April had been a disaster for the TF strategy, as a combination of unusual market conditions, poor decisions and bad luck led to a cascading series of losses that wiped out the profits made since August 2019.

On hindsight, I had been too eager to maintain the prior performance of the strategy, and mistakenly assumed that market conditions had gone back to normal following the volatility explosion in March.

After carrying out a full review of the TF strategy however, I’ve determined that it’s still viable. So instead of setting it aside, I’ll keep trading with it and will be monitoring the ongoing results.

Some thoughts

A “downside” of openly sharing my short-term trading results is the self-imposed pressure to look good in front of my blog readers.

I underestimated this effect as, after reflecting on what happened, I realized I’d been preoccupied with “looking like a winner” instead of just doing the work and letting the results be. The change in mindset is subtle, but the consequences are significant.

Ironically, the heightened desire to win led to the exact opposite result.

I am inclined to keep sharing my results however, as I think it can be helpful to others, and that not enough traders are doing it. If you find these trading reports to be helpful, please let me know in the comments section so I know I’m not just deluding myself.

For now, I’m taking it as a personal challenge to overcome the mental obstacle of “performing” in public without letting it get to my head.

Algorithmic Forex Trading

Meanwhile, I’m starting to appreciate the benefits of algorithmic trading.

I don’t know if it’s feasible for a retail Forex trader to operate almost entirely with algos, but I believe it’s a premise worth exploring because:

  • Algo trading research helps me identify market tendencies that I otherwise would not have noticed
  • Algos can monitor the market around the clock so I don’t have to personally check in with the market multiple times a day (this is a HUGE benefit to me)
  • Trading with algorithms removes emotions from the equation, which makes it much easier to make objective decisions

I’ve so far managed to code up a handful of trading robots and run a few dozen backtests before coming across this gem:

For a 100% automated trading robot, this result is quite impressive. The question is, will it continue to perform under real-time conditions? We’ll see.

I am now running this robot on a demo account and if the results are similar to the backtest the next step is to move it to a live account.

The goal is to have a dozen or so robots all running at the same time.

My role as a “trader” would then be to monitor and adjust my capital allocation across a portfolio of robots, rather than trading manually.

As mentioned earlier, I don’t know if this is a feasible goal but I’m going to find out.

If you have any feedback, questions or suggestions, let me know in the comments below.