• Title/Summary/Keyword: Gram-Charlier expansion

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Reliability Calculation of Power Generation Systems Using Generalized Expansion

  • Kim, Jin-O
    • Journal of Electrical Engineering and information Science
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    • v.2 no.6
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    • pp.123-130
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    • 1997
  • This paper presents a generalized expansion method for calculating reliability index in power generation systems. This generalized expansion with a gamma distribution is a very useful tool for the approximation of capacity outage probability distribution of generation system. The well-known Gram-Charlier expansion and Legendre series are also studied in this paper to be compared with this generalized expansion using a sample system IEEE-RTS(Reliability Test System). The results show that the generalized expansion with a composite of gamma distributions is more accurate and stable than Gram-Charlier expansion and Legendre series as addition of the terms to be expanded.

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Numerical studies on approximate option prices (근사적 옵션 가격의 수치적 비교)

  • Yoon, Jeongyoen;Seung, Jisu;Song, Seongjoo
    • The Korean Journal of Applied Statistics
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    • v.30 no.2
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    • pp.243-257
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    • 2017
  • In this paper, we compare several methods to approximate option prices: Edgeworth expansion, A-type and C-type Gram-Charlier expansions, a method using normal inverse gaussian (NIG) distribution, and an asymptotic method using nonlinear regression. We used two different types of approximation. The first (called the RNM method) approximates the risk neutral probability density function of the log return of the underlying asset and computes the option price. The second (called the OPTIM method) finds the approximate option pricing formula and then estimates parameters to compute the option price. For simulation experiments, we generated underlying asset data from the Heston model and NIG model, a well-known stochastic volatility model and a well-known Levy model, respectively. We also applied the above approximating methods to the KOSPI200 call option price as a real data application. We then found that the OPTIM method shows better performance on average than the RNM method. Among the OPTIM, A-type Gram-Charlier expansion and the asymptotic method that uses nonlinear regression showed relatively better performance; in addition, among RNM, the method of using NIG distribution was relatively better than others.

Comparison of methods of approximating option prices with Variance gamma processes (Variance gamma 확률과정에서 근사적 옵션가격 결정방법의 비교)

  • Lee, Jaejoong;Song, Seongjoo
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.181-192
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    • 2016
  • We consider several methods to approximate option prices with correction terms to the Black-Scholes option price. These methods are able to compute option prices from various risk-neutral distributions using relatively small data and simple computation. In this paper, we compare the performance of Edgeworth expansion, A-type and C-type Gram-Charlier expansions, a method of using Normal inverse gaussian distribution, and an asymptotic method of using nonlinear regression through simulation experiments and real KOSPI200 option data. We assume the variance gamma model in the simulation experiment, which has a closed-form solution for the option price among the pure jump $L{\acute{e}}vy$ processes. As a result, we found that methods to approximate an option price directly from the approximate price formula are better than methods to approximate option prices through the approximate risk-neutral density function. The method to approximate option prices by nonlinear regression showed relatively better performance among those compared.

Probabilistic Load Flow for Power Systems with Wind Power Considering the Multi-time Scale Dispatching Strategy

  • Qin, Chao;Yu, Yixin;Zeng, Yuan
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1494-1503
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    • 2018
  • This paper proposes a novel probabilistic load flow model for power systems integrated with large-scale wind power, which considers the multi-time scale dispatching features. The ramp limitations of the units and the steady-state security constraints of the network have been comprehensively considered for the entire duration of the study period; thus, the coupling of the system operation states at different time sections has been taken into account. For each time section, the automatic generation control (AGC) strategy is considered, and all variations associated with the wind power and loads are compensated by all AGC units. Cumulants and the Gram-Charlier expansion are used to solve the proposed model. The effectiveness of the proposed method is validated using the modified IEEE RTS 24-bus system and the modified IEEE 118-bus system.

A Study on the Probabilistic Production Cost Simulation by the Mixture of Cumulants Approximation (Mixture of Cumulants Approximaton 법에 의한 발전 시물레이션에 관한 연구)

  • 송길영;김용하
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.1
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    • pp.1-9
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    • 1991
  • This paper describes a new method of calculating expected energy generation and loss of load probability (L.O.L.P) for electric power system operation and expansion planning. The method represents an equivalent load duration curve (E.L.D.C) as a mixture of cumulants approximation (M.O.N.A). By regarding a load distribution as many normal distributions-rather than one normal distribution-and representing each of them in terms of Gram-Charlier expansion, we could improve the accuracy of results. We developed an algorithm which automatically determines the number of distribution and demarcation points. In modeling of a supply system, we made subsets of generators according to the number of generator outage: since the calculation of each subset's moment needs to be processed rapidly, we further developed specific recursive formulae. The method is applied to the test systems and the results are compared with those of cumulant, M.O.N.A. and Booth-Baleriaux method. It is verified that the M.O.C.A. method is faster and more accure than any other method.

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Levy-Type Swaption Pricing Model (Levy-Swaption 가치 평가 모형)

  • Lee, Joon-Hee;Park, Jong-Woo
    • Korean Management Science Review
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    • v.25 no.3
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    • pp.1-12
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    • 2008
  • The Swaption is one of the popular Interest rates derivatives. In spite of such a popularity, the swaption pricing formula is hard to derived within the theoretical consistency. Most of swaption pricing model are heavily depending on the simulation technique. We present a new class of swaption model based on the multi-factor HJM levy-mixture model. A key contribution of this paper is to provide a generalized swaption pricing formula encompassing many market stylize facts. We provide an approximated closed form solution of the swaption price using the Gram-Charlier expansion. Specifically, the solution form is similar to the market models, since our approximation is based on the Lognormal distribution. It can be directly compared with the traditional Black's formula when the size of third and fourth moments are not so large. The proposed extended levy model is also expected to be capable of producing the volatility smiles and skewness.