The purpose of the paper is to study the relationship between stock return correlation and volatility.
Abstract
Purpose
The purpose of the paper is to study the relationship between stock return correlation and volatility.
Design/methodology/approach
Utilizing a logit‐type regression model, the paper analyzes the incremental effect of volatility on the level of correlation. The focus of the paper is set on the impact of the volatilities involved in the definition and calculation of the correlation as well as on the effects of external volatilities from other markets.
Findings
In the paper, an explicit model was constructed to investigate the contribution of the level of volatility on mutual correlations of the markets. The empirical results strongly support the findings that high volatility tends to increase correlations between the markets (see for example). An analysis of the small Nordic markets further showed that the local volatilities may play a role in the change of the level of correlation. However, it is the general world‐wide volatility level that mainly drives the changes in the correlations.
Originality/value
Particularly, the results of the paper show that market correlations tend to be dependent on the general world‐wide volatility rather than on local volatilities of single markets. This approach gives us important information about the behavior of the correlation with respect to the level of each market's risk as well as to the general global market‐risk level. The results can be directly utilized by portfolio managers in planning portfolio diversification strategies in accordance with the expected future volatility.
Details
Keywords
In the paper we provide new evidence on the predictability of Scandinavian stock returns, when utilizing the determinants of global capital asset pricing. Three factors are…
Abstract
In the paper we provide new evidence on the predictability of Scandinavian stock returns, when utilizing the determinants of global capital asset pricing. Three factors are extracted by principal components factor analysis. The VARIMAX‐rotated factor loadings matrix clearly suggests the presence of geographically distinguished returns generating factors: Europe, Asia and America. The corresponding factor price series are used as driving forces for the Finnish and Swedish market returns. The results indicate that the predictability of Scandinavian stock returns is significantly improved by the world factors.