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.
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 Ph.D. in physics from NYU and his scientific activity has been
mainly in theoretical physics and computer science.
Table of Contents
Preface.
1 Fourier Pricing Methods.
1.1 Introduction.
1.2 A general representation of option prices.
1.3 The dynamics of asset prices.
1.4 A generalized function approach to Fourier pricing.
1.5 Hilbert transform.
1.6 Pricing via FFT.
1.7 Related literature.
2 The Dynamics of Asset Prices.
2.1 Introduction.
2.2 Efficient markets and Lévy processes.
2.3 Construction of Lévy markets.
2.4 Properties of Lévy processes.
3 Non Stationary Market Dynamics.
3.1 Non-stationary processes.
3.2 Time changes.
3.3 Simulation of Lévy processes.
4 Arbitrage Free Pricing.
4.1 Introduction.
4.2 Equilibrium and arbitrage.
4.3 Arbitrage-free pricing.
4.4 Derivatives.
4.5 Lévy martingale Processes.
4.6 Lévy markets.
5 Generalized Functions.
5.1 Introduction.
5.2 The vector space of test functions.
5.3 Distributions.
5.4 The calculus of distributions.
5.5 Slow growth distributions.
5.6 Function convolution.
5.7 Distributional convolution.
5.8 The convolution of distributions in S.
6 The Fourier Transform.
6.1 Introduction.
6.2 The Fourier transformation of functions.
6.3 Fourier transform and option pricing.
6.4 Fourier transform for a generalized functions.
6.5 Exercises.
6.6 Fourier option pricing with generalized functions.
7 Fourier Transforms at Work.
7.1 Introduction.
7.2 The Black–Scholes model.
7.3 Finite activity models.
7.4 Infinite activity models.
7.5 Stochastic volatility.
7.6 FFT at work.
Appendices.
A Elements of probability.
A.1 Elements of measure theory.
A.2 Elements of stochastic processes theory.
B Elements of Complex Analysis.
B.1 Complex numbers.
B.2 Functions of complex variables.
C Complex Integration.
C.1 Definitions.
C.2 The Cauchy–Goursat theorem.
C.3 Consequences of Cauchy's theorem.
C.4 Principal value.
C.5 Laurent series.
C.6 Complex residue.
C.7 Residue theorem.
C.8 Jordan's Lemma.
D Vector Spaces and Function Spaces.
D.1 Definitions.
D.2 Inner product space.
D.3 Topological vector spaces.
D.4 Functionals and dual space.
E The Fast Fourier Transform (FFT).
E.1 Discrete Fourier transform.
E.2 Fast Fourier transform.
F The Fractional Fourier Transform.
F.1 Circular matrix.
F.2 Toepliz matrix.
F.3 Some numerical results.
G Affine models: The path integral approach.
G.1 The problem.
G.2 Solution of the Riccati equations.
Index.
256 pages, Hardcover
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