hquantlib 0.0.2.3 → 0.0.2.4

raw patch · 7 files changed

+147/−94 lines, 7 filesdep +statisticsdep +vectordep ~HUnitdep ~QuickCheckdep ~containersPVP: major bump suggested

API removals or changes: PVP suggests a major version bump

Dependencies added: statistics, vector

Dependency ranges changed: HUnit, QuickCheck, containers, hmatrix, hmatrix-special, mersenne-random, parallel, test-framework, test-framework-hunit, test-framework-quickcheck2, time

API changes (from Hackage documentation)

Files

• hquantlib.cabal +18/−15
• src/QuantLib/Math/Copulas.hs +17/−16
• src/QuantLib/Models.hs +5/−0
• src/QuantLib/Models/Volatility.hs +100/−0
• src/QuantLib/Prices.hs +3/−3
• src/QuantLib/TimeSeries.hs +4/−0
• src/QuantLib/VolatilityModel.hs +0/−60

@@ -1,5 +1,5 @@ name:           hquantlib-version:        0.0.2.3+version:        0.0.2.4 license:        LGPL license-file:   LICENSE author:         Pavel Ryzhov@@ -19,7 +19,7 @@ source-repository this         type:           git         location:       https://github.com/paulrzcz/hquantlib.git-        tag:            0.0.2.3+        tag:            0.0.2.4  flag optimize         description : Enable optimizations for library and benchmarks@@ -37,12 +37,13 @@                 QuantLib.PricingEngines                 QuantLib.PricingEngines.BlackFormula                 QuantLib.Quotes-                QuantLib.VolatilityModel                 QuantLib.Time                 QuantLib.TimeSeries                 QuantLib.Money                 QuantLib.Math                 QuantLib.Math.Copulas+                QuantLib.Models+                QuantLib.Models.Volatility                 QuantLib.Prices                 QuantLib.Position                 QuantLib.Options@@ -62,13 +63,15 @@                 QuantLib.Math.InverseNormal                  build-depends:  -                        base            >3 && <5,-                        time            >= 1.2.0.0,-                        containers      >= 0.4.0.0,-                        hmatrix         >= 0.11.0.0,-                        hmatrix-special >= 0.1.1,-                        parallel        >= 3.1.0.0,-                        mersenne-random >= 1.0.0.0+                        base            >3              && <5,+                        time            >= 1.4.0.0      && < 1.5.0.0,+                        containers      >= 0.5.0.0      && < 0.6.0.0,+                        hmatrix         >= 0.14.0.0     && < 0.15.0.0,+                        hmatrix-special >= 0.2.0        && < 0.3.0,+                        parallel        >= 3.2.0.0      && < 3.3.0.0,+                        mersenne-random >= 1.0.0.1      && < 2.0.0.0,+                        statistics      >= 0.10.4.0     && < 0.11.0.0,+                        vector          >= 0.10.0.0     && < 0.11.0.0          hs-source-dirs: src         ghc-options:    -Wall@@ -81,9 +84,9 @@         main-is         :   Test.hs         hs-source-dirs  :   src         build-depends   :   base,-                            test-framework  >= 0.6,-                            test-framework-hunit >= 0.2.7,-                            test-framework-quickcheck2 >= 0.2.12.0,-                            QuickCheck      >= 2.4.0,-                            HUnit           >= 1.2.4.0+                            test-framework  >= 0.8                && < 0.9,+                            test-framework-hunit >= 0.3.0         && < 0.4.0,+                            test-framework-quickcheck2 >= 0.3.0.0 && < 0.4.0,+                            QuickCheck      >= 2.5.0              && < 2.6.0,+                            HUnit           >= 1.2.5.2            && < 2.0.0.0 

