An Empirical Study on the Determinants of Korean Won Denominated Exchange Risk Premium : The Equity Risk Factors Approach

2003 ◽  
Vol 7 (1) ◽  
pp. 25
Author(s):  
Yoon-Goo Lee ◽  
Kyung-Il Khoe
2018 ◽  
Vol 26 (3) ◽  
pp. 311-343
Author(s):  
Sungjeh Moon ◽  
Joonhyuk Song

This paper introduces two risk factors which are the covariance between long-run consumption growth and cash flows and the duration of cash flow, and investigates how these factors serve to explain the KOSPI return risk premiums. Based on our empirical results comparing the proposed two-factor cash flow model with the standard benchmark models such as CAPM and Fama-French 3-factor model (FF-3F), using KOSPI equity including de-listed stocks, the cash flow model explains 74.7% of the cross-section of equity risk premium while CAPM and FF-3F model explains 41.9% and 64.1% to the maximum, respectively, showing that the cash-flow model is superior in explaining the risk premium factor structure compared with the benchmark models. Also, the pricing error is only 4% in the two-factor cash flow model, while CAPM and FF-3F are 7.7% and 4.7%, respectively, indicating the cash flow model outperforms the standard benchmark models in pricing error as well. These results can be interpreted that the cross section of the equity risk premium is related to a firm’s cash flow and long-run consumption, and therefore the growth rate of consumption in the long run rather than contemporaneous consumption growth rate has a greater influence on the determination of the risk premium.


2019 ◽  
Vol 12 (2) ◽  
pp. 91
Author(s):  
Jian Huang ◽  
Huazhang Liu

To search significant variables which can illustrate the abnormal return of stock price, this research is generally based on the Fama-French five-factor model to develop a multi-factor model. We evaluated the existing factors in the empirical study of Chinese stock market and examined for new factors to extend the model by OLS and ridge regression model. With data from 2007 to 2018, the regression analysis was conducted on 1097 stocks separately in the market with computer simulation based on Python. Moreover, we conducted research on factor cyclical pattern via chi-square test and developed a corresponding trading strategy with trend analysis. For the results, we found that except market risk premium, each industry corresponds differently to the rest of six risk factors. The factor cyclical pattern can be used to predict the direction of seven risk factors and a simple moving average approach based on the relationships between risk factors and each industry was conducted in back-test which suggested that SMB (size premium), CMA (investment growth premium), CRMHL (momentum premium), and AMLH (asset turnover premium) can gain positive return.


2002 ◽  
Vol 2002 (3) ◽  
pp. 37-48 ◽  
Author(s):  
Peter L. Bernstein

2004 ◽  
Author(s):  
Rui M. Alpalhão ◽  
Paulo F. Pereira Alves

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