public void Calculate()
{
double summary = 0;
foreach (var pair in pairs)
{
var regression = new LinearRegression();
regression.Compute(pair.DeltaValues.ToDecimal(), synthIndex.ToDecimal());
pair.Weight = 1 / (1 + Math.Abs(regression.Beta.ToDouble()));
summary += pair.Weight;
}
foreach (var pair in pairs)
{
pair.Weight = pair.Weight / summary;
pair.TradeVolume = Balance * pair.Weight;
}
foreach (var pair in pairs)
{
double beta = pair.Regression.Beta.ToDouble();
double weight = 1.0 / (1.0 + Math.Abs(beta));
pair.X.TradeVolume = pair.TradeVolume * (weight * Math.Abs(beta));
pair.Y.TradeVolume = pair.TradeVolume * weight;
}
}
public void LinearTest()
{
decimal[] x = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
decimal[] y = { 8, 6, 10, 6, 10, 13, 9, 11, 15, 17 };
var lr = new LinearRegression();
lr.Compute(y, x);
Assert.AreEqual(0.8141, (double)lr.RValue, 0.0001);
Assert.AreEqual(0.6628, (double)lr.RSquared, 0.0001);
Assert.AreEqual(5.1333, (double)lr.Alpha, 0.0001);
Assert.AreEqual(0.9757, (double)lr.Beta, 0.0001);
}
public void ComputeTest()
{
double[] x = new double[]
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
};
double[] y = new double[]
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
};
var result = LinearRegression.Compute(x, y);
Assert.AreEqual(result.Intercept, 0.0);
Assert.AreEqual(result.Slope, 1.0);
Assert.AreEqual(result.CorrelationCoefficient, 1.0);
Assert.AreEqual(result.SquareStandardError, 0.0);
}
protected void SetRegression(double[] x, double[] y)
{
Regression = new LinearRegression();
Regression.Compute(x.ToDecimal(), y.ToDecimal());
}
public double Evaluate(IChromosome chromosome)
{
var genes = chromosome.GetGenes();
List <Point> getPointList = new List <Point>();
for (int i = 0; i < genes.Length; i++)
{
if ((int)genes[i].Value == 1)
{
getPointList.Add(pointArr[i]);
}
}
if (getPointList.Count <= 1)
{
return(double.MinValue);
}
double Score = Math.Pow(10, -getPointList.Count); //KS:使得取到的点越多越好
//Console.Write(""+ Score+" "+getPointList.Count+" ");
decimal[] x = new decimal[getPointList.Count];
decimal[] y = new decimal[getPointList.Count];
decimal diffx = 0;
decimal diffy = 0;
for (int i = 0; i < getPointList.Count; i++)
{
x[i] = getPointList[i].X;
y[i] = getPointList[i].Y;
//Console.Write(" x:"+x[i]+" y:"+y[i] );
if (i >= 1)
{
diffx += Math.Abs(x[i] - x[i - 1]);
diffy += Math.Abs(y[i] - y[i - 1]);
}
}
//KS:防止斜率为0或者无穷大
if (diffx <= 1E-5m || diffy <= 1E-5m)
{
return(-Score * MinLimitScoreRadio);
}
lr = new LinearRegression();
lr.Compute(y, x);
var b = lr.Alpha;
var k = lr.Beta;
decimal total = 0;
for (int i = 0; i < getPointList.Count; i++)
{
decimal temp = (getPointList[i].X * k + b) - getPointList[i].Y;
total += temp * temp;
}
/* double RSquared = (double)lr.RSquared;
* Console.WriteLine(" " + lr.RSquared + " " + lr.RValue);*/
Score = Score * Math.Max((double)total, MinLimitScoreRadio);
return(-Score);
}
