Derivatives Analytics with Python

Derivatives Analytics with Python PDF Author: Yves Hilpisch
Publisher: John Wiley & Sons
ISBN: 111903793X
Category : Business & Economics
Languages : en
Pages : 376

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Book Description
Supercharge options analytics and hedging using the power ofPython Derivatives Analytics with Python shows you how toimplement market-consistent valuation and hedging approaches usingadvanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. Thisunique guide offers detailed explanations of all theory, methods,and processes, giving you the background and tools necessary tovalue stock index options from a sound foundation. You'll find anduse self-contained Python scripts and modules and learn how toapply Python to advanced data and derivatives analytics as youbenefit from the 5,000+ lines of code that are provided to help youreproduce the results and graphics presented. Coverage includesmarket data analysis, risk-neutral valuation, Monte Carlosimulation, model calibration, valuation, and dynamic hedging, withmodels that exhibit stochastic volatility, jump components,stochastic short rates, and more. The companion website featuresall code and IPython Notebooks for immediate execution andautomation. Python is gaining ground in the derivatives analytics space,allowing institutions to quickly and efficiently deliver portfolio,trading, and risk management results. This book is the financeprofessional's guide to exploiting Python's capabilities forefficient and performing derivatives analytics. Reproduce major stylized facts of equity and options marketsyourself Apply Fourier transform techniques and advanced Monte Carlopricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamicallyhedge options Recent developments in the Python ecosystem enable analysts toimplement analytics tasks as performing as with C or C++, but usingonly about one-tenth of the code or even less. DerivativesAnalytics with Python — Data Analysis, Models, Simulation,Calibration and Hedging shows you what you need to know tosupercharge your derivatives and risk analytics efforts.

Derivatives Analytics with Python

Derivatives Analytics with Python PDF Author: Yves Hilpisch
Publisher: John Wiley & Sons
ISBN: 111903793X
Category : Business & Economics
Languages : en
Pages : 376

Get Book Here

Book Description
Supercharge options analytics and hedging using the power ofPython Derivatives Analytics with Python shows you how toimplement market-consistent valuation and hedging approaches usingadvanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. Thisunique guide offers detailed explanations of all theory, methods,and processes, giving you the background and tools necessary tovalue stock index options from a sound foundation. You'll find anduse self-contained Python scripts and modules and learn how toapply Python to advanced data and derivatives analytics as youbenefit from the 5,000+ lines of code that are provided to help youreproduce the results and graphics presented. Coverage includesmarket data analysis, risk-neutral valuation, Monte Carlosimulation, model calibration, valuation, and dynamic hedging, withmodels that exhibit stochastic volatility, jump components,stochastic short rates, and more. The companion website featuresall code and IPython Notebooks for immediate execution andautomation. Python is gaining ground in the derivatives analytics space,allowing institutions to quickly and efficiently deliver portfolio,trading, and risk management results. This book is the financeprofessional's guide to exploiting Python's capabilities forefficient and performing derivatives analytics. Reproduce major stylized facts of equity and options marketsyourself Apply Fourier transform techniques and advanced Monte Carlopricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamicallyhedge options Recent developments in the Python ecosystem enable analysts toimplement analytics tasks as performing as with C or C++, but usingonly about one-tenth of the code or even less. DerivativesAnalytics with Python — Data Analysis, Models, Simulation,Calibration and Hedging shows you what you need to know tosupercharge your derivatives and risk analytics efforts.

Large Deviations and Asymptotic Methods in Finance

Large Deviations and Asymptotic Methods in Finance PDF Author: Peter K. Friz
Publisher: Springer
ISBN: 3319116053
Category : Mathematics
Languages : en
Pages : 590

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Book Description
Topics covered in this volume (large deviations, differential geometry, asymptotic expansions, central limit theorems) give a full picture of the current advances in the application of asymptotic methods in mathematical finance, and thereby provide rigorous solutions to important mathematical and financial issues, such as implied volatility asymptotics, local volatility extrapolation, systemic risk and volatility estimation. This volume gathers together ground-breaking results in this field by some of its leading experts. Over the past decade, asymptotic methods have played an increasingly important role in the study of the behaviour of (financial) models. These methods provide a useful alternative to numerical methods in settings where the latter may lose accuracy (in extremes such as small and large strikes, and small maturities), and lead to a clearer understanding of the behaviour of models, and of the influence of parameters on this behaviour. Graduate students, researchers and practitioners will find this book very useful, and the diversity of topics will appeal to people from mathematical finance, probability theory and differential geometry.

