Author: Ali Hirsa
Publisher: CRC Press
ISBN: 1466576049
Category : Business & Economics
Languages : en
Pages : 440
Book Description
Helping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical methods. It addresses key computational methods in finance, including transform techniques, the finite difference method, and Monte Carlo simulation. Developed from his courses at Columbia University and the Courant Institute of New York University, the author also covers model calibration and optimization and describes techniques, such as Kalman and particle filters, for parameter estimation.
Computational Methods in Finance
Author: Ali Hirsa
Publisher: CRC Press
ISBN: 1466576049
Category : Business & Economics
Languages : en
Pages : 440
Book Description
Helping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical methods. It addresses key computational methods in finance, including transform techniques, the finite difference method, and Monte Carlo simulation. Developed from his courses at Columbia University and the Courant Institute of New York University, the author also covers model calibration and optimization and describes techniques, such as Kalman and particle filters, for parameter estimation.
Publisher: CRC Press
ISBN: 1466576049
Category : Business & Economics
Languages : en
Pages : 440
Book Description
Helping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical methods. It addresses key computational methods in finance, including transform techniques, the finite difference method, and Monte Carlo simulation. Developed from his courses at Columbia University and the Courant Institute of New York University, the author also covers model calibration and optimization and describes techniques, such as Kalman and particle filters, for parameter estimation.
Tools for Computational Finance
Author: Rüdiger U. Seydel
Publisher: Springer Science & Business Media
ISBN: 3662225514
Category : Mathematics
Languages : en
Pages : 256
Book Description
Tools for Computational Finance offers a clear explanation of computational issues arising in financial mathematics. The new third edition is thoroughly revised and significantly extended, including an extensive new section on analytic methods, focused mainly on interpolation approach and quadratic approximation. Other new material is devoted to risk-neutrality, early-exercise curves, multidimensional Black-Scholes models, the integral representation of options and the derivation of the Black-Scholes equation. New figures, more exercises, and expanded background material make this guide a real must-to-have for everyone working in the world of financial engineering.
Publisher: Springer Science & Business Media
ISBN: 3662225514
Category : Mathematics
Languages : en
Pages : 256
Book Description
Tools for Computational Finance offers a clear explanation of computational issues arising in financial mathematics. The new third edition is thoroughly revised and significantly extended, including an extensive new section on analytic methods, focused mainly on interpolation approach and quadratic approximation. Other new material is devoted to risk-neutrality, early-exercise curves, multidimensional Black-Scholes models, the integral representation of options and the derivation of the Black-Scholes equation. New figures, more exercises, and expanded background material make this guide a real must-to-have for everyone working in the world of financial engineering.
Financial Modelling in Python
Author: Shayne Fletcher
Publisher: John Wiley & Sons
ISBN: 0470747897
Category : Business & Economics
Languages : en
Pages : 244
Book Description
"Fletcher and Gardner have created a comprehensive resource that will be of interest not only to those working in the field of finance, but also to those using numerical methods in other fields such as engineering, physics, and actuarial mathematics. By showing how to combine the high-level elegance, accessibility, and flexibility of Python, with the low-level computational efficiency of C++, in the context of interesting financial modeling problems, they have provided an implementation template which will be useful to others seeking to jointly optimize the use of computational and human resources. They document all the necessary technical details required in order to make external numerical libraries available from within Python, and they contribute a useful library of their own, which will significantly reduce the start-up costs involved in building financial models. This book is a must read for all those with a need to apply numerical methods in the valuation of financial claims." –David Louton, Professor of Finance, Bryant University This book is directed at both industry practitioners and students interested in designing a pricing and risk management framework for financial derivatives using the Python programming language. It is a practical book complete with working, tested code that guides the reader through the process of building a flexible, extensible pricing framework in Python. The pricing frameworks' loosely coupled fundamental components have been designed to facilitate the quick development of new models. Concrete applications to real-world pricing problems are also provided. Topics are introduced gradually, each building on the last. They include basic mathematical algorithms, common algorithms from numerical analysis, trade, market and event data model representations, lattice and simulation based pricing, and model development. The mathematics presented is kept simple and to the point. The book also provides a host of information on practical technical topics such as C++/Python hybrid development (embedding and extending) and techniques for integrating Python based programs with Microsoft Excel.
