In My Life as a Quant, Emanuel Derman relives his exciting journey as one of the first high-energy particle physicists to migrate to Wall Street. Page by page, Derman details his adventures in this field―analyzing the incompatible personas of traders and quants, and discussing the dissimilar nature of knowledge in physics and finance. Throughout this tale, he also reflects on the appropriate way to apply the refined methods of physics to the hurly-burly world of markets.

The Complete Guide to Capital Markets for Quantitative Professionals is a comprehensive resource for readers with a background in science and technology who want to transfer their skills to the financial industry.It is written in a clear, conversational style and requires no prior knowledge of either finance or financial analytics. The book begins by discussing the operation of the financial industry and the business models of different types of Wall Street firms, as well as the job roles those with technical backgrounds can fill in those firms. Then it describes the mechanics of how these firms make money trading the main financial markets (focusing on fixed income, but also covering equity, options and derivatives markets), and highlights the ways in which quantitative professionals can participate in this money-making process. The second half focuses on the main areas of Wall Street technology and explains how financial models and systems are created, implemented, and used in real life. This is one of the few books that offers a review of relevant literature and Internet resources.

Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key Features Design, train, and evaluate machine learning algorithms that underpin automated trading strategies Create a research and strategy development process to apply predictive modeling to trading decisions Leverage NLP and deep learning to extract tradeable signals from market and alternative data Book DescriptionThe explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models.This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research.This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples.By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learn Leverage market, fundamental, and alternative text and image data Research and evaluate alpha factors using statistics, Alphalens, and SHAP values Implement machine learning techniques to solve investment and trading problems Backtest and evaluate trading strategies based on machine learning using Zipline and Backtrader Optimize portfolio risk and performance analysis using pandas, NumPy, and pyfolio Create a pairs trading strategy based on cointegration for US equities and ETFs Train a gradient boosting model to predict intraday returns using AlgoSeek s high-quality trades and quotes data Who this book is forIf you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required. Table of Contents Machine Learning for Trading - From Idea to Execution Market and Fundamental Data - Sources and Techniques Alternative Data for Finance - Categories and Use Cases Financial Feature Engineering - How to Research Alpha Factors Portfolio Optimization and Performance Evaluation The Machine Learning Process Linear Models - From Risk Factors to Return Forecasts The ML4T Workflow - From Model to Strategy Backtesting(N.B. Please use the Look Inside option to see further chapters)

2nd Edition of Quantitative Finance and Risk Management: A Physicist's ApproachWritten by a physicist with over 15 years of experience as a quant on Wall Street, this book treats a wide variety of topics. Presenting the theory and practice of quantitative finance and risk, it delves into the "how to" and "what it's like" aspects not covered in textbooks or research papers. Both standard and new results are presented. A "Technical Index" indicates the mathematical level -- from zero to PhD -- for each chapter. The finance in each chapter is self-contained. Real-life comments on "life as a quant" are included.An errata and Additions (3rd Reprint, 2008) to the book is available.

The worlds of Wall Street and The City have always held a certain allure, but in recent years have left an indelible mark on the wider public consciousness and there has been a need to become more financially literate. The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types, whether for general interest or because of the enormous monetary rewards on offer.An Introduction to Quantitative Finance concerns financial derivatives a derivative being a contract between two entities whose value derives from the price of an underlying financial asset and the probabilistic tools that were developed to analyse them. The theory in the text is motivated by a desire to provide a suitably rigorous yet accessible foundation to tackle problems the author encountered whilst trading derivatives on Wall Street. The book combines an unusual blend of real world derivatives trading experience and rigorous academic background.Probability provides the key tools for analysing and valuing derivatives. The price of a derivative is closely linked to the expected value of its pay out, and suitably scaled derivative prices are martingales, fundamentally important objects in probability theory.The prerequisite for mastering the material is an introductory undergraduate course in probability. The book is otherwise self contained and in particular requires no additional preparation or exposure to finance. It is suitable for a one semester course, quickly exposing readers to powerful theory and substantive problems. The book may also appeal to students who have enjoyed probability and have a desire to see how it can be applied. Signposts are given throughout the text to more advanced topics and to different approaches for those looking to take the subject further.

