Chapter 12: Time-Series Analysis

In this section

• Autoregressive and Moving Average Models
  Autoregressive and Moving Average Models (CFA Level 1): Autoregressive (AR) Models, Core Concept, and Why AR Models Matter. Key definitions, formulas, and exam tips.
• ARMA and ARIMA Processes
  ARMA and ARIMA Processes (CFA Level 1): ARMA(p, q) Models, Model Specification, and Identification via ACF and PACF. Key definitions, formulas, and exam tips.
• Unit Roots, Stationarity, and Forecasting
  Unit Roots, Stationarity, and Forecasting (CFA Level 1): Why Stationarity Matters, Stationarity: Formal Definition, and Concept of Unit Roots. Key definitions, formulas, and exam tips.
• Seasonality and Trend Analysis
  Seasonality and Trend Analysis (CFA Level 1): Core Concepts of Seasonality, Detecting Seasonality, and Understanding Trend Analysis. Key definitions, formulas, and exam tips.
• Autocorrelation and Partial Autocorrelation Functions
  Autocorrelation and Partial Autocorrelation Functions (CFA Level 1): Autocorrelation: Detecting Patterns Over Lags, Mathematical Definition, and What Large ACF Values Imply. Key definitions, formulas, and exam tips.
• Cointegration and Error Correction Models
  Cointegration and Error Correction Models (CFA Level 1): Background and Motivation, Preliminaries: Stationarity and Integrated Processes, and Defining Cointegration. Key definitions, formulas, and exam tips.