• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

volatility

Joined
6/21/19
Messages
1
Points
11
Hi all,

I have a serious doubt about volatility, let me explain here.

My coworkers are calculating return of a IR serie, as Rd-Rd-1 (they call it, absolute return), and then they are calculating volatility using this “absolute return”. My point is that this volatility is not comparable between nodes because of the “absolute return” and no even right.

Then they argue that they are calculating volatility points, and the volatility calculated with “absolute returns” is the same as volatility calculate with log returns multiplied by the average price.


To be specific, im using the 1M libor rate, if I compute the log return, and then standard deviation, I have 2.52% daily volatility.

If I compute absolute return, and then standard deviation is 0.05%.

What they say is, that if I take my log volatility (2.52%) and multiply for the average price of the serie (in this case rate because is libor, which is 2.29%) I get their volatility 2.52%*2.29%=0.05% they call it volatility basis points



I don’t see this explanation to be right. Can you help me here?
 
your coworkers seem right. you calculate std of the change as of a portion of the rate itself; while your coworkers estimate std of the change of the rate. in rate market, people care more about the change of the rate itself. think about it, your libor 1m is already kind of a return and you estimate the return of a return...

and the std on rate change is usually easier to interpret, e.g. the 5 bps std you obtained can easily be thought as about 70% of the daily rate changes fall within +-5 bps assuming gaussian. but your 2.52% std on the log changes of rates is a little hard to be conveniently digested.
 
Hey @IntoDarkness, thank you. I was struggling about how to take returns from a time series of interest rates and your comment made all make sense.
 
Back
Top