Dynamic Hedging Effectiveness in South Korean Index Futures and the Impact of the Asian Financial Crisis

This paper focuses on the impact of the 1997 Asian financial market crisis upon hedging effectiveness within the KOSPI 200 stock index and index futures markets. The paper utilizes the inter-temporal relationship between the two markets to examine the characteristics of several minimum variance hedge ratios. It also examines the performances of alternative hedging strategies for dynamic portfolio management in the presence of cointegrated time-varying risks. The results show a decline in the persistence of conditional volatility within market prices after the crisis. This decline leads to the relative performance of utilizing constant hedge ratios to increase, though not significantly so to guarantee a superior performance over more sophisticated time-varying hedge ratio strategies.     

STOCK INDEX FUTURES HEDGING: HEDGE RATIO ESTIMATION, DURATION EFFECTS, EXPIRATION EFFECTS AND HEDGE RATIO STABILITY

This paper examines hedging effectiveness for the FTSE-100 Stock Index futures contract from 1984 to 1992. It investigates the appropriate econometric technique to use in estimating minimum variance hedge ratios by undertaking estimations using OLS, an ECM and GARCH. Simple OLS outperforms more complex econometric techniques. Additionally, the paper examines the impact ofhedge duration and time to expiration on estimated hedge ratios and hedge ratio stability over time. It is shown that hedge ratios and hedging effectiveness increase with hedge duration, hedge ratios approach unity as expiration approaches and while hedge ratios vary over time they are stationary.     

Hedging effectiveness of the Athens stock index futures contracts

This paper examines the hedging effectiveness of the FTSE/ATHEX-20 and FTSE/ATHEX Mid-40 stock index futures contracts in the relatively new and fairly unresearched futures market of Greece. Both in-sample and out-of-sample hedging performances using weekly and daily data are examined, considering both constant and time-varying hedge ratios. Results indicate that time-varying hedging strategies provide incremental risk-reduction benefits in-sample, but under-perform simple constant hedging strategies out-of-sample. Moreover, futures contracts serve effectively their risk management role and compare favourably with results in other international stock index futures markets. Estimation of investor utility functions and corresponding optimal utility maximising hedge ratios yields similar results, in terms of model selection. For the FTSE/ATHEX Mid-40 contracts we identify the existence of speculative components, which lead to utility-maximising hedge ratios, that are different to the minimum variance hedge ratio solutions.     

Hedging index exchange traded funds

This paper presents an empirical comparison of the out of sample hedging performance from naïve and minimum variance hedge ratios for the four largest US index exchange traded funds (ETFs). Efficient hedging is important to offset long and short positions on market maker’s accounts, particularly imbalances in net creation or redemption demands around the time of dividend payments. Our evaluation of out of sample hedging performance includes aversion to negative skewness and excess kurtosis. The results should be of interest to hedge funds employing tax arbitrage or leveraged long–short equity strategies as well as to ETF market makers.     

Hedging with futures: Efficacy of GARCH correlation models to European electricity markets

European electricity markets have been subject to a broad deregulation process in the last few decades. We analyse hedging policies implemented through different hedge ratios estimation. More specifically we compare naïve, ordinary least squares, and GARCH conditional variance and correlations models to test if GARCH models lead to higher variance reduction in a context of high time varying volatility as the case of electricity markets. Our results show that the choice of the hedge ratio estimation model is central on determining the effectiveness of futures hedging to reduce the portfolio volatility.     

Hedging and speculative pressures and the transition of the spot-futures relationship in energy and metal markets

This paper examines the impact of hedging and speculative pressures on the transition of the spot-futures relationship in metal and energy markets. We build a Markov regime switching (MRS) model where hedging and speculative pressures affect the transition probabilities between a stronger and weaker spot-futures relationship. It is found that hedging pressure increases the likelihood of transition, i.e. destabilises the existing spot-futures relationship, while speculative pressure reduces it, i.e. stabilises the relationship, in the copper, crude oil and natural gas markets, but this effect is relatively weak in the silver and heating oil markets. We also examine whether these findings generate practical benefits by testing the hedging effectiveness of the minimum variance hedge ratios (MVH) derived from the MRS models with hedging and speculative pressures. A relatively strong reduction of the portfolio variance, hedger's utility and value at risk (VaR) is observed in the energy markets.     

Better cross hedges with composite hedging? Hedging equity portfolios using financial and commodity futures

Unless a direct hedge is available, cross hedging must be used. In such circumstances portfolio theory implies that a composite hedge (the use of two or more hedging instruments to hedge a single spot position) will be beneficial. The study and use of composite hedging has been neglected; possibly because it requires the estimation of two or more hedge ratios. This paper demonstrates a statistically significant increase in out-of-sample effectiveness from the composite hedging of the Amex Oil Index using S&P500 and New York Mercantile Exchange crude oil futures. This conclusion is robust to the technique used to estimate the hedge ratios, and to allowance for transactions costs, dividends and the maturity of the futures contracts.     

