Non-storable Commodities Research Articles

Identifying Risk Factors and Their Premia: A Study on Electricity Prices

Abstract Risk premia are difficult to identify in nonstorable commodities such as electricity. In this article, we propose a modified Fama–French regression framework and show that when the spot prices do not follow a martingale—a common assumption in the electricity market—model specifications play an important role in detecting time-varying risk premia in the futures market. With this insight, we propose a multi-factor model that captures important dynamics in electricity prices and an estimation method based on particle Markov chain Monte Carlo to separate risk factors in energy prices. Using spot and futures data in the Germany/Austria electricity market, we demonstrate that our proposed model surpasses alternative models that ignore some of risk factors in forecasting spot prices and in detecting time-varying risk premia. Based on our proposed model, we separately identify risk premia carried by individual risk factors and document large variations in the premia of each factor.

Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities

The purpose of this paper is to analyze market reflexivity in agricultural futures contracts with different maturities. To this end, we apply a four-dimensional Hawkes model to storable and non-storable agricultural commodities. We find market reflexivity for both storable and non-storable commodities. Reflexivity accounts for about 50 to 70% of the total trading activity. Differences between nearby and deferred contracts are less pronounced for non-storable than for storable commodities. We conclude that the co-existence of exogenous and endogenous price dynamics does not change qualitative characteristics of the price discovery process that have been observed earlier without the consideration of market reflexivity.

Introducing stylized facts on electricity futures through a market impact model

This paper provides an alternative way to introduce the stylized facts on electricity futures. For nonstorable commodities, forward-looking information is not necessarily incorporated in the price history. In contrast to contemporary electricity finance models, we introduce a mechanism based on the trading behavior of market participants and their corresponding market impact by exploiting characteristic initial positions and quantity risk considerations. For long times to maturity we end up with a market influenced by hedging pressure, whereas for short times to maturity quantity risk comes into play and yields an increased volatility. In addition, prices can also be negative. The model is accompanied by an empirical analysis showing that parameters that are typically only relevant on small timescales have a significant dynamic in daily returns over a period of years. This allows us to access the toolbox usually reserved for high-frequency modeling.

Duration dependence among agricultural futures with different maturities

ABSTRACTThe purpose of this paper is to analyse the interdependence of price durations among agricultural futures contracts with different maturities. We apply an extended autoregressive conditional duration (ACD) model to storable and non-storable agricultural commodities. Using Chicago Mercantile Exchange (CME) Best-Bid-Best-Offer (BBO) futures data, we find duration dependence for corn, wheat, live cattle, and lean hog. Somewhat surprisingly, we do not find differences between storable and non-storable commodities. The main contribution of our analysis is to provide empirical evidence that short-term effects motivated by market microstructure theory do not outweigh arbitrage relations along the forward curve as suggested by theories of storage and normal backwardation.

The Role of Liquidity in Electricity Markets

Starting from the premise that hedging pressure is based on limited market efficiency I provide an analogy that electricity markets over years behave like intraday stock or FX markets during the liquidation of a block trade. In this endeavour I relate the returns of some liquidity exploitation strategies with the degree of liquidity metrics by utilising the characteristic initial endowments of market participants in electricity markets. In a second step I introduce a simple stochastic model that is able to capture a variety of stylized facts of asset returns (first order price impact, Samuelson Effect, negative prices) over the whole life span of the contract and that circumvents typical information modeling pitfalls for non-storable commodities. This argument is based on modeling 'market impact' as an additional asset with a known terminal value and is justified by an enlargement of filtration argument.

Portfolio optimization of power futures market: Evidence from France and Germany

Understanding the nature of power futures is particularly crucial, for non-storable commodities such as wholesale electricity since it has been deregulated. This paper examines different types of optimisation techniques and provides a temporal analysis of energy future prices. In particular, it highlights how one of the well-known elements of modern finance theory could improve the accuracy of evaluating the risk exposure inherent in power futures market via a modified version of the mean-variance portfolio (MVP) theory. The optimisation techniques employed account for the initial capital requirement of the energy futures and estimate the optimal weights needed to mitigate the downside risk inherent in the energy futures market. One major finding of this paper shows that, a portfolio of energy prices with different maturities could provide market players with a less risky investment in the energy market. In addition, the feasibility of the methodologies utilised have been presented.

Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach

In this paper we derive analytic formulas for electricity derivatives under assumption that electricity spot prices follow a 3-regime Markov regime-switching model with independent spikes and drops and periodic transition matrix. Since the classical derivatives pricing methodology cannot be used in the case of non-storable commodities, we employ the concept of the risk premium. The obtained theoretical results are then used for the European Energy Exchange data analysis. We calculate the risk premium in the case of the calibrated 3-regime MRS model. We find a time varying structure of the risk premium and an evidence for a negative risk premium (or positive forward premium), especially at short times before delivery. Finally, we use the obtained risk premium to calculate prices of European options written on spot, as well as, forward prices.

Forecasting the daily dynamic hedge ratios by GARCH models: evidence from the agricultural futures markets

This paper investigates the forecasting ability of six different generalized autoregressive conditional heteroskedasticity (GARCH) models; bivariate GARCH, BEKK GARCH, GARCH-X, BEKK-X, Q-GARCH and GARCH–GJR based on two different distributions (normal and student-t). Forecast errors based on four agricultural commodities’ futures portfolio return forecasts (based on forecasted hedge ratio) are employed to evaluate the out-of-sample forecasting ability of the six GARCH models. The four commodities under investigation are two storable commodities: wheat and soybean, and two non-storable commodities: live cattle and live hogs. We apply the rolling forecasting method and the Model Confidence Set approach to evaluate and compare the forecasting ability of the six GARCH models. Our results show that the forecasting performances of the six GARCH models are different for storable and non-storable agricultural commodities. We find that the BEKK-type models perform the best in the case of storable products, while the asymmetric GARCH models dominate in the case of non-storable commodities. These results are regardless of the forecast horizon and residual distributions.

Integrated data envelopment analysis: Global vs. local optimum

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approaches. European Journal of Operational Research 201, 477–489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal network structure with multiple inputs, outputs, and consumptions. They claim that any optimal solutions determined by their DEA model are a global optimum, not a local optimum. We show that such a conclusion is a false statement due to their misuse of Hessian matrix in examining the concavity of the objective function, and their DEA model is actually a non-convex optimization problem. As a result, their DEA model is unusable in practice due to a lack of efficient algorithm for this particular non-convex DEA model. We further show that Chiou et al.’s (2010) model is a special case of a well-known two-stage network DEA model, and it can be transformed into a parametric linear program for which an approximate global optimal solution can be obtained by solving a sequence of linear programs in combination with a simple search algorithm.

The informational content of distant-delivery futures contracts

Futures markets have two main goals: price discovery and risk management. Because management decisions often have to be made on a time horizon longer than the time until expiration of the nearby futures contract, it is important to determine how well distant-delivery futures contracts are able to assist in price discovery. We focus on soybean and live cattle distant-delivery futures contracts and test for the informational value added to nearby contracts. Two tests for information value provide partially conflicting results due to the different information measures employed. If being able to predict the price trend is sufficient, then we find some information value in distantdelivery futures contracts, while if accurate point estimates of future spot prices are desired the results are negative. Surprisingly, we do not find the expected dichotomy between the storable (soybeans) and non-storable (cattle) commodities.

Revealing the impact of index traders on commodity futures markets

Commodity futures prices and volatility increased dramatically from 2006 to 2008, following a period during which index traders, a class of large investment funds, took on massive commodity futures positions. This article presents a method to reveal the extent to which index trader trading activity (volume) might have caused increases in futures price volatility. This approach is useful when position-level data are incomplete or confidential, as with index trader position data. The method is applied to leading agricultural commodity futures data. The impact of index traders is identified during their period of greatest activity, that is, 2005 to 2006, using aggregated volume data that are filtered using wavelet transforms. The filtering decision rule is guided by the Commodity Futures Trading Commission's (CFTC) finding that index traders do not engage in short-run trades. A joint model of futures (filtered) volume and (unfiltered) price volatility is estimated by 2SLS to account for the endogeneity of prices and volume. As a robustness check, both log-range and GARCH measures of volatility are used. The evidence provides no support for the claim that index traders have increased price volatility for storable commodities (grains/oilseeds) and only weak support in the case of nonstorable commodities (meats).

A joint measurement of efficiency and effectiveness for non-storable commodities: Integrated data envelopment analysis approaches

Efficiency and effectiveness for non-storable commodities represent two distinct dimensions and a joint measurement of both is necessary to fully capture the overall performance. This paper proposes two novel integrated data envelopment analysis (IDEA) approaches, the integrated Charnes, Cooper and Rhodes (ICCR) and integrated Banker, Charnes and Cooper (IBCC) models, to jointly analyze the overall performance of non-storable commodities under constant and variable returns to scale technologies. The core logic of the proposed models is simultaneously determining the virtual multipliers associated with inputs, outputs, and consumption by additive specifications for technical efficiency and service effectiveness terms with equal weights. We show that both ICCR and IBCC models possess the essential properties of rationality, uniqueness, and benchmarking power. A case analysis also demonstrates that the proposed novel IDEA approaches have higher benchmarking power than the conventional separate DEA approaches. More generalized specifications of IDEA models with unequal weights are also elaborated.

