Analysis of a Duopoly Supply Chain and its Application in Electricity Spot Markets

This paper studies a supply chain consisting of two suppliers and one retailer in a spot market, where the retailer uses the newsvendor solution as its purchase policy, and suppliers compete for the retailer’s purchase. Since each supplier’s bidding strategy affects the other’s profit, a game theory approach is used to identify optimal bidding strategies. We prove the existence and uniqueness of a Nash solution. It is also shown that the competition between the supplier leads to a lower market clearing price, and as a result, the retailer benefits from it. Finally, we demonstrate the applicability of the obtained results by deriving optimal bidding strategies for power generator plants in the deregulated California energy market. Supported in part by RGC (Hong Kong) Competitive Earmarked Research Grants (CUHK4167/04E and CUHK4239/03E), a Distinguished Young Investigator Grant from the National Natural Sciences Foundation of China, and a grant from Hundred Talents Program of the Chinese Academy of Sciences.     

Equilibria of a two-stage market with chance outcome in the spot market

We address the problem of how to improve the efficiency of markets of similar goods (electric power, gas, and other resources). One way to undermine the market dominance of some companies is the possibility of forward contracts. Here a model of the spot and forward markets functioning as Curnout auctions is studied using the example of symmetrical oligopoly. Suppliers try to maximize their profit by this two-stage game’s strategies of traded subgame equilibrium (TSE). The conditions for equilibrium achieved by correlated mixed strategies are elucidated: either a “bull” or “bear” market is established according to a chance factor. The optimum strategies of rational bidders are found to depend on the reserve price and a risk-avoiding parameter. TSE is compared to the Nash equilibria for one-stage models.     

The efficiency of financial futures markets: Tests of prediction accuracy

The prices of financial futures contracts can be interpreted as forecasts of the spot rates, which will apply at the final delivery date of that contract. Financial futures contracts have been traded daily since the early 1980s and provide a substantial bank of data to test the forecasting efficiency of such contracts. Tests are carried out to examine whether the interest rates implied by the futures price for eurodollar and short sterling contracts are cointegrated with the final settlement price over forecasting horizons of 1, 2 and 3 months. Similar analysis is carried out for the yen/dollar exchange rate futures contract. The paper then examines the forecasting performance of the three contracts over the forecasting horizons of 1, 2 and 3 months and in particular whether the forecasts implied by the futures contract provide better predictions than the naı̈ve no-change (i.e. random walk), a vector error correction model (VECM) or an ARIMA model.An examination of the relative efficiency of the markets for the three markets over the three time horizons is carried out and finally trading strategies are simulated to see whether excess profits can be achieved. In fact the results suggest that both profits and losses would be attracted.     

DERIVATIVES ON NONSTORABLE RENEWABLE RESOURCES: FISH FUTURES AND OPTIONS,NOT SO FISHY AFTER ALL

Abstract We study forwards and European call options, which are written on a nonstorable renewable resource. Examples of such derivatives in form of futures on fresh catch of wild salmon for the United States and the recently created Fish Pool market in Norway, where futures on a composite of wild catch and farmed salmon are traded, will be discussed. We approach the problem of pricing these contracts from first principles, starting off by modeling the dynamics of the resource reserves, and assuming that in approximation resource extraction is managed as open access. We derive formulas for the forward price of the renewable resource as well as European call options written on it.     

A Non‐Gaussian Ornstein–Uhlenbeck Process for Electricity Spot Price Modeling and Derivatives Pricing

A mean‐reverting model is proposed for the spot price dynamics of electricity which includes seasonality of the prices and spikes. The dynamics is a sum of non‐Gaussian Ornstein–Uhlenbeck processes with jump processes giving the normal variations and spike behaviour of the prices. The amplitude and frequency of jumps may be seasonally dependent. The proposed dynamics ensures that spot prices are positive, and that the dynamics is simple enough to allow for analytical pricing of electricity forward and futures contracts. Electricity forward and futures contracts have the distinctive feature of delivery over a period rather than at a fixed point in time, which leads to quite complicated expressions when using the more traditional multiplicative models for spot price dynamics. In a simulation example it is demonstrated that the model seems to be sufficiently flexible to capture the observed dynamics of electricity spot prices. The pricing of European call and put options written on electricity forward contracts is also discussed.     

