The application is to Brownian motion (which of course originated in physics!), which, to oversimplify, can be viewed as a time-dependent Gaussian distribution whose variance grows linearly with time and therefore its standard deviation grows proportionally to the square root of time. The proportionality constant in the standard deviation is called the volatility, and the units for volatility are the units for the standard deviation (think of that as a spatial dimension) divided by the square root of time. To take another tack, Brownian motion is closely related to the heat equation (again, a physical thing) u_t = (v^2/2)u_xx, where v is a constant measuring how well heat conducts in the material (I'll let the physicists make this more precise). The quantity v is the volatility. You could say that we should be working with v^2 and not v itself, and I won't disagree. But I have to live with common usage and convention. As for why Brownian motion matters in finance, I'm going to plead "off-topic" here, but you could try to look for explanations of the Black-Scholes formula. (Terence Tao at math.ucla.edu has a terrific but very terse explanation) So indeed, things like (time_duration)^(-1/2) do arise and are needed. Sorry. Your hopes were entirely reasonable, but fractional powers of fundamental units are really needed. But couldn't this be done rather nicely using the MPL map type, using a compile-time rational number type? I'm not exactly sure how to contruct the derived unit type from the unit types of two factors, but I bet it could be done most easily using this approach. Matt Calabrese wrote:
On 10/11/05, Deane Yang <deane_yang@yahoo.com> wrote:
What I'm more interested in learning is how you handle "composite quantities", which are obtained by multiplying and dividing existing units (like "meters/second"), as well as raising to a rational power (like the standard unit of volatility in finance, "1/square_root(years)".
Rational powers are handled with power functions and metafunctions, as I showed in later replies. However, I would like much more information regarding "volatility in finance." Up until now, I have seen absolutely no cases where non-derived unit classifications raised to a non-integer powers makes sense and have even talked about such situations with mathematicians. Looking back to the archives, I see people talking about fractional-powered base units being possible and speak of examples from other threads, but I can't seem to find such examples. An exact link would be very helpful. Right now I support fractional powers, but not when the operation yields fractional-powered base units. For instance, I allow the expression
power< 1, 2 >( your_meters_quantity * your_meters_quantity ) // where power< 1,2 > denotes a power of 1/2
However, I have chosen to disallow:
power< 1, 2 >( your_meters )
since it does not seem to ever make sense -- for any base classification type, not just length. In an attempt to rationalize why this was the case, I noticed that a base classification raised to a power could be looked at as a hyper-volume in N-dimensional space, where N is the value of the exponent. Continuing with "length" as an example, your_meters^2 represents a hyper-volume in 2 dimensional space (area), and your_meters^3 represents a hyper-volume in 3 dimensional space (volume), and your_meters^-3 could be looked at as units per volume, etc. This model makes sense for all integer powers, yet not for rational powers for base units, as it would imply a concept of fractions of a dimension, which intuitively I do not believe exist, though I am admittedly not a mathematician and my model could be too specific.
Keep in mind that rational powered derived-classifications are still perfectly fine, just so long as the resultant unit type does not have fractional powered base units in its make-up. Considering you apparently have an example where fractional-powered years is used (years being a base unit of time), I suppose my logic could be flawed, though I haven't heard of your example and googling around doesn't appear to be helping either. If you can, would you link to information regarding such fractional-powered base classifications? It's easy to go back and allow them in my library, as my restriction is mostly just superficial, but I won't do so until I see a place in practice where such operations actually make sense.
Thanks in advance.
-- -Matt Calabrese _______________________________________________ Unsubscribe & other changes: http://lists.boost.org/mailman/listinfo.cgi/boost