WIP

.github/workflows/CI.yml

@@ -32,7 +32,7 @@ jobs:
           - x64
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}

Project.toml

@@ -1,10 +1,14 @@
-name = "OnlinePortfolioAnalysis"
+name = "OnlinePortfolioAnalytics"
 uuid = "d39dbdee-9d7b-4a6f-a064-c0eaa0a6e939"
 authors = ["FemtoTrader <[email protected]>"]
 version = "1.0.0-DEV"
 
 [deps]
+OnlineStats = "a15396b6-48d5-5d58-9928-6d29437db91e"
 OnlineStatsBase = "925886fa-5bf2-5e8e-b522-a9147a512338"
+Rocket = "df971d30-c9d6-4b37-b8ff-e965b2cb3a40"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
 julia = "1.6.7"

README.md

@@ -1,3 +1,20 @@
-# OnlinePortfolioAnalysis
+# OnlinePortfolioAnalytics
 
-[![Build Status](https://github.com/femtotrader/OnlinePortfolioAnalysis.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/femtotrader/OnlinePortfolioAnalysis.jl/actions/workflows/CI.yml?query=branch%3Amain)
+WIP: Work in progress - not usable currently
+
+[![Build Status](https://github.com/femtotrader/OnlinePortfolioAnalytics.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/femtotrader/OnlinePortfolioAnalytics.jl/actions/workflows/CI.yml?query=branch%3Amain)
+
+This project aims to provide users with functionality for performing quantitative portfolio analytics via [online algorithms](https://en.wikipedia.org/wiki/Online_algorithm).
+
+It depends especially on [OnlineStatsBase.jl](https://joshday.github.io/OnlineStats.jl/)
+
+It's inspired by the following projects:
+
+- Julia
+  - PortfolioAnalytics.jl https://github.com/doganmehmet/PortfolioAnalytics.jl
+- R
+  - PerformanceAnalytics https://cran.r-project.org/web/packages/PerformanceAnalytics/
+  - PortfolioAnalytics https://cran.r-project.org/web/packages/PortfolioAnalytics/
+- Python
+  - pyfolio https://github.com/quantopian/pyfolio
+  - empyrical https://quantopian.github.io/empyrical

src/OnlinePortfolioAnalytics.jl

@@ -0,0 +1,29 @@
+module OnlinePortfolioAnalytics
+
+using OnlineStatsBase
+#using OnlineStats: GeometricMean
+using Statistics
+import StatsBase
+
+export SimpleAssetReturn, LogAssetReturn
+export Mean  # from OnlineStatsBase
+export GeometricMeanReturn  # different from OnlineStats: GeometricMean
+export StdDev
+export CumulativeReturn
+export DrawDowns, ArithmeticDrawDowns
+export AssetReturnMoments
+
+export fit!, value
+
+abstract type PortfolioAnalytics{T} <: OnlineStat{T} end
+
+include("asset_return.jl")
+include("mean_return.jl")
+include("cumulative_return.jl")
+include("std_dev.jl")
+include("drawdowns.jl")
+include("moments.jl")
+
+include("value_at_risk.jl")
+
+end

src/asset_return.jl

@@ -1,4 +1,4 @@
-mutable struct SimpleAssetReturn{T} <: PortfolioAnalysis{T}
+mutable struct SimpleAssetReturn{T} <: PortfolioAnalytics{T}
     value::Union{Missing,T}
     n::Int
 
@@ -8,7 +8,7 @@ mutable struct SimpleAssetReturn{T} <: PortfolioAnalysis{T}
 
     input_values::CircBuff
 
-    function SimpleAssetReturn{T}(; period::Int=1) where {T}
+    function SimpleAssetReturn{T}(; period::Int = 1) where {T}
         input_values = CircBuff(T, period + 1, rev = false)
         new{T}(missing, 0, false, period, input_values)
     end
@@ -28,9 +28,7 @@ function OnlineStatsBase._fit!(stat::SimpleAssetReturn, data)
     end
 end
 
-
-
-mutable struct LogAssetReturn{T} <: PortfolioAnalysis{T}
+mutable struct LogAssetReturn{T} <: PortfolioAnalytics{T}
     value::Union{Missing,T}
     n::Int
 
