The Ultimate Moving Average Handbook - by Valeriy Zakamulin & Javier Giner (Hardcover)

Book Synopsis

Moving averages of prices serve as the primary tool for tracking trends in financial markets, filtering out noise, and highlighting trend directions. With a plethora of moving averages and trend-following rules at their disposal, traders often find themselves overwhelmed by the sheer variety of choices. Moreover, traders persistently devise new forms of exotic moving averages, each purportedly offering improved responsiveness and smoothness compared to its predecessors. While it is relatively straightforward to visually compare the responsiveness of two different moving averages, assessing their smoothing properties proves to be more challenging. Comparisons made through visual inspection are inherently subjective and prone to biases. A pressing need exists for quantitative metrics to objectively assess the properties of moving averages and their associated trend-following rules.

In this book, the authors propose a quantitative assessment of the properties of trend-following rules based on moving averages. They argue that there are three primary properties of trend-following rules: responsiveness, smoothness, and accuracy. Given the prevalent claims that each exotic moving average offers superior responsiveness and smoothness compared to prior versions, the book provides a means to verify the accuracy of these assertions. It offers systematic and comprehensive coverage of various types of moving averages and the trend-following rules based on moving averages, and focuses on identifying the most crucial properties of trend-following rules and proposing quantitative metrics for their evaluation.

Despite the plethora of books and academic publications, contemporary trend-following with moving averages remains more of an art than a science. This book injects scientific principles into the practice of trend-following, offering invaluable, distinct, and objective insights tailored for traders and investment professionals involved in trend-following investing alongside academics and students within economic and finance departments.

From the Back Cover

"A must-read for serious investors, this book brings scientific rigor to trend following. The authors cut through the noise with a systematic, research-backed approach to moving averages. An invaluable resource for practitioners and academics alike."
--Wesley R. Gray, Ph.D., CEO of Alpha Architect

"In The Ultimate Moving Average Handbook, Zakamulin and Giner employ academic rigor to transform the art of trend following into a science. By challenging conventional thought and exposing the myths surrounding so-called superior moving averages, they provide traders and researchers with an objective, data-driven framework for evaluating and optimizing trend-based trading rules. This book should serve as a guidepost for making more informed investment decisions. It is an essential read for anyone serious about systematic investing and technical analysis."

--Gary Antonacci, author of Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk

"While claiming to be academic, this book provides a fountain of information for trend followers with techniques that have been overlooked. I was particularly interested in the zero-lag models and the calculation frequency. It is remarkably readable and a great achievement."

--Perry Kaufman, author of the classic Trading Systems and Methods book

"This book is a tour de force that extends and accelerates the important trend in technical analysis toward scientific rigor and empirical evidence. Moving averages--one of the field's key tools--are covered in all their forms and from every angle, making this required reading for every serious technical analyst. Most importantly, moving averages are evaluated within a rules-based framework--an important and highly pragmatic approach to the subject."

--David Aronson, author of Evidence-Based Technical Analysis book

"In an era dominated by AI, writing a book about the humble moving average is nothing short of audacious. But here's why it matters: MA-driven investment strategies consistently deliver rock-solid out-of-sample results--frequently outpacing AI-powered approaches. And here's the secret: many systematic fund managers quietly agree. While MAs may seem simple, this book goes beyond the surface, digging deep and leaving no stone unturned. If systematic trading is your game, consider this your goldmine of insights--packed with fresh ideas to supercharge your strategies."

--Dr Tom Starke, Founder of AAAQuants

Valeriy Zakamulin is a Finance Professor at the University of Agder, Norway, whose research focuses on asset pricing, portfolio management, and technical trading strategies.

Javier Giner is a Senior Lecturer in Financial Economics at the University of La Laguna, Spain, with research spanning quantitative methods in both acoustics and finance.

About the Author

Valeriy Zakamulin is a Finance Professor at the University of Agder's School of Business and Law in Norway. He holds a Master's in Business Administration and a PhD in Finance from the Norwegian School of Economics. Valeriy has contributed articles to different academic and practitioner journals and often speaks at international conferences. Additionally, he has served on the Editorial Boards of journals like the Open Economics Journal, Journal of Banking and Finance, and International Journal of Emerging Markets. His research focuses on areas such as behavioral finance, portfolio management, active trading strategies, momentum and mean reversion in financial time series, and stock return and risk predictability.

Javier Giner is a Senior Lecturer in Financial Economics at the University of La Laguna, Spain. His research is linked to quantitative and computational methods, initially in the field of room acoustics, and later in quantitative finance. His current research covers the application of statistical and computational techniques for the modeling of financial series, volatility analysis and the study of investment strategies based on moving averages.