Stationary Time Series

What this stationary time series question tests

This is an easy conceptual question on time series fundamentals. It checks whether you can identify and articulate the key properties that define a stationary process — a foundational requirement for anyone working with financial data, econometric models, or algorithmic trading strategies.

Stationarity is central to time series analysis because it governs which statistical methods are valid and which forecasting approaches will be reliable. Understanding its formal definition — and recognizing it in practice — is essential before applying techniques like ARIMA or cointegration tests. The question rewards clear recall of the mathematical conditions, not computation.

• Mean and variance stability over time
• Autocovariance structure and lag dependence
• Distinction between strict and weak stationarity
• Why non-stationary data leads to spurious regression