A consistent two-factor model for pricing temperature derivatives

In the past decade, the Chicago Mercantile Exchange began to trade weather derivatives to hedge weather risk. The pricing of weather derivatives is challenging since the underlying is not tradable and thus classical arbitrage approaches have to be used with caution. In typical pricing approaches all information available to the market is assumed to be incorporated in the underlying and thus forward-looking information about non-tradable assets such as meteorological forecasts is often ignored. In this article, we analyze a new pricing methodology for temperature derivatives that accounts for forward-looking information. More precisely, we provide an empirical back-up for the theoretical framework of so-called consistent factor models for temperature forecast curves introduced previously in the literature and put this pricing approach into practice. First, we perform a thorough statistical analysis of meteorological forecast curve data. Second, based on this analysis we propose a specific consistent two-factor model, derive explicit temperature derivative prices, and calibrate the market price of risk (MPR). The power of the model is demonstrated against alternative pricing models. This confirms that at least parts of the irregularity of the MPR observed in earlier studies are not due to irregular risk perception but rather due to information misspecification.     

An equilibrium pricing model for wind power futures

Generation from wind power plants is intermittent and affects profits of wind power generators and conventional generators alike. Currently, generators have limited options for transferring the resulting wind-related volume risks. The European Energy Exchange (EEX) recently introduced exchange-traded wind power futures to address this market imperfection. We propose a stylized equilibrium pricing model featuring two representative agents and analyze equilibrium prices as well as the mechanics behind risk premia for wind power futures. We calibrate and simulate stochastic models for wind power generation, power prices, electricity demand, as well as other relevant sources of uncertainty and use the resulting scenarios to conduct a case study for the German market; analyzing prices, hedging effectiveness, and risk premia. Our main result suggests that wind generators are willing to pay an insurance premium to conventional generators to reduce their risks. We conduct a thorough sensitivity analysis to test the influence of model parameters and find that our results on risk premia hold for a broad range of reasonable inputs.     

Hedging strategies in energy markets: The case of electricity retailers

As market intermediaries, electricity retailers buy electricity from the wholesale market or self-generate for re(sale) on the retail market. Electricity retailers are uncertain about how much electricity their residential customers will use at any time of the day until they actually turn switches on. While demand uncertainty is a common feature of all commodity markets, retailers generally rely on storage to manage demand uncertainty. On electricity markets, retailers are exposed to joint quantity and price risk on an hourly basis given the physical singularity of electricity as a commodity. In the literature on electricity markets, few articles deal on intra-day hedging portfolios to manage joint price and quantity risk whereas electricity markets are hourly markets. The contributions of the article are twofold. First, we define through a VaR and CVaR model optimal portfolios for specific hours (3 am, 6 am,. . . ,12 pm) based on electricity market data from 2001 to 2011 for the French market. We prove that the optimal hedging strategy differs depending on the cluster hour. Secondly, we demonstrate the significantly superior efficiency of intra-day hedging portfolios over daily (therefore weekly and yearly) portfolios. Over a decade (2001–2011), our results clearly show that the losses of an optimal daily portfolio are at least nine times higher than the losses of optimal intra-day portfolios.     

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.     

Humps in the volatility structure of the crude oil futures market: New evidence

This paper analyses the volatility structure of commodity derivatives markets. The model encompasses hump-shaped, unspanned stochastic volatility, which entails a finite-dimensional affine model for the commodity futures curve and quasi-analytical prices for options on commodity futures. Using an extensive database of crude oil futures and futures options spanning 21 years, we find the presence of hump-shaped, partially spanned stochastic volatility in the crude oil market. The hump shaped feature is more pronounced when the market is more volatile, and delivers better pricing as well as hedging performance under various dynamic factor hedging schemes.     

A model for hedging load and price risk in the Texas electricity market

Energy companies with commitments to meet customers' daily electricity demands face the problem of hedging load and price risk. We propose a joint model for load and price dynamics, which is motivated by the goal of facilitating optimal hedging decisions, while also intuitively capturing the key features of the electricity market. Driven by three stochastic factors including the load process, our power price model allows for the calculation of closed-form pricing formulas for forwards and some options, products often used for hedging purposes. Making use of these results, we illustrate in a simple example the hedging benefit of these instruments, while also evaluating the performance of the model when fitted to the Texas electricity market.     

Effects of stochastic energy prices on long-term energy-economic scenarios

In view of the currently observed energy prices, recent price scenarios, which have been very moderate until 2004, also tend to favor high future energy prices. Having a large impact on energy-economic scenarios, we incorporate uncertain energy prices into an energy systems model by including a stochastic risk function. Energy systems models are frequently used to aid scenario analysis in energy-related studies. The impact of uncertain energy prices on the supply structures and the interaction with measures in the demand sectors is the focus of the present paper.

