From 28f025e23b7c2799cb06606a99e3b384948088a3 Mon Sep 17 00:00:00 2001
From: Phil <pdoh00@gmail.com>
Date: Sun, 3 Mar 2013 20:55:55 -0800
Subject: [PATCH 1/5] Addition of Financial bases absolute risk stats

Addition of stats and unit tests.  Still need test for GainLossRatio.
The tests may be a bit sparse compared to what is required for a pull.
Will need to talk to Chrisoph about that.
---
 .../Financial/AbsoluteRiskStatistics.cs       | 198 ++++++++++++++++++
 src/Numerics/Numerics.csproj                  |   1 +
 .../FinancialTests/DownsideDeviationTests.cs  | 113 ++++++++++
 .../FinancialTests/GainLossRatioTests.cs      |  42 ++++
 src/UnitTests/FinancialTests/GainMeanTests.cs | 105 ++++++++++
 .../GainStandardDeviationTests.cs             | 119 +++++++++++
 src/UnitTests/FinancialTests/LossMeanTests.cs | 105 ++++++++++
 .../LossStandardDeviationTests.cs             | 117 +++++++++++
 .../FinancialTests/SemiDeviationTests.cs      | 108 ++++++++++
 src/UnitTests/UnitTests.csproj                |   6 +
 10 files changed, 914 insertions(+)
 create mode 100644 src/Numerics/Financial/AbsoluteRiskStatistics.cs
 create mode 100644 src/UnitTests/FinancialTests/DownsideDeviationTests.cs
 create mode 100644 src/UnitTests/FinancialTests/GainLossRatioTests.cs
 create mode 100644 src/UnitTests/FinancialTests/GainMeanTests.cs
 create mode 100644 src/UnitTests/FinancialTests/GainStandardDeviationTests.cs
 create mode 100644 src/UnitTests/FinancialTests/LossMeanTests.cs
 create mode 100644 src/UnitTests/FinancialTests/LossStandardDeviationTests.cs
 create mode 100644 src/UnitTests/FinancialTests/SemiDeviationTests.cs

