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Author: David Aronson
Publisher: John Wiley & Sons
ISBN: 1118160584
Category : Business & Economics
Languages : en
Pages : 572
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Book Description
Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Author: David Aronson
Publisher: John Wiley & Sons
ISBN: 1118160584
Category : Business & Economics
Languages : en
Pages : 572
Get Book Here
Book Description
Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.
Author: Julie R. Dahlquist
Publisher: FT Press
ISBN: 0132900432
Category : Business & Economics
Languages : en
Pages : 252
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Book Description
Gaps have attracted the attention of market technicians from the earliest days of charting. They're not merely conspicuous: they represent price jumps that could signal profitable trading opportunities. Until now, however, "folklore" about gap trading has been common, and tested, research-based knowledge virtually nonexistent. In Technical Analysis of Gaps, renowned technical analysis researchers Julie Dahlquist and Richard Bauer change all that. Drawing on 60 years of comprehensive data, they demonstrate how to sort "strategic" gaps from trivial ones, and successfully trade on gaps identified as significant. Building on work that recently earned them the Market Technicians Association's 2011 Charles H. Dow Award for creativity and innovation in technical analysis, Dahlquist and Bauer offer specific gap-related trading tips for stocks, futures, and options. They consider a wide variety of market conditions, including gap size, volume and previous price movement, illuminating their findings with easy-to-understand diagrams. Coverage includes: understanding what gaps are and how they arise; recognizing windows on candlestick charts; identifying gaps with superior profit potential; combining gaps with other technical techniques for a more complete and effective analysis; and putting it all together with real trading strategies. For stock, commodity, and currency traders in the U.S. and worldwide, and for active individual investors seeking new ways to maximize returns.
Author: James Altucher
Publisher: John Wiley & Sons
ISBN: 1118045785
Category : Business & Economics
Languages : en
Pages : 245
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Book Description
Learn the successful strategies behind hedge fund investing Hedge funds and hedge fund trading strategies have long been popular in the financial community because of their flexibility, aggressiveness, and creativity. Trade Like a Hedge Fund capitalizes on this phenomenon and builds on it by bringing fresh and practical ideas to the trading table. This book shares 20 uncorrelated trading strategies and techniques that will enable readers to trade and invest like never before. With detailed examples and up-to-the-minute trading advice, Trade Like a Hedge Fund is a unique book that will help readers increase the value of their portfolios, while decreasing risk. James Altucher (New York, NY) is a partner at Subway Capital, a hedge fund focused on special arbitrage situations, and short-term statistically based strategies. Previously, he was a partner with technology venture capital firm 212 Ventures and was CEO and founder of Vaultus, a wireless and software company.
Author: Ray Pawson
Publisher: SAGE
ISBN: 1446227839
Category : Social Science
Languages : en
Pages : 415
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Book Description
In this important new book, Ray Pawson examines the recent spread of evidence-based policy making across the Western world. Few major public initiatives are mounted these days in the absence of a sustained attempt to evaluate them. Programmes are tried, tried and tried again and researched, researched and researched again. And yet it is often difficult to know which interventions, and which inquiries, will withstand the test of time. The evident solution, going by the name of evidence-based policy, is to take the longer view. Rather than relying on one-off studies, it is wiser to look to the ′weight of evidence′. Accordingly, it is now widely agreed the most useful data to support policy decisions will be culled from systematic reviews of all the existing research in particular policy domains. This is the consensual starting point for Ray Pawson′s latest foray into the world of evaluative research. But this is social science after all and harmony prevails only in the first chapter. Thereafter, Pawson presents a devastating critique of the dominant approach to systematic review - namely the ′meta-analytic′ approach as sponsored by the Cochrane and Campbell collaborations. In its place is commended an approach that he terms ′realist synthesis′. On this vision, the real purpose of systematic review is better to understand programme theory, so that policies can be properly targeted and developed to counter an ever-changing landscape of social problems. The book will be essential reading for all those who loved (or loathed) the arguments developed in Realistic Evaluation (Sage, 1997). It offers a complete blueprint for research synthesis, supported by detailed illustrations and worked examples from across the policy waterfront. It will be of especial interest to policy-makers, practitioners, researchers and students working in health, education, employment, social care, criminal justice, regeneration and welfare.