The information premium for non-storable commodities

The information premium for non-storable commodities

Quantifying multiscale inefficiency in electricity markets

One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies.

Strategic Trading of Forward Contracts in Oligopolistic Industries with Non-Storable Commodities

We introduce demand uncertainty in the model of Allaz-Vila (1993). Traders' risk attitude in the forward market crucially determines the degree of competitiveness of the spot market. The higher demand uncertainty the lower the competition-enhancing effect of forward trading.

Equilibrium Forward Contracts on Nonstorable Commodities in the Presence of Market Power

Bilateral supply contracts are widely used despite the presence of spot markets. In this paper we provide a potential explanation for this prevalence of supply contracts even when spot markets are liquid and without delivery lag. Specifically, we consider the determination of an equilibrium forward contract on a nonstorable commodity between two firms that have mean-variance preferences over their risky profits and negotiate the forward contract through a Nash bargaining process. We derive the unique equilibrium forward in closed form and provide an extensive analysis of the equilibrium contract. We show that it is the risk hedging benefit from a forward that justifies its prevalence in spite of liquid spot markets. In addition, while a forward does not affect production decisions due to the presence of spot markets, it does affect inventory decisions of the storable input factor due to its hedging effect against the inventory risk. We also show that price volatilities and correlations are important determinants of the equilibrium contract. In particular, the equilibrium forward price can be nonmonotonic in the spot price volatility and can decrease as the initial spot price increases.

Equilibrium Forward Contracts on Nonstorable Commodities in the Presence of Market Power

Bilateral supply contracts are widely used despite the presence of spot markets. In this paper, we provide a potential explanation for this prevalence of supply contracts even when spot markets are liquid and without delivery lag. Specifically, we consider the determination of an equilibrium forward contract on a nonstorable commodity between two firms that have mean-variance preferences over their risky profits and negotiate the forward contract through a Nash bargaining process. We derive the unique equilibrium forward contract in closed form and provide an extensive analysis. We show that it is the risk-hedging benefit from a forward that justifies its prevalence in spite of liquid spot markets. In addition, while a forward does not affect production decisions due to the presence of spot markets, it does affect inventory decisions of the storable input factor due to its hedging effect against the inventory risk. We also show that price volatilities and correlations are important determinants of the equilibrium contract. In particular, the equilibrium forward price can be nonmonotonic in the spot price volatility and can decrease as the initial spot price increases.

Asset storability and hedging effectiveness in commodity futures markets

This paper examines risk minimization hedging effectiveness for major storable and nonstorable agricultural commodity futures markets. Based on the error correction model - bivariate GARCH frameworks, some evidence is found that the hedging effectiveness is stronger for storable commodities than nonstorable commodities under consideration. The finding illustrates an important difference between storable and nonstorable commodities with regard to their hedging function.

Contract Design: A Note on Cash Settled Futures

This note presents an intuitive interpretation and expression for pricing cash settled futures contracts. In particular, the choice of the averaging period for the underlying cash index is evaluated. A question arises as to how the choice of the averaging period may effect how the futures contract is priced. In this note, it is shown that under certain assumptions, the behavior of the futures price prior to entering the expiration interval is independent of the averaging interval’s length for storable commodities. However, this is not the case for nonstorable commodities. An examination of the Minneapolis Grain Exchange’s National Corn Index futures provides empirical support for the results. Given the increasing interest in cash settled futures, especially for futures contracts on agricultural commodities, these results should prove useful to futures exchanges when considering contract design. Ultimately, contract design choices are a critical factor in the success of any futures contract. In the context of agricultural futures contracts, successful contracts can contribute to increased social welfare and greater efficiency of the food marketing system.

Asset Storability and Price Discovery of Commodity Futures Markets: A New Look

This paper examines the price discovery performance of futures markets for storable and nonstorable commodities in the long run, allowing for the compounding factor of stochastic interest rates. The evidence shows that asset storability does not affect the existence of cointegration between cash and futures prices and the usefulness of future markets in predicting future cash prices. However, it may affect the magnitude of bias of futures markets' estimates (or predictions) for future cash prices. These findings have several important implications for commodity production decision-making, commodity hedging and commodity price forecasting.