As an experiment for this blog, over the next few months I’ll be posting updates about:

  • My short-term trading results, and
  • What I’ve been up to, as well as thoughts and plans for the future

If you’d like me to keep putting out these updates, please let me know in the comments section below.

Feb ’20 Trading Update

My short-term trading approach (codename: TF) has evolved over the past five years, and here’s the live results of the latest version:


Performance over the last two months has been mediocre as the TF strategy went through a drawdown period from mid-Dec to end-Feb.

As of February ’20, the TF method achieved a gain-to-drawdown ratio of 0.39 (average monthly gain / max drawdown).

This is a result I’m satisfied with, and is something that can hopefully be maintained. I’m not too concerned about the under-performance in Dec and Jan, as this is well within historical norms.

There are no plans to make any adjustments to the TF strategy at this time. As long as it continues to perform along similar lines, I’m happy.

What’s New: Quantitative Analysis & Algo Trading

It has become clear to me that quantitative analysis and algorithmic trading will inevitably be a necessary part of any profitable – and sustainable – retail trading operation.

I do not think that going 100% into algo trading is the answer (at least, not any time soon), but I’d be missing out on a big part of the equation if I ignored the benefits of quantitative data analysis and/or some form of automated trading.

While I have some basic knowledge of MQL (the native programming language of Metatrader 4), I have practically zero experience with R. This is a “hole” in my skill set that I’ll be looking to patch this year.

In case you didn’t know, R is a programming language used to organize and analyze data (in this case, market price data). Think of it like a less newbie-friendly but more powerful and flexible version of Microsoft Excel. Excel is fine for handling thousands of rows of data points… but when analyzing potentially millions of data points, one needs something more suited to the job. That’s where R comes in. It’s a tool often used by data scientists and engineers. Right now, the trading world is still mostly using Excel, but I believe that R (or something similar to it) will inevitably take its place as a tool for analysis.

One area I’d like to explore with R is Machine Learning. Can it be useful for trading at the retail level? If the answer is yes, the implications are significant.

Next, is the topic of MQL. It’s a limited programming language in the sense that it’s only used on the MT4 platform, so I might eventually have to move away from it to a more widely-used language like Python. For now though, I’ll be delving deeper into MQL for my automation needs. I have a couple of trading ideas I’d like to test that is practically impossible to do manually.

If you have a considered opinion about any of these topics, I’d love to hear about it.

What Do You Think?

Do you think the quantitative analysis of market data is a waste of time for retail traders?
Do you think it would be realistic to run an algo trading operation at the retail level?
Do you have any questions for me?
Would you like me to keep posting updates like this?
Let me know in the comments below.