Recent Articles

Standard Normal Distribution

A normal distribution can be described using just two parameters, namely (μ), mean and variance (σ2). In a normal distribution, these two variables could take any value. For example, for a normally distributed stock portfolio, the mean could be 10% and the standard...

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Confidence Intervals for a Normal Distribution

A confidence interval is an interval in which we expect the actual outcome to fall with a given probability (confidence). Consider the following statement: In a normal distribution, 68% of the values fall within 1 standard deviation of the mean. So, if X is a normal...

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Univariate Vs. Multivariate Distribution

A univariate distribution refers to the distribution of a single random variable. Note that the above characteristics we saw of a normal distribution are for the distribution of one normal random variable, representing a univariate distribution. On the other hand, a...

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Normal Distribution

The normal distribution is the well-known bell-shaped curve depicted below. The bell-shaped curve comes from a statistical tendency for outcomes to cluster symmetrically around the mean (or average). Deviations from the mean are described in terms of standard...

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Continuous Uniform Distribution

We know that a discrete uniform random variable is a discrete random variable for which the probability of each outcome is the same. We also know that a random variable is continuous if it can take an infinite number of values between the possible values for the...

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Tracking Error and Tracking Risk

Tracking error is a measure of how closely a portfolio follows its benchmark. A tracking error of zero means that the portfolio exactly follows its benchmark. The benchmark could be an index such as S&P 500 index. Let’s say the S&P 500 index provides a return...

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