These themes include mathematical reasoning, combinatorial analysis, discrete structures, algorithmic thinking, and enhanced problem-solving skills through modeling. Its intent is to demonstrate the relevance and practicality of discrete mathematics to all students. The Fifth Edition includes a more thorough and linear presentation of logic, proof types and proof writing, and mathematical reasoning. This enhanced coverage will provide students with a solid understanding of the material as it relates to their immediate field of study and other relevant subjects. The inclusion of applications and examples to key topics has been significantly addressed to add clarity to every subject. True to the Fourth Edition, the text-specific web site supplements the subject matter in meaningful ways, offering additional material for students and instructors. Discrete math is an active subject with new discoveries made every year. The continual growth and updates to the web site reflect the active nature of the topics being discussed. The book is appropriate for a one- or two-term introductory discrete mathematics course to be taken by students in a wide variety of majors, including computer science, mathematics, and engineering. College Algebra is the only explicit prerequisite.

    The interviewers use the same questions year-after-year and here they are---with solutions! These questions come from all types of interviews (corporate finance, sales and trading, quant research, etc), but they are especially likely in quantitative capital markets job interviews. The questions come from all levels of interviews (undergrad, MBA, PhD), but they are especially likely if you have, or almost have, an MS or MBA. The latest edition includes over 120 non-quantitative actual interview questions, and a new section on interview technique---based partly on Dr. Crack's experiences interviewing candidates for the world's largest institutional asset manager. Dr. Crack has a PhD from MIT. He has won many teaching awards and has publications in the top academic, practitioner, and teaching journals in finance. He has degrees in Mathematics/Statistics, Finance, and Financial Economics and a diploma in Accounting/Finance. Dr. Crack taught at the university level for 20 years including four years as a front line teaching assistant for MBA students at MIT. He recently headed a quantitative active equity research team at the world's largest institutional money manager.

    Risk measurement and quantitative tools are critical aids for supporting risk management, but quantitative tools alone are no substitute for judgment, wisdom, and knowledge. Managers within a financial organization must be, before anything else, risk managers in the true sense of managing the risks that the firm faces.

    In A Mathematician Plays the Stock Market , best-selling author John Allen Paulos employs his trademark stories, vignettes, paradoxes, and puzzles to address every thinking reader's curiosity about the market -- Is it efficient? Is it random? Is there anything to technical analysis, fundamental analysis, and other supposedly time-tested methods of picking stocks? How can one quantify risk? What are the most common scams? Are there any approaches to investing that truly outperform the major indexes? But Paulos's tour through the irrational exuberance of market mathematics doesn't end there. An unrequited (and financially disastrous) love affair with WorldCom leads Paulos to question some cherished ideas of personal finance. He explains why "data mining" is a self-fulfilling belief, why "momentum investing" is nothing more than herd behavior with a lot of mathematical jargon added, why the ever-popular Elliot Wave Theory cannot be correct, and why you should take Warren Buffet's "fundamental analysis" with a grain of salt. Like Burton Malkiel's A Random Walk Down Wall Street , this clever and illuminating book is for anyone, investor or not, who follows the markets -- or knows someone who does.

    

    You're trading against other traders who care about only one thing: taking your money. That's the #1 hard reality of trading - and most traders either don't know it, or don't act as if they do. In this book, top trader and hedge fund manager Quint Tatro shows how to win consistently in the "zero sum" game of trading, where there's a loser for every winner. You'll learn how to reflect your trading competition in every facet of trading and investing: choosing companies to invest in, knowing when to jump in and out of the market, and mastering the psychology and gamesmanship of trading. Coverage includes: Understanding the "other side of the trade": the thousands of pros you're trading against. Finding a technical edge with technical analysis you can exploit over and over again. Understanding sentiment and overcoming the human emotions and biases that cost you dearly. Utilizing the most essential strategies of fundamental analysis. Playing positions and probabilities, not P+Ls. Recognizing and capturing huge opportunities in down markets.

    He has the bankwide oversight on all quantitative research and the development of new products and applications supporting the trading and structuring businesses. Dan Galai, Ph.D., is the Abe Gray Professor of Banking and Finance at The Hebrew University. He is a co-CEO of Sigma PCM, an investment banking firm. Galai has consulted for the Chicago Board Options Exchange and the American Stock Exchange, and for many major banks and corporations. Robert M. Mark Ph.D., is the Chief Executive Officer of Black Diamond, which provides corporate governance, risk management consulting, and transaction services. He is the chairperson of The Professional Risk Managers' International Association's (PRMIA) Blue Ribbon Panel. He was awarded the Financial Risk Manager of the Year by the Global Association of Risk Professionals (GARP).

    What began more than sixty years ago as a modest proposal that a mathematician and an economist write a short paper together blossomed, in 1944, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences.This sixtieth anniversary edition includes not only the original text but also an introduction by Harold Kuhn, an afterword by Ariel Rubinstein, and reviews and articles on the book that appeared at the time of its original publication in the New York Times, tthe American Economic Review, and a variety of other publications. Together, these writings provide readers a matchless opportunity to more fully appreciate a work whose influence will yet resound for generations to come.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    Clear, comprehensive coverage of utility theory, 2-person zero-sum games, 2-person non-zero-sum games, n-person games, individual and group decision-making, more. Bibliography.

    Details are given of actual investments made by the authors, one of whom more then doubled $100,000 in five years.

    "Using Econometrics: A Practical Guide "provides readers with a practical introduction that combines single-equation linear regression analysis with real-world examples and exercises. This text also avoids complex matrix algebra and calculus, making it an ideal text for beginners. New problem sets and added support make "Using Econometrics" modern and easier to use.

    This book starts from the ground up to provide detailed explanations of both these techniques: - An introduction to the different types of execution is followed by a review of market microstructure theory. Throughout the book examples from empirical studies bridge the gap between the theory and practice of trading. - Orders are the fundamental building blocks for any strategy. Market, limit, stop, hidden, iceberg, peg, routed and immediate-or-cancel orders are all described with illustrated examples. - Trading algorithms are explained and compared using charts to show potential trading patterns. TWAP, VWAP, Percent of Volume, Minimal Impact, Implementation Shortfall, Adaptive Shortfall, Market On Close and Pairs trading algorithms are all covered, together with common variations. - Transaction costs can have a significant effect on investment returns. An in-depth example shows how these may be broken down into constituents such as market impact, timing risk, spread and opportunity cost and other fees. - Coverage includes all the major asset classes, from equities to fixed income, foreign exchange and derivatives. Detailed overviews for each of the world's major markets are provided in the appendices. - Order placement and execution tactics are covered in more detail, as well as potential enhancements (such as short-term forecasts), for those interested in the specifics of implementing these strategies. - Cutting edge applications such as portfolio and multi-asset trading are also considered, as are handling news and data mining/artificial intelligence.

    This work is designed to help students understand the field of banking from the perspective of both a bank customer as well as a bank manager. It provides a description of the banking industry.