@@ -23,19 +23,19 @@  {-| Copula data types with parameters required by the concrete copula definition  -}-data Copulas = ClaytonCopula Double-        | MinCopula-        | MaxCopula-        | AliMikhailHaqCopula Double-        | FarlieGumbelMorgensternCopula Double-        | FrankCopula Double-        | GalambosCopula Double-        | GaussianCopula Double-        | GumbelCopula Double-        | HuslerReissCopula Double-        | IndependentCopula-        | MarshallOlkinCopula Double Double-        | PlackettCopula Double+data Copulas = ClaytonCopula Double -- ^ Clayton copula+        | MinCopula -- ^ Min copula+        | MaxCopula -- ^ Max copula+        | AliMikhailHaqCopula Double -- ^ Ali-Mikhail-Haq copula+        | FarlieGumbelMorgensternCopula Double -- ^ Farlie-Gumbel-Morgenstern copula+        | FrankCopula Double -- ^ Frank copula+        | GalambosCopula Double -- ^ Galambos copula+        | GaussianCopula Double -- ^ Gaussian copula /Not implemented yet!/+        | GumbelCopula Double -- ^ Gumbel copula+        | HuslerReissCopula Double -- ^ Husler-Reiss copula /Not implemented yet!/+        | IndependentCopula -- ^ Independent copula+        | MarshallOlkinCopula Double Double -- ^ Marshall-Olkin copula+        | PlackettCopula Double -- ^ Plackett copula  instance Copula Copulas where         copulaFunc (ClaytonCopula theta)                    = claytonCopula theta@@ -80,7 +80,7 @@  	| otherwise  	= Just $ max( (x ** (-theta) ) +   (y ** (-theta)-1.0)  **   (-1.0/theta)) 0-	+ minCopula ::  Ord a => a -> a -> Maybe a minCopula x y = Just (min x y) @@ -98,7 +98,7 @@     | otherwise     = Just (x * y * exp ( ( (-log x) ** (-theta) + (-log y) ** (-theta) ) ** (-1.0/theta)  ))  gaussianCopula ::  (Fractional a, Ord a) => a -> t -> t1 -> Maybe a1-gaussianCopula rho x y+gaussianCopula rho _ _     | rho >= -1.0 && rho <= 1.0 = undefined     | otherwise                 = Nothing @@ -107,7 +107,8 @@     | theta >= 1.0  = Just (exp ( - ( (-log x) ** theta + (-log y) ** theta) ** (1.0/theta)))     | otherwise     = Nothing -huslerReissCopula theta x y+huslerReissCopula :: (Fractional a, Ord a) => a -> a -> a -> Maybe a+huslerReissCopula theta _ _     | theta > 0.0   = undefined     | otherwise     = Nothing 

@@ -0,0 +1,5 @@+module QuantLib.Models +    ( module QuantLib.Models.Volatility+    ) where++import QuantLib.Models.Volatility

@@ -0,0 +1,100 @@+module QuantLib.Models.Volatility +    ( Volatility+    , Estimation (..)+    , VolatilityEstimator (..)+    , VolatilityEstimatorAlgorithm (..)+    ) where++import QuantLib.Prices (IntervalPrice(..))+import QuantLib.TimeSeries (IntervalPriceSeries)++import qualified Data.Map as M+import Statistics.Sample (stdDev, fastVarianceUnbiased)+import qualified Data.Vector.Unboxed as U++-- | Volatility type+type Volatility = Double++-- | Estimation type with strictness as it is usually required only one 'Double' to process+data Estimation = Estimation {-# UNPACK #-} !Volatility+    deriving (Show, Eq)++-- | Type class of volatility estimators+class VolatilityEstimator algorithm where+    -- | The estimation procedure that takes a series of 'QuantLib.Prices.IntervalPrice'+    estimate :: algorithm -> IntervalPriceSeries -> Estimation++data VolatilityEstimatorAlgorithm = SimpleEstimator -- ^ Simple estimator with drift+    | SimpleDriftLessEstimator    -- ^ Simple estimator without drift+    | ParkinsonEstimator          -- ^ Parkinson number+    | GarmanKlass5Estimator       -- ^ Garman-Klass estimator+    | RogersSatchelEstimator      -- ^ Rogers-Stachel estimator+    | YangZhangEstimator          -- ^ Yang-Zhang estimator+    deriving (Show, Eq, Enum)++instance VolatilityEstimator VolatilityEstimatorAlgorithm where+    estimate ParkinsonEstimator       = parkinson+    estimate SimpleEstimator          = simple+    estimate SimpleDriftLessEstimator = simpleDriftLess+    estimate GarmanKlass5Estimator    = garmanKlass5+    estimate RogersSatchelEstimator   = rogersSatchel+    estimate YangZhangEstimator       = yangZhang++{- Private implementation -}++-- we assume that the array is already sorted by time stamp+toLogArray :: IntervalPriceSeries -> U.Vector Double+toLogArray prices = U.fromList $ zipWith delog bars (tail bars)+    where+        bars        = map snd $ M.toAscList prices+        delog x0 x1 = log (ipClose x1/ipClose x0)++simple :: IntervalPriceSeries -> Estimation+simple = Estimation . stdDev . toLogArray++simpleDriftLess :: IntervalPriceSeries -> Estimation+simpleDriftLess = Estimation . sqrt . divByN . U.foldl' accum (T 0.0 0) . toLogArray+    where+        accum (T a n) b = T (a + b*b) (n + 1)+        divByN (T a n)  = a / fromIntegral n++parkinson :: IntervalPriceSeries -> Estimation+parkinson = Estimation . sqrt . divByN . M.foldl' summate (T 0.0 0)+    where+        divByN (T a n) = a / (4*log 2) / fromIntegral n+        summate (T a n) (IntervalPrice _ l h _) = T (a + logBase l h ** 2) (n + 1)++garmanKlass5 :: IntervalPriceSeries -> Estimation+garmanKlass5 = Estimation . sqrt . combine . M.foldl' point (TT 0.0 0.0 0)+    where+        logConst = 2.0 * log 2.0 - 1.0+        combine (TT a b n) = (0.5*a - logConst*b) / fromIntegral n+        point (TT a b n) (IntervalPrice o l h c) = TT (a + logBase l h ** 2) (b + logBase o c ** 2) (n + 1)++rogersSatchel :: IntervalPriceSeries -> Estimation+rogersSatchel = Estimation . sqrt . varRS++varRS :: IntervalPriceSeries -> Double+varRS = combine . M.foldl' point (T 0.0 0)+    where+        combine (T a n) = a / fromIntegral n+        point (T a n) (IntervalPrice o h l c) = +            T (a + logBase c h * logBase o h + logBase c l * logBase o l) (n + 1)++toSimpleLogWith :: (IntervalPrice -> Double) -> IntervalPriceSeries -> U.Vector Double+toSimpleLogWith f = U.fromList . map (f . snd) . M.toAscList++yangZhang :: IntervalPriceSeries -> Estimation+yangZhang prices = Estimation $ sqrt (varO + k * varC + (1.0 - k) * varRS prices)+    where+        n        = fromIntegral $ M.size prices+        k        = 0.34/(1.34 + (n + 1) / (n - 1))+        opens    = toSimpleLogWith (log . ipOpen) prices+        closes   = toSimpleLogWith (log . ipClose) prices+        varO     = fastVarianceUnbiased opens+        varC     = fastVarianceUnbiased closes++-- Strict data structure for efficient folds++data T = T {-# UNPACK #-} !Double {-# UNPACK #-} !Int+data TT = TT {-# UNPACK #-} !Double {-# UNPACK #-} !Double {-# UNPACK #-} !Int