For the illustration of the methodological approach, scenarios for four EU countries are presented. Including the stochastic risk function, elements of high energy price scenarios can be found in scenarios with a moderate future development of energy prices. In contrast to scenarios with stochastic investment costs for a limited number of technologies, the inclusion of stochastic energy prices directly affects all parts of the energy system. Robust elements of hedging strategies include increasing utilization of domestic energy carriers, the use of CHP and district heat and the application of additional energy-saving measures in the end-use sectors. Region-specific technology portfolios, i.e., different hedging options, can cause growing energy exchange between the regions in comparison with the deterministic case.     

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.     

Hydro resource management,risk aversion and equilibrium in an incomplete electricity market setting

Since the outset of power system reform, one of the main objectives of regulation has been to assess whether the market, of its own accord, can induce agents to adopt decisions that maximise social welfare.This paper analyses the effect of generating companies' risk aversion on their medium-term (typically 1 year) hydroelectric resource planning, along with its possible inducement of system operation that deviates from the centralised (maximum social welfare) solution.Forward markets may play a key role by making hedging instruments available to risk-averse agents. A stylised mathematical model is used in this study to prove the equivalence of centralised planning and market equilibrium in the presence of such agents under the following assumptions: 1) both the spot and forward markets are perfectly competitive; 2) it has at least one risk-neutral consumer or arbitrageur; 3) all agents share the same beliefs about uncertain parameters; 4) only one price is in place in each trading period (which can be perfectly hedged with a forward contract); and 5) a solution for the resulting market equilibrium problem exists.The findings show that such equivalence vanishes when forward markets are missing or inaccessible (attributable in some electricity markets to the absence of demand-side participation). This article consequently suggests that requiring demand-side agents to sign forward contracts with generators might constitute an effective regulatory measure where no fully functional forward market is already in place.     

基于短期均衡模型的动态电价经济效率研究

针对动态电价是实现电力市场资源优化配置的重要途径问题,基于微观经济学理论建立了动态电价的短期均衡模型,通过实际算例分析了峰荷、用电总量、用户用电成本、消费者剩余、生产者剩余及社会剩余对动态电价的经济有效性。结果表明,动态电价能有效反映供电成本,引导用户有序用电,减少用电成本,具有良好的经济效率。     

通过匹配原油计价量与加工量规避原油计价风险的探讨

进口原油具有的贸易特点及计价方法,与炼油企业当期销售成品油的计价方法不同,造成原油与成品油计价期不同,在国际油价剧烈波动,特别是油价快速下跌时,使炼油企业严重亏损。当企业均衡生产时,这种时间差带来的市场风险会通过装置长周期运行而减小,但当企业的加工和采购进度因装置检修、非计划停工以及市场供需调整等原因进行大幅调整时,成本和产品价格之间的时间差可能会给企业带来巨大风险。分别介绍了进口原油、成品油的贸易特点及计价方法,提出了如何研究国际油价走势。分析了国际油价上涨时,如何选择原油计价期,实现低价采购原油、高价销售成品油的目标;国际油价下跌时,如何实现同期原油计价量与原油加工量匹配,实现均衡计价,规避因国际油价波动造成的企业亏损,进一步剖析了如何运用套期保值方法,锁定当期炼油企业原油加工效益。同时,列举了操作中的注意事项,提出套期保值应善于选择时机操作,加强计划管理的重要性,以及控制合理库存的必要性。     

Locational price spreads and the pricing of contracts for difference: Evidence from the Nordic market

In electricity markets, not only does the risk of substantial price variations over time exist, but so does the risk of price variations over space, as prices between locations can differ due to transmission congestion. To manage this risk, Contracts for Difference (CfDs), i.e., forwards on the spread between a particular area price and the (unconstrained) system price, were introduced at the Scandinavian electricity exchange Nord Pool at the end of 2000. We empirically investigate the pricing of these CfDs over the period 2001 through 2006 and find that CfD prices contain significant risk premia. Their sign and magnitude, however, differ substantially between areas and delivery periods, because areas are subject to transmission congestion to a varying extent. While the relation between risk premia and time-to-maturity is not uniform for CfDs, there is a negative relation for implied area and system forwards, which can be explained by the relative hedging demand of market participants. In addition, we find that risk premia of CfDs and implied area forwards vary systematically with the variance and skewness of the underlying spot prices. This confirms both implications of the Bessembinder and Lemmon [Bessembinder, H., Lemmon, M.L., 2002. Equilibrium pricing and optimal hedging in electricity forward markets. Journal of Finance, 57, 1347–1382] model.     

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.     

