Long memory and structural breaks in commodity futures markets

Abstract

to explore the impact of the time series properties of the futures-spot basis and the cost of carry on forward market unbiasedness. The main result is that the basis of 16 assets exhibits both long memory and structural breaks. The long memory in the basis is robust even to the use of break-adjusted data. It implies that the cost-of-carry has long memory which the empirical results confirm using the interest cost as a proxy. These new findings suggest that the forecast error has long memory and are inconsistent with unbiasedness. They could be consistent with a weaker version of market efficiency in the presence of a fractionally integrated, time-varying risk premium but they could also be rationalized Long Memory and Structural Breaks 1077Journal of Futures Markets DOI: 10.1002/fut by priced noise trader risk with limits to arbitrage in less than fully efficient markets.

Realized Volatility Forecasting of Agricultural Commodity Futures Using Long Memory and Regime Switching

“…Following Coakley et al . (), we employ the ARFIMA(1, d ,0) and ARFIMA(1, d ,1) models to estimate the fractional differencing parameter d and employ t ‐statistics to test the estimated d . The null for no long memory and for a unit root are H 0 : d = 0 and H 0 : d = 1 respectively.…”

“…Therefore, these series may be better characterized by a fractionally integrated or I(d) process. Following Coakley et al (2011), we employ the ARFIMA(1,d,0) and ARFIMA(1,d,1) models to estimate the fractional differencing parameter d and employ t-statistics to test the estimated d. The null for no long memory and for a unit root are H 0 : d = 0 and H 0 : d = 1 respectively. Panel B of Table 2 presents the test results for all realized volatility series.…”

Testing the Persistence of the Forward Premium: Structural Changes or Misspecification?

“…However, the literature has yet definitively to resolve the puzzle. Looking at 16 futures-spot basis as well as the forward premium in the exchange rate market, Coakley et al (2011)'s findings point to a rejection of the unbiasedness hypothesis when considering multiple breaks in the mean. Moreover, Chen and Yu (2011) find results contrary to Sakoulis et al (2010), where high persistence property is detected in the forward premium when the structural breaks are incorporated in the regression.…”

Spurious long memory, uncommon breaks and the implied–realized volatility puzzle

“…A frequently adopted approach (see Coakley et al, 2011, Choi et al, 2010, Kellard and Sarantis, 2008, and Choi and Zivot, 2007 to estimate multiple structural breaks is due to Bai and Perron (1998, 2003a, 2003b. To explain, consider the m -breaks in mean model below A useful attribute of the Perron (1998, 2003a) method is that their test statistics 12 can be generated under reasonably general specifications.…”