Here are 51 books that The Complete Guide to Option Pricing Formulas fans have personally recommended if you like
The Complete Guide to Option Pricing Formulas.
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Having a master's degree in chemical engineering, I wasn't destined to work in the area of quantitative finance… the reason why I professionally moved to this discipline aren't worth exposing, but as a matter of fact, I've been quickly fascinated by this science, and encountered some of my favorites, such as maths and statistics, as used in the traditional activity of an engineer. And I had many opportunities of combining the knowledge and practice of financial markets with pragmatism, typically of the engineer’s education, i.e. oriented toward problem solving. In addition, I've always loved teaching, and writing books on financial markets & instruments, hence the importance I'm giving to pedagogy in professional books.
Having read or browsed many books dedicated to the mathematics of options and other derivative instruments, I unquestionably consider Neftci’s book as by far the best choice.
Starting with the fundamentals, it goes much further than a simple “introduction”, and typically fits with the needs of a “quant” specializing in options, with a good balance between pure theoretical, mathematical developments (such as Partial Differential Equations, Girsanov theorem, Markov processes, etc) and practical applications on option pricing.
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.
Having a master's degree in chemical engineering, I wasn't destined to work in the area of quantitative finance… the reason why I professionally moved to this discipline aren't worth exposing, but as a matter of fact, I've been quickly fascinated by this science, and encountered some of my favorites, such as maths and statistics, as used in the traditional activity of an engineer. And I had many opportunities of combining the knowledge and practice of financial markets with pragmatism, typically of the engineer’s education, i.e. oriented toward problem solving. In addition, I've always loved teaching, and writing books on financial markets & instruments, hence the importance I'm giving to pedagogy in professional books.
For financial market practitioners, it would be unwise not to deeply care about the various financial risks associated with their uses.
This book thoroughly covers the whole set of such financial risks, i.e. market risk, credit/counterparty risk, liquidity risk (both on the asset and liability sides), broadening the subject up to the firmwide level risk. It goes both into theoretical and practical considerations (risk management of a portfolio of financial instruments), illustrated by useful examples, with a great pedagogical sense.
A global banking risk management guide geared toward the practitioner
Financial Risk Management presents an in-depth look at banking risk on a global scale, including comprehensive examination of the U.S. Comprehensive Capital Analysis and Review, and the European Banking Authority stress tests. Written by the leaders of global banking risk products and management at SAS, this book provides the most up-to-date information and expert insight into real risk management. The discussion begins with an overview of methods for computing and managing a variety of risk, then moves into a review of the economic foundation of modern risk management and the…
Having a master's degree in chemical engineering, I wasn't destined to work in the area of quantitative finance… the reason why I professionally moved to this discipline aren't worth exposing, but as a matter of fact, I've been quickly fascinated by this science, and encountered some of my favorites, such as maths and statistics, as used in the traditional activity of an engineer. And I had many opportunities of combining the knowledge and practice of financial markets with pragmatism, typically of the engineer’s education, i.e. oriented toward problem solving. In addition, I've always loved teaching, and writing books on financial markets & instruments, hence the importance I'm giving to pedagogy in professional books.
In the vast array of quantitative finance relative to financial markets instruments and related risks, the case of credit or counterparty risk remains by far the most complex one, and thus, unsurprisingly, the least mastered by financial markets professionals.
A lot has been done, but a lot remains to be done: covering this is precisely the goal of this book. In a nutshell, the main obstacle to succeed in developing grounded and useful models of default prediction is due to the fact that a default is (fortunately) a rare event, in other words, with a (very) low probability of occurrence, and statistical tools are uncomfortable with very low probability levels. Hence the need of this book, to help the practitioner to go ahead in this matter.
