Showing papers on "Spot contract published in 2014"
TL;DR: In this paper, the authors analyzed the impact of renewable energy sources on the formation of day-ahead electricity prices at EEX and showed that renewable energies decrease market spot prices and have implications on the traditional fuel mix for electricity production.
235 citations
TL;DR: The authors examined the impacts of three types of OPEC news announcements on volatility spillovers and persistence in international energy and cereal commodity markets, and showed that the persistence of volatility decreases for the crude oil and heating oil (gasoline) returns after accounting for the OPEC announcements in these multivariate GARCH models.
214 citations
01 Jan 2014
TL;DR: In this article, a survey of the major idiosyncrasies of commodity markets and the methods which have been proposed to handle them in spot and forward price models is presented, focusing on the most idiosyncratic of all: electricity markets.
Abstract: The goal of this survey is to review the major idiosyncrasies of the commodity markets and the methods which have been proposed to handle them in spot and forward price models. We devote special attention to the most idiosyncratic of all: electricity markets. Following a discussion of traded instruments, market features, historical perspectives, recent developments and various modelling approaches, we focus on the important role of other energy prices and fundamental factors in setting the power price. In doing so, we present a detailed analysis of the structural approach for electricity, arguing for its merits over traditional reduced-form models. Building on several recent articles, we advocate a broad and flexible structural framework for spot prices, incorporating demand, capacity and fuel prices in several ways, while calculating closed-form forward prices throughout.
127 citations
TL;DR: The authors examined the out-of-sample predictability of commodity prices by means of macroeconomic and financial variables and found that commodity price predictability varies substantially across economic states, being strongest during economic recessions.
123 citations
TL;DR: In this article, the authors present and estimate a model of the prices of oil and other storable commodities, a model that can be characterized as reflecting the carry trade, focusing on speculative factors, here defined as the trade-off between interest rates on the one hand and market participants' expectations of future price changes on the other hand.
105 citations
TL;DR: This article investigated the role of crude oil spot and futures prices in the process of price discovery by using a cost-of-carry model with an endogenous convenience yield and daily data over the period from January 1990 to December 2008.
Abstract: We investigate the role of crude oil spot and futures prices in the process of price discovery by using a cost-of-carry model with an endogenous convenience yield and daily data over the period from January 1990 to December 2008. We provide evidence that futures markets play a more important role than spot markets in the case of contracts with shorter maturities, but the relative contribution of the two types of market turns out to be highly unstable, especially for the most deferred contracts. The implications of these results for hedging and forecasting crude oil spot prices are also discussed.
95 citations
Proceedings Article•
05 Mar 2014TL;DR: This paper introduces an online learning algorithm for resource allocation that dynamically adapts resource allocation by learning from its performance on prior job executions while incorporating history of spot prices and workload characteristics.
Abstract: Cloud computing provides an attractive computing paradigm in which computational resources are rented on-demand to users with zero capital and maintenance costs. Cloud providers offer different pricing options to meet computing requirements of a wide variety of applications. An attractive option for batch computing is spot-instances, which allows users to place bids for spare computing instances and rent them at a (often) substantially lower price compared to the fixed on-demand price. However, this raises three main challenges for users: how many instances to rent at any time? what type (on-demand, spot, or both)? and what bid value to use for spot instances? In particular, renting on-demand risks high costs while renting spot instances risks job interruption and delayed completion when the spot market price exceeds the bid. This paper introduces an online learning algorithm for resource allocation to address this fundamental tradeoff between computation cost and performance. Our algorithm dynamically adapts resource allocation by learning from its performance on prior job executions while incorporating history of spot prices and workload characteristics. We provide theoretical bounds on its performance and prove that the average regret of our approach (compared to the best policy in hindsight) vanishes to zero with time. Evaluation on traces from a large datacenter cluster shows that our algorithm outperforms greedy allocation heuristics and quickly converges to a small set of best performing policies.
91 citations
TL;DR: In this article, the authors designed a complex network approach for examining the dynamics of the co-movement between crude oil futures and spot prices and analyzed the transformation characteristics between the modes by weighted complex network models and evolutionary models.
84 citations
TL;DR: In this paper, the authors investigate how electricity markets relate to emission allowance prices and find that natural gas, oil prices and the switching possibilities between gas and coal for electricity generation are significant drivers of the carbon futures price.
