Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach

We develop a new multivariate generalized ARCH (GARCH) parameterization suitable for testing the hypothesis that the optimal futures hedge ratio is constant over time, given that the joint distribution of cash and futures prices is characterized by autoregressive conditional heteroskedasticity (ARCH). The advantage of the new parameterization is that it allows for a flexible form of time-varying volatility, even under the null of a constant hedge ratio. The model is estimated using weekly corn prices. Statistical tests reject the null hypothesis of a constant hedge ratio and also reject the null that time variation in optimal hedge ratios can be explained solely by deterministic seasonality and time to maturity effects.     

Heavy-tailed Behavior of Commodity Price Distribution and Optimal Hedging Demand

This study explores the importance of imposing a correct distributional hypothesis in a risk management strategy, by comparing hedge ratios under the restrictive normality assumption to those under the generalized stable distribution. Concepts are illustrated for the case of a representative Pennsylvania dairy farm manager who purchases corn as a feed input. The results show that time processes of corn prices and basis risk in five Pennsylvania regions do not correspond to the normal distribution, and they more correctly correspond to one of the stable distribution set. The estimated hedge ratios under the stable distribution are typically larger than those under the normal distribution. The difference would be a bias from imposing a wrong distributional assumption.     

The impact of hedging on the market value of equity

We examine the annual stock performance of firms that disclose the use of derivatives to hedge over the period 1995 to 1999. We find that only 21.6% of publicly traded U.S. corporations in our sample hedged with derivative instruments over this period and their use is concentrated in the larger companies. Similar to other studies we find that when derivatives are used, interest rate and currency securities are used much more frequently than commodity products. Our sample of 1308 companies that hedge outperforms other securities by 4.3% per year on average over our sample period. This result is robust to several alternative methods of estimating abnormal returns. When we segment performance by the type of hedge used, however, we find that the over-performance is due entirely to larger firms that hedge currency. We find no abnormal returns for firms hedging either interest rates or commodities. The abnormal returns in firms hedging currency is robust to alternative models that seek to control for exchange rate fluctuations and global equity returns; however, we find no significant abnormal returns to currency hedgers when using an augmented model that controls for the role of intangible assets.     

The pricing of supershares

The new ‘supershare’ securities proposed by Hakansson (1977, 1976) are subject to the same sort of rickless-hedge combinations as are other forms of secondary securities such as stock options. In consequence, the prices of supershares must, even in the absence of distributional assumptions, obey certain pricing relationships with each other and with the underlying primary security. When the primary security is assumed in addition to follow a geometric Brownian motion process, exact supershare valuation formulae of the Black-Scholes (1973) type are obtained. The ‘hedge portfolio algebra’ of Garman (1976) is employed to make the analysis concise.     

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.     

PRICING AND HEDGING SHORT STERLING OPTIONS USING NEURAL NETWORKS

This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging short sterling options. Using high‐frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging short sterling options positions using short sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model. Copyright © 2012 John Wiley & Sons, Ltd.     

The impact of derivatives on firm risk: An empirical examination of new derivative users

The appropriateness of financial reporting rules for derivative securities depends on corporations' reasons for using the instruments. Empirically, little is documented about how the instruments affect firms' risk exposures. This study examines derivatives' roles in firms initiating derivatives use. The results are consistent with firms using derivatives to hedge, and not to increase, entity risk. Firm risk (measured several ways) declines following derivatives use. Realized risk reductions and decisions to initiate derivatives programs vary across firms with the expected benefits from hedging. The findings emphasize the importance of hedge-accounting rules that incorporate the impact of derivatives and hedged items simultaneously.     

PRICING NIKKEI PUT WARRANTS: SOME EMPIRICAL EVIDENCE

The newly created Nikkei put warrants represent a recent innovation in security development. These privately issued puts enable investors to hedge or speculate on price movements in the Japanese market. Understanding the pricing behavior of these new securities provides U.S. investors and issuers with valuable information to assess potential benefits and costs. In this research two alternative pricing models are used to explain the observed prices of several privately issued Nikkei put warrants. While results from the two models indicate some pricing biases, pricing errors are very small overall.     

Do commodities make effective hedges for equity investors?

The purpose of this paper is to evaluate whether commodities are effective hedges for equity holders. We employ three different methodologies to calculate time varying hedge ratios. First, we examine time-varying hedge ratios and how much portfolio risk can be reduced relative to a long position in the S&P 500. We calculate hedge ratios from realized variances and covariances; second, we estimate a recursive multivariate GARCH (BEKK) model and calculate the hedge ratios from the estimated covariances; and thirdly, we calculate the hedge ratios by estimating recursive OLS regressions. The results of our paper are very clear. First, commodities are not effective hedges for the S&P 500. Equity market investors and asset managers looking for a way to manage and reduce portfolio risk will be well advised to search for alternative hedges for the S&P 500 than commodities. Second, our results do not support the claim that commodities were a good hedge for the equity market during the financial crisis.     

