Are IV values calculated by QuantLib scaled by a factor?

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Are IV values calculated by QuantLib scaled by a factor?

Morpheous
I am using QuantLib to calculate IV values. I am suprised at the magbitude of the difference between my calculated historical volatility (HV) values, compared to the implied vol (IV) values calculated by QuantLib.

I am using QuantLib to calculate implied volatilities.

I am trying to understand the calculated figures (especially, when compared to historical volatility). The calculated implied volatility numbers are seldom below 0.5, whilst the historic volatility numbers* is never above 0.5.

Here is an output from my program:

DEBUG: 20 day historic volatility: 0.10
DEBUG: 20 day implied vol: 0.519485358338
DEBUG: 30 day historic volatility: 0.10
DEBUG: 30 day implied vol: 0.515820883886
DEBUG: 40 day historic volatility: 0.12
DEBUG: 40 day implied vol: 0.624451849413
DEBUG: 50 day historic volatility: 0.16
DEBUG: 50 day implied vol: 0.692403434852
DEBUG: 60 day historic volatility: 0.30
DEBUG: 60 day implied vol: 0.492372372425
DEBUG: 70 day historic volatility: 0.27
DEBUG: 70 day implied vol: 0.544712487074
DEBUG: 80 day historic volatility: 0.31
DEBUG: 80 day implied vol: 0.579945073422
DEBUG: 90 day historic volatility: 0.12
DEBUG: 90 day implied vol: 0.489174212819
DEBUG: 100 day historic volatility: 0.31
DEBUG: 100 day implied vol: 0.563068062254
DEBUG: 110 day historic volatility: 0.24
DEBUG: 110 day implied vol: 0.608231639138
DEBUG: 120 day historic volatility: 0.38
DEBUG: 120 day implied vol: 0.62748262992

The IVs are several multiples of the HV figures. I haven't looked under the bonnet and delved into the code just yet, but the consistently large difference (with IV constantly several multiples above HV) does suggest some scaling.

Finally, is a IV reading of 0.62748262992 to be interpreted as 0.6275% or 62.75% (the latter interpretation seems outrageously high)

*Note: Historic vols shown are annualized and calculated as the AVG square root of the variance of log returns.
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Re: Are IV values calculated by QuantLib scaled by a factor?

Marcin Pawlik
On 1 August 2012 03:57, Morpheous <[hidden email]> wrote:
>
> I am using QuantLib to calculate IV values. I am suprised at the magbitude of
> the difference between my calculated historical volatility (HV) values,
> compared to the implied vol (IV) values calculated by QuantLib.
>
> I am using QuantLib to calculate implied volatilities.

Can you provide the data and the code used?


> Here is an output from my program:
>
> DEBUG: 20 day historic volatility: 0.10
> DEBUG: 20 day implied vol: 0.519485358338

Perhaps for this set.


> The IVs are several multiples of the HV figures.

Usually it is so that IV > HV.


> I haven't looked under the
> bonnet and delved into the code just yet, but the consistently large
> difference (with IV constantly several multiples above HV) does suggest some
> scaling.

Not necessarily.


> Finally, is a IV reading of 0.62748262992 to be interpreted as 0.6275% or
> 62.75% (the latter interpretation seems outrageously high)

No, it doesn't.

M.

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Re: Are IV values calculated by QuantLib scaled by a factor?

Ferdinando M. Ametrano-3
In reply to this post by Morpheous
On Wed, Aug 1, 2012 at 3:57 AM, Morpheous <[hidden email]> wrote:
> Finally, is a IV reading of 0.62748262992 to be interpreted as 0.6275% or
> 62.75% (the latter interpretation seems outrageously high)

62.75%, and it not an outrageously high value for log-normal
volatilities in the current markets

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Re: Are IV values calculated by QuantLib scaled by a factor?

Peter Caspers-2
I sometimes fell for the "scaling factor" \sqrt(\tau) in functions like
blackFormulaImpliedStdDev() ...

Am 03.08.2012 16:21, schrieb Ferdinando Ametrano:

> On Wed, Aug 1, 2012 at 3:57 AM, Morpheous<[hidden email]>  wrote:
>> Finally, is a IV reading of 0.62748262992 to be interpreted as 0.6275% or
>> 62.75% (the latter interpretation seems outrageously high)
> 62.75%, and it not an outrageously high value for log-normal
> volatilities in the current markets
>
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> Exclusive live event will cover all the ways today's security and
> threat landscape has changed and how IT managers can respond. Discussions
> will include endpoint security, mobile security and the latest in malware
> threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
> _______________________________________________
> QuantLib-users mailing list
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> https://lists.sourceforge.net/lists/listinfo/quantlib-users


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