2. Lecture 10 Implementation Issues – Part 1

3. Overview Choosing among the various models Approaches for choosing parameters for the models

4. How to Choose Among the Various Models? Consider the application Precision: investment bank vs. strategic planning Security characteristics: sensitivity to term structure model assumptions Model deficiencies and the application Negative interest rates Perfect correlation among all rates Tradeoff – complexity vs. accuracy

5. How to Choose Parameters? You’ve chosen a model (whew!) Which parameters are best? Three approaches Judgment Statistical estimation Calibration

6. Statistical Estimation Analyze historical movements Given a specific interest rate model, jointly estimate all parameters Joint estimation is difficult Chan, Karolyi, Longstaff, and Saunders (1992, JF), Pearson and Sun (1994, JF), Amin and Morton (1994, JFE)

7. Model Calibration Interest rate model should reflect existing market conditions Model prices should approximate set of market prices Determine the best fit parameters for alternative interest rate models Various measures of “fit” Least sum of squared errors

8. Example 1: Volatility Volatility () is important for option pricing If parameter is too low, options will be underpriced If selling options, you will undercharge If buying options, you won’t find acceptable prices Lesson: Consistency with other actively traded security values Implied volatility

9. Example 2: Low Interest Rates Vasicek or CIR Estimate long-term mean of interest rates to set  (the mean level parameter) Value of  near 8% over last 30 years If today’s interest rate is 4.5%, what happens to asset values in a few years? Lesson: Consistency with current economy

10. Example 3: Yield Spread Options Yield spread options provide payoffs when the long-term rates exceed short-term rates by some margin (slope increases) One-factor models (like Vasicek, CIR, Ho-Lee, BDT) all assume all yields are perfectly correlated Limits the range of the slopes Lesson: Appropriate for application

11. Summary Structure of model is only half the battle Parameter selection is challenging Consider your application Be cognizant of model limitations Scrutinize projections