Forecasting the Main Indicators of Insurance Companies
Анотація
Abstract. Introduction. Econometric and adaptive models make it possible to predict financial and economic indicators in the short and long term. The most common forecasting models are linear trend models, adaptive Brown, Holt, Holt-Winters, Box-Jenkins, autoregressive and other models. It has been proved that the use of adaptive forecasting models becomes especially relevant in the context of constant changes in the external environment, instability of the economic and political situation. Purpose. The purpose of this article is to substantiate the expediency of using forecasting methods when planning the development of the insurance market and to implement the procedure for forecasting the main indicators of its development using modern methods and techniques. Results. Improving the efficiency of the insurance market is facilitated by the correct organization of its planning and the direct implementation of the planned indicators. Optimality of planning is determined by the degree to which the accuracy of the predicted level of planned indicators is achieved. The methodology and results of the forecast of insurance payments made for the near future can be taken as a basis for drawing up current and strategic plans of insurance companies. Conclusions. It has been established that one of the barriers to the effective development of the insurance market in general and insurance companies in particular is the insufficient level of planning of their activities, especially in terms of forecasting key indicators. The procedure for forecasting the receipt of insurance payments was implemented using modern forecasting methods. The effectiveness of the Brown’s adaptive model for short-term planning of insurance premiums is proved. The proposed model was tested for adequacy, on its basis, recommendations were developed for further application in the practice of insurance companies. Keywords: insurance; insurance market; planning; forecasting; econometric model; adaptive model; trend extrapolation.
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