dppalomar
Professor of Optimization, Hong Kong University of Science and Technology (HKUST)
Hong Kong Univ. of Sci&Tech (HKUST)Clear Water Bay, Hong Kong
Pinned Repositories
fitHeavyTail
Mean and Covariance Matrix Estimation under Heavy Tails
riskparity.py
Fast and scalable construction of risk parity portfolios
spectralGraphTopology
Structured Graph Learning via Laplacian Spectral Constraints (NeurIPS 2019)
covFactorModel
Covariance Matrix Estimation via Factor Models
highOrderPortfolios
Design of High-Order Portfolios via Mean, Variance, Skewness, and Kurtosis
imputeFin
Imputation of Financial Time Series with Missing Values and/or Outliers
pob
Supporting data package for the Portfolio Optimization Book
portfolioBacktest
Automated Backtesting of Portfolios over Multiple Datasets
riskParityPortfolio
Design of Risk Parity Portfolios
sparseIndexTracking
Design of Portfolio of Stocks to Track an Index
dppalomar's Repositories
dppalomar/riskParityPortfolio
Design of Risk Parity Portfolios
dppalomar/portfolioBacktest
Automated Backtesting of Portfolios over Multiple Datasets
dppalomar/sparseIndexTracking
Design of Portfolio of Stocks to Track an Index
dppalomar/covFactorModel
Covariance Matrix Estimation via Factor Models
dppalomar/imputeFin
Imputation of Financial Time Series with Missing Values and/or Outliers
dppalomar/highOrderPortfolios
Design of High-Order Portfolios via Mean, Variance, Skewness, and Kurtosis
dppalomar/pob
Supporting data package for the Portfolio Optimization Book
dppalomar/sparseEigen
Computation of Sparse Eigenvectors of a Matrix
dppalomar/deepdow
Portfolio optimization with deep learning.
dppalomar/spectralGraphTopology
Learning Graphs from Data via Spectral Constraints for k-component, bipartite, and k-component bipartite graphs
dppalomar/dppalomar