Analysis of short term price trends in daily stock-market index data

TL;DR

This paper investigates the duration of monotonic trends in daily stock-market index data, revealing deviations from no-memory models and comparing observed and expected distributions using statistical tests.

Contribution

It introduces an analysis of elemental trend durations in stock indices and compares their distributions to theoretical no-memory expectations.

Findings

Trend durations often differ from no-memory models

Observed distributions show significant deviations

Statistical tests confirm non-random trend durations

Abstract

In financial time series there are periods in which the value increases or decreases monotonically. We call those periods elemental trends and study the probability distribution of their duration for the indices DJIA, NASDAQ and IPC. It is found that the trend duration distribution often differs from the one expected under no memory. The expected and observed distributions are compared by means of the Anderson-Darling test.