Team members
Selina Sun, Shiyu Han, Zhiheng liu
Inspiration
We want to understand the growth of one of the world’s IT giants (Indian IT industry) by conducting data analysis and machine learning. We want to learn more about trading algorithms and the applications of machine learning in the financial market All group members are pursuing major pertaining to this topic so this project will be beneficial for a future career path.
What it does
It does data analysis to address three research questions. 1) How do the stock close prices and volumes for HCLTECH change over time? Is there a correlation between the close prices and volumes of the IT stocks? 2) What changes can be observed in the entire IT industry from 2010 to 2018? How do the performance of IT stocks compare with other stocks in the NIFTY 50 index? 3) Is Long Short-Term Memory (LSTM) a good model for stock price prediction?
How we built it
We use python 3.7 as well as many python libraries, including tensorflow, pandas, plotly, etc. to write programs and get the results.
Challenges we ran into
We had challenges in installing the TensorFlow library and learning the new machine learning model: LSTM.
Accomplishments that we're proud of
We successfully plotted the graphs wanted and examined the accuracy of LSTM model.
What we learned
We learned new libraries for python as well as new machine learning models.
What's next for Stock Data Analysis for Indian IT industry
We want to experiment more with model hyperparameters and check out other machine learning models for predicting stock prices and time-series data.
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