文章基本信息

标题：Averaged-Calibration-Length Prediction for Currency Exchange Rates by a Time-Dependent Vasicek Model
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作者：Tomasz Serafin ; Anna Michalak ; Łukasz Bielak 等
期刊名称：Theoretical Economics Letters
印刷版ISSN：2162-2078
电子版ISSN：2162-2086
出版年度：2020
卷号：10
期号：3
页码：579-599
DOI：10.4236/tel.2020.103037
出版社：Scientific Research Publishing
摘要：The mining business is extremely sensitive to market factors in price behavior. One of the main risk factors in the KGHM, one of the biggest mining companies in the world, is the currency exchange rates prices. Thus, one of the main problems from the market risk management perspective is to properly predict the dynamics of the currency exchange rate data in the long-term horizon. In this paper, we propose to model the data by the so-called extended Vasicek model, which is a natural generalization of the classical Vasicek model, also known as the Ornstein-Uhlenbeck process. The classical model is very popular in the financial data modeling, however, it does not capture the possible changes in the long-term mean and long-term variance. The extended model takes into consideration the fact that the dynamics of the data may change over time by using time-varying coefficients. Applying the extended Vasicek model, we demonstrate the problem of long-term prediction and propose a new approach in this context which is based on the averaging of the predictions obtained from different calibration sample lengths.
关键词：Modeling;Vasicek Model;Time-Dependent Model;Long-Term Prediction;Calibration;Estimation