diff --git a/src/Numerics/Financial/AbsoluteRiskStatistics.cs b/src/Numerics/Financial/AbsoluteRiskStatistics.cs
new file mode 100644
index 00000000..0d7e8aa6
--- /dev/null
+++ b/src/Numerics/Financial/AbsoluteRiskStatistics.cs
@@ -0,0 +1,198 @@
+// <copyright file="AbsoluteRiskStatistics.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+//
+// Copyright (c) 2009-2010 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.Financial
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using System.Text;
+    using MathNet.Numerics.Statistics;
+
+    public static class AbsoluteRiskStatistics
+    {
+        //Note: The following statistics would be condidered an absolute risk statistic in the finance realm as well.
+        // Standard Deviation 
+        // Annualized Standard Deviation = Math.Sqrt(Monthly Standard Deviation x ( 12 ))
+        // Skewness
+        // Kurtosis  
+
+
+        /// <summary>
+        /// Calculation is similar to Standard Deviation , except it calculates an average (mean) return only for periods with a gain 
+        /// and measures the variation of only the gain periods around the gain mean. Measures the volatility of upside performance.
+        /// © Copyright 1996, 1999 Gary L.Gastineau. First Edition. © 1992 Swiss Bank Corporation.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        public static double GainStandardDeviation(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var gains = data.Where(x => x >= 0);
+            var count = gains.Count();
+            if (count == 0 || count == 1)
+                return double.NaN;
+
+            return gains.StandardDeviation();
+        }
+
+        /// <summary>
+        /// Similar to standard deviation, except this statistic calculates an average (mean) return for only the periods with a loss and then 
+        /// measures the variation of only the losing periods around this loss mean. This statistic measures the volatility of downside performance.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
+        public static double LossStandardDeviation(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var losses = data.Where(x => x < 0);
+            var count = losses.Count();
+            if (count == 0 || count == 1)
+                return double.NaN;
+
+            return losses.StandardDeviation();
+        }
+
+        /// <summary>
+        /// This measure is similar to the loss standard deviation except the downside deviation
+        /// considers only returns that fall below a defined minimum acceptable return (MAR) rather than the arithmetic mean.
+        /// For example, if the MAR is 7%, the downside deviation would measure the variation of each period that falls below
+        /// 7%. (The loss standard deviation, on the other hand, would take only losing periods, calculate an average return for
+        /// the losing periods, and then measure the variation between each losing return and the losing return average).
+        /// </summary>
+        /// <param name="data"></param>
+        /// <param name="minimalAcceptableReturn"></param>
+        /// <returns></returns>
+        public static double DownsideDeviation(this IEnumerable<double> data, double minimalAcceptableReturn)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var belowMARdata = data.Where(x => x < minimalAcceptableReturn);
+            var count = belowMARdata.Count();
+            if (count == 0 || count == 1)
+                return double.NaN;
+
+            return belowMARdata.StandardDeviation();
+        }
+
+        /// <summary>
+        /// A measure of volatility in returns below the mean. It's similar to standard deviation, but it only
+        /// looks at periods where the investment return was less than average return.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        public static double SemiDeviation(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var belowMeanData = data.Where(x => x < data.Mean());
+            var count = belowMeanData.Count();
+            if (count == 0 || count == 1)
+                return double.NaN;
+
+            return belowMeanData.StandardDeviation();
+        }
+
+        /// <summary>
+        /// Average Gain or Gain Mean
+        /// This is a simple average (arithmetic mean) of the periods with a gain. It is calculated by summing the returns for gain periods (return 0) 
+        /// and then dividing the total by the number of gain periods.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
+        public static double GainMean(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var gains = data.Where(x => x >= 0);
+            return gains.Mean();
+        }
+
+        /// <summary>
+        /// Average Loss or LossMean
+        /// This is a simple average (arithmetic mean) of the periods with a loss. It is calculated by summing the returns for loss periods (return < 0)
+        /// and then dividing the total by the number of loss periods.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
+        public static double LossMean(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var losses = data.Where(x => x < 0);
+            return losses.Mean();
+        }
+
+        /// <summary>
+        /// Measures a fund’s average gain in a gain period divided by the fund’s average loss in a losing
+        /// period. Periods can be monthly or quarterly depending on the data frequency.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        public static double GainLossRatio(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var gains = data.Where(x => x >= 0);
+            var losses = data.Where(x => x < 0);
+
+            var lossMean = losses.Mean();
+            if(lossMean != 0.0)
+                return Math.Abs(gains.Mean() / losses.Mean());
+            return 0.0;
+        }
+    }
+}
diff --git a/src/Numerics/Numerics.csproj b/src/Numerics/Numerics.csproj
index 60be540e..226e8d46 100644
--- a/src/Numerics/Numerics.csproj
+++ b/src/Numerics/Numerics.csproj
@@ -105,6 +105,7 @@
     <Compile Include="Constants.cs" />
     <Compile Include="Control.cs" />
     <Compile Include="Complex32.cs" />
+    <Compile Include="Financial\AbsoluteRiskStatistics.cs" />
     <Compile Include="LinearAlgebra\Generic\Matrix.BCL.cs" />
     <Compile Include="LinearAlgebra\Generic\Vector.BCL.cs" />
     <Compile Include="SpecialFunctions\Evaluate.cs" />
diff --git a/src/UnitTests/FinancialTests/DownsideDeviationTests.cs b/src/UnitTests/FinancialTests/DownsideDeviationTests.cs
new file mode 100644
index 00000000..fa2e2165
--- /dev/null
+++ b/src/UnitTests/FinancialTests/DownsideDeviationTests.cs
@@ -0,0 +1,113 @@
+// <copyright file="DownsideDeviationTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class DownsideDeviationTests
+    {
+        [Test]
+        public void returns_undefined_with_no_input_data()
+        {
+            //arrange
+            const double minimumAcceptableReturn = 0.05;
+            var inputData = new List<double>();
+            //act
+            var dsDeviation = inputData.DownsideDeviation(minimumAcceptableReturn);
+            //assert
+            Assert.AreEqual(double.NaN, dsDeviation);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_positive_input()
+        {
+            //arrange
+            const double minimumAcceptableReturn = 0.05;
+            var inputData = new[] { 1.0 };
+            //act
+            var dsDeviation = inputData.DownsideDeviation(minimumAcceptableReturn);
+            //assert
+            Assert.AreEqual(double.NaN, dsDeviation);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_negative_input()
+        {
+            //arrange
+            const double minimumAcceptableReturn = 0.05;
+            var inputData = new[] { -1.0 };
+            //act
+            var dsDeviation = inputData.DownsideDeviation(minimumAcceptableReturn);
+            //assert
+            Assert.AreEqual(double.NaN, dsDeviation);
+        }
+
+        [Test]
+        public void only_uses_data_points_below_the_minimum_acceptable_return()
+        {
+            //arrange
+            const double minimumAcceptableReturn = 0.05;
+            var inputData = new[] { 0.0021, 0.02, 0.5, 0.12 };
+            var expectedSemiDeviation = inputData.Where(x => x < minimumAcceptableReturn).StandardDeviation();
+            //act
+            var semiDeviation = inputData.DownsideDeviation(minimumAcceptableReturn);
+            //assert
+            Assert.AreEqual(expectedSemiDeviation, semiDeviation);
+        }
+
+        [Test]
+        public void handles_negative_values()
+        {
+            //arrange
+            const double minimumAcceptableReturn = 0.05;
+            var inputData = new[] { -0.1, -0.02, 0.4, 0.12 };
+            var expectedSemiDeviation = inputData.Where(x => x < minimumAcceptableReturn).StandardDeviation();
+            //act
+            var semiDeviation = inputData.DownsideDeviation(minimumAcceptableReturn);
+            //assert
+            Assert.AreEqual(expectedSemiDeviation, semiDeviation);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null()
+        {
+            //arrange
+            const double minimumAcceptableReturn = 0.05;
+            List<double> inputData = null;
+            //act
+            inputData.DownsideDeviation(minimumAcceptableReturn);
+        }
+
+    }
+}
diff --git a/src/UnitTests/FinancialTests/GainLossRatioTests.cs b/src/UnitTests/FinancialTests/GainLossRatioTests.cs
new file mode 100644
index 00000000..89b0aebb
--- /dev/null
+++ b/src/UnitTests/FinancialTests/GainLossRatioTests.cs
@@ -0,0 +1,42 @@
+// <copyright file="GainLossRatioTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using System.Text;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class GainLossRatioTests
+    {
+
+    }
+}
diff --git a/src/UnitTests/FinancialTests/GainMeanTests.cs b/src/UnitTests/FinancialTests/GainMeanTests.cs
new file mode 100644
index 00000000..154d92a1
--- /dev/null
+++ b/src/UnitTests/FinancialTests/GainMeanTests.cs
@@ -0,0 +1,105 @@
+// <copyright file="GainMeanTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class GainMeanTests
+    {
+        [Test]
+        public void returns_zero_when_its_the_only_data()
+        {
+            //arrange
+            var inputData = new[] { 0.0 };
+            //act
+            var gainMean = inputData.GainMean();
+            //assert
+            Assert.AreEqual(0.0, gainMean);
+        }
+        [Test]
+        public void returns_zero_when_all_input_is_negative()
+        {
+            //arrange
+            var inputData = new[] { -1.0, -2.0, -3.0 };
+            //act
+            var gainMean = inputData.GainMean();
+            //assert
+            Assert.AreEqual(0.0, gainMean);
+        }
+
+        [Test]
+        public void returns_same_as_mean_when_all_values_are_positive()
+        {
+            //arrange
+            var inputData = new[] { 1.0, 2.0, 3.0 };
+            var mean = inputData.Mean();
+            //act
+            var gainMean = inputData.GainMean();
+            //assert
+            Assert.AreEqual(mean, gainMean);
+        }
+
+        [Test]
+        public void does_not_use_negative_input_values()
+        {
+            //arrange
+            var inputData = new[] { 1.0, -1.0 };
+            //act
+            var gainMean = inputData.GainMean();
+            //assert
+            Assert.AreEqual(1.0, gainMean);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))]
+        public void throws_when_input_data_is_null() //assert
+        {
+            //arrange
+            var inputData = new[] { 1.0 };
+            inputData = null;