NEW YORK TIMES BESTSELLERShortlisted for the Financial Times/McKinsey Business Book of the Year AwardThe unbelievable story of a secretive mathematician who pioneered the era of the algorithm–and made $23 billion doing it.The greatest money maker in modern financial history, no other investor–Warren Buffett, Peter Lynch, Ray Dalio, Steve Cohen, or George Soros–has touched Jim Simons’ record. Since 1988, Renaissance’s signature Medallion fund has generated average annual returns of 66 percent. The firm has earned profits of more than $100 billion, and upon his passing, Simons left a legacy of investors who use his mathematical, computer-oriented approach to trading and building wealth.Drawing on unprecedented access to Simons and dozens of current and former employees, Zuckerman, a veteran Wall Street Journal investigative reporter, tells the gripping story of how a world-class mathematician and former code breaker mastered the market. Simons pioneered a data-driven, algorithmic approach that’s swept the world.As Renaissance became a market force, its executives began influencing the world beyond finance. Simons became a major figure in scientific research, education, and liberal politics. Senior executive Robert Mercer is more responsible than anyone else for the Trump presidency, placing Steve Bannon in the campaign and funding Trump’s victorious 2016 effort. Mercer also impacted the campaign behind Brexit.The Man Who Solved the Market is a portrait of a modern-day Midas who remade markets in his own image, but failed to anticipate how his success would impact his firm and his country. It’s also a story of what Simons’s revolution will mean for the rest of us long after his death in 2024.

This book is about trading, the people who trade securities and contracts, the marketplaces where they trade, and the rules that govern it. Readers will learn about investors, brokers, dealers, arbitrageurs, retail traders, day traders, rogue traders, and gamblers; exchanges, boards of trade, dealer networks, ECNs (electronic communications networks), crossing markets, and pink sheets. Also covered in this text are single price auctions, open outcry auctions, and brokered markets limit orders, market orders, and stop orders. Finally, the author covers the areas of program trades, block trades, and short trades, price priority, time precedence, public order precedence, and display precedence, insider trading, scalping, and bluffing, and investing, speculating, and gambling.

With the immediacy of today’s NASDAQ close and the timeless power of a Greek tragedy, The Quants is at once a masterpiece of explanatory journalism, a gripping tale of ambition and hubris, and an ominous warning about Wall Street’s future.In March of 2006, four of the world’s richest men sipped champagne in an opulent New York hotel. They were preparing to compete in a poker tournament with million-dollar stakes, but those numbers meant nothing to them. They were accustomed to risking billions.On that night, these four men and their cohorts were the new kings of Wall Street. Muller, Griffin, Asness, and Weinstein were among the best and brightest of a new breed, the quants. Over the prior twenty years, this species of math whiz--technocrats who make billions not with gut calls or fundamental analysis but with formulas and high-speed computers--had usurped the testosterone-fueled, kill-or-be-killed risk-takers who’d long been the alpha males the world’s largest casino. The quants helped create a digitized money-trading machine that could shift billions around the globe with the click of a mouse. Few realized, though, that in creating this unprecedented machine, men like Muller, Griffin, Asness and Weinstein had sowed the seeds for history’s greatest financial disaster.Drawing on unprecedented access to these four number-crunching titans, The Quants tells the inside story of what they thought and felt in the days and weeks when they helplessly watched much of their net worth vaporize--and wondered just how their mind-bending formulas and genius-level IQ’s had led them so wrong, so fast.

Algorithmic trading and Direct Market Access (DMA) are important tools helping both buy and sell-side traders to achieve best execution (Note: the focus is on institutional sized orders, not those of individuals/retail traders).This book starts from the ground up to provide detailed explanations of both these techniques: An introduction to the different types of execution is followed by a review of market microstructure theory. Throughout the book examples from empirical studies bridge the gap between the theory and practice of trading. Orders are the fundamental building blocks for any strategy. Market, limit, stop, hidden, iceberg, peg, routed and immediate-or-cancel orders are all described with illustrated examples. Trading algorithms are explained and compared using charts to show potential trading patterns. TWAP, VWAP, Percent of Volume, Minimal Impact, Implementation Shortfall, Adaptive Shortfall, Market On Close and Pairs trading algorithms are all covered, together with common variations. Transaction costs can have a significant effect on investment returns. An in-depth example shows how these may be broken down into constituents such as market impact, timing risk, spread and opportunity cost and other fees. Coverage includes all the major asset classes, from equities to fixed income, foreign exchange and derivatives. Detailed overviews for each of the world's major markets are provided in the appendices. Order placement and execution tactics are covered in more detail, as well as potential enhancements (such as short-term forecasts), for those interested in the specifics of implementing these strategies. Cutting edge applications such as portfolio and multi-asset trading are also considered, as are handling news and data mining/artificial intelligence.There is also a website for this book at www.algo-dma.com

