In this first part of the stock market analysis, I used pandas to get many stocks information from search engines, visualize the different attributes of it, and finally a roughly risk prediction of stocks based on their previous performance history. I used one dimensional random walk model to simulate the dynamics of the market using Monte Carlo simulation using the parameters extracted from the data. In the second part of this project, I will use different time series models (e.g., ARIMA) to predict stocks performance and will compare with the random walk model.
- Numpy
- Pandas
- Seaborn
- web
- datetime