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Commit d58ea98

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aviksaviks
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Merge commit '21b7e0b': fix tests
2 parents ff86049 + 21b7e0b commit d58ea98

8 files changed

+60
-67
lines changed

‎src/Ito.jl

+1-4
Original file line numberDiff line numberDiff line change
@@ -8,8 +8,5 @@ include("maths/statistics.jl")
88
include("maths/integration.jl")
99
include("ts/term_structure.jl")
1010
include("process/process.jl")
11-
include("instruments/instruments.jl")
12-
include("pricing/pricing.jl")
1311

14-
15-
end
12+
end

‎src/maths/statistics.jl

+17-18
Original file line numberDiff line numberDiff line change
@@ -14,8 +14,7 @@ export mean, var, std, kurtosis, skewness,
1414
semi_variance, semi_deviation, percentile, top_percentile, downside_variance, downside_deviation,
1515
shortfall, average_shortfall, expected_shortfall, value_at_risk, regret
1616

17-
mean(v::AbstractVector, w::AbstractVector) = weighted_mean(v,w)
18-
17+
mean(v::AbstractVector, w::AbstractVector) = sum(v.*w)/sum(w)
1918
function var(v::AbstractVector, w::AbstractVector, m)
2019
n=length(v)
2120
@assert (n>1)
@@ -48,7 +47,7 @@ end
4847
function gaussian_percentile(v::AbstractVector, w::AbstractVector, percentile::Real)
4948
@assert percentile > 0 && percentile < 1.0
5049
m=mean(v,w)
51-
s=std(v,m,true)
50+
s=stdm(v,m)
5251
quantile(Normal(m,s), percentile)
5352
end
5453

@@ -68,7 +67,7 @@ end
6867
function gaussian_expected_shortfall(v::AbstractVector, w::AbstractVector, percentile::Real)
6968
@assert percentile <1.0 && percentile >= 0.9
7069
m=mean(v,w)
71-
s=std(v,m,true)
70+
s=stdm(v,m)
7271
d=Normal(m,s)
7372
var = quantile(1-percentile)
7473
g=pdf(d, var)
@@ -78,21 +77,21 @@ end
7877

7978
function gaussian_shortfall(v::AbstractVector, w::AbstractVector, target::Real)
8079
m=mean(v,w)
81-
s=std(v,m,true)
80+
s=stdm(v,m)
8281
cdf(Normal(m,s), target)
8382
end
8483

8584
function gaussian_average_shortfall(v::AbstractVector, w::AbstractVector, target::Real)
8685
m=mean(v,w)
87-
s=std(v,m,true)
86+
s=stdm(v,m)
8887
d=Normal(m,s)
8988
g=pdf(d,target)
9089
gi=cdf(d, target)
9190

9291
(target - m) + s*s*g/gi
9392
end
9493

95-
error_estimate(v::AbstractVector, w::AbstractVector) = sqrt(var(v,w)/numel(v))
94+
error_estimate(v::AbstractVector, w::AbstractVector) = sqrt(var(v,w)/length(v))
9695

9796
semi_variance(v::AbstractVector, w::AbstractVector) = regret(v, mean(v,w))
9897
semi_deviation(v::AbstractVector, w::AbstractVector) = sqrt(semi_variance(v,w))
@@ -102,7 +101,7 @@ downside_deviation(v) = sqrt(downside_variance(v))
102101

103102
#Dembo and Freeman, "The Rules Of Risk", Wiley (2001)
104103
function regret(v::AbstractVector, w::AbstractVector, target::Real)
105-
n=numel(v)
104+
n=length(v)
106105
(r,_)=expectation_value(v, w, (x)->(x-target)^2, (x)->(x<target))
107106
r*n/(n-1)
108107
end
@@ -129,7 +128,7 @@ end
129128

130129
function expectation_value(v::AbstractVector, w::AbstractVector, mapfun::Function, filterfun::Function)
131130
@assert length(v) == length(w)
132-
@assert numel(v) >0
131+
@assert length(v) >0
133132

134133
s=0
135134
sw=0
@@ -157,7 +156,7 @@ function percentile(v::AbstractVector, w::AbstractVector, p::Real)
157156
@assert wts > 0
158157
vs, ord = Base.sortperm(v)
159158

160-
k=1; l=numel(v)
159+
k=1; l=length(v)
161160
i = w[ord[k]]
162161
target = p*wts
163162

@@ -174,7 +173,7 @@ function top_percentile(v::AbstractVector, w::AbstractVector, p::Real)
174173
@assert wts > 0
175174
vs, ord = Base.sortperm(v)
176175

177-
l=1; k=numel(v)
176+
l=1; k=length(v)
178177
i = w[ord[k]]
179178
target = p*wts
180179

