Momentum Mean Reversion And Social Media
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Momentum Mean Reversion And Social Media
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Author : Shreyash Agrawal
language : en
Publisher:
Release Date : 2019
Momentum Mean Reversion And Social Media written by Shreyash Agrawal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
We analyze the relation between stock market liquidity and real-time measures of sentiment obtained from the social-media platforms StockTwits and Twitter. Linear regression analysis shows that extreme sentiment corresponds to higher demand and lower supply of liquidity, with negative sentiment having a much larger effect on demand and supply than positive sentiment. An intraday event study shows that booms and panics end when bullish and bearish sentiment reach extreme levels, respectively. After extreme sentiment, prices become more mean-reverting and spreads narrow. To quantify the magnitudes of these effects, we conduct a historical simulation of a market-neutral mean-reversion strategy that uses social-media information to determine its portfolio allocations. Our results suggest that the demand and supply of liquidity are influenced by investor sentiment, and that market makers who can keep their transaction costs to a minimum are able to profit by using extreme bullish and bearish emotions in social media as a real-time barometer for the end of momentum and a return to mean reversion.
The Book Of Alternative Data
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Author : Alexander Denev
language : en
Publisher: John Wiley & Sons
Release Date : 2020-07-02
The Book Of Alternative Data written by Alexander Denev and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-02 with Business & Economics categories.
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
Python For Algorithmic Trading
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Author : Yves Hilpisch
language : en
Publisher: O'Reilly Media
Release Date : 2020-11-12
Python For Algorithmic Trading written by Yves Hilpisch and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms
Trading On Sentiment
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Author : Richard L. Peterson
language : en
Publisher: John Wiley & Sons
Release Date : 2016-03-21
Trading On Sentiment written by Richard L. Peterson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-21 with Business & Economics categories.
In his debut book on trading psychology, Inside the Investor’s Brain, Richard Peterson demonstrated how managing emotions helps top investors outperform. Now, in Trading on Sentiment, he takes you inside the science of crowd psychology and demonstrates that not only do price patterns exist, but the most predictable ones are rooted in our shared human nature. 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 social media data opened up an unprecedented world of insight into the elusive patterns of investor sentiment driving repeating market moves. Inside, you gain a privileged 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. Learn how traders are using sentiment analysis and statistical tools to extract value from media data in order to: Foresee important price moves using an understanding of how investors process news. Make more profitable investment decisions by identifying when prices are trending, when trends are turning, and when sharp market moves are likely to reverse. Use media sentiment to improve value and momentum investing returns. Avoid the pitfalls of unique price patterns found in commodities, currencies, and during speculative bubbles Trading on Sentiment deepens your understanding of markets and supplies you with the tools and techniques to beat global markets— whether they’re going up, down, or sideways.
Machine Learning Optimization And Data Science
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Author : Giuseppe Nicosia
language : en
Publisher: Springer Nature
Release Date : 2021-01-07
Machine Learning Optimization And Data Science written by Giuseppe Nicosia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-07 with Computers categories.
This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Mining Data For Financial Applications
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Author : Valerio Bitetta
language : en
Publisher: Springer Nature
Release Date : 2021-01-14
Mining Data For Financial Applications written by Valerio Bitetta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Computers categories.
This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.* The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain. *The workshop was held virtually due to the COVID-19 pandemic. “Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets” and “Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Asset Management Tools And Issues
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Author : Frank J Fabozzi
language : en
Publisher: World Scientific
Release Date : 2020-12-02
Asset Management Tools And Issues written by Frank J Fabozzi and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-02 with Business & Economics categories.
Long gone are the times when investors could make decisions based on intuition. Modern asset management draws on a wide-range of fields beyond financial theory: economics, financial accounting, econometrics/statistics, management science, operations research (optimization and Monte Carlo simulation), and more recently, data science (Big Data, machine learning, and artificial intelligence). The challenge in writing an institutional asset management book is that when tools from these different fields are applied in an investment strategy or an analytical framework for valuing securities, it is assumed that the reader is familiar with the fundamentals of these fields. Attempting to explain strategies and analytical concepts while also providing a primer on the tools from other fields is not the most effective way of describing the asset management process. Moreover, while an increasing number of investment models have been proposed in the asset management literature, there are challenges and issues in implementing these models. This book provides a description of the tools used in asset management as well as a more in-depth explanation of specialized topics and issues covered in the companion book, Fundamentals of Institutional Asset Management. The topics covered include the asset management business and its challenges, the basics of financial accounting, securitization technology, analytical tools (financial econometrics, Monte Carlo simulation, optimization models, and machine learning), alternative risk measures for asset allocation, securities finance, implementing quantitative research, quantitative equity strategies, transaction costs, multifactor models applied to equity and bond portfolio management, and backtesting methodologies. This pedagogic approach exposes the reader to the set of interdisciplinary tools that modern asset managers require in order to extract profits from data and processes.