Author: Marcos Lopez de Prado
Publisher: John Wiley & Sons
ISBN: 1119482119
Category : Business & Economics
Languages : en
Pages : 395
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Book Description
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 Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Author: David Aronson
Publisher: Createspace Independent Publishing Platform
ISBN: 9781489507716
Category : Algorithmus
Languages : en
Pages : 0
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Book Description
This book serves two purposes. First, it teaches the importance of using sophisticated yet accessible statistical methods to evaluate a trading system before it is put to real-world use. In order to accommodate readers having limited mathematical background, these techniques are illustrated with step-by-step examples using actual market data, and all examples are explained in plain language. Second, this book shows how the free program TSSB (Trading System Synthesis & Boosting) can be used to develop and test trading systems. The machine learning and statistical algorithms available in TSSB go far beyond those available in other off-the-shelf development software. Intelligent use of these state-of-the-art techniques greatly improves the likelihood of obtaining a trading system whose impressive backtest results continue when the system is put to use in a trading account. Among other things, this book will teach the reader how to: Estimate future performance with rigorous algorithms Evaluate the influence of good luck in backtests Detect overfitting before deploying your system Estimate performance bias due to model fitting and selection of seemingly superior systems Use state-of-the-art ensembles of models to form consensus trade decisions Build optimal portfolios of trading systems and rigorously test their expected performance Search thousands of markets to find subsets that are especially predictable Create trading systems that specialize in specific market regimes such as trending/flat or high/low volatility More information on the TSSB program can be found at TSSBsoftware dot com.
Author: Emilio Tomasini
Publisher: Harriman House Pub
ISBN: 9781905641796
Category : Business & Economics
Languages : en
Pages : 240
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Book Description
"Trading Systems" offers an insight into what a trader should know and do in order to achieve success on the markets.
Author: Jeffrey A. Hirsch
Publisher: John Wiley & Sons
ISBN: 0470225777
Category : Business & Economics
Languages : en
Pages : 194
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Book Description
The Stock Trader's Almanac is a practical investment tool that has helped traders and investors forecast market trends with accuracy and confidence for over 40 years. Organized in an easy-to-access calendar format, the 2008 Edition contains historical price information on the stock market, provides monthly and daily reminders, and alerts users to seasonal opportunities and dangers. For its wealth of information and authority of its sources, the Stock Trader's Almanac stands alone as the guide to intelligent investing. "Jeff Hirsch is following in the great tradition of his father, Yale Hirsch, with this nonpareil almanac of Wall Street data. It's a treasure for investors who want to remember the past as they plan for the future." -Louis Rukeyser, late founding host, Wall $treet Week "Information is key to successful investing and investors will find the Almanac a chock-a-block source of need-to-know stuff." -Steve Forbes, President, CEO, and Editor in Chief, Forbes "I have every issue since 1976 in my bookcase. The Stock Trader's Almanac is an invaluable resource." -Marty Zweig, author, Martin Zweig's Winning on Wall Street "The Stock Trader's Almanac should be on every investor's desk. It's an invaluable source of investment advice, trading patterns, and Wall Street lore. It's also fun to read. I refer to it frequently throughout the year." -Myron Kandel, founding financial editor, CNN
Author: Gordon Scott
Publisher: CFA Institute Research Foundation
ISBN: 1944960120
Category : Business & Economics
Languages : en
Pages : 45
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Book Description
Author: Michael Zhang
Publisher: Taylor & Francis
ISBN: 1040145884
Category : Business & Economics
Languages : en
Pages : 311
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Book Description
Bridging the gap between theoretical asset pricing and industry practices in factors and factor investing, Zhang et al. provides a comprehensive treatment of factors, along with industry insights on practical factor development. Chapters cover a wide array of topics, including the foundations of quantamentals, the intricacies of market beta, the significance of statistical moments, the principles of technical analysis, and the impact of market microstructure and liquidity on trading. Furthermore, it delves into the complexities of tail risk and behavioral finance, revealing how psychological factors affect market dynamics. The discussion extends to the sophisticated use of option trading data for predictive insights and the critical differentiation between outcome uncertainty and distribution uncertainty in financial decision-making. A standout feature of the book is its examination of machine learning's role in factor investing, detailing how it transforms data preprocessing, factor discovery, and model construction. Overall, this book provides a holistic view of contemporary financial markets, highlighting the challenges and opportunities in harnessing alternative data and machine learning to develop robust investment strategies. This book would appeal to investment management professionals and trainees. It will also be of use to graduate and upper undergraduate students in quantitative finance, factor investing, asset management and/or trading.
