TY - UNPB
T1 - A Comparative Study of Symbolic Aggregate Approximation and Topological Data Analysis
AU - Hobbelhagen, Fredrik
AU - Diamantis, Ioannis
PY - 2024/7/22
Y1 - 2024/7/22
N2 - The movement of stocks is often perceived as random due to the complex interactions between different stocks and the inherently chaotic nature of the market. This study investigates the similarity in stock movements across multiple industry sectors in Europe. Specifically, we apply Topological Data Analysis (TDA) to analyze stock time series data and compare the results with those obtained using an expanded form of a more classical time series analysis method, Symbolic Aggregate Approximation (SAX). Our findings suggest that TDA is better suited for detailed, high-frequency trading analyses as it captures ``local'' properties of the data, whereas SAX is more appropriate for broader analyses where less detail is required.
AB - The movement of stocks is often perceived as random due to the complex interactions between different stocks and the inherently chaotic nature of the market. This study investigates the similarity in stock movements across multiple industry sectors in Europe. Specifically, we apply Topological Data Analysis (TDA) to analyze stock time series data and compare the results with those obtained using an expanded form of a more classical time series analysis method, Symbolic Aggregate Approximation (SAX). Our findings suggest that TDA is better suited for detailed, high-frequency trading analyses as it captures ``local'' properties of the data, whereas SAX is more appropriate for broader analyses where less detail is required.
KW - topological data analysis
KW - symbolic aggregate approximation
KW - comparison
KW - time series
KW - stock markets
M3 - Preprint
BT - A Comparative Study of Symbolic Aggregate Approximation and Topological Data Analysis
ER -