Showing papers on "Spot contract published in 2011"
TL;DR: In this article, a large file of Texas-based 15-min data was used to show that while increasing wind generation does indeed tend to reduce the level of spot prices, it is also likely to enlarge the spot-price variance.
372 citations
29 Nov 2011
TL;DR: By analyzing the spot price histories of Amazon's EC2 cloud, this work reverse engineer how prices are set and construct a model that generates prices consistent with existing price traces, finding that prices are usually not market-driven as sometimes previously assumed.
Abstract: Cloud providers possessing large quantities of spare capacity must either incentivize clients to purchase it or suffer losses. Amazon is the first cloud provider to address this challenge, by allowing clients to bid on spare capacity and by granting resources to bidders while their bids exceed a periodically changing spot price. Amazon publicizes the spot price but does not disclose how it is determined. By analyzing the spot price histories of Amazon's EC2 cloud, we reverse engineer how prices are set and construct a model that generates prices consistent with existing price traces. We find that prices are usually not market-driven as sometimes previously assumed. Rather, they are typically generated at random from within a tight price interval via a dynamic hidden reserve price. Our model could help clients make informed bids, cloud providers design profitable systems, and researchers design pricing algorithms.
250 citations
TL;DR: In this paper, the authors hypothesize that the price spike and collapse of 2007-2008 are driven by both changes in both market fundamentals and speculative pressures, and they argue for the role of speculation based on a significant increase in private US crude oil inventories since 2004.
204 citations
TL;DR: In this paper, the co-movement and determinants of commodity prices were investigated using nonstationary panel methods, and a statistically significant degree of comovement due to a common factor was found.
197 citations
05 Dec 2011
TL;DR: A comprehensive analysis of SIs based on one year price history in four data centers of Amazon's EC2 and a proposed statistical model that fits well these two data series is proposed.
Abstract: The surge in demand for utilizing public Cloud resources has introduced many trade-offs between price, performance and recently reliability. Amazon's Spot Instances (SIs) create a competitive bidding option for the public Cloud users at lower prices without providing reliability on services. It is generally believed that SIs reduce monetary cost to the Cloud users, however it appears from the literature that their characteristics have not been explored and reported. We believe that characterization of SIs is fundamental in the design of stochastic scheduling algorithms and fault tolerant mechanisms in public Cloud environments for spot market. In this paper, we have done a comprehensive analysis of SIs based on one year price history in four data centers of Amazon's EC2. For this purpose, we have analyzed all different types of SIs in terms of spot price and the inter-price time (time between price changes) and determined the time dynamics for spot price in hour-in-day and day-of-week. Moreover, we have proposed a statistical model that fits well these two data series. The results reveal that we are able to model spot price dynamics as well as the inter-price time of each SI by the mixture of Gaussians distribution with three or four components. The proposed model is validated through extensive simulations, which demonstrate that our model exhibits a good degree of accuracy under realistic working conditions.
144 citations
TL;DR: In this article, the authors explored wind power integration issues for the South Australian (SA) region of the Australian National Electricity Market (NEM) by assessing the interaction of regional wind generation, electricity demand and spot prices over 2 recent years of market operation.
123 citations
TL;DR: The value of long-term contracting as a complement to spot sourcing in the beef supply chain is elucidates for the first time and some rules of thumb for the packer for the strategic management of the procurement portfolio are provided.
Abstract: This paper analyzes the optimal procurement, processing, and production decisions of a meat-processing company (hereafter, a “packer”) in a beef supply chain. The packer processes fed cattle to produce two beef products, program (premium) boxed beef and commodity boxed beef, in fixed proportions, but with downward substitution of the premium product for the commodity product. The packer can source input (fed cattle) from a contract market, where long-term contracts are signed in advance of the required delivery time, and from a spot market on the spot day. Contract prices are taken to be of a general window form, linear in the spot price but capped by upper and lower limits on realized contract price. Our analysis provides managerial insights on the interaction of window contract terms with processing options. We show that the packer benefits from a low correlation between the spot price and product market uncertainties, and this is independent of the form of the window contract. Although the expected revenues from processing increase in spot price variability, the overall impact on profitability depends on the parameters of the window contract. Using a calibration based on the report by the GIPSA (Grain Inspection, Packers and Stockyards Administration. 2007. GIPSA livestock and meat marketing study, vol. 3: Fed cattle and beef industries. Report, U.S. Department of Agriculture, Washington, DC), this paper elucidates for the first time the value of long-term contracting as a complement to spot sourcing in the beef supply chain. Our comparative statics results provide some rules of thumb for the packer for the strategic management of the procurement portfolio. In particular, we show that higher variability (higher spot price variability, product market variability, and correlation) increases the profits of the packer, but decreases the reliance on the contract market relative to the spot market.
