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发表于 2010-10-8 17:14:43 |显示全部楼层

Input:  c1    (0),       { Coefficient of indicator 1 }
      c2    (0),       { Coefficient of indicator 2 }
      c3    (0),       { Coefficient of indicator 3 }
      c4    (0),       { Coefficient of indicator 4 }
      c5    (0),       { Coefficient of indicator 5 }
      c6    (0),       { Coefficient of indicator 6 }
      NMA1    (10),       { Length of moving average 1 }
      NMA2    (50),       { Length of moving average 2 }
      NMA3    (135),       { Length of moving average 3 }
      NATR    (27),       { Period for average true range }
      NRnge (30),       { Period for computing average daily range }
      RngeFr (0.6);       { Fraction of daily range }

Var: SessLen  (0),       { Length in minutes of trading session }
      Time1Thrd(0),       { Time of end of 1st third of session }
      Time2Thrd(0),       { Time of end of 2nd third of session }
      NBarsDay (0),       { Number of bars per day }
      minTrend (0),       { minimum required daily change for "trend" }
      AveCO (0),       { Average close - open }
      ACOPrior (0),       { Value of AveCO on prior day }
      DayRnge  (0),       { Most recent day's close - open }
      DRPrior  (0),       { Prior day's DayRnge }
      MovAve1  (0),       { Value of moving average 1 }
      MA1Prior (0),       { Value of moving average 1 on prior day }
      MovAve2  (0),       { Value of moving average 2 }
      MA2Prior (0),       { Value of moving average 2 on prior day }
      MovAve3  (0),       { Value of moving average 3 }
      MA3Prior (0),       { Value of moving average 3 on prior day }
      ATR    (0),       { Average true range }
      ATRPrior (0),       { Value of ATR on prior day }
      TRPrior  (0),       { Prior day's true range }
      PatVal (0),       { Pattern number }
      PatCount (0),       { Number of occurances of pattern PatID }
      DayCount (0),       { Number of days examined }
      Cond1L (False),    { Condition 1, up trend }
      Cond1S (False),    { Condition 1, down trend }
      Cond2L (False),    { Condition 2, up trend }
      Cond2S (False),    { Condition 2, down trend }
      Cond3L (False),    { Condition 3, up trend }
      Cond3S (False),    { Condition 3, down trend }
      Cond4L (False),    { Condition 4, up trend }
      Cond4S (False),    { Condition 4, down trend }
      Cond5L (False),    { Condition 5, up trend }
      Cond5S (False),    { Condition 5, down trend }
      Cond6L (False),    { Condition 6, up trend }
      Cond6S (False),    { Condition 6, down trend }
      SumCondL (False),    { Summary of conditions for up trend }
      SumCondS (False),    { Summary of conditions for down trend }
      Score (0),       { Accuracy of neural network prediction }
      FalsePos (0),       { Number of false positives: predicted pattern when not present }
      FalseNeg (0);       { Number of false negatives: didn't predict pattern when present }

Array: OThird[3](0),                { Open prices for each third of day }
      HThird[3](0),                { High prices for each third of day }
      LThird[3](99999999),          { Low prices for each third of day }
      CThird[3](0);                { Close prices for each third of day }

{ Calculate indicator values }
ATR = Average(TrueRange, NATR);
MovAve1 = Average(C, NMA1);
MovAve2 = Average(C, NMA2);
MovAve3 = Average(C, NMA3);

{ Initialize some variables on 1st bar }
If BarNumber = 1 then Begin
SessLen = AbsValue(TimeToMinutes(SessionEndTime(0,1)) - TimeToMinutes(SessionStartTime(0,1)));
Time1Thrd = CalcTime(SessionStartTime(0,1), SessLen/3.);
Time2Thrd = CalcTime(SessionStartTime(0,1), (2. * SessLen/3.));

If BarInterval > 0 then
   NBarsDay = SessLen/BarInterval;
End;

{ Calculations on first bar of new day }
If date <> date[1] or BarNumber = 1 then Begin

DayRnge = AbsValue(CloseD(1) - OpenD(1)); { range of prior day }

{ Calculate the minimum required move for a trend based on average daily range }
AveCO = GetAveDayRange(NRnge);
minTrend = RngeFr * AveCO;
{Print("AveCO = ", AveCO, " minTrend = ", minTrend);}

{ Obtain O, H, L, C of each third of day }
Value1 = GetDayThirds(Time1Thrd, Time2Thrd, NBarsDay, OThird, HThird, LThird, CThird);

End;

{ Initialize prior values of indicators }
If BarNumber = 1 then Begin
MA1Prior = MovAve1;
MA2Prior = MovAve2;
MA3Prior = MovAve3;
DRPrior = DayRnge;
ACOPrior = AveCO;
ATRPrior = ATR;
TRPrior = TrueRange;
End;

