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題名 Do economic variables improve bond return volatility forecasts?
作者 趙世偉
Chao, Shih Wei
貢獻者 金融系
關鍵詞 Bond return volatility; Predictive ability; Forecast combination; Forecast performance decomposition
日期 2016-11
上傳時間 23-Aug-2017 11:21:19 (UTC+8)
摘要 This paper explores whether various economic variables improve monthly bond return volatility forecasts using the 1963–2012 data. In-sample analysis indicates that stock return or Federal Funds rate difference Granger causes bond volatility of all maturities. The forecasting ability of other variables mainly appears at the short end of the term structure or during the relatively turbulent time. Out-of-sample analysis suggests little evidence of forecast improvement, though forecast combination does improve the performance. Decomposing the out-of-sample forecasts indicates that the poor performance is primarily attributed to overfitting, and variable reduction by principal components does not change the results.
關聯 International Review of Economics and Finance, 46, 10-26
資料類型 article
DOI http://dx.doi.org/10.1016/j.iref.2016.08.001
dc.contributor 金融系
dc.creator (作者) 趙世偉zh_tw
dc.creator (作者) Chao, Shih Weien_US
dc.date (日期) 2016-11
dc.date.accessioned 23-Aug-2017 11:21:19 (UTC+8)-
dc.date.available 23-Aug-2017 11:21:19 (UTC+8)-
dc.date.issued (上傳時間) 23-Aug-2017 11:21:19 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112113-
dc.description.abstract (摘要) This paper explores whether various economic variables improve monthly bond return volatility forecasts using the 1963–2012 data. In-sample analysis indicates that stock return or Federal Funds rate difference Granger causes bond volatility of all maturities. The forecasting ability of other variables mainly appears at the short end of the term structure or during the relatively turbulent time. Out-of-sample analysis suggests little evidence of forecast improvement, though forecast combination does improve the performance. Decomposing the out-of-sample forecasts indicates that the poor performance is primarily attributed to overfitting, and variable reduction by principal components does not change the results.
dc.format.extent 418548 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) International Review of Economics and Finance, 46, 10-26
dc.subject (關鍵詞) Bond return volatility; Predictive ability; Forecast combination; Forecast performance decomposition
dc.title (題名) Do economic variables improve bond return volatility forecasts?en_US
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.iref.2016.08.001
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.iref.2016.08.001