Authors - Md. Shahidul Islam, Md. Raihan Habib Abstract - Detecting structural breaks and anticipating volatility regimes in foreign exchange markets remain challenging due to the non-stationary and nonlinear nature of exchange rate dynamics. This study proposes a non-parametric framework for identifying structural breaks in the NZD/ USD exchange rate by integrating sliding-window volatility estimation, concentration bound based change point detection, and wavelet-based time frequency analysis. Volatility is first quantified using a movingwindow approach and compared against a Hoeffding bound to detect extraordinary events. The resulting change points are used to segment the exchange rate series into statistically reliable sequences, which are subsequently analyzed using wavelet scalograms. Empirical results reveal a consistent three-regime structure in the wavelet domain, comprising post-event reaction, stable market behavior, and pre-event escalation phases. Non-parametric statistical tests confirm significant differences in volatility distributions across these regimes, with the pre-event regime exhibiting markedly higher variability and acting as a precursor to structural breaks. The findings demonstrate that wavelet coefficients contain informative signatures of impending market instability. Overall, the proposed framework provides an interpretable and robust approach for analyzing regime-dependent volatility dynamics and offers valuable insights for early warning and risk management in currency markets.
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