The Effect of the Hedge Horizon on Optimal Hedge Size and Effectiveness When Prices are Cointegrated

Abstract

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.

Hedging Ratio Measurement Methods and Hedging Effectiveness in Jakarta Futures Exchanges

“…Time varying hedge ratio assumes the spot price volatility have a changing correlation, that varies over time, with price volatility futures. Assumptions of time varying hedge ratio is pretty much supported by previous research as showed by Cotter and Hanly (2012) and Juhl et al (2012). However, the implementation of time varying hedge ratio requires higher cost because hedge ratio can vary over time reflecting correlation of spot and futures price volatility.…”

“…It is found also by Gupta and Kaur (2015) in India, Bhargava and Malhotra (2007) in some Asian countries, and Lien (2005) in the United States and some European countries. Juhl et al, (2012) show the effectiveness of hedging strategy in the short term by using simpler method is higher than using the more complex method. Some researchers suggest that the effectiveness of hedging strategy is not only influenced by appropriate hedge ratio measurement method but also affected by market liquidity conditions (Gupta and Singh, 2009) and asymmetric behavior of spot and futures price volatility (Cotter and Hanly, 2012).…”

“…The simplest static hedge ratio is estimated by using OLS regression model. This simplest hedge ratio is problematic when there is a contegration relationship between spot price and futures price (Juhl, et al 2012). Time varying hedge ratio assumes the spot price volatility have a changing correlation, that varies over time, with price volatility futures.…”

“…TARCH or Threshhold ARCH is used to accommodate the asymmetric behavior of spot and futures prices. The effectiveness of hedging strategy by implementing this three hedge ratio will be tested by using hedging effectiveness measures which is generally used also in previous research, for example, Cotter and Hanly (2012) and Juhl et al (2012). By revealing the effectiveness of the hedging strategy implementing this three different methods of hedge ratios measures, this study is not only an academic empirical test that help us to deeper understandings of less liquid commodity futures exchange such as in Indonesia, but also give an important reference for practitioners in developing hedging strategies and how to implement those strategy in Indonesia futures exchanges context.…”

Performance of Utility Based Hedges

“…We estimate and compare optimal utility based hedges using performance metrics based on the underlying optimization criteria as well as an economic comparison between the different hedging models using Value at Risk (VaR). Given the potential impact of hedge horizon on optimal hedges (see Juhl, Kawaller and Koch, 2012) we estimate hedge strategies across three time horizons, daily, weekly and monthly. For our analysis we use two of the most broadly used characterisations of investor utility; quadratic and exponential.…”