The book reveals to traders how to consistently outperform credit benchmarks, how to hedge the credit risk premium, and how to overcome pension liability deficits. In addition, several successful trading strategies are presented including debt versus equities, Co-Co bond trading and a quantitative analysis of the municipal bond market. Chapters include: Credit Models, Past Present and Future Predicting Annual Default Rates and Implications for Market Prices Risk and Relative Value in the Municipal Bond Market Contingent Collateral Bonds Model for Sovereign Default and Relative Value Beating Credit Benchmarks Analyzing and Hedging Systemic Liquidity Risk Building on the best-selling first edition,…
Having a master's degree in chemical engineering, I wasn't destined to work in the area of quantitative finance… the reason why I professionally moved to this discipline aren't worth exposing, but as a matter of fact, I've been quickly fascinated by this science, and encountered some of my favorites, such as maths and statistics, as used in the traditional activity of an engineer. And I had many opportunities of combining the knowledge and practice of financial markets with pragmatism, typically of the engineer’s education, i.e. oriented toward problem solving. In addition, I've always loved teaching, and writing books on financial markets & instruments, hence the importance I'm giving to pedagogy in professional books.
Technical Analysis is traditionally denigrated by the academic community, not without good reasons. But as a matter of fact, traders and practitioners used them (also, not without good reasons) extensively, to the extent that Technical Analysis is often qualified as “self-fulfilling prophecy”.
There is therefore a good reason to be more or less familiar with these techniques, at worst, following the adage “Know your enemy”. The problem, with Technical Analysis, is that, as it is not a true science, it is not easy to find books about it, written in a serious way. This is however the case with this one, covering all the usual technical analysis methods, both the graphic and the numeric ones, in a clear, concise, and exemplified way.
This book is updated and revised - with over 35 brand new indicators! It is a comprehensive catalog of today's major technical analysis indicators - indispensable for trading in stocks, bonds, futures, and options! 'There is an urgent need for a concise reference on such a vast array of technical tools. Achelis' new edition fulfills that need and should provide an invaluable guide to newcomers and veterans alike' - John J. Murphy President, MurphyMorris.com, Author, "Technical Analysis of the Financial Markets and Intermarket Technical Analysis".'Steve Achelis has done it again. The first edition was a wonderfully comprehensive encyclopedia of market…
A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.
Disclaimer: I like Euan’s books not because he is a friend and has endorsed my books. Long before we became friends, I have bought his book, and said to myself “Wow! This is the first book about options trading that is not just a bunch of trite statements about payouts from various straddles and spreads positions!” It talks about some unique arbitrage opportunities that only professionals knew about. On the other hand, the amount of mathematics is very manageable, and can largely be skipped without affecting the practical applications of the concepts.
An A to Z options trading guide for the new millennium and the new economy Written by professional trader and quantitative analyst Euan Sinclair, Option Trading is a comprehensive guide to this discipline covering everything from historical background, contract types, and market structure to volatility measurement, forecasting, and hedging techniques. This comprehensive guide presents the detail and practical information that professional option traders need, whether they're using options to hedge, manage money, arbitrage, or engage in structured finance deals. It contains information essential to anyone in this field, including option pricing and price forecasting, the Greeks, implied volatility, volatility measurement…
Richard L. Weissman is one of the world’s foremost authorities and thought leaders in the fields of derivatives, risk management and technical analysis. He is the author of two books: Mechanical Trading Systems: Pairing Trader Psychology with Technical Analysis (Wiley, 2004) and Trade Like a Casino: Find Your Edge, Manage Risk and Win Like the House (Wiley, 2011) which was a finalist for the 2012 Technical Analyst Book of the Year Award. Mr. Weissman has over thirty years experience as a derivatives trader and has provided training and consultation services to traders and risk managers at investment banks, hedge funds, energy, and agricultural companies for over twenty years.
Traders often ask me for a book that will teach them the nuts and bolts (pricing models, volatility, the Greeks, spread strategies, etc.,) of options and I always recommend this book. When I was learning options, the Natenberg book hadn’t been written and although there were “good” books on the topic, Natenberg is truly the gold standard for options traders.
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…
I am a reader of primary texts. One can be dismayed by the number of followers’ easy reliance on secondary literature to create interpretations of their leader’s economic ideas about the sources of society’s well-being. Distortive alteration and the recycling of unfounded ideas about conflicting influential economists’ theories is actually counterproductive. Only scrutiny of an author’s work can reveal false assertions. I’m proposing four authors I’ve scrutinised to find out what they really thought about my main teaching interests: money and credit, and their impact on prices, and the manipulation of the volume of either/both to affect purchasing power. It has been astounding to learn what theory applications, distorting their intent, bear their name.
