Syllabus
Office hours: M 4pm-6pm or by appointment
Lectures:
Lecture 1: Introduction
Lecture 2: Introduction to Forecasting,
Lecture 3: Review of Linear Regression Model
Table02_3_Data.xls
Lecture 5: Statistics and Time Series,
Figure03_fig01_fig7_DJI.xls
Figure03_10_HoursWorkedUSA.xls
Lecture 6: Tools of the Forecaster,
Lecture 7: Forecasting using MA(q) models
PRS85006013.csv
Lecture 9: Forecasting with Autoregressive (AR) Processes,
Figure07_07_CAincome.xls
Lecture 10: Forecasting Practice 1,
Figure08_01_SDhouseprices.xls
Lecture 11: Seasonal Models,
Figure07_17_clothingsales.xls,
Figure07_19_constructionchanges.xls
Lecture 13: Assessment of Forecasts,
ghpca.wf1
Lecture 16: Deterministic Trends,
jnj.wf1
Lecture 18: Stochastic Trends,
ir_ur_inf.wf1
Lecture 20: Vector Autoregression Models (VAR),
hp_CA.wf1
Lecture 23: Forecasting the Long Term and the Short Term Jointly (VEC models),
npce_q.wf1
denmark.wf1
Lecture 25: Forecasting Volatility I,
rSP500weekly.wf1
Lecture 26: Forecasting Volatility II,
rSP500daily.wf1,
rGOOGdaily.wf1
Lecture 28: Financial Applications of Time-Varying Volatility,
Lecture 29: Financial Applications of Time-Varying Volatility,
aapl_fcx_sp500.wf1
Homeworks:
HW1 problems
HW2 problems
HW3 problems
HW4 problems
HW5 problems
HW6 problems
HW7 problems
HW8 problems
HW9 problems
Practice problems:
Practice Problems 1