I finished this week in profit. I opened three trades, two using my Hermes low volatility system, and one using my Set weekly two-bar reversal system.
GBPUSD - 1D - Hermes low volatility system
I spotted this setup on Monday morning before the market opened. The GDPUSD closed on Friday with low volatility, which made a good entry signal. I went short on the break of Friday's low and used a 0.5 reward-to-risk ratio. Looking at the chart below, I know I could've bagged alot more profit (4 * risk?), but those are the breaks with mechanical trading.
USDCAD - 1D - Hermes low volatility system
It's a similar story with the USDCAD. There wasn't much movement on the USDCAD during Monday. I went long on the break of Monday's high and took profit using a 0.5 reward-to-risk ratio.
GBPJPY - 1W - Set two-bar Reversal system
A two bar reversal pattern appeared on the GBPJPY;s weekly chart. I used a 0.25 reward-to-risk ratio. Price reversed shortly after hitting my profit target.
System development - weekly dojis and a few lessons on R:R ratios
I'm 90% complete on developing my weekly doji system. There's only one more pair I want to backtest, and then I'll see what I can achieve with optimisation. Below are two equity curves of my un-optimised system. The backtest results are from 12 years of data across 16 currency pairs, using 2% risk per trade on a starting balance of $10,000.
The first equity curve is the result of using a 1:1 reward:risk ratio. My profit factor is 1.31. Max drawdown was 24%.
# of Trades
The second equity curve is from using a 0.25:1 reward:risk ratio. Profit factor is 1.36. Max drawdown was 6%.
What can we learn from this? It got me thinking about using small reward-to-risk ratios, and why they may be better than large ratios.
A small reward-to-risk ratio usually mean small, consistent wins, occasionally punctuated with a massive loss. That's the price we pay. But what else can we glean about the nature of small R:R ratios?
We can also say that they are less susceptible to choppy markets. This seems to bear out in the equity curves above, where the 0.25 R:R equity curve seems more smoother than 1:1 R:R. The dips and spikes in the 1:1 equity curve seem to indicate greater sensitivity to changing market conditions.
From a risk-management perspective, small R:R ratios also provide an earlier "system failure" warning than large R:R ratios.
For example, suppose we have a breakeven system using a 0.25 reward : risk ratio. Since this system is breakeven, we expect 4 wins for every loss. If we risk 2% per trade and experience 5 consecutive losses, we know that something is wrong and we can halt trading. In this case, our drawdown would be 10% (2% * 5 losses).
However, suppose we use another breakeven system, this time with a 4:1 reward : risk ratio. We expect one win for every 4 losses. If we experience 5 consecutive losses, we are still within our expectations. It may take 10-15 consecutive losses before we halt trading. By this stage, our drawdown is now between 20%-30%.
We have two systems with the same profit factor and expectancy. However, the system with the smaller R:R ratio is better able to alert us to system failure, and protect our equity.
These are just a few ideas that's been bouncing around in my head.