Monte Carlo Simulation Vs Historical Simulation

Monte Carlo simulation and historical simulation are both methods that can be used to determine the riskiness of a financial project. However, each method uses different assumptions and techniques in order to come up with the probability distribution of possible…

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Monte Carlo Simulations

Monte Carlo simulations involve the creation of a computer-based model into which the variabilities and interrelationships between random variables are entered. A spread of results is obtained when the model is run many times – 100s or 1000s. The method…

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Continuous Compounding

Continuous compounding applies when either the frequency with which we calculate interest is infinitely large or the time interval is infinitely small. Put quite simply, under continuous compounding, time is viewed as continuous. This differs from discrete compounding where we…

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Lognormal Distribution Vs the Normal Distribution

A variable X is said to have a lognormal distribution if Y = ln(X) is normally distributed, where “ln” denotes the natural logarithm. In other words, when the logarithms of values form a normal distribution, we say that the original…

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Shortfall Risk, Safety-first Ratio and Selection of an Optimal Portfolio Using Roy’s Safety-first Criterion

Shortfall risk Shortfall risk refers to the probability that a portfolio will not exceed the minimum (benchmark) return that has been set by the investor. In other words, it is the risk that a portfolio will fall short of the…

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The standard Normal Distribution: Calculation and Interpretation of Probabilities

The standard normal distribution refers to a normal distribution that has been standardized such that it has a mean of 0 and a standard deviation of 1. The shorthand notation used is:

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Confidence Intervals

A confidence interval (CI) gives an “interval estimate” of an unknown population parameter such as the mean. It gives us the probability that the parameter lies within the stated interval (range). The precision or accuracy of the estimate depends on…

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Univariate Vs Multivariate Distributions and the role of Correlation in the Multivariate Normal Distribution

Univariate and multivariate normal distributions are very robust and useful in most statistical procedures. Understanding their form and function will help you learn a lot about most statistical routines.

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Key Properties of the Normal Distribution

A random variable is said to have the normal distribution (Gaussian curve) if its values make a smooth curve that assumes a “bell shape” A normal variable has a mean “μ”, pronounced as “mu” and a standard deviation “σ”, pronounced…

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Continuous Uniform Distribution

The continuous uniform distribution is such that the random variable X takes values between α (lower limit) and β (upper limit). In the field of statistics, α and β are known as the parameters of the continuous uniform distribution. We…

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