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The significance of the numbers in the Forex Smart EA test report

 Any trade can be tested on historical data After the test is completed, the summary results forexrebateindonesia some features will be displayed Forex rebate king the report tab Report allows for comparison of different smart Forexrebateking, for the same and different input data of smart trades for comparison This article will analyze in detail the significance of the cashbackinforexs in the test report Test results report examples of the following parties Test report results for example to analyze:        To cashback forexTrades–TotalTrades;ProfitTrades–TotalWinTrades;LossTrades–Loss TotalTrades–GrossProfit–TotalNetWinTrades;GrossLoss–TotalNetLossTrades. To some extent from the initial balance shows a reduction in the original value: AbsoluteDrawDown=InitialDeposit-MinimalBalance the maximum difference between the maximum borrowing value and the current minimum borrowing value: MaximalDrawDown=Maxof(MaximalPeak- nextMinimalPeak)The basic state of the maximum borrowing value tested is given at the bottom of the chartThe total maximum borrowing value is marked with a thick arrow    The ratio of the maximum borrowing percentage is equal to the quotient of the maximum borrowing and its respective value: MaxDrawDown%=MaxDrawDown/ itsMaxPeak*100% other results shown in the report can be calculated by applying simple mathematical methods Totaltrades–the total number of transactions in the test; Shortpositions(won%)–the total amount of short sale positions and the percentage of winnings therein (short sale positions/total short sale positions*100%). Longpositions(won%)–the total amount of call positions and the percentage of winnings therein (call positions/total call positions*100%); Profittrades(%oftotal)–the total number of winning trades and the percentage of total trades (winning trades/total trades*100%). Losstrades(%oftotal)–percentage of total number of losing trades and total number of trades (losing trades/total number of trades*100%); Largestprofittrade–maximum winnings obtained in winning trades; Largestlosstrade–maximum winnings obtained in losing trades winnings; Averageprofittrade–the average number of winnings in winning trades (net winnings value/winning trades); Averagelosstrade–the average number of losses in losing trades (net loss value/loss trades); Maximumconsecutivewins( profitinmoney)–themaximumconsecutiveprofitinthisseriesoftotalwinsandtransactionsofwinningseries;Maximumconsecutivelosses(lossinmoney)–themaximumconsecutivelossesinthisseriesoftotallossesandtransactionsoflosseseries. Maximalconsecutiveprofit(countofwins)–themaximumconsecutivelosses(countoflosses)–themaximumconsecutivelosses in the total number of transactions. Averageconsecutivewins–theaverage number of consecutive profits in the winning series; Averageconsecutivelosses–theaverage number of consecutive losses in the losing series. The following colors are applied in the model schematic The following colors are applied in the following schematic: Bright green - intra-minute model, labeled 7 in the figure Slightly darker green– shows the large time range of the model, from M5 to H4 Pink - fully irregular fragmented model Labeled 2 in the figure Gray - original model, labeled 1 in the figure The color schematic above is calculated according to the original model data. Barsintest=4190;StartBar=2371;StartGen(H4)=3042(marked as 3 in the figure);StartH1=3355(marked as 4 in the figure);StartM30=3841(marked as 5 in the figure);StartM15=3891(marked as 6 in the figure);StartM5=0 (not labeled in the figure); StartM1=3917. From these values and the formula of the model above, the following results are obtained: ((0.25*(3042-2371)+0.5*(3917-3042)+0.9*(4190-3917))/(4190-2371))*100%=((0.25*671+0.5*875 +0.9*273)/1819)*100%=46.78%
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