Volatility linkages between energy and agricultural commodity prices

We investigate price and volatility risk originating in linkages between energy and agricultural commodity prices in Germany and study their dynamics over time. We propose an econometric approach to quantify the volatility and correlation risk structure, which has a large impact for investment and hedging strategies of market participants as well as for policy makers. Volatilities and their short and long run linkages are analyzed using an asymmetric dynamic conditional correlation GARCH model as well as a multivariate multiplicative volatility model. Our approach provides a flexible and accurate fitting procedure for volatility and correlation risk. We find that in the long run prices move together and preserve an equilibrium, while correlations are mostly positive with persistent market shocks. Our results reveal that concerns about biodiesel being the cause of high and volatile agricultural commodity prices are rather unjustified.     

Government procurement of peak capacity in the New Zealand electricity market

This paper analyzes the impact of government procurement of reserve electricity generation capacity on the long-run equilibrium in the electricity market. The approach here is to model the electricity market in a context where the supply companies have market power. The model is then used to analyze the impact of government direct supply of peak capacity on the market. We find that the firms build less peak-generation capacity when the government procures peak generating capacity. The long-run equilibrium with N firms and government capacity of K_G results in an increase of total peak generation capacity of K_G/(N+1) compared to the long-run equilibrium with no government capacity. Supply disruptions of baseline capacity during the peak time period are also considered. It is found that peak prices do not go up any further with (anticipated) supply disruptions. Instead the entire cost of the extra peakers is borne by customers on traditional meters and off-peak customers who face real-time pricing.     

The futures and forward price differential in the Nordic electricity market

This note investigates price differentials between electricity forwards and portfolios of short-term futures with identical delivery periods at the Nordic Power Exchange (Nord Pool). Since both contracts are traded at the same exchange, there is no influence of, for example, different market microstructure and default risk when examining the effect of the marking-to-market of futures on the price differential. Although the prices of the futures portfolios are, on average, below the corresponding forward prices, these price differentials are, on average, not statistically significant and not economically significant when taking transaction costs into account. Given the characteristics of the electricity contracts under observation, this is consistent with the predictions of the Cox et al. (1981) model and indicates efficient pricing in the Nord Pool forward market in contrast to previous results.     

Crude oil price shocks and hedging performance: A comparison of volatility models

From a practical perspective, it is crucial to hedge the crude oil price risk in periods of dramatic price change. In this study, we directly investigate the performance of crude oil hedge portfolios in the five periods in which the largest oil price shocks in history occurred. We use stochastic volatility (SV), GARCH, and the diagonal BEKK model to estimate the minimum variance hedge ratio of hedge portfolios. Our empirical results provide evidence that hedging strategies based on the SV model are able to outperform the GARCH and BEKK models in terms of variance reduction. Our results are also consistently valid for various hedge horizons. Interestingly, although it is important to estimate variance and covariance accurately when constructing minimum variance portfolios, we find that reducing the mean squared and mean absolute errors does not guarantee superior hedge performance.     

Pricing reliability options under different electricity price regimes

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first derived by means of closed-form pricing formulae, which are obtained under several assumptions about the dynamics of electricity prices and strike prices. Then, the value of the Reliability Option is simulated under a real-market calibration, using data of the Italian power market. We perform sensitivity analyses to highlight the role of the level and volatility of both power and strike price, of the mean reversion speeds and of the correlation coefficient on the Reliability Options' value. Finally, we calculate the parameter model risk to quantify the impact that a model misspecification has on the equilibrium value of the RO.     

基于博弈论的跨区域电力交易多主体均衡模型研究

为了及时解决跨区域交易中各方的均衡问题、促进和规范跨区域电能交易,分析了跨区域电力交易各参与主体的特点及其利润构成,以跨区域电力交易各主体的收益之和最大化为目标,构建了基于博弈论的跨区域电力交易各主体均衡模型,并对一个包含4个区域的跨区域电力交易系统进行模拟分析,比较了纳什均衡和合作均衡下算例的模拟结果。结果表明,在合作均衡中,实施跨区域电力交易可提高市场均衡电量并有效降低市场均衡价格,真正地实现了资源优化配置。     

Modeling and predicting oil VIX: Internet search volume versus traditional mariables

As a key variable in option pricing models and monetary policy decisions, volatility is an important factor in valuing and hedging investments. This paper models and predicts the CBOE Crude Oil Volatility Index using Heterogeneous Autoregressive (HAR) models that include traditional macro-finance variables as well as abnormal search volume from Google (ASVI). We find that a pure HAR model fits oil volatility remarkably well. When adding ASVI, we discover that this variable has a significant and positive relationship with oil volatility. This relationship remains statistically significant when traditional financial and macroeconomic variables are accounted for; therefore, ASVI is not only a good proxy for traditional macro-finance variables, but also carries additional information. More importantly, out-of-sample predictions show that ASVI has high economic value, allowing traders of volatility-exposed portfolios to significantly increase returns.