Hedging downside risk of oil refineries: A vine copula approach

The financial health of an oil refinery greatly depends on its refining margin or the difference between the prices of its refined products (typically, gasoline and heating oil) and the cost of crude oil. The refinery may hedge against the downside risk of unfavorable price movements using crude oil, gasoline, and heating oil futures. This paper examines the use of a vine copula approach to estimate multiproduct hedge ratios that minimize the downside risk of the refinery. The advantage of the vine copula approach is that it allows us to capture important characteristics of petroleum price changes, including skewness and fat-tailedness in the marginal distributions of individual price change series as well as heterogeneous (tail) dependence patterns between different pairs of price changes. The out-of-sample hedging effectiveness of two popular classes of vine copula models – canonical (C-) and drawable (D-) vine copula models – are evaluated and compared with that of the widely used nonparametric method and three standard multivariate copula models. The empirical results reveal that the D-vine copula model is a good and safe choice in managing the downside risk of the refinery.     

Optimal hedging in the US natural gas market: The effect of maturity and cointegration

We use the US natural gas market as the rich experimental context to test multiple features of hedging performances. First, we compare the hedging effectiveness of a single futures contract (i.e. Henry Hub) used for hedging six different physical price positions. Second, we examine the performance of hedging, when one uses a futures contract with time-to-maturity beyond the hedging horizon (i.e. a non-matching hedging strategy). Finally, we quantify the effect of accounting for cointegration and also the time varying volatility in the calculation of optimal hedge ratios. As a robustness check we conduct our analysis using both ex-ante (out of sample) and ex-post (in sample) methods. Our findings suggest that using longer maturity contracts may improve the hedging effectiveness. We also find that accounting for cointegration and time varying prices has minimal effect on the hedge ratio and hedging effectiveness for almost all physical prices. Our findings can inform businesses exposed to commodity price risks in on making better risk-management decisions.     

Is hedging the crack spread no longer all it's cracked up to be?

The traditional approach to hedging the crude oil refining margin (crack spread) adopts a fixed 3:2:1 ratio between the futures positions of crude oil, gasoline, and heating oil. However, hedging the latter in arbitrary proportions might be more effective under some conditions. The paper constructs optimal hedging strategies for both scenarios during the periods of relatively stable and volatile oil prices observed in recent years. Minimization of downside risk (LPM₂) and variance are used as alternative hedging objectives. The joint distribution of spot and futures price log returns is modeled using a kernel copula method. The hedging performance of the constructed strategies is compared using hedging effectiveness, expected profit, and expected shortfall. The results show that allowing for arbitrary proportions in the sizes of futures positions generally achieves a better hedging performance. The advantage becomes particularly important during periods characterized by greater variation of the cross-dependence between the price log returns of individual commodities. In addition, using LPM₂ as a hedging criterion can help hedgers to better track downside risk as well as lead to higher expected profit and lower expected shortfall.     

Hedging strategy for crude oil trading and the factors influencing hedging effectiveness

This study analyzes the hedging effectiveness of different hedge type and period by Korean oil traders. Both crude oil price and exchange rate risks are considered. Theoretical models are formulated to estimate the hedge ratios by separate and complex hedge types. The hedging period covers 1–12 months. This study also performs some statistical works to investigate the relationship between the hedging effectiveness and the crude oil price sensitivity to exchange rate. In addition, the relationship between the hedging effectiveness and the volatilities of crude oil price and exchange rate is analyzed.     

Performance of utility based hedges

Hedgers as investors are concerned with both risk and return. However when measuring hedging performance, the role of returns and investor risk aversion has generally been neglected in the literature, by its focus on minimum variance hedging. In this paper we address this by using utility based performance metrics to evaluate the hedging effectiveness of utility based hedges for hedgers with both moderate and high risk aversion together with the more traditional minimum variance approach. To examine this for an energy hedger, we apply our approach to WTI Crude Oil, for three different hedging horizons, daily, weekly and monthly. We find significant differences between the minimum variance and utility based hedging strategies in-sample for all frequencies. However performance differentials between the different strategies are small and not economically significant. Out-of-sample results support these findings across all frequencies.     

