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Trading on sentiment : the power of minds over markets /

Peterson's team developed text analysis engines to mine data - topics, beliefs, and emotions - from social media. Based on that data, they put together a market-neutral social media-based hedge fund that beat the S & P 500 by more than twenty-four percent--through the 2008 financial crisis....

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Peterson, Richard L., 1972- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, New Jersey : John Wiley & Sons, Inc., [2016]
Colección:Online access with DDA: Askews (Economics)
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Peterson, Richard L.,  |d 1972-  |e author. 
245 1 0 |a Trading on sentiment :  |b the power of minds over markets /  |c Richard L. Peterson. 
264 1 |a Hoboken, New Jersey :  |b John Wiley & Sons, Inc.,  |c [2016] 
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505 0 |a Title Page; Copyright; Table of Contents; Dedication; About the Author; Preface; Mathematical Mayhem; Framing the Issue; Trading on Sentiment; The Book; Notes; Acknowledgments; Part One: Foundations; Chapter 1: Perception and the Brain; A Long Estrangement; The Beauty Contest; What Moves Traders?; Chained to the Mast; The Brain: Structure and Function; Emotion versus Reason; In Summary; Notes; Chapter 2: Mind and Emotion; Crowds Moving Markets; Emotional Priming; Feelings and Finance; How Emotions Move Traders; Arousal, Stress, and Urgency; Anger, Fear, and Gloom; Information Impact. 
505 8 |a In SummaryNotes; Chapter 3: Information Processing; Media and the Flash Crash; Diversity Breakdowns; Price Patterns; Information Characteristics; A Scarce Resource; What's in a Name?; "All That Glitters"; Profiting From Social Inattention; In Summary; Notes; Chapter 4: Sentimental Markets; Reflexivity; Sentiment; Understanding Media; The Thomson Reuters MarketPsych Indices; In Summary; Notes; Chapter 5: Finding Signal in the Noise; Can Investment Research Be Believed?; Data Biases; Nonlinear Characteristics; Exploring Sentiment Data; Statistical Models; Cross-Sectional Models; Decision Trees. 
505 8 |a Moving Average CrossoversCan Sentiment Be Trusted?; In Summary; Notes; Part Two: Short-term Patterns; Chapter 6: Information Impact; The Need for Speed; Bankruptcy Deja Vu; Faster than a Speeding Specialist; A Rehash of the #HashCrash; Breaking News; Leaking News; News Momentum; Gross National Happiness; Social Sentiment; The Human Advantage; In Summary; Notes; Chapter 7: Daily Reversals; Social Media and Insider Trading; Daily Reversals Research; Global Price Forecasts; In Summary; Notes; Chapter 8: Weekly Deceptions; Weekly Reversals; Emotions in Markets; Tricky Sentiments. 
505 8 |a The Lessons of MagicIn Summary; Notes; Chapter 9: The Only Thing to Fear; Estimates of Fear; To Catch a Falling Knife; Good News for People Who Love Bad News; Panics and Bounces; The Fear Factor in Markets; In Summary; Notes; Chapter 10: Buy on the Rumor; Price Forecasts; Sweet Anticipation; Earnings and IPOs; The Neuroscience of Disappointed Expectations; Tricks of the Stock Promoters' Trade; In Summary; Notes; Part Three: Long-term Patterns; Chapter 11: Trends and Price Momentum; What Causes Trends?; Investor Underreaction; Timing Trends with Moving Averages; Augmented Momentum. 
505 8 |a Going with the FlowIn Summary; Notes; Chapter 12: Value Investing; The Manic-Depressive Mr. Market; Value Investing; Selling to Optimists; Value Traps and Catalysts; In Summary; Notes; Chapter 13: Anger and Mistrust; Anger under the Microscope; The Value of Anger; Trust; Who Trusts Bankers?; The Trust Factor; Trust and Forgiveness; In Summary; Notes; Chapter 14: The Psychology of Leadership; Blaming Management; The Emotional Value of Human Sacrifice; Superstar CEOs; Buy Mistrusted Leadership; Buy Unstable Governments; Using Text Analytics to Improve Executive Communication; Conclusion. 
520 |a Peterson's team developed text analysis engines to mine data - topics, beliefs, and emotions - from social media. Based on that data, they put together a market-neutral social media-based hedge fund that beat the S & P 500 by more than twenty-four percent--through the 2008 financial crisis. In this groundbreaking guide, he shows you how they did it and why it worked. Applying algorithms to soƯcial media data opened up an unprecedented world of insight into the elusive patterns of investor sentiment driving repeating market moves. Inside, you gain a priviƯleged look at the media content that moves investors, along with time-tested techniques to make the smart moves--even when it doesn't feel right. This book digs underneath technicals and fundamentals to explain the primary mover of market prices - the global information flow and how investors react to it. It provides the expert guidance you need to develop a competitive edge, manage risk, and overcome our sometimes-flawed human nature. 
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