Modelling and Simulation of Stochastic Volatility in Finance

Modelling and Simulation of Stochastic Volatility in Finance PDF Author: Christian Kahl
Publisher: Universal-Publishers
ISBN: 1581123833
Category : Business & Economics
Languages : en
Pages : 219

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Book Description
The famous Black-Scholes model was the starting point of a new financial industry and has been a very important pillar of all options trading since. One of its core assumptions is that the volatility of the underlying asset is constant. It was realised early that one has to specify a dynamic on the volatility itself to get closer to market behaviour. There are mainly two aspects making this fact apparent. Considering historical evolution of volatility by analysing time series data one observes erratic behaviour over time. Secondly, backing out implied volatility from daily traded plain vanilla options, the volatility changes with strike. The most common realisations of this phenomenon are the implied volatility smile or skew. The natural question arises how to extend the Black-Scholes model appropriately. Within this book the concept of stochastic volatility is analysed and discussed with special regard to the numerical problems occurring either in calibrating the model to the market implied volatility surface or in the numerical simulation of the two-dimensional system of stochastic differential equations required to price non-vanilla financial derivatives. We introduce a new stochastic volatility model, the so-called Hyp-Hyp model, and use Watanabe's calculus to find an analytical approximation to the model implied volatility. Further, the class of affine diffusion models, such as Heston, is analysed in view of using the characteristic function and Fourier inversion techniques to value European derivatives.

The Volatility Surface

The Volatility Surface PDF Author: Jim Gatheral
Publisher: John Wiley & Sons
ISBN: 1118046455
Category : Business & Economics
Languages : en
Pages : 204

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Book Description
Praise for The Volatility Surface "I'm thrilled by the appearance of Jim Gatheral's new book The Volatility Surface. The literature on stochastic volatility is vast, but difficult to penetrate and use. Gatheral's book, by contrast, is accessible and practical. It successfully charts a middle ground between specific examples and general models--achieving remarkable clarity without giving up sophistication, depth, or breadth." --Robert V. Kohn, Professor of Mathematics and Chair, Mathematical Finance Committee, Courant Institute of Mathematical Sciences, New York University "Concise yet comprehensive, equally attentive to both theory and phenomena, this book provides an unsurpassed account of the peculiarities of the implied volatility surface, its consequences for pricing and hedging, and the theories that struggle to explain it." --Emanuel Derman, author of My Life as a Quant "Jim Gatheral is the wiliest practitioner in the business. This very fine book is an outgrowth of the lecture notes prepared for one of the most popular classes at NYU's esteemed Courant Institute. The topics covered are at the forefront of research in mathematical finance and the author's treatment of them is simply the best available in this form." --Peter Carr, PhD, head of Quantitative Financial Research, Bloomberg LP Director of the Masters Program in Mathematical Finance, New York University "Jim Gatheral is an acknowledged master of advanced modeling for derivatives. In The Volatility Surface he reveals the secrets of dealing with the most important but most elusive of financial quantities, volatility." --Paul Wilmott, author and mathematician "As a teacher in the field of mathematical finance, I welcome Jim Gatheral's book as a significant development. Written by a Wall Street practitioner with extensive market and teaching experience, The Volatility Surface gives students access to a level of knowledge on derivatives which was not previously available. I strongly recommend it." --Marco Avellaneda, Director, Division of Mathematical Finance Courant Institute, New York University "Jim Gatheral could not have written a better book." --Bruno Dupire, winner of the 2006 Wilmott Cutting Edge Research Award Quantitative Research, Bloomberg LP

Options - 45 Years Since The Publication Of The Black-scholes-merton Model: The Gershon Fintech Center Conference

Options - 45 Years Since The Publication Of The Black-scholes-merton Model: The Gershon Fintech Center Conference PDF Author: David Gershon
Publisher: World Scientific
ISBN: 9811259151
Category : Business & Economics
Languages : en
Pages : 554

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Book Description
This book contains contributions by the best-known and consequential researchers who, over several decades, shaped the field of financial engineering. It presents a comprehensive and unique perspective on the historical development and the current state of derivatives research. The book covers classical and modern approaches to option pricing, realized and implied volatilities, classical and rough stochastic processes, and contingent claims analysis in corporate finance. The book is invaluable for students, academic researchers, and practitioners working with financial derivatives, market regulation, trading, risk management, and corporate decision-making.