64 citations
TL;DR: In this paper, a dynamic equilibrium model of storable commodities populated by producers, dealers, and households is constructed, which leads to lower equilibrium excess returns on futures, a more frequently upwardsloping futures curve, and higher volatility in futures and spot markets.
Abstract: I construct a dynamic equilibrium model of storable commodities populated by producers, dealers, and households. When financial innovation allows households to trade in futures markets, they choose a long position that leads to lower equilibrium excess returns on futures, a more frequently upward-sloping futures curve, and higher volatility in futures and spot markets. The effect on spot price levels is modest, and extremely high spot prices only occur in conjunction with low inventories and poor productivity. Therefore such "financialization'' of commodities may explain several recently observed changes in spot and futures market dynamics, but it cannot directly account for a large increase in spot prices.
62 citations
TL;DR: In this article, the authors find that price discovery is absent between the onshore and offshore spot markets, and they conclude that the price discovery differences in the offshore markets stem from the offshore spot and forward contracts tracking different aspects of yuan rates.
Abstract: The People's Bank of China (PBC) lifted yuan trading restrictions in July of 2010 that led to offshore yuan spot trading in Hong Kong. Based on causality analyses, we find that price discovery is absent between the onshore and offshore spot markets. However, we document the presence of price discovery between onshore spot and offshore nondeliverable forward (NDF) rates. These seemingly inconsistent results present a puzzle wherein one offshore market appears to be more informationally integrated with the onshore market than another. We conclude that price discovery differences in the offshore markets stem from the offshore spot and forward contracts tracking different aspects of yuan rates (e.g., the offshore nondeliverable rate tracks onshore spot rates whereas the offshore spot rate tracks onshore interest rates). Moreover, the introduction of offshore spot trading in Hong Kong has led to an increase in cross-market price discovery between onshore spot and offshore NDF rates. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 34:103–123, 2014
TL;DR: This paper analyzes electricity spot-prices of the Italian Power Exchange IPEX and proposes three different methods to model prices time series: a discrete-time univariate econometric model ARMA-GARCH and two computational-intelligence techniques Neural Network and Support Vector Machine.
Abstract: In European countries, the last decade has been characterized by a deregulation of power production and electricity became a commodity exchanged in proper markets. This resulted in an increasing interest of the scientific community on electricity exchanges for modeling both market activity and price process. This paper analyzes electricity spot-prices of the Italian Power Exchange IPEX and proposes three different methods to model prices time series: a discrete-time univariate econometric model ARMA-GARCH and two computational-intelligence techniques Neural Network and Support Vector Machine. Price series exhibit a strong daily seasonality, addressed by analyzing separately a series for each of the 24 hours. One-day ahead forecasts of hourly prices have been considered so to compare the prediction performances of three different methods, with respect to the canonical benchmark model based on the random walk hypothesis. Results point out that Support Vector Machine methodology gives better forecasting accuracy for price time series, closely followed by the econometric technique.
TL;DR: In this paper, the authors investigated whether a lead-lag relationship exists between the spot market and the futures market in Thailand during the period 2006 through 2012 and found that lagged changes in spot prices lead changes in futures prices.
Abstract: This study investigates whether a lead–lag relationship exists between the spot market and the futures market in Thailand during the period 2006 through 2012. In a rational, efficient market, returns on derivative securities and their underlying assets should be perfectly contemporaneously correlated. However, due to market imperfections, one of these two markets may reflect information faster. Using daily data, our results show that there is a price discovery in the Thailand futures market. We find that lagged changes in spot prices lead changes in futures prices. Our results are robust to the use of an alternative equity index. Our results show that the error correction model, which utilizes the traditional linear model, is found to be the best forecasting model. Furthermore, we find that a trading strategy based on this model outperforms the market even after allowing for transaction costs.
TL;DR: The authors examined the relation among daily returns to crude oil prices, equity prices, and commodity markets by modifying previous efforts in two important ways; expanding the model to include the equity price for an oil-producing firm, ConocoPhillips, which ameliorated omitted variable bias and estimating the expanded model using the Kalman Filter, which reduces uncertainty associated with OLS estimates from rolling windows.
TL;DR: In this paper, the authors examined the impact of futures trading on the European real estate securities market and found that futures trading did not destabilize the underlying listed market, and also revealed that the introduction of a futures market has improved the speed and quality of information flowing to the spot market.
