Expert answer:STOCK MARKET PREDICTION USING PYTHON

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Senior project
Weekly Deliverable list
Week 1. Feature generation:
•
Research on different well-known stock market price indices.
•
Understanding the feature of major stock market of the world.
Week 2. Implementation of algorithms:
•
Understand how to develop algorithm for coding and revise classes that deals with algorithm.
Week 3. Feature or model selection:
•
Study different models of prediction and
•
Select the right feature which is more accurate for prediction of the stock market.
Week 4. python programming techniques:
•
Understand different python programming techniques from different websites and books like
“Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and
TensorFlow, 2nd Edition”.
Week 5. Coding:
•
Understand the list of models needed to have python programming run correctly.
•
Understand different python source codes that are close to our project.
Weekly Deliverable 1
1.
Previous week’s work on feature analysis
•
Research on different well-known stock market price indices.
•
Understanding the feature of major stock market of the world.
•
Studying the historical daily price of some selected stocks.
2.
Research was conducted to understand and be familiar with stock market price daily price
movement and factors that affect the future price of the stock. for example, we did our research on the
price of S&P 500.
•
Downloading the historical daily price of major American company’s stock market. The table
below shows the last week price history of S&P 500
Date
Open
High
Low
Close
Adj Close
Volume
10/30/2017
2568.66
3.43E+09
2572.18
2565.58
2569.13
2569.13
10/27/2017
2566.52
2567.4 2544
2557.15
2557.15
3.87E+09
10/26/2017
2560.08
2567.07
2559.8 2560.4 2560.4 3.87E+09
10/25/2017
2570.26
3.89E+09
2582.98
2565.94
2581.07
2581.07
10/24/2017
2577.75
3.66E+09
2580.03
2568.25
2572.83
2572.83
•
We answered the question how we get relevant information out of this features for our
algorithm.
•
All financial institution has deepened interaction to each other.
•
Converting the movement of each daily stock price to binary combination.
3.
Next week’s research will focus on understanding the implementation of algorithms and revise
classes that deals with this particular machine learning.
Website :
Title: Stock Market Prediction Using Python
Take a look at the following web links: (Make sure to look at all the 6 parts)
1) http://francescopochetti.com/stock-market-prediction-part-introduction/
2) http://francescopochetti.com/stock-market-prediction-part-ii-feature-generation/
3) http://francescopochetti.com/part-iii-scikit-classification-algorithms/
4) http://francescopochetti.com/part-iv-modelfeature-selection/
5) http://francescopochetti.com/part-iv-results-test-set/
6) http://francescopochetti.com/part-vii-backtest-portfolio-performance/
…
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