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Burg Extrapolator EA
The EA uses the method of Burg's linear prediction. The linear prediction is based on finding the future values as the values of the lienar functions of the past values. Assume that we have a number of prices x[0]..x[n-1] where the higher index is compliant with the recent price. The prediction of the future price x[n] is calculated as
xn = -Sum(ai*xn-i, i=1..p)
where ai=1..p - coefficients of the model, p - order of the model. The Burg's method finds the a[] coefficients by decreasing the mean-root-square error on the training last n-p bars.
Strategy Tester Report
Burg Extrapolator - opt
InterbankFX-MT4 Demo Accounts 2 (Build 220)
Symbol EURUSD (Euro vs US Dollar)
Period 4 Hours (H4) 2007.12.03 00:00 - 2008.12.02 20:00 (2007.12.03 - 2008.12.03)
Model Every tick (the most precise method based on all available least timeframes)
Parameters MaxRisk=0.5; ntmax=5; MinProfit=160; MaxLoss=130; TakeProfit=0; StopLoss=180; TrailingStop=10; PastBars=200; ModelOrder=0.37; UseMOM=true; UseROC=false;
Bars in test 2584 Ticks modelled 3936616 Modelling quality n/a
Mismatched charts errors 5263
Initial deposit 10000.00
Total net profit 2150865.30 Gross profit 3755013.80 Gross loss -1604148.50
Profit factor 2.34 Expected payoff 8467.97
Absolute Array 2463.43 Maximal Array 763930.92 (38.56%) Relative Array 70.14% (47506.11)
Total trades 254 Short positions (won %) 92 (71.74%) Long positions (won %) 162 (82.72%)
Profit trades (% of total) 200 (78.74%) Loss trades (% of total) 54 (21.26%)
Largest profit trade 314280.00 loss trade -90000.00
Average profit trade 18775.07 loss trade -29706.45
Maximum consecutive wins (profit in money) 26 (21889.31) consecutive losses (loss in money) 6 (-26080.89)
Maximal consecutive profit (count of wins) 1372487.83 (6) consecutive loss (count of losses) -314864.76 (4)
Average consecutive wins 7 consecutive losses 2
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The EA uses the method of Burg's linear prediction. The linear prediction is based on finding the future values as the values of the lienar functions of the past values. Assume that we have a number of prices x[0]..x[n-1] where the higher index is compliant with the recent price. The prediction of the future price x[n] is calculated as
xn = -Sum(ai*xn-i, i=1..p)
where ai=1..p - coefficients of the model, p - order of the model. The Burg's method finds the a[] coefficients by decreasing the mean-root-square error on the training last n-p bars....
Thank you for sharing the information about the Burg Extrapolator EA and your Strategy Tester Report. It's always interesting to explore new trading strategies and tools.
The Burg Extrapolator EA seems to be utilizing Burg's linear prediction method to forecast future prices based on past data. This concept of linear prediction is quite intriguing. It relies on a model with coefficients (ai) to make predictions, and the Burg method optimizes these coefficients to minimize the mean-root-square error. It's a sophisticated approach to trading.
The Strategy Tester Report you provided indicates that you tested this EA on the EURUSD pair with a 4-hour timeframe from 2007.12.03 to 2008.12.02. The results look impressive with a total net profit of 2150865.30, a profit factor of 2.34, and a majority of winning trades. These are promising numbers!
-It's a good practice to test the EA over a more extended period.
-You might want to explore different parameter settings to see how the EA reacts under various conditions.
-The MaxLoss of 130 seems relatively low compared to the total net profit. Evaluate and adjust your risk management strategy.
-While the EA has shown impressive results, the maximal Array of 38.56% is quite significant. Consider if you're comfortable with this level of risk.
-If the extended backtesting also proves successful, consider running this EA on a demo account or with a small live account to see how it performs in real-time.
-Even after going live, it's important to monitor the EA's performance and make adjustments as necessary.
It's great that you've shared the EA file. Others in the forum may want to test it as well.
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