This study investigates the distributions of returns on crude oil, heating oil and natural gas futures. Given substantial evidence of kurtosis and skewness in the returns, wavelet analysis is used to investigate the local correlation in time-frequency space between these three types of energy futures. In all three series, volatility is much more prevalent at shorter frequencies. This suggests that the departure from normality, and thus the trading risk, is greater at shorter timescales. In addition, the wavelet coherences between the returns on energy futures indicate high correlations over lower frequencies between 2005 and 2010, with the returns on crude oil futures often serving as the volatility leader. The results demonstrate the capability of wavelet analysis in processing nonstationary data and its ability to reveal causality. In addition, this study suggests that risk management based on the assumption of a normal distribution has limited applicability.