Improving the forecasting function for a Credit Hire operator in the UK

Nicolas D. Savio, Konstantinos Nikolopoulos () and Konstantinos Bozos

International Journal of Business Forecasting and Marketing Intelligence, 2009, vol. 1, issue 2, 134-138

Abstract: This study aims to test on the predictability of Credit Hire services for the automobile and insurance industry. A relatively sophisticated time series forecasting procedure, which conducts a competition among exponential smoothing models, is employed to forecast demand for a leading UK Credit Hire operator (CHO). The generated forecasts are compared against the Naive method, resulting that demand for CHO services is indeed extremely hard to forecast, as the underlying variable is the number of road accidents – a truly stochastic variable.

Keywords: time series forecasting; exponential smoothing; credit hire operators; CHO; automobile industry insurance industry; UK; United Kingdom; road accidents; automotive accidents; car accidents. (search for similar items in EconPapers)
Date: 2009
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