The incremental value of a futures hedge using realized volatility

Abstract

A number of prior studies have developed a variety of multivariate volatility models to describe the joint distribution of spot and futures, and have applied the results to form the optimal futures hedge. In this study, the authors propose a new class of multivariate volatility models encompassing realized volatility (RV) estimates to estimate the risk-minimizing hedge ratio, and compare the hedging performance of the proposed models with those generated by return-based models. In an out-of-sample context with a daily rebalancing approach, based on an extensive set of statistical and economic performance measures, the empirical results show that improvement can be substantial when switching from daily to intraday. This essentially comes from the advantage that the intraday-based RV potentially can provide more accurate daily covariance matrix estimates than RV utilizing daily prices. Finally, this study also analyzes the effect of hedge horizon on hedge ratio and hedging effectiveness for both the in-sample and the out-of-sample data.

Incremental Value of a Futures Hedge Using Realized Ranges

“…Second, the persistence of volatility implied by BEKK(RR) approximates unity, which is greater than 0.9676 suggested by BEKK(Daily) . This is similar to the result of Lai and Sheu (). They indicated that the persistence for S&P 500 position is about 0.9999 when GARCH estimations utilize intraday returns.…”

“…Lai and Sheu () showed that the improvement in hedging effectiveness is substantial when switching from daily to intraday returns; that is, they focused on comparing the performance of BEKK(Daily) and BEKK(RV). We compare the performance of spot–futures positions with the augmented model based on daily returns, intraday price returns, and intraday price ranges and their combinations.…”

Cojumping: Evidence from the US Treasury bond and futures markets

“…1 Intraday portfolio management involves recognizing and responding to such jumps. In particular, Lai and Sheu (2010) demonstrate that the use of realized volatility measures, which incorporate jump behaviors, compiled from high frequency data delivers measurable improvements in hedging performance, while Todorov and Bollerslev (2010) estimate distinct betas for jump risk on individual stocks. These findings reinforce the potential gains from time varying hedge ratios, such as demonstrated in Brooks et al (2002).…”

Optimal Hedging in Carbon Emission Markets Using Markov Regime Switching Models

“…Lien and Yang (2008) argue that the lagged basis can help to determine the movement of spot and futures prices and facilitate the mean-reverting process, and therefore can serve as the proxy for the long-run relationship. Kroner and Sultan (1993) and Lai and Sheu (2010), among others, also use the lagged basis as the proxy for the long-run relationship. Therefore, we use the lagged basis to measure the long-run relationship of spot and future prices in this paper.…”