Electricity swing options: Behavioral models and pricing

Electricity swing options are supply contracts for power, which give the owner the right to change the required delivery on short time notice. It gives more flexibility than fixed base load or peak load contracts. The name “option” is a bit misleading, since it gives the owner multiple exercise rights at many different time horizons with exercise amounts on a continuous scale. We look at the problem to determine a rational ask price for such a contract from the viewpoint of the contract seller. The pricing of these contracts differs drastically from the pricing of financial options. First, peculiar properties arise from the non-storability of the underlying (the energy) and therefore the impossibility to hedge with the underlying, hedging is only possible with some future contracts. Second, the behavior of the owner plays an important role. Based on some behavioral model for the option holder, we develop a game-theoretic model, which allows to identify the equilibrium price. Besides some theoretical results, we present some numerical results which clarify the dependence of the asked price on the amount of flexibility offered in the swing option.     

A non-Gaussian Ornstein–Uhlenbeck model for pricing wind power futures

The recent introduction of wind power futures written on the German wind power production index has brought with it new interesting challenges in terms of modelling and pricing. Some particularities of this product are the strong seasonal component embedded in the underlying, the fact that the wind index is bounded from both above and below and also that the futures are settled against a synthetically generated spot index. Here, we consider the non-Gaussian Ornstein–Uhlenbeck type processes proposed by Barndorff-Nielsen and Shephard in the context of modelling the wind power production index. We discuss the properties of the model and estimation of the model parameters. Further, the model allows for an analytical formula for pricing wind power futures. We provide an empirical study, where the model is calibrated to 37 years of German wind power production index that is synthetically generated assuming a constant level of installed capacity. Also, based on 1 year of observed prices for wind power futures with different delivery periods, we study the market price of risk. Generally, we find a negative risk premium whose magnitude decreases as the length of the delivery period increases. To further demonstrate the benefits of our proposed model, we address the pricing of European options written on wind power futures, which can be achieved through Fourier techniques.     

Pricing and clearing combinatorial markets with singleton and swap orders

In this article we consider combinatorial markets with valuations only for singletons and pairs of buy/sell-orders for swapping two items in equal quantity. We provide an algorithm that permits polynomial time market-clearing and -pricing. The results are presented in the context of our main application: the futures opening auction problem. Futures contracts are an important tool to mitigate market risk and counterparty credit risk. In futures markets these contracts can be traded with varying expiration dates and underlyings. A common hedging strategy is to roll positions forward into the next expiration date, however this strategy comes with significant operational risk. To address this risk, exchanges started to offer so-called futures contract combinations, which allow the traders for swapping two futures contracts with different expiration dates or for swapping two futures contracts with different underlyings. In theory, the price is in both cases the difference of the two involved futures contracts. However, in particular in the opening auctions price inefficiencies often occur due to suboptimal clearing, leading to potential arbitrage opportunities. We present a minimum cost flow formulation of the futures opening auction problem that guarantees consistent prices. The core ideas are to model orders as arcs in a network, to enforce the equilibrium conditions with the help of two hierarchical objectives, and to combine these objectives into a single weighted objective while preserving the price information of dual optimal solutions. The resulting optimization problem can be solved in polynomial time and computational tests establish an empirical performance suitable for production environments.     

A two stage stochastic equilibrium model for electricity markets with two way contracts

This paper investigates generators’ strategic behaviors in contract signing in the forward market and power transaction in the electricity spot market. A stochastic equilibrium program with equilibrium constraints (SEPEC) model is proposed to characterize the interaction of generators’ competition in the two markets. The model is an extension of a similar model proposed by Gans et al. (Aust J Manage 23:83–96, 1998) for a duopoly market to an oligopoly market. The main results of the paper concern the structure of a Nash–Cournot equilibrium in the forward-spot market: first, we develop a result on the existence and uniqueness of the equilibrium in the spot market for every demand scenario. Then, we show the monotonicity and convexity of each generator’s dispatch quantity in the spot equilibrium by taking it as a function of the forward contracts. Finally, we establish some sufficient conditions for the existence of a local and global Nash equilibrium in the forward-spot markets. Numerical experiments are carried out to illustrate how the proposed SEPEC model can be used to analyze interactions of the markets.     

Exercising flexible load contracts: Two simple strategies

A flexible load contract is a type of swing option where the holder has the right to receive a given quantity of electricity within a specified period, at a fixed maximum effect (delivery rate). The contract is flexible, in the sense that delivery (the take hours) is called one day in advance. We investigate two simple strategies for exercising flexible load contracts, where both use price information from the forward market. For 10 contracts traded in the period 1997–2001, we calculate the performance of the two strategies and compare with the reported performance of one complex dynamic programming approach as well as the actual results obtained by three anonymous market participants. The comparison indicates that our simple computer‐efficient strategies perform better on average and produce more stable results. Copyright © 2007 John Wiley & Sons, Ltd.     

