Although many traders seem to be looking for the GRQ (Get Rich Quick) strategy my approach is Long Term and is more concerned with the Reward to Risk ratio. We have to take on the Risk to enter the market but what size Reward are we targeting?
Basic common sense tells us that there are few good trading opportunities in any market, maybe only 1 or 2 great trades a year exist in any market. Sometimes a market can go sideways for 1 or 2 years before it breaks out of its range and starts pushing higher or lower with momentum (see GBPUSD Weekly).
So developing a strategy that trades every week or every day is not something I have been trying to do.
Instead I have been working on the Long Term approach where Trades with a very high Reward/Risk ratio are targeted. We can think of the ratio like this
????? / $300.
If we are to risk $300 how much do you think the reward should be? I cannot answer that question so I decided to let the Market answer that question for me.
I designed my (Take the Risk) Entry using a combination of Intra Day and Daily time frames but for the (Take the Profit) Exit I looked only for a breakdown of the Daily
Trend (the bigger Trend). This enables the capture of very large moves which is of course good for the overall Profit Factor (PF) but the prompt elimination of the Risk is also critical to obtaining a high PF. Of course there has to be some big market movement in the first place.
This approach may be of interest to some developers as 10/1 Reward/Risk ratios can easily be achieved and 100/1 ratios are not impossible either. Most strategies I have seen posted on here and other forums have PF’s of about 1 or 2 but with this long term approach I am able to obtain PF’s ten times greater. Maybe you can too.
I will attach an image of the Equity Curve from the MHT file generated by Tradestation whose platform and Historical data was used. I cannot attach the MHT file type so I will attach an Excel copy of the performance report and a Weekly image of the GBPUSD Spot market on which the back test report was performed.
The Spread has been factored into the report and also a 2 pip’s round turn for Slippage.
The back test was run over the complete set of historical data.
John
Basic common sense tells us that there are few good trading opportunities in any market, maybe only 1 or 2 great trades a year exist in any market. Sometimes a market can go sideways for 1 or 2 years before it breaks out of its range and starts pushing higher or lower with momentum (see GBPUSD Weekly).
So developing a strategy that trades every week or every day is not something I have been trying to do.
Instead I have been working on the Long Term approach where Trades with a very high Reward/Risk ratio are targeted. We can think of the ratio like this
????? / $300.
If we are to risk $300 how much do you think the reward should be? I cannot answer that question so I decided to let the Market answer that question for me.
I designed my (Take the Risk) Entry using a combination of Intra Day and Daily time frames but for the (Take the Profit) Exit I looked only for a breakdown of the Daily
Trend (the bigger Trend). This enables the capture of very large moves which is of course good for the overall Profit Factor (PF) but the prompt elimination of the Risk is also critical to obtaining a high PF. Of course there has to be some big market movement in the first place.
This approach may be of interest to some developers as 10/1 Reward/Risk ratios can easily be achieved and 100/1 ratios are not impossible either. Most strategies I have seen posted on here and other forums have PF’s of about 1 or 2 but with this long term approach I am able to obtain PF’s ten times greater. Maybe you can too.
I will attach an image of the Equity Curve from the MHT file generated by Tradestation whose platform and Historical data was used. I cannot attach the MHT file type so I will attach an Excel copy of the performance report and a Weekly image of the GBPUSD Spot market on which the back test report was performed.
The Spread has been factored into the report and also a 2 pip’s round turn for Slippage.
The back test was run over the complete set of historical data.
John