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.

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;
+        }
+    }
+}

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" />

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);
+        }
+
+    }
+}

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
+    {
+
+    }
+}

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);
+        }
+
+    }
+}

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; }
+    }
+}

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);
+        }
+    }
+}

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();
+        }
+    }
+}

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();
+        }
+    }
+}

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" />