Using Kurtosis and Skewness to Classify Trends and Enter Trades

Summary

The document introduces excess kurtosis and skewness as statistical measures for classifying market conditions. It proposes treating negative excess kurtosis as a sign of a trending market, then using positive skewness to indicate an upward bias and negative skewness to indicate a downward bias. The stated rules are to go long or short when those conditions align, and to exit when the trend reverses.

The accompanying trading-system example calculates both statistics over a rolling window, places stop entries around recent price levels after a kurtosis trigger, and offers several exit methods, including fixed stops, profit targets, time-based exits, and ATR trailing stops. The document gives definitions and parameter values but no performance results or validation. Its statistical interpretations are presented as trading heuristics; the text also shifts between raw kurtosis and excess kurtosis and includes example rules whose thresholds and signs do not clearly match the prose. These inconsistencies make independent implementation and testing necessary.

Key ideas

• Excess kurtosis is used to distinguish the proposed trending regime from sideways conditions.
• Skewness is used to infer whether the market has an upward or downward bias.
• The strategy combines regime classification with directional entries and exits on trend reversal.
• The example includes stop entries and multiple stop, target, time-based, and ATR trailing exit choices.
• The document supplies no performance evidence, and some definitions and example conditions are inconsistent.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.