Strong consistency of the empirical martingale simulation option price estimator

A simulation technique known as empirical martingale simulation （EMS） was proposed to improve simulation accuracy. By an adjustment to the standard Monte Carlo simulation, EMS ensures that the simulated price satisfies the rational option pricing bounds and that the estimated derivative contract price is strongly consistent with payoffs that satisfy Lipschitz condition. However, for some currently used contracts such as self-quanto options and asymmetric or symmetric power options, it is open whether the above asymptotic result holds. In this paper, we prove that the strong consistency of the EMS option price estimator holds for a wider class of univariate payoffs than those restricted by Lipschitz condition. Numerical experiments demonstrate that EMS can also substantially increase simulation accuracy in the extended setting.     

Structural Electricity Models and Asymptotically Normal Estimators to Quantify Parameter Risk

ABSTRACT

We estimate a structural electricity (multi-commodity) model based on historical spot and futures data (fuels and power prices, respectively) and quantify the inherent parameter risk using an average value at risk approach (‘expected shortfall’). The mathematical proofs use the theory of asymptotic statistics to derive a parameter risk measure. We use far in-the-money options to derive a confidence level and use it as a prudent present value adjustment when pricing a virtual power plant. Finally, we conduct a present value benchmarking to compare the approach of temperature-driven demand (based on load data) to an ‘implied demand approach’ (demand implied from observable power futures prices). We observe that the implied demand approach can easily capture observed electricity price volatility whereas the estimation against observable load data will lead to a gap, because – amongst others – the interplay of demand and supply is not captured in the data (i.e., unexpected mismatches).     

Optimal Supply Functions in Electricity Markets with Option Contracts and Non-smooth Costs

In this paper we investigate the optimal supply function for a generator who sells electricity into a wholesale electricity spot market and whose profit function is not smooth. In previous work in this area, the generator’s profit function has usually been assumed to be continuously differentiable. However in some interesting instances, this assumption is not satisfied. These include the case when a generator signs a one-way hedge contract before bidding into the spot market, as well as a situation in which a generator owns several generation units with different marginal costs. To deal with the non-smooth problem, we use the model of Anderson and Philpott, in which the generator’s objective function is formulated as a Stieltjes integral of the generator’s profit function along his supply curve. We establish the form of the optimal supply function when there are one-way contracts and also when the marginal cost is piecewise smooth.We would like to thank two anonymous referees for careful reading of the paper and helpful comments which lead to a significant improvement of this paper.     

Eurodollar futures pricing in log-normal interest rate models in discrete time

We demonstrate the appearance of explosions in three quantities in interest rate models with log-normally distributed rates in discrete time. (1) The expectation of the money market account in the Black, Derman, Toy model, (2) the prices of Eurodollar futures contracts in a model with log-normally distributed rates in the terminal measure and (3) the prices of Eurodollar futures contracts in the one-factor log-normal Libor market model (LMM). We derive exact upper and lower bounds on the prices and on the standard deviation of the Monte Carlo pricing of Eurodollar futures in the one factor log-normal Libor market model. These bounds explode at a non-zero value of volatility, and thus imply a limitation on the applicability of the LMM and on its Monte Carlo simulation to sufficiently low volatilities.     

A note on the dynamics of incentive contracts

Laffont and Tirole (Econometrica 56:1153–1175) show that when uncertainty about an agent’s ability is small, the equilibrium must involve a large amount of pooling, but, whether the continuation equilibrium induced by an optimal first-period menu of contracts is partitional or not, remains unclear. They construct a non-partitional continuation equilibrium for a given first-period menu of contracts and conjecture that this continuation equilibrium need not be suboptimal for the whole game under small uncertainty. We show that, irrespective of the amount of uncertainty, this non-partitional continuation equilibrium generates a strictly smaller payoff for the principal than a different menu of contracts with a partitional continuation equilibrium. In this sense, Laffont and Tirole’s menu of contracts, giving rise to a non-partitional continuation equilibrium, is not optimal.     

