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cantaro86 avatar

cantaro86/Financial-Models-Numerical-Methods

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6,831 stars·1,216 forks·Jupyter Notebook·AGPL-3.0·20 views

Financial Models Numerical Methods

This project is a quantitative finance library providing implementations of numerical methods for financial engineering. It focuses on derivative pricing, portfolio optimization, stochastic simulation, and volatility calibration.

The library includes tools for calculating option values using Monte Carlo simulations, binomial trees, and Fourier inversion. It provides a framework for fitting volatility smiles to market data and a simulation engine for generating asset price paths via geometric Brownian motion and jump-diffusion models.

The codebase covers broader numerical analysis capabilities, including solvers for partial differential equations, linear equation system solvers, and tools for mean-variance portfolio optimization using quadratic programming. It also includes utilities for cleaning market data and tracking real-time volatility through noise-reduction filters.

The implementation is provided as a collection of interactive notebooks and code.

Features

  • Quantitative Finance & Trading - Provides a comprehensive collection of numerical methods and models for quantitative finance and trading.
  • Portfolio Optimization - Determines optimal asset allocations using quadratic programming and mean-variance optimization.
  • Derivative Pricing Models - Provides mathematical models for computing option values, implied volatility, and risk metrics.
  • Asset Allocation Optimization - Implements mathematical methods for determining optimal asset weights to balance risk and return.
  • Asset Price Path Simulators - Implements stochastic processes like Geometric Brownian Motion to model future asset price movements.
  • Option Pricing Models - Estimates the value of various option types using Monte Carlo simulations and binomial trees.
  • Quadratic Programming Allocation - Provides mathematical optimization of portfolio weights using quadratic functions to manage variance and returns.
  • Financial Parameter Estimation - Estimates time-varying volatility and autocorrelation using linear regression and filtering techniques.
  • Calibration Frameworks - Matches model parameters to market data by fitting volatility smiles through root-finding methods.
  • Numerical Inversion - Pricess options based on characteristic functions using fast Fourier transforms and numerical inversion.
  • Differential Equation Solvers - Provides numerical solvers for partial differential equations to price options and jump-diffusion models.
  • Linear System Solvers - Calculates matrix solutions using decomposition methods and iterative solvers for large equation sets.
  • Volatility Calibration - Fits volatility smiles to market data using root-finding and filtering techniques.

Star history

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How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does cantaro86/financial-models-numerical-methods do?

This project is a quantitative finance library providing implementations of numerical methods for financial engineering. It focuses on derivative pricing, portfolio optimization, stochastic simulation, and volatility calibration.

What are the main features of cantaro86/financial-models-numerical-methods?

The main features of cantaro86/financial-models-numerical-methods are: Quantitative Finance & Trading, Portfolio Optimization, Derivative Pricing Models, Asset Allocation Optimization, Asset Price Path Simulators, Option Pricing Models, Quadratic Programming Allocation, Financial Parameter Estimation.

What are some open-source alternatives to cantaro86/financial-models-numerical-methods?

Open-source alternatives to cantaro86/financial-models-numerical-methods include: google/tf-quant-finance — This is a quantitative finance library built on TensorFlow for financial engineering, asset pricing, and risk… jerbouma/fundamentalanalysis — FundamentalAnalysis is a comprehensive financial analysis library, quantitative finance framework, and macroeconomic… jerbouma/financetoolkit — The FinanceToolkit is an open-source Python library for quantitative finance that provides a unified framework for… fincept-corporation/finceptterminal — FinceptTerminal is a quantitative finance platform and financial engineering library designed for asset valuation,… llmquant/quant-wiki — quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering,… letianzj/quantresearch — QuantResearch is a quantitative research framework and specialized toolkit for algorithmic simulation, financial…

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