Using the short-lived arbitrage model to compute minimum variance hedge ratios: application to indices,stocks and commodities

The short-lived arbitrage model has been shown to significantly improve in-sample option pricing fit relative to the Black–Scholes model. Motivated by this model, we imply both volatility and virtual interest rates to adjust minimum variance hedge ratios. Using several error metrics, we find that the hedging model significantly outperforms the traditional delta hedge and a current benchmark hedge based on the practitioner Black–Scholes model. Our applications include hedges of index options, individual stock options and commodity futures options. Hedges on gold and silver are especially sensitive to virtual interest rates.     

Measuring minimum variance hedging effectiveness: Traditional vs. sophisticated models

This study investigates whether the more sophisticated GARCH based models are better minimum variance hedging strategies than the less sophisticated regression based traditional models. The findings of the study suggest that the traditional models that directly estimate the optimal hedge ratio significantly outperform the more sophisticated models that indirectly estimate the optimal hedge ratio based on timevarying variance-covariance parameters. Although, the sophisticated models seem to have more theoretical appeal, the higher estimation and misspecification errors of these models reduce their hedging effectiveness, making them inferior to the traditional models.     

Selective hedging strategies for crude oil futures based on market state expectations

This paper studies the ex-ante selective hedging strategies of crude oil futures contracts based on market state expectations and compares the hedging performances to the traditional minimum variance routine hedging strategies. The main advantage of the proposed method is that it achieves a trade-off between return and risk, rather than hedges risk at all costs. Specifically, we first use a multi-input Hidden Markov Model(HMM) to identify the market state, assess the market’s herding impact, and then integrate the findings of identification and measurement to forecast the price trend. We offer an adjustment criterion for the hedge ratios driven by GARCH²-type models based on the anticipated market state. We conducted an empirical analysis to examine the hedging effect of WTI and Brent crude oil futures, the results indicate that the proposed state-dependent hedging strategies are superior to the traditional model-driven hedging strategies concerning the hedged portfolio based on four criteria. The robustness check reveals that the proposed hedging strategies still outperform in different market situation. The findings can help traders in the crude oil markets, and the methodology can be applied to other energy markets.     

Intraday data and hedging efficiency in interest spread trading

Three government bond futures contracts and their respective 3-month interest rate futures contracts traded on LIFFE are examined. The data period covers three years of observations, January 1994-December 1996, sampled at half-hourly intervals. Borrowing from the calculation of minimum variance hedge ratios, half-hourly minimum variance spread ratios (the ratio of one contract to another, which provides the minimum variance) are estimated for the above contracts. The hypothesis under examination is whether there is any value-added in estimating minimum spread ratios based on intraday data. Three spread ratios are defined: two ratios calculated from daily data and a third one based on intraday data. Evidence tends to indicate that spread ratios calculated from intraday data exhibit a substantially lower variance than the other two spread ratio speciications. Thus, it is shown that intraday data, in comparison with daily data, allow for lower hedging costs. Moreover, the use of intraday-based spread ratios might be a contributing factor to reducing the maximum cumulative loss potentially incurred while holding a spread position.     

Dynamic hedging with futures: a copula-based GARCH model with high-frequency data

Modeling the joint distribution of spot and futures returns is crucial for establishing optimal hedging strategies. This paper proposes a new class of dynamic copula-GARCH models that exploits information from high-frequency data for hedge ratio estimation. The copula theory facilitates constructing a flexible distribution; the inclusion of realized volatility measures constructed from high-frequency data enables copula forecasts to swiftly adapt to changing markets. By using data concerning equity index returns, the estimation results show that the inclusion of realized measures of volatility and correlation greatly enhances the explanatory power in the modeling. Moreover, the out-of-sample forecasting results show that the hedged portfolios constructed from the proposed model are superior to those constructed from the prevailing models in reducing the (estimated) conditional hedged portfolio variance. Finally, the economic gains from exploiting high-frequency data for estimating the hedge ratios are examined. It is found that hedgers obtain additional benefits by including high-frequency data in their hedging decisions; more risk-averse hedgers generate greater benefits.     

Learning minimum variance discrete hedging directly from the market

Option hedging is a critical risk management problem in finance. In the Black–Scholes model, it has been recognized that computing a hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter dependence on the underlying price (see e.g. Coleman et al., J. Risk, 2001, 5(6), 63–89; Hull and White, J. Bank. Finance, 2017, 82, 180–190). In this paper, we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data-driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in Hull and White [J. Bank. Finance, 2017, 82, 180–190], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.     

The minimum variance hedge and the bankruptcy risk of the firm

In this paper, we analyze the influence of hedging with forward contracts on the firm's probability of bankruptcy (POB). The minimization of this probability can serve as a substitute for the maximization of shareholders' wealth. It is shown that the popular minimum variance hedge is generally neither necessary nor sufficient for the minimization of the firm's POB. Moreover, our model suggests a correction of the widespread view that a reduction in the variance of the future value of the firm is inevitably accompanied by a reduction in its default risk. We derive an analytical solution for the variance-minimizing hedge ratio of a firm exposed to both input and output price uncertainty that takes into account the issue of correlation. Based on this solution, we provide a graphical analysis to prove our claim that there is a fundamental difference between hedging policies focused on bankruptcy risk and those following conventional wisdom even if positive correlation constitutes a “natural” hedge.     

