|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
THETA AG
|
|
Tel. +41 44 217 80 14
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Rolling Moments
|
Single Asset View: MSCI EM
|
|
Index Family: [dynAAx EMMA]
|
|
|
|
|
|
|
How to read this graph
|
Time series plots of rolling moments show us how the distribution of financial returns changes over time. Moments, (mean and variance), and Cumulants (skewness and kurtosis) are computed from a running window of one year length which are shifted on a monthly base.
The mean is the average location measure of the returns. High values reflect high performance gains, negative values reflect losses. Steep increases in the mean reflect a bullish market, steep decreases a bearish market.
Standard deviation is computed as the square root of the variance which measures the disperson from the mean. High values of the standard deviation reflect a volatile market. Incresing volatility means increasing risk.
Skewness measures the spread of financial returns symmetrically around the mean value. A positive skewness tells us that gains overbalnance losse. On the otherhand a negative skewness reflects that losses dominate the financial return series.
Kurtosis is a measure of the peakedness of the financial return distribution. Higher kurtosis means more of the variance is due to infrequent extreme deviations, as opposed to frequent modestly-sized deviations. Financial return series with high kurtosis show often also fat tails.
|
|
|
|
|
|
|
|
|
|