This paper was accepted by Yossi Aviv, operations management.
113 citations
TL;DR: In this article, the authors assess whether and to what extent financial activity in the oil futures markets has contributed to destabilizing oil prices in recent years, and disentangle this non-fundamental …nancial shock from fundamental shocks to oil supply and demand to determine their relative importance.
Abstract: We assess whether and to what extent …nancial activity in the oil futures markets has contributed to destabilize oil prices in recent years. We de…ne a destabilizing …nancial shock as a shift in oil prices that is not related to current and expected fundamentals, and thereby distorts e¢ cient pricing in the oil market. Using a structural VAR model identi…ed with sign restrictions, we disentangle this non-fundamental …nancial shock from fundamental shocks to oil supply and demand to determine their relative importance. We …nd that shocks to oil demand and supply remain the main drivers of oil price swings. Financial investors in the futures market can however destabilize oil spot prices, although only in the short run. Moreover, …nancial activity appears to have exacerbated gyrations in the oil market over the past decade, particularly in 2007-2009.
109 citations
01 Jan 2011
TL;DR: In this paper, a simple spot price model that is the exponential of the sum of an Ornstein-Uhlenbeck and an independent mean-reverting pure process is examined. But the model is not suitable for the case of spikes.
Abstract: Most electricity markets exhibit high volatilities and occ asional distinctive price spikes,which result in demand for derivative products which protec t the holder against highprices. In this paper we examine a simple spot price model tha t is the exponentialof the sum of an Ornstein-Uhlenbeck and an independent mean r everting pure jumpprocess. We derive the moment generating function as well as various approximations tothe probability density function of the logarithm of the spo t price process at maturityT . Hence we are able to calibrate the model to the observed forw ard curve and presentsemi-analytic formulae for premia of path-independent opt ions as well as approximationsto call and put options on forward contracts with and without a delivery period. In orderto price path-dependent options with multiple exercise rig hts like swing contracts a gridmethod is utilised which in turn uses approximations to the c onditional density of thespot process. 1 Introduction A distinctive feature of electricity markets is the formati on of price spikes which are causedwhen the maximum supply and current demand are close, often w hen a generator or partof the distribution network fails unexpectedly. The occurr ence of spikes has far reachingconsequences for risk management and pricing purposes. In t his context a parsimoniousmodel with some degree of analytic tractability has clear ad vantages, and in this paper wepropose and examine in detail a simple mean-reverting spot p rice process exhibiting spikes.In our model the spot price process S is de ned to be the exponential of the sum of three com-ponents: a deterministicperiodicfunction f characterisingseasonality, an Ornstein-Uhlenbeck(OU) process X and a mean-reverting process with a jump component to incorp orate spikesY . We set this up formally. Let ( ;F ;P ) be a probability space equipped with a ltration(F
97 citations
TL;DR: In this article, the authors conduct an empirical analysis of three recently proposed and widely used models for electricity spot price process, including the jump-diffusion model, the threshold model, and the factor model, where the price dynamics is a superposition of Ornstein-Uhlenbeck processes driven by subordinators.
Abstract: We conduct an empirical analysis of three recently proposed and widely used models for electricity spot price process. The first model, called the jump-diffusion model, was proposed by Cartea and Figueroa (2005), and is a one-factor mean-reversion jump-diffusion model, adjusted to incorporate the most important characteristics of electricity prices. The second model, called the threshold model, was proposed by Roncoroni (2002) and further developed by Geman and Roncoroni (2006), and is an exponential Ornstein-Uhlenbeck process driven by a Brownian motion and a state-dependent compound Poisson process. It is designed to capture both statistical and pathwise properties of electricity spot prices. The third model, called the factor model, was proposed by Benth et al. (2007). It is an additive linear model, where the price dynamics is a superposition of Ornstein-Uhlenbeck processes driven by subordinators to ensure positivity of the prices. It separates the modelling of spikes and base components. We calibrate all three models to German spot price data. Besides employing techniques similar to those used in the original papers we adopt the prediction based estimating functions technique (S rensen (2000)) and the filtering technique (Meyer-Brandis and Tankov (2008)). We critically compare the properties and the estimation of the three models and discuss several shortcomings and possible improvements. Besides analysing the spot price behaviour, we compute forward prices and risk premia for all three models for various German forward data and identify the key forward price drivers.
