Algoritmic Trading System Based on State Model for Moving Average in a Binary-Temporal Representation

Abstract

One of the most basic methods of technical analysis that is used in the practice of investment is the analysis of moving averages, usually calculated for exchange rates in a candlestick representation. The following paper proposes a new, state model, describing the process of trajectory changes in a binary-temporal representation. This kind of representation carries a significantly higher informative value than the candlestick one. The model is based on a proper definition of the moving average, proposed for a binary-temporal representation. The new model allows for exchange rate trajectory prediction in a short future window and, as a consequence, can be used to construct effective HFT systems. The article provides a concept of this kind of system and its comparison with others based on historical data for AUD/NZD exchange rate from the 2014–2020 period.

Keywords

• automatic forecasting
• price forecasting
• high frequency econometric
• investment decision support
• econometric models