A list of online resources for quantitative modeling, trading, portfolio management
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Updated
Jun 15, 2024
A list of online resources for quantitative modeling, trading, portfolio management
A Python library for mathematical finance
Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.
Companion code for "Modern Computational Finance: AAD and Parallel Simulations" (Antoine Savine, Wiley, 2018)
Python Financial ENGineering (PyFENG package in PyPI.org)
using the Inverse-Transform method to speed up options pricing simulations in R
A walk through the frameworks of Python in Finance. The repository is currently in the development phase. The finalized version will include a full-fledged integration and utilization of Quantopian, GS-Quant, WRDS API and their relevant datasets and analytics.
Entropy Pooling in Python with a BSD 3-Clause license.
AAD enabled and scripting included derivatives modeling.
A python telegram bot to fetch real-time global financial market indices, latest news articles in the world of finance & business, and articles of math models & finance for algorithmic trading
Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possible, even though certain models have their own Machine Learning Model with assessment and performance.
Financial Engineering in R
A Program to calculate the price of American put or call option with Least Square Monte Carlo
Tools and analytics for smart derivative contracts.
A mathematical model for Fibonacci Retracement and location entry and exit formulation using ML
This project try to bring closer the stochastic calculus and Typescript.
This repository contains some of the implementations related to my master thesis under supervision of Prof Josef Teichmann at ETH Zurich.
Course material for Mathematical and Computational Finance 1
Find arbitrage-free initial price for options in the CRR binomial options pricing model
All code, scripts, and figures for Topological Data Analysis related papers.
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