Publisher: John Wiley & Sons
ISBN: 0470747897
Category : Business & Economics
Languages : en
Pages : 244
Book Description
"Fletcher and Gardner have created a comprehensive resource that will be of interest not only to those working in the field of finance, but also to those using numerical methods in other fields such as engineering, physics, and actuarial mathematics. By showing how to combine the high-level elegance, accessibility, and flexibility of Python, with the low-level computational efficiency of C++, in the context of interesting financial modeling problems, they have provided an implementation template which will be useful to others seeking to jointly optimize the use of computational and human resources. They document all the necessary technical details required in order to make external numerical libraries available from within Python, and they contribute a useful library of their own, which will significantly reduce the start-up costs involved in building financial models. This book is a must read for all those with a need to apply numerical methods in the valuation of financial claims." –David Louton, Professor of Finance, Bryant University This book is directed at both industry practitioners and students interested in designing a pricing and risk management framework for financial derivatives using the Python programming language. It is a practical book complete with working, tested code that guides the reader through the process of building a flexible, extensible pricing framework in Python. The pricing frameworks' loosely coupled fundamental components have been designed to facilitate the quick development of new models. Concrete applications to real-world pricing problems are also provided. Topics are introduced gradually, each building on the last. They include basic mathematical algorithms, common algorithms from numerical analysis, trade, market and event data model representations, lattice and simulation based pricing, and model development. The mathematics presented is kept simple and to the point. The book also provides a host of information on practical technical topics such as C++/Python hybrid development (embedding and extending) and techniques for integrating Python based programs with Microsoft Excel.
Mathematical Modeling And Computation In Finance: With Exercises And Python And Matlab Computer Codes
Author: Cornelis W Oosterlee
Publisher: World Scientific
ISBN: 1786347962
Category : Business & Economics
Languages : en
Pages : 1310
Book Description
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.
Publisher: World Scientific
ISBN: 1786347962
Category : Business & Economics
Languages : en
Pages : 1310
Book Description
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.
Financial Modeling
Author: Simon Benninga
Publisher: MIT Press
ISBN: 9780262024822
Category : Business & Economics
Languages : en
Pages : 648
Book Description
Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. "Financial Modeling" bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial problems with spreadsheets. The CD-ROM contains Excel* worksheets and solutions to end-of-chapter exercises. 634 illustrations.
Publisher: MIT Press
ISBN: 9780262024822
Category : Business & Economics
Languages : en
Pages : 648
Book Description
Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. "Financial Modeling" bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial problems with spreadsheets. The CD-ROM contains Excel* worksheets and solutions to end-of-chapter exercises. 634 illustrations.
Financial Modeling
Author: Simon Benninga
Publisher: MIT Press (MA)
ISBN: 9780262026284
Category : Business & Economics
Languages : en
Pages : 1132
Book Description
Too often, finance courses stop short of making a connection between textbook financeand the problems of real-world business. Financial Modeling bridges this gapbetween theory and practice by providing a nuts-and-bolts guide to solving common financial modelswith spreadsheets. Simon Benninga takes the reader step by step through each model, showing how itcan be solved using Microsoft Excel. The long-awaited third edition of this standard text maintainsthe "cookbook" features and Excel dependence that have made the first and second editionsso popular. It also offers significant new material, with new chapters covering such topics as bankvaluation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and theirapplications to option pricing, and using array functions and formulas. Other chapters, includingthose on basic financial calculations, portfolio models, calculating the variance-covariance matrix,and generating random numbers, have been revised, with many offering substantially new and improvedmaterial. Other areas covered include financial statement modeling, leasing, standard portfolioproblems, value at risk (VaR), real options, duration and immunization, and term structure modeling.Technical chapters treat such topics as data tables, matrices, the Gauss-Seidel method, and tips forusing Excel. The last section of the text covers the Visual Basic for Applications (VBA) techniquesneeded for the book. The accompanying CD contains Excel worksheets and solutions to end-of-chapterexercises.
Publisher: MIT Press (MA)
ISBN: 9780262026284
Category : Business & Economics
Languages : en
Pages : 1132
Book Description
Too often, finance courses stop short of making a connection between textbook financeand the problems of real-world business. Financial Modeling bridges this gapbetween theory and practice by providing a nuts-and-bolts guide to solving common financial modelswith spreadsheets. Simon Benninga takes the reader step by step through each model, showing how itcan be solved using Microsoft Excel. The long-awaited third edition of this standard text maintainsthe "cookbook" features and Excel dependence that have made the first and second editionsso popular. It also offers significant new material, with new chapters covering such topics as bankvaluation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and theirapplications to option pricing, and using array functions and formulas. Other chapters, includingthose on basic financial calculations, portfolio models, calculating the variance-covariance matrix,and generating random numbers, have been revised, with many offering substantially new and improvedmaterial. Other areas covered include financial statement modeling, leasing, standard portfolioproblems, value at risk (VaR), real options, duration and immunization, and term structure modeling.Technical chapters treat such topics as data tables, matrices, the Gauss-Seidel method, and tips forusing Excel. The last section of the text covers the Visual Basic for Applications (VBA) techniquesneeded for the book. The accompanying CD contains Excel worksheets and solutions to end-of-chapterexercises.
Computational Finance
Author: Argimiro Arratia
Publisher: Springer Science & Business Media
ISBN: 9462390703
Category : Computers
Languages : en
Pages : 305
Book Description
The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.
