We present here a new way of building vine copulas that allows us to create a vast number of new vine copulas, allowing for more precise modeling in high dimensions. To deal with this great number of copulas we present a new efficient selection methodology using a lattice structure on the vine set. Our model allows for a lot of degrees of freedom, but further improvements face numerous problems caused by vines' complexity as an estimator in a statistical and computational way, problems that we will expose in this paper. Robust n-variate models would be a great breakthrough for asset risk management in banks and insurance companies.
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Find related papers by JEL classification: D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
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