Chartered Market Technician (CMT) Practice Exam 2025 – Your All-in-One Guide to Exam Success!

Detrending price data is essential to identify underlying cycles without the influence of long-term trends or noise. Dividing closing prices by a moving average of those prices provides a clear view of the relative performance of the asset over a specific period. This method effectively normalizes the data, allowing for the isolation of cyclical patterns that might be masked by prevailing trends.

When prices are divided by a moving average, it helps visualize how the price behaves relative to its average performance over time. It highlights fluctuations and cycles rather than the overall trending direction of the price, enabling analysts to focus on short-term movements and recurring patterns.

Other methods, while useful in their contexts, do not specifically target cycle identification as effectively. Subtracting moving averages might reveal trends but can obscure cyclical behavior. Using exponential smoothing focuses more on recent data, which may diminish the visibility of cycles that span broader timeframes. Lastly, applying seasonal adjustments is excellent for data that exhibits strong seasonal patterns but does not necessarily assist in removing trends or identifying cycles in the same way that dividing by a moving average does.