Here are 58 books that The Fundamentals of Heavy Tails fans have personally recommended if you like
The Fundamentals of Heavy Tails.
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I’ve spent most of my life writing code—and too much of that life teaching new programmers how to write code like a professional. If it’s true that you only truly understand something after teaching it to someone else, then at this point I must really understand programming! Unfortunately, that understanding has not led to an endless stream of bug-free code, but it has led to some informed opinions on programming and books about programming.
Yes, it’s a textbook, albeit a particularly well-written one. You may already have it on your shelf, if you’ve taken a programming class or two.
I’m way too old to have used CLRS as a textbook, though! For me, it’s an effectively bottomless collection of neat little ideas—an easy-to-describe problem, then a series of increasingly clever ways to solve that problem. How often do I end up using one of those algorithms? Not very often! But every time I read the description of an algorithm, I get a nugget of pure joy from the “aha” moment when I first understand how it works.
It is April 1st, 2038. Day 60 of China's blockade of the rebel island of Taiwan.
The US government has agreed to provide Taiwan with a weapons system so advanced that it can disrupt the balance of power in the region. But what pilot would be crazy enough to run…
Dr. Jeremy Kepner is head and founder of the MIT Lincoln Laboratory Supercomputing Center (LLSC), and also a Founder of the MIT-Air Force AI Accelerator. Lincoln Laboratory is a 4000-person National Laboratory whose mission is to create defensive technologies to protect our Nation and the freedoms enshrined in the Constitution of the United States. Dr. Kepner is one of five Lincoln Laboratory Fellows, a position that "recognizes the Laboratory's strongest technical talent for outstanding contributions to Laboratory programs over many years." Dr. Kepner is recognized as one of nine MIT Fellows of the Society of Industrial Applied Mathematics (SIAM), for "contributions to interactive parallel computing, matrix-based graph algorithms, green supercomputing, and big data."
Unix/Linux has emerged as the most common operating system in the world. Found on almost every server, smartphone, and network-enabled device, Unix plays a critical role in all aspects of computing. Unix for the Beginning Mage is a fun introduction to Unix for the novice who may be intimidated by other texts.
Dr. Jeremy Kepner is head and founder of the MIT Lincoln Laboratory Supercomputing Center (LLSC), and also a Founder of the MIT-Air Force AI Accelerator. Lincoln Laboratory is a 4000-person National Laboratory whose mission is to create defensive technologies to protect our Nation and the freedoms enshrined in the Constitution of the United States. Dr. Kepner is one of five Lincoln Laboratory Fellows, a position that "recognizes the Laboratory's strongest technical talent for outstanding contributions to Laboratory programs over many years." Dr. Kepner is recognized as one of nine MIT Fellows of the Society of Industrial Applied Mathematics (SIAM), for "contributions to interactive parallel computing, matrix-based graph algorithms, green supercomputing, and big data."
A British term of endearment for a person engaged in scientific or technical research, Boffins have played a critical role in the development of our modern society. This book is the autobiography of the first Boffin who was essential in developing the radar system that won the Battle of Britain. Although nearly a century has passed, the “can-do” technical spirit of Boffins, Geeks, Nerds, and Hackers remains at the core of modern innovation.
An account of the history of radar, which traces its evolution and vital military role, particularly with regard to Britain's aerial victories in World War II.
A Duke with rigid opinions, a Lady whose beliefs conflict with his, a long disputed parcel of land, a conniving neighbour, a desperate collaboration, a failure of trust, a love found despite it all.
Alexander Cavendish, Duke of Ravensworth, returned from war to find that his father and brother had…
From our very beginning, Americans have stood out from all other people on earth in one odd habit: We have a powerful reflex to fix problems ourselves—directly, locally, as individuals—instead of waiting for nobles or experts or government officials to save us. Between the volunteer hours and money we donate, our philanthropic efforts total close to a trillion dollars of organic problem-solving every year. It’s a wellspring of our national success. Struck by the effectiveness of our grassroots charitable action, I spent several years compiling the authoritative reference book that documents exactly how private giving bolsters U.S. prosperity, the Almanac of American Philanthropy. Then, I produced a historical novel portraying some great givers.
Many of us know that philanthropists have been central to eradicating disease, that charitable groups are powerful forces against hunger and poverty, and that philanthropy is behind many of our greatest educational successes. But did you know that private donors were largely responsible for making America the world leader in rocketry? That they willed the fields of aeronautics and biomedical engineering into existence.
During World War II, it was not a government agency but rather a philanthropist who jumpstarted the rollout of radar and then rescued the effort to create atomic weapons after it had bogged down in our defense bureaucracy. With this book, you can marvel at the WWII heroics accomplished by entrepreneur and generous giver Alfred Loomis.