Most economists associate volume of money with price-level (inflation/deflation), not Keynes.
For him, a macro price-level does not reveal the unsynchronized dynamics affecting the prices of its components: commodities, labor, capital, raw materials, profits; it must be decomposed.
When FunCorp invests in a rollercoaster, its decision is based on present costs and future returns (ticket sales, performance, stock options, etc.).
Windfall profits will lead to more expansion; losses, to curtailed activity. Both expansion, contingent on easy credit, or recession, on the tightening of credit, depend on bankers’ use of individuals’ savings and their creation of more deposits.
For Keynes, an institutionalised banking system is essential for a modern economy but he advocated, in the public interest, for strict rules on bankers’ abuse of credit, to mitigate the inflation/deflation rollercoaster.
2011 Reprint of 1930 American Edition. Two volumes Complete in One. Full facsimile of the original edition, not reproduced with Optical Recognition Software. Volumes One and Two of Keynes' classic work published in a handy one volume format. Exact facsimile of the original Edition. Keynes had begun a theoretical work to examine the relationship between unemployment, money and prices back in the 1920s. The work, Treatise on Money, was published in 1930 in two volumes. We reproduce this two volume edition in one volume. A central idea of the work was that if the amount of money being saved exceeds…
Microeconomics is a turnoff to most readers. Not without reason. Many books in this field are dull rewrites of other books and opaque. In particular, it is not clear how the behavior of individual consumers and producers adds to the performance—good or bad—of an economy. The books listed here helped me to sharpen my own mind and to make my writing lucid.
As a math student I found economics a slippery subject and, therefore, was hesitant to read any book on the subject.
Theory of Value is a short, formal manuscript, that includes the definition of an economy. It was the first book I read in economics and I loved it. It induced me to move to New York and to study the field.
"[This] beautiful and austere book . . . [is] an important landmark of economic theory."-F.H. Hahn, Journal of Political Economy "An immortal classic of twentieth century economics. Every economist should own a copy."-Robert Lucas, University of Chicago Theory of Value offers a rigorous, axiomatic, and formal analysis of producer behavior, consumer behavior, general equilibrium, and the optimality of the market mechanism for resource allocation.
A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.
Finally, for those who are not afraid of math, they should read this book because there is a lot of heavy-duty math. The good news for the rest of us is you can ignore all the math and still get a lot out of it, especially knowledge about market microstructure and how to find the theoretically optimal trading strategies given some assumptions about the price dynamics. Even if you don’t want to or can’t solve those darn stochastic differential equations, you can still implement a numerical approximation. At the minimum, you will learn common trading lingo such as “walking the book” or “the ITCH feed”.
The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and…
A noted quantitative hedge fund manager and quant finance author, Ernie is the founder of QTS Capital Management and Predictnow.ai. Previously he has applied his expertise in machine learning at IBM T.J. Watson Research Center’s Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. Ernie was quoted by Bloomberg, the Wall Street Journal, New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program. He is an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervises student theses there. Ernie holds a Ph.D. in theoretical physics from Cornell University.
By now, you may notice that I like to recommend textbooks. I use this bestseller for my course in Financial Machine Learning at Northwestern University, but really, nobody interested in financial machine learning hasn’t read this book. The topics are highly relevant to every investor or trader – I read it at least 5 times to digest every nugget and have put them to very productive use in my trading as well as in my fintech firm predictnow.ai. It covers basic techniques such as random forest to advanced techniques such as Hierarchical Risk Parity, which is a big improvement over traditional portfolio optimization methods.
Marcos used to be Head of Machine Learning at AQR (AUM=$143B), and now is the Global Head of Quant Research at Abu Dhabi Investment Authority. He is also very approachable to his readers and students. There was seldom an email or message from me to which…
Learn to understand and implement the latest machine learning innovations to improve your investment performance
Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that - until recently - only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest.
In the book, readers will learn how to:
Structure big data in a way that is amenable to ML algorithms
Conduct research with ML algorithms on big data
Use supercomputing methods and back test their discoveries while avoiding false positives
