A Primer for Financial Engineering

A Primer for Financial Engineering

Author: Ali N. Akansu

Publisher: Academic Press

Published: 2015-03-25

Total Pages: 156

ISBN-13: 0128017503

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This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial markets. The book builds from the fundamentals, with the help of simple examples, clearly explaining the concepts to the level needed by an engineer, while showing their practical significance. Topics covered include an in depth examination of market microstructure and trading, a detailed explanation of High Frequency Trading and the 2010 Flash Crash, risk analysis and management, popular trading strategies and their characteristics, and High Performance DSP and Financial Computing. The book has many examples to explain financial concepts, and the presentation is enhanced with the visual representation of relevant market data. It provides relevant MATLAB codes for readers to further their study. Please visit the companion website on http://booksite.elsevier.com/9780128015612/ Provides engineering perspective to financial problems In depth coverage of market microstructure Detailed explanation of High Frequency Trading and 2010 Flash Crash Explores risk analysis and management Covers high performance DSP & financial computing


Mathematics and Tools for Financial Engineering

Mathematics and Tools for Financial Engineering

Author: Petros A. Ioannou

Publisher: SIAM

Published: 2021-09-07

Total Pages: 294

ISBN-13: 1611976766

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This book presents an overview of fundamental concepts in mathematics and how they are applied to basic financial engineering problems, with the goal of teaching students to use mathematics and engineering tools to understand and solve financial problems. Part I covers mathematical preliminaries (set theory, linear algebra, sequences and series, real functions and analysis, numerical approximations and computations, basic optimization theory, and stochastic processes), and Part II addresses financial topics ranging from low- to high-risk investments (interest rates and value of money, bonds, dynamic asset modeling, portfolio theory and optimization, option pricing, and the concept of hedging). Based on lectures for a master’s program in financial engineering given by the author over 12 years at the University of Southern California, Mathematics and Tools for Financial Engineering contains numerous examples and problems, establishes a strong general mathematics background and engineering modeling techniques in a pedagogical fashion, and covers numerical techniques with applications to solving financial problems using different software tools. This textbook is intended for graduate and advanced undergraduate students in finance or financial engineering and is useful to readers with no prior knowledge in finance who want to understand some basic mathematical tools and theories associated with financial engineering. It is also appropriate as an overview of many mathematical concepts and engineering tools relevant to courses on numerical analysis, modeling and data science, numerical optimization, and approximation theory.


Optimal Statistical Inference in Financial Engineering

Optimal Statistical Inference in Financial Engineering

Author: Masanobu Taniguchi

Publisher: CRC Press

Published: 2007-11-26

Total Pages: 379

ISBN-13: 1420011030

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Until now, few systematic studies of optimal statistical inference for stochastic processes had existed in the financial engineering literature, even though this idea is fundamental to the field. Balancing statistical theory with data analysis, Optimal Statistical Inference in Financial Engineering examines how stochastic models can effectively des


Computational Finance

Computational Finance

Author: Argimiro Arratia

Publisher: Springer Science & Business Media

Published: 2014-05-08

Total Pages: 305

ISBN-13: 9462390703

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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.


Financial Engineering

Financial Engineering

Author: Tanya S. Beder

Publisher: John Wiley & Sons

Published: 2011-06-07

Total Pages: 616

ISBN-13: 0470455810

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FINANCIAL ENGINEERING Financial engineering is poised for a great shift in the years ahead. Everyone from investors and borrowers to regulators and legislators will need to determine what works, what doesn't, and where to go from here. Financial Engineering—part of the Robert W. Kolb Series in Finance—has been designed to help you do just this. Comprised of contributed chapters by distinguished experts from industry and academia, this reliable resource will help you focus on established activities in the field, developing trends and changes, as well as areas of opportunity. Divided into five comprehensive parts, Financial Engineering begins with an informative overview of the discipline, chronicling its complete history and profiling potential career paths. From here, Part II quickly moves on to discuss the evolution of financial engineering in major markets—fixed income, foreign exchange, equities, commodities and credit—and offers important commentary on what has worked and what will change. Part III then examines a number of recent innovative applications of financial engineering that have made news over the past decade—such as the advent of securitized and structured products and highly quantitative trading strategies for both equities and fixed income. Thoughts on how risk management might be retooled to reflect what has been learned as a result of the recent financial crisis are also included. Part IV of the book is devoted entirely to case studies that present valuable lessons for active practitioners and academics. Several of the cases explore the risk that has instigated losses across multiple markets, including the global credit crisis. You'll gain in-depth insights from cases such as Countrywide, Société Générale, Barings, Long-Term Capital Management, the Florida Local Government Investment Pool, AIG, Merrill Lynch, and many more. The demand for specific and enterprise risk managers who can think outside the box will be substantial during this decade. Much of Part V presents new ways to be successful in an era that demands innovation on both sides of the balance sheet. Chapters that touch upon this essential topic include Musings About Hedging; Operational Risk; and The No-Arbitrage Condition in Financial Engineering: Its Use and Mis-Use. This book is complemented by a companion website that includes details from the editors' survey of financial engineering programs around the globe, along with a glossary of key terms from the book. This practical guide puts financial engineering in perspective, and will give you a better idea of how it can be effectively utilized in real- world situations.


Monte Carlo Methods in Financial Engineering

Monte Carlo Methods in Financial Engineering

Author: Paul Glasserman

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 603

ISBN-13: 0387216170

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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


Financial Engineering and Computation

Financial Engineering and Computation

Author: Yuh-Dauh Lyuu

Publisher: Cambridge University Press

Published: 2002

Total Pages: 654

ISBN-13: 9780521781718

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A comprehensive text and reference, first published in 2002, on the theory of financial engineering with numerous algorithms for pricing, risk management, and portfolio management.