Search results for "60g10"

showing 7 items of 7 documents

Futures pricing in electricity markets based on stable CARMA spot models

2012

We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary independent increments process for the low-frequency dynamics, and model the large uctuations by a non-Gaussian stable CARMA process. The model allows for analytic futures prices, and we apply these to model and estimate the whole market consistently. Besides standard parameter estimation, an estimation procedure is suggested, where we t the non-stationary trend using futures data with long time until delivery, and a robust L 1 -lter to nd the states of …

FOS: Computer and information sciencesEconomics and EconometricsElectricity spot pricebusiness.industryEstimation theoryRisk premium60G52 62M10 91B84 (Primary) 60G10 60G51 91B70 (Secondary)Lévy processStatistics - ApplicationsCARMA model electricity spot prices electricity forward prices continuous time linear model Lévy process stable CARMA process risk premium robust filterddc:MicroeconomicsFOS: Economics and businessGeneral EnergyBase load power plantPeak loadEconometricsEconomicsApplications (stat.AP)ElectricityPricing of Securities (q-fin.PR)businessFutures contractQuantitative Finance - Pricing of Securities
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Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

2013

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. The second-order structure and stationarity of the model are analyzed in detail. A simulation method for Monte Carlo generation of price paths is introduced and a numerical example is presented.

Statistics and Probability15A04Spot contractSABR volatility model01 natural sciences010104 statistics & probabilityEnergy marketVolatility swap0502 economics and businessEconometricsForward volatilityMean reversionstochastic volatilityleverage0101 mathematicsMathematics050208 financeStochastic volatilityApplied Mathematics05 social sciences91G60subordinator91G20Constant elasticity of variance modelVolatility smileOrnstein-Uhlenbeck process60H3060G1060G51Advances in Applied Probability
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Self-stabilizing processes: uniqueness problem for stationary measures and convergence rate in the small-noise limit

2011

In the context of self-stabilizing processes, that is processes attracted by their own law, living in a potential landscape, we investigate different properties of the invariant measures. The interaction between the process and its law leads to nonlinear stochastic differential equations. In [S. Herrmann and J. Tugaut. Electron. J. Probab. 15 (2010) 2087–2116], the authors proved that, for linear interaction and under suitable conditions, there exists a unique symmetric limit measure associated to the set of invariant measures in the small-noise limit. The aim of this study is essentially to point out that this statement leads to the existence, as the noise intensity is small, of one unique…

Statistics and ProbabilityMcKean-Vlasov equationLaplace transformdouble-well potential010102 general mathematicsMathematical analysisFixed-point theoremfixed point theoremDouble-well potentialInvariant (physics)01 natural sciencesself-interacting diffusionuniqueness problem[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]010104 statistics & probabilityRate of convergenceLaplace's methodUniquenessInvariant measureperturbed dynamical systemstationary measures0101 mathematicsLaplace's methodprimary 60G10; secondary: 60J60 60H10 41A60Mathematics
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Variable Length Memory Chains: Characterization of stationary probability measures

2021

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, turn out to be an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability theory. The question of the existence of stationary probability measures leads us to introduce a key combinatorial structure for words produced by a VLMC: the Longest Internal Suffix. This notion allows us to state a necessary and sufficient condition for a general VLMC to admit a unique invariant probability measure. This condition turns out to get a much simpler form for a subclass of VLMC: the stable VLMC. This natural subclass, unlike the general case, enj…

Statistics and ProbabilityPure mathematicsLongest Internal SuffixStationary distributionMarkov chain60J05 60C05 60G10Probability (math.PR)010102 general mathematics01 natural sciencesMeasure (mathematics)Variable Length Memory Chains010104 statistics & probabilityProbability theoryConvergence of random variablesFOS: MathematicsCountable setState spaceRenewal theory[MATH]Mathematics [math]0101 mathematicsstable context treessemi-Markov chainsMathematics - Probabilitystationary probability measureMathematicsBernoulli
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Pricing of Forwards and Options in a Multivariate Non-Gaussian Stochastic Volatility Model for Energy Markets

2013

In Benth and Vos (2013) we introduced a multivariate spot price model with stochastic volatility for energy markets which captures characteristic features, such as price spikes, mean reversion, stochastic volatility, and inverse leverage effect as well as dependencies between commodities. In this paper we derive the forward price dynamics based on our multivariate spot price model, providing a very flexible structure for the forward curves, including contango, backwardation, and hump shape. Moreover, a Fourier transform-based method to price options on the forward is described.

TheoryofComputation_MISCELLANEOUSspread optionStatistics and Probability15A04Computer Science::Computer Science and Game TheoryFinancial economicsNormal backwardationImplied volatility01 natural sciences010104 statistics & probabilityEnergy marketVolatility swap0502 economics and businessEconometricsForward volatilitystochastic volatility0101 mathematicsMathematics050208 financeStochastic volatilityApplied Mathematics05 social sciencesContangosubordinatorforward pricing91G20Forward priceVolatility smile60H3060G1060G51Advances in Applied Probability
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Characterization of stationary probability measures for Variable Length Markov Chains

2020

By introducing a key combinatorial structure for words produced by a Variable Length Markov Chain (VLMC), the longest internal suffix, precise characterizations of existence and uniqueness of a stationary probability measure for a VLMC chain are given. These characterizations turn into necessary and sufficient conditions for VLMC associated to a subclass of probabilised context trees: the shift-stable context trees. As a by-product, we prove that a VLMC chain whose stabilized context tree is again a context tree has at most one stationary probability measure.

[MATH.MATH-PR]Mathematics [math]/Probability [math.PR][MATH.MATH-PR] Mathematics [math]/Probability [math.PR]60J05 60C05 60G10Probability (math.PR)FOS: MathematicsMathematics - Probability
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Extracting Conditionally Heteroskedastic Components using Independent Component Analysis

2020

In the independent component model, the multivariate data are assumed to be a mixture of mutually independent latent components. The independent component analysis (ICA) then aims at estimating these latent components. In this article, we study an ICA method which combines the use of linear and quadratic autocorrelations to enable efficient estimation of various kinds of stationary time series. Statistical properties of the estimator are studied by finding its limiting distribution under general conditions, and the asymptotic variances are derived in the case of ARMA-GARCH model. We use the asymptotic results and a finite sample simulation study to compare different choices of a weight coef…

asymptotic normalityautocorrelationOriginal Articlesaikasarja-analyysiprincipal volatility componentARMA-GARCH processmonimuuttujamenetelmätblind source separationGARCH-mallit62m10ARMA‐GARCH processOriginal Articletilastolliset mallit60g10
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