There’s an example in Kaplan secret sauce and just wondering what am I doing wrong.
Daily Std Dev = 0.0011 1Day Rtn = 0.00085 Value of Portfolio=100m
So var at 5% significance: VaR(daily) = [0.00085 - 1.65(0.0011)] * 100m = -96,500
I am trying to convert this to Annual VaR now considering 250 days
VaR(annual) = [0.00085*250 - 1.65(0.0011*(sqrt(250)))]* 100m = 18,380,233
Why my VaR is positive?
Thanks in advance for any help.
What is the right answer according Kaplan ?
Paste this in google
This is due to MV multiplication at the end. Take that out and var is positive.
schweser only has daily var calculated.
Oh, now I see it.
The Sharpe ratio for annual VAR is 12.07.
Makes sense since the daily VAR is 0.09% of the portfolio, and that scales down when you increase the time period.
So nothing I am doing wrong
nah, it’s just the figures are a little bit unfortunate here - the daily var was slightly negative but because you multiply returns by 250 and volatilty by only 250^0.5, the outcome happens to be positive
Well . . . .
I ran a Monte Carlo simulation using the data you gave (assuming that the returns are normally distributed), compounding the daily return for 250 days. The results are:
- Mean annual return = 2.37% (which is consistent with 0.85% compounded for 250 days)
- Annual standard deviation of returns = 2.15%, which is a lot more than 0.11% × √ 250 (=1.7393%)
That’s probably why they didn’t compute the statistics for the annual return: it isn’t remotely as simple as you’d imagine.
I don’t think compounding mean returns is a good idea.
But the data aren’t clear on whether that mean return is to be compounded or not.
I mean from a statistical prespective, since this is a single period model, and we’re using standard deviation.