This paper studies the performance and persistence of Norwegian mutual funds utilizing a new data set of daily returns. Daily data allow us to evaluate the performance over short time horizons in a reliable manner, which is important because the risk exposure of funds can change over time. We complement the existing literature by providing the first study based on daily data outside of the US. Our results show that the performance of top and bottom funds cannot be explained by luck. The performance of these top and bottom funds persists for short horizons, of only up to one year. The mutual fund industry as a whole underperforms the benchmark by approximately the fund fees.

We examine the information content of the CBOE Crude Oil Volatility Index (OVX) when forecasting realized volatility in the WTI futures market. Additionally, we study whether other market variables, such as volume, open interest, daily returns, bid-ask spread and the slope of the futures curve, contain predictive power beyond what is embedded in the implied volatility. In out-of-sample forecasting we find that econometric models based on realized volatility can be improved by including implied volatility and other variables. Our results show that including implied volatility significantly improves daily and weekly volatility forecasts; however, including other market variables significantly improves daily, weekly and monthly volatility forecasts.