The Alpha Formula - High Powered Strategies to Beat The Market With Less Risk

Strategies by Connors Research have always been effective, easy to follow, and simple to implement. And while I enjoyed previous Connors books, I also had some criticism with these. The Alpha Formula is on an entirely new level: It features a new style of writing and a more diversified approach to trading.NEW STYLE OF WRITINGThe Alpha Formula’s new style of writing is a considerable improvement over previous books by Connors Research. In particular, I appreciate the following changes:• More detailed results. All strategies presented include comprehensive metrics and detailed charts. Further, the book discusses the backtested results, points out key findings, and puts the strategies into a broader context.• Context and background. A larger part of the book focuses on behavioral finance, why prices behave the way they do, and why trend following and mean-reversion work. This context is used throughout the book to show how the various strategies interact with each other.MORE DIVERSIFICATIONMany books on trading strategies only provide a collection of loosely related strategies. The Alpha Formula is different:• First, it presents four individual strategies, which are very different in nature and designed to work together in unison. While none of the strategies are ground-breaking in itself, they are all solid.• Then, the book constructs the Alpha Portfolio from these individual strategies. A portfolio diversified in asset classes, methodology, time frame, and market condition. This portfolio delivers smooth returns with a low risk profile over a wide array of market situations.VERDICTIn summary, The Alpha Formula appeals equally to readers looking for a strategy they can use out of the box, as it does to quant developers looking to jump start their development. I consider The Alpha Formula a must-read for anybody interested in quantitative trading, and the best trading-related book I read in a while.

One of the challenges facing algorithmic trading systems, especially those with Artificial Intelligence or Machine Learning (AI / ML) components, is the ability to explain the results. If you cannot explain why a system placed (or did not place) a trade, it is difficult to determine whether the algorithm will work in the future.In The Alpha Formula, the authors clearly present the principles behind their approach to algorithm design. They clearly present the specific steps required to implement each of the four algorithms described in the book. They provide detailed performance data, which can be confirmed either by writing your own code or purchasing the code from Connors Research.I purchased the code and ran the algorithms on Quantopian.com, then ran the backtest results through Quantopian's backtest performance analyzer. I can confirm the results.In addition to the clarity of their presentation of each algorithm, the authors make another valuable contribution: they show the value (again with detailed results) of employing a portfolio of strategies. As they write, Ray Dalio has recommended this, but The Alpha Formula makes the value of this recommendation concrete by showing specific algorithms and the results of combining them into a portfolio.I think any algorithmic trader would benefit from reading this book and applying the approaches presented (developing from first principles and diversification of strategies) to their own work.

The idea of 4 non-correlated strategies to garner robust returns is terrific, as is the approach of capital utilization lasting days or weeks as opposed to years. But after all is said in done, "The Alpha Formula" provides a return of about 11% annualized, and that is with high-maintenance (ie. strategies requiring high-frequency trading) and leverage.If we're really serious about capturing alpha, shouldn't readers question the wisdom and utility of a pretax 11% return requiring leverage and a great deal of work? The hidden absurdity is that in back-testing "The Alpha Formula Strategy", with returns of 11% against owning an index position in the S&P 500, short-term taxation eats up all "The Alpha Formula"'s alpha. Another caveat: The 11% return quoted in the text is conveniently based on non-taxable returns only since the Great Recession, one of the greatest bull runs in history. We really don't know how the strategy performs in prolonged bad periods, but we are told that one of the two bear market strategies --a defensive bond strategy-- generates returns of a bit over 2% annualized, which is not especially compelling. The other bear market strategy is a complicated short-sale common-stock approach which will require a great deal of the reader's attention to execute.All told, the purported alpha here is high-maintenance, minuscule and a bit of a let down amidst the rather aggressive sales pitch that accompanies this book.Regarding the generally high ratings here, the author encourages his seminar students to leave favorable reviews on Amazon and I suspect the reviews are accordingly somewhat inflated. Caveat emptor.

This was an interesting and insightful read, introducing concepts I never heard discussed before.I never heard of structuring portfolios bases on First Principles or inherent truths, but it makes a ton of sense. I also love the behavioral explanation of both short-term mean reversion and longer-term trend following, I have also long believed that human (mis)behaviors are behind these market tendencies.The strategies are relatively simple, economically logical and most importantly have worked on a historical basis. All rules and backtests are shown.These strategies will make any trader better.

Backtests up to end of 2018 only. There are not many strategies discussed