Quantitative Portfolio Management


The Art and Science of Statistical Arbitrage

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ISBN: 9781119821328 Category:

<p><b>Discover foundational and advanced techniques in quantitative equity trading from a&nbsp;veteran&nbsp;insider&nbsp;</b></p> <p>In&nbsp;<i>Quantitative Portfolio Management:&nbsp;The Art and Science of Statistical Arbitrage</i>, distinguished physicist-turned-quant&nbsp;Dr. Michael&nbsp;Isichenko&nbsp;delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn&nbsp;patterns of&nbsp;asset returns from historical data,&nbsp;generate&nbsp;and combine multiple forecasts, manage risk, build a&nbsp;stock portfolio&nbsp;optimized for risk and trading costs, and execute trades.&nbsp;</p> <p>In this important book,&nbsp;you&rsquo;ll&nbsp;discover:&nbsp;</p> <ul> <li>Machine learning methods&nbsp;of forecasting stock returns in efficient financial markets&nbsp;</li> <li>How to combine&nbsp;multiple&nbsp;forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods</li> <li>Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as &ldquo;benign overfitting&rdquo; in machine learning&nbsp;</li> <li>The theoretical and&nbsp;practical&nbsp;aspects of portfolio construction, including multi-factor risk models,&nbsp;multi-period&nbsp;trading costs, and optimal leverage&nbsp;</li> </ul> <p>Perfect for investment professionals, like quantitative traders and portfolio managers,&nbsp;<i>Quantitative Portfolio Management</i>&nbsp;will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data&nbsp;science, machine learning, and optimization&nbsp;to the stock market.&nbsp;</p> <br />


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