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MULTIVARIATE CHANGE OF MEASURE AS CORRECTION METHOD IN ETHICAL PRICING LOI DAMOUR BIZIMANAA Thesis in The Department of Mathematics and StatisticsPresented in Partial Fulfillment of the Requirements
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How to fill out multivariate change of measure

01
Identify the random variables involved in your multivariate analysis.
02
Determine the joint distribution of the variables you want to study.
03
Select the target measure you wish to change to, based on your analysis needs.
04
Establish the relationship between the original measure and the new measure using a change of measure formula.
05
Compute the likelihood ratio of the new measure relative to the original measure.
06
Apply the likelihood ratio to transform the joint distribution into the new measure.
07
Verify the transformation by checking if all required properties hold under the new measure.

Who needs multivariate change of measure?

01
Statistical analysts who work with multivariate distributions.
02
Researchers conducting studies involving multiple interdependent variables.
03
Financial analysts assessing risk in multi-asset portfolios.
04
Data scientists needing to model complex dependencies in their datasets.
05
Professionals in fields requiring advanced statistical modeling techniques.
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Multivariate change of measure is a statistical technique used to adjust the probability measure of a multivariate random variable to account for changes in the underlying distribution or to reflect certain conditions.
Typically, entities or individuals engaged in financial or statistical analysis that involve multivariate distributions may be required to file multivariate change of measure, depending on regulatory requirements.
Filling out a multivariate change of measure involves specifying the original distribution, the new distribution, and the parameters necessary to describe both distributions, along with any relevant data or calculations.
The purpose of multivariate change of measure is to facilitate the analysis of multivariate systems under different circumstances by enabling the comparison of different probability measures.
Information that must be reported includes the original and new measures, relevant statistical parameters, observational data, and any assumptions made during the analysis.
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