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EN
Aim/purpose – The aim of this paper is to evaluate the efficiency of an investing in investment funds with different risk levels in times of a future life expectancy increase. For this purpose, it was analysed how future prices of the investment funds’ entities behave, depending on the window function and the age of the investors, in particular people of retirement age, for whom an investment income may be a supplementary way of raising additional capital. Design/methodology/approach – Based on the historical data of the funds chosen from the different risk groups, a simulation of their price behaviour in the window function was carried out covering investor’s further life expectancy. Then, based on the result, the distribution of prices was analysed and the efficiency of investing in investment funds according to risk exposure was evaluated. Findings – According to the conducted analyses, the funds with the lowest efficiency were share funds. The best funds, in terms of efficiency, were bond and money funds. Research implications/limitations – The study was conducted on a limited number of funds, but this analysis can help take investment decisions. Originality/value/contribution – In this study, the investment in investment funds is treated as a long-term project which expires after 25-30 years, and therefore it may be problematic to use standard methods of evaluation for the purpose of this paper. As a result, the NPV (Net Present Value) method was applied as a measure of the investment’s efficiency. In the literature, this approach to the evaluation of investment funds is unique.
PL
W artykule przedstawiono symulacyjną analizę efektywności wykorzystania metod numerycznych w prognozowaniu zmiennej ekonomicznej dla luk niesystematycznych. Do budowy prognoz inter- i ekstrapolacyjnych, na podstawie szeregów oczyszczonych z sezonowości, zostały wykorzystane metody: odcinkowa, łuków oraz Lagrange’a dla węzłów interpolacyjnych rozmieszczonych proporcjonalnie. Rozpatrywane były trzy warianty luk, różniące się odsetkami brakujących danych. Przeprowadzono również analizę porównawczą dokładności błędów prognoz inter- i ekstrapolacyjnych względem klasycznych modeli szeregu czasowego z trendem liniowym oraz periodycznym składnikiem sezonowym, jak również z trendem wykładniczym z relatywnie stałą sezonowością. Obliczenia zostały wykonane z wykorzystaniem pakietu R oraz Statistica 12.
EN
In the article was presented an efficiency analysis of numerical methods in forecasting economic variable with unsystematic gaps. To construction of inter- and extrapolative forecasts, based on the seasonal adjusted time series, were used: the segmental method, the arches method and the Lagrange interpolation method for nodes distributed proportionally. In analysis were considered three variants of gaps, differing in the percent-age of the missing data. A comparative analysis of the accuracy of forecast errors of classical time series with linear trend and periodic seasonal component and exponential trend with relatively constant seasonality was also performed. Calculations were made using R environment and Statistica 12.
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