This comprehensive guide offers traders, quants, and students the tools and techniques for using advanced models for pricing options. The accompanying website includes data files, such as options prices, stock prices, or index prices, as well as all of the codes needed to use the option and volatility models described in the book. Praise for Option Pricing Models & Volatility Using Excel-VBA"Excel is already a great pedagogical tool for teaching option valuation and risk management. But the VBA routines in this book elevate Excel to an industrial-strength financial engineering toolbox. I have no doubt that it will become hugely successful as a reference for option traders and risk managers."―Peter Christoffersen, Associate Professor of Finance, Desautels Faculty of Management, McGill University"This book is filled with methodology and techniques on how to implement option pricing and volatility models in VBA. The book takes an in-depth look into how to implement the Heston and Heston and Nandi models and includes an entire chapter on parameter estimation, but this is just the tip of the iceberg. Everyone interested in derivatives should have this book in their personal library."―Espen Gaarder Haug, option trader, philosopher, and author of Derivatives Models on Models"I am impressed. This is an important book because it is the first book to cover the modern generation of option models, including stochastic volatility and GARCH."―Steven L. Heston, Assistant Professor of Finance, R.H. Smith School of Business, University of Maryland

Praise for How I Became a Quant"Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching!"--Ira Kawaller, Kawaller & Co. and the Kawaller Fund"A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions."--David A. Krell, President and CEO, International Securities Exchange"How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis."--Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management"Quants"--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk.How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution.

For courses in business, economics, and financial engineering and mathematics.The definitive guide to derivatives markets, updated with contemporary examples and discussions Known as “the bible” to business and economics professionals and a consistent best-seller, Options, Futures, and Other Derivatives gives readers a modern look at derivatives markets. By incorporating the industry’s hottest topics, such as the securitization and credit crisis, author John C. Hull helps bridge the gap between theory and practice. The 10th Edition covers all of the latest regulations and trends, including the Black-Scholes-Merton formulas, overnight indexed swaps, and the valuation of commodity derivatives.

"This new edition of Active Portfolio Management continues the standard of excellence established in the first edition, with new and clear insights to help investment professionals."-William E. Jacques, Partner and Chief Investment Officer, Martingale Asset Management."Active Portfolio Management offers investors an opportunity to better understand the balance between manager skill and portfolio risk. Both fundamental and quantitative investment managers will benefit from studying this updated edition by Grinold and Kahn."-Scott Stewart, Portfolio Manager, Fidelity Select Equity ® DisciplineCo-Manager, Fidelity Freedom ® Funds."This Second edition will not remain on the shelf, but will be continually referenced by both novice and expert. There is a substantial expansion in both depth and breadth on the original. It clearly and concisely explains all aspects of the foundations and the latest thinking in active portfolio management."-Eric N. Remole, Managing Director, Head of Global Structured Equity, Credit Suisse Asset Management.Mathematically rigorous and meticulously organized, Active Portfolio Management broke new ground when it first became available to investment managers in 1994. By outlining an innovative process to uncover raw signals of asset returns, develop them into refined forecasts, then use those forecasts to construct portfolios of exceptional return and minimal risk, i.e., portfolios that consistently beat the market, this hallmark book helped thousands of investment managers. Active Portfolio Management, Second Edition, now sets the bar even higher. Like its predecessor, this volume details how to apply economics, econometrics, and operations research to solving practical investment problems, and uncovering superior profit opportunities. It outlines an active management framework that begins with a benchmark portfolio, then defines exceptional returns as they relate to that benchmark. Beyond the comprehensive treatment of the active management process covered previously, this new edition expands to cover asset allocation, long/short investing, information horizons, and other topics relevant today. It revisits a number of discussions from the first edition, shedding new light on some of today's most pressing issues, including risk, dispersion, market impact, and performance analysis, while providing empirical evidence where appropriate. The result is an updated, comprehensive set of strategic concepts and rules of thumb for guiding the process of-and increasing the profits from-active investment management.

The individual investor's comprehensive guide to momentum investingQuantitative Momentum brings momentum investing out of Wall Street and into the hands of individual investors. In his last book, Quantitative Value, author Wes Gray brought systematic value strategy from the hedge funds to the masses; in this book, he does the same for momentum investing, the system that has been shown to beat the market and regularly enriches the coffers of Wall Street's most sophisticated investors. First, you'll learn what momentum investing is not: it's not 'growth' investing, nor is it an esoteric academic concept. You may have seen it used for asset allocation, but this book details the ways in which momentum stands on its own as a stock selection strategy, and gives you the expert insight you need to make it work for you. You'll dig into its behavioral psychology roots, and discover the key tactics that are bringing both institutional and individual investors flocking into the momentum fold.Systematic investment strategies always seem to look good on paper, but many fall down in practice. Momentum investing is one of the few systematic strategies with legs, withstanding the test of time and the rigor of academic investigation. This book provides invaluable guidance on constructing your own momentum strategy from the ground up. Learn what momentum is and is not Discover how momentum can beat the market Take momentum beyond asset allocation into stock selection Access the tools that ease DIY implementationThe large Wall Street hedge funds tend to portray themselves as the sophisticated elite, but momentum investing allows you to 'borrow' one of their top strategies to enrich your own portfolio. Quantitative Momentum is the individual investor's guide to boosting market success with a robust momentum strategy.

