PROCEEDINGS May 15, 16, 17, 18, 2005 - Casualty Actuarial Society

MODELING FINANCIAL SCENARIOS 205transforming the regression coefficients as in Formulas (3.5) and(3.6), we getdu t =0:13 ¢ (6:1% ¡ u t )dt ¡ 0:72dq t +0:76% ¢ dB ut :(3.22)Comments on Selecting Parameters of the ModelSome have argued that the performance of any model shouldbe measured by comparing projected results against history. Itis not our intent to perfectly match the distribution of historicalvalues for interest rates, equity returns, and so on. To do sowould naively predict a future based on random draws from thepast. If perfect fit is desired, history already provides the set ofeconomic scenarios that may be used for actuarial applicationsand the development of an integrated financial scenario model iscompletely unnecessary. Instead, the model presented here providesan alternative: an integrated approach to creating alternativescenarios that are tractable and realistic. While history is used togain important insights into the characteristics of relevant variables,it would be impossible to build tractable models that yielda perfect fit to historical distributions. In general, we believeour theoretical framework provides a parsimonious approach toclosed-form solutions of particular variables of interest.4. USING THE FINANCIAL SCENARIO MODELThe financial scenario model is an Excel spreadsheet thatbenefits from the use of a simulation software package called@RISK, available through Palisade Corporation (http://www.palisade.com). @RISK leverages the simplicity of spreadsheetsand integrates powerful analysis tools that are used to help randomlyselect future scenarios and examine risk in a stochasticfinancial environment. The software package allows users to defineuncertain variables as a distribution, take numerous drawsfrom these inputs, and then capture each iteration’s impact on auser-defined output variable of interest, such as profits, sales, oran insurer’s surplus.