Consider the data in databases “bsedata1” and “nsedata1” that you have already obtained. Now for each of the stocks and for each of the market indices do the following :
- Plot the prices against time (daily, weekly and monthly).
- Compute the returns Ri (daily, weekly and monthly) and plot histograms of normalized returns
,
where µ and σ are sample mean and sample standard deviation respectively. Superimpose on each of these histograms a graph of the density function N(0,1).
Now, zoom into the tails of all these plots. What are your observations ?
- Will the observations be different if you instead use the log returns ?
- Now, consider the daily data only for the period January 1, 2014 to December 31, 2017 and estimate the µ and σ using log returns. Using the µ and σ, generate a path of stock prices that resembles (as closely as possible) the actual path of the stock for the period of January 1, 2018 to December 31, 2018.
- Repeat the above with weekly and monthly data.
Summarize your observations in your report for each of the above questions.