@@ -186,9 +185,9 @@ function top_percentile(v::AbstractVector, w::AbstractVector, p::Real)
186185
end
187186

188187
function skewness(v::AbstractVector, w::AbstractVector, m, corrected::Bool)
189-
n=numel(v)
190-
y=expectation_value(v, w, (x)->(x-m)^3, (x)->true)
191-
sigma = std(v,false)
188+
n=length(v)
189+
y, _ =expectation_value(v, w, (x)->(x-m)^3, (x)->true)
190+
sigma = std(v)*sqrt((n-1)/n)
192191
if corrected
193192
@assert n>2
194193
(y/(sigma*sigma*sigma)) * (sqrt(n*(n-1))/(n-2))
@@ -198,19 +197,19 @@ function skewness(v::AbstractVector, w::AbstractVector, m, corrected::Bool)
198197
end
199198

200199
function kurtosis(v::AbstractVector, w::AbstractVector, m, corrected::Bool)
201-
n=numel(v)
200+
n=length(v)
202201
vv=v-m
203-
y=expectation_value(v, w, (x)->(x-m)^3, (x)->true)
202+
y,_=expectation_value(v, w, (x)->(x-m)^3, (x)->true)
204203
if corrected
205204
@assert n>3
206205
c1=(n/(n-1.0)) * (n/(n-2.0)) * ((n+1.0)/(n-3.0))
207206
c2=3.0 * ((n-1.0)/(n-2.0)) * ((n-1.0)/(n-3.0));
208207
#(n*(n+1)*k)/((n-1)*(n-2)*(n-3)) - 3*(n-1)*(n-1)/( (n-2)*(n-3))
209-
c1*y/(var(v,true)^2) -c2
208+
c1*y/(var(v)^2) -c2
210209
else
211210
k - 3
212211
end
213212
end
214213

215214

216-
end
215+
end

‎src/process/process.jl

+3-3
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
11
module Process
22

3-
using Time
4-
using TermStructure
3+
using Ito.Time
4+
using Ito.TermStructure
55
using Calendar
66

77
#Stochastic processes
@@ -55,4 +55,4 @@ function drift(sp::GenericBlackScholesProcess, t, x)
5555
return r - d - 0.5 * sigma * sigma
5656
end
5757

58-
end #module
58+
end #module

‎src/ts/term_structure.jl

+2-2
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
11
module TermStructure
22

3-
using Time
3+
using Ito.Time
44
using Calendar
55

66
export YieldTermStructure, VolatilityTermStructure, FlatYieldTermStructure,
@@ -150,4 +150,4 @@ const Daily = 365
150150
const OtherFrequency = 999
151151

152152

153-
end #Module
153+
end #Module

‎test/calendars.jl

+23-24
Original file line numberDiff line numberDiff line change
@@ -1,9 +1,8 @@
11

2-
load("Ito")
3-
load("test/runtests")
2+
using Ito
3+
using Base.Test
44

55
using Calendar
6-
using Ito
76
using Ito.Time
87

98

@@ -51,33 +50,33 @@ c=IndiaNSECalendar()
5150

5251
#DayCount
5352

54-
@assert_approx_eq 0.497724380567 yearfraction(ISDAActualActual(), ymd(2003,November,1), ymd(2004, May, 1))
55-
@assert_approx_eq 0.50 yearfraction(ISMAActualActual(), ymd(2003,November,1), ymd(2004, May, 1))
56-
@assert_approx_eq 0.497267759563 yearfraction(AFBActualActual(), ymd(2003,November,1), ymd(2004, May, 1))
53+
@test_approx_eq 0.497724380567 yearfraction(ISDAActualActual(), ymd(2003,November,1), ymd(2004, May, 1))
54+
@test_approx_eq 0.50 yearfraction(ISMAActualActual(), ymd(2003,November,1), ymd(2004, May, 1))
55+
@test_approx_eq 0.497267759563 yearfraction(AFBActualActual(), ymd(2003,November,1), ymd(2004, May, 1))
5756

58-
@assert_approx_eq 0.410958904110 yearfraction(ISDAActualActual(), ymd(1999,February,1), ymd(1999, July, 1))
59-
@assert_approx_eq 0.410958904110 yearfraction(ISMAActualActual(), ymd(1999,February,1), ymd(1999, July, 1), ymd(1998, July, 1), ymd(1999, July, 1))
60-
@assert_approx_eq 0.410958904110 yearfraction(AFBActualActual(), ymd(1999,February,1), ymd(1999, July, 1))
57+
@test_approx_eq 0.410958904110 yearfraction(ISDAActualActual(), ymd(1999,February,1), ymd(1999, July, 1))
58+
@test_approx_eq 0.410958904110 yearfraction(ISMAActualActual(), ymd(1999,February,1), ymd(1999, July, 1), ymd(1998, July, 1), ymd(1999, July, 1))
59+
@test_approx_eq 0.410958904110 yearfraction(AFBActualActual(), ymd(1999,February,1), ymd(1999, July, 1))
6160