Forecasting risk,informed speculation,and financial innovation

Speculators who prey on hedgers can stifle financial innovation in the sense that new markets can fail. In this paper I analyze whether a profit maximizing exchange nonetheless chooses to open markets for speculative securities and if so, how to circumvent the problem of market failure. I find that the optimal financial innovation takes two forms. The first is a market structure consisting of hedge instruments, traded in low volume at stable asset prices. The second is a market structure consisting of speculative instruments, traded in greater volume at volatile asset prices. These strategies are derived within the same framework where the cost and the quality of the speculators' information set and the hedgers risk aversion ultimately determine which is the optimal one.     

Convertible Bond Arbitrage: Risk and Return

Abstract:  This paper specifies a simulated convertible bond arbitrage portfolio to characterise the risks in convertible bond arbitrage. For comparison the risk profile of convertible bond arbitrage hedge fund indices at both monthly and daily frequencies is also examined. Results indicate that convertible bond arbitrage is positively related to default and term structure risk factors. These risk factors are augmented with the simulated convertible bond arbitrage portfolio, mimicking a passive investment in convertible bond arbitrage, to assess the risk and return of individual hedge funds. We provide estimates of the performance of two hedge fund indices (an equally weighted and value weighted index) and a sample of convertible bond arbitrage hedge funds using a factor model methodology. Lagged and contemporaneous observations of the risk factors are specified, controlling for illiquidity in the securities held by funds. Our results cover two time periods. Initially we find evidence of abnormal risk adjusted returns in the individual hedge fund data and the equally weighted hedge fund index and no evidence of abnormal risk adjusted returns in the value weighted hedge fund index. When we examine performance during the credit crisis of 2007 and 2008 we find evidence of negative abnormal returns amongst individual hedge funds and the hedge fund indices.     

Hedging bonds subject to credit risk

This paper provides a simple and practical approach to hedging bonds that are subject to credit risk. Three new hedge ratios are derived and tested and the roles of basis risk and diversification is investigated. Empirical tests reveal that basis risk is an important factor in hedging corporate bonds. These tests identify a need for new interest rate derivatives where the underlying asset is subject to credit risk.     

Optimal hedging of demographic risk in life insurance

A Markov chain model is taken to describe the development of a multi-state life insurance policy or portfolio in a stochastic economic?Cdemographic environment. It is assumed that there exists an arbitrage-free market with tradeable securities derived from demographic indices. Adopting a mean-variance criterion, two problems are formulated and solved. First, how can an insurer optimally hedge environmental risk by trading in a given set of derivatives? Second, assuming that insurers perform optimal hedging strategies in a given derivatives market, how can the very derivatives be designed in order to minimize the average hedging error across a given population of insurers? The paper comes with the caveat emptor that the theory will find its prime applications, not in securitization of longevity risk, but rather in securitization of catastrophic mortality risk.     

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.     

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 FUTURES HEDGE WITH MARKING-TO-MARKET AND STOCHASTIC INTEREST RATES

We investigate the effect of marking-to-market on an optimal futures hedge under stochastic interest rates. An intertemporal optimal hedge ratio that accounts for basis risk and marking-to-market is derived. This ratio includes all previous hedge ratios, with constant interest rates as special cases. In a preliminary empirical study using S&P 500 index futures contracts, we demonstrate that the futures-forward hedging differential is nontrivial, especially in risk-return optimization. We also show that the covariances between interest rates and spot and futures prices explain the differential: the larger the covariances are, the larger the differential will be.     

The absorption effect of US Treasury auctions

An event study methodology shows that the relative yields of off-the-run Treasury securities are not insulated from the effects related to the auction calendar. A statistically significant but short-lived increase in relative yields is associated with the introduction of additional cashflows at corresponding and neighboring horizons. This absorption effect, where the additional supply of cashflows is associated with lower prices, is identified separately from the liquidity effect, where newly auctioned issues obtain higher prices. While sensitive to the specification of event window, an analogous methodology employed for on-the-run bonds, finds a 1-day negative effect at the benchmark 5-, 10-, and 30-year horizons.     

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.     

The long-run relationship between stock prices and goods prices: New evidence from panel cointegration

We examine the long-run relationship between stock prices and goods prices to gauge whether stock market investment can hedge against inflation. Data from 16 OECD countries over the period 1970–2006 are used. We account for different inflation regimes with the use of sub-sample regressions, while maintaining the power of tests in small sample sizes by combining time-series data across our sample countries in a panel unit root and panel cointegration econometric framework. The evidence supports a positive long-run relationship between goods prices and stock prices with the estimated goods price coefficient being in line with the generalized Fisher hypothesis.     

Comparing Trading Performance of the Constant and Dynamic Hedge Models: A Note

The constant and dynamic hedge models, with the presence of transaction costs are compared for the Share Price Index futures contract trading on the Sydney Futures Exchange. The optimal hedge ratio is estimated by using a dynamic, bivariate two-stage model for the return equation with a dynamic GARCH error structure for the conditional hedge ratios. When portfolio projections are compared based on their profit positions (net of transaction costs), the GARCH hedge model dominates the next best competitor in terms of trading profit.