The Asymmetric Commodity Inventory Effect on the Optimal Hedge Ratio

Hedging strategies for commodity prices largely rely on dynamic models to compute optimal hedge ratios. This study illustrates the importance of considering the commodity inventory effect (effect by which the commodity price volatility increases more after a positive shock than after a negative shock of the same magnitude) in modeling the variance–covariance dynamics. We show by in‐sample and out‐of‐sample forecasts that a commodity price index portfolio optimized by an asymmetric BEKK–GARCH model outperforms the symmetric BEKK, static (OLS), or naïve models. Robustness checks on a set of commodities and by an alternative mean‐variance optimization framework confirm the relevance of taking into account the inventory effect in commodity hedging strategies.     

Production and hedging under Knightian uncertainty

This article introduces Knightian uncertainty into the production and futures hedging framework. The firm has imprecise information about the probability density function of spot or futures prices in the future. Decision‐making under such scenario follows the “max‐min” principle. It is shown that inertia in hedging behavior prevails under Knightian uncertainty. In a forward market, there is a region for the current forward price within which full hedge is the optimal hedging policy. This result may help explain why the one‐to‐one hedge ratio is commonly observed. Also inertia increases as the ambiguity with the probability density function increases. When hedging on futures markets with basis risk, inertia is established at the regression hedge ratio. Moreover, if only the futures price is subject to Knightian uncertainty, the utility function has no bearing on the possibility of inertia. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20: 397–404, 2000     

A note on estimating the minimum extended Gini hedge ratio

The extended Gini coefficient, Γ, is a measure of dispersion with strong theoretical merit for use in futures hedging. Yitzhaki (1982, 1983) provides conditions under which a two-parameter framework using the mean and Γ of portfolio returns yields an efficient set consistent with second-order stochastic dominance. Unlike mean-variance theory, the mean-Γ framework requires no particular return distribution or utility function to yield this conclusion. However, Γ must be computed iteratively making it less convenient to use than variance. Shalit (1995) offers a solution to the computation problem by suggesting an instrumental variables (IV) slope estimator, β^IV, as the basis for the minimum extended Gini hedge ratio where the instruments are based on the empirical distribution function (edf) of futures prices. However, the validity of employing the IV slope coefficient as the basis for the minimum extended Gini hedge ratio requires the questionable assumption that the rankings of futures prices to be the same as those for the profits of the hedged portfolio. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19:101–113, 1999     

The incremental value of a futures hedge using realized volatility

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. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:874–896, 2010     

An empirical analysis of the relationship between the hedge ratio and hedging horizon: A simultaneous estimation of the short‐ and long‐run hedge ratios

This article analyzes the effects of the length of hedging horizon on the optimal hedge ratio and hedging effectiveness using 9 different hedging horizons and 25 different commodities. We discuss the concept of short‐ and long‐run hedge ratios and propose a technique to simultaneously estimate them. The empirical results indicate that the short‐run hedge ratios are significantly less than 1 and increase with the length of hedging horizon. We also find that hedging effectiveness increases with the length of hedging horizon. However, the long‐run hedge ratio is found to be close to the naïve hedge ratio of unity. This implies that, if the hedging horizon is long, then the naïve hedge ratio is close to the optimum hedge ratio. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:359–386, 2004     

The Canadian Hedge Fund Industry: Performance and Market Timing

We analyze the risk and return characteristics of Canadian hedge funds based on a comprehensive database we compiled. We find that Canadian hedge funds have higher risk‐adjusted performance and different distributional characteristics relative to the global hedge fund indices. We investigate market timing by Canadian hedge funds and find that they do not time the Canadian or global stock and bond markets, but hedge funds in the Managed Futures strategy group time the commodity market. These results are robust to parameter instability and structural changes in the model. We also illustrate the impact of using local and global risk factors to analyze the performance of local investment firms.     

Futures hedging under mark‐to‐market risk

This article introduces mark‐to‐market risk into the conventional futures hedging framework. It is shown that a hedger concerned with maximum daily loss will considerably reduce his futures position when the risk is taken into account. In case of a moderate hedge horizon, the hedger will hedge approximately 80% of his spot position. The effect of mark‐to‐market risk decreases very slowly as the hedge horizon increases. If the hedger is concerned with average daily loss, the effect is minimal for a moderate hedge horizon. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:389–398, 2003     

On a Mean—Generalized Semivariance Approach to Determining the Hedge Ratio

A new mean‐risk hedge ratio based on the concept of generalized semivariance (GSV) is proposed. The proposed mean‐GSV (M‐GSV) hedge ratio is consistent with the GSV‐based risk–return model developed by Fishburn (1977), Bawa (1975, 1978), and Harlow and Rao (1989). The M‐GSV hedge ratio can also be considered an extension of the GSV‐minimizing hedge ratio considered by De Jong, De Roon, and Veld (1997) and Lien and Tse (1998, 2000). The M‐GSV hedge ratio is estimated for Standard & Poor's (S&P) 500 futures and compared to six other widely used hedge ratios. Because all the hedge ratios considered are known to converge to the minimum‐variance (Johnson) hedge ratio under joint normality and martingale conditions, tests for normality and martingale conditions are carried out. The empirical results indicate that the joint normality and martingale hypotheses do not hold for the S&P 500 futures. The M‐GSV hedge ratio varies less than the GSV hedge ratio for low and relevant levels of risk aversion. Furthermore, the M‐GSV hedge ratio converges to a value different from the values of the other hedge ratios for higher values of risk aversion. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21: 581–598, 2001     