+            //act
+            inputData.GainMean();
+        }
+
+        [Test]
+        public void returns_zero_with_no_input_data()
+        {
+            //arrange
+            var inputData = new List<double>();
+            //act
+            var gainMean = inputData.GainMean();
+            //assert
+            Assert.AreEqual(0.0, gainMean);
+        }
+
+    }
+}
diff --git a/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs b/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs
new file mode 100644
index 00000000..f7a163fe
--- /dev/null
+++ b/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs
@@ -0,0 +1,119 @@
+// <copyright file="GainStandardDeviationTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class GainStandardDeviationTests
+    {
+        [Test]
+        public void returns_undefined_with_no_input_data()
+        {
+            //arrange
+            var inputData = new List<double>();
+            //act
+            var gainStdDev = inputData.GainStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, gainStdDev);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_positive_input()
+        {
+            //arrange
+            var inputData = new[] { 1.0 };
+            //act
+            var gainStdDev = inputData.GainStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, gainStdDev);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_negative_input()
+        {
+            //arrange
+            var inputData = new[] { -1.0 };
+            //act
+            var gainStdDev = inputData.GainStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, gainStdDev);
+        }
+
+        [Test]
+        public void does_not_use_negative_input_data()
+        {
+            //arrange
+            var inputData = new[] { -1.0, 1.0, -2.0, 2.0 };
+            var expectedGainStdDeviation = inputData.Where(x => x >= 0).StandardDeviation();
+            //act
+            var gainStdDev = inputData.GainStandardDeviation();
+            //assert
+            Assert.AreEqual(expectedGainStdDeviation, gainStdDev);
+        }
+
+        [Test]
+        public void returns_undefined_for_a_set_of_all_negative_numbers()
+        {
+            //arrange
+            var inputData = new[] { -1.0, -1.0, -2.0, -3.0 };
+            //act
+            var gainStdDev = inputData.GainStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, gainStdDev);
+        }
+
+        [Test]
+        public void handles_zero_in_the_data_input_as_a_positive_number()
+        {
+            //arrange
+            var inputData = new[] { -1.0, 0.0, 1.0, 2.0 };
+            var expectedGainStdDeviation = inputData.Where(x => x >= 0).StandardDeviation();
+            //act
+            var gainStdDev = inputData.GainStandardDeviation();
+            //assert
+            Assert.AreEqual(expectedGainStdDeviation, gainStdDev);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null()
+        {
+            //arrange
+            List<double> inputData = null;
+            //act
+            inputData.GainStandardDeviation();
+        }
+
+        public double gainStdDev { get; set; }
+    }
+}
diff --git a/src/UnitTests/FinancialTests/LossMeanTests.cs b/src/UnitTests/FinancialTests/LossMeanTests.cs
new file mode 100644
index 00000000..8b57a4e4
--- /dev/null
+++ b/src/UnitTests/FinancialTests/LossMeanTests.cs
@@ -0,0 +1,105 @@
+// <copyright file="LossMeanTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class LossMeanTests
+    {
+        [Test]
+        public void returns_zero_when_zero_is_the_only_input()
+        {
+            //arrange
+            var inputData = new[] { 0.0 };
+            //act
+            var lossMean = inputData.LossMean();
+            //assert
+            Assert.AreEqual(0.0, lossMean);
+        }
+
+        [Test]
+        public void returns_zero_when_all_input_is_positive()
+        {
+            //arrange
+            var inputData = new[] { 1.0 };
+            //act
+            var lossMean = inputData.LossMean();
+            //assert
+            Assert.AreEqual(0.0, lossMean);
+        }
+
+        [Test]
+        public void returns_the_same_as_mean_when_all_values_are_negative()
+        {
+            //arrange
+            var inputData = new[] { -1.0, -2.0 };
+            var mean = inputData.Mean();
+            //act
+            var lossMean = inputData.LossMean();
+            //assert
+            Assert.AreEqual(mean, lossMean);
+        }
+
+        [Test]
+        public void does_not_use_positive_input_values()
+        {
+            //arrange
+            var inputData = new[] { -1.0, 2.0 };
+            //act
+            var lossMean = inputData.LossMean();
+            //assert
+            Assert.AreEqual(-1.0, lossMean);
+        }
+
+
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null() 
+        {
+            //arrange
+            List<double> inputData = null;
+            //act
+            inputData.LossMean();
+        }
+
+        [Test]
+        public void returns_zero_with_no_input_data()
+        {
+            //arrange
+            var inputData = new List<double>();
+            //act
+            var lossMean = inputData.LossMean();
+            //assert
+            Assert.AreEqual(0.0, lossMean);
+        }
+    }
+}
diff --git a/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs b/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs
new file mode 100644
index 00000000..b3367ec5
--- /dev/null
+++ b/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs
@@ -0,0 +1,117 @@
+// <copyright file="LossStandardDeviationTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class LossStandardDeviationTests
+    {
+        [Test]
+        public void returns_undefined_with_no_input_data()
+        {
+            //arrange
+            var inputData = new List<double>();
+            //act
+            var lossStdDev = inputData.LossStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, lossStdDev);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_positive_input()
+        {
+            //arrange
+            var inputData = new[] { 1.0 };
+            //act
+            var lossStdDev = inputData.LossStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, lossStdDev);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_negative_input()
+        {
+            //arrange
+            var inputData = new[] { -1.0 };
+            //act
+            var lossStdDev = inputData.LossStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, lossStdDev);
+        }
+
+        [Test]
+        public void does_not_use_positive_input_data()
+        {
+            //arrange
+            var inputData = new[] { -1.0, 1.0, -2.0, 2.0 };
+            var expectedLossStdDeviation = inputData.Where(x => x < 0).StandardDeviation();
+            //act
+            var lossStdDev = inputData.LossStandardDeviation();
+            //assert
+            Assert.AreEqual(expectedLossStdDeviation, lossStdDev);
+        }
+
+        [Test]
+        public void handles_zero_in_the_data_input_as_a_positive_number()
+        {
+            //arrange
+            var inputData = new[] { -1.0, 0.0, -6.0, 2.0 };
+            var expectedLossStdDeviation = inputData.Where(x => x < 0).StandardDeviation();
+            //act
+            var lossStdDev = inputData.LossStandardDeviation();
+            //assert
+            Assert.AreEqual(expectedLossStdDeviation, lossStdDev);
+        }
+
+        [Test]
+        public void returns_undefined_for_a_set_of_all_positive_numbers()
+        {
+            //arrange
+            var inputData = new[] { 1.0, 1.0, 2.0, 3.0 };
+            //act
+            var lossStdDev = inputData.LossStandardDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, lossStdDev);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null()
+        {
+            //arrange
+            List<double> inputData = null;
+            //act
+            inputData.LossStandardDeviation();
+        }
+    }
+}
diff --git a/src/UnitTests/FinancialTests/SemiDeviationTests.cs b/src/UnitTests/FinancialTests/SemiDeviationTests.cs
new file mode 100644
index 00000000..0394b10e
--- /dev/null
+++ b/src/UnitTests/FinancialTests/SemiDeviationTests.cs
@@ -0,0 +1,108 @@
+// <copyright file="SemiDeviationTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using MathNet.Numerics.Financial;
+    using MathNet.Numerics.Statistics;
+    using NUnit.Framework;
+
+    [TestFixture]
+    public class SemiDeviationTests
+    {
+        [Test]
+        public void returns_undefined_with_no_input_data()
+        {
+            //arrange
+            var inputData = new List<double>();
+            //act
+            var semiDeviation = inputData.SemiDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, semiDeviation);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_positive_input()
+        {
+            //arrange
+            var inputData = new[] { 1.0 };
+            //act
+            var semiDeviation = inputData.SemiDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, semiDeviation);
+        }
+
+        [Test]
+        public void returns_undefined_with_single_negative_input()
+        {
+            //arrange
+            var inputData = new[] { -1.0 };
+            //act
+            var semiDeviation = inputData.SemiDeviation();
+            //assert
+            Assert.AreEqual(double.NaN, semiDeviation);
+        }
+
+        [Test]
+        public void only_uses_data_points_below_the_mean_of_all_data()
+        {
+            //arrange
+            var inputData = new[] { 1.0, 2.0, 3.0, 4.0 };
+            var mean = inputData.Mean();
+            var expectedSemiDeviation = inputData.Where(x => x < mean).StandardDeviation();
+            //act
+            var semiDeviation = inputData.SemiDeviation();
+            //assert
+            Assert.AreEqual(expectedSemiDeviation, semiDeviation);
+        }
+
+        [Test]
+        public void handles_negative_values()
+        {
+            //arrange
+            var inputData = new[] { -1.0, 2.0, 3.0, 4.0 };
+            var mean = inputData.Mean();
+            var expectedSemiDeviation = inputData.Where(x => x < mean).StandardDeviation();
+            //act
+            var semiDeviation = inputData.SemiDeviation();
+            //assert
+            Assert.AreEqual(expectedSemiDeviation, semiDeviation);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null() 
+        {
+            //arrange
+            List<double> inputData = null;
+            //act
+            inputData.SemiDeviation();
+        }
+    }
+}
diff --git a/src/UnitTests/UnitTests.csproj b/src/UnitTests/UnitTests.csproj
index 5afd12db..257c5945 100644
--- a/src/UnitTests/UnitTests.csproj
+++ b/src/UnitTests/UnitTests.csproj
@@ -122,6 +122,12 @@
     <Compile Include="DistributionTests\Multivariate\MultinomialTests.cs" />
     <Compile Include="DistributionTests\Multivariate\NormalGammaTests.cs" />
     <Compile Include="DistributionTests\Multivariate\WishartTests.cs" />
+    <Compile Include="FinancialTests\DownsideDeviationTests.cs" />
+    <Compile Include="FinancialTests\GainStandardDeviationTests.cs" />
+    <Compile Include="FinancialTests\LossMeanTests.cs" />
+    <Compile Include="FinancialTests\GainMeanTests.cs" />
+    <Compile Include="FinancialTests\LossStandardDeviationTests.cs" />
+    <Compile Include="FinancialTests\SemiDeviationTests.cs" />
     <Compile Include="IntegralTransformsTests\FourierTest.cs" />
     <Compile Include="IntegralTransformsTests\HartleyTest.cs" />
     <Compile Include="IntegralTransformsTests\InverseTransformTest.cs" />