{ Evaluate indicators to obtain prediction on prior day }
If date <> date[1] then Begin

{ Use indicator values from day prior to one we're trying to predict }
MovAve1 = MA1Prior;
MovAve2 = MA2Prior;
MovAve3 = MA3Prior;
ATR = ATRPrior;

{ Pattern on prior day; we want to predict this }
PatVal = GetTrendPattern(OThird, HThird, LThird, CThird, minTrend);

{ See if we can predict pattern or absence of pattern }
DayCount = DayCount + 1;

If AbsValue(PatVal) > 0 then
   PatCount = PatCount + 1;

{ Construct indicators and evaluate }
Cond1L = TRUE;
Cond1S = TRUE;
If AbsValue(c1) > 0 then Begin
   Cond1L = c1 * (CloseD(2) - MovAve1) > 0;
   Cond1S = -c1 * (CloseD(2) - MovAve1) > 0;
End;

Cond2L = TRUE;
Cond2S = TRUE;
If AbsValue(c2) > 0 then Begin
   Cond2L = c2 * (CloseD(2) - MovAve2) > 0;
   Cond2S = -c2 * (CloseD(2) - MovAve2) > 0;
End;

Cond3L = TRUE;
Cond3S = TRUE;
If AbsValue(c3) > 0 then Begin
   Cond3L = c3 * (CloseD(2) - MovAve3) > 0;
   Cond3S = -c3 * (CloseD(2) - MovAve3) > 0;
End;

Cond4L = TRUE;
Cond4S = TRUE;
If AbsValue(c4) > 0 then Begin
   Cond4L = c4 * (DRPrior - ACOPrior) > 0;
   Cond4S = -c4 * (DRPrior - ACOPrior) > 0;
End;

Cond5L = TRUE;
Cond5S = TRUE;
If AbsValue(c5) > 0 then Begin
   Cond5L = c5 * (CloseD(2) - CloseD(3)) > 0;
   Cond5S = -c5 * (CloseD(2) - CloseD(3)) > 0;
End;

Cond6L = TRUE;
Cond6S = TRUE;
If AbsValue(c6) > 0 then Begin
   { Cond6L = c6 * (TRPrior - ATR) > 0;
   Cond6S = -c6 * (TRPrior - ATR) > 0; }
   Cond6L = c6 * (CloseD(2) - OpenD(2)) > 0;
   Cond6S = -c6 * (CloseD(2) - OpenD(2)) > 0;
End;

SumCondL = Cond1L and Cond2L and Cond3L and Cond4L and Cond5L and Cond6L;
SumCondS = Cond1S and Cond2S and Cond3S and Cond4S and Cond5S and Cond6S;

If PatVal > 0 then Begin             { Long pattern present so see if we predict its presence }
   If SumCondL then
      Score = Score + 1       { Correct prediction }
   Else
      FalseNeg = FalseNeg + 1; { False negative }
End
Else If PatVal < 0 then Begin       { Short pattern present so see if we predict its presence }
   If SumCondS then
      Score = Score + 1       { Correct prediction }
   Else
      FalseNeg = FalseNeg + 1; { False negative }
End
Else Begin                               { Pattern not present, so see if we don't predict it }
   If SumCondL = False and SumCondS = False then
      Score = Score + 1       { Correct prediction }
   Else
      FalsePos = FalsePos + 1; { False positive }
End;
{Print("Date: ", Date[1]:0:0, " Pattern: ", PatVal:0:0); }

{ Calculate indicator values at end of prior day }
MA1Prior = MovAve1[1];
MA2Prior = MovAve2[1];
MA3Prior = MovAve3[1];
ACOPrior = AveCO;
DRPrior = DayRnge;
TRPrior = TrueRange[1];
ATRPrior = ATR[1];
End;

If LastBarOnChart then Begin
If DayCount > 0 then
   Score = 100 * Score/DayCount;
If PatCount > 0 then
   FalseNeg = 100 * FalseNeg/PatCount;
If (DayCount - PatCount) > 0 then
   FalsePos = 100 * FalsePos/(DayCount - PatCount);
Print("FindPrediction (c1 c2 c3 c4 c5 c6 Score FNeg FPos DayCount PatCount):,", c1:0:0, ",", c2:0:0, ",", c3:0:0,
      ",", c4:0:0, ",", c5:0:0, ",", c6:0:0, ",", Score:0:2, ",", FalseNeg:0:1, ",", FalsePos:0:1, ",", DayCount:0:0, ",",
      PatCount:0:0);
End;

请高手会改成TB的

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