scholarly journals Stochastic approach to model spot price and value forward contracts on energy markets under uncertainty

2021 ◽  
Author(s):  
Michał Pawłowski ◽  
Piotr Nowak
Keyword(s):  
Analytical Formula ◽  
Stochastic Approach ◽  
Spot Price ◽  
Fuzzy Arithmetic ◽  
Model Parameters ◽  
Electricity Prices ◽  
Forward Contracts ◽  
Spot Prices ◽  
Hyperexponential Distribution ◽  
Diffusion With Jumps

AbstractThe paper deals with a model of electricity spot prices. The proposed dynamics of electricity spot prices is driven by a mean reverting diffusion with jumps having hyperexponential distribution. The analytical formula for the forward contract’s price is derived in a crisp case. Inasmuch as the model parameters are considered to be evaluated imprecisely, their fuzzy counterparts are introduced. With usage of the fuzzy arithmetic, the analytical expression for the forward contract’s price is derived. Several numerical examples highlighting attributes of the fuzzy forward electricity prices are brought out.

scholarly journals A STRUCTURAL RISK-NEUTRAL MODEL OF ELECTRICITY PRICES

2009 ◽  
Vol 12 (07) ◽  
pp. 925-947 ◽  
Author(s):  
RENÉ AÏD ◽  
LUCIANO CAMPI ◽  
ADRIEN NGUYEN HUU ◽  
NIZAR TOUZI
Keyword(s):  
Electricity Market ◽  
Structural Aspect ◽  
Electricity Prices ◽  
Forward Contracts ◽  
Spot Prices ◽  
Modeling Methodology ◽  
Risk Neutral ◽  
Risk Neutral Probabilities ◽  
Crude Approximation ◽  
Forward Prices

The objective of this paper is to present a model for electricity spot prices and the corresponding forward contracts, which relies on the underlying market of fuels, thus avoiding the electricity non-storability restriction. The structural aspect of our model comes from the fact that the electricity spot prices depend on the dynamics of the electricity demand at the maturity T, and on the random available capacity of each production means. Our model explains, in a stylized fact, how the prices of different fuels together with the demand combine to produce electricity prices. This modeling methodology allows one to transfer to electricity prices the risk-neutral probabilities of the market of fuels and under the hypothesis of independence between demand and outages on one hand, and prices of fuels on the other hand, it provides a regression-type relation between electricity forward prices and forward prices of fuels. Moreover, the model produces, by nature, the well-known peaks observed on electricity market data. In our model, spikes occur when the producer has to switch from one technology to the lowest cost available one. Numerical tests performed on a very crude approximation of the French electricity market using only two fuels (gas and oil) provide an illustration of the potential interest of this model.

scholarly journals An Ambit Stochastic Approach to Pricing Electricity Forward Contracts: The Case of the German Energy Market

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Luca Di Persio ◽  
Isacco Perin
Keyword(s):  
Stochastic Model ◽  
Detailed Analysis ◽  
Energy Exchange ◽  
Stochastic Approach ◽  
Forward Model ◽  
Energy Market ◽  
Spot Price ◽  
Exchange Market ◽  
Forward Contracts ◽  
Forward Prices

We propose an ambit stochastic model to study the electricity forward prices. We provide a detailed analysis of the probabilistic properties of such model, discussing the related martingale conditions and deriving concrete implementation of it for the related underlying spot price. The latter is obtained from the forward model through a limiting argument. Furthermore, we show, also providing a concrete example, that a proper specification of these models is able to effectively forecast prices of forward contracts written on the European Energy Exchange (EEX) AG, or German Energy Exchange, market.

scholarly journals ANALYSIS OF SOYBEAN TRADE STRATEGIES WITH FORWARD CONTRACTS ON THE CHICAGO STOCK EXCHANGE AND ON THE SPOT MARKET IN CASCAVEL, BRAZIL

