First implemented by financial advisors at Merrill Lynch--under the leadership of author Rob Knapp--it has grown increasingly popular within the financial services industry. The Supernova Advisor skillfully outlines this proven model and reveals how it can be used to create an exceptional experience for your clients, while significantly growing your business.

    It emphasizes forms suitable for students and researchers whose interest lies in solving equations rather than in general theory. Solutions to odd-numbered problems appear at the end. 1957 edition.

    The most talented investors in the world play this game, and if you try to compete against them, it’s like playing against the house in a casino. Luck can be your friend for a while, but eventually the house wins. But what if you could lay down your bets with the house instead of against it? In the stock market, the most successful large investors—particularly hedge fund managers—represent the house. These managers like to refer to their top investments as their “best ideas.” In this book, you will learn how to farm the best ideas of the world’s top hedge fund managers. You will learn who they are, how to track their funds and stock picks, and how to use that information to help guide your own portfolio. In essence, you will learn how to play more like the house in a casino and less like the sucker relying on dumb luck.

    There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again for the classroom or for self-study.Principles of Statistics was created primarily for the student of natural sciences, the social scientist, the undergraduate mathematics student, or anyone familiar with the basics of mathematical language. It assumes no previous knowledge of statistics or probability; nor is extensive mathematical knowledge necessary beyond a familiarity with the fundamentals of differential and integral calculus. (The calculus is used primarily for ease of notation; skill in the techniques of integration is not necessary in order to understand the text.)Professor Bulmer devotes the first chapters to a concise, admirably clear description of basic terminology and fundamental statistical theory: abstract concepts of probability and their applications in dice games, Mendelian heredity, etc.; definitions and examples of discrete and continuous random variables; multivariate distributions and the descriptive tools used to delineate them; expected values; etc. The book then moves quickly to more advanced levels, as Professor Bulmer describes important distributions (binomial, Poisson, exponential, normal, etc.), tests of significance, statistical inference, point estimation, regression, and correlation. Dozens of exercises and problems appear at the end of various chapters, with answers provided at the back of the book. Also included are a number of statistical tables and selected references.

    His aim is to present calculus as the first real encounter with mathematics: it is the place to learn how logical reasoning combined with fundamental concepts can be developed into a rigorous mathematical theory rather than a bunch of tools and techniques learned by rote. Since analysis is a subject students traditionally find difficult to grasp, Spivak provides leisurely explanations, a profusion of examples, a wide range of exercises and plenty of illustrations in an easy-going approach that enlightens difficult concepts and rewards effort. Calculus will continue to be regarded as a modern classic, ideal for honours students and mathematics majors, who seek an alternative to doorstop textbooks on calculus, and the more formidable introductions to real analysis.

     Generate your owns calls. Trend following high profit low risk entry and exit strategy The book is exclusively dedicated towards intraday trading. It is said that you cannot make money in intraday trading, but with right discipline and right strategy anybody can make money in intraday very easily with very less efforts. Purpose of the book is to provide the readers with right resources, right knowledge and right working and backtested strategy. The book is equally beneficial for beginners as well as professional traders. OVERVIEW Introduction Chapter I – Probability Chapter II – Indicators and Oscillators Chapter III – Opening Range Breakout (ORB) Chapter IV – How to scan stocks? Chapter V – How to narrow down the selected stocks Chapter VI – Intraday Trading Strategy Chapter VII – Risk Management Chapter VIII – Trading psychology Summary Download your very own copy now...

    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.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    KEY TOPICS: This classic book enables readers to make connections between classical and modern physics - an indispensable part of a physicist's education. In this new edition, Beams Medal winner Charles Poole and John Safko have updated the book to include the latest topics, applications, and notation, to reflect today's physics curriculum. They introduce readers to the increasingly important role that nonlinearities play in contemporary applications of classical mechanics. New numerical exercises help readers to develop skills in how to use computer techniques to solve problems in physics. Mathematical techniques are presented in detail so that the book remains fully accessible to readers who have not had an intermediate course in classical mechanics. MARKET: For college instructors and students.

    This second edition is appropriate as a supplementary (companion) text for any college-level course covering digital signal processing.

    He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the "prediction paradox": The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good-or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary-and dangerous-science.Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.

    This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrated by graphics, formulas, and plenty of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis. Organized into four distinct sections, Statistics in a Nutshell offers you:Introductory material: Different ways to think about statistics Basic concepts of measurement and probability theoryData management for statistical analysis Research design and experimental design How to critique statistics presented by others Basic inferential statistics: Basic concepts of inferential statistics The concept of correlation, when it is and is not an appropriate measure of association Dichotomous and categorical data The distinction between parametric and nonparametric statistics Advanced inferential techniques: The General Linear Model Analysis of Variance (ANOVA) and MANOVA Multiple linear regression Specialized techniques: Business and quality improvement statistics Medical and public health statistics Educational and psychological statistics Unlike many introductory books on the subject, Statistics in a Nutshell doesn't omit important material in an effort to dumb it down. And this book is far more practical than most college texts, which tend to over-emphasize calculation without teaching you when and how to apply different statistical tests. With Statistics in a Nutshell, you learn how to perform most common statistical analyses, and understand statistical techniques presented in research articles. If you need to know how to use a wide range of statistical techniques without getting in over your head, this is the book you want.

    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

     Because these bonds serve as the foundation of our current financial system, when they are in a bubble, it means that all risk assets (truly EVERYTHING), are in a bubble, hence our title, The Everything Bubble. In this sense, the Everything Bubble represents the proverbial end game for central bank policy: the final speculative frenzy induced by Federal Reserve overreach. The Everything Bubble book is the result of over a decade of research and analysis of the financial markets and economy by noted investment analyst, Graham Summers, MBA. As such, this book is intended for anyone who wants to understand how the US financial system truly operates as well as those interested in the Federal Reserve’s future policy responses when the Everything Bubble bursts. To that end, The Everything Bubble is divided into two sections: How We Got Here and What’s to Come. Combined, these sections represent a blueprint for all things finance and money-related in the United States. This knowledge is now yours.