Handouts
| Handout | Topic |
| Notes 1 | Introduction, Basics |
| Notes 2 | Elementary Frequency Domain Facts and Techniques |
| Pgram | Figure: Periodograms |
| Notes 3 | Leakage, and its Reduction by Data Windows |
| Notes 4 | Properties of the Discrete Fourier Transform |
| Notes 5 | Smoothing, Linear Filtering |
| Filter | Figure: Linear Filtering of Interest Rates |
| Notes 6 | The Fast Fourier Transform |
| Notes 7 | The Periodogram of a Noise Series |
| Notes 8 | Formulas Involving the Periodogram and Sample Autocovariances |
| Notes 9 | The Spectrum |
| Notes10 | The Spectral Representation for Weakly Stationary Processes |
| Notes 11 | More on Linear Filters |
| Notes 12 | Autoregressive and Moving Average Processes in Discrete Time |
| Notes 13 | The Linear Prediction Problem |
| Notes 14 | Spectrum Estimation |
| ARMAbasics | The Basics of ARMA Models |
| NonLin | Nonlinear Models |
| GARCH | Conditional Heteroscedasticity and GARCH Models |
| Chaos | Chaos and Nonlinear Time Series |
| Spectrum | The Spectrum of a Weakly Stationary Process |
| Bispectrum | The Bispectrum and Tests for Nonlinearity |
| UnitRoot | Differencing and Unit Root Tests |
| Mem.Intro | Introduction to Long Memory Series |
| TreasMem | US Treasury Bills: Figures for Intro to Long Memory |
| FARIMA | The ARIMA(0,d,0) Model |
| Fractal | Fractals and Fractional Dimension |
| fBm | Continuous Time Long Memory Models: Fractional Brownian Motion and Fractional Gaussian Noise |
| FARIMA2 | The Fractional ARIMA(p,d,q) Model |
| Whittle | Whittle's Approximation to the Likelihood Function |
| Semipar | A Smiparametric Long Memory Model |
| Coint | Fractional Cointegration |
| YuleWalker | The Yule-Walker Equations |
| AICC | The AICC Criterion for Autoregressive Model Selection |