Re: [Quantlib-dev] Intraday patch

[Klaus S. <kl...@sp...>]

Hi Joe,

I was struggling with the same problem of intraday pricing a while ago. I've 
now found  the time to bundle my solution into a patch. 

In short, I've added intraday resolution directly to QuantLib's Date class 
using boost::posix_time::ptime while keeping the existing interfaces and 
behavior the same. The test suite runs unchanged with the new Date class. If 
you are interest then please find more details 

https://hpcquantlib.wordpress.com/2015/01/04/intraday-high-resolution-day-counters/

regards
 Klaus

On Monday, December 22, 2014 03:58:19 PM Joseph Wang wrote:
> I've just pushed up a patch to quantlib that provides basic support
> for intraday calculations.  The patch consists of two new classes
> 
> timestamp - which is a simple UTC timestamp class.  It is a subclass
> of Date, and can be used whereever date is.
> 
> continoustime - is a day counter that supports intraday calculations
> with timestamp.  ContinousTime allows the user to specify the base
> unit, so it is now possible to specify
> interest rates and volatility per day, per week, or per month (which
> is defined as 30 days) rather than per year.
> 
> The only non backward compartible part is the use of "yearFraction" to
> specify something other than a fraction of a year.  There is a
> function "timeFraction" which calls yearFraction.
> 
> Also this counter does not handle leap seconds, but I plan to add that.
> 
> I also intentionally left time zones out of these additions since
> that's another level of complexity.
> 
> I can write some unit tests and I'll add some more comments.  However,
> before I do, I'd like some feedback about the general class structure
> and to go through a code review.
> 
> Below is python code that uses the new interface
> 
> def option(strike, vol, t, putcall):
>     now = TimeStamp.now()
>     Settings.instance().evaluationDate = now
>     settlementDate = todaysDate + Period(3, Weeks)
>     riskFreeRate = FlatForward(settlementDate, 0.00,
> ContinuousTime.perDay())
> 
>     # option parameters
>     exercise = EuropeanExercise(settlementDate)
>     payoff = PlainVanillaPayoff(Option.Call, strike)
>     x = np.arange(strike*0.8, strike*1.2, 0.01);
> 
>     volatility = BlackConstantVol(todaysDate, TARGET(), vol,
> ContinuousTime.perDay())
>     dividendYield = FlatForward(settlementDate, 0.00,
> ContinuousTime.perDay()) underlying = SimpleQuote(0.0)
>     process = BlackScholesMertonProcess(QuoteHandle(underlying),
>                                     YieldTermStructureHandle(dividendYield),
> YieldTermStructureHandle(riskFreeRate),
> BlackVolTermStructureHandle(volatility)) option = VanillaOption(payoff,
> exercise)
>     # method: analytic
>     option.setPricingEngine(AnalyticEuropeanEngine(process))
>     def myfunc(x):
>         underlying .setValue(x)
>         return option.NPV()
>     def mydelta(x):
>         underlying.setValue(x)
>         return option.delta()
>     def mytheta(x):
>         underlying.setValue(x)
>         return option.theta()
>     plt.figure(1, figsize=(5,8))
>     plt.subplot(211)
>     y = map(payoff, x)
>     plt.plot(x, y)
>     plt.plot(x, map(myfunc,x))
>     plt.subplot(212)
>     plt.plot(x, map(mydelta,x))
> 
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