A Re-introduction To Quantitative Investing

It’s been almost 11 years now since I posted my introduction to quantitative investing. It’s kind of hard to believe as I’m typing these words. A lot has happened since that summer day in 2013. And a lot has stayed the same. Learning about, implementing, and allocating to this type of investing has been the best investment decision I’ve made. This type of algorithmic investing in individual stocks has outperformed out of sample and continues to outperform. But it also not easy. And it doesn’t outperorm all the time. Since 2018 when I launched a quant investing subscription to the public, only about 30% of investors who give it a try end up sticking with it. That gave me the idea to re-introduce some of the basic concepts behind the approach, demonstrate recent performance, and discuss some ways I’ve come up with to make this approach easier to implement. This will become a series of posts where will dive down into some implementations of the individual strategies.

My base references for most of the strategies I use and have developed continues to be the same. What Works on Wall Street by O’Shaughnessy (latest edition is from 2011). The book documents over 200 investment strategies that use the classic investment factors like value, momentum, and growth to pick a portfolio of individual stocks that outperform the market. Another similar approach, but much more specific, is The Little Book That Beats the Market by Greenblatt (from 2005) in which he proposes a deep value strategy that beats the market over the long term. The fundamentals of the strategies I use continue to be the same.

The real challenge is selecting and adapting the strategies to make them usable by an individual investor. I have chosen and implemented around 15 of the strategies. The good news is that the best strategies historically continue to be the best strategies. But the adaptation of the strategy for the individual investor, basically the use of a much smaller number of stocks, requires at the minimum the implementation of some type of risk-management. But you can achieve some pretty impressive results. For example, the best performing strategy from O’Shaughnessy’s book is the Microcap strategy. Below is the performance of my version of that strategy since the data in the book stops, from the beginning of 2009. The microcap strategy has performed better than it has historically in this period. Also, in terms of risk-adjusted returns, i.e the sharpe ratio.

The next best performing strategy from the book is the Trending Value strategy. Let’s take a look at the results of my implementation of the strategy since the end of 2008.

Trending value also has done incredibly well. Not as good as the data in the book, in terms of returns, but pretty close and very impressive to say the least. But it’s not all so simple right? If you look at the performance charts, you’ll see that there are periods, sometimes quite long, of underperformance. Trending value went through a multi-year period of underperformance before coming back strongly and the Microcap strategy could have entered one recently. Obviously, this makes you question the strategy and if its time of outperformance is over. There are ways to deal with this that I will address in subsequent posts. But let me finish out with the other top performing strategy, pure momentum, the most people can easily identify with.

In the case of Pure Momentum we have a different scenario. At very good performing strategy in the past, but not in the top 10, became a great performing strategy. This strategy is very straightforward. It invests in stocks with the highest 6 month momentum and that’s it. Rinse and repeat. I do add risk management and some liquidity filters but basically this is a large cap momentum strategy. Below are the results.

Pure momentum also happens to be the easiest strategy to implement and is usually the one I recommend most people start with. There are a few pitfalls in implementation to avoid, especially in risk-management, but anyone with simple tools could run this strategy.

It’s not just about knocking the ball out of the park in terms of returns. You have to able to sleep at night. Risk management is key. I choose strategies for many reasons, some for performance, some for lower risk, and some to access certain parts of the market. For example, I use a low-vol stock strategy and a fixed income strategy to achieve some of these goals. The quant methods works across all types of strategies. Below is a summary of the performance of all the strategies I have chosen to implement over time.

Pretty darn good. I highlighted 10 year since that was the closest to when I first published about quant investing. Not that my implementation of these strategies would have any effect on their subsequent performance. Also, 2018 is when I started my QuantPulse service to subscribers.

In summary, 10 years later, the results for these types of strategies continue to be very impressive. This type of quantitative investing in individual stocks has worked in the past and continues to work. The consistent application of quant investing over time can make incredible differences to your portfolio. It’s not easy by any means but through risk-management, re-balancing, and with the help of a tool like my QuantPulse service it is something worth considering trying out. In my next post on this topic I’ll dive into some of the pitfalls to avoid in quant investing, particularly in strategy selection.