An empirical analysis of the relationship between hedge ratio and hedging horizon using wavelet analysis

In this article, optimal hedge ratios are estimated for different hedging horizons for 23 different futures contracts using wavelet analysis. The wavelet analysis is chosen to avoid the sample reduction problem faced by the conventional methods when applied to non‐overlapping return series. Hedging performance comparisons between the wavelet hedge ratio and error‐correction (EC) hedge ratio indicate that the latter performs better for more contracts for shorter hedging horizons. However, the performance of the wavelet hedge ratio improves with the increase in the length of the hedging horizon. This is true for both within‐sample and out‐of‐sample cases. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:127–150, 2007     

Flexible Ubers and Fixed Taxis: the Effect of Fuel Prices on Car Services

This paper is the first to empirically compare the impact of fuel price on ridership of taxicabs and transportation network companies (TNCs) like Uber and Lyft. We build a theoretical model of the car service market to demonstrate how drivers under the two systems may have different reactions to fuel prices. Although all drivers pay for their own gasoline, TNC drivers have more flexibility in reducing their supply when operating costs are relatively higher. Due to greater regulation, taxi drivers are more fixed in their supply but receive a “rigidity dividend” from paying greater gas costs while profiting from the reduced competition when TNC drivers leave the market. Through ordinary least squares and seemingly unrelated regression estimation, we find that a 1-day 1% increase of fuel prices in New York City is associated with a 0.367% to 0.486% decrease in trips from TNCs, while the quantity of taxi trips will slightly increase by 0.033% to 0.088%. Empirical results additionally show a diminishing marginal effect for the fuel price elasticity of TNC trips.

     

Robust estimation of the optimal hedge ratio

When using derivative instruments such as futures to hedge a portfolio of risky assets, the primary objective is to estimate the optimal hedge ratio (OHR). When agents have mean‐variance utility and the futures price follows a martingale, the OHR is equivalent to the minimum variance hedge ratio,which can be estimated by regressing the spot market return on the futures market return using ordinary least squares. To accommodate time‐varying volatility in asset returns, estimators based on rolling windows, GARCH, or EWMA models are commonly employed. However, all of these approaches are based on the sample variance and covariance estimators of returns, which, while consistent irrespective of the underlying distribution of the data, are not in general efficient. In particular, when the distribution of the data is leptokurtic, as is commonly found for short horizon asset returns, these estimators will attach too much weight to extreme observations. This article proposes an alternative to the standard approach to the estimation of the OHR that is robust to the leptokurtosis of returns. We use the robust OHR to construct a dynamic hedging strategy for daily returns on the FTSE100 index using index futures. We estimate the robust OHR using both the rolling window approach and the EWMA approach, and compare our results to those based on the standard rolling window and EWMA estimators. It is shown that the robust OHR yields a hedged portfolio variance that is marginally lower than that based on the standard estimator. Moreover, the variance of the robust OHR is as much as 70% lower than the variance of the standard OHR, substantially reducing the transaction costs that are associated with dynamic hedging strategies. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:799–816, 2003     

Regime switching and cointegration tests of the efficiency of futures markets

Many researchers have found that spot and futures prices are not cointegrated in some commodity markets, or they are cointegrated but not with a cointegrating vector (1, −1). One interpretation is that disturbances to excess returns have a unit root persistence, which implies that spot and futures prices do not move together one-for-one in the long run. To provide an alternative explanation for this finding, this article proposes a regime switching model of spot prices that can be viewed in the same framework as Fama and French (1988). Based on this model, Monte Carlo experiments are performed to show that tests for cointegration and estimates of the cointegrating vector are likely to be biased when a sample contains infrequent changes in regime. Taking these shifts into account, the null hypothesis that spot and futures prices are cointegrated and move together one-for-one in the long run can no longer be rejected. © 1998 John Wiley & Sons, Inc. Jrl Fut Mark 18:871–901, 1998     

Rational speculative bubbles in the gold futures market: An application of dynamic factor analysis

The existence of speculative bubbles in financial markets has been a longstanding issue under debate. Many financial economists believe that, given the assumption of rational expectations and rational behavior of economic agents, an asset should be priced according to its “market fundamentals.” Others argue that self‐fulfilling rumors of market participants can influence asset prices as well. These self‐fulfilling rumors are initiated by events extraneous to markets and are often called bubbles. The rationality of both expectations and behavior often does not imply that the price of an asset be equal to its fundamental value. In other words, there can be rational deviations of the price from this value—rational bubbles. A rational bubble can arise when the actual market price depends positively on its own expected rate of change, as normally occurs in asset markets. Since agents forming rational expectations do not make systematic prediction errors, the positive relationship between price and its expected rate of change implies a similar relationship between price and its actual rate of change. Under such conditions, the arbitrary, self‐fulfilling expectation of price changes may drive actual price changes independently of market fundamentals; we refer to such a situation as a rational price bubble.¹ © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:79–108, 2001     

