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ai-for-trading2's Introduction

AI for Trading

Project portfolio of work created while doing the AI for Trading Nano Degree program on Udacity

Setup

Run the following commands to setup environment

# install with conda
conda env create -f quantenv.yml
conda activate quantenv

# install with pip
pip install -r requirements.txt

Start Jupyter Notebook

jupyter notebook

Jupyter Notebooks / Notes

  • Notes
  • Advanced Opt
  • Advanced Portfolio Optimization using cvxpy
  • Autoregression Quiz
  • calculate Returns
  • Clean Forward Returns
  • Covariance Matrix Assets
  • CVXPY Optimize Two Assets
  • Factor Model Asset Return
  • Factor Model Portfolio Return
  • Factor Returns
  • Historical Variance
  • m3l4 Covariance
  • Momentum-dtype
  • Overnight Returns
  • Pairs Candidates
  • PCA Toy Problem
  • PCA Basics
  • PCA Core
  • PCA Factor Model
  • Portfolio Variance
  • Quantiles
  • Rank IC
  • Rank
  • Regression Against Time
  • Regression
  • Resample Data
  • Rolling Windows
  • Sector Neutral
  • Sharpe Ratio
  • Smoothing
  • Stock Data
  • T Test
  • Test Normality
  • Top and Bottom Performing
  • Transfer Coefficient
  • Turnover
  • Zipline Pipeline
  • Z Score
  • Projects
    • Trading with Momentum
    • Breakout Strategy
    • Smart Beta and Portfolio Optimization

ai-for-trading2's People

Contributors

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