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This paper empirically examines the intraday price relationship between S&P 500 futures and the S&P 500 index using minute‐to‐minute data. Three‐stage least‐squares regression is used to estimate lead and lag relationships with estimates for expiration days of the S&P 500 futures compared with estimates for days prior to expiration. The results suggest that futures price movements consistently lead index movements by twenty to forty‐five minutes while movements in the index rarely affect futures beyond one minute.

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This study compares two alternative regression specifications for sizing hedge positions and measuring hedge effectiveness: a simple regression on price changes and an error correction model (ECM). We show that, when the prices of the hedged item and the hedging instrument are cointegrated, both specifications yield similar results which depend on the hedge horizon (i.e., the time frame for measuring price changes). In particular, the estimated hedge ratio and regression R 2 will both be small when price changes are measured over short intervals, but as the hedge horizon is lengthened both measures will converge toward one. These results imply that, when prices are cointegrated, a longer hedge horizon will yield an optimal hedge ratio closer to one, while at the same time enhancing the ability to qualify for hedge accounting.The Financial Accounting Standards Board (FASB) has recently released an exposure draft that, if enacted, would lower the requirement from "highly" effective to "reasonably" effective. It is not clear whether or how this change would affect the current practice of requiring the regression R 2 statistic to be at least 0.80. 4 Levy and Sarnat (1984) and Marmer (1986) discuss various drawbacks to the textbook approach. Schneeweis (1981, 1982) and Dale (1981) debate use of a simple regression on price levels versus price changes.

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