Ezequiel Parini Corominas's repositories
Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
High-Frequency-Trading-Model-with-IB
A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python
machine-learning-for-trading
Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading
RSI-Analysis
The objective is to understand how many companies are above or below a specific threshold to understand the level of overbought or oversold of the companies within a specific index
td-ameritrade-python-api
Unofficial Python API client library for TD Ameritrade
awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
God-Level-Data-Science-ML-Full-Stack
A collection of scientific methods, processes, algorithms, and systems to build stories & models. This roadmap contains 16 Chapters, whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI
gpt-engineer
Specify what you want it to build, the AI asks for clarification, and then builds it.
QuantResearch
Quantitative analysis, strategies and backtests
ByteTrack
ByteTrack: Multi-Object Tracking by Associating Every Detection Box
Deep_Learning_Machine_Learning_Stock
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
Financial-Risk-Management
Code for Financial Risk Management
fromthetransistor
From the Transistor to the Web Browser, a rough outline for a 12 week course
Jupyter-Notebooks
Quantitative Risk Book
Papers
My Quant Research Papers (incl. Coding & Excel Examples)
PiML-Toolbox
PiML (Python Interpretable Machine Learning) toolbox for model development and validation
PyMySQL
Pure Python MySQL Client
Python_Option_Pricing
An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options
Riskfolio-Lib
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
RustBooks
List of Rust books
slimevolleygym
A simple OpenAI Gym environment for single and multi-agent reinforcement learning
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
StudyBook
Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)
systematictradingexamples
Examples of code related to book www.systematictrading.org and blog qoppac.blogspot.com