Quantitative Finance for Dummies

When the 1974 recession hit Wall Street, investment professionals desperately turned to academia to help regain the value of their clients' holdings. Bernstein shows how Wall Street finally embraced the advences wrought in academic seminars and technical journals tht ultimately transformed the art of investing.

WHAT EVERY OPTION TRADER NEEDS TO KNOW. THE ONE BOOK EVERY TRADER SHOULD OWN.The bestselling Option Volatility & Pricing has made Sheldon Natenberg a widely recognized authority in the option industry. At firms around the world, the text is often the first book that new professional traders aregiven to learn the trading strategies and risk management techniques required for success in option markets.Now, in this revised, updated, and expanded second edition, this thirty-year trading professional presents the most comprehensive guide to advanced trading strategies and techniques now in print. Covering a wide range of topics as diverse and exciting as the marketitself, this text enables both new and experiencedtraders to delve in detail into the many aspects of option markets, including: The foundations of option theory Dynamic hedging Volatility and directional trading strategies Risk analysis Position management Stock index futures and options Volatility contractsClear, concise, and comprehensive, the second edition of Option Volatility & Pricing is sure to be an important addition to every option trader's library--as invaluable as Natenberg's acclaimed seminars at the world'slargest derivatives exchanges and trading firms.You'll learn how professional option traders approach the market, including the trading strategies and risk management techniques necessary for success. You'll gain afuller understanding of how theoretical pricing models work. And, best of all, you'll learn how to apply the principles of option evaluation to create strategies that, given a trader's assessment of market conditions and trends, have the greatest chance of success.Option trading is both a science and an art. This book shows how to apply both to maximum effect.

Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.

"A lot has happened in the financial markets since 1992, when Peter Bernstein wrote his seminal Capital Ideas. Happily, Peter has taken up his facile pen again to describe these changes, a virtual revolution in the practice of investing that relies heavily on complex mathematics, derivatives, hedging, and hyperactive trading. This fine and eminently readable book is unlikely to be surpassed as the definitive chronicle of a truly historic era." —John C. Bogle, founder of The Vanguard Group and author, The Little Book of Common Sense Investing "Just as Dante could not have understood or survived the perils of the Inferno without Virgil to guide him, investors today need Peter Bernstein to help find their way across dark and shifting ground. No one alive understands Wall Street's intellectual history better, and that makes Bernstein our best and wisest guide to the future. He is the only person who could have written this book; thank goodness he did." —Jason Zweig, Investing Columnist, Money magazine "Another must-read from Peter Bernstein! This well-written and thought-provoking book provides valuable insights on how key finance theories have evolved from their ivory tower formulation to profitable application by portfolio managers. This book will certainly be read with keen interest by, and undoubtedly influence, a wide range of participants in international finance." —Dr. Mohamed A. El-Erian, President and CEO of Harvard Management Company, Deputy Treasurer of Harvard University, and member of the faculty of the Harvard Business School "Reading Capital Ideas Evolving is an experience not to be missed. Peter Bernstein's knowledge of the principal characters-the giants in the development of investment theory and practice-brings this subject to life." —Linda B. Strumpf, Vice President and Chief Investment Officer, The Ford Foundation "With great clarity, Peter Bernstein introduces us to the insights of investment giants, and explains how they transformed financial theory into portfolio practice. This is not just a tale of money and models; it is a fascinating and contemporary story about people and the power of their ideas." —Elroy Dimson, BGI Professor of Investment Management, London Business School "Capital Ideas Evolving provides us with a unique appreciation for the pervasive impact that the theory of modern finance has had on the development of our capital markets. Peter Bernstein once again has produced a masterpiece that is must reading for practitioners, educators and students of finance." —André F. Perold, Professor of Finance, Harvard Business School

The first in-depth analysis of pairs trading Pairs trading is a market-neutral strategy in its most simple form. The strategy involves being long (or bullish) one asset and short (or bearish) another. If properly performed, the investor will gain if the market rises or falls. Pairs Trading reveals the secrets of this rigorous quantitative analysis program to provide individuals and investment houses with the tools they need to successfully implement and profit from this proven trading methodology. Pairs Trading contains specific and tested formulas for identifying and investing in pairs, and answers important questions such as what ratio should be used to construct the pairs properly. Ganapathy Vidyamurthy (Stamford, CT) is currently a quantitative software analyst and developer at a major New York City hedge fund.

