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  2. Expected return - Wikipedia

    en.wikipedia.org/wiki/Expected_return

    The expected return (or expected gain) on a financial investment is the expected value of its return (of the profit on the investment). It is a measure of the center of the distribution of the random variable that is the return. [1] It is calculated by using the following formula: [] = = where

  3. Modern portfolio theory - Wikipedia

    en.wikipedia.org/wiki/Modern_portfolio_theory

    The return - standard deviation space is sometimes called the space of 'expected return vs risk'. Every possible combination of risky assets, can be plotted in this risk-expected return space, and the collection of all such possible portfolios defines a region in this space.

  4. Markowitz model - Wikipedia

    en.wikipedia.org/wiki/Markowitz_model

    The Capital Market Line says that the return from a portfolio is the risk-free rate plus risk premium. Risk premium is the product of the market price of risk and the quantity of risk, and the risk is the standard deviation of the portfolio. The CML equation is : R P = I RF + (R M – I RF)σ P /σ M. where, R P = expected return of portfolio

  5. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    When only a sample of data from a population is available, the term standard deviation of the sample or sample standard deviation can refer to either the above-mentioned quantity as applied to those data, or to a modified quantity that is an unbiased estimate of the population standard deviation (the standard deviation of the entire population).

  6. Downside risk - Wikipedia

    en.wikipedia.org/wiki/Downside_risk

    That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference. [ 1 ] [ 2 ] Risk measures typically quantify the downside risk, whereas the standard deviation (an example of a deviation risk measure ) measures both the upside and downside risk.

  7. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    These are the expected value (or mean) and standard deviation of the variable's natural logarithm, ⁡ (), not the expectation and standard deviation of itself. Relation between normal and log-normal distribution.

  8. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    These inequalities are significant for their nearly complete lack of conditional assumptions. For example, for any random variable with finite expectation, the Chebyshev inequality implies that there is at least a 75% probability of an outcome being within two standard deviations of the expected value. However, in special cases the Markov and ...

  9. Risk–return spectrum - Wikipedia

    en.wikipedia.org/wiki/Risk–return_spectrum

    All this can be visualised by plotting expected return on the vertical axis against risk (represented by standard deviation upon that expected return) on the horizontal axis. This line starts at the risk-free rate and rises as risk rises. The line will tend to be straight, and will be straight at equilibrium (see discussion below on domination).