Analysis of the trends in the index of the Dow Jones Industrial Average (DJIA) of the New York Stock Exchange (NYSE)

TL;DR

This paper analyzes historical DJIA data to decompose price movements into trend and random components, finding statistical evidence that recent trends can predict near-future index movements and potential economic downturns.

Contribution

It introduces a method to empirically decompose stock index data into trend and random parts and demonstrates that recent trend patterns can forecast upcoming index directions.

Findings

Historical trends can predict near-term DJIA movements.

Statistical evidence supports the relation between trend types and future index directions.

Recent trend patterns may indicate upcoming economic recessions.

Abstract

It is hypothesized that price charts can be empirically decomposed into two components as random and non random. The non random component, which can be treated as approximately regular behavior of the prices (trend) in an epoch, is a geometric line. Thus, the random component fluctuates around the non random component with various amplitudes. Moreover, the shape of a trend in an epoch may be different in another epoch. It is further hypothesized that statistical evidence can be found for various relations between several types of trends and the direction of the next movements of the prices. These hypotheses are tested on the historical data of the DJIA (Dow) and confirmed. Moreover, it is statistically showed that a number of trends that have occurred in the near past course of the Dow can be utilized to presage the near future of the index. As a result, upcoming of a recession in the DJIA, which may portend a worldwide economic crisis, is predicted.