I normally use Net Profit, Return on Account and Profit Factor as criteria for my optimization.
Those criteria aren't bad, but I want to place more emphasis on stable returns over the whole period. This isn't just the smoothness (that is solved by ROA or Sharpe) but rather having a relatively constant slope of equity curve throughout the period.
I believe the coefficient of determination (R-Squared) of the equity curve can be useful for that. Then, perhaps multiply it by the Net Profit and have (P * R^2) as the criteria.
For that, I would like to use a custom signal, using the SetCustomFitnessValue, as explained in https://www.multicharts.com/trading-sof ... timization
Now for my question - is there already such a signal available (or something similar) that I can use, or should I write it from scratch?
R-square optimization criteria
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TraderWalrus
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TraderWalrus
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Anna MultiCharts
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Re: R-square optimization criteria
Hello, TraderWalrus!
I’m afraid there’s no such pre-built signal or any other study. You will need to create it yourself or search for it on the Internet, as there’s quite a number of free available studies written in EasyLanguage/PowerLanguage.
I’m afraid there’s no such pre-built signal or any other study. You will need to create it yourself or search for it on the Internet, as there’s quite a number of free available studies written in EasyLanguage/PowerLanguage.
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TraderWalrus
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Re: R-square optimization criteria
Thanks, I wrote it myself. My code is below. Simply, it calculates R squared by Pearson correlation on equity with a vector of running numbers (1 onwards). Hope it helps others.
Code: Select all
variables:
maxIndex(0), curIndex(0), curXval(0), curYval(0),
sumX(0), sumY(0), sumOfxSqr(0), sumOfySqr(0), sumOfxy(0),
numerator(0), denominator(0), retVal(0);
arrays: equity[](0);
maxIndex = array_getmaxindex(equity);
equity[maxIndex] = i_OpenEquity;
if not LastBarOnChart then
array_setmaxindex(equity,maxIndex+1)
else
begin // Calculate r squared
for curIndex = 0 to maxIndex
begin
curXval = curIndex + 1; // x values are simply running numbers starting from 1 onwards
curYval = equity[curIndex];
sumX = sumX + curXval;
sumY = sumY + curYval;
sumOfxSqr = sumOfxSqr + curXval * curXval;
sumOfySqr = sumOfySqr + curYval * curYval;
sumOfxy = sumOfxy + curXval * curYval;
denominator = (maxIndex * sumOfxSqr - sumX * sumX) * (maxIndex * sumOfySqr - sumY * sumY);
if denominator <> 0 then
begin
numerator = maxIndex * maxIndex * sumOfxy * sumOfxy +
sumX * sumX * sumY * sumY -
2 * maxIndex * sumOfxy * sumX * sumY;
retVal = numerator / denominator;
end
else
retVal = 0;
end;
end;
G_R_Squared_Equity = retVal;
Re: R-square optimization criteria
I would second to have this appear on the detailed equity curve simulations. The graph speaks 1000X what a single digit can.
But despite having this feature, interpreting optimization results goes way beyond simply finding the best number.
But despite having this feature, interpreting optimization results goes way beyond simply finding the best number.