95 citations
25 Jul 2011
TL;DR: Two virtual server provisioning algorithms are proposed to minimize the provisioning cost for long- and short-term planning using Stochastic programming, robust optimization, and sample-average approximation to obtain the optimal solutions of the algorithms.
Abstract: Amazon Elastic Compute Cloud (EC2) provides a cloud computing service by renting out computational resources to customers (i.e., cloud users). The customers can dynamically provision virtual servers (i.e., computing instances) in EC2, and then the customers are charged by Amazon on a pay-per-use basis. EC2 offers three options to provision virtual servers, i.e., on-demand, reservation, and spot options. Each option has different price and yields different benefit to the customers. Spot price (i.e., price of spot option) could be the cheapest, however, the spot price is fluctuated and even more expensive than the prices of on-demand and reservation options due to supply-and-demand of available resources in EC2. Although the reservation and on-demand options have stable prices, their costs are mostly more expensive than that of spot option. The challenge is how the customers efficiently purchase the provisioning options under uncertainty of price and demand. To address this issue, two virtual server provisioning algorithms are proposed to minimize the provisioning cost for long- and short-term planning. Stochastic programming, robust optimization, and sample-average approximation are applied to obtain the optimal solutions of the algorithms. To evaluate the performance of the algorithms, numerical studies are extensively performed. The results show that the algorithms can significantly reduce the total provisioning cost incurred to customers.
TL;DR: The authors revisited the relationship between spot and futures oil prices of West Texas Intermediate covering 1986 to 2009 with an innovative approach named quantile cointegration, which targets the issues of cointegrating relationships, causalities, and market efficiency based on different market states under different maturities of oil futures.
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TL;DR: A method that greatly reduces the computational burden induced by the introduction of independent regimes and performs a simulation study to test its efficiency is proposed.
Abstract: In this paper we discuss the calibration of models built on mean-reverting processes combined with Markov regime-switching (MRS). We propose a method that greatly reduces the computational burden induced by the introduction of independent regimes and perform a simulation study to test its efficiency. Our method allows for a 100 to over 1000 times faster calibration than in case of a competing approach utilizing probabilities of the last 10 observations. It is also more general and admits any value of gamma in the base regime dynamics. Since the motivation for this research comes from a recent stream of literature in energy economics, we apply the new method to sample series of electricity spot prices from the German EEX and Australian NSW markets. The proposed MRS models fit these datasets well and replicate the major stylized facts of electricity spot price dynamics.
TL;DR: In this article, the authors investigate the use of fixed price contracts for Norwegian salmon exports to France based on all export transactions between the two countries and show that almost 25% of these exports were traded using fixed-price contracts and contract prices were renegotiated at different intervals.
Abstract: Sales and distribution innovations have increased productivity in the salmon aquaculture industry. In this article, we investigate the use of fixed price contracts for Norwegian salmon exports to France based on all export transactions between the two countries. Our analysis shows that almost 25% of these exports were traded using fixed price contracts and contract prices were renegotiated at different intervals, including as infrequently as once a year. Some contracts allow the contracting parties to adjust contract prices when the export price moves significantly. Benchmark analysis, which shows a marginal 0.5% difference between average unit revenue for the year from spot sales relative to contract sales, indicates that contracts primarily change revenue time profiles. The use of contracts creates a wedge between salmon export prices and spot prices in periods of price volatility, which in turn reduces price transmission. JEL Classification Code: L14, Q22
TL;DR: In this paper, the authors consider a simple and easy-to-implement capacity reservation-base stock policy and compare it to single sourcing options, and examine the joint effect of demand and spot market price uncertainty.
TL;DR: In this article, an explanation for the forward premium puzzle in foreign exchange markets based upon investor overconfidence is proposed, where overconfident individuals overreact to their information about future inflation, which causes greater overshooting in the forward rate than in the spot rate.