Publisher: Springer Science & Business Media
ISBN: 9462390703
Category : Computers
Languages : en
Pages : 305
Book Description
The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.
Monte Carlo Methods in Financial Engineering
Author: Paul Glasserman
Publisher: Springer Science & Business Media
ISBN: 0387216170
Category : Mathematics
Languages : en
Pages : 603
Book Description
From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
Publisher: Springer Science & Business Media
ISBN: 0387216170
Category : Mathematics
Languages : en
Pages : 603
Book Description
From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
Artificial Intelligence, Learning and Computation in Economics and Finance
Author: Ragupathy Venkatachalam
Publisher: Springer Nature
ISBN: 3031152948
Category : Science
Languages : en
Pages : 331
Book Description
This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded. Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools. The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
Publisher: Springer Nature
ISBN: 3031152948
Category : Science
Languages : en
Pages : 331
Book Description
This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded. Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools. The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
Professional Financial Computing Using Excel and VBA
Author: Donny C. F. Lai
Publisher: John Wiley & Sons
ISBN: 1118179080
Category : Business & Economics
Languages : en
Pages : 372
Book Description
"Professional Financial Computing Using Excel and VBA is an admirable exposition that bridges the theoretical underpinnings of financial engineering and its application which usually appears as a "black-box" software application. The book opens the black-box and reveals the architecture of risk-modeling and financial engineering based on industry-standard stochastic models by utilizing Excel and VBA functionality to create a robust and practical modeling tool-kit. Financial engineering professionals who purchase this book will have a jumpstart advantage for their customized financial engineering and modeling needs." Dr. Cameron Wicentowich Vice President, Treasury Analytics Canadian Imperial Bank of Commerce (CIBC) "Spreadsheet modeling for finance has become a standard course in the curriculum of many Quantitative Finance programs since the Excel-based Visual Basic programming is now widely used in constructing optimal portfolios, pricing structured products and managing risks. Professional Financial Computing Using Excel and VBA is written by a unique team of finance, physics and computer academics and practitioners. It is a good reference for those who are studying for a Masters degree in Financial Engineering and Risk Management. It can also be useful for financial engineers to jump-start a project on designing structured products, modeling interest term structure or credit risks." Dr. Jin Zhang Director of Master of Finance Program and Associate Professor The University of Hong Kong "Excel has been one of the most powerful tools for financial planning and computing over the last few years. Most users utilize a fraction of its capabilities. One of the reasons is the limited availability of books that cover the advanced features of Excel for Finance. Professional Financial Computing Using Excel and VBA goes the extra mile and deals with the Excel tools many professionals call for. This book is a must for professionals or students dealing with financial engineering, financial risk management, computational finance or mathematical finance. I loved the way the authors covered the material using real life, hands-on examples." Dr. Isaac Gottlieb Temple University Author, Next Generation Excel: Modeling in Excel for Analysts and MBAs
Publisher: John Wiley & Sons
ISBN: 1118179080
Category : Business & Economics
Languages : en
Pages : 372
Book Description
"Professional Financial Computing Using Excel and VBA is an admirable exposition that bridges the theoretical underpinnings of financial engineering and its application which usually appears as a "black-box" software application. The book opens the black-box and reveals the architecture of risk-modeling and financial engineering based on industry-standard stochastic models by utilizing Excel and VBA functionality to create a robust and practical modeling tool-kit. Financial engineering professionals who purchase this book will have a jumpstart advantage for their customized financial engineering and modeling needs." Dr. Cameron Wicentowich Vice President, Treasury Analytics Canadian Imperial Bank of Commerce (CIBC) "Spreadsheet modeling for finance has become a standard course in the curriculum of many Quantitative Finance programs since the Excel-based Visual Basic programming is now widely used in constructing optimal portfolios, pricing structured products and managing risks. Professional Financial Computing Using Excel and VBA is written by a unique team of finance, physics and computer academics and practitioners. It is a good reference for those who are studying for a Masters degree in Financial Engineering and Risk Management. It can also be useful for financial engineers to jump-start a project on designing structured products, modeling interest term structure or credit risks." Dr. Jin Zhang Director of Master of Finance Program and Associate Professor The University of Hong Kong "Excel has been one of the most powerful tools for financial planning and computing over the last few years. Most users utilize a fraction of its capabilities. One of the reasons is the limited availability of books that cover the advanced features of Excel for Finance. Professional Financial Computing Using Excel and VBA goes the extra mile and deals with the Excel tools many professionals call for. This book is a must for professionals or students dealing with financial engineering, financial risk management, computational finance or mathematical finance. I loved the way the authors covered the material using real life, hands-on examples." Dr. Isaac Gottlieb Temple University Author, Next Generation Excel: Modeling in Excel for Analysts and MBAs