• 제목/요약/키워드: black scholes model with two assets

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THE DYNAMICS OF EUROPEAN-STYLE OPTION PRICING IN THE FINANCIAL MARKET UTILIZING THE BLACK-SCHOLES MODEL WITH TWO ASSETS, SUPPORTED BY VARIATIONAL ITERATION TECHNIQUE

  • FAROOQ AHMED SHAH;TAYYAB ZAMIR;EHSAN UL HAQ;IQRA ABID
    • Journal of Applied and Pure Mathematics
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    • 제6권3_4호
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    • pp.141-154
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    • 2024
  • This article offers a thorough exploration of a modified Black-Scholes model featuring two assets. The determination of option prices is accomplished through the Black-Scholes partial differential equation, leveraging the variational iteration method. This approach represents a semi-analytical technique that incorporates the use of Lagrange multipliers. The Lagrange multiplier emerges as a beacon of efficiency, adeptly streamlining the computational intricacies, and elevating the model's efficacy to unprecedented heights. For better understanding of the presented system, a graphical and tabular interpretation is presented with the help of Maple software.

국면전환 블랙-숄즈 모형에서 정합성을 가진 모수의 추정 (Calibrated Parameters with Consistency for Option Pricing in the Two-state Regime Switching Black-Scholes Model)

  • 한규식
    • 대한산업공학회지
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    • 제36권2호
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    • pp.101-107
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    • 2010
  • Among a variety of asset dynamics models in order to explain the common properties of financial underlying assets, parametric models are meaningful when their parameters are set reliably. There are two main methods from which we can obtain them. They are to use time-series data of an underlying price or the market option prices of the underlying at one time. Based on the Girsanov theorem, in the pure diffusion models, the parameters calibrated from the option prices should be partially equivalent to those from time-series underling prices. We call this phenomenon model consistency. In this paper, we verify that the two-state regime switching Black-Scholes model is superior in the sense of model consistency, comparing with two popular conventional models, the Black-Scholes model and Heston model.