2013 Reprint of 1957 Edition. Full facsimile of the original edition, not reproduced with Optical Recognition Software. Joseph Penso de la Vega, best known as Joseph de la Vega (ca.1650-1692), was a successful Jewish merchant, poet, and philanthropist residing in 17th century Amsterdam. He became famous for his masterpiece "Confusion of Confusions" the oldest book ever written on the stock exchange business. Although not a descriptive account of the process of stock trading, Penso presented the history of speculation in stocks and acquainted the reader with the sophisticated financial instruments used. The dialogue format allowed the reader to understand the respective perspectives of the various market participants and the intricacies of speculation and trading. Penso also came up with four basic rules of the share market that are still of the greatest relevance today: The first rule in speculation is: Never advise anyone to buy or sell shares. Where guessing correctly is a form of witchcraft, counsel cannot be put on airs. The second rule: Accept both your profits and regrets. It is best to seize what comes to hand when it comes, and not expect that your good fortune and the favorable circumstances will last. The third rule: Profit in the share market is goblin treasure: at one moment, it is carbuncles, the next it is coal; one moment diamonds, and the next pebbles. Sometimes, they are the tears that Aurora leaves on the sweet morning's grass, at other times, they are just tears. The fourth rule: He who wishes to become rich from this game must have both money and patience. Includes Foreword by Hermann Kellenbenz.

Updated and revised to reflect the most current information, this introduction to futures and options markets is ideal for those with a limited background in mathematics. Based on Hull's Options, Futures and Other Derivatives, one of the best-selling books on Wall Street, this book presents an accessible overview of the topic without the use of calculus. Packed with numerical samples and accounts of real-life situations, the Fifth Edition effectively guides readers through the material while providing them with a host of tangible examples. For professionals with a career in futures and options markets, financial engineering and/or risk management.

Here is the first rigorous and accessible account of the mathematics behind the pricing, construction, and hedging of derivative securities. With mathematical precision and in a style tailored for market practioners, the authors describe key concepts such as martingales, change of measure, and the Heath-Jarrow-Morton model. Starting from discrete-time hedging on binary trees, the authors develop continuous-time stock models (including the Black-Scholes method). They stress practicalities including examples from stock, currency and interest rate markets, all accompanied by graphical illustrations with realistic data. The authors provide a full glossary of probabilistic and financial terms.

This text explains in an intuitive yet rigorous way the mathematical and statistical applications relevant to modern financial instruments and risk management techniques. It progresses at a pace that is comfortable for those with less mathematical expertise yet reaches a level of analysis that will reward even the most experienced. The strong applied emphasis makes this book ideal for anyone who is seriously interested in mastering the quantitative techniques underpinning modern financial decision making.

Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data.This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.

This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems.Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book's methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives.Fully revised and expanded to reflect developments in the field since the financial crisis Features shorter chapters to facilitate teaching and learning Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing Includes a new chapter on market risk and new material on risk measures and risk aggregation

Combining their corporate and academic experiences, Jamil Baz and George Chacko offer financial analysts a complete, succinct account of the principles of financial derivatives pricing. Readers with a basic knowledge of finance, calculus, probability and statistics will learn about the most powerful tools in applied finance: equity derivatives, interest rate markets, and the mathematics of pricing. Baz and Chacko apply concepts such as volatility and time, and generic pricing to the valuation of conventional and more specialized cases. Other topics include: *Interest rate markets, government and corporate bonds, swaps, caps, and swaptions *Factor models and term structure consistent models *Mathematical allocation decisions such as mean-reverting processes and jump processes *Stochastic calculus and related tools such as Kilmogorov equations, martingales techniques, stocastic control and partial differential equations Meant for financial analysts and graduate students in finance and economics, Financial Derivatives begins with basic economic principles of risk and builds up various pricing and hedging techniques from those principles. Baz and Chacko simplify the mathematical presentation, and balance theory and real analysis, making it a more accessible and practical manual. Jamil Baz holds an M.S. in Management from MIT and a Ph.D. in Business Economics from Harvard University. He is a Managing Director at Deutsche Bank in London. George Chacko has a B.S. from MIT in electrical engineering and a Ph.D. in Business Economics from Harvard University. He is an Associate Professor of Business Administration at Harvard Business School. Both authors have worked extensively for financial services firms in the private sector. They have published in leading academic journals including the Review of Financial Studies and the Journal of Financial Economics as well as practitioner journals such as the Journal of Fixed Income and the Journal of Applied Corporate Finance.

