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<a href="../MathNet.Numerics.Financial/AbsoluteReturnMeasures.htm">AbsoluteReturnMeasures</a>
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<p class="class"><strong>Type</strong> AbsoluteRiskMeasures</p>
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<p><strong>Namespace</strong> MathNet.Numerics.Financial</p>
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<div class="sub-header">
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<h3 class="section">Static Functions</h3>
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<ul>
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<li><a href="../MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm#DownsideDeviation">DownsideDeviation</a></li>
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<li><a href="../MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm#GainLossRatio">GainLossRatio</a></li>
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<li><a href="../MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm#GainStandardDeviation">GainStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm#LossStandardDeviation">LossStandardDeviation</a></li>
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<li><a href="../MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm#SemiDeviation">SemiDeviation</a></li>
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<h3 class="section">Public Static Functions</h3>
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<div id="DownsideDeviation" class="method">
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<h4><span title="System.double">double</span> <strong>DownsideDeviation</strong>(this <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> data, <span title="System.double">double</span> minimalAcceptableReturn)</h4>
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<div class="content">This measure is similar to the loss standard deviation except the downside deviation
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considers only returns that fall below a defined minimum acceptable return (MAR) rather than the arithmetic mean.
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For example, if the MAR is 7%, the downside deviation would measure the variation of each period that falls below
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7%. (The loss standard deviation, on the other hand, would take only losing periods, calculate an average return for
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the losing periods, and then measure the variation between each losing return and the losing return average).
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</div>
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</div>
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<div id="GainLossRatio" class="method">
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<h4><span title="System.double">double</span> <strong>GainLossRatio</strong>(this <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> data)</h4>
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<div class="content">Measures a fund’s average gain in a gain period divided by the fund’s average loss in a losing
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period. Periods can be monthly or quarterly depending on the data frequency.
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</div>
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</div>
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<div id="GainStandardDeviation" class="method">
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<h4><span title="System.double">double</span> <strong>GainStandardDeviation</strong>(this <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> data)</h4>
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<div class="content">Calculation is similar to Standard Deviation , except it calculates an average (mean) return only for periods with a gain
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and measures the variation of only the gain periods around the gain mean. Measures the volatility of upside performance.
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© Copyright 1996, 1999 Gary L.Gastineau. First Edition. © 1992 Swiss Bank Corporation.
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</div>
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</div>
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<div id="LossStandardDeviation" class="method">
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<h4><span title="System.double">double</span> <strong>LossStandardDeviation</strong>(this <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> data)</h4>
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<div class="content">Similar to standard deviation, except this statistic calculates an average (mean) return for only the periods with a loss and then
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measures the variation of only the losing periods around this loss mean. This statistic measures the volatility of downside performance. <blockquote class="remarks">
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http://www.offshore-library.com/kb/statistics.php
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</blockquote>
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</div>
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</div>
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<div id="SemiDeviation" class="method">
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<h4><span title="System.double">double</span> <strong>SemiDeviation</strong>(this <span title="System.Collections.Generic.IEnumerable<double>">IEnumerable<double></span> data)</h4>
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<div class="content">A measure of volatility in returns below the mean. It's similar to standard deviation, but it only
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looks at periods where the investment return was less than average return.
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