Hedging size risk: Theory and application to the US gas market

Many corporate commitments exhibit a combined financial exposure to both market prices and idiosyncratic size components (e.g., volume, load, or business turnover). We design a customized contract to optimally mitigate the risk of joint fluctuations in price and size terms. The hedge is sought out among contingent claims written on price and any quoted index that is statistically dependent on commitment size. Closed-form solutions are derived for the optimal custom hedge pay-off and for the asset holdings of two market strategies, one based on price-linked forwards, the other based on price-linked and index-linked forwards. Analytical hedges are obtained using a stylized lognormal market model. Detailed comparative statics provide a thorough analysis of optimal hedging pay-off functions. Performance assessment is conducted in the context of the US gas market and a prototypical urban region. Results suggest that hedging through suitable custom claims written on price and an additional index significantly outperforms standard price-based as well as mixed price-index forward hedging alternatives. Our optimal custom hedge could be adopted as a benchmark for the relative assessment of any risk management solution.     

Optimal hedging under biased energy futures markets

Optimal futures hedging positions for those agents trying to maximize their expected utility will depend on their view about the evolution of the market and on how risk adverse they are. The most risk adverse agents will probably decide to full-cover their positions. But when a futures bias exists, hedgers with moderate or low degree of risk aversion can alter their strategy depending on the expected gains in futures markets. In our application to the UK natural gas market, we find a statistically significant time-varying negative futures bias that can be forecasted with confidence. As a result of this bias, most effective and best performing hedging strategies for moderate risk-averse agents are those involving short (long) hedging in winter (summer) with a hedging ratio above (below) the minimum variance hedge ratio. These findings are of great interest to practitioners in the UK natural gas markets and the methodology can be extrapolated to other energy markets.     

Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas

We consider a firm, which can choose between crude oil and natural gas to run its business. The firm selects the energy source, which minimizes its energy or production costs at a given time horizon. Assuming the energy strategy to be established over a fixed time window, the energy choice decision will be made at a given future date T. In this light, the firm's energy cost can be considered as a long position in a risk-free bond by an amount of the terminal oil price, and a short position in a European put option to switch from oil to gas by an amount of the terminal oil price too. As a result, the option to switch from crude oil to natural gas allows for establishing a hedging strategy with respect to energy costs. Modeling stochastically the underlying asset of the European put, we propose a valuation formula of the option to switch and calibrate the pricing formula to empirical data on a daily basis. Hence, our innovative framework handles widely the hedge against the price increase of any given energy source versus the price of another competing energy source (i.e. minimizing energy costs). Moreover, we provide a price for the cost-reducing effect of the capability to switch from one energy source to another one (i.e. hedging energy price risk).     

Pure martingale and joint normality tests for energy futures contracts

In this study, we empirically analyze to see if the pure martingale hypothesis holds for three energy-related commodities: crude oil, heating oil and natural gas. We also test this hypothesis for five different hedging horizons: 1-day, 1-week, 4-week, 8-week and 12-week. Our empirical results show that the pure martingale hypothesis holds for all three commodities and all five horizons. This implies that the expected return on futures contract can be ignored in determining the optimal hedge ratio. We also test to see if the joint normality between futures and spot returns holds for the same three commodities and five hedging horizons. We reject the joint normality hypothesis for all three commodities and five hedging horizons. This implies that hedgers with different utility function have different optimal hedge ratios. Thus, in general, one needs to take into account of hedger's utility function when deriving optimal hedge ratio. Our results are robust to pre- and post-financial crisis as well as some other specifications considered in the paper.     