2019 ◽  
Vol 12 (4) ◽  
pp. 1487
Author(s):  
Odilon Felipe Tavares Aguiar ◽  
Jonathan Dias Ferreira
Keyword(s):  
Stock Exchange ◽  
Spot Market ◽  
Spot Price ◽  
Spot Markets ◽  
Forward Contracts ◽  
Spot Prices ◽  
Forward Markets ◽  
Market Risks ◽  
The Moment ◽  
Chicago Board Of Trade

In the wake of frequent variables that interfere with the agricultural market, rural agents (producers) suffer liabilities due to their decisions, especially at the moment of commercialization. The forward market is precisely a strategy that may reduce the risks in oscillating prices of commodities and makes way towards the future formation of prices. Current paper compares the commercialization of soybeans in the forward and spot markets in terms of prices practiced between the harvest years 2011/2012 and 2016/2017. Data provided by the Chicago Board of Trade (CBOT) were used as reference for forward contracts traded in September with maturation in January and spot prices practiced in January retrieved from data from Coopavel in Cascavel PR Brazil. Forward contracts traded in September with maturity in January had a better performance when compared to January spot prices for harvests 2011/2012, 2012/2013, 2013/2014. Due to fluctuations in weather and market trends, they were the factors that weighed most on harvests 2014/2015, 2015/2016 and 2016/2017 for better prices on most of the maturities for January on the spot market. Results show that, although spot price was better in certain periods, the marketing strategy on forward markets is highly interesting since the producer can employ profits and have guarantees against market risks

Pricing of Futures Contracts

2018 ◽  
Author(s):  
Timothy A. Krause
Keyword(s):  
Fair Value ◽  
Commodity Futures ◽  
Futures Contracts ◽  
Spot Price ◽  
Futures Prices ◽  
No Arbitrage ◽  
Spot Prices ◽  
Cost Of Carry ◽  
Contract Expiration ◽  
The Cost

This chapter examines the relation between futures prices relative to the spot price of the underlying asset. Basic futures pricing is characterized by the convergence of futures and spot prices during the delivery period just before contract expiration. However, “no arbitrage” arguments that dictate the fair value of futures contracts largely determine pricing relations before expiration. Although the cost of carry model in its various forms largely determines futures prices before expiration, the chapter presents alternative explanations. Related commodity futures complexes exhibit mean-reverting behavior, as seen in commodity spread markets and other interrelated commodities. Energy commodity futures prices can be somewhat accurately modeled as a generalized autoregressive conditional heteroskedastic (GARCH) process, although whether these models provide economically significant excess returns is uncertain.

scholarly journals A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 388
Author(s):  
Riccardo De Blasis ◽  
Giovanni Batista Masala ◽  
Filippo Petroni
Keyword(s):  
Markov Model ◽  
Electricity Market ◽  
Wind Farm ◽  
Central Italy ◽  
High Order ◽  
Distribution Model ◽  
Spot Price ◽  
Model Parameters ◽  
Price Series ◽  
Cross Correlations

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm.

scholarly journals High-Resolution Electricity Spot Price Forecast for the Danish Power Market

2020 ◽  
Vol 12 (10) ◽  
pp. 4267 ◽  
Author(s):  
Jannik Schütz Roungkvist ◽  
Peter Enevoldsen ◽  
George Xydis
Keyword(s):  
Electricity Market ◽  
Thermal Power ◽  
Power Market ◽  
Power Production ◽  
Spot Price ◽  
Price Forecasting ◽  
Learning Approaches ◽  
Electricity Prices ◽  
Price Forecast ◽  
Electricity Spot Price

Energy markets with a high penetration of renewables are more likely to be challenged by price variations or volatility, which is partly due to the stochastic nature of renewable energy. The Danish electricity market (DK1) is a great example of such a market, as 49% of the power production in DK1 is based on wind power, conclusively challenging the electricity spot price forecast for the Danish power market. The energy industry and academia have tried to find the best practices for spot price forecasting in Denmark, by introducing everything from linear models to sophisticated machine-learning approaches. This paper presents a linear model for price forecasting—based on electricity consumption, thermal power production, wind production and previous electricity prices—to estimate long-term electricity prices in electricity markets with a high wind penetration levels, to help utilities and asset owners to develop risk management strategies and for asset valuation.