From f9af5aa84426161322c9f53f1eb55125e3727e6b Mon Sep 17 00:00:00 2001
From: Phil <pdoh00@gmail.com>
Date: Mon, 4 Mar 2013 19:37:43 -0800
Subject: [PATCH 2/5] Added GainLossRatio Tests

Added tests around GainLossRatio, but I still have some questions as
noted per test.
---
 .../FinancialTests/GainLossRatioTests.cs      | 82 ++++++++++++++++++-
 src/UnitTests/UnitTests.csproj                |  1 +
 2 files changed, 82 insertions(+), 1 deletion(-)

diff --git a/src/UnitTests/FinancialTests/GainLossRatioTests.cs b/src/UnitTests/FinancialTests/GainLossRatioTests.cs
index 89b0aebb..d3c3536b 100644
--- a/src/UnitTests/FinancialTests/GainLossRatioTests.cs
+++ b/src/UnitTests/FinancialTests/GainLossRatioTests.cs
@@ -29,7 +29,6 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using System;
     using System.Collections.Generic;
     using System.Linq;
-    using System.Text;
     using MathNet.Numerics.Financial;
     using MathNet.Numerics.Statistics;
     using NUnit.Framework;
@@ -37,6 +36,87 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     [TestFixture]
     public class GainLossRatioTests
     {
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null()
+        {
+            //arrange
+            List<double> inputData = null;
+            //act
+            inputData.GainLossRatio();
+        }
 
+        [Test]
+        //Not sure this is correct.  Undefined may be more correct.
+        public void returns_zero_for_a_single_positive_input()
+        {
+            //arrange
+            var inputData = new[] { 1.0 };
+            //act
+            var gainLossRatio = inputData.GainLossRatio();
+            //assert
+            Assert.AreEqual(0.0, gainLossRatio);
+        }
+
+        [Test]
+        //Not sure this is correct.  Undefined may be more correct.
+        public void returns_zero_for_a_single_negative_input()
+        {
+            //arrange
+            var inputData = new[] { -1.0 };
+            //act
+            var gainLossRatio = inputData.GainLossRatio();
+            //assert
+            Assert.AreEqual(0.0, gainLossRatio);
+        }
+
+        [Test]
+        //Not sure this is correct.  Undefined may be more correct.
+        public void returns_zero_for_a_set_of_all_positive_numbers()
+        {
+            //arrange
+            var inputData = new[] { 1.0, 2.0, 3.0 };
+            //act
+            var gainLossRatio = inputData.GainLossRatio();
+            //assert
+            Assert.AreEqual(0.0, gainLossRatio);
+        }
+
+        [Test]
+        //Not sure this is correct.  Undefined may be more correct.
+        public void returns_zero_for_a_set_of_all_negative_numbers()
+        {
+            //arrange
+            var inputData = new[] { -1.0, -2.0, -3.0 };
+            //act
+            var gainLossRatio = inputData.GainLossRatio();
+            //assert
+            Assert.AreEqual(0.0, gainLossRatio);
+        }
+
+        [Test]
+        public void handles_a_value_of_zero_as_a_positive()
+        {
+            //arrange
+            var inputData = new[] { 0.0, 1.0, 2.0 };
+            //act
+            var gainLossRatio = inputData.GainLossRatio();
+            //assert
+            Assert.AreEqual(0.0, gainLossRatio);
+        }
+
+        [Test]
+        public void calculates_the_correct_ratio_given_a_set_of_gains_and_losses()
+        {
+            //arrange
+            var inputData = new[] { -2.0, -1.0, 0.0, 1.0, 2.0 };
+            var meanOfGains = inputData.Where(x => x >= 0).Mean();
+            var meanOfLosses = inputData.Where(x => x < 0).Mean();
+            var expectedRatio = Math.Abs(meanOfGains / meanOfLosses);
+            //act
+            var gainLossRatio = inputData.GainLossRatio();
+            //assert
+            Assert.AreEqual(expectedRatio, gainLossRatio);
+        }
     }
 }
diff --git a/src/UnitTests/UnitTests.csproj b/src/UnitTests/UnitTests.csproj
index 257c5945..51cb7a03 100644
--- a/src/UnitTests/UnitTests.csproj
+++ b/src/UnitTests/UnitTests.csproj
@@ -123,6 +123,7 @@
     <Compile Include="DistributionTests\Multivariate\NormalGammaTests.cs" />
     <Compile Include="DistributionTests\Multivariate\WishartTests.cs" />
     <Compile Include="FinancialTests\DownsideDeviationTests.cs" />
+    <Compile Include="FinancialTests\GainLossRatioTests.cs" />
     <Compile Include="FinancialTests\GainStandardDeviationTests.cs" />
     <Compile Include="FinancialTests\LossMeanTests.cs" />
     <Compile Include="FinancialTests\GainMeanTests.cs" />