Crude oil hedging strategies using dynamic multivariate GARCH

The paper examines the performance of several multivariate volatility models, namely CCC, VARMA-GARCH, DCC, BEKK and diagonal BEKK, for the crude oil spot and futures returns of two major benchmark international crude oil markets, Brent and WTI, to calculate optimal portfolio weights and optimal hedge ratios, and to suggest a crude oil hedge strategy. The empirical results show that the optimal portfolio weights of all multivariate volatility models for Brent suggest holding futures in larger proportions than spot. For WTI, however, DCC, BEKK and diagonal BEKK suggest holding crude oil futures to spot, but CCC and VARMA-GARCH suggest holding crude oil spot to futures. In addition, the calculated optimal hedge ratios (OHRs) from each multivariate conditional volatility model give the time-varying hedge ratios, and recommend to short in crude oil futures with a high proportion of one dollar long in crude oil spot. Finally, the hedging effectiveness indicates that diagonal BEKK (BEKK) is the best (worst) model for OHR calculation in terms of reducing the variance of the portfolio.     

Modeling EU allowances and oil market interdependence. Implications for portfolio management

This paper examines the dependence structure between European Union allowances (EUAs) and crude oil markets during the second commitment period of the European Union Emissions Trading Scheme and the implications for portfolio management. Using different copula models, our findings suggest positive average dependence and extreme symmetric independence that is consistent with interdependence and no contagion effects between the EUA and crude oil markets. The implication of this result for EUA-oil portfolios points to the existence of diversification benefits, hedging effectiveness, and value-at-risk reductions. The EUA market is therefore an attractive market for investors in terms of diversifying market risk and reducing downside risk in crude oil markets.     

European natural gas seasonal effects on futures hedging

This paper is the first to discuss the design of futures hedging strategies in European natural gas markets (NBP, TTF and Zeebrugge). A common feature of energy prices is that conditional mean and volatility are driven by seasonal trends due to weather, demand, and storage level seasonalities. This paper follows and extends the Ederington and Salas (2008) framework and considers seasonalities in mean and volatility when minimum variance hedge ratios are computed. Our results show that hedging effectiveness is much higher when the seasonal pattern in spot price changes is approximated with lagged values of the basis (futures price minus spot price). This fact remains true for short (a week) and long (one, three and six months) hedging periods. Furthermore, volatility of weekly price changes also has a seasonal pattern and is higher in winter than in summer. A simple volatility seasonal model that is based on sinusoidal functions on the basis improves the risk reduction obtained by strategies in which hedging ratios are estimated with linear regressions. Seasonal hedging strategies, linear regression based strategies, or even a naïve position, perform better than more sophisticated statistical methods.     

A regime switching approach for hedging tanker shipping freight rates

Tanker shipping is the primary means for the transportation of petroleum and petroleum products around the world and thus plays a crucial role in the energy supply chain. However, the high volatility of tanker freight rates has been a major concern for market participants and led to the development of the tanker freight derivatives in the form of forward freight agreements (FFAs). The aim of this paper is to investigate the performance of these instruments in managing tanker freight rate risk. Using a data set for six major tanker routes covering the period between 2005 and 2013, we examine the effectiveness of alternative hedging methods, including a bivariate Markov Regime Switching GARCH model, in hedging tanker freight rates. The regime switching GARCH specification links the concept of equilibrium freight rate determination underlying different market conditions and the dynamics of the conditional second moments across high and low volatility regimes. Overall, we find evidence supporting the argument that the tanker freight market is characterized by different regimes. However, while the use of a regime switching model allows for a significant improvement in the performance of the hedge in-sample, out-of-sample results are mixed.     

The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging

Motivated by previous studies documenting significant return and volatility effects of economic policy uncertainty (EPU) on the stock market, this study examines whether EPU has an effect on the dynamic conditional correlations between stock and commodity returns. Our findings point to a positive and significant effect of EPU on stock-commodity correlations with particularly stronger effects in the case of energy and industrial metals. The EPU effect is stronger during weak economic conditions, while VIX as a proxy of market uncertainty is generally found to be insignificant. Finally, we show that the EPU effect on correlations has investment implications as well, implied by a significant effect on optimal hedge ratios in commodities in order to mitigate stock market risks. Our results underscore the importance of selective hedging strategies in which risk managers base the timing and size of their hedging programs on future price expectations, conditional on the level of policy uncertainty state and prevalent economic conditions.     

