Pole A Statistical Arbitrage Algorithmic Trading Insights And Techniques
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Statistical Arbitrage
While statistical arbitrage has faced some tough times?as markets experienced dramatic changes in dynamics beginning in 2000?new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Pole?s own research and experience running a statistical arbitrage hedge fund for eight years?in partnership with a group whose own history stretches back to the dawn of what was first called pairs trading?this unique guide provides detailed insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.
Enterprise Applications, Markets and Services in the Finance Industry
This book constitutes the revised selected papers from the 10th International Workshop on Enterprise Applications, Markets and Services in the Finance Industry, FinanceCom 2020, held in Helsinki, Finland, in August 2020. Due to the COVID-19 pandemic the conference took place virtually. The 6 full papers presented together with 1 extended abstract in this volume were carefully reviewed and selected from a total of 14 submissions to the workshop.They are grouped in topical sections named Machine Learning Applications in Trading and Financial Markets, Fraud Detection and Information Generation in Finance, and Alternative Trading and Investment Offerings by FinTechs.The workshop spans multiple disciplines, including analytical, technical, service, economic, sociological and behavioral sciences.
The Handbook of Equity Market Anomalies
Investment pioneer Len Zacks presents the latest academic research on how to beat the market using equity anomalies The Handbook of Equity Market Anomalies organizes and summarizes research carried out by hundreds of finance and accounting professors over the last twenty years to identify and measure equity market inefficiencies and provides self-directed individual investors with a framework for incorporating the results of this research into their own investment processes. Edited by Len Zacks, CEO of Zacks Investment Research, and written by leading professors who have performed groundbreaking research on specific anomalies, this book succinctly summarizes the most important anomalies that savvy investors have used for decades to beat the market. Some of the anomalies addressed include the accrual anomaly, net stock anomalies, fundamental anomalies, estimate revisions, changes in and levels of broker recommendations, earnings-per-share surprises, insider trading, price momentum and technical analysis, value and size anomalies, and several seasonal anomalies. This reliable resource also provides insights on how to best use the various anomalies in both market neutral and in long investor portfolios. A treasure trove of investment research and wisdom, the book will save you literally thousands of hours by distilling the essence of twenty years of academic research into eleven clear chapters and providing the framework and conviction to develop market-beating strategies. Strips the academic jargon from the research and highlights the actual returns generated by the anomalies, and documented in the academic literature Provides a theoretical framework within which to understand the concepts of risk adjusted returns and market inefficiencies Anomalies are selected by Len Zacks, a pioneer in the field of investing As the founder of Zacks Investment Research, Len Zacks pioneered the concept of the earnings-per-share surprise in 1982 and developed the Zacks Rank, one of the first anomaly-based stock selection tools. Today, his firm manages U.S. equities for individual and institutional investors and provides investment software and investment data to all types of investors. Now, with his new book, he shows you what it takes to build a quant process to outperform an index based on academically documented market inefficiencies and anomalies.