org.drip.portfolioconstruction.bayesian

Class BlackLittermanCombinationEngine

java.lang.Object

org.drip.portfolioconstruction.bayesian.BlackLittermanCombinationEngine

public class BlackLittermanCombinationEngine
extends java.lang.Object

BlackLittermanCombinationEngine implements the Engine that generates the Combined/Posterior Distributions from the Prior and the Conditional Joint R^1 Multivariate Normal Distributions. The References are: - He. G., and R. Litterman (1999): The Intuition behind the Black-Litterman Model Portfolios, Goldman Sachs Asset Management - Idzorek, T. (2005): A Step-by-Step Guide to the Black-Litterman Model: Incorporating User-Specified Confidence Levels, Ibbotson Associates, Chicago

Author:

Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor and Description
BlackLittermanCombinationEngine(ForwardReverseOptimizationOutput frooUnadjusted, PriorControlSpecification pcs, ProjectionSpecification ps) BlackLittermanCombinationEngine Construction

Method Summary

Modifier and Type	Method and Description
BlackLittermanCustomConfidenceOutput	customConfidenceRun() Conduct a Black Litterman Run using a Theil-like Mixed Model Estimator Using the specified Confidence Level
BlackLittermanOutput	fullConfidenceRun() Conduct a Black Litterman Run using a Theil-like Mixed Model Estimator For 100% Confidence in the Projection
ProjectionImpliedConfidenceOutput	impliedConfidenceRun() Compute the Idzorek Implied Projection Confidence Level
BlackLittermanOutput	noConfidenceRun() Conduct a Black Litterman Run using a Theil-like Mixed Model Estimator For 0% Confidence in the Projection
ProjectionExposure	projectionExposureAttribution() Compute the Exposure Loadings Attribution on a per-Projection Basis
R1ToR1	tiltDepartureR1ToR1(double[] adblUserConfidenceProjectionTilt, int iProjectionIndex, boolean bDerivative) Generate the Squared Tilt Departure R^1 To R^1
double	tiltMismatch(double[] adblUserConfidenceProjectionTilt, int iProjectionIndex, double dblProjectionVariance) Compute the Mismatch between the User Specified Projection and the Custom Confidence Implied Tilts
double[][]	userConfidenceProjectionTilt(double[] adblUserSpecifiedProjectionConfidence) Compute the Idzorek Implied Tilt from the User Projection Confidence Level

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BlackLittermanCombinationEngine

public BlackLittermanCombinationEngine(ForwardReverseOptimizationOutput frooUnadjusted,
                                       PriorControlSpecification pcs,
                                       ProjectionSpecification ps)
                                throws java.lang.Exception

BlackLittermanCombinationEngine Construction

Parameters:

frooUnadjusted - The Unadjusted Instance of FROO

pcs - The Prior Control Specification Instance

ps - The View Projection Specification Settings

Throws:

java.lang.Exception - Thrown if the Inputs are Invalid

Method Detail

noConfidenceRun

public BlackLittermanOutput noConfidenceRun()

Conduct a Black Litterman Run using a Theil-like Mixed Model Estimator For 0% Confidence in the Projection

Returns:

Output of the Black Litterman Run

customConfidenceRun

public BlackLittermanCustomConfidenceOutput customConfidenceRun()

Conduct a Black Litterman Run using a Theil-like Mixed Model Estimator Using the specified Confidence Level

Returns:

Output of the Black Litterman Run

fullConfidenceRun

public BlackLittermanOutput fullConfidenceRun()

Conduct a Black Litterman Run using a Theil-like Mixed Model Estimator For 100% Confidence in the Projection

Returns:

Output of the Black Litterman Run

impliedConfidenceRun

public ProjectionImpliedConfidenceOutput impliedConfidenceRun()

Compute the Idzorek Implied Projection Confidence Level

Returns:

The Idzorek Implied Projection Confidence Level

projectionExposureAttribution

public ProjectionExposure projectionExposureAttribution()

Compute the Exposure Loadings Attribution on a per-Projection Basis

Returns:

The Exposure Loadings Attribution on a per-Projection Basis

userConfidenceProjectionTilt

public double[][] userConfidenceProjectionTilt(double[] adblUserSpecifiedProjectionConfidence)

Compute the Idzorek Implied Tilt from the User Projection Confidence Level

Parameters:

adblUserSpecifiedProjectionConfidence - Array of User-specified Projection Confidence

Returns:

The Idzorek Implied Tilt from the Projection Confidence Level

tiltMismatch

public double tiltMismatch(double[] adblUserConfidenceProjectionTilt,
                           int iProjectionIndex,
                           double dblProjectionVariance)
                    throws java.lang.Exception

Compute the Mismatch between the User Specified Projection and the Custom Confidence Implied Tilts

Parameters:

adblUserConfidenceProjectionTilt - Array of the User Confidence induced Projection Tilts

iProjectionIndex - The Index into the Projection Meta

dblProjectionVariance - The Projection Variance

Returns:

The Squared Mismatch

Throws:

java.lang.Exception - Thrown if the Squared Mismatch cannot be calculated

tiltDepartureR1ToR1

public R1ToR1 tiltDepartureR1ToR1(double[] adblUserConfidenceProjectionTilt,
                                  int iProjectionIndex,
                                  boolean bDerivative)

Generate the Squared Tilt Departure R^1 To R^1

Parameters:

adblUserConfidenceProjectionTilt - Array of the User Confidence induced Projection Tilts

iProjectionIndex - The Index into the Projection Meta

bDerivative - TRUE - Generate the Derivative of the Tilt Departure

Returns:

The Squared Tilt Departure R^1 To R^1