An Introduction to the Mathematics of Financial Derivatives, Second Edition, introduces the mathematics underlying the pricing of derivatives. The increased interest in dynamic pricing models stems from their applicability to practical situations: with the freeing of exchange, interest rates, and capital controls, the market for derivative products has matured and pricing models have become more accurate. This updated edition has six new chapters and chapter-concluding exercises, plus one thoroughly expanded chapter. The text answers the need for a resource targeting professionals, Ph.D. students, and advanced MBA students who are specifically interested in financial derivatives. This edition is also designed to become the main text in first year masters and Ph.D. programs for certain courses, and will continue to be an important manual for market professionals and professionals with mathematical, technical, or physics backgrounds.

Over 6.4 billion people participate in a $36.5 trillion global economy, designed and overseen by no one. How did this marvel of self-organized complexity evolve? How is wealth created within this system? And how can wealth be increased for the benefit of individuals, businesses, and society? In The Origin of Wealth, Eric D. Beinhocker argues that modern science provides a radical perspective on these age-old questions, with far-reaching implications. According to Beinhocker, wealth creation is the product of a simple but profoundly powerful evolutionary formula: differentiate, select, and amplify. In this view, the economy is a "complex adaptive system" in which physical technologies, social technologies, and business designs continuously interact to create novel products, new ideas, and increasing wealth. Taking readers on an entertaining journey through economic history, from the Stone Age to modern economy, Beinhocker explores how "complexity economics" provides provocative insights on issues ranging from creating adaptive organizations to the evolutionary workings of stock markets to new perspectives on government policies. A landmark book that shatters conventional economic theory, The Origin of Wealth will rewire our thinking about how we came to be here--and where we are going.

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.This book is being published in two volumes. The first volume presents the binomial asset-pricing model primarily as a vehicle for introducing in the simple setting the concepts needed for the continuous-time theory in the second volume.Chapter summaries and detailed illustrations are included. Classroom tested exercises conclude every chapter. Some of these extend the theory and others are drawn from practical problems in quantitative finance.Advanced undergraduates and Masters level students in mathematical finance and financial engineering will find this book useful.Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

Each financial crisis calls for — by its novelty and the mechanisms it shares with preceding crises — appropriate means to analyze financial risks. In Extreme Financial Risks and Asset Allocation, the authors present in an accessible and timely manner the concepts, methods, and techniques that are essential for an understanding of these risks in an environment where asset prices are subject to sudden, rough, and unpredictable changes. These phenomena, mathematically known as “jumps”, play an important role in practice. Their quantitative treatment is generally tricky and is sparsely tackled in similar books. One of the main appeals of this book lies in its approachable and concise presentation of the ad hoc mathematical tools without sacrificing the necessary rigor and precision.This book contains theories and methods which are usually found in highly technical mathematics books or in scattered, often very recent, research articles. It is a remarkable pedagogical work that makes these difficult results accessible to a large readership. Researchers, Masters and PhD students, and financial engineers alike will find this book highly useful.

Contrarian investing--what it is, how it works, and why millions of successful investors see it as the only logical choice "(Davis is) one of the most widely respected technical market analysts operating today." --Louis Rukeyser Contrarians say that, when it comes to investing, the crowd is wrong more often than it is right--and prove it with their 200-year history of success! The Triumph of Contrarian Investing is a fascinating, in depth examination of the impact of crowd psychology on markets, how the crowd is often predictably incorrect, and how investors can use long-proven contrarian investing strategies to uncover tremendous buying and selling opportunities. Ned Davis, one of today's biggest names in investing, reveals: \nHow to ignore the temptation to "join the crowd" and uncover tremendous opportunities \nConsistent signs that a stock's price has been driven too high or too low \nStrategies for protecting contrarian portfolios when--as sometimes happens--the crowd is right \n

One of the most highly regarded independent investment research firms, Ned Davis Research, shares not only their views on grave near-term economic risks and how the investment world works, but more importantly, they provide the tools, tactics, and strategies necessary for manaing risks and making money.

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.This book is being published in two volumes. This second volume develops stochastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time.Master's level studentsand researchers in mathematical finance and financial engineering will find this book useful.

