re-examine the old strategies from the library
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As to the one at your link, I think it’s really basic and was not so good. As it is I don’t think it may perform any better now.
You cannot write a strategy based only on RSI, or MA’s or whatever else. KISS (Keep It Simple and Stupid) is a nice acronym, were it only written KIS!
A solution would be to add some price action patterns or further indicators. But, in the end, it’s far easier to code a new one when you have an idea.
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i Think grahal has a file with systems from this forum and performance if im not wrong.
I have tried to encourage use of a Log, but hardly anybody contributes by entering performance stats etc.
- One Year After got more entries initially, but then stopped.
I then thought maybe folks can’t be bothered if it takes more than 10 seconds of their time to enter data so I came up with a much simplified version
- Forward Test – Sys Perf but that went down like a lead balloon! 🙂
At any stage I am open to suggestions to amend columns / data required in the log to make a Log what the Community wants to see and use?
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This code was made 2017 October.
Since then it has made € 300 in profits.
https://www.prorealcode.com/prorealtime-trading-strategies/simple-gets-eurusd-2h-atr-strength/
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This code was made 2017 October. Since then it has made € 300 in profits.
Yes – but before we jump in and just trade it perhaps we should analyse it?
Let’s start with the exit conditions. There are two – get out if there is another big green or red body or get out if a certain amount of time has passed by. Alarm bells are already ringing with time based exits! The best way to examine each is to remove one at a time.
The first image shown is the results with both exit conditions.
The second image is the results with just the body size condition.
The third image is the results with just the time based condition.
mmmm……. me thinks that this strategy might just be a bit of time based data mining but we’ll keep testing.
The fourth image is with all exit conditions removed so that we just reverse position based on entry conditions.
Let’s do one final check.
Another test we can do to see how exit condition biased a strategy is by adding 1 to a flag every time an exit condition is hit and GRAPH the results. Like this:
1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556ATR = average[p](tr)//AverageTrueRange[p](close)LongEntry = close - open > ATR * 2LongExit1 = close - open > ATR * 2LongExit2 = BarIndex = TradeIndex + 8ShortEntry = open - close > ATR * 2ShortExit1 = open - close > ATR * 2ShortExit2 = BarIndex = TradeIndex + 8Maxpos = 1// Conditions to enter long positionsIF CountOfLongShares < MaxPos AND LongEntry THENBUY 1 CONTRACTS AT MARKETif shortonmarket thenshortexit3flag = shortexit3flag + 1endifENDIF// Conditions to exit long positionsIf LongOnMarket AND LongExit1 THENSELL AT MARKETlongexit1flag = longexit1flag +1ENDIFIf LongOnMarket AND LongExit2 THENSELL AT MARKETlongexit2flag = longexit2flag +1ENDIF// Conditions to enter short positionsIF CountOfShortShares < MaxPos AND ShortEntry THENSELLSHORT 1 CONTRACTS AT MARKETif longonmarket thenlongexit3flag = longexit3flag + 1endifENDIF// Conditions to exit short positionsIF ShortOnMarket AND ShortExit1 THENEXITSHORT AT MARKETshortexit1flag = shortexit1flag + 1ENDIFIF ShortOnMarket AND ShortExit2 THENEXITSHORT AT MARKETshortexit2flag = shortexit2flag + 1ENDIFgraph shortexit1flaggraph longexit1flaggraph shortexit2flaggraph longexit2flaggraph shortexit3flaggraph longexit3flagexit 1 flags are ATR based exits
exit 2 flags are time based exits.
exit 3 flags are reversal exits.
The results are shown in the last image.
It seems pretty conclusive that this strategy is purely time based data mining from these tests even if it has made a few hundred pips in forward testing.
All is not totally lost for the strategy though as it does help us analyse how long it is wise to hold on to a position after one of these entries. If you remove all other exit conditions and then run a optimisation back test and then put the results in an Excel graph then we can see that there is definitely a range where holding is profitable but hold too long and watch any potential profits disappear.
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Sorry – I just realised that the image in the last post is incorrect. I was testing with a different value for ATR. Average[p](tr) instead of AverageTrueRange[p](close). The correct image is attached.
We can see that the need to get out of a trade happens much sooner. So at least we have learned something else – Average[p](tr) is a better entry condition than AverageTrueRange[p](close)!
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