Welcome to the report for the month of February!

After some conversation with both active readers and prospective, I’ve got some housekeeping to do before we get in to the data, above the paywall this time so everyone gets to see whats changing;

• Yes, this is the second report “for February”.

  • In a couple conversations, it was asked why data being collected from the month of January was being called the report for February. In my mind, it was February’s report because it was being sent out in February. That said, the confusion was completely understood and will be named for the month the data was collected in.

• “So I want to know what to run, and you spend a lot of time calling everything dangerous and bad.”

  • If you know me, I’m extremely skeptical of things I would consider poorly made strategies. There are a lot of those that we track, purely for “scientific purposes". Add on to that the fact that Garen and I hold rather different investment philosophies, and you get to a spot where the guy doing the writing doesn’t agree with the guy who planned all the initial investments.

    Going forward, I’m going to be marking strategies in the database with where they stand in the portfolio, who decided to run it, or what purpose I think it servers.

    I’m going to be working with the following tags;

    • Jakes Portfolio

      • I’m very analytical, and very critical of strategies. I don’t put money in to things I personally deem overfit, low quality, or questionable, unless its to prove a point. I’m aiming to follow something akin to a “traditional portfolio management” setup, akin to the works of Dalio, Browne, and Bogle with the majority of my allocations, with a small amount to what could be considered “high risk” strategies. If your goal here is to find high risk, potentially high reward strategies, you can safely ignore almost anything I’m invested in.

    • Garens Portfolio  

      • Garen takes what could be accurately described as a Shotgun approach to algorithmic investment. Find strategies that, on their own, may not go up and to the right all the time, but when you assembled 1000 of them they work themselves out over a long enough timeframe. This certainly allows for many things I’d consider highly speculative, if not outright dangerous, to make their way in to the portfolio. However, if you keep your speculation reasonably diverse across logic and asset classes, many esteemed investors argue you’re setting yourself up on the path to success.

    • Pure Science

      • This one should be self explanatory, we have live money in it, but we have zero expectations for it. Many times, strategies in this category will be testing out new theoretical logic or purely trying to prove or disprove a point or claim someone made. If you decide to use something in this category, please size your position accordingly.

Additionally, in the next month or so, I’m going to be running the entire databases contents through the Correlation Tool and putting together “portfolios” of strategies that would compliment eachother, based off the live data we’ve collected. Similar to the original concept of the Genesis Portfolio, for those of you who’ve been around long enough to remember that, but with the added benefit of more live trading and better tools than we had before!

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