applicability of the asset pricing model in a portfolio made up of groups of countries, the G20 for this case. In the meantime, it was intended to compare a complete sample of 14 constituent countries of the group, a subsample of four countries belonging to the BRICS and another of the countries that do not belong. The survey sample consisted of long-term interest rate data from these countries collected in the OECD database and also from the Central Bank of Brazil (Bacen). Based on the results of the regression of Panel data on fixed effects, we found evidence that there is a statistically positive relationship between the market risk premium and the interest rate risk premiums. The regression betas showed that the interest rate risk premium is not sensitive when considering the full sample of the G20 countries but is sensitive in the BRICS sample.

scholarly journals Technology prospect and the cross-section of stock returns: evidence from the Australian market

2013 ◽  
Vol 11 (1) ◽  
pp. 295-303
Author(s):  
Qi Shi ◽  
Ali F. Darrat ◽  
Bin Li ◽  
Richard Chung
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Cross Section ◽  
Factor Models ◽  
Estimation Methods ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
The Cross ◽  
Three Factor

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.

scholarly journals A Statistical Factor Asset Pricing Model Versus the 4-Factor Model

2019 ◽  
Vol 16 (4) ◽  
pp. 545
Author(s):  
Verônica De Fátima Santana ◽  
Alex Augusto Timm Rathke
Keyword(s):  
Time Series ◽  
Asset Pricing ◽  
Cross Section ◽  
Factor Model ◽  
Abnormal Returns ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Statistical Factor ◽  
The Cross ◽  
Section Dimension

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.

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