scholarly journals SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence

2020 ◽  
Vol 17 (10) ◽  
pp. 3535 ◽  
Author(s):  
Alberto Godio ◽  
Francesca Pace ◽  
Andrea Vergnano
Keyword(s):  
Particle Swarm Optimization ◽  
Stochastic Approach ◽  
Model Parameters ◽  
Medium Term ◽  
Swarm Optimization ◽  
Community Mobility ◽  
Italian Regions ◽  
The World ◽  
Model Equations ◽  
Official Data

We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardy, Piedmont, and Veneto regions. We focused on the application of a stochastic approach in fitting the model parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyzed the official data and the predicted evolution of the epidemic in the Italian regions, and we compared the results with the data and predictions of Spain and South Korea. We linked the model equations to the changes in people’s mobility, with reference to Google’s COVID-19 Community Mobility Reports. We discussed the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

scholarly journals Research on Risk Control under the Background of Electricity Futures Market

2020 ◽  
Vol 165 ◽  
pp. 06032
Author(s):  
Suyuan Chang ◽  
Dunnan Liu ◽  
Xiaoyu Li
Keyword(s):  
Electricity Market ◽  
Effective Means ◽  
Futures Market ◽  
Spot Price ◽  
Price Difference ◽  
Forward Contracts ◽  
Hedging Strategies ◽  
Futures Hedging ◽  
The Difference ◽  
Market Factors

In the process of electricity marketization, the electricity futures market is an effective means to avoid the risk of electricity price fluctuations. Based on the background of the electricity futures market, this article first analyzes the physical and market factors of the price fluctuation risk in the electricity market; then, it studies the principle and implementation effects of the power futures hedging function; finally, the manufacturer’s strategy of hedging based on the price difference between the spot price of electricity and the price of forward contracts has been studied in detail. This article believes that the electricity futures market can effectively hedge the spot market risk, and hedging strategies based on the difference between the spot price and the forward price are better.

scholarly journals Simplified Building Thermal Model Development and Parameters Evaluation Using a Stochastic Approach

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2899
Author(s):  
Abhinandana Boodi ◽  
Karim Beddiar ◽  
Yassine Amirat ◽  
Mohamed Benbouzid
Keyword(s):  
Reference Model ◽  
Model Development ◽  
Network Models ◽  
Real Data ◽  
Stochastic Approach ◽  
Simplified Model ◽  
Model Parameters ◽  
Order Model ◽  
Parameter Values ◽  
Low Order

This paper proposes an approach to develop building dynamic thermal models that are of paramount importance for controller application. In this context, controller requires a low-order, computationally efficient, and accurate models to achieve higher performance. An efficient building model is developed by having proper structural knowledge of low-order model and identifying its parameter values. Simplified low-order systems can be developed using thermal network models using thermal resistances and capacitances. In order to determine the low-order model parameter values, a specific approach is proposed using a stochastic particle swarm optimization. This method provides a significant approximation of the parameters when compared to the reference model whilst allowing low-order model to achieve 40% to 50% computational efficiency than the reference one. Additionally, extensive simulations are carried to evaluate the proposed simplified model with solar radiation and identified model parameters. The developed simplified model is afterward validated with real data from a case study building where the achieved results clearly show a high degree of accuracy compared to the actual data.

Over-the-counter forward contracts and spot price volatility in shipping

2004 ◽  
Vol 40 (4) ◽  
pp. 273-296 ◽  
Author(s):  
Manolis G. Kavussanos ◽  
Ilias D. Visvikis ◽  
Roy A. Batchelor
Keyword(s):  
Price Volatility ◽  
Spot Price ◽  
Forward Contracts ◽  
Over The Counter
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