Correcting checkstyle issues.
@@ -27,8 +27,7 @@ public class MertonModel implements CharacteristicFunctionModel{
private final double jumpSizeStdDev;
/**
- * Construct a Merton jump diffusion model with discount curves for the forward price
- * (i.e. repo rate minus dividend yield) and for discounting.
+ * Construct a Merton jump diffusion model with discount curves for the forward price (i.e. repo rate minus dividend yield) and for discounting.
*
* @param initialValue
* @param discountCurveForForwardRate
@@ -55,8 +54,7 @@ public class MertonModel implements CharacteristicFunctionModel{
}
/**
- * Construct a Merton jump diffusion model with constant rates for the forward price
- * (i.e. repo rate minus dividend yield) and for the discount curve.
+ * Construct a Merton jump diffusion model with constant rates for the forward price (i.e. repo rate minus dividend yield) and for the discount curve.
*
* @param initialValue
* @param riskFreeRate
@@ -91,8 +89,7 @@ public class MertonModel implements CharacteristicFunctionModel{
* @param jumpSizeMean
* @param jumpSizeStdDev
*/
- public MertonModel(double initialValue, double riskFreeRate,
- double volatility,
+ public MertonModel(double initialValue, double riskFreeRate, double volatility,
double jumpIntensity, double jumpSizeMean, double jumpSizeStdDev) {
this(initialValue,riskFreeRate,volatility,jumpIntensity,jumpSizeMean,jumpSizeStdDev,riskFreeRate);
}
@@ -109,10 +106,8 @@ public class MertonModel implements CharacteristicFunctionModel{
.add(iargument.multiply(iargument.multiply(jumpSizeStdDev*jumpSizeStdDev/2.0)));
Complex jumpTransform = ((exponent.exp()).subtract(1.0)).multiply(jumpIntensity*time);
- //phiJ_u = lambda*(exp(1i*u*alpha_j-0.5*u.*u*sigma_j^2)-1);
- //phiJ_i = lambda*(exp(alpha_j+0.5*sigma_j^2)-1);
- double jumpTransformCompensator = jumpIntensity*time*(Math.exp(transformedMean+jumpSizeStdDev*jumpSizeStdDev/2.0)-1.0);
+ double jumpTransformCompensator = jumpIntensity*time*(Math.exp(transformedMean+jumpSizeStdDev*jumpSizeStdDev/2.0)-1.0);
return iargument
.multiply(
