Pinned Repositories
2019-datascience-lectures
Lecture content for 2019 course.
Adv_Fin_ML_Exercises
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
Advanced-Deep-Trading
Mostly experiments based on "Advances in financial machine learning" book
AeroPy
Python interface for XFOIL. The objective of this library is to be able to be able to call XFOIL from Python iteratively for any simulation in a total of 4 lines total.
agency-loan-level
Loan-level analysis of Fannie Mae and Freddie Mac data
AIAlpha
Use unsupervised and supervised learning to predict stocks
aidoom.github.io
test
test
tnet's Repositories
tnet/AIAlpha
Use unsupervised and supervised learning to predict stocks
tnet/BMC
Notes on Scientific Computing for Biomechanics and Motor Control
tnet/Disciplined-Kalman-Filter-Implementation-in-Python
This code implements the Kalman filter in Python by using an object oriented approach.
tnet/ECM-in-python
I implement and test an ECM on JP Morgan's stock and the S&P500
tnet/Econometrics-With-Python
Tutorials of econometrics featuring Python programming. This is a crash course for reviewing the most important concepts and techniques of basic econometrics, the theories are presented lightly without hustles of derivation and Python codes are straightforward.
tnet/epcalc
Epidemic Calculator
tnet/Financial-Machine-Learning-Articles
Contains the code for my financial machine learning articles
tnet/fracdiff
Moved Permanently: https://github.com/fracdiff/fracdiff
tnet/fractional_differencing_gpu
Rapid large-scale fractional differencing with RAPIDS to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.
tnet/gabgoh.github.io
COVID online calculator git http://gabgoh.github.io/COVID/index.html
tnet/go
The Open Source Data Science Masters
tnet/gQuant
A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.
tnet/GradBoost
GradBoost takes in a regression model with methods .fit(X, y) and .predict(X), a set of testing X data to be predicted, training X and y data to fit on, and returns a tuple of the predicted y-values for the training data and testing data. The boosting rounds and learning rate are adjustable. The flexibility of model choice allows custom loss functions for the weak learners.
tnet/gs-quant
Python toolkit for quantitative finance
tnet/MarketAnalysis
Portfolio Theory, Options Theory, & Quant Finance
tnet/mlfinlab
tnet/mlfinlab-1
tnet/Money-Weighted-Return
Money-weighted return calculator in Python
tnet/nltk
NLTK Source
tnet/PerformanceAnalytics
Performance Anayltics for Investment Portfolios
tnet/PortfolioLab
tnet/PyCaret-Example
tnet/pyqstrat
A fast, extensible, transparent python library for backtesting quantitative strategies.
tnet/qlib
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
tnet/quantstats
Portfolio analytics for quants, written in Python
tnet/Riskfolio-Lib
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
tnet/stock-trading-ml
A stock trading bot that uses machine learning to make price predictions.
tnet/stock_cnn_blog_pub
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"
tnet/Stocks
Programs for stock prediction and evaluation
tnet/vaderSentiment
VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.