@@ -1,5 +1,7 @@ module QuantLib.Prices-        ( module QuantLib.Prices+        ( PriceType (..)+        , CallPrice (..)+        , IntervalPrice (..)         ) where  -- | Price types@@ -20,5 +22,3 @@         ipLow   :: Double,         ipClose :: Double         } deriving (Show, Eq)--

@@ -2,8 +2,12 @@         ( module QuantLib.TimeSeries         ) where +import QuantLib.Prices(IntervalPrice) import Data.Time.LocalTime import qualified Data.Map as M  -- | Time series type TimeSeries m = M.Map LocalTime m++-- | Interval price time series+type IntervalPriceSeries = TimeSeries IntervalPrice

@@ -1,60 +0,0 @@-module QuantLib.VolatilityModel-        ( module QuantLib.VolatilityModel-        ) where--import QuantLib.Prices-import QuantLib.TimeSeries-import qualified Data.Map as M---- | Volatility type-type Volatility = Double---- | Volatility time series-type VolatilitySeries = TimeSeries Volatility---- | The estimator of time series of doubles-class DoubleVolatilityEstimator a where-        dveCalculate :: a->TimeSeries Double->VolatilitySeries---- | The calculator of volatility for interval price-class IntervalPointCalculator a where-        ipcCalculatePoint :: a->IntervalPrice->Volatility---- | Interval price volatility estimator-class IntervalVolatilityEstimator a where-        iveCalculate :: IntervalPointCalculator b => a->b->TimeSeries IntervalPrice->VolatilitySeries---- | Simple local estimator-data SimpleLocalEstimator = SimpleLocalEstimator {-        sleYearFraction :: Double-        } deriving (Show, Eq)--instance DoubleVolatilityEstimator SimpleLocalEstimator where-        dveCalculate (SimpleLocalEstimator yf) series = M.fromList result-                where-                       (result, _) =  M.foldrWithKey volFunc ([], Nothing) series-                       volFunc _ s (xs, Nothing) = (xs, Just s)-                       volFunc k s (xs, Just s0) = ((k, estimator s0 s):xs, Just s)-                       estimator s0 s1 = abs (log (s1 / s0) ) / yf---- | Garman-Klass interval estimators-data GarmanKlass = GarmanKlass {-        gkYearFraction  :: Double-        } deriving (Show, Eq)--instance IntervalVolatilityEstimator GarmanKlass where-        iveCalculate (GarmanKlass yf) ipc series = M.fromList result-                where   result = M.foldrWithKey volFunc [] series-                        volFunc k s xs = (k, abs (calculatePoint s) / yf):xs-                        calculatePoint = ipcCalculatePoint ipc---- | Types of Garman-Klass estimators-data GarmanKlassPoint = GarmanKlassSimpleSigma-        | ParkinsonSigma--instance IntervalPointCalculator GarmanKlassPoint where-        ipcCalculatePoint GarmanKlassSimpleSigma (IntervalPrice open _ _ close) =  log (close/open) ** 2--        ipcCalculatePoint ParkinsonSigma (IntervalPrice o h l _) = (u-d)**2 / 4.0 / log 2.0-                where   u = log (h/o)-                        d = log (l/o)