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AnshDani2004/README.md

Ansh Hemang Dani

Quantitative Research · Stochastic Modeling · Statistical Inference

Portfolio LinkedIn

About

CS + Mathematics at Barrett, The Honors College, ASU.

Currently writing an honors thesis on Kelly criterion impossibility under infinite variance.

Building tools at the intersection of probability theory, machine learning, and finance.

Research

🔬 Rough Volatility Neural SDEs Neural SDE framework · deep hedging · fBM simulation

📊 Bayesian Portfolio Optimization HMC/NUTS · LKJ priors · tail-risk capture

Python · C++ · PyTorch · NumPy · SciPy · SQL · R · TypeScript · Docker

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  1. Rough-Volatility-Neural-SDEs Rough-Volatility-Neural-SDEs Public

    Neural SDE framework for rough volatility modeling (H ≈ 0.1) with deep hedging. Implements Davies-Harte fBM, signature-based losses, and convergence analysis.

    Jupyter Notebook

  2. AnshDani2004 AnshDani2004 Public

  3. Hierarchical-Bayesian-Portfolio-Optimization Hierarchical-Bayesian-Portfolio-Optimization Public

    Implemented hierarchical model using Hamiltonian Monte Carlo (NUTS) for covariance estimation with LKJ priors. Superior tail-risk capture vs Mean-Variance optimization.

    Python

  4. LeftoverLink LeftoverLink Public

    Our app, LeftoverLink, is a SwiftUI-based platform that helps students share excess food with others nearby.

    Swift