Study On The Measurement Precision And Management Of Heavy-tailed Operational Risk Based On LDA

Previous literatures have shown that there is a class of operational risk which lossseverity is the heavy-tailed Distribution.The Extreme Value Distribution Model isoptimal approach to measure the operational risk.Currently,the Loss DistributionApproach is a main approach to measure the operational risk in the industry.Thus,thispaper combines the Extreme Value Distribution Model with the Loss DistributionApproach to discuss the measurement precision and management of heavy-tailedoperational risk.Firstly,the paper analyses the factors which affect the measurementdeviation of heavy-tailed operational risk.Additionally,basing on some certaindemonstration researches and choosing typical heavy-tailed distribution that regards theWeibull distribution and Pareto distribution as loss severity distribution from twoclasses of Extreme Value Distribution Models(BMM and GPD),the paper discusses themeasurement precision and key management parameters of heavy-tailed operational riskat high confidence level,and gives the demonstrations.And an analysis of modelapplication is illustrated with a numerical example.Furthermore,the paper bringsforward a choosing method of the loss severity distribution.Based on theafore-mentioned studies,this paper gets main innovative conclusions as follow.(1) The paper discusses the factors that influence the measurement deviation,andfinds out that the existence of this deviation has objectives.There are two influencefactors:One is sample heterogeneity.In inside and outside pool loss datum,there is notonly the difference threshold,but also the distinctions of internal and externalenvironment lead to the sample heterogeneity,which brings about the measurementdeviation.Secondly,there are distribution model extrapolate problems in themeasurement.The loss datum of heavy-tailed operational risk are rare,as a consequence,there are extrapolate problems when we measure operational risk at high confidencelevel,which lead to uncertainty in measurement results.Because of the above factors,the measurement deviation cannot be ignored.(2) Basing on the deviation of the measurement results of heavy-tailedoperational risk,in Chapter 3,this paper further discusses the measurement precision.Under the Loss Distribution Approach,the confidence intervals' length of Operational VaR represents the measurement precision.After a systematic study of measurementprecision,we have the conclusions as follow.1) The changes of measurement precision' sensitvity of heavy-tailed operationalVaR just relate with the shape parameter and the frequency parameter.Using theelasticity analysis method,and basing on the theory researches of uncertain propagationcoefficients' sensitvity and its changes,we have the conclusions that the changes ofuncertain propagation coefficients' sensitvity just relate with the shape parameter andthe frequency parameter,but do not relate to the scale parameter.As a result,thechanges of measurement precision' sensitvity of operational VaR just relate with theshape parameter and the frequency parameter if we keep other conditions unchanged.2) Using the theory model established in this chapter,the key influencingparameters of measurement precision can be distinguished.With changes of thecharacter parameter,there will be changes in measurement precision and changes in keyinfluencing parameters.The numerical example analysis validates the validity of thistheory model.(3) From the angle of measurement,the character parameters which impact theoperational risk most can be distinguished.As a key management parameter,it leads tothe possibility of the combination of measurement model and management model.Andwe can build the dynamic management system of operational risk and improvemeasurement efficiency.(4) Integrating of the conclusion in chapter 3 and 4,we can conclude that thereare changes of operational VaR and measurement precision with the changes ofcharacter parameters.Therefore,the extraction method of regulatory capital can bemended.And the regulatory capital equal to the lower confidence limit.From the lowerto upper confidence limit regulatory capital is allocated by a risk-free asset,which givesthe financial institutions flexibility to allocate the capital.(5) In Chapter Five,this paper propose a selection method of loss severitydistribution that regards the maximum of the sensitivity of supervised systems ofoperational risk as a choosing standard.