Real-time Analysis of the Elliott Wave Principle Utilizing Historical Market Data

Abstract

The Elliott wave Principle is a theory developed by Ralph Nelson Elliott which describes a pattern of movement in financial markets. When drawn correctly, Elliott waves provide an opportunity to make profitable buy and sell decisions. An Elliott wave consists of 5 waves or lines. There are many varieties of formations depending upon various rules (e.g., line length). Creating an Elliott wave with historical data can be relatively easy for several reasons. Since all data is known, it is possible to construct a complete wave and assess the wave in terms of profitability. Constructing Elliott waves in real-time is a considerable challenge compared to finding Elliott waves within historical data. The primary problem is that once a complete wave (all 5 lines) is identified, an investor cannot go back retroactively and enter a trade. Furthermore, the dynamics of real-time data can impact the identification of respective waves. This research first identifies Elliott waves using historical financial data. Various Elliott wave formations are characterized. After grouping similar waves, their respective formations are statistically analyzed and described in terms of probabilities. This information will provide insight into the assessment of Elliott waves using real-time data. Waiting to identify a complete Elliott wave in real-time is not very fruitful. Thus, this research examines the partial formation of Elliott waves.