Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.

    By revealing how top investors and traders think and act Steven Sears shows the stock market to be an undulating ocean of money, with seasoned investors reading the waves others cannot.Teaching readers to think about the market in radically different ways, "The Indomitable Investor" shows how to improve returns--and, just as importantly, avoid losses--with disciplines deployed by people who almost always do exactly the opposite of what Wall Street says to do.Laying bare great fallacies, the book explains that non-professional investors wrongly think the stock market is a place to make money, which is what Wall Street wants them to try to do. "The Indomitable Investor" says otherwise and shows how Wall Street's best investors have a completely different focus.Explains the critical ideas and insights of top traders and investors in language anyone can understand and implementPacked with material rarely shared off Wall Street that is used every day by professional investorsIntroduces the 17 most important words on Wall StreetTeaches critical skills, including: How to increase returns by focusing on risk, not potential profits; how to use the stock market's historical patterns to optimize investment decisions; understanding key relationships between stocks and the economy that predict what will happen to stocks and the broader market; how to increase mutual fund returns with an easy adjustment that redirects the bulk of profits to you--not mutual fund companies, and how to analyze information like seasoned investors to move beyond "statement of the obvious" news reports that turn ordinary investors into Dumb MoneyAccessible to readers of all backgrounds, including those with a limited understanding of investing, "The Indomitable Investor" will change how investors view the stock market, Wall Street, and themselves.

    The metric gives unparalleled insight into which teams and players are performing at the highest level.Professional gamblers have used Expected Goals to make millions through football betting. Club scouts have used Expected Goals to identify hidden gems in the transfer market. And the media have recently started using Expected Goals to offer more profound insight in their broadcasts.Despite this, most ordinary fans still don’t understand what the Expected Goals method is – or appreciate the significant impact that it is set to have on the sport in coming years.Expected Goals (otherwise known as xG) was originally conjured up by a small corner of the online football analytics community. It didn’t take long for professional gamblers to begin using xG to predict match outcomes. These bettors utilised the Expected Goals method to turn over hundreds of millions of pounds from the bookmakers.Before long, football clubs had caught on to the ground-breaking insight given by xG. Brentford FC were leaders in this field, managing to assemble a Play-Off-reaching squad on a shoe-string budget. In the last five years, the small West London side have turned over more than £100m in transfer profit from their use of the Expected Goals method in player recruitment.More recently, the Expected Goals method has been adopted by the media as a form of insight. Fans are finally catching on to the pioneering means of football analysis. Soon enough, anyone who doesn’t understand the Expected Goals philosophy will be left behind.“This book will make you watch football differently” – Tobias Pedersen“Possibly the most ground-breaking football book ever written” – Football Impact“A brilliant account of the history and future of Expected Goals” – StatShot

    Drawing on his experience as a professional trader, author Sheldon Natenberg examines both the theory and reality of option trading. He presents the foundations of option theory explaining how this theory can be used to identify and exploit trading opportunities. "Option Volatility & Pricing" teaches you to use a wide variety of trading strategies and shows you how to select the strategy that best fits your view of market conditions and individual risk tolerance.New sections include: Expanded coverage of stock option Strategies for stock index futures and options A broader, more in-depth discussion volatility Analysis of volatility skews Intermarket spreading with options

    This book foregoes the sensational, headline-grabbing stories about the few billionaire hedge fund managers to reach the top of the field. Instead, it focuses on the much more common travails of start-ups and small investment firms. The successes and failures of a talented group of competitive managers—all highly educated and well trained—show what it takes for managers and allocators to succeed. These accounts include lessons on funding, team development, strategy, performance, and allocation. The hedge fund industry is concentrated in the largest funds, and the big funds are getting bigger. In time, some of these funds will not survive their founders and large sums will get reallocated to a broader selection of different managers. This practical guide outlines the allocation process for fledgling funds, and demonstrates how allocators can avoid pitfalls in their investments. So You Want to Start a Hedge Fund also shows how to: Develop a sound strategy and raise the money you need Gain a real-world perspective about how allocators think and act Structure your team and investment process for success Recognize the patterns of successful start-ups The industry is approaching a significant crossroads. Aggregate growth is slowing and competition is shifting away from industry-wide growth, at the expense of traditional asset classes, to market share capture within the industry. So You Want to Start a Hedge Fund provides guidance for the little funds—the potential future leaders of the industry.

    

    For the calculus-based General Physics course primarily taken by engineers and scientists.

    The authors take time to explain statistical procedures so that you can go beyond memorizing formulas and gain a conceptual understanding of statistics. The authors also take care to show you how having an understanding of statistical procedures will help you comprehend published findings and will lead you to become a savvy consumer of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support your learning.

    Switching from thin tailed to fat tailed distributions requires more than "changing the color of the dress." Traditional asymptotics deal mainly with either n=1 or n=∞, and the real world is in between, under the "laws of the medium numbers"-which vary widely across specific distributions. Both the law of large numbers and the generalized central limit mechanisms operate in highly idiosyncratic ways outside the standard Gaussian or Levy-Stable basins of convergence. A few examples: - The sample mean is rarely in line with the population mean, with effect on "na�ve empiricism," but can be sometimes be estimated via parametric methods. - The "empirical distribution" is rarely empirical. - Parameter uncertainty has compounding effects on statistical metrics. - Dimension reduction (principal components) fails. - Inequality estimators (Gini or quantile contributions) are not additive and produce wrong results. - Many "biases" found in psychology become entirely rational under more sophisticated probability distributions. - Most of the failures of financial economics, econometrics, and behavioral economics can be attributed to using the wrong distributions. This book, the first volume of the Technical Incerto, weaves a narrative around published journal articles.

    Now in one quick reference, Kotler provides answers to some of the toughest ones, revealing his philosophies on marketing topics including strategy, product, price, place, promotion, marketing research and planning, direct marketing, small business marketing, and more. According to Kotler offers his insightful, thought-provoking answers to questions such as: - What effects are dynamics like globalization, hyper competition, and the Internet having on marketing? - What skills do marketing managers need to be successful? - What marketing strategies make sense during a recession? - What are holistic marketing and reverse marketing? - How can a local brand be turned into a global brand? - What signs might indicate a need for a change in strategy? - What does the marketing department of the future look like? Kotler expounds on these and many other questions in this fascinating, landmark book no marketing professional should be without.

    From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.

    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.

    The Fourth Edition of volumes 1 and 2 is concerned with mechanics and E&M/Optics. New features include: expanded coverage of classic physics topics, substantial increases in the number of in-text examples which reinforce text exposition, the latest pedagogical and technical advances in the field, numerical analysis, computer-generated graphics, computer projects and much more.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    He explains how bankers worldwide created a secret trillion-dollar machine that delivered cheap mortgages to the masses and riches beyond dreams to the financial innovators.Fundamental to this saga is how “the people who hated to lose” were persuaded to accept risk by “the people who loved to win.” Why did people come to trust and respect arcane financial tools? Who were the bankers competing to assemble the basic components into increasingly intricate machines? How did this process achieve its own unstoppable momentum—ending in collapse, bailouts, and a public outcry against the giants of finance?Provocative and intriguing, The Devil’s Derivatives sheds much-needed light on the forces that fueled the most brutal economic downturn since the Great Depression.