Underline Asset Range Finder

Dear Sir,
First of all thanks for great job regarding education for Indian Stock Market with modules.
I have one doubt regarding finding range of underline asset(such as nifty-50, bank-nifty or stock).
In the chapter-17 where you discuss standard deviation and normal distribution for finding range of nifty.
Sir you used formulae yearly average return and yearly standard deviation, after that use of exponential % in example. But in Chapter-18 you didn’t use exponential % you use only normal percentage for finding range of nifty-50. Please clarify.


Here is the exact calculation for determining the price range -

  1. Calculate daily log returns

  2. Calculate the mean & SD of log returns series

  3. 68% confidence interval is current price * exp (meantime +/- SD sqrt(time))

  4. 95% confidence interval is current price * exp (meantime +/- 2SD*sqrt(time))

The process involves computationally intensive tasks such as calculating log returns, calculating the exponential of a value etc. Under the following circumstances, the above calculations can be approximated with simpler calculations -

  1. Short periods: When time is small, (mean * time) is so small that it hardly makes any difference to the final value i.e. mean * time << SD * sqrt(time)

  2. When daily percentage movement < 10%, percentage returns and log returns are nearly equal. Computationally, the percentage is much faster to calculate than log returns. So percentages are used instead of logs.

The computationally faster approximation is:

  1. calculate percentage returns

  2. calculate mean and SD

  3. 68% confidence interval is current price (1 +/- SD*sqrt(time))

  4. 95% confidence interval is current price (1 +/- SD*sqrt(time))

I might have switched between approximate and accurate methods in many chapters, and this is to highlight the two different methods that you can employ.

If you are implementing a system, a rule of thumb one can use is

Go for a simpler method; if the price range > 20%, recalculate with the accurate method; otherwise, you can process with approximation.

1 Like

Thanks for detail calculation.