**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 |