Already used by people and companies around the world, many forecast that Bitcoin could radically transform the global economy. The value of a bitcoin has soared from less than a dollar in 2011 to well over $1000 in 2013, with many spikes and crashes along the way. The rise in value has brought Bitcoin into the public eye, but the cryptocurrency still confuses many people. Bitcoin for the Befuddled covers everything you need to know about Bitcoin—what it is, how it works, and how to acquire, store, and use bitcoins safely and securely. You'll also learn about Bitcoin's history, its complex cryptography, and its potential impact on trade and commerce. The book includes a humorous, full-color comic explaining Bitcoin concepts, plus a glossary of terms for easy reference.

    This entertaining guide builds on scores of case studies taken from business, sports, the movies, politics, and gambling. It outlines the basics of good strategy making and then shows how you can apply them in any area of your life.

    Farrar, Straus and Giroux, 2009.

    His explanation and classification of alpha will enlighten even a seasoned veteran." ?Blair Hull, Founder, Hull Trading & Matlock Trading"Rishi provides a comprehensive overview of quantitative investing that should prove useful both to those allocating money to quant strategies and those interested in becoming quants themselves. Rishi's experience as a well-respected quant fund of funds manager and his solid relationships with many practitioners provide ample useful material for his work." ?Peter Muller, Head of Process Driven Trading, Morgan Stanley"A very readable book bringing much needed insight into a subject matter that is not often covered. Provides a framework and guidance that should be valuable to both existing investors and those looking to invest in this area for the first time. Many quants should also benefit from reading this book." ?Steve Evans, Managing Director of Quantitative Trading, Tudor Investment Corporation"Without complex formulae, Narang, himself a leading practitioner, provides an insightful taxonomy of systematic trading strategies in liquid instruments and a framework for considering quantitative strategies within a portfolio. This guide enables an investor to cut through the hype and pretense of secrecy surrounding quantitative strategies." ?Ross Garon, Managing Director, Quantitative Strategies, S.A.C. Capital Advisors, L.P."Inside the Black Box is a comprehensive, yet easy read. Rishi Narang provides a simple framework for understanding quantitative money management and proves that it is not a black box but rather a glass box for those inside." ?Jean-Pierre Aguilar, former founder and CEO, Capital Fund Management"This book is great for anyone who wants to understand quant trading, without digging in to the equations. It explains the subject in intuitive, economic terms." ?Steven Drobny, founder, Drobny Global Asset Management, and author, Inside the House of Money"Rishi Narang does an excellent job demystifying how quants work, in an accessible and fun read. This book should occupy a key spot on anyone's bookshelf who is interested in understanding how this ever increasing part of the investment universe actually operates."?Matthew S. Rothman, PhD, Global Head of Quantitative Equity Strategies Barclays Capital"Inside the Black Box provides a comprehensive and intuitive introduction to "quant" strategies. It succinctly explains the building blocks of such strategies and how they fit together, while conveying the myriad possibilities and design details it takes to build a successful model driven investment strategy." ?Asriel Levin, PhD, Managing Member, Menta Capital, LLC

    Since its introduction in 1978, this book has charted and followed this volatile world of financial markets. Charles Kindleberger's brilliant, panoramic history revealed how financial crises follow a nature-like rhythm: they peak and purge, swell and storm. Now this newly revised and expanded Fourth Edition probes the most recent "natural disasters" of the markets--from the difficulties in East Asia and the repercussions of the Mexican crisis to the 1992 Sterling crisis. His sharply drawn history confronts a host of key questions. Charles P. Kindleberger (Boston, MA) was the Ford Professor of Economics at MIT for thirty-three years. He is a financial historian and prolific writer who has published over twenty-four books.

