Handouts
| Intro | Introduction |
| Chapt1 | Basic Concepts of Forecasting |
| LinPred | Linear Prediction of a Random Variable |
| Chapt2 | Trend-Line Fitting and Forecasting |
| Chapt3.1 | Forecasting from Time Series Models, Part I: White Noise and Moving Average Models |
| Chapt3.2 | Chapter 3, Part II: Autoregressive Models |
| Chapt3.3 | Chapter 3, Part III: Mixed Autoregressive-Moving Average Models |
| Chapt3.4 | Chapter 3, Part IV: The Box-Jenkins Approach to Model Building |
| Chapt3.5 | Chapter 3, Part V: More on Model Identification; Examples |
| AICC | The Corrected AIC |
| Analysis of Google Series, The Constant Term, Problems with t-ratios | |
| IMA | Integrated Moving Averages |
| Intervals | Forecast Intervals |
| NonLin | Nonlinear Models |
| Chaos | Chaos and Nonlinear Time Series |
| BestPred | Best Linear Forecasts Vs. Best Possible Forecasts |
| Scholes | Some Drawbacks of Black-Scholes |
| ARCH | ARCH Models and Conditional Volatility |
| ARCH.mle | Estimation and Automatic Selection of ARCH Models |
| UsingR | Using R for ARCH Modeling |
| LongMem | Long Memory in Volatility |
| DWTest | The Durbin Watson Test |
| UnitRoot | Differencing and Unit Root Tests |
| ARCH-M | ARCH-M Models |
| Chapt4.1 | Chapter 4, Part I: Cycles and the Seasonal Component |
| FED | Modeling the Federal Reserve Board Production Index |
| Pitfalls in Time Series | Discusses things that can go wrong, and describes cointegration. (Not an official handout). |