In the fall of 1940, as German bombers flew over London and with America not yet at war, a small team of British scientists on orders from Winston Churchill carried out a daring transatlantic mission. The British unveiled their most valuable military secret in a clandestine meeting with American nuclear physicists at the Tuxedo Park mansion of a mysterious Wall Street tycoon, Alfred Lee Loomis. Powerful, handsome, and enormously wealthy, Loomis had for years led a double life, spending his days brokering huge deals and his weekends working with the world's leading scientists in his deluxe private laboratory that was…
I’m an archaeologist, which means that I’ve been lucky enough to travel to many places to dig and survey ancient remains. What I’ve realized in handling those dusty old objects is that all over the world, in both past and present, people are defined by their stuff: what they made, used, broke, and threw away. Most compelling are the things that people cherished despite being worn or flawed, just like we have objects in our house that are broken or old but that we keep anyway.
This looks like it’s the sternest and most boring book ever, but I love Steedman’s cool-and-collected ability to address the implications of the obvious: You can only do one thing at a time. You only have two hands. And when you’re with one set of belongings, you’re neglecting all the other stuff you own.
Standard economic theory of consumer behaviour considers consumers' preferences, their incomes and commodity prices to be the determinants of consumption. However, consumption takes time and no consumer has more - or less - than 168 hours per week. This simple fact is almost invisible in standard theory, and takes the centre stage in this book.
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,…
The Duke's Christmas Redemption
by
Arietta Richmond,
A Duke who has rejected love, a Lady who dreams of a love match, an arranged marriage, a house full of secrets, a most unneighborly neighbor, a plot to destroy reputations, an unexpected love that redeems it all.
Lady Charlotte Wyndham, given in an arranged marriage to a man she…
As a boy, I wanted to play baseball professionally. But, alas, talent was not within me, and I became one of the few people in the world who chose physics as a career because something else was too hard. Part of my career as a scientist is learning new things; another part is teaching and, hopefully, imbuing students with a love of science. The sports science books here all taught me a great deal, and I have recommended them to several of my students. Sports can be an excellent vehicle for learning some science, and such learning about a sport one loves can make watching the sport even more fun.
I confess that I know Trevor Lipscombe, but I would add his book to this list if I did not know him. Like Haché’s book on ice hockey, I was out of my comfort zone while reading a book on rugby. As I write this, I am in the midst of my third sabbatical year. All three of my sabbatical years have been spent researching at universities in Sheffield, England. People are enthusiastic about rugby in England as well as in other parts of the world.
Not only did this book introduce me to a new way to apply physics, but it also taught me so much about rugby that I can cheer with mates in a pub while watching a match! It is the go-to book on rugby science.
What if Einstein played rugby? Surely Time Magazine's "Man of the Century" might offer useful tips and techniques to defeat the opposition? In this book, the world of physics joins forces with the world of rugby, to show you how to tackle harder, pass safer, run faster, and scrum better - all the things you need to do to win. Blending simple physics, the kind you meet in high school, with anecdotes and stories from the world of rugby, Trevor Lipscombe takes us on a journey from scrum ruck and maul, to the running and passing of the offence, the…
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.
It’s been fantastic to work in computer vision, especially when it is used to build biometric systems. I and my 80 odd PhD students have pioneered systems that recognise people by the way they walk, by their ears, and many other new things too. To build the systems, we needed computer vision techniques and architectures, both of which work with complex real-world imagery. That’s what computer vision gives you: a capability to ‘see’ using a computer. I think we can still go a lot further: to give blind people sight, to enable better invasive surgery, to autonomise more of our industrial society, and to give us capabilities we never knew we’d have.
David Marr shaped the field of computer vision in its early days. His seminal book laid the structure for interpreting images and one which is still largely followed. He popularised notions of the primal sketch and his work on edge detection led to one of the most sophisticated approaches. His work and influence continue to endure despite his early death: we missed and miss him a lot.
Available again, an influential book that offers a framework for understanding visual perception and considers fundamental questions about the brain and its functions.
David Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field. In Vision, Marr describes a general framework for understanding visual perception and touches on broader questions about how the brain and its functions can be studied and understood. Researchers from a range of brain and cognitive sciences have long valued Marr's creativity, intellectual power, and ability to integrate insights and data from neuroscience, psychology, and computation. This…
This book follows the journey of a writer in search of wisdom as he narrates encounters with 12 distinguished American men over 80, including Paul Volcker, the former head of the Federal Reserve, and Denton Cooley, the world’s most famous heart surgeon.
In these and other intimate conversations, the book…
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
