Here are 41 books that Credit Risk Modelling fans have personally recommended if you like
Credit Risk Modelling.
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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.
The valuation of options has been the subject of numerous studies, papers, and books.
The originality of this one is that it is collecting the resulting formulae to be used in practice, and for each of them, proposing related Excel spreadsheets, and VBA coding (also with a CD included). All types of options are covered, from “vanilla” to “exotics”, on every kind of underlyings (from traditional ones up to commodities and energy).
It also develops calculation methods for the options “greeks” and volatility. But the book is not only such a catalog of formulae, these are assorted by useful comments about the best way to apply them, and their validity limits. Not surprisingly, this book is qualified as the “bible” of options valuation.
Long-established as a definitive resource by Wall Street professionals, The Complete Guide to Option Pricing Formulas has been revised and updated to reflect the realities of today's options markets. The Second Edition contains a complete listing of virtually every pricing formula_all presented in an easy-to-use dictionary format, with expert author commentary and ready-to-use programming code.
The Second Edition of this classic guide now includes more than 60 new option models and formulas...extensive tables providing an overview of all formulas...new examples and applications...and an updated CD containing all pricing formulas, with VBA code and ready-to-use Excel spreadsheets.
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…
I grew up in the 1950s next door to Long Island’s iconic Levittown. All my aunts and uncles lived in similar modest suburbs, and I assumed everyone else did, too. Maybe that explains why America’s sharp economic U-turn in the 1970s so rubbed me the wrong way. We had become, in the mid-20th century, the first major nation where most people—after paying their monthly bills—had money left over. Today we rate as the world’s most unequal major nation. Our richest 0.1 percent hold as much wealth as our bottom 90 percent. I’ve been working with the Institute for Public Studies, as co-editor of Inequality.org, to change all that.
Our nation’s most insightful—and readable—sociologist? Boston College’s Juliet Schorr has my vote.
Over the past quarter-century, Schor has probably done more than anyone else in the world to bring grand conceptual constructs like income distribution down to the nitty-gritty of daily life.
Her 1999 best-seller,The Overspent American, strikingly exposes how inequality unleashes a “competitive consumption” dynamic that has us consuming ever more and enjoying life ever less. And that dynamic poses more dangers today than ever before.
As Schor put it in an interview with her I did some years back, we have “no chance” at achieving ecological sustainability “with the kind of extreme income distribution” that we have today.
An in-depth look at the corruption of the American Dream, the follow-up to the the Overworked American examines the consumer lives of Americans and the pitfalls of keeping up with the Joneses. Schor explains how and why the purchases of others in our social and professional communities can put pressure on us to spend more than we can afford to, how television viewing can undermine our ability to save, and why even households with good incomes have taken on so much debt for so many products they dont need and often dont even want.
Crypto’s rollercoaster journey has given rise to some of the most thrilling real-life tales of the last two decades. These tales teem with personal drama and reveal much larger truths: about our fractured global moment, about the ripple effects of well-intentioned technological systems, and about the massive divide between how we want society to function and how it actually does.
As much as some people wish it dead, crypto is not going away any time soon. Many of its followers have adopted a religious-like belief that it will transform humanity and bring unlimited wealth to its followers; others simply believe it to be a good investment. Their collective trust in these strange digital currencies means that crypto will continue to shape the world in unpredictable ways.
The journalist Nathaniel Popper starts at the beginning, telling the story of how Bitcoin emerged from message boards and was slowly but surely propelled forward by government-wary libertarians, computer science nerds, and opportunistic venture capitalists.
Popper persuasively articulates the many problems that Bitcoin solves across the world—and then reveals its extremely bumpy road toward adoption.
Shortlisted for the Financial Times and McKinsey Business Book of the Year Award
A New York Times technology and business reporter charts the dramatic rise of Bitcoin and the fascinating personalities who are striving to create a new global money for the Internet age.
Digital Gold is New York Times reporter Nathaniel Popper's brilliant and engrossing history of Bitcoin, the landmark digital money and financial technology that has spawned a global social movement.
The notion of a new currency, maintained by the computers of users around the world, has been the butt of many jokes, but that has not stopped…
I have long found it mysterious how we can live in what is truly one interconnected global order. Traders, merchants, deal-makers have long been viewed with suspicion. I wrote Compass of Societyto explore how one country, France, with its tradition of land-based elites, could contemplate remaking itself as a “commercial society.” Adam Smith said that even in his time, everyone “becomes in some measure a merchant, and the society itself... a commercial society.” Revisionists are finding high levels of commercialization even in premodern China and India. In this list, I picked five of my favorite books that reshaped our understanding of where European “capitalism” came from.
This major synthesis broadens the canvas to Europe as a whole, especially Western and Northwest Europe. On the continent, peasant culture was more prominent than in England, and the French historian Fontaine—who has also written ground-breaking studies of peddling and the second-hand trade—shows vividly how resilient, enterprising, even manipulative ordinary Europeans in village and mountain could be in maneuvering their way through economic life. “In early modern Europe,” she writes at one point, “everyone was more or less a merchant”—which, of course, is exactly what Adam Smith had said.
The Moral Economy examines the nexus of poverty, credit, and trust in early modern Europe. It starts with an examination of poverty, the need for credit, and the lending practices of different social groups. It then reconstructs the battles between the Churches and the State around the ban on usury, and analyzes the institutions created to eradicate usury and the informal petty financial economy that developed as a result. Laurence Fontaine unpacks the values that structured these lending practices, namely, the two competing cultures of credit that coexisted, fought, and sometimes merged: the vibrant aristocratic culture and the capitalistic merchant…
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…
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
