The article explores different trading strategies used by Commodity Trading Advisors (CTAs) by analyzing daily returns from 89 programs. The researchers found that daily data shows characteristics like fat-tail distributions, volatility clustering, and long memory in volatility, which are not typically seen in monthly data. This suggests that relying solely on monthly data may not provide an accurate picture of market behavior for CTAs.