시계열 회귀모형에 근거한 자동차 보험료 추정

Estimating Automobile Insurance Premiums Based on Time Series Regression

초록

An estimation model for premiums and components is essential to determine reasonable insurance premiums. In this study, we introduce diverse models for the estimation of property damage premiums(premium, depth and frequency) that include a regression model using a dummy variable, additive independent variable model,autoregressive error model, seasonal ARIMA model and intervention model. In addition, the actual property damage premium data was used to estimate the premium, depth and frequency for each model. The estimation results of the models are comparatively examined by comparing the RMSE(Root Mean Squared Errors) of estimates and actual data. Based on real data analysis, we found that the autoregressive error model showed the best performance.

키워드

Depth; Durbin-Watson; frequency; insurance; premium; regression; time series.; 더빈-왓슨 통계량; 보험료; 빈도; 시계열; 심도; 회귀모형.
제목
시계열 회귀모형에 근거한 자동차 보험료 추정
제목 (타언어)
Estimating Automobile Insurance Premiums Based on Time Series Regression
저자
김영화; 박원서
DOI
10.5351/KJAS.2013.26.2.237
발행일
2013-04
저널명
응용통계연구
권
26
호
2
페이지
237 ~ 252