A sophisticated Monte Carlo simulation engine for analyzing liquidity dynamics and risk management in evergreen private equity funds and semi-liquid alternative investment vehicles. For model and code see notebook.
This project implements a Monte Carlo simulation to model and analyze the liquidity dynamics of an evergreen-style private equity fund. The simulation accounts for various factors including subscriptions, redemptions, deal cash flows, and asset performance to help understand and optimize fund liquidity management.
- Monte Carlo simulation of fund liquidity dynamics
- Comprehensive state variable tracking (Cash, Liquid Buffer, Illiquid Assets, NAV, etc.)
- Stochastic modeling of key variables:
- Subscriptions
- Redemption requests
- Net deal cash flows
- Illiquid asset returns
- Sophisticated cash flow waterfall implementation
- Queue-based gating mechanism
- Revolver debt management
- Liquidity sleeve optimization
- Cash in operating account
- Liquid sleeve (T-bills/money-market)
- Illiquid assets
- Net Asset Value (NAV)
- Revolver balance
- Redemption queue
- Liquidity sleeve target
- Revolver gate limit
The model incorporates several stochastic processes using appropriate distributions:
- LogNormal distributions for subscriptions and redemptions
- Normal distribution for net deal cash flows
- LogNormal distribution for illiquid returns
Future extensions choose more flexible statistical distributions, potentially driven by another system (Macroeconomy -> Market Factors -> Fund Flows -> Fund Waterfall Dynamics)
- Python 3.x
- Jupyter Notebook
- Required Python packages (to be added to requirements.txt)
- Clone this repository
- Install required dependencies
- Open liquidity_sim.ipynb in Jupyter Notebook
The simulation is implemented in a Jupyter notebook (liquidity_sim.ipynb). The notebook contains:
- Detailed model documentation
- Implementation of the simulation logic using Pydantic for data validation
- Visualization of results
- Analysis of key metrics
- Asset Performance & Interest Accrual
- Cash Flow Processing
- Queue-based Gating
- Cash Flow Waterfall Implementation
- Surplus Management
- Revolver Debt Management
- Liquidity Sleeve Optimization
- Model fund profit structure w/ high-water mark
- Refactor the codebase to make modular
- Optimize for performance w/ JIT-compilation w/ PyTorch or Numba
- Explore AD-compatability
- Write unit-tests
- Implement CI/CD using Github Actions
- Write convenience functions for dashboard use
This project is licensed under the terms included in the LICENSE file.
David Leather
Contributions are welcome! Please feel free to submit a Pull Request.