Quantitative Portfolio Management. Michael Isichenko
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Название: Quantitative Portfolio Management

Автор: Michael Isichenko

Издательство: John Wiley & Sons Limited

Жанр: Ценные бумаги, инвестиции

Серия:

isbn: 9781119821212

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СКАЧАТЬ reviewed with an emphasis on regularization methods, bias-variance and other tradeoffs, generalization error, the curse of dimensionality, and traps of overfitting. ML involves a wealth of parametric, nonparametric, deep, online, and latent structure algorithms, whose success is data-dependent according to the “No free lunch” theorem. Meta-learning methods include hyperparameter optimization, boosting, and other ensemble methods. An important context of financial ML is competition-based market efficiency imposing limits on the acceptable complexity and expected performance of predictive models. Some topics of active research such as “benign overfitting” in interpolating deep neural nets and other ML algorithms are also covered. Several approaches of combining multiple forecasts are discussed using secondary ML, dimensionality reduction, and other methods, while highlighting correlation-based limits on alpha diversification. Multi-factor risk models and trading costs are reviewed including both theoretical and empirical aspects relevant to portfolio construction. Effects of price impact on stock market macro elasticity are also discussed. A unified framework of multi-period portfolio optimization is presented with several special closed-form solutions with impact and slippage costs and approximations for efficient algorithmic approaches. Optimal portfolio capacity and leverage are discussed, including a critical review of the Kelly criterion. The book also presents a brief review of intraday algorithmic execution and high-frequency trading (HFT) and raises fundamental questions of more efficient market design to benefit the general investing public.

      This book wouldn't be possible without the author's interaction with many colleagues in academia and coworkers, competitors, and friends in the financial industry. The role of the early mentors, Vladimir Yankov (in physics) and Aaron Sosnick (in finance), was especially valuable in forming the author's ways of thinking about challenging problems and asking better questions.

      Special thanks to all my superiors in the industry for prudently hiring or dismissing me, as appropriate for each occasion, and to all my peers and direct reports for the opportunity to learn from them.

      I would like to thank Marco Avellaneda and Jean-Philippe Bouchaud for encouraging me to write up this material, as well as Aaron for discouraging it. A few fellow quants including, but not limited to, Colin Rust and Alexander Barzykin provided valuable comments and critique on various parts of the book draft. Their feedback is gratefully acknowledged.

      Warm regards to those interviewers and interviewees who made the endless Q&A sessions more fun than they are supposed to be.

      The time needed to write this book was an unexpected byproduct of the spread of the SARS-CoV-2 virus, which may have caused a temporary loss of smell, taste, or job, but hopefully not of sense of humor.

       Science is what we understand well enough to explain to a computer. Art is everything else we do.

      Donald Knuth

      Financial investment is a way of increasing existing wealth by buying and selling assets of fluctuating value and bearing related risk. The value of a bona fide investment is expected to grow on average, or in expectation, albeit without a guarantee. The very fact that such activity, pure gambling aside, exists is rooted in the global accumulation of capital, or, loosely speaking, increase in commercial productivity through rational management and technological innovation. There are also demographic reasons for the stock market to grow—or occasionally crash.

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      1 1 Organization for Economic Co-operation and Development (OECD) presents a detailed analysis of world equity ownership: A. De La Cruz, A. Medina, Y. Tang, Owners of the World's Listed Companies, OECD Capital Market Series, Paris, 2019.

      2 2 F. Jareño, A. Escribano, A. Cuenca, Macroeconomic variables and stock markets: an international study, Applied Econometrics and International Development, 19(1), 2019.

      3 3 A.W. Lo, Hedge Funds: An Analytic Perspective - Updated Edition, Princeton University Press, 2010.