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Author : 孙佰清
language : zh-CN
Publisher: BEIJING BOOK CO. INC.
Release Date : 2023-01-01
written by 孙佰清 and has been published by BEIJING BOOK CO. INC. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Business & Economics categories.
《另类数据：投资新动力》全书分为五章，全方位地介绍了另类数据在金融市场中的应用。本书和作者所著的另一本另类数据的作品《另类数据：理论与实践》互相补充、互为配套，为国内讲述另类数据及其应用的专著。 本书第一章和第二章主要讲述了各种类型的另类数据包括文本数据、消费相关数据、传感器数据、ESG数据、投资者关注数据、商业洞察数据、卫星图像数据、位置数据在股票量化投资和股票主观投资中的应用。第三章讨论了另类数据在利率和汇率投资中的应用。第四章和第五章分别介绍了另类数据在大宗商品和重要宏观经济变量预测中的应用。
Dual Momentum Investing An Innovative Strategy For Higher Returns With Lower Risk
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Author : Gary Antonacci
language : en
Publisher: McGraw Hill Professional
Release Date : 2014-11-21
Dual Momentum Investing An Innovative Strategy For Higher Returns With Lower Risk written by Gary Antonacci and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-21 with Business & Economics categories.
The investing strategy that famously generates higher returns with substantially reduced risk--presented by the investor who invented it "A treasure of well researched momentum-driven investing processes." Gregory L. Morris, Chief Technical Analyst and Chairman, Investment Committee of Stadion Money Management, LLC, and author of Investing with the Trend Dual Momentum Investing details the author’s own momentum investing method that combines U.S. stock, world stock, and aggregate bond indices--a formula proven to dramatically increase profits while lowering risk. Antonacci reveals how momentum investors could have achieved long-run returns nearly twice as high as the stock market over the past 40 years, while avoiding or minimizing bear market losses--and he provides the information and insight investors need to achieve such success going forward. His methodology is designed to pick up on major changes in relative strength and market trend. Gary Antonacci has over 30 years experience as an investment professional focusing on under exploited investment opportunities. In 1990, he founded Portfolio Management Consultants, which advises private and institutional investors on asset allocation, portfolio optimization, and advanced momentum strategies. He writes and runs the popular blog and website optimalmomentum.com. Antonacci earned his MBA at Harvard.
The Handbook Of News Analytics In Finance
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Author : Gautam Mitra
language : en
Publisher: John Wiley & Sons
Release Date : 2011-07-13
The Handbook Of News Analytics In Finance written by Gautam Mitra and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-13 with Business & Economics categories.
The Handbook of News Analytics in Finance is a landmarkpublication bringing together the latest models and applications ofNews Analytics for asset pricing, portfolio construction, tradingand risk control. The content of the Hand Book is organised to provide arapid yet comprehensive understanding of this topic. Chapter 1 setsout an overview of News Analytics (NA) with an explanation of thetechnology and applications. The rest of the chapters are presentedin four parts. Part 1 contains an explanation of methods and modelswhich are used to measure and quantify news sentiment. In Part 2the relationship between news events and discovery of abnormalreturns (the elusive alpha) is discussed in detail by the leadingresearchers and industry experts. The material in this part alsocovers potential application of NA to trading and fund management.Part 3 covers the use of quantified news for the purpose ofmonitoring, early diagnostics and risk control. Part 4 is entirelyindustry focused; it contains insights of experts from leadingtechnology (content) vendors. It also contains a discussion oftechnologies and finally a compact directory of content vendor andfinancial analytics companies in the marketplace of NA. Thebook draws equally upon the expertise of academics andpractitioners who have developed these models and is supported bytwo major content vendors - RavenPack and Thomson Reuters - leadingproviders of news analytics software and machine readablenews. The book will appeal to decision makers in the banking, finance andinsurance services industry. In particular: asset managers;quantitative fund managers; hedge fund managers; algorithmictraders; proprietary (program) trading desks; sell-side firms;brokerage houses; risk managers and research departments willbenefit from the unique insights into this new and pertinent areaof financial modelling.