Titlebook: Applications of Fourier Transform to Smile Modeling; Theory and Implement Jianwei Zhu Book 2010Latest edition Springer-Verlag Berlin Heidel

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Applications of Fourier Transform to Smile Modeling978-3-642-01808-4Series ISSN 1616-0533 Series E-ISSN 2195-0687

冒號

Marian Brezina,Jonathan Hu,Ray Tuminaro and begin with the next chapter directly. A Brownian motion is an elemental building-block in modeling the dynamics of stock returns, and correspondingly the geometric Brownian motion as an exponential function of Brownian motion is the simplest and most popular process for stock prices, on which t

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Marian Brezina,Jonathan Hu,Ray Tuminarock price is analytically unknown. To express (quasi-) closed-form exercise probabilities and valuation formula, characteristic functions of the underlying stock returns (logarithms) are proven to be not only a powerful and convenient tool to achieve analytical tractability, but also a large accommod

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ironic

Marian Brezina,Jonathan Hu,Ray Tuminarostic volatility models is crucial for a sound performance of the pricing engine and the model calibration, and includes some different aspects: the numerical integration of (inverse) Fourier transform, the computation of functions of complex number, especially the logarithm of complex number, the ca

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駁船

https://doi.org/10.1007/978-0-387-09766-4a based on a stock price process generated by a mixture of a Brownian motion and a Poisson process. This mixed process is also called the jump-diffusion process. The requirement for a jump component in a stock price process is intuitive, and supported by the big crashes in stock markets: The Black M

軟弱

https://doi.org/10.1007/978-0-387-09766-4 be regarded as two special cases of Lévy process, and have only finite activity in a finite time interval. In this chapter, we only consider Lévy processes with infinity activity in a finite time interval. With respect to jump event modeling in finance, compound Poisson jumps discussed in Chapter 7