Derivatives by Paul Wilmott provides the most comprehensive and accessible analysis of the art of science in financial modeling available. Wilmott explains and challenges many of the tried and tested models while at the same time offering the reader many new and previously unpublished ideas and techniques. Paul Wilmott has produced a compelling and essential new work in this field. The basics of the established theories-such as stochastic calculus, Black-Scholes, binomial trees and interest-rate models-are covered in clear and precise detail, but Derivatives goes much further. Complex models-such as path dependency, non-probabilistic models, static hedging and quasi-Monte Carlo methods-are introduced and explained to a highly sophisticated level. But theory in itself is not enough, an understanding of the role the techniques play in the daily world of finance is also examined through the use of spreadsheets, examples and the inclusion of Visual Basic programs. The book is divided into six parts: Part One: acts as an introduction and explanation of the fundamentals of derivatives theory and practice, dealing with the equity, commodity and currency worlds. Part Two: takes the mathematics of Part One to a more complex level, introducing the concept of path dependency. Part Three: concerns extensions of the Black-Scholes world, both classic and modern. Part Four: deals with models for fixed-income products. Part Five: describes models for risk management and measurement. Part Six: delivers the numerical methods required for implementing the models described in the rest of the book. Derivatives also includes a CD containing a wide variety of implementation material related to the book in the form of spreadsheets and executable programs together with resource material such as demonstration software and relevant contributed articles. At all times the style remains readable and compelling making Derivatives the essential book on every finance shelf.

Paul Wilmott on Quantitative Finance, Second Edition provides a thoroughly updated look at derivatives and financial engineering, published in three volumes with additional CD-ROM.Volume 1: Mathematical and Financial Foundations; Basic Theory of Derivatives; Risk and Return.The reader is introduced to the fundamental mathematical tools and financial concepts needed to understand quantitative finance, portfolio management and derivatives. Parallels are drawn between the respectable world of investing and the not-so-respectable world of gambling.Volume 2: Exotic Contracts and Path Dependency; Fixed Income Modeling and Derivatives; Credit RiskIn this volume the reader sees further applications of stochastic mathematics to new financial problems and different markets.Volume 3: Advanced Topics; Numerical Methods and Programs.In this volume the reader enters territory rarely seen in textbooks, the cutting-edge research. Numerical methods are also introduced so that the models can now all be accurately and quickly solved.Throughout the volumes, the author has included numerous Bloomberg screen dumps to illustrate in real terms the points he raises, together with essential Visual Basic code, spreadsheet explanations of the models, the reproduction of term sheets and option classification tables. In addition to the practical orientation of the book the author himself also appears throughout the book—in cartoon form, readers will be relieved to hear—to personally highlight and explain the key sections and issues discussed.Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Stochastic calculus has important applications to mathematical finance. This book will appeal to practitioners and students who want an elementary introduction to these areas. From the reviews: "As the preface says, ‘This is a text with an attitude, and it is designed to reflect, wherever possible and appropriate, a prejudice for the concrete over the abstract’. This is also reflected in the style of writing which is unusually lively for a mathematics book." --ZENTRALBLATT MATH

Fueled in part by some extraordinary theoretical developments in finance, an explosive growth of information and computing technology, and the global expansion of investment activity, investment theory currently commands a high level of intellectual attention. Recent developments in the field are being infused into university classrooms, financial service organizations, business ventures, and into the awareness of many individual investors. Modern investment theory using the language of mathematics is now an essential aspect of academic and practitioner training. Representing a breakthrough in the organization of finance topics, Investment Science will be an indispensable tool in teaching modern investment theory. It presents sound fundamentals and shows how real problems can be solved with modern, yet simple, methods. David Luenberger gives thorough yet highly accessible mathematical coverage of standard and recent topics of introductory investments: fixed-income securities, modern portfolio theory and capital asset pricing theory, derivatives (futures, options, and swaps), and innovations in optimal portfolio growth and valuation of multiperiod risky investments. Throughout the book, he uses mathematics to present essential ideas of investments and their applications in business practice. The creative use of binomial lattices to formulate and solve a wide variety of important finance problems is a special feature of the book. In moving from fixed-income securities to derivatives, Luenberger increases naturally the level of mathematical sophistication, but never goes beyond algebra, elementary statistics/probability, and calculus. He includes appendices on probability and calculus at the end of the book for student reference. Creative examples and end-of-chapter exercises are also included to provide additional applications of principles given in the text. Ideal for investment or investment management courses in finance, engineering economics, operations research, and management science departments, Investment Science has been successfully class-tested at Boston University, Stanford University, and the University of Strathclyde, Scotland, and used in several firms where knowledge of investment principles is essential. Executives, managers, financial analysts, and project engineers responsible for evaluation and structuring of investments will also find the book beneficial. The methods described are useful in almost every field, including high-technology, utilities, financial service organizations, and manufacturing companies.

