Fourier Transform Methods in Finance

Β· Β· Β·
Β· John Wiley & Sons
5,0
1Β ΠΎΡ‚Π·ΠΈΠ²
Π•Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°
256
Π‘Ρ‚Ρ€Π°Π½ΠΈΡ†ΠΈ
ΠžΡ†Π΅Π½ΠΊΠΈΡ‚Π΅ ΠΈ ΠΎΡ‚Π·ΠΈΠ²ΠΈΡ‚Π΅ Π½Π΅ са ΠΏΠΎΡ‚Π²ΡŠΡ€Π΄Π΅Π½ΠΈ  НаучСтС ΠΏΠΎΠ²Π΅Ρ‡Π΅

Всичко Π·Π° Ρ‚Π°Π·ΠΈ Π΅Π»Π΅ΠΊΡ‚Ρ€ΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°

In recent years, Fourier transform methods have emerged as one of the major methodologies for the evaluation of derivative contracts, largely due to the need to strike a balance between the extension of existing pricing models beyond the traditional Black-Scholes setting and a need to evaluate prices consistently with the market quotes.

Fourier Transform Methods in Finance is a practical and accessible guide to pricing financial instruments using Fourier transform. Written by an experienced team of practitioners and academics, it covers Fourier pricing methods; the dynamics of asset prices; non stationary market dynamics; arbitrage free pricing; generalized functions and the Fourier transform method.

Readers will learn how to:

  • compute the Hilbert transform of the pricing kernel under a Fast Fourier Transform (FFT) technique
  • characterise the price dynamics on a market in terms of the characteristic function, allowing for both diffusive processes and jumps
  • apply the concept of characteristic function to non-stationary processes, in particular in the presence of stochastic volatility and more generally time change techniques
  • perform a change of measure on the characteristic function in order to make the price process a martingale
  • recover a general representation of the pricing kernel of the economy in terms of Hilbert transform using the theory of generalised functions
  • apply the pricing formula to the most famous pricing models, with stochastic volatility and jumps.

Junior and senior practitioners alike will benefit from this quick reference guide to state of the art models and market calibration techniques. Not only will it enable them to write an algorithm for option pricing using the most advanced models, calibrate a pricing model on options data, and extract the implied probability distribution in market data, they will also understand the most advanced models and techniques and discover how these techniques have been adjusted for applications in finance.

ISBN 978-0-470-99400-9

ΠžΡ†Π΅Π½ΠΊΠΈ ΠΈ ΠΎΡ‚Π·ΠΈΠ²ΠΈ

5,0
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Π—Π° Π°Π²Ρ‚ΠΎΡ€Π°

UMBERTO CHERUBINI is Associate Professor of Financial Mathematics at the University of Bologna. He is fellow of the Financial Econometrics Research Center, FERC, University of Warwick and Ente Einaudi, Bank of Italy, and member of the Scientific Committee of the Risk Management Education program of the Italian Banking Association (ABI). He has published in international journals in economics and finance, and he is co-author of the books Copula Methods in Finance, John Wiley & Sons, 2004, and Structured Finance: The Object Oriented Approach, John Wiley & Sons, 2007.

GIOVANNI DELLA LUNGA is a quantitative analyst at Prometeia Consulting. Prior to this he was head of Market Risk Methodologies at Prometeia and acted as Principal at Polyhedron Computational Finance, a Florence-based consulting company in mathematical models for financial firms and software companies. He also lectures at the University of Bologna in computational finance for undergraduates and runs courses in computational finance at the Bank of Italy. Giovanni is a member of the scientific committee of Abiformazione, the educational branch of the Italian Banking Association and manages the charge of screen-based educational program. His research background covers physics, chemistry and finance, and he co-authored Structured Finance: The Object Oriented Approach, John Wiley & Sons, 2007.

SABRINA MULINACCI is a Professor of Mathematical Methods for Economics and Finance at the University of Bologna, Italy. Prior to this Sabrina was Associate Professor of Mathematical Methods for Economics and Actuarial Sciences at the Catholic University of Milan. She has a PhD in Mathematics from the University of Pisa and has published a number of research papers in international journals in probability and mathematical finance.

PIETRO ROSSI is a Senior Financial Analyst within the Market Risk Group at Prometeira Consulting, specializing in the development of analytical tractable approximations for exotic options. Prior to this, he worked as senior scientist at ENEA in the high performance computing division and was also Director of the Parallel Computing Group at the Center for Advanced Studies, Research and Development in Sardinia (CRS4), working on high performance computing and large scale computational problems for companies such as FIAT. He has a PhD in physics from NYU and his scientific activity has been mainly in theoretical physics and computer science.

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