Quantitative Definitions

Z Score

Z Score is a statistical measure that shows how many units of the standard deviation a case is above or below the mean of a data set.

Outlier

An outlier is a price data point that lies far away from the trendline. See also: Moving Averages

Normal Distribution

Normal distribution describes data set that varies around an average value. See also: Market Profile, Standard Deviation

Capital Asset Pricing Model – CAPM

The Capital Asset Pricing Model expresses the level of return an investor can expect relative to the amount of risk being assumed. The CAPM formula takes into account the time for which an investment is held and the amount of risk carried by the investment. See also: Modern Portfolio Theory (MPT)

Game Theory

Game theory is an area of applied mathematics and economics examining how entities behave in strategic situations where participants choose different actions in order to achieve the best results. Game Theory looks at what others are likely to do and their likely r

Monte Carlo Simulation

A method used to estimate a probable outcome using multiple simulations with random variables. In the context of finance, Monte Carlo Simulation is used to forecast the probabilities of different possible outcomes of a trading or investment strategy. Named after the wealthy European city which is al

Beta Coefficient

The Beta Coefficient in terms of finance and investing is a measure of the systematic risk of a stock or portfolio. It quantifies relative volatility in relation to the overall market, which is defined as having a beta of 1.0. A security or portfolio with a Beta value less than 1.0 indicates a lower

Linear/Arithmetic Scaling

On a linear or arithmetic scale chart, the spacing between each point on the vertical axis is equal. The scale is not averaged out to give more weight to the lower prices as with Logarithmic/Percentage Scaling.

Sharpe Ratio

Sharpe Ratio is a risk adjusted measure of a fund’s market performance. It measures a fund’s average historical return per unit of risk. The higher the number the better the fund has performed. This performance measure was developed by William F. Sharp

Alpha Equation

The alpha equation of a fund is as follows: [ (sum of y) -((b)(sum of x)) ] / n where: n =number of observations (36-60 months) b = beta of the fund x = rate of return for the S&P 500, or another benchmark index y = rate of return for the fund