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High-dimensional Portfolio Optimization using Joint Shrinkage
We consider the problem of optimizing a portfolio of financial assets, where the number of assets can be much larger than the number of observations.
Bayesian inference in high-dimensional models
Bayesian methods have been proposed for such problems more recently, where the prior takes care of the sparsity structure.
Bayesian Inference
Statistics Theory
Statistics Theory
Change-point Analysis in Financial Networks
In this paper, we use sequential change point detection in dynamic networks to detect changes in the network characteristics of thirteen stock markets across the globe.
Statistical Finance Applications
