Large-scale financial collateral optimization using the Primal-Dual Hybrid Gradient (PDHG / Chambolle-Pock) algorithm implemented in JAX
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Updated
Feb 16, 2026 - Python
Large-scale financial collateral optimization using the Primal-Dual Hybrid Gradient (PDHG / Chambolle-Pock) algorithm implemented in JAX
Passive index replication of the NASDAQ-100 using Mixed Integer Programming that selects an optimal 25-asset fund from 97 equities to maximise correlation-weighted similarity across rolling market regimes.
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