Abstract: In 2007 futures contracts were introduced based upon the listed real estate market in Europe. Following their launch they have received increasing attention from property investors, however, few studies have considered the impact their introduction has had. This study considers two key elements. Firstly, a traditional Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, the approach of Bessembinder & Seguin (1992) and the Gray’s (1996) Markov-switching-GARCH model are used to examine the impact of futures trading on the European real estate securities market. The results show that futures trading did not destabilize the underlying listed market. Importantly, the results also reveal that the introduction of a futures market has improved the speed and quality of information flowing to the spot market. Secondly, we assess the hedging effectiveness of the contracts using two alternative strategies (naive and Ordinary Least Squares models). The empirical results also show that the contracts are effective hedging instruments, leading to a reduction in risk of 64 %.
26 Jun 2014
TL;DR: In this article, the forward price dynamics in commodity markets are modeled as a process with values in a Hilbert space of absolutely continuous functions defined by Filipovic (consistency problems for Heath-Jarrow-Morton interest rate models, 2001).
Abstract: We study the forward price dynamics in commodity markets realised as a process with values in a Hilbert space of absolutely continuous functions defined by Filipovic (Consistency problems for Heath–Jarrow–Morton interest rate models, 2001). The forward dynamics are defined as the mild solution of a certain stochastic partial differential equation driven by an infinite-dimensional Levy process. It is shown that the associated spot price dynamics can be expressed as a sum of Ornstein–Uhlenbeck processes, or more generally, as a sum of certain stationary processes. These results link the possibly infinite-dimensional forward dynamics to classical commodity spot models. We continue with a detailed analysis of multiplication and integral operators on the Hilbert spaces and show that Hilbert–Schmidt operators are essentially integral operators. The covariance operator of the Levy process driving the forward dynamics and the diffusion term can both be specified in terms of such operators, and we analyse in several examples the consequences on model dynamics and their probabilistic properties. Also, we represent the forward price for contracts delivering over a period in terms of an integral operator, a case being relevant for power and gas markets. In several examples, we reduce our general model to existing commodity spot and forward dynamics.
TL;DR: In this article, the authors use network theory to analyze the interactions of a representative sample of 13 European (EU) electricity spot prices during the period 2007-2012, and construct 7651 dynamic multivariate networks, where the nodes correspond to different EU countries and the links weight the Granger-causality between the variations of the respective electricity prices.
TL;DR: In this paper, a new modeling framework for electricity futures markets based on so-called ambit fields is proposed, which can capture many of the stylised facts observed in electricity futures and is highly analytically tractable.
Abstract: In this paper we propose a new modelling framework for electricity futures markets based on so-called ambit fields. The new model can capture many of the stylised facts observed in electricity futures and is highly analytically tractable. We discuss martingale conditions, option pricing, and change of measure within the new model class. Also, we study the corresponding model for the spot price, which is implied by the new futures model, and show that, under certain regularity conditions, the implied spot price can be represented in law as a volatility modulated Volterra process.
TL;DR: In this article, the behavior of U.S. natural gas futures and spot prices on and around the weekly announcements by the EIA of the amount of natural gas in storage was studied.
TL;DR: In this paper, the authors examined the direction, strength and extent of causal relationship between futures and spot prices of Indian commodity markets using frequency domain approach of Breitung and Candelon (2006).
TL;DR: In this paper, the authors explore the relationship between congestion and spot prices using a simple network model, paying particular attention to the influence of storage and find that as congestion between two hubs increases, the scarcity value of transmission capacity rises, driving a wedge between spot prices.
Abstract: In the U.S., natural gas pipeline transport has undergone a wave of deregulatory actions over the past several decades. The underlying motive has been the presumption that removing regulatory frictions would facilitate spot price arbitrage, helping to integrate prices across geographic locations and improve efficiency. Yet certain frictions, specifically the effect of congestion on transportation costs, inhibit positive deregulatory impacts on efficiency. With the increase in domestic production and consumption of natural gas over the coming decades, upward pressure on the demand for transport will likely result in an increased occurrence of persistently congested pipeline routes. In this paper we explore the relationship between congestion and spot prices using a simple network model, paying particular attention to the influence of storage. We find that as congestion between two hubs increases, the scarcity value of transmission capacity rises, driving a wedge between spot prices. We empirically quantify this effect over a specific pipeline route in the Rocky Mountain region that closely resembles our structural design. Although our results paint a stark picture of the impact that congestion can have on efficiency, we also find evidence that the availability of storage mitigates the price effects of congestion through the intertemporal substitution of transmission services.
