• Title/Summary/Keyword: option pricing

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ASYMPTOTIC OPTION PRICING UNDER A PURE JUMP PROCESS

  • Song, Seong-Joo
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.237-256
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    • 2007
  • This paper studies the problem of option pricing in an incomplete market. The market incompleteness comes from the discontinuity of the underlying asset price process which is, in particular, assumed to be a compound Poisson process. To find a reasonable price for a European contingent claim, we first find the unique minimal martingale measure and get a price by taking an expectation of the payoff under this measure. To get a closed-form price, we use an asymptotic expansion. In case where the minimal martingale measure is a signed measure, we use a sequence of martingale measures (probability measures) that converges to the equivalent martingale measure in the limit to compute the price. Again, we get a closed form of asymptotic option price. It is the Black-Scholes price and a correction term, when the distribution of the return process has nonzero skewness up to the first order.

Pricing Outside Floating-Strike Lookback Options

  • Lee, Hang-Suck
    • The Korean Journal of Applied Statistics
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    • v.22 no.1
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    • pp.59-73
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    • 2009
  • A floating-strike lookback call option gives the holder the right to buy at the lowest price of the underlying asset. Similarly, a floating-strike lookback put option gives the holder the right to sell at the highest price. This paper will propose an outside floating-strike lookback call (or put) option that gives the holder the right to buy (or sell) one underlying asset at some percentage of the lowest (or highest) price of the other underlying asset. In addition, this paper will derive explicit pricing formulas for these outside floating-strike lookback options. Sections 3 and 4 assume that the underlying assets pay no dividends. In contrast, Section 5 will derive explicit pricing formulas for these options when their underlying assets pay dividends continuously at a rate proportional to their prices. Some numerical examples will be discussed.

COMPARISON OF STOCHASTIC VOLATILITY MODELS: EMPIRICAL STUDY ON KOSPI 200 INDEX OPTIONS

  • Moon, Kyoung-Sook;Seon, Jung-Yon;Wee, In-Suk;Yoon, Choong-Seok
    • Bulletin of the Korean Mathematical Society
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    • v.46 no.2
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    • pp.209-227
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    • 2009
  • We examine a unified approach of calculating the closed form solutions of option price under stochastic volatility models using stochastic calculus and the Fourier inversion formula. In particular, we review and derive the option pricing formulas under Heston and correlated Stein-Stein models using a systematic and comprehensive approach which were derived individually earlier. We compare the empirical performances of the two stochastic volatility models and the Black-Scholes model in pricing KOSPI 200 index options.

Pring Fixed-Strike Lookback Options

  • Lee, Hangsuck
    • Communications for Statistical Applications and Methods
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    • v.11 no.2
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    • pp.213-225
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    • 2004
  • A fixed-strike lookback option is an option whose payoff is determined by the maximum (or minimum) price of the underlying asset within the option's life. Under the Black-Scholes framework, the time-t price of an equity asset follows a geometric Brownian motion. Applying the method of Esscher transforms, this paper will derive explicit pricing formulas for fixed-strike lookback call and put options, respectively. In addition, this paper will show a relationship (duality property) between the pricing formulas of the call and put options. Finally, this paper will derive explicit pricing formulas for the fixed-strike lookback options when their underlying asset pays dividends continuously at a rate proportional to its price.

PRICING OF TIMER DIGITAL POWER OPTIONS BASED ON STOCHSTIC VOLATILITY

  • Mijin Ha;Sangmin Park;Donghyun Kim;Ji-Hun Yoon
    • East Asian mathematical journal
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    • v.40 no.1
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    • pp.63-74
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    • 2024
  • Timer options are financial instruments proposed by Société Générale Corporate and Investment Banking in 2007. Unlike vanilla options, where the expiry date is fixed, the expiry date of timer options is determined by the investor's choice, which is in linked to a variance budget. In this study, we derive a pricing formula for hybrid options that combine timer options, digital options, and power options, considering an environment where volatility of an underlying asset follows a fast-mean-reverting process. Additionally, we aim to validate the pricing accuracy of these analytical formulas by comparing them with the results obtained from Monte Carlo simulations. Finally, we conduct numerical studies on these options to analyze the impact of stochastic volatility on option's price with respect to various model parameters.

PRICING OF POWER OPTIONS UNDER THE REGIME-SWITCHING MODEL

  • Kim, Jerim
    • Journal of applied mathematics & informatics
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    • v.32 no.5_6
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    • pp.665-673
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    • 2014
  • Power options have payoffs that are determined by the price of the underlying asset raised to some power. In this paper, power options are considered under a regime-switching model which can capture complex asset dynamics by permitting switching between different regimes. The pricing formulas for the Laplace transforms of power options are obtained. The prices of power options are calculated using the formulas and compared with the results of the Monte Carlo simulation.

An Option Pricing Model for the Natural Resource Development Projects (해외자원개발사업 평가를 위한 옵션가격 결정모형 연구)

  • Lee, In-Suk;Heo, Eunnyeong
    • Environmental and Resource Economics Review
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    • v.13 no.4
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    • pp.735-761
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    • 2004
  • As a possible alternative to Traditional Discounted Cash Flow Method, "Option Pricing Model" has drawn academic attentions for the last a few decades. However, it has failed to replace traditional DCF method practically due to its mathematical complexity. This paper introduces an option pricing valuation model specifically adjusted for the natural resource development projects. We add market information and industry-specific features into the model so that the model remains objective as well as realistic after the adjustment. The following two features of natural resource development projects take central parts in model construction; product price is a unique source of cash flow's uncertainty, and the projects have cost structure from capital-intense industry, in which initial capital cost takes most part of total cost during the projects. To improve the adaptability of Option Pricing Model specifically to the natural resource development projects, we use Two-Factor Model and Long-term Asset Model for the analysis. Although the model introduced in this paper is still simple and reflects limited reality, we expect an improvement in applicability of option pricing method for the evaluation of natural resource development projects can be made through the process taken in this paper.

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PRICING FLOATING-STRIKE LOOKBACK OPTIONS

  • Lee, Hang-Suck
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.153-158
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    • 2005
  • A floating-strike lookback call option gives the holder the right to buy at the lowest price of the underlying asset. Similarly, a floating-strike lookback put option gives the holder the right to sell at the highest price. This paper will derive explicit pricing formulas for these floating-strike lookback options with flexible monitoring periods. The monitoring periods of these options start at an arbitrary date and end at another arbitrary date before maturity.

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SIMULATIONS IN OPTION PRICING MODELS APPLIED TO KOSPI200

  • Lee, Jon-U;Kim, Se-Ki
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.7 no.2
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    • pp.13-22
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    • 2003
  • Simulations on the nonlinear partial differential equation derived from Black-Scholes equation with transaction costs are performed. These numerical experiments using finite element methods are applied to KOSPI200 in 2002 and the option prices obtained with transaction costs are closer to the real prices in market than the prices used in Korea Stock Exchange.

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