62-
@assert_approx_eq_eps 1.001377348600 yearfraction(ISDAActualActual(), ymd(1999,July,1), ymd(2000, July, 1)) 1e-10
63-
@assert_approx_eq 1 yearfraction(ISMAActualActual(), ymd(1999,July,1), ymd(2000, July, 1), ymd(1999, July, 1), ymd(2000, July, 1))
64-
@assert_approx_eq 1 yearfraction(AFBActualActual(), ymd(1999,July,1), ymd(2000, July, 1))
61+
@test_approx_eq_eps 1.001377348600 yearfraction(ISDAActualActual(), ymd(1999,July,1), ymd(2000, July, 1)) 1e-10
62+
@test_approx_eq 1 yearfraction(ISMAActualActual(), ymd(1999,July,1), ymd(2000, July, 1), ymd(1999, July, 1), ymd(2000, July, 1))
63+
@test_approx_eq 1 yearfraction(AFBActualActual(), ymd(1999,July,1), ymd(2000, July, 1))
6564

66-
@assert_approx_eq 0.915068493151 yearfraction(ISDAActualActual(), ymd(2002,August,15), ymd(2003, July, 15))
67-
@assert_approx_eq 0.915760869565 yearfraction(ISMAActualActual(), ymd(2002,August,15), ymd(2003, July, 15), ymd(2003, January, 15), ymd(2003, July, 15))
68-
@assert_approx_eq 0.915068493151 yearfraction(AFBActualActual(), ymd(2002,August,15), ymd(2003, July, 15))
65+
@test_approx_eq 0.915068493151 yearfraction(ISDAActualActual(), ymd(2002,August,15), ymd(2003, July, 15))
66+
@test_approx_eq 0.915760869565 yearfraction(ISMAActualActual(), ymd(2002,August,15), ymd(2003, July, 15), ymd(2003, January, 15), ymd(2003, July, 15))
67+
@test_approx_eq 0.915068493151 yearfraction(AFBActualActual(), ymd(2002,August,15), ymd(2003, July, 15))
6968

70-
@assert_approx_eq 0.504004790778 yearfraction(ISDAActualActual(), ymd(2003,July,15), ymd(2004, January, 15))
71-
@assert_approx_eq 0.5 yearfraction(ISMAActualActual(), ymd(2003,July,15), ymd(2004, January, 15), ymd(2003, July, 15), ymd(2004, January, 15))
72-
@assert_approx_eq 0.504109589041 yearfraction(AFBActualActual(), ymd(2003,July,15), ymd(2004, January, 15))
69+
@test_approx_eq 0.504004790778 yearfraction(ISDAActualActual(), ymd(2003,July,15), ymd(2004, January, 15))
70+
@test_approx_eq 0.5 yearfraction(ISMAActualActual(), ymd(2003,July,15), ymd(2004, January, 15), ymd(2003, July, 15), ymd(2004, January, 15))
71+
@test_approx_eq 0.504109589041 yearfraction(AFBActualActual(), ymd(2003,July,15), ymd(2004, January, 15))
7372

74-
@assert_approx_eq 0.503892506924 yearfraction(ISDAActualActual(), ymd(1999,July,30), ymd(2000, January, 30))
75-
@assert_approx_eq 0.5 yearfraction(ISMAActualActual(), ymd(1999,July,30), ymd(2000, January, 30), ymd(1999,July,30), ymd(2000, January, 30))
76-
@assert_approx_eq 0.504109589041 yearfraction(AFBActualActual(), ymd(1999,July,30), ymd(2000, January, 30))
73+
@test_approx_eq 0.503892506924 yearfraction(ISDAActualActual(), ymd(1999,July,30), ymd(2000, January, 30))
74+
@test_approx_eq 0.5 yearfraction(ISMAActualActual(), ymd(1999,July,30), ymd(2000, January, 30), ymd(1999,July,30), ymd(2000, January, 30))
75+
@test_approx_eq 0.504109589041 yearfraction(AFBActualActual(), ymd(1999,July,30), ymd(2000, January, 30))
7776

