The impact of federal fund rate changes on Thai stock market volatility: a time series based on clustering approach

As global financial markets become more connected, changes in U.S. monetary policy—particularly in the Federal Funds Rate—can have significant effects on economies like Thailand. This study explores how such policy changes influence volatility in the Thai stock market by applying a time-series clustering framework that integrates financial econometric modeling with unsupervised learning techniques. Focusing on 126 companies listed on the Stock Exchange of Thailand (SET), across 8 industry groups and 28 business sectors (excluding the suspended Mining sector), we aim to identify volatility patterns and sectoral sensitivities over different interest rate regimes. To overcome the limitations of traditional clustering on noisy, non-stationary financial data, we employ the ECCV (Enhanced Clustering using Conditional Volatility) framework. This approach extracts conditional volatility (CV) using a two-stage process: first, ARIMA models remove trends and seasonality; then, GARCH models estimate volatility from the residuals. These CV features serve as robust representations for clustering algorithms such as KMeans, Agglomerative, and neural network-based methods. For the real-world application, we utilize KDBA (K-means with DTW Barycenter Averaging) to account for temporal misalignments in financial time series. The research comprises two parts: (1) a benchmark study using 40 labeled datasets to assess the effectiveness of CV-based clustering across diverse scenarios, and (2) a real-world application analyzing how Thai stocks respond to changes in the U.S. Federal Funds Rate. Our results show that incorporating CV significantly enhances clustering performance, yielding clearer groupings and more interpretable insights than raw-data approaches. These findings underscore the value of volatility-aware techniques in understanding financial market dynamics and support more informed decision-making in the face of global monetary shifts.