quantfin-0.1.0.2: src/Quant/Models/Black.hs
{-# LANGUAGE ExistentialQuantification #-}
module Quant.Models.Black (
Black (..)
) where
import Quant.Time
import Quant.YieldCurve
import Data.Random
import Control.Monad.State
import Quant.MonteCarlo
import Quant.ContingentClaim
-- | 'Black' represents a Black-Scholes model.
data Black = forall a b . (YieldCurve a, YieldCurve b) => Black {
blackInit :: Double -- ^ Initial asset level.
, blackVol :: Double -- ^ Volatility.
, blackForwardGen :: a -- ^ 'YieldCurve' to generate forwards
, blackYieldCurve :: b } -- ^ 'YieldCurve' to handle discounting
--instance CharFunc Black where
-- charFunc (Black s vol _ _) t k = exp
-- $ i*logs + negate i*vol'*vol'/2.0*t'*k-vol'*vol'*k*k/2.0*t'
-- where
-- i = 0 :+ 1
-- t' = t :+ 0
--vol' = vol :+ 0
--logs = log s :+ 0
instance Discretize Black where
initialize (Black s _ _ _) = put (Observables [s], Time 0)
{-# INLINE initialize #-}
evolve' b@(Black _ vol _ _) t2 anti = do
(Observables (stateVal:_), t1) <- get
fwd <- forwardGen b t2
let grwth = (fwd - vol*vol/2) * timeDiff t1 t2
postVal <- do
resid <- lift stdNormal
if anti then
return $ stateVal * exp (grwth - resid*vol)
else
return $ stateVal * exp (grwth + resid*vol)
put (Observables [postVal], t2)
{-# INLINE evolve' #-}
discount (Black _ _ _ dsc) t = disc dsc t
{-# INLINE discount #-}
forwardGen (Black _ _ fg _) t2 = do
(_, t1) <- get
return $ forward fg t1 t2
{-# INLINE forwardGen #-}
maxStep _ = 100