From b8f4e66770dca690e99df9ab25f8ee2b0c18a5c3 Mon Sep 17 00:00:00 2001
From: Phil <pdoh00@gmail.com>
Date: Fri, 29 Mar 2013 08:08:03 -0700
Subject: [PATCH 3/5] Updated financial calcs and unit tests to deal with NaN
 return

---
 .../Financial/AbsoluteReturnMeasures.cs       | 103 ++++++++++++++++++
 .../Financial/AbsoluteRiskStatistics.cs       |  46 +-------
 src/Numerics/Numerics.csproj                  |   1 +
 .../CompoundMonthlyReturnTests.cs             |  75 +++++++++++++
 .../FinancialTests/DownsideDeviationTests.cs  |   1 +
 .../FinancialTests/GainLossRatioTests.cs      |  23 ++--
 src/UnitTests/FinancialTests/GainMeanTests.cs |   9 +-
 .../GainStandardDeviationTests.cs             |   1 +
 src/UnitTests/FinancialTests/LossMeanTests.cs |  15 +--
 .../LossStandardDeviationTests.cs             |   1 +
 .../FinancialTests/SemiDeviationTests.cs      |   1 +
 src/UnitTests/UnitTests.csproj                |   1 +
 12 files changed, 213 insertions(+), 64 deletions(-)
 create mode 100644 src/Numerics/Financial/AbsoluteReturnMeasures.cs
 create mode 100644 src/UnitTests/FinancialTests/CompoundMonthlyReturnTests.cs

diff --git a/src/Numerics/Financial/AbsoluteReturnMeasures.cs b/src/Numerics/Financial/AbsoluteReturnMeasures.cs
new file mode 100644
index 00000000..369340a8
--- /dev/null
+++ b/src/Numerics/Financial/AbsoluteReturnMeasures.cs
@@ -0,0 +1,103 @@
+// <copyright file="AbsoluteReturnMeasures.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+//
+// Copyright (c) 2009-2010 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.Financial
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using System.Text;
+    using MathNet.Numerics.Statistics;
+
+    public static class AbsoluteReturnMeasures
+    {
+        /// <summary>
+        /// Compound Monthly Return or Geometric Return or Annualized Return
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        public static double CompoundMonthlyReturn(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var samples = data.Count();
+            if (samples == 0)
+                return double.NaN;
+
+            double compoundReturn = 1.0;
+            foreach (var item in data)
+            {
+                compoundReturn *= (1 + item);
+            }
+            return Math.Pow(compoundReturn, 1.0 / (double)samples) - 1.0;
+        }
+
+        /// <summary>
+        /// Average Gain or Gain Mean
+        /// This is a simple average (arithmetic mean) of the periods with a gain. It is calculated by summing the returns for gain periods (return 0) 
+        /// and then dividing the total by the number of gain periods.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
+        public static double GainMean(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var gains = data.Where(x => x >= 0);
+            return gains.Mean();
+        }
+
+        /// <summary>
+        /// Average Loss or LossMean
+        /// This is a simple average (arithmetic mean) of the periods with a loss. It is calculated by summing the returns for loss periods (return < 0)
+        /// and then dividing the total by the number of loss periods.
+        /// </summary>
+        /// <param name="data"></param>
+        /// <returns></returns>
+        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
+        public static double LossMean(this IEnumerable<double> data)
+        {
+            if (data == null)
+            {
+                throw new ArgumentNullException("data");
+            }
+
+            var losses = data.Where(x => x < 0);
+            return losses.Mean();
+        }
+    }
+}
\ No newline at end of file
diff --git a/src/Numerics/Financial/AbsoluteRiskStatistics.cs b/src/Numerics/Financial/AbsoluteRiskStatistics.cs
index 0d7e8aa6..f092493e 100644
--- a/src/Numerics/Financial/AbsoluteRiskStatistics.cs
+++ b/src/Numerics/Financial/AbsoluteRiskStatistics.cs
@@ -36,7 +36,7 @@ namespace MathNet.Numerics.Financial
     using System.Text;
     using MathNet.Numerics.Statistics;
 
-    public static class AbsoluteRiskStatistics
+    public static class AbsoluteRiskMeasures
     {
         //Note: The following statistics would be condidered an absolute risk statistic in the finance realm as well.
         // Standard Deviation 
@@ -135,44 +135,6 @@ namespace MathNet.Numerics.Financial
             return belowMeanData.StandardDeviation();
         }
 
