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Title: Forecasting cash holding with cash deposit using time series approaches
Authors: Kobpongkit Navapan
Jianxu Liu
Songsak Sriboonchitta
Keywords: Computer Science
Issue Date: 1-Feb-2017
Abstract: © Springer International Publishing AG 2017. The levels of cash holding and cash deposit for Thai banks have significantly increased over the past 10 years. This paper aims to forecast cash holding by using cash deposit. For banks, cash holding partially is from the cash deposited. In addition, accurate prediction on the cash holding would provide valuable information and indicators supervising bankers to control the levels of both cash holding and cash deposit effectively. In addition, the empirical relevance of cash holding and cash deposit is examined with three different models; linear model, ARIMA model and state space model. Experimental results with real data sets illustrate that state space model tends be the most accurate model compared to the other two models for prediction.
ISSN: 1860949X
Appears in Collections:CMUL: Journal Articles

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