Simulation-based Econometric Methods

Simulation-based Econometric Methods PDF Author: Christian Gouriéroux
Publisher: OUP Oxford
ISBN: 019152509X
Category : Business & Economics
Languages : en
Pages : 190

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Book Description
This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.

Lévy Processes

Lévy Processes PDF Author: Ole E Barndorff-Nielsen
Publisher: Springer Science & Business Media
ISBN: 1461201977
Category : Mathematics
Languages : en
Pages : 414

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Book Description
A Lévy process is a continuous-time analogue of a random walk, and as such, is at the cradle of modern theories of stochastic processes. Martingales, Markov processes, and diffusions are extensions and generalizations of these processes. In the past, representatives of the Lévy class were considered most useful for applications to either Brownian motion or the Poisson process. Nowadays the need for modeling jumps, bursts, extremes and other irregular behavior of phenomena in nature and society has led to a renaissance of the theory of general Lévy processes. Researchers and practitioners in fields as diverse as physics, meteorology, statistics, insurance, and finance have rediscovered the simplicity of Lévy processes and their enormous flexibility in modeling tails, dependence and path behavior. This volume, with an excellent introductory preface, describes the state-of-the-art of this rapidly evolving subject with special emphasis on the non-Brownian world. Leading experts present surveys of recent developments, or focus on some most promising applications. Despite its special character, every topic is aimed at the non- specialist, keen on learning about the new exciting face of a rather aged class of processes. An extensive bibliography at the end of each article makes this an invaluable comprehensive reference text. For the researcher and graduate student, every article contains open problems and points out directions for futurearch. The accessible nature of the work makes this an ideal introductory text for graduate seminars in applied probability, stochastic processes, physics, finance, and telecommunications, and a unique guide to the world of Lévy processes.

The Heston Model and its Extensions in Matlab and C#

The Heston Model and its Extensions in Matlab and C# PDF Author: Fabrice D. Rouah
Publisher: John Wiley & Sons
ISBN: 1118695178
Category : Business & Economics
Languages : en
Pages : 437

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Book Description
Tap into the power of the most popular stochastic volatility model for pricing equity derivatives Since its introduction in 1993, the Heston model has become a popular model for pricing equity derivatives, and the most popular stochastic volatility model in financial engineering. This vital resource provides a thorough derivation of the original model, and includes the most important extensions and refinements that have allowed the model to produce option prices that are more accurate and volatility surfaces that better reflect market conditions. The book's material is drawn from research papers and many of the models covered and the computer codes are unavailable from other sources. The book is light on theory and instead highlights the implementation of the models. All of the models found here have been coded in Matlab and C#. This reliable resource offers an understanding of how the original model was derived from Ricatti equations, and shows how to implement implied and local volatility, Fourier methods applied to the model, numerical integration schemes, parameter estimation, simulation schemes, American options, the Heston model with time-dependent parameters, finite difference methods for the Heston PDE, the Greeks, and the double Heston model. A groundbreaking book dedicated to the exploration of the Heston model—a popular model for pricing equity derivatives Includes a companion website, which explores the Heston model and its extensions all coded in Matlab and C# Written by Fabrice Douglas Rouah a quantitative analyst who specializes in financial modeling for derivatives for pricing and risk management Engaging and informative, this is the first book to deal exclusively with the Heston Model and includes code in Matlab and C# for pricing under the model, as well as code for parameter estimation, simulation, finite difference methods, American options, and more.

Recent Advances in Applied Probability

Recent Advances in Applied Probability PDF Author: Ricardo Baeza-Yates
Publisher: Springer Science & Business Media
ISBN: 0387233946
Category : Mathematics
Languages : en
Pages : 497

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Book Description
Applied probability is a broad research area that is of interest to scientists in diverse disciplines in science and technology, including: anthropology, biology, communication theory, economics, epidemiology, finance, geography, linguistics, medicine, meteorology, operations research, psychology, quality control, sociology, and statistics. Recent Advances in Applied Probability is a collection of survey articles that bring together the work of leading researchers in applied probability to present current research advances in this important area. This volume will be of interest to graduate students and researchers whose research is closely connected to probability modelling and their applications. It is suitable for one semester graduate level research seminar in applied probability.

Financial Modelling with Jump Processes

Financial Modelling with Jump Processes PDF Author: Peter Tankov
Publisher: CRC Press
ISBN: 1135437947
Category : Business & Economics
Languages : en
Pages : 552

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Book Description
WINNER of a Riskbook.com Best of 2004 Book Award! During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematic