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Found 5 papers, 0 papers with code
A Portfolio's Common Causal Conditional Risk-neutral PDE
Portfolio's optimal drivers for diversification are common causes of the constituents' correlations.
Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction
A closed-form solution with least-squares is presented, which to the authors knowledge, is the fastest solution in the literature for multiple hypotheses and structured predictions.
Measuring Cause-Effect with the Variability of the Largest Eigenvalue
By analyzing the time series of the standard deviation of the greatest eigenvalue for $2\times 2$ correlation matrices with different lags we can analyze deviations from the Tracy-Widom distribution to test structural relationships between these two time variables.
A Clustering Algorithm for Correlation Quickest Hub Discovery Mixing Time Evolution and Random Matrix Theory
With our geometric version of the tests via clustering, we can test the hypothesis that we can improve state-of-the-art settings for QHD, by combining QCD and QHD simultaneously, as well as including information about pre-change time-evolution in correlations.
Portfolio Optimization based on Neural Networks Sensitivities from Assets Dynamics respect Common Drivers
Portfolio constituents are embedded into the space of sensitivities with respect to their common drivers, and a distance matrix in this space called the Sensitivity matrix is used to solve the convex optimization for diversification.
