Package org.drip.execution.bayesian

Class PriorDriftDistribution

java.lang.Object

org.drip.measure.continuous.R1Univariate

org.drip.measure.gaussian.R1UnivariateNormal

org.drip.execution.bayesian.PriorDriftDistribution

public class PriorDriftDistribution
extends R1UnivariateNormal

PriorDriftDistribution holds the Prior Belief Distribution associated with the Directional Drift. The References are:

• Bertsimas, D., and A. W. Lo (1998): Optimal Control of Execution Costs Journal of Financial Markets 1 1-50
• Almgren, R., and N. Chriss (2000): Optimal Execution of Portfolio Transactions Journal of Risk 3 (2) 5-39
• Brunnermeier, L. K., and L. H. Pedersen (2005): Predatory Trading Journal of Finance 60 (4) 1825-1863
• Almgren, R., and J. Lorenz (2006): Bayesian Adaptive Trading with a Daily Cycle Journal of Trading 1 (4) 38-46
• Kissell, R., and R. Malamut (2007): Algorithmic Decision Making Framework Journal of Trading 1 (1) 12-21

• Module = Product Core Module
• Library = Transaction Cost Analytics
• Project = Optimal Impact/Capture Based Trading Trajectories - Deterministic, Stochastic, Static, and Dynamic
• Package = Bayesian Price Based Optimal Execution

Author:

Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor	Description
PriorDriftDistribution(double dblExpectation, double dblConfidence)	Construct an Instance of Prior Drift Distribution

Method Summary

Modifier and Type	Method	Description
double	confidence()	Retrieve the Confidence of the Prior Drift Distribution
double	expectation()	Retrieve the Expectation of the Prior Drift Distribution
double[]	realizedDrift(int iNumRealization)	Generate the given Number of Bayesian Drift Realizations

Methods inherited from class org.drip.measure.gaussian.R1UnivariateNormal

confidence, confidenceInterval, cumulative, density, errorFunction, histogram, incremental, invCumulative, mean, median, mode, random, sigma, Standard, support, variance

Methods inherited from class org.drip.measure.continuous.R1Univariate

bPOE, centralMoment, cvar, differentialEntropy, excessKurtosis, expectedShortfall, fisherInformation, iqr, kullbackLeiblerDivergence, momentGeneratingFunction, nonCentralMoment, populationCentralMeasures, probabilityGeneratingFunction, quantile, randomArray, skewness, supported, tukeyAnomaly, tukeyCriterion

Methods inherited from class java.lang.Object

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

Constructor Details

PriorDriftDistribution

public PriorDriftDistribution(double dblExpectation,
double dblConfidence)
                       throws java.lang.Exception

Construct an Instance of Prior Drift Distribution

Parameters:

dblExpectation - Expectation of the Prior Drift

dblConfidence - Confidence of the Prior Drift

Throws:

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

Method Details

expectation

public double expectation()

Retrieve the Expectation of the Prior Drift Distribution

Returns:

The Expectation of the Prior Drift Distribution

confidence

public double confidence()

Retrieve the Confidence of the Prior Drift Distribution

Returns:

The Confidence of the Prior Drift Distribution

realizedDrift

public double[] realizedDrift(int iNumRealization)

Generate the given Number of Bayesian Drift Realizations

Parameters:

iNumRealization - The Number of Realizations to be generated

Returns:

Array of the Drift Realizations