I am Daniel Palomar, a Professor at the Hong Kong University of Science and Technology (HKUST). I work on optimization problems related to financial systems and data analytics in general. My webpage is https://www.danielppalomar.com
Here you'll find repositories that host practical implementations of the research published by the Convex Group. Video presentations are available on YouTube: https://www.youtube.com/danielpalomar.
- spectralGraphTopology: Structured graph learning via Laplacian spectral constraints (NeurIPS 2019) [CRAN]
- sparseGraph: Nonconvex Sparse Graph Learning under Laplacian-structured Graphical Model (NeurIPS 2020)
- fingraph: Graphical Models in Heavy-Tailed Markets (NeurIPS 2021) [CRAN]
- bipartite: Learning Bipartite Graphs: Heavy Tails and Multiple Components (NeurIPS 2022) [CRAN]
- riskParityPortfolio: Design of Risk Parity Portfolios [CRAN] - Listed in Task View on Empirical Finance
- riskparity.py: SCRIP: Successive Convex Optimization Methods for Risk Parity Portfolio Design (IEEE TSP 2015)
- highOrderPortfolios: Design of High-Order Portfolios via Mean, Variance, Skewness, and Kurtosis [CRAN]
- portfolioBacktest: Automated Backtesting of Portfolios over Multiple Datasets [CRAN]
- sparseIndexTracking: Design of Portfolio of Stocks to Track an Index [CRAN]
- intradayModel: Modeling and Forecasting Financial Intraday Signals [CRAN]
- fitHeavyTail: Mean and Covariance Matrix Estimation under Heavy Tails [CRAN]
- imputeFin: Imputation of Financial Time Series with Missing Values [CRAN] - Listed in Task View on Missing Data
- sparseEigen: Computation of Sparse Eigenvectors of a Matrix [CRAN]
- TRexSelector: Performs fast variable selection in high-dimensional settings while controlling the false discovery rate (FDR) at a user-defined target level [CRAN]
- tlars: Computes the solution path of the Terminating-LARS (T-LARS) algorithm [CRAN]