Model-free hedge ratios and scale-invariant models

A price process is scale-invariant if and only if the returns distribution is independent of the price measurement scale. We show that most stochastic processes used for pricing options on financial assets have this property and that many models not previously recognised as scale-invariant are indeed so. We also prove that price hedge ratios for a wide class of contingent claims under a wide class of pricing models are model-free. In particular, previous results on model-free price hedge ratios of vanilla options based on scale-invariant models are extended to any contingent claim with homogeneous pay-off, including complex, path-dependent options. However, model-free hedge ratios only have the minimum variance property in scale-invariant stochastic volatility models when price–volatility correlation is zero. In other stochastic volatility models and in scale-invariant local volatility models, model-free hedge ratios are not minimum variance ratios and our empirical results demonstrate that they are less efficient than minimum variance hedge ratios.     

Optimal hedge ratio and hedging effectiveness of stock index futures: evidence from India

In a free capital mobile world with increased volatility, the need for an optimal hedge ratio and its effectiveness is warranted to design a better hedging strategy with future contracts. This study analyses four competing time series econometric models with daily data on NSE Stock Index Futures and S&P CNX Nifty Index. The effectiveness of the optimal hedge ratios is examined through the mean returns and the average variance reduction between the hedged and the unhedged positions for 1-, 5-, 10- and 20-day horizons. The results clearly show that the time-varying hedge ratio derived from the multivariate GARCH model has higher mean return and higher average variance reduction across hedged and unhedged positions. Even though not outperforming the GARCH model, the simple OLS-based strategy performs well at shorter time horizons. The potential use of this multivariate GARCH model cannot be sublined because of its estimation complexities. However, from a cost of computation point of view, one can equally consider the simple OLS strategy that performs well at the shorter time horizons.     

Forward Hedging the Exchange Risks of U.S. Equity Investments in the U.K., Germany and France

This paper simulates forward hedging of foreign exchange risks for U.S. investments in U.K., German and French equities. Rolling OLS and SUR regressions are used to obtain monthly exposure coefficients (hedge ratios), and the micro-market mechanics of the exchange rate bid-ask spread are considered throughout. While the coefficient of variation favors not hedging, no statistically significant differences are found between no hedge and hedge strategies. However, hedging produces a nontrivial incidence of cases where liquidated foreign equity values are less than amounts sold forward. The results, robust to rising and falling dollar sub-periods, do not support forward hedging.     

The use and abuse of the hedging effectiveness measure

Ederington (1979) proposed an effectiveness measure for futures hedging. Since then, this measure has been widely adopted in the literature to compare different hedge ratios against the OLS (ordinary least squares) hedge ratio. This note attempts to demonstrate this application is inappropriate. Ederington hedging effectiveness is only useful for measuring the risk reduction effect of the OLS hedge ratio. It does not apply to other hedge ratios and therefore should not serve as a criterion to compare different hedge strategies against the OLS strategy. A strict application of this measure almost always leads to an incorrect conclusion stating that the OLS hedge ratio is the best hedging strategy.     

Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets

The dynamic minimum variance hedge ratios (MVHRs) have been commonly estimated using the Bivariate GARCH model that overlooks the basis effect on the time-varying variance–covariance of spot and futures returns. This paper proposes an alternative specification of the BGARCH model in which the effect is incorporated for estimating MVHRs. Empirical investigation in commodity markets suggests that the basis effect is asymmetric, i.e., the positive basis has greater impact than the negative basis on the variance and covariance structure. Both in-sample and out-of-sample comparisons of the MVHR performance reveal that the model with the asymmetric effect provides greater risk reduction than the conventional models, illustrating importance of the asymmetric effect when modeling the joint dynamics of spot and futures returns and hence estimating hedging strategies.     

The hedging effect of green bonds on carbon market risk

This paper explores effective hedging instruments for carbon market risk. Examining the relationship between the carbon futures returns and the returns of four major market indices, i.e., the VIX index, the commodity index, the energy index and the green bond index, we find that the connectedness between the carbon futures returns and the green bond index returns is the highest and this connectedness is extremely pronounced during the market's volatile period. Further, we develop and evaluate hedging strategies based on three dynamic hedge ratio models (DCC-APGARCH, DCC-T-GARCH, and DCC-GJR-GARCH models) and the constant hedge ratio model (OLS model). Empirical results show that among the four market indices the green bond index is the best hedge for carbon futures and performs well even in the crisis period. The paper also provides evidence that the dynamic hedge ratio models are superior to the OLS model in the volatile period as more sophisticated models can capture the dynamic correlation and volatility spillover between the carbon futures and market index returns.