Cointegration
Cointegration is a statistical concept in econometrics and time series analysis that describes a long-term equilibrium relationship between two or more non-stationary time series variables. It indicates that while individual series may wander randomly over time, a linear combination of them remains stationary, meaning they move together in the long run despite short-term deviations. This property is crucial for modeling and forecasting in fields like finance, economics, and environmental science.
Developers should learn cointegration when working on quantitative finance applications, such as algorithmic trading, risk management, or economic forecasting, where understanding long-term relationships between assets (e.g., stock prices, exchange rates) is essential. It is also valuable in data science projects involving time series data from economics, climate studies, or supply chain analytics to build robust models that account for underlying trends and avoid spurious regression results.