    The book brings to life the people and ideas that forged modern finance and investing, from the formative days of Wall Street through the Great Depression and into the financial calamity of today. It's a tale that features professors who made and lost fortunes, battled fiercely over ideas, beat the house in blackjack, wrote bestselling books, and played major roles on the world stage. It's also a tale of Wall Street's evolution, the power of the market to generate wealth and wreak havoc, and free market capitalism's war with itself.The efficient market hypothesis--long part of academic folklore but codified in the 1960s at the University of Chicago--has evolved into a powerful myth. It has been the maker and loser of fortunes, the driver of trillions of dollars, the inspiration for index funds and vast new derivatives markets, and the guidepost for thousands of careers. The theory holds that the market is always right, and that the decisions of millions of rational investors, all acting on information to outsmart one another, always provide the best judge of a stock's value. That myth is crumbling.Celebrated journalist and columnist Fox introduces a new wave of economists and scholars who no longer teach that investors are rational or that the markets are always right. Many of them now agree with Yale professor Robert Shiller that the efficient markets theory "represents one of the most remarkable errors in the history of economic thought." Today the theory has given way to counterintuitive hypotheses about human behavior, psychological models of decision making, and the irrationality of the markets. Investors overreact, underreact, and make irrational decisions based on imperfect data. In his landmark treatment of the history of the world's markets, Fox uncovers the new ideas that may come to drive the market in the century ahead.

    More than two centuries after Euler's death, it is still regarded as a conceptual diamond of unsurpassed beauty. Called Euler's identity or God's equation, it includes just five numbers but represents an astonishing revelation of hidden connections. It ties together everything from basic arithmetic to compound interest, the circumference of a circle, trigonometry, calculus, and even infinity. In David Stipp's hands, Euler's identity formula becomes a contemplative stroll through the glories of mathematics. The result is an ode to this magical field.

    The original and bestselling 2000 edition of Irrational Exuberance evoked Alan Greenspan’s infamous 1996 use of that phrase to explain the alternately soaring and declining stock market. It predicted the collapse of the tech stock bubble through an analysis of the structural, cultural, and psychological factors behind levels of price growth not reflected in any other sector of the economy. In the second edition (2005), Shiller folded real estate into his analysis of market volatility, marshalling evidence that housing prices were dangerously inflated as well, a bubble that could soon burst, leading to a “string of bankruptcies” and a “worldwide recession.” That indeed came to pass, with consequences that the 2009 preface to this edition deals with. Irrational Exuberance is more than ever a cogent, chilling, and astonishingly far-seeing analytical work that no one with any money in any market anywhere can afford not to read–and heed.

    

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Designed for two-semester, beginning graduate courses in Mathematical Statistics, and for senior undergraduate Mathematics, Statistics, and Actuarial Science majors, this text retains its ongoing features and continues to provide students with background material.

    In a series of startling experiments, Canadian scientist Dr. John Coates identified a feedback loop between testosterone and success that dramatically lowers the fear of risk in men, especially young men; he has vividly dubbed the moment when traders transform into exuberant high flyers "the hour between dog and wolf." Similarly, intense failure leads to a rise in levels of cortisol, which dramatically lowers the appetite for risk. His book expands on his seminal research to offer lessons from the exploding new field studying the biology of risk. Coates's conclusions shed light on all types of high-pressure decision-making, from the sports field to the battlefield, and leaves us with a powerful recognition: to handle risk isn't a matter of mind over body, it's a matter of mind and body working together. We all have it in us to be transformed from dog to wolf; the only question is whether we can understand the causes and the consequences.

    He proposes his solution.

    Today Nash's beautiful math has become a universal language for research in the social sciences and has infiltrated the realms of evolutionary biology, neuroscience, and even quantum physics. John Nash won the 1994 Nobel Prize in economics for pioneering research published in the 1950s on a new branch of mathematics known as game theory. At the time of Nash's early work, game theory was briefly popular among some mathematicians and Cold War analysts. But it remained obscure until the 1970s when evolutionary biologists began applying it to their work. In the 1980s economists began to embrace game theory. Since then it has found an ever expanding repertoire of applications among a wide range of scientific disciplines. Today neuroscientists peer into game players' brains, anthropologists play games with people from primitive cultures, biologists use games to explain the evolution of human language, and mathematicians exploit games to better understand social networks. A common thread connecting much of this research is its relevance to the ancient quest for a science of human social behavior, or a Code of Nature, in the spirit of the fictional science of psychohistory described in the famous Foundation novels by the late Isaac Asimov. In A Beautiful Math, acclaimed science writer Tom Siegfried describes how game theory links the life sciences, social sciences, and physical sciences in a way that may bring Asimov's dream closer to reality.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.