Hedging performance analysis of energy markets: Evidence from copula quantile regression

This study investigates hedging performance with respect to different market structures for energy-related commodities, including West Texas Intermediate crude oil, Brent crude oil, Chinese crude oil, and Heating oil. Copula quantile regression functions and the generalized autoregressive conditionally heteroscedasticity model are combined to analyze the nonlinear impact of dependence and the heterogeneous impact of market structure changes on hedging performance. Results show that hedging performance presents nonlinearity and market structure changes have surprisingly strong heterogeneous effects on the quantile hedge ratio, where bearish and bullish have lower hedge ratios than normal markets, which is captured better by Clayton copula quantile regression. Additionally, the trend of hedging effectiveness over different market structures also shows an inverted U shape. After changing data frequency or the types of futures contracts, the conclusions remain the same. Our empirical findings imply that hedgers are supposed to adjust the hedging number of futures according to market structure changes to hedge price risk effectively.     

Hedge Fund Performance and Manager Skill

Using data on the monthly returns of hedge funds during the period January 1990 to August 1998, we estimate six‐factor Jensen alphas for individual hedge funds, employing eight different investment styles. We find that about 25% of the hedge funds earn positive excess returns and that the frequency and magnitude of funds' excess returns differ markedly with investment style. Using six‐factor alphas as a measure of performance, we also analyze performance persistence over 1‐year and 2‐year horizons and find evidence of significant persistence among both winners and losers. These findings, together with our finding that hedge funds that pay managers higher incentive fees also have higher excess returns, are consistent with the view that fund manager skill may be a partial explanation for the positive excess returns earned by hedge funds. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:1003–1028, 2001     

Can Hedge Funds Time the Market?

We answer the somewhat narrower question of whether hedge funds adjust their conditional market exposure in response to real‐time changes in macroeconomic conditions, and whether doing so improves their performance. We find that hedge funds differ substantially in their responsiveness to macroeconomic data. The most procyclical market timers outperform their less active and counter‐cyclical peers by over 4% annualized with a risk adjusted alpha of 5.5%.     

Consumer Substitution Effects under Full Industry Equilibrium

To be of practical use comparative statics must be able to compare long‐period equilibria. Such equilibria will almost never have price vectors that are proportional with respect to all prices but one—yet such price vectors are precisely those underlying the usual substitution effect analysis. We consider how this tension may be resolved.     

The use of term structure information in the hedging of mortgage‐backed securities

This article examines the importance of term structure variables in the hedging of mortgage‐backed securities (MBS) with Treasury futures. Koutmos, G., Kroner, K., and Pericli, A. (1998) find that the optimal hedge ratio is time varying; we determine the effect of yield levels and slopes on this variation. As these variables are closely tied with mortgage refinancing, intuition suggests them to be relevant determinants of the hedge ratio. It was found that a properly specified model of the time varying hedge ratio that excludes the level and slope of the yield curve from the information set would provide similar out‐of‐sample hedging results to a model in which term structure information is included. Thus, both the level of interest rates and the slope of the yield curve are unimportant variables in determining the empirically optimal hedge ratio between MBS and Treasury futures contracts. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:661–678, 2005     

Price Discovery in the Pits: The Role of Market Makers on the CBOT and the Sydney Futures Exchange

This paper uses the methods of error correction and common factor analysis to estimate the contribution of locals (market makers who may participate directly by trading for their own account) and non‐local traders to price discovery on the floor of the Chicago Board of Trade (CBOT) and the Sydney Futures Exchange (SFE) during a period when open outcry trading was used on both exchanges. We examine these two execution channels for the CBOT's U.S. Treasury bond contract and the SFE's three‐year bonds, ten‐year bonds, ninety‐day bankers' accepted bills, and stock index contracts. For each of the futures contracts, the trade price series of local and non‐local traders are cointegrated. VAR analysis reveals lag structures eight to fifteen trades long in the dynamic adjustment of equilibrium prices in these markets, but time spans of only one to three seconds within synchronous trades. We find evidence of multilateral price discovery by the two execution channels for each of the five contracts. Locals account for 44 to 73% of the price discovery in the four SFE contracts and for 58% of the price discovery in the CBOT's T‐bond contract. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:785–804, 2004     

Predicting returns and changes in real activity: evidence from emerging economies

This paper studies the relation between real activity and share prices in nine emerging economies. Especially, it is investigated whether the time series of real activity and share prices are cointegrated, whether the deviations from the cointegration relations contain information that can be used to predict returns and changes in real activity, and finally whether returns are proportional to the predictions of changes in real activity. The results reveal that the deviations from the cointegration relations contain information that can be used to predict returns and changes in real activity in those countries where cointegration between share prices and real activity cannot be rejected. Furthermore, it is also found that returns are not proportional to the predictions of changes in real activity.