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TitleFinancial Innovation and Divisia Monetary Indices in Taiwan:A Neural Network Approach
Creator陳樹衡
Chen,Shu-Heng
Key WordsFinancial Innovation; Neural Networks; Divisia Money
Date2002-06
Date Issued24-Nov-2010 22:04:56 (UTC+8)
SummaryIn this paper a weighted index measure of money using the ‘Divisia’ formulation is constructed for the Taiwan economy and its inflation forecasting potential is compared with that of its traditional simple sum counterpart. This research extends an earlier study by Gazely and Binner by examining the theory that rapid financial innovation, particularly during the financial liberalization of the 1980s, has been responsible for the poor performance of conventional simple sum monetary aggregates. The Divisia index is adjusted in two ways to allow for the major financial innovations that Taiwan has experienced since the 1970s. The technique of neural networks is used to allow a completely flexible mapping of the variables and a greater variety of functional form than is currently achievable using conventional econometric techniques. Results suggest that superior tracking of inflation is possible for networks that employ a Divisia M2 measure of money that has been adjusted to incorporate a learning mechanism to allow individuals to gradually alter their perceptions of the increased productivity of money. Divisia measures of money appear to offer advantages over their simple sum counter parts as macroeconomic indicators.
RelationEuropean Journal of Finance,8(2),238-247
Typearticle
DOI http://dx.doi.org/10.1080/13518470110071173
dc.creator (作者) 陳樹衡zh_TW
dc.creator (作者) Chen,Shu-Heng-
dc.date (日期) 2002-06-
dc.date.accessioned 24-Nov-2010 22:04:56 (UTC+8)-
dc.date.available 24-Nov-2010 22:04:56 (UTC+8)-
dc.date.issued (上傳時間) 24-Nov-2010 22:04:56 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/48588-
dc.description.abstract (摘要) In this paper a weighted index measure of money using the ‘Divisia’ formulation is constructed for the Taiwan economy and its inflation forecasting potential is compared with that of its traditional simple sum counterpart. This research extends an earlier study by Gazely and Binner by examining the theory that rapid financial innovation, particularly during the financial liberalization of the 1980s, has been responsible for the poor performance of conventional simple sum monetary aggregates. The Divisia index is adjusted in two ways to allow for the major financial innovations that Taiwan has experienced since the 1970s. The technique of neural networks is used to allow a completely flexible mapping of the variables and a greater variety of functional form than is currently achievable using conventional econometric techniques. Results suggest that superior tracking of inflation is possible for networks that employ a Divisia M2 measure of money that has been adjusted to incorporate a learning mechanism to allow individuals to gradually alter their perceptions of the increased productivity of money. Divisia measures of money appear to offer advantages over their simple sum counter parts as macroeconomic indicators.-
dc.language zh_TWen
dc.language.iso en_US-
dc.relation (關聯) European Journal of Finance,8(2),238-247en
dc.subject (關鍵詞) Financial Innovation; Neural Networks; Divisia Money-
dc.title (題名) Financial Innovation and Divisia Monetary Indices in Taiwan:A Neural Network Approachen
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1080/13518470110071173en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1080/13518470110071173en_US