Winner of the prestigious Paul A. Samuelson Award for scholarly writing on lifelong financial security, John Cochrane's Asset Pricing now appears in a revised edition that unifies and brings the science of asset pricing up to date for advanced students and professionals. Cochrane traces the pricing of all assets back to a single idea--price equals expected discounted payoff--that captures the macro-economic risks underlying each security's value. By using a single, stochastic discount factor rather than a separate set of tricks for each asset class, Cochrane builds a unified account of modern asset pricing. He presents applications to stocks, bonds, and options. Each model--consumption based, CAPM, multifactor, term structure, and option pricing--is derived as a different specification of the discounted factor.\n The discount factor framework also leads to a state-space geometry for mean-variance frontiers and asset pricing models. It puts payoffs in different states of nature on the axes rather than mean and variance of return, leading to a new and conveniently linear geometrical representation of asset pricing ideas.\n Cochrane approaches empirical work with the Generalized Method of Moments, which studies sample average prices and discounted payoffs to determine whether price does equal expected discounted payoff. He translates between the discount factor, GMM, and state-space language and the beta, mean-variance, and regression language common in empirical work and earlier theory.\n The book also includes a review of recent empirical work on return predictability, value and other puzzles in the cross section, and equity premium puzzles and their resolution. Written to be a summary for academics and professionals as well as a textbook, this book condenses and advances recent scholarship in financial economics.

An inside look at modern approaches to modeling equity portfolios Financial Modeling of the Equity Market is the most comprehensive, up-to-date guide to modeling equity portfolios. The book is intended for a wide range of quantitative analysts, practitioners, and students of finance. Without sacrificing mathematical rigor, it presents arguments in a concise and clear style with a wealth of real-world examples and practical simulations. This book presents all the major approaches to single-period return analysis, including modeling, estimation, and optimization issues. It covers both static and dynamic factor analysis, regime shifts, long-run modeling, and cointegration. Estimation issues, including dimensionality reduction, Bayesian estimates, the Black-Litterman model, and random coefficient models, are also covered in depth. Important advances in transaction cost measurement and modeling, robust optimization, and recent developments in optimization with higher moments are also discussed. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm, The Intertek Group. He is a member of the editorial board of the Journal of Portfolio Management. He is also the author of numerous articles and books on financial modeling. Petter N. Kolm, PhD (New Haven, CT and New York, NY), is a graduate student in finance at the Yale School of Management and a financial consultant in New York City. Previously, he worked in the Quantitative Strategies Group of Goldman Sachs Asset Management, where he developed quantitative investment models and strategies.

Discusses in the practical and theoretical aspects of one-period asset allocation, i.e. market Modeling, invariants estimation, portfolia evaluation, and portfolio optimization in the prexence of estimation risk The book is software based, many of the exercises simulate in Matlab the solution to practical problems and can be downloaded from the book's web-site

The 11th edition contains 170 quantitative questions collected from actual job interviews in investment banking, investment management, and options trading. The interviewers use the same questions year-after-year and here they are---with solutions! These questions come from all types of interviews (corporate finance, sales and trading, quant research, etc), but they are especially likely in quantitative capital markets job interviews. The questions come from all levels of interviews (undergrad, MBA, PhD), but they are especially likely if you have, or almost have, an MS or MBA. The latest edition includes 125 non-quantitative actual interview questions, and a new section on interview technique---based partly on Dr. Crack's experiences interviewing candidates for the world's largest institutional asset manager. Dr. Crack has a PhD from MIT. He has won many teaching awards and has publications in the top academic, practitioner, and teaching journals in finance. He has degrees in Mathematics/Statistics, Finance, and Financial Economics and a diploma in Accounting/Finance. Dr. Crack taught at the university level for 20 years including four years as a front line teaching assistant for MBA students at MIT. He recently headed a quantitative active equity research team at the world's largest institutional money manager.

Paul Wilmott writes, "Quantitative finance is the most fascinating and rewarding real-world application of mathematics. It is fascinating because of the speed at which the subject develops, the new products and the new models which we have to understand. And it is rewarding because anyone can make a fundamental breakthrough. "Having worked in this field for many years, I have come to appreciate the importance of getting the right balance between mathematics and intuition. Too little maths and you won't be able to make much progress, too much maths and you'll be held back by technicalities. I imagine, but expect I will never know for certain, that getting the right level of maths is like having the right equipment to climb Mount Everest; too little and you won't make the first base camp, too much and you'll collapse in a heap before the top. "Whenever I write about or teach this subject I also aim to get the right mix of theory and practice. Finance is not a hard science like physics, so you have to accept the limitations of the models. But nor is it a very soft science, so without those models you would be at a disadvantage compared with those better equipped. I believe this adds to the fascination of the subject. "This FAQs book looks at some of the most important aspects of financial engineering, and considers them from both theoretical and practical points of view. I hope that you will see that finance is just as much fun in practice as in theory, and if you are reading this book to help you with your job interviews, good luck! Let me know how you get on!"