Abstract: We offer an explanation for the forward premium puzzle in foreign exchange markets based upon investor overconfidence. In the model, overconfident individuals overreact to their information about future inflation, which causes greater overshooting in the forward rate than in the spot rate. Thus, when agents observe a signal of higher future inflation, the consequent rise in the forward premium predicts a subsequent downward correction of the spot rate. The model can explain the magnitude of the forward premium bias and several other stylized facts related to the joint behaviour of forward and spot exchange rates. Our approach is also consistent with the availability of profitable carry trade strategies.
TL;DR: In this paper, the authors focus on the mechanisms by which investor demand affects spot prices, and in particular on two questions: how does an increase in investor demand on the futures markets affect the spot market and spot price?
TL;DR: In this article, the authors examined empirically the relationship between electricity spot and futures prices, by analysing a decade of data for a set of short term-to-maturity futures contracts traded in the Nordic Power Exchange.
01 Jan 2011
25 May 2011
TL;DR: In this article, a forecasting technique to model day-ahead spot price using well known ARIMA model to analyze and forecast time series is presented, which is applied to time series consisting of day ahead electricity prices from EPEX power exchange.
Abstract: Electricity price forecasting is becoming more important in everyday business of power utilities. Good forecasting models can increase effectiveness of producers and buyers playing roles in electricity market. Price is also a very important element in investment planning process. This paper presents a forecasting technique to model day-ahead spot price using well known ARIMA model to analyze and forecast time series. The model is applied to time series consisting of day-ahead electricity prices from EPEX power exchange.
TL;DR: In this article, the first exercise of nonparametric modeling applied to carbon markets is presented, and the empirical application unfolds in the case of BlueNext spot and ECX futures prices.
TL;DR: In this paper, a mixed-integer programming model for a power providing agent that jointly considers the problem of selecting custom electricity contracts and finding the optimal procurement strategy of meeting contract obligations under spot price uncertainty is developed.
TL;DR: Xiong et al. as mentioned in this paper developed an equilibrium model with producers, retailers, and traders to study and quantify the impact of forward markets and vertical integration on prices, risk premia, and retail market shares.
Abstract: This paper analyzes the interactions between competitive (wholesale) spot, retail, and forward markets and vertical integration in electricity markets. We develop an equilibrium model with producers, retailers, and traders to study and quantify the impact of forward markets and vertical integration on prices, risk premia, and retail market shares. We point out that forward hedging and vertical integration are two separate mechanisms for demand and spot price risk diversification that both reduce the retail price and increase retail market shares. We show that they differ in their impact on prices and firms' utility because of the asymmetry between production and retail segments. Vertical integration restores the symmetry between producers' and retailers' exposure to demand risk, whereas linear forward contracts do not. Vertical integration is superior to forward hedging when retailers are highly risk averse. We illustrate our analysis with data from the French electricity market.
This paper was accepted by Wei Xiong, finance.
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01 Jan 2011
TL;DR: In this paper, the interactions between competitive spot, retail, and forward markets and vertical integration in electricity markets were analyzed and the impact of vertical integration on prices, risk premia, and retail market shares was analyzed.
Abstract: This paper analyzes the interactions between competitive (wholesale) spot, retail, and forward markets and vertical integration in electricity markets. We develop an equilibrium model with producers, retailers, and traders to study and quantify the impact of forward markets and vertical integration on prices, risk premia, and retail market shares. We point out that forward hedging and vertical integration are two separate mechanisms for demand and spot price risk diversification that both reduce the retail price and increase retail market shares. We show that they differ in their impact on prices and firms utility because of the asymmetry between production and retail segments. Vertical integration restores the symmetry between producers and retailers exposure to demand risk, whereas linear forward contracts do not. Vertical integration is superior to forward hedging when retailers are highly risk averse. We illustrate our analysis with data from the French electricity market
TL;DR: In this article, the authors use time series models combined with new advances in causal inference to answer the questions of how dynamic price information flow among Northern European electricity spot prices and prices of major electricity generation fuel sources.
TL;DR: In this article, a new stylized fact regarding the dynamics of the commodity convenience yield was revealed: the volatility of the convenience yield is heteroskedastic for industrial commodities; specifically, the volatility (variance) depends on the convenience yields level.