Optimal crop planting schedules and financial hedging strategies under ENSO-based climate forecasts

This paper investigates the impact of ENSO-based climate forecasts on optimal planting schedules and financial yield-hedging strategies in a framework focused on downside risk. In our context, insurance and futures contracts are available to hedge against yield and price risks, respectively. Furthermore, we adopt the Conditional-Value-at-Risk (CVaR) measure to assess downside risk, and Gaussian copula to simulate scenarios of correlated non-normal random yields and prices. The resulting optimization problem is a mixed 0?C1 integer programming formulation that is solved efficiently through a two-step procedure, first through an equivalent linear form by disjunctive constraints, followed by decomposition into sub-problems identified by hedging strategies. With data for a representative cotton producer in the Southeastern United States, we conduct a study that considers a wide variety of optimal planting schedules and hedging strategies under alternative risk profiles for each of the three ENSO phases (Niña, Niño, and Neutral.) We find that the Neutral phase generates the highest expected profit with the lowest downside risk. In contrast, the Niña phase is associated with the lowest expected profit and the highest downside risk. Additionally, yield-hedging insurance strategies are found to vary significantly, depending critically on the ENSO phase and on the price bias of futures contracts.     

Robust strategies for natural gas procurement

In order to serve their customers, natural gas local distribution companies (LDCs) can select from a variety of financial and non-financial contracts. The present paper is concerned with the choice of an appropriate portfolio of natural gas purchases that would allow a LDC to satisfy its demand with a minimum tradeoff between cost and risk, while taking into account risk associated with modeling error. We propose two types of strategies for natural gas procurement. Dynamic strategies model the procurement problem as a mean-risk stochastic program with various risk measures. Naive strategies hedge a fixed fraction of winter demand. The hedge is allocated equally between storage, futures and options. We propose a simulation framework to evaluate the proposed strategies and show that: (i) when the appropriate model for spot prices and its derivatives is used, dynamic strategies provide cheaper gas with low risk compared to naive strategies. (ii) In the presence of a modeling error, dynamic strategies are unable to control the variance of the procurement cost though they provide cheaper cost on average. Based on these results, we define robust strategies as convex combinations of dynamic and naive strategies. The weight of each strategy represents the fraction of demand to be satisfied following this strategy. A mean–variance problem is then solved to obtain optimal weights and construct an efficient frontier of robust strategies that take advantage of the diversification effect.     

Convexity Bias in Eurodollar Futures Prices: A Dimension-Free HJM Criterion

In the theory of interest rate futures, the difference between the futures rate and forward rate is called the “convexity bias,” and there are several widely offered reasons why the convexity bias should be positive. Nevertheless, it is not infrequent that the empirical the bias is observed to be negative. Moreover, in its most general form, the benchmark Heath–Jarrow–Morton (HJM) term structure model is agnostic on the question of the sign of the bias; it allows for models where the convexity bias can be positive or negative. In partial support of the practitioner’s arguments, we develop a simple scalar condition within the HJM framework that suffices to guarantee that the convexity bias is positive. Moreover, when we check this condition on the LIBOR futures data, we find strong empirical support for the new condition. The empirical validity of the sufficient condition and the periodic observation of negative bias, therefore leads one to a paradoxical situation where either (1) there are arbitrage possibilities or (2) a large subclass of HJM models provide interest rate dynamics that fail to capture a fundamental feature of LIBOR futures.     

Forward Variance Dynamics: Bergomi’s Model Revisited

Abstract

In this article, we propose an arbitrage-free modelling framework for the joint dynamics of forward variance along with the underlying index, which can be seen as a combination of the two approaches proposed by Bergomi. The difference between our modelling framework and the Bergomi (2008. Smile dynamics III. Risk, October, 90–96) models is mainly the ability to compute the prices of VIX futures and options by using semi-analytic formulas. Also, we can express the sensitivities of the prices of VIX futures and options with respect to the model parameters, which enables us to propose an efficient and easy calibration to the VIX futures and options. The calibrated model allows to Delta-hedge VIX options by trading in VIX futures, the corresponding hedge ratios can be computed analytically.     

Joint pricing-servicing decision and channel strategies in the supply chain

This paper investigates the equilibrium behavior of a two-echelon supply chain in four channel strategies: (i) vertical integration, (ii) vertical Nash (iii) manufacturer’s Stackelberg and (vi) retailer’s Stackelberg. We examine the price and service level decision for each of the above four channel strategies in two cases: (i) Simultaneous service-level decision: Here, the manufacturer and retailer simultaneously choose a service level. (ii) Sequentially service-level decision: Here, the manufacturer and retailer sequentially choose a service level. We model the demand as a deterministic linear function of retailer’s price and both manufacturer’s and retailer’s service levels. We discuss the optimal configuration from each individual’s perspective for each of the above channel strategies. We show that vertical integration dominates other strategies and leads to the highest service level but lowest retail price among various channel coordination policies considered here. We yield several conclusions about the provision of service level by each supply chain individual to coordinate the channel.