On the use of financial analysis tools for the study of Dst time series in the frame of complex systems

TL;DR

This paper explores the novel application of financial technical analysis tools to Dst time series data for predicting Earth's magnetic storms, aiming to enhance space weather forecasting methods.

Contribution

It introduces a new methodology applying SMA, Bollinger bands, and RSI to magnetospheric data, bridging financial analysis techniques with space weather prediction.

Findings

Encouraging results in identifying storm phases

Potential for early magnetic storm detection

Method shows promise for space weather forecasting

Abstract

Technical analysis is considered the oldest, currently omnipresent, method for financial markets analysis, which uses past prices aiming at the possible short-term forecast of future prices. In the frame of complex systems, methods used to quantitatively analyze specific dynamic phenomena are often used to analyze phenomena from other disciplines on the grounds that are governed by similar dynamics. An interesting task is the forecast of a magnetic storm. The hourly Dst is used as a global index for the monitoring of Earth's magnetosphere, which could be either in quiet (normal) or in magnetic storm (pathological) state. This work is the first attempt to apply technical analysis tools on Dst time series, aiming at the identification of indications which could be used for the study of the temporal evolution of Earth's magnetosphere state. We focus on the analysis of Dst time series around the occurrence of magnetic storms, discussing the possible use of the resulting information in the frame of multidisciplinary efforts towards extreme events forecasting. We employ the following financial analysis tools: simple moving average (SMA), Bollinger bands, and relative strength index (RSI). Using these tools, we formulate a methodology based on all indications that could be revealed in order to infer the onset, duration and recovery phase of a magnetic storm, focusing on the temporal sequence they occur. The applicability of the proposed methodology is examined on characteristic cases of magnetic storms with encouraging results for space weather forecasting.