mondatrend

Mondatrend is a term used in data analysis and market research to describe a method for extracting the monthly pattern and the long-term movement from monthly data. The term originated in early 2010s academic and industry discussions as a shorthand for combining seasonal decomposition with trend estimation, emphasizing month-level cycles.

Methodology: Mondatrend typically involves decomposing a monthly series into trend, seasonal, and residual components. Common techniques include seasonal-trend decomposition using LOESS (STL), seasonal adjustment methods such as X-12-ARIMA or X-13, and smoothing via moving averages. The approach aims to separate predictable monthly seasonality from the underlying trend to improve forecasting, benchmarking, and comparability across periods. Some implementations incorporate exogenous variables like promotions or macro indicators to explain irregularities.

Applications: Used in retail sales, consumer analytics, inventory planning, and finance to forecast monthly demand, evaluate performance, and guide marketing or supply-chain decisions.

Variations and limitations: While practical, mondatrend assumes some stability in seasonal patterns and requires sufficient historical data. Structural breaks, regime shifts, or extraordinary events can distort the decomposition, and misinterpretation of residuals is possible.

Reception and see also: In practice, analysts may refer to standard time-series decomposition or seasonal adjustment rather than the term itself. See also time-series analysis, seasonal adjustment, trend estimation, forecasting.