What explains long memory in futures price volatility?

Long memory in futures price volatility is a well-documented stylized fact with implications for market efficiency, risk management, forecasting and option pricing bias. The implications of long-memory differ, however, based on whether it is of a 'fractional' or of a 'stochastic' type. The aims of this article are to determine, in the case of agricultural commodity futures data, which type better describes price volatility and also to evaluate several competing explanations for findings of long memory. The evidence presented here finds little support for three out of four potential explanations, namely, excessive noise in the volatility measure, bias in the long-memory estimator and understated SEs of the long-memory parameter. For the data considered, price volatility appears to be most likely generated by a nonfractional long-memory process such as a stochastic break or stochastic unit root.