-        /// <summary>
-        /// Average Gain or Gain Mean
-        /// This is a simple average (arithmetic mean) of the periods with a gain. It is calculated by summing the returns for gain periods (return 0) 
-        /// and then dividing the total by the number of gain periods.
-        /// </summary>
-        /// <param name="data"></param>
-        /// <returns></returns>
-        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
-        public static double GainMean(this IEnumerable<double> data)
-        {
-            if (data == null)
-            {
-                throw new ArgumentNullException("data");
-            }
-
-            var gains = data.Where(x => x >= 0);
-            return gains.Mean();
-        }
-
-        /// <summary>
-        /// Average Loss or LossMean
-        /// This is a simple average (arithmetic mean) of the periods with a loss. It is calculated by summing the returns for loss periods (return < 0)
-        /// and then dividing the total by the number of loss periods.
-        /// </summary>
-        /// <param name="data"></param>
-        /// <returns></returns>
-        /// <remarks>http://www.offshore-library.com/kb/statistics.php</remarks>
-        public static double LossMean(this IEnumerable<double> data)
-        {
-            if (data == null)
-            {
-                throw new ArgumentNullException("data");
-            }
-
-            var losses = data.Where(x => x < 0);
-            return losses.Mean();
-        }
-
         /// <summary>
         /// Measures a fund’s average gain in a gain period divided by the fund’s average loss in a losing
         /// period. Periods can be monthly or quarterly depending on the data frequency.
@@ -190,9 +152,9 @@ namespace MathNet.Numerics.Financial
             var losses = data.Where(x => x < 0);
 
             var lossMean = losses.Mean();
-            if(lossMean != 0.0)
-                return Math.Abs(gains.Mean() / losses.Mean());
-            return 0.0;
+
+            return Math.Abs(gains.Mean() / losses.Mean());
+
         }
     }
 }
diff --git a/src/Numerics/Numerics.csproj b/src/Numerics/Numerics.csproj
index 226e8d46..8da1e940 100644
--- a/src/Numerics/Numerics.csproj
+++ b/src/Numerics/Numerics.csproj
@@ -105,6 +105,7 @@
     <Compile Include="Constants.cs" />
     <Compile Include="Control.cs" />
     <Compile Include="Complex32.cs" />
+    <Compile Include="Financial\AbsoluteReturnMeasures.cs" />
     <Compile Include="Financial\AbsoluteRiskStatistics.cs" />
     <Compile Include="LinearAlgebra\Generic\Matrix.BCL.cs" />
     <Compile Include="LinearAlgebra\Generic\Vector.BCL.cs" />
diff --git a/src/UnitTests/FinancialTests/CompoundMonthlyReturnTests.cs b/src/UnitTests/FinancialTests/CompoundMonthlyReturnTests.cs
new file mode 100644
index 00000000..1cbc23dc
--- /dev/null
+++ b/src/UnitTests/FinancialTests/CompoundMonthlyReturnTests.cs
@@ -0,0 +1,75 @@
+// <copyright file="CompoundMonthlyReturnTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+// Copyright (c) 2009-2010 Math.NET
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.FinancialTests
+{
+    using System;
+    using System.Collections.Generic;
+    using System.Linq;
+    using System.Text;
+    using MathNet.Numerics.Financial;
+    using NUnit.Framework;
+
+    [TestFixture]
+    [Category("FinancialTests")]
+    public class CompoundMonthlyReturnTests
+    {
+        [Test]
+        [ExpectedException(typeof(ArgumentNullException))] //assert
+        public void throws_when_input_data_is_null()
+        {
+            //arrange
+            List<double> inputData = null;
+            //act
+            inputData.CompoundMonthlyReturn();
+        }
+
+        [Test]
+        public void returns_undefined_with_empty_input_data()
+        {
+            //arrange
+            List<double> inputData = new List<double>();
+            //act
+            var cmpdReturn = inputData.CompoundMonthlyReturn();
+            //assert
+            Assert.AreEqual(double.NaN, cmpdReturn);
+        }
+
+        [Test]
+        public void calculates_the_compound_monthly_return()
+        {
+            //arrange
+            var inputData = new[] { 0.2, 0.06, 0.01 };
+            //act
+            var cmpdReturn = inputData.CompoundMonthlyReturn();
+            //assert
+            AssertHelpers.AlmostEqual(0.0870999982199265, cmpdReturn, 15);
+        }
+
+        //Definitly need more tests here.  Would love to find test data for these stats similar to the .dat files used for other tests.
+    }
+
+}
\ No newline at end of file
diff --git a/src/UnitTests/FinancialTests/DownsideDeviationTests.cs b/src/UnitTests/FinancialTests/DownsideDeviationTests.cs
index fa2e2165..d57075bf 100644
--- a/src/UnitTests/FinancialTests/DownsideDeviationTests.cs
+++ b/src/UnitTests/FinancialTests/DownsideDeviationTests.cs
@@ -34,6 +34,7 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class DownsideDeviationTests
     {
         [Test]
diff --git a/src/UnitTests/FinancialTests/GainLossRatioTests.cs b/src/UnitTests/FinancialTests/GainLossRatioTests.cs
index d3c3536b..571345df 100644
--- a/src/UnitTests/FinancialTests/GainLossRatioTests.cs
+++ b/src/UnitTests/FinancialTests/GainLossRatioTests.cs
@@ -34,6 +34,7 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class GainLossRatioTests
     {
         [Test]
@@ -48,61 +49,61 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
 
         [Test]
         //Not sure this is correct.  Undefined may be more correct.
-        public void returns_zero_for_a_single_positive_input()
+        public void returns_NaN_for_a_single_positive_input()
         {
             //arrange
             var inputData = new[] { 1.0 };
             //act
             var gainLossRatio = inputData.GainLossRatio();
             //assert
-            Assert.AreEqual(0.0, gainLossRatio);
+            Assert.AreEqual(double.NaN, gainLossRatio);
         }
 
         [Test]
         //Not sure this is correct.  Undefined may be more correct.
-        public void returns_zero_for_a_single_negative_input()
+        public void returns_NaN_for_a_single_negative_input()
         {
             //arrange
             var inputData = new[] { -1.0 };
             //act
             var gainLossRatio = inputData.GainLossRatio();
             //assert
-            Assert.AreEqual(0.0, gainLossRatio);
+            Assert.AreEqual(double.NaN, gainLossRatio);
         }
 
         [Test]
         //Not sure this is correct.  Undefined may be more correct.
-        public void returns_zero_for_a_set_of_all_positive_numbers()
+        public void returns_NaN_for_a_set_of_all_positive_numbers()
         {
             //arrange
             var inputData = new[] { 1.0, 2.0, 3.0 };
             //act
             var gainLossRatio = inputData.GainLossRatio();
             //assert
-            Assert.AreEqual(0.0, gainLossRatio);
+            Assert.AreEqual(double.NaN, gainLossRatio);
         }
 
