Paul Laurendeau

My name is Paul Laurendeau. I am an architect by profession, based in Montreal. I am self-taught in finance, with a mathematical and geometric perspective on numbers and market models. Here is how, since 2017, my quantitative investment strategies have taken shape.

Early days in the market

In March 2017, I began investing in the stock market out of interest and curiosity. Since 1995, I had entrusted my savings to a portfolio manager who invested in a traditional manner, producing a typical annual return of approximately 6.5% over 22 years.

I first built a portfolio of Canadian and American equities. I read extensively, seeking to understand the criteria for selecting securities and the approach of investors such as Warren Buffett. My approach was rather fundamental — intuitive, and above all consistent with what most managers do: placing money in funds and securities chosen on that basis.

Discovering momentum

In August 2017, while listening to podcasts on markets and economics, I came across an interview with Meb Faber. He spoke about momentum and trend following. I read several of his texts, including A Quantitative Approach to Tactical Asset Allocation (2006), with its tables and charts comparing different approaches and hypotheses. This analytical process — formulating a hypothesis, testing it, measuring the result — immediately captured my attention.

At first, I calculated the momentum of equities in Excel spreadsheets. Tedious work, until I discovered online platforms that performed these calculations instantly. I nonetheless manually verified their results, as certain sites present unreliable data.

In parallel, I read Dual Momentum by Gary Antonacci, in which he presents his Global Equities Momentum model as the culmination of a trend following approach applied to global markets, showing returns superior to indices over the long term.

These models were my starting points. I used online platforms to test every idea and hypothesis that came to mind. Despite the well-known warnings about the fragility of backtests for predicting the future, I sometimes implemented overfitted models too early, which generated a series of controlled losses. These experiences were my tuition fees.

The 2022 drawdown

In 2022, my strategies suffered a significant setback between January and June. These market conditions exposed vulnerabilities related to the asset class universe I was trading, as well as the historical limitations of my backtests, sometimes restricted to the 2007–2015 period. I also did not know at the time that trend following strategies typically experience larger losses at pivot points when trends change regime.

I then reviewed and analyzed all my strategies one by one to identify their weaknesses. This is a delicate exercise that can lead to overoptimization. I was careful to keep each strategy as simple as possible, without adding layers of parameters that obscure the expression of the trend.

The following years were a long process of financial recovery and methodical monitoring of each strategy. I made adjustments, launched new strategies and closed those that were underperforming.

What I share on Quant Performance

Since 2023, I have observed increased stability in my strategies with overall performance above the markets. To ensure precise tracking of daily fluctuations, I created detailed Google Sheets that record the daily returns of each strategy. I publish some of these tables on this site along with certain holdings.

The models presented here are a sample of those I trade in my own portfolio. I offer them as the result of serious, rigorous and mathematical work — strategies based on systematic rules, little known to individual investors, and which show returns above market indices in a world where even professionals struggle to consistently reach that threshold.