zhezhangue/stockprediction

This is a co-worked project for ECE-GY 6143 Introduction to Machine Learning

Stock Price Prediction

This is a co-worked project for ECE-GY 6143 Introduction to Machine Learning Stock price prediction based on machine learning

Teammate names: Zhiming Fan（zf2035）、 Qizhi Xu（qx529）、Rongji Yao（ry1107）、Zhe Zhang（zz3230）

Table of Contents

• Deep Learning Models

  • Long Short Term Memory (LSTM)

• Machine Learning libraries in Python

  • keras
  • numpy
  • Pandas
  • seaborn
  • matplotlib
  • datetime

• Data Set

  • pandas_datareader.data ( Extract yahoo finance data of historical stock )

• Simulation Stock Prediction

  In this lab, we select APPLE, GOOGLE, MICROSOFT, AMAZON, AAL, CYCEY, TSLA as data samples from Yahoo finance, the dataframe contains elements : High, Low, Open, Close, Volume, Ad Close, company_name.

• APPLE, GOOGLE, MICROSOFT, AMAZON are the most essential stocks because they are technology companies.

• AAL, CYCEY, TSLA are industry groups.

• Historical Closing Prices

• Total Volume of Being traded per day

• Moving Average of various stocks

• Daily returns

• Correlation of daily returns between TSLA and AMAZON

• Pair Plot from DataFrames

• Pair Scatter Plot from DataFrames

• Correlation Plot of daily returns

• Correlation Plot of closing price

• Correlation between risk and expected returns

• Prediction Result of RYCEY