Journal Article•
TL;DR: In this article, the authors investigate the emergence of spot electricity markets with particular emphasis on Indian electricity market which has never been done before and review selected finance and econometrics inspired literature and models for forecasting electricity spot prices.
Abstract: In the new framework of competitive electricity markets, all power market participants need accurate price forecasting tools. Electricity price forecasts characterize significant information that can help captive power producer, independent power producer, power generation companies, power distribution companies or open access consumers in careful planning of their bidding strategies for maximizing their profits, benefits and utilities from long term, medium term and short term perspective. Short term spot electricity price forecasting techniques are either inspired from electrical engineering literature (i.e. load forecasting) or from economics literature (i.e. game theory models and the time-series econometric models). In this study we investigate the emergence of spot electricity markets with particular emphasis on Indian electricity market which has never been done before and review selected finance and econometrics inspired literature and models for forecasting electricity spot prices in deregulated wholesale spot electricity markets.
TL;DR: In this article, the authors examined the market efficiency of the commodity futures market in India and found that a cointegrating relationship exists between these indices and that the market appears efficient during the more recent sub-sample period since July 2009 onwards.
Abstract: This article aims to examine the market efficiency of the commodity futures market in India, which has been growing phenomenally over the last few years. We estimate the long-run equilibrium relationship between multi-commodity futures and spot prices and then test for weak-form market efficiency by applying both the dynamic ordinary least squares and fully modified ordinary least squares methods. The entire sample period is from 2 January 2006 to 31 March 2011. The results indicate that a cointegrating relationship exists between these indices and that the commodity futures market appears efficient during the more recent sub-sample period since July 2009 onwards.
Posted Content•
TL;DR: In this article, the authors investigate the potential presence of jumps in natural gas spot prices in the U.S. and U.K. and find compelling empirical evidence for the importance of jumps.
Abstract: Natural gas is likely to become increasingly important in the future. Understanding the stochastic underpinnings of natural gas prices will be critical, both to policy analysts and to market participants. To this end, we investigate the potential presence of jumps in natural gas spot prices in the U. S. and in the U. K. We find compelling empirical evidence for the importance of jumps in both markets, though jumps appear to appear more frequently in the U. K. Some of the difference between the U.S. and U.K. jump probabilities may be due to oil prices, other factors play a role.
TL;DR: In this article, the authors show that the stock-to-use ratio and the degree of internationalization are the most systematically statistically significant coefficients among commodities, and that over time, consecutive low stock to use ratios and a thin international market provoke typically high volatility.
TL;DR: In this paper, the authors provide empirical support for Tilton et al.'s hypothesis that investor demand on futures markets affects spot and futures prices similarly when the markets are in strong contango but somewhat less so when they are in weak contango or backwardation.
TL;DR: In this article, the authors present three relatively simple spot price forecast models for the Nord Pool market based on historic spot and futures prices including data for inflow and reservoir levels, which achieve a relatively accurate forecast of the weekly spot prices.
TL;DR: In this paper, a self-exciting marked point process model is proposed to capture the stylized attributes of electricity spot prices, such as the clustering of extremes, heavy tails and common spikes.
TL;DR: In this article, the authors study option-implied interest rate forecasts and the development of risk premium and state prices in the Euribor futures option market using parametric and non-parametric statistical calibration.
Abstract: In this paper we study option-implied interest rate forecasts and the development of risk premium and state prices in the Euribor futures option market. Using parametric and non-parametric statistical calibration, we transform the risk-neutral option implied densities for the Euribor futures rate into real-world densities. We investigate the period from the introduction of the Euro in 1999 until December 2012. The estimated densities are used to provide a measure for the interest rate risk premium and state prices implicit in the futures market. We find that the real-world option-implied distributions can be used to forecast the futures rate, while the forecasting ability of the risk-neutral distributions is rejected. The state price densities in the market show a U-shaped curve suggesting that investors price higher states with high and low rates compared to the expected spot rate. However, we show that, in general, state prices have a more pronounced right tail, implying that investors are more risk averse to increasing interest rates. We also document a negative market price of interest rate risk which generates positive premium for the futures contract.
TL;DR: In this paper, the authors derived 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.
Abstract: 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.