Mahler 1 - Credibility and Shifting Risk Parameters Flashcards
1
Q
3 Criteria for evaluating credibility weighting
A
- Lease square error
- minimizes the squared error between observed and predicted results
- the smaller MSE, the better - Small chance of large errors
- minimizes the probability that observed results will be greater than k% different from predicted. - correlation
- calculate correlation between - ratio of actual losing % to predicted losing % and
- ratio of predicted losing % to grand mean
- closer to 0, the better
2
Q
three methods for testing risk parameter shift
A
- Binomial test
- determine whether there is an inherent difference in losing % among the teams
- if all teams results are from a random distribution, 95% of the teams would have an average losing % between 49% and 51%.
- only 3 of 16 teams did - Chi-squared
- Null: risk parameters do not shift over time
- Chi statistic = Sum[(actual - expected) ^2/expected]
- to test if there is a inherent difference in results over the years (i.e. are parameters shifting over time?)
- if statistic > chi-squared value => reject null - Study of correlation pairs
- group data by pairs based on time lag
- compute correlation between actual and expected for each pair
- calculate avg correlation by time lag
c. Exam correlation by lag pattern.
- if correlation decreases as the difference in time between the years increases => parameters are shifting over time.
3
Q
Effect of a delay in receiving data
A
- as delay increases, the squared error increases significantly
- as delay increases, optimal credibility decreases
4
Q
Contrasting Meyers/Dorweillers method vs LSE & small chance of large errors
A
- both least square and small chance of large errors method seek to eliminate large errors
- Meyers/Dorweiller method is more concerned with patterns of error.
5
Q
The estimate gets worse or better when more years of data are used when parameters shift over time.
A
worse