Page 3 - QuantScan-User Guide

Professional investors only
Statistics - Return
Proportion of positive (negative) returns is the number of positive (negative) returns divided by the total number of observations. A positive (negative) return is above (below) zero.
Mean - or mathematical expectation - is the central value of the distribution of returns.
Variance is the expectation of the squared deviations of returns from the mean. High variance indicates high deviations from the mean.
Skewness measures the asymmetry of the distribution of returns. A positive (negative) skewness indicates a larger tail on the right (left) of the number of returns. A normal distribution has a skewness of zero.
Kurtosis measures the outliers present in the distribution of returns. Higher kurtosis indicates more extreme deviations from the mean. A normal distribution has a kurtosis of 3.
Mean absolute deviation is the average of absolute deviations (i.e. positive differences) from the mean.
Standard deviation is the square root of the variance. If the distribution of returns is normal, 95% of returns are comprised between +/- 2 standard deviations from the mean.
Confidence Interval is the interval estimate (low and high) of the true mean of returns with 95% confidence.
Maximum - Minimum (Maximum return minus Minimum return) is the « range » of the distribution of returns. The higher the range, the more the dispersion of returns.
Quantiles indicate the cut points of the probability distribution of returns. Q2 is known as the « median » and Q3 - Q1 is known as the « interquartile range »).
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