| dc.contributor | 財管系 | |
| dc.creator (作者) | Chen, Jo-Hui;Chang, Ting-Tzu;Ho, Chao-Rung;Diaz, John Francis | |
| dc.date (日期) | 2014-11 | |
| dc.date.accessioned | 3-Sep-2015 14:48:28 (UTC+8) | - |
| dc.date.available | 3-Sep-2015 14:48:28 (UTC+8) | - |
| dc.date.issued (上傳時間) | 3-Sep-2015 14:48:28 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/78227 | - |
| dc.description.abstract (摘要) | This study employs the Grey Relational Analysis (GRA) and Artificial Neural Network (ANN) to measure the impact of key elements on the forecasting performance of real estate investment trust (REIT) returns. To manage risks from a real estate price bubble, the findings of GRA suggest that the REIT is best influenced by industrial production index, lending rate, dividend yield, stock index and its own lagged performance. Consequently, this paper adjusts the parameters from GRA and inserts the key elements into the fitted ANN model by comparing the learning effect of the Back-propagation Neural Network (BPN). This study found that the ranking provided by the GRA is significant in correcting prediction errors using the learning outcome of the BPN. The neural network model proved to minimize error function and was able to adjust weighted values in order to enhance prediction accuracy. | |
| dc.format.extent | 733651 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Quantitative Finance, 14(11), 2033-2044 | |
| dc.subject (關鍵詞) | Artificial Neural Network (ANN);Back-propagation Neural Network (BPN);F3;Grey Relational Analysis (GRA);Real estate investment trust (REIT) | |
| dc.title (題名) | Grey Relational Analysis and Neural Network Forecasting of REIT returns | |
| dc.type (資料類型) | article | en |
| dc.identifier.doi (DOI) | 10.1080/14697688.2013.816765 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1080/14697688.2013.816765 | |
