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  2. Downside risk - Wikipedia

    en.wikipedia.org/wiki/Downside_risk

    Downside risk is the financial risk associated with losses. That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference. That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference.

  3. Post-modern portfolio theory - Wikipedia

    en.wikipedia.org/wiki/Post-modern_portfolio_theory

    Downside risk (DR) is measured by target semi-deviation (the square root of target semivariance) and is termed downside deviation. It is expressed in percentages and therefore allows for rankings in the same way as standard deviation. An intuitive way to view downside risk is the annualized standard deviation of returns below the target.

  4. Tracking error - Wikipedia

    en.wikipedia.org/wiki/Tracking_error

    The best measure is the standard deviation of the difference between the portfolio and index returns. Many portfolios are managed to a benchmark, typically an index. Some portfolios, notably index funds , are expected to replicate, before trading and other costs, the returns of an index exactly, while others ' actively manage ' the portfolio by ...

  5. Sharpe ratio - Wikipedia

    en.wikipedia.org/wiki/Sharpe_ratio

    The ex-post Sharpe ratio uses the same equation as the one above but with realized returns of the asset and benchmark rather than expected returns; see the second example below. The information ratio is a generalization of the Sharpe ratio that uses as benchmark some other, typically risky index rather than using risk-free returns.

  6. Deviation risk measure - Wikipedia

    en.wikipedia.org/wiki/Deviation_risk_measure

    In financial mathematics, a deviation risk measure is a function to quantify financial risk (and not necessarily downside risk) in a different method than a general risk measure. Deviation risk measures generalize the concept of standard deviation .

  7. Deviance (statistics) - Wikipedia

    en.wikipedia.org/wiki/Deviance_(statistics)

    In statistics, deviance is a goodness-of-fit statistic for a statistical model; it is often used for statistical hypothesis testing.It is a generalization of the idea of using the sum of squares of residuals (SSR) in ordinary least squares to cases where model-fitting is achieved by maximum likelihood.

  8. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.

  9. Deviation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Deviation_(statistics)

    In mathematics and statistics, deviation serves as a measure to quantify the disparity between an observed value of a variable and another designated value, frequently the mean of that variable. Deviations with respect to the sample mean and the population mean (or " true value ") are called errors and residuals , respectively.