TL;DR: In this article, the authors consider the excess return from 20 internationally tradable emerging market (EM) currencies against the US dollar and calculate the difference between the forward exchange rate and the spot rate at maturity.
Abstract: We consider the excess return from 20 internationally tradable emerging market (EM) currencies against the US dollar It has two contributions. First, we document stylized facts about EM currencies. EM currencies have provided significant equity-like excess returns against major currencies, but with low volatility. Picking EM currencies with a relatively high forward premium raises the portfolio return substantially. Second, our calculation incorporates institutional features of the foreign exchange market, such as lags in settling spot contracts, FX swaps, and bid/ offer spreads. Transaction costs arising from bid/ offer spreads are less than one-fifth of what is typically presumed in the literature. (JEL C58, F31, G15) examine the foreign exchange excess return (the difference between the forward exchange rate and the spot rate at maturity) from taking long positions in 20 internationally tradable emerging market (EM) currencies for the US dollar (USD) investors. Our paper has two contributions. First, it contributes to the vast literature on the failure of uncovered interest rate parity (UIP)1 by providing corroborating facts and some new ones for EM currencies. We do so by utilizing a propriety dataset (Gilmore and Hayashi 201 1) that we believe is superior to publicly available alternatives. Second, our calculation of the excess return takes into account institutional features of the foreign exchange market. They include lags in settling spot contracts, foreign exchange (FX) swaps2, and bid/offer spreads. There are two classes of tests of UIP. One, sometimes called the unconditional
TL;DR: In this paper, the benefits of forward contracting for goods and services have been extensively researched in terms of mitigating market power effects in spot markets, and the risk in spot price formation induces a counteracting premium in the contract prices.
Abstract: Whilst the benefits of forward contracting for goods and services have been extensively researched in terms of mitigating market power effects in spot markets, we analyse how the risk in spot price formation induces a counteracting premium in the contract prices. We consider and test a wide-ranging set of propositions, involving fundamental, behavioural, dynamic, market conduct and shock components, on a long data set from the most liquid of European electricity forward markets, the EEX. We show that much of what is conventionally regarded as the market price of risk in electricity is actually that of its underlying fuel commodity, gas; that market power has a double effect on prices, insofar as it increases spot prices and induces a forward premium; that oil price sentiment spills over and that the premium reacts to scarcity and the higher moments of spot price uncertainty. We observe that considerations of the scale and determinants of the forward premium are at least as important as the market power effects in spot market price formation when evaluating the efficiency of wholesale power trading.
TL;DR: In this paper, the area hyperbolic sine transform is used to model negative power prices in the German EEX spot market, the ERCOT West Texas market and the exemplary valuation of an option.
Abstract: Negative prices for electricity are a novelty in European power markets. At the German EEX spot market negative hourly prices have since occurred frequently, down to values as extreme as minus several hundred €/MWh. However, in some non-European markets as USA, Australia and Canada, negative prices are a characteristic for a longer period already. Negative prices are in fact natural for electricity spot trading: plant flexibility is limited and costly, thus, incurring a negative price for an hour can nevertheless be economically optimal overall. Negative prices pose a basic problem to stochastic price modelling: going from prices to log-prices is not possible. So far, this has been dealt with by “workarounds”. However, here a thorough approach is advocated, based on the area hyperbolic sine transformation. The transformation is applied to spot modelling of the German EEX, the ERCOT West Texas market and the exemplary valuation of an option. It is concluded that the area hyperbolic sine transform is well and naturally suited as a starting point for modelling negative power prices. It can be integrated in common stochastic price models without adding much complexity. Moreover, this transformation might be in general more appropriate for power prices than the log transformation, considering fundamentals of power price formation. Eventually, a thorough treatment of negative prices is indispensable since they significantly affect business.
Patent•
14 Mar 2011
TL;DR: In this article, a method for offering an asset in a financial environment is provided that includes receiving a request to perform a selected one of a purchasing and a selling operation for a futures contract.
Abstract: A method for offering an asset in a financial environment is provided that includes receiving a request to perform a selected one of a purchasing and a selling operation for a futures contract. The futures contract includes a first asset class having a first value associated therewith and a second asset class having a second value associated therewith. A price for the futures contract is determined at least partially by the first and second values.