17% Annual Stock Returns: Lessons Learned
How it worked, and why I didn’t continue this approach.
A warm hello to all new readers! I’m glad you are on board.
New here? I’m Michael and on a mission to make beating the stock market as easy for you as choosing your favorite ice cream. I write an algorithm that does exactly that.
Read the full story here.
Life isn't just about reaching your destination - how you get there counts.
'Every car might get you to your destination, but the right one makes the journey unforgettable.'
My ride into the territory of quantitative value investing gave birth to an algorithm that delivered a 17% annual return.
Before we take off, I shall start with an analogy that has shaped my way of approaching decisions and new developments in general. This story is as much about the journey as it is about the destination, and about choosing the right car for a long trip.
As a former automotive engineer with over 13 years of experience and hundreds of cars tested, I’ve learned that while every car might get you to your destination, the choice of vehicle still matters a lot. This insight into cars—where even budget models no longer come with too nasty surprises at the first glance—parallels the world of investing, where strategies abound but true value can be elusive.
When it comes to cars, my essentials are simple: air conditioning, adaptive cruise control, and seat heating. Everything else is a bonus. When it comes to investing, I have also tried to reduce many strategies to their core and their usable insights. Just as air conditioning, adaptive cruise control, and seat heating represent my non-negotiables in a car for comfort and control, in investing, I prioritize strategies that offer stability, adaptability, and lower volatility.
Merging Lanes - The Algorithm
I initially began with rebuilding Joel Greenblatt’s “Magic Formula,” quickly realizing its effectiveness had waned as more investors caught on. The market, it seemed, had adapted, and it’s not enough to just go after two simple ratios. This led me to study the broader investment landscape, filled with value investors, growth fans, and momentum chasers.
My second algorithm aimed to merge these three promising paths: selecting stocks through a blend of value indicators (like P/E Ratio, P/S Ratio, and Price/Book Value), growth metrics such as surging sales and earnings, and past price momentum signals (3, 6, 9 and 12 months) to capture market sentiment.
Yet, the key lesson from my automotive days—understanding the essence of what truly matters—came to the forefront again. Although initial results were promising, with annual returns of 14% to 17%.
The problem with the algorithm’s failure was not that it was chasing the taillights of the market, but that it couldn’t see where the road was going with these inputs. However, volatility and the returns after tweaking the model highlighted this: the importance of a focus on fundamentals over trying to catch the market’s fleeting whims by pure interpretation of price momentum and growth stories.
Conclusion
This research underscored a critical point in relying too heavily on past stock price momentum.
Rising stock prices result mostly from fundamental inputs.
Interestingly, a second finding was that extending the momentum timeframe improved outcomes, suggesting that short-term market moves were less meaningful than longer-term trends.
My journey through the valley of quantitative investing has underscored a fundamental truth: selecting the right investment strategies mirrors developing the perfect car.
It demands not just a blend of knowledge and adaptability, but a deep understanding of one’s objectives and what realistic outcome you can expect from this combo. Please read that again, because the metric I want to optimize is the 12-month-rolling cycle of my strategy. So, keep that in mind. My findings may not fit your focus and objectives.
The development and refinement of the first and second algorithm served first and foremost as a practical course. To understand why it’s performing the way it did. Each iteration, much like test-driving cars with different set-ups, provided valuable insights and honed my understanding of the factors that influence outcomes.
In both areas, it’s often the subtle nuances that contribute to overall performance. Knowing that it can’t perform perfectly in all conditions, because as always in closed systems, one influences the other. Whether it’s the comfort of the drive or the robustness of an investment strategy, the sum of all details creates the overall feeling of a complete and effective system.
A critical insight from these coding sessions was recognizing that there is often a lag between identifying an attractive company and observing the impact on its stock price. My experience was a typical delay of roughly three months before a noticeable trend emerged past the stock purchase.
This lag period is like the time to truly appreciate a car’s worth after you get it —like understanding its details, how to drive it efficiently, and how it complements your lifestyle.
Similarly, in investing, patience is paramount. Recognizing the inherent delay in the manifestation of value allows for strategic decisions that are more informed, rather than reactive.
Just as with finding a car that fits your needs and desires, crafting and adjusting an investment strategy is a journey of discovery, attention to detail, and a firm focus on long-term goals.
Progress
First the good, then the ugly.
I’ve thought about how I can present stock data more interestingly because I think charts are rather boring, although they transport a lot of information. But we are used to it. So I’ve created this video to make it more engaging. The goal is to create some micro content people would share with their friends. This was one of the important points after a call I had with
.I also had a big downer this week. A couple of weeks ago, I accidentally stopped the training of my algorithm. I thought “No big deal. Just restart it where it stopped.” And so I did. Little did I know. The surprise came in the second round when I realized that something was off. I saw it early, and yet it cost me time. My key learning and the good thing is, the code is sound, but you shouldn’t interrupt it. So I started it all over again, setting me back around three weeks. Yeah, it sucks, but it was my fault, so there is nothing to complain about. My second key learning was, never to run too many scripts in the same project. Rather, create a new one to systematically minimize the potential for failures.
I had my first success with the macro indicators. I experimented with inflation forecasting and it looks good.
Plan
Create a couple more video templates to streamline my microcontent strategy.
What’s on my head
It’s great to see the progress, and it satisfyingly pushes me. More and more things click and come together.
Nuggets I’ve enjoyed
Have a great day StockStar!
Hit that heart if you love your dream car!
Michael
If you think somebody should read this, share it, and make them happy.
Recommend The Economy Rocket to your readers and friends
I share my stock investment story without sugarcoating – you get the good, the bad, and those tricky ego trips. I'm developing a service with a mix of smart code and proven investment strategies, making stock analysis a thing of the past if you wish. Because life offers so much more beyond the confines of stock analysis.
Disclaimer:
The information in this article is my personal opinion. I’m not a certified investment professional. It is not consulting, nor does it constitute investment recommendations.
I do my research carefully and follow my personal investment strategy.
The stock market is a complex building with its own rules. There are no rules set in stone, like the rules of physics.
Therefore, use the contents of this newsletter at your own risk and do your own research as well. Investing in the stock market can lead to a total loss of the capital invested.
Love all the progress you are making on your Value Vantage platform. Storytelling through data visualization is such a powerhouse. Looking forward ot your next post.