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shivrajld/README.md

Shivraj Dharwad

I am focused on quantitative finance, derivatives, portfolio construction, risk management, and machine learning for asset management. My work is mostly Python, C++, Excel modeling, and applied statistical methods.

This GitHub is organized as a portfolio of projects I built across pricing, risk, time series, private markets, and AI. The repositories below are the best place to start.

Featured Work

qflib

C++ quantitative finance library with Python bindings for derivatives pricing, Monte Carlo simulation, PDE solvers, yield curves, volatility curves, and delta hedging.

Repository

JPMC Evergreen Private Funds Capstone

Capstone project on evergreen private funds, public SEC filing data, synthetic private market indices, performance analysis, and illiquidity aware portfolio allocation.

Repository

AI in Asset Management Research

Applied AI and mathematical finance studies covering Black Litterman allocation, PSO option pricing, knowledge graphs, causal DAGs, financial NLP, reinforcement learning, LDA, and Naive Bayes.

Repository

Risk Management CVA and VaR Models

Counterparty credit risk project covering FX exposure profiles, interest rate swap exposure, CVA, sensitivity analysis, historical simulation VaR, CDS hedges, vega hedges, and PCA swap curve scenarios.

Repository

DCC GARCH Portfolio Optimization

Time series project comparing DCC GARCH and CCC GARCH covariance forecasts for SPY and TLT minimum variance portfolios, with rolling out of sample tests and Diebold Mariano comparisons.

Repository

Quantitative Portfolio Risk Methods

Excel based portfolio construction model using factor regressions, historical simulation, mean variance optimization, inverse volatility risk parity, total risk contribution, VaR, and CVaR.

Repository

Technical Areas

  • Derivatives pricing: Black Scholes, binomial trees, Longstaff Schwartz, Monte Carlo, PDE methods, stochastic calculus
  • Risk management: VaR, CVaR, CVA, exposure profiles, hedge VaR, scenario generation
  • Portfolio construction: mean variance optimization, Black Litterman, risk parity, factor models
  • Time series: GARCH, DCC, volatility forecasting, rolling out of sample evaluation
  • Machine learning: NLP, LDA, Naive Bayes, causal graphs, knowledge graphs, reinforcement learning
  • Tools: Python, C++, CMake, Jupyter, pandas, NumPy, SciPy, scikit learn, Excel

Current Focus

I am building toward quant research, quant development, and asset management roles where strong implementation and financial modeling judgment both matter.

Pinned Loading

  1. qflib qflib Public

    C++ quantitative finance library for derivatives pricing with Monte Carlo, PDE solvers, and Python bindings

    C++

  2. jpmc-evergreen-private-funds jpmc-evergreen-private-funds Public

    JPMC capstone on evergreen private funds, synthetic private market indices, and illiquidity-aware portfolio allocation

    Jupyter Notebook

  3. dcc-garch-portfolio-optimization dcc-garch-portfolio-optimization Public

    DCC GARCH and CCC GARCH covariance forecasting for SPY TLT minimum variance portfolios

    Jupyter Notebook

  4. ai-asset-management-research ai-asset-management-research Public

    AI and mathematical finance research for asset management, portfolio construction, NLP networks, causal graphs, reinforcement learning, and option pricing

    Jupyter Notebook

  5. quant-methods-portfolio-risk quant-methods-portfolio-risk Public

    Quantitative portfolio risk model using factor regressions, historical simulation, MVO, risk parity, VaR, and CVaR

    Python

  6. risk-management-cva-var risk-management-cva-var Public

    Risk management models for exposure simulation, CVA, hedge VaR, and PCA swap curve scenarios

    Jupyter Notebook