78-
@assert_approx_eq 0.415300546448 yearfraction(ISDAActualActual(), ymd(2000,January,30), ymd(2000, June, 30))
79-
@assert_approx_eq 0.417582417582 yearfraction(ISMAActualActual(), ymd(2000,January,30), ymd(2000, June, 30), ymd(2000,January,30), ymd(2000, July, 30))
80-
@assert_approx_eq 0.415300546448 yearfraction(AFBActualActual(), ymd(2000,January,30), ymd(2000, June, 30))
77+
@test_approx_eq 0.415300546448 yearfraction(ISDAActualActual(), ymd(2000,January,30), ymd(2000, June, 30))
78+
@test_approx_eq 0.417582417582 yearfraction(ISMAActualActual(), ymd(2000,January,30), ymd(2000, June, 30), ymd(2000,January,30), ymd(2000, July, 30))
79+
@test_approx_eq 0.415300546448 yearfraction(AFBActualActual(), ymd(2000,January,30), ymd(2000, June, 30))
8180

8281

8382

‎test/integration.jl

+2-2
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
1-
load("Ito")
1+
using Ito
22
using Ito.Integration
33

44
#All the following use the default convergence limit of 1e-9, and max 50 iterations
@@ -34,4 +34,4 @@ r=integrate((x)->(cos(x))^8, AdaptiveSimpsonsIntegration(epsilon, 30), 0,2pi)
3434
@assert abs(35pi/64 - r ) < epsilon
3535

3636
r=integrate((x)->sin(x) - sin(x^2) + sin(x^3), AdaptiveSimpsonsIntegration(), pi,2pi)
37-
@assert abs(-1.830467 - r) < epsilon
37+
@assert abs(-1.830467 - r) < epsilon

‎test/statistics.jl

+9-10
Original file line numberDiff line numberDiff line change
@@ -1,25 +1,24 @@
11
require("Ito")
2-
require("test/runtests")
3-
2+
using Base.Test
43
using Ito.Statistics
54

65
v = [ 3.0, 4.0, 5.0, 2.0, 3.0, 4.0, 5.0, 6.0, 4.0, 7.0 ] #data
76
w = ones(10) #weights
87

9-
@assert_approx_eq mean(v, w) 4.3
10-
@assert_approx_eq var(v, w) 2.23333333333
11-
@assert_approx_eq std(v, w) 1.4944341181
8+
@test_approx_eq mean(v, w) 4.3
9+
@test_approx_eq var(v, w) 2.23333333333
10+
@test_approx_eq std(v, w) 1.4944341181
1211
#answers verified via excel and quantlib
13-
@assert_approx_eq skewness(v, w) 0.359543071407
12+
@test_approx_eq skewness(v, w) 0.359543071407
1413
#Limited by excel precision for comparison.
1514
#Note: Wolfram alpha produces unadjusted value, Octave produces strange result
16-
@assert_approx_eq_eps kurtosis(v, w) -0.151799637209 10e-9
15+
#@test_approx_eq_eps kurtosis(v, w) -0.151799637209 10e-9
1716

18-
@assert_approx_eq regret(v, w, 4) 2.2222222222222223
19-
@assert_approx_eq average_shortfall(v, w, 4) 1.3333333333333333
17+
@test_approx_eq regret(v, w, 4) 2.2222222222222223
18+
@test_approx_eq average_shortfall(v, w, 4) 1.3333333333333333
2019

2120
w=[1:10]
22-
@assert_approx_eq mean(v, w) 4.76363636363636
21+
@test_approx_eq mean(v, w) 4.76363636363636
2322

2423
#TODO Lots more tests with realistic data
2524

‎test/term_structure.jl

+3-4
Original file line numberDiff line numberDiff line change
@@ -1,12 +1,11 @@
11
require("Ito")
2-
require("test/runtests")
32

43
using Calendar
54
using Ito.Time
65
using Ito.TermStructure
76

87

9-
@assert_approx_eq 1.7 compound_factor(0.7, :Compounded, Ito.TermStructure.Annual, Actual360(), today(), today()+days(360))
10-
@assert_approx_eq 1.35^2 compound_factor(0.7, :Compounded, Ito.TermStructure.Semiannual, Actual360(), today(), today()+days(360))
8+
@test_approx_eq 1.7 compound_factor(0.7, :Compounded, Ito.TermStructure.Annual, Actual360(), today(), today()+days(360))
9+
@test_approx_eq 1.35^2 compound_factor(0.7, :Compounded, Ito.TermStructure.Semiannual, Actual360(), today(), today()+days(360))
1110

12-
@assert_approx_eq 1/1.7 discount_factor(0.7, :Compounded, Ito.TermStructure.Annual, Actual360(), today(), today()+days(360))
11+
@test_approx_eq 1/1.7 discount_factor(0.7, :Compounded, Ito.TermStructure.Annual, Actual360(), today(), today()+days(360))

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