1. Forecast Objectives Fin250f: Lecture 8.2 Spring 2010 Reading: Brooks, chapter 5.9-5.11

2. Outline  Forecasting methodology and dangers  Linear forecasts  Forecast objectives

3. Forecasting Methodology  Prediction about tomorrow  In sample/Out of sample forecasts  One step ahead/multi-step Direct/iterative  Recursive/rolling windows

4. AR(1): Zero mean form

5. Forecasting the AR(1)

6. Forecasting the AR(1): Multiperiods

7. Forecasting an MA(1)

8. Exponential Smoothing  Ad hoc forecasting tool  Primitive (but maybe effective)  Common in business forecasting environments

9. Exponential Smoothing

10. Forecast Objectives  Mean Squared Error (MSE)  Mean Absolute Error (MAE)  Theil's U-statistic  Sign predictions  Trading profits

11. Mean Squared Error

12. Mean Absolute Error

13. Theil's U-statistic

14. Sign Prediction

15. Reminder on Central Limit Theorem

16. Binomial Test

17. Trading Profits

18. Comparisons  How do you weight outliers? MSE: a lot Sign: Not much  How does this connect to economics MSE: not much Sign: more Trading: a lot  Mistakes connected to real losses  Weights problems with large returns in a sensible way  Actual trading is still more complex (costs, slippage)