Analyzing and simulating the price of Tesla Stock data for the period 2010 to 2020 using basic Python visualisations
The Work will help one to understand the growth of stocks and whether to invest or not. It will also give one a idea of the profit one will attain as well as the market risks involved.
On the analysis of the data one gets to know:
- Whether one can get profit by buying the stocks?
- Will the profit of buying will increase?
- What is the risk on investing?
- Which was the best period of time to invest?
- Average profit to loss ratio
- Average volume of shares sold every day
- Plotting - to visualize the data and see trend of growth in the share of stocks
- Bar Graphs - to find the lowest and highest stocks, as well as to see the consistency in growth
- It is used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables.
- Daily Return = ln(Days’s Price/ Previous Day Price)
- N number of trials is conducted for predefined number of days
- The Price for a particular day has a great chance in lying between the lowest price projected and the highest price projected.
- For example 50th day from the last date the Price has a chance of ending between 500 and 1500 (Image in Monte-Carlo Folder)