Hedging emerging market stock prices with oil,gold, VIX,and bonds: A comparison between DCC,ADCC and GO-GARCH

While much research uses multivariate GARCH to model volatility dynamics and risk measures, one particular type of multivariate GARCH model, GO-GARCH, has been underutilized. This paper uses DCC, ADCC and GO-GARCH to model volatilities and conditional correlations between emerging market stock prices, oil prices, VIX, gold prices and bond prices. A rolling window analysis is used to construct out-of-sample one-step-ahead forecasts of dynamic conditional correlations and optimal hedge ratios. In most of the situations we study, oil is the best asset to hedge emerging market stock prices. Hedge ratios from the ADCC model are preferred (most effective) for hedging emerging market stock prices with oil, VIX, or bonds. Hedge ratios estimated from the GO-GARCH are most effective for hedging emerging market stock prices with gold in some instances. These results are reasonably robust to choice of model refits, forecast length and distributional assumptions.     

Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness

Building on the increased interest in oil prices and other financial assets, this paper examines the dynamic conditional correlations among their implied volatility indices. We then proceed to the examination of the optimal hedging strategies and optimal portfolio weights for implied volatility portfolios between oil and fourteen asset volatilities, which belong to four different asset classes (stocks, commodities, exchange rates and macroeconomic conditions). The results suggest that the oil price implied volatility index (OVX) is highly correlated with the US and emerging stock market volatility indices, whereas the lowest correlations are observed with the implied volatilities of gold and the Euro/dollar exchange rate. Hedge ratios indicate that VIX is the least useful implied volatility index to hedge against oil implied volatility. Finally, we show that investors can benefit substantially by adjusting their portfolios based on the dynamic weights and hedge ratios obtained from the dynamic conditional correlation models, although a trade-off exists between the level of risk reduction and portfolio profitability.     

Selective hedging in hydro-based electricity companies

We analyze risk management trends in electricity commodity markets using the production and transaction data and written hedging policies of 12 Norwegian hydropower companies. The scope of our analysis is the hedging of physical electricity production using the power derivatives available at NASDAQ OMX Commodities. In their hedging policy, these companies either use a Cashflow at Risk (C-FaR) approach or a hedge ratio approach, or follow no explicitly stated approach. We find that the derivative cashflows constitute substantial profits for these companies. Furthermore, hedging contributes to reducing the C-FaR for 10 of the companies. These findings are surprising considering that we expect hedging to yield zero expected profit and to smooth the earnings. Overall, our findings reveal that a practice of incorporating market views in hedging decisions is widespread in the sample companies, as both sanctioned in their written hedging policy and as indicated by the substantial hedging profits.     

Electricity portfolio management: Optimal peak/off-peak allocations

Electricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to optimally allocate positions in peak and off-peak forward contracts. It is shown that the optimal allocations are based on the difference in risk premiums per unit of day-ahead risk as a measure of relative costs of hedging risk in the day-ahead markets. The outcomes of the model are then applied to show (i) that it is typically not optimal to hedge a baseload consumption profile with a baseload forward contract and (ii) that, under reasonable assumptions, risk taking by the purchaser is rewarded by lower expected costs.     

A further inquiry into FTR properties

William Hogan introduced financial transmission rights as a tool to hedge the locational risk inherent in locational marginal prices. FTRs are claimed to serve four main purposes: (1) provide a hedge for nodal price differences, (2) provide revenue sufficiency for contracts for differences, (3) distribute the merchandizing surplus an RTO accrues in market operations, and (4) provide a price signal for transmission and generation developers. This paper examines the hedging and redistributional properties of FTRs. It argues that FTR allocation has important distributional impacts and related implications for retail rates. This observation adds an additional explanation for rate increases in light of decreased production costs due to restructuring. This paper also shows that RTO practices have important implications for the hedging characteristics of FTRs. It further shows, via counterexample, that, even in theory, FTRs may not serve as a perfect hedge against congestion charges. The paper concludes with a series of recommendations for FTR allocation and the functions that FTRs should serve.