Mario J. Pinheiro's Projects
This includes a notebook on how to implement Quantitative Strategies, specifically the Pairs Trading Algorithm.
Core smart contracts
An open source simulated options brokerage and UI for paper trading, algorithmic interfaces and backtesting.
A simple program to simulate attraction/reuplsion forces between many particles
A Peer-to-Peer Lending Robo-Advisor Using a Neural Network (Probability of Default) and a Random Forest Regression (Annualized Returns)
Collection of codes to simulate physical phenomena and econophysics
Vectorized Plasma PIC code (Python)
A fully-functional but succinct Particle-In-Cell Plasma Simulation codebase with several parallel implementations (MPI, OpenMP, SSE, CUDA). This code is meant to highlight the core PIC algorithms, especially issues around parallelization, by implementing a minimal number of features in favor of clarity, ease of use, and extensibility.
Pipeline Extension for Live Trading
Get Philippines stock exchange (PSE) publicly traded companies and market historical price.
A stock market back-tester for algorithmic trading built in Python.
Python live trade execution library with zipline interface.
Library to extract publicly available real-time and historical data from NSE website.
Code for How To Create A Fully Automated AI Based Trading System Withย Python
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.
Web portal of Quantum Open Source Foundation
A Commission-Free Algo Trading Bot By Machine Learning Company SEC Filing Language
QuTiP: Quantum Toolbox in Python
A collection of IPython notebooks using QuTiP: examples, tutorials, development test, etc.
radioactivity decay period
High Frequency Intraday Trading
Download NIFTY historic data and calculate Calmar Ratio, Sortino Ratio, Sterling ratio, Sharpe Ratio, Treynor ratio, Jensens alpha, Information ratio, Appraisal ratio, Tracking error, Max drawdown, Average drawdown. Select the best stocks based on Risk Adjusted Return and other parameters like debt to equity, insider holding, profit margin etc.
An RL model that uses double deep Q learning to generate an optimal policy of stock market trades
An environment to high-frequency trading agents under reinforcement learning
Automated trading on Robinhood via RNN
Another attempt to use Deep-Learning in the financial markets