It has been shown that the univariate distributions and other properties of asset returns are sensitive to the data frequency, but the effects of the data frequency on the dependence among returns have hardly been explored. The paper seeks to fill this gap by analyzing the impact of frequency changes on the dependence structure across the returns of 100 highly-traded American stocks and the market return over the period 2000-2010. It shows that in some cases, the association between stock returns and the market return changes according to the data frequency and, in general, investments based on monthly trades tend to be more conservative than investments made on a daily basis.

There is ample evidence in the literature concerning the difference in some properties of univariate asset returns at diverse frequencies. Nonetheless, studies on the impact of the frequency variation on the dependence across returns are scarce. The paper aims to provide further insights into this issue by verifying the dependence structure between stock returns and market return at two different frequencies (daily and monthly).

The study analyzes 100 American stocks during the period 2000-2010 and concludes that data frequency affects the relationship between the return of each stock and the overall market return. The main practical implication of this study is that trading frequency has an influence on investment risk profile such that daily trades tend to yield more speculative results than monthly trades. That is, the probability of joint extreme events (losses or gains) in daily data is higher than in monthly data for most of the stocks considered.

Financial Risk Management Journal, The paper, analyzing, the impact, frequency, dependence structure, 100 highly-traded American stocks, the market return, 2000-2010.