tendencydriven
Tendencydriven is a term used to describe an approach in data analysis and decision making in which actions are guided by detected tendencies or prevailing directions in data rather than by single, instantaneous observations. Tendencies may include momentum, long-term drift, seasonality, and regime shifts in the data-generating process.
In practice, tendencydriven methods integrate historical tendencies into predictive or control rules. They often use features
Applications span several fields. In finance, tendencydriven strategies rely on momentum or trend signals to form
Advantages include robustness to short-term noise and better alignment with evolving data patterns. Disadvantages include lag
The concept overlaps with trend following, momentum strategies, and nonstationarity-aware modelling. Critics caution that detecting genuine