         [Test]
         //Not sure this is correct.  Undefined may be more correct.
-        public void returns_zero_for_a_set_of_all_negative_numbers()
+        public void returns_NaN_for_a_set_of_all_negative_numbers()
         {
             //arrange
             var inputData = new[] { -1.0, -2.0, -3.0 };
             //act
             var gainLossRatio = inputData.GainLossRatio();
             //assert
-            Assert.AreEqual(0.0, gainLossRatio);
+            Assert.AreEqual(double.NaN, gainLossRatio);
         }
 
         [Test]
         public void handles_a_value_of_zero_as_a_positive()
         {
             //arrange
-            var inputData = new[] { 0.0, 1.0, 2.0 };
+            var inputData = new[] { 0.0, -1.0 };
             //act
-            var gainLossRatio = inputData.GainLossRatio();
+            var gainLossRatio = inputData.GainLossRatio(); 
             //assert
-            Assert.AreEqual(0.0, gainLossRatio);
+            Assert.AreEqual(0.0, gainLossRatio); //0.0 / -1.0 => 0.0
         }
 
         [Test]
diff --git a/src/UnitTests/FinancialTests/GainMeanTests.cs b/src/UnitTests/FinancialTests/GainMeanTests.cs
index 154d92a1..c91d9460 100644
--- a/src/UnitTests/FinancialTests/GainMeanTests.cs
+++ b/src/UnitTests/FinancialTests/GainMeanTests.cs
@@ -33,6 +33,7 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class GainMeanTests
     {
         [Test]
@@ -46,14 +47,14 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
             Assert.AreEqual(0.0, gainMean);
         }
         [Test]
-        public void returns_zero_when_all_input_is_negative()
+        public void returns_NaN_when_all_input_is_negative()
         {
             //arrange
             var inputData = new[] { -1.0, -2.0, -3.0 };
             //act
             var gainMean = inputData.GainMean();
             //assert
-            Assert.AreEqual(0.0, gainMean);
+            Assert.AreEqual(double.NaN, gainMean);
         }
 
         [Test]
@@ -91,14 +92,14 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
         }
 
         [Test]
-        public void returns_zero_with_no_input_data()
+        public void returns_NaN_with_no_input_data()
         {
             //arrange
             var inputData = new List<double>();
             //act
             var gainMean = inputData.GainMean();
             //assert
-            Assert.AreEqual(0.0, gainMean);
+            Assert.AreEqual(double.NaN, gainMean);
         }
 
     }
diff --git a/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs b/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs
index f7a163fe..d9dbc79b 100644
--- a/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs
+++ b/src/UnitTests/FinancialTests/GainStandardDeviationTests.cs
@@ -34,6 +34,7 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class GainStandardDeviationTests
     {
         [Test]
diff --git a/src/UnitTests/FinancialTests/LossMeanTests.cs b/src/UnitTests/FinancialTests/LossMeanTests.cs
index 8b57a4e4..6646cc87 100644
--- a/src/UnitTests/FinancialTests/LossMeanTests.cs
+++ b/src/UnitTests/FinancialTests/LossMeanTests.cs
@@ -33,28 +33,29 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class LossMeanTests
     {
         [Test]
-        public void returns_zero_when_zero_is_the_only_input()
+        public void returns_NaN_when_zero_is_the_only_input()
         {
             //arrange
             var inputData = new[] { 0.0 };
             //act
             var lossMean = inputData.LossMean();
             //assert
-            Assert.AreEqual(0.0, lossMean);
+            Assert.AreEqual(double.NaN, lossMean);
         }
 
         [Test]
-        public void returns_zero_when_all_input_is_positive()
+        public void returns_NaN_when_all_input_is_positive()
         {
             //arrange
-            var inputData = new[] { 1.0 };
+            var inputData = new[] { 0.0, 1.0 };
             //act
             var lossMean = inputData.LossMean();
             //assert
-            Assert.AreEqual(0.0, lossMean);
+            Assert.AreEqual(double.NaN, lossMean);
         }
 
         [Test]
@@ -92,14 +93,14 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
         }
 
         [Test]
-        public void returns_zero_with_no_input_data()
+        public void returns_NaN_with_no_input_data()
         {
             //arrange
             var inputData = new List<double>();
             //act
             var lossMean = inputData.LossMean();
             //assert
-            Assert.AreEqual(0.0, lossMean);
+            Assert.AreEqual(double.NaN, lossMean);
         }
     }
 }
diff --git a/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs b/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs
index b3367ec5..27728703 100644
--- a/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs
+++ b/src/UnitTests/FinancialTests/LossStandardDeviationTests.cs
@@ -34,6 +34,7 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class LossStandardDeviationTests
     {
         [Test]
diff --git a/src/UnitTests/FinancialTests/SemiDeviationTests.cs b/src/UnitTests/FinancialTests/SemiDeviationTests.cs
index 0394b10e..8f631f93 100644
--- a/src/UnitTests/FinancialTests/SemiDeviationTests.cs
+++ b/src/UnitTests/FinancialTests/SemiDeviationTests.cs
@@ -34,6 +34,7 @@ namespace MathNet.Numerics.UnitTests.FinancialTests
     using NUnit.Framework;
 
     [TestFixture]
+    [Category("FinancialTests")]
     public class SemiDeviationTests
     {
         [Test]
diff --git a/src/UnitTests/UnitTests.csproj b/src/UnitTests/UnitTests.csproj
index 51cb7a03..487e3c6f 100644
--- a/src/UnitTests/UnitTests.csproj
+++ b/src/UnitTests/UnitTests.csproj
@@ -122,6 +122,7 @@
     <Compile Include="DistributionTests\Multivariate\MultinomialTests.cs" />
     <Compile Include="DistributionTests\Multivariate\NormalGammaTests.cs" />
     <Compile Include="DistributionTests\Multivariate\WishartTests.cs" />
+    <Compile Include="FinancialTests\CompoundMonthlyReturnTests.cs" />
     <Compile Include="FinancialTests\DownsideDeviationTests.cs" />
     <Compile Include="FinancialTests\GainLossRatioTests.cs" />
     <Compile Include="FinancialTests\GainStandardDeviationTests.cs" />

From 86428a2caf8f8feeb59bfc2fc235b14460d30919 Mon Sep 17 00:00:00 2001
From: Phil <pdoh00@gmail.com>
Date: Fri, 29 Mar 2013 08:14:16 -0700
Subject: [PATCH 4/5] renamed file to match class name