@@ -40,7 +38,7 @@ mutable struct LogAssetReturn{T} <: PortfolioAnalysis{T}
 
     input_values::CircBuff
 
-    function LogAssetReturn{T}(; period::Int=1) where {T}
+    function LogAssetReturn{T}(; period::Int = 1) where {T}
         input_values = CircBuff(T, period + 1, rev = false)
         new{T}(missing, 0, false, period, input_values)
     end

src/cumulative_return.jl

@@ -0,0 +1,18 @@
+mutable struct CumulativeReturn{T} <: PortfolioAnalytics{T}
+    value::T
+    n::Int
+
+    prod::Prod
+
+    function CumulativeReturn{T}() where {T}
+        val = zero(T)
+        p = Prod()
+        new{T}(val, 0, p)
+    end
+end
+
+function OnlineStatsBase._fit!(stat::CumulativeReturn, data)
+    fit!(stat.prod, 1 + data)
+    stat.n += 1
+    stat.value = value(stat.prod)
+end

src/drawdowns.jl

@@ -0,0 +1,45 @@
+mutable struct DrawDowns{T} <: PortfolioAnalytics{T}
+    value::T
+    n::Int
+
+    prod::Prod
+    extrema::Extrema
+
+    function DrawDowns{T}() where {T}
+        new{T}(T(0), 0, Prod(), Extrema(T))
+    end
+end
+
+function OnlineStatsBase._fit!(stat::DrawDowns, ret)
+    r1 = 1 + ret
+    fit!(stat.prod, r1)
+    rprod = value(stat.prod)
+    fit!(stat.extrema, rprod)
+    stat.n += 1
+    max_cumulative_returns = value(stat.extrema).max
+    ddowns = (rprod / max_cumulative_returns) - 1
+    stat.value = ddowns
+end
+
+
+mutable struct ArithmeticDrawDowns{T} <: PortfolioAnalytics{T}
+    value::T
+    n::Int
+
+    sum::Sum
+    extrema::Extrema
+
+    function ArithmeticDrawDowns{T}() where {T}
+        new{T}(T(0), 0, Sum(), Extrema(T))
+    end
+end
+
+function OnlineStatsBase._fit!(stat::ArithmeticDrawDowns, ret)
+    fit!(stat.sum, ret)
+    r1 = value(stat.sum) + 1
+    fit!(stat.extrema, r1)
+    stat.n += 1
+    max_cumulative_returns = value(stat.extrema).max
+    ddowns = (r1 / max_cumulative_returns) - 1
+    stat.value = ddowns
+end

src/mean_return.jl

@@ -0,0 +1,40 @@
+"""
+    Prod(T::Type = Float64)
+
+Track the overall prod.
+"""
+mutable struct Prod{T} <: OnlineStat{Number}
+    prod::T
+    n::Int
+end
+Prod(T::Type = Float64) = Prod(T(1), 0)
+Base.prod(o::Prod) = o.prod
+OnlineStatsBase._fit!(o::Prod{T}, x::Real) where {T<:AbstractFloat} =
+    (o.prod *= convert(T, x); o.n += 1)
+OnlineStatsBase._fit!(o::Prod{T}, x::Real) where {T<:Integer} =
+    (o.prod *= round(T, x); o.n += 1)
+OnlineStatsBase._fit!(o::Prod{T}, x::Real, n) where {T<:AbstractFloat} =
+    (o.prod *= convert(T, x * n); o.n += n)
+OnlineStatsBase._fit!(o::Prod{T}, x::Real, n) where {T<:Integer} =
+    (o.prod *= round(T, x * n); o.n += n)
+OnlineStatsBase._merge!(o::T, o2::T) where {T<:Prod} = (o.prod *= o2.prod; o.n += o2.n; o)
+
+# https://github.com/joshday/OnlineStatsBase.jl/issues/41
+
+mutable struct GeometricMeanReturn{T} <: PortfolioAnalytics{T}
+    value::T
+    n::Int
+
+    prod::Prod
+
+    function GeometricMeanReturn{T}() where {T}
+        p = Prod()
+        new{T}(T(0), 0, p)
+    end
+end
+
+function OnlineStatsBase._fit!(stat::GeometricMeanReturn, data)
+    fit!(stat.prod, 1 + data)
+    stat.n += 1
+    stat.value = value(stat.prod)^(1 / stat.n) - 1
+end

src/moments.jl

@@ -0,0 +1,22 @@
+mutable struct AssetReturnMoments{T} <: PortfolioAnalytics{T}
+    value::NamedTuple
+    n::Int
+
+    moments::Moments
+
+    function AssetReturnMoments{T}() where {T}
+        val = (mean = T(0), std = T(0), skewness = T(0), kurtosis = T(0))
+        new{T}(val, 0, Moments())
+    end
+end
+
+function OnlineStatsBase._fit!(stat::AssetReturnMoments, ret)
+    stat.n += 1
+    fit!(stat.moments, ret)
+    stat.value = (
+        mean = Statistics.mean(stat.moments),
+        std = Statistics.std(stat.moments),
+        skewness = StatsBase.skewness(stat.moments),
+        kurtosis = StatsBase.kurtosis(stat.moments),
+    )
+end

src/std_dev.jl

@@ -1,4 +1,4 @@
-mutable struct StdDev{T} <: PortfolioAnalysis{T}
+mutable struct StdDev{T} <: PortfolioAnalytics{T}
     value::T
     n::Int
 

src/value_at_risk.jl

@@ -0,0 +1 @@
+