---
 .../{AbsoluteRiskStatistics.cs => AbsoluteRiskMeasures.cs}      | 0
 src/Numerics/Numerics.csproj                                    | 2 +-
 2 files changed, 1 insertion(+), 1 deletion(-)
 rename src/Numerics/Financial/{AbsoluteRiskStatistics.cs => AbsoluteRiskMeasures.cs} (100%)

diff --git a/src/Numerics/Financial/AbsoluteRiskStatistics.cs b/src/Numerics/Financial/AbsoluteRiskMeasures.cs
similarity index 100%
rename from src/Numerics/Financial/AbsoluteRiskStatistics.cs
rename to src/Numerics/Financial/AbsoluteRiskMeasures.cs
diff --git a/src/Numerics/Numerics.csproj b/src/Numerics/Numerics.csproj
index 8da1e940..9249bd1a 100644
--- a/src/Numerics/Numerics.csproj
+++ b/src/Numerics/Numerics.csproj
@@ -106,7 +106,7 @@
     <Compile Include="Control.cs" />
     <Compile Include="Complex32.cs" />
     <Compile Include="Financial\AbsoluteReturnMeasures.cs" />
-    <Compile Include="Financial\AbsoluteRiskStatistics.cs" />
+    <Compile Include="Financial\AbsoluteRiskMeasures.cs" />
     <Compile Include="LinearAlgebra\Generic\Matrix.BCL.cs" />
     <Compile Include="LinearAlgebra\Generic\Vector.BCL.cs" />
     <Compile Include="SpecialFunctions\Evaluate.cs" />

From 043de9838e9886ff76f4995f6682bea44cd6b934 Mon Sep 17 00:00:00 2001
From: Christoph Ruegg <git@cdrnet.ch>
Date: Wed, 3 Apr 2013 23:23:03 +0200
Subject: [PATCH 5/5] Financial: tweaks, add to portable build

---
 .../Financial/AbsoluteReturnMeasures.cs       |  5 ++-
 .../Financial/AbsoluteRiskMeasures.cs         | 32 ++++---------------
 src/Portable/Portable.csproj                  |  6 ++++
 3 files changed, 14 insertions(+), 29 deletions(-)

diff --git a/src/Numerics/Financial/AbsoluteReturnMeasures.cs b/src/Numerics/Financial/AbsoluteReturnMeasures.cs
index 369340a8..446c9e33 100644
--- a/src/Numerics/Financial/AbsoluteReturnMeasures.cs
+++ b/src/Numerics/Financial/AbsoluteReturnMeasures.cs
@@ -4,7 +4,7 @@
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
 //
-// Copyright (c) 2009-2010 Math.NET
+// Copyright (c) 2009-2013 Math.NET
 //
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
@@ -33,8 +33,7 @@ namespace MathNet.Numerics.Financial
     using System;
     using System.Collections.Generic;
     using System.Linq;
-    using System.Text;
-    using MathNet.Numerics.Statistics;
+    using Statistics;
 
     public static class AbsoluteReturnMeasures
     {
diff --git a/src/Numerics/Financial/AbsoluteRiskMeasures.cs b/src/Numerics/Financial/AbsoluteRiskMeasures.cs
index f092493e..2db55192 100644
--- a/src/Numerics/Financial/AbsoluteRiskMeasures.cs
+++ b/src/Numerics/Financial/AbsoluteRiskMeasures.cs
@@ -4,7 +4,7 @@
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
 //
-// Copyright (c) 2009-2010 Math.NET
+// Copyright (c) 2009-2013 Math.NET
 //
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
@@ -33,8 +33,7 @@ namespace MathNet.Numerics.Financial
     using System;
     using System.Collections.Generic;
     using System.Linq;
-    using System.Text;
-    using MathNet.Numerics.Statistics;
+    using Statistics;
 
     public static class AbsoluteRiskMeasures
     {
@@ -60,10 +59,6 @@ namespace MathNet.Numerics.Financial
             }
 
             var gains = data.Where(x => x >= 0);
-            var count = gains.Count();
-            if (count == 0 || count == 1)
-                return double.NaN;
-
             return gains.StandardDeviation();
         }
 
@@ -82,10 +77,6 @@ namespace MathNet.Numerics.Financial
             }
 
             var losses = data.Where(x => x < 0);
-            var count = losses.Count();
-            if (count == 0 || count == 1)
-                return double.NaN;
-
             return losses.StandardDeviation();
         }
 
@@ -106,12 +97,8 @@ namespace MathNet.Numerics.Financial
                 throw new ArgumentNullException("data");
             }
 
-            var belowMARdata = data.Where(x => x < minimalAcceptableReturn);
-            var count = belowMARdata.Count();
-            if (count == 0 || count == 1)
-                return double.NaN;
-
-            return belowMARdata.StandardDeviation();
+            var belowMARData = data.Where(x => x < minimalAcceptableReturn);
+            return belowMARData.StandardDeviation();
         }
 
         /// <summary>
@@ -127,11 +114,8 @@ namespace MathNet.Numerics.Financial
                 throw new ArgumentNullException("data");
             }
 
-            var belowMeanData = data.Where(x => x < data.Mean());
-            var count = belowMeanData.Count();
-            if (count == 0 || count == 1)
-                return double.NaN;
-
+            var mean = data.Mean();
+            var belowMeanData = data.Where(x => x < mean);
             return belowMeanData.StandardDeviation();
         }
 
@@ -150,11 +134,7 @@ namespace MathNet.Numerics.Financial
 
             var gains = data.Where(x => x >= 0);
             var losses = data.Where(x => x < 0);
-
-            var lossMean = losses.Mean();
-
             return Math.Abs(gains.Mean() / losses.Mean());
-
         }
     }
 }
diff --git a/src/Portable/Portable.csproj b/src/Portable/Portable.csproj
index d279b8b5..c471e09e 100644
--- a/src/Portable/Portable.csproj
+++ b/src/Portable/Portable.csproj
@@ -192,6 +192,12 @@
     <Compile Include="..\Numerics\Distributions\Multivariate\Wishart.cs">
       <Link>Distributions\Multivariate\Wishart.cs</Link>
     </Compile>
+    <Compile Include="..\Numerics\Financial\AbsoluteReturnMeasures.cs">
+      <Link>Financial\AbsoluteReturnMeasures.cs</Link>
+    </Compile>
+    <Compile Include="..\Numerics\Financial\AbsoluteRiskMeasures.cs">
+      <Link>Financial\AbsoluteRiskMeasures.cs</Link>
+    </Compile>
     <Compile Include="..\Numerics\GlobalizationHelper.cs">
       <Link>GlobalizationHelper.cs</Link>
     </Compile>