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題名 投資組合複製模型實證研究－以波羅的海指數為例
Empirical studies of portfolio replication: Baltic dry index作者 黃嘉閔
Huang, Chia-Min貢獻者 郭維裕
Kuo, Wei-Yu
黃嘉閔
Huang, Chia-Min關鍵詞 滾動視窗
遞迴視窗
最小平方法
追蹤投資組合
總體經濟
Rolling window
Recursive window
Least square
Tracking portfolio
Macroeconomics日期 2018 上傳時間 19-Jul-2018 17:24:00 (UTC+8) 摘要 本研究以Lamont (2001)提出的Economic Tracking Portfolio (ETP)追蹤波羅的海指數 (Baltic Dry Index)。 根據先前關於ETP的研究，如Christoffersen (2000), Hayes (2001), Junttila (2004) 與 Raunig (2007)，ETP皆以一國境內的資產報酬率預測國內總體經濟變數。Junttila (2007)將此方法延伸至以多國資產報酬率預測總體經濟變數。而本研究也以此概念追蹤波羅的海指數，並探討追蹤績效，基於不同的預測期間與估計期間，其中控制變數並無加入投資組合當中。研究結果顯示，無論資料頻率為何，遞迴視窗之追蹤績效優於滾動視窗。相較於其他產業，採礦業與鋼鐵業之報酬率包含最多關於波羅的海指數之資訊。整體而言，此追蹤投資組合能夠補捉波羅的海指數之趨勢，可被使用為避險工具以規避此風險。
In this paper, I apply the economic tracking portfolio (ETP) approach developed by Lamont (2001) to track Baltic Dry Index (BDI). According to previous studies of ETP, such as Christoffersen (2000), Hayes (2001), Junttila (2004) and Raunig (2007), ETP is tested in closed-economy, using domestic equity as base assets. Junttila (2007) extends this approach to forecast the macroeconomic variables by using international equity returns. Our study also utilizes this concept to forecast BDI, control variables ignored here, and investigates the tracking performance based on different data frequency, forecast horizon, and training period. The results show that, no matter what data frequency is, the performance of recursive window is better than that of rolling window. The returns of diversified mining and iron steel contain more information than other industries about BDI. As a whole, the tracking portfolio can capture the trend of BDI, and also can be used as hedging tool by the practitioners.參考文獻 [1] Chen, N., Roll, R. and Ross, S.A. (1986), Economic forces and the stock market, The Journal of Business, 59, 383-403.[2] Campbell, J. Y. (1991), A variance decomposition for stock returns, The Economic Jour- nal, 101, 157-179.[3] Chan, L. K. C., Karceski, J. and Lakonishok, J. (1998), The risk and return from factors, The Journal of Financial and Quantitative Analysis, 33, 159-188.[4] Christoffersen, P. and Slok, T. (2000), Do asset prices in transition countries contain information about future economic activity?, IMB, Working Paper.[5] Christoffersen, P., Ghysels, E. and Swanson R. (2002), Let’s get real about using economic data, Journal of Empirical Finance, 9, 343-360.[6] Dowing, C. T., Longstaff, F. A. and Rierson, M. A. (2012), Inflation tracing portfolios, NBER, Working Paper, No. 18135.[7] Estrella, A. and Mishkin, F. S. (1998), Predicting U.S. recession: financial variables as leading indicators, The Review of Economics and Statistics, 80, 45-61.[8] Harvey, C. R. (1989), Forecasts of economic growth from the bond and stock markets, Financial Analysts Journal, 45, 38-45.[9] Hayes, S. (2001), Leading indicator information in UK equity prices: an assessment of economic tracking portfolios, Bank of England, Working Paper, No. 137.[10] Ferson, W.E. and Harvey, C.R. (1991), The Variation of Economic Risk Premiums, Bank of England, The Journal of Business, 99, 385-415.[11] Ferson, W.E. and Korajczyk, R.A. (1995), Do arbitrage pricing model explain the pre- dictability of stock returns, Journal of Political Economy, 68, 309-349.[12] Jones, C.M., Lamont, O.A. and Lumsdaine, R.L. (1998), Macroeconomic news and bond market volatility, Journal of Financial Economics, 47, 315-337.[13] Junttila, J. (2004), The performance of economic tracking portfolios in an IT-intensive stock market, The Quarterly Review of Economics and Finance, 44, 601-623.[14] Junttila, J. (2007), Forecasting the macroeconomy with current financial market information: Europe and the United States, Review of Financial Economics, 16, 149-175.[15] Lamont, O. A. (2001), Economic tracking portfolios, Journal of Economics, 105, 161-184.[16] Lun, Y.H. and Quddus, M.A. (2009), An empirical model of the bulk shipping market, Int. J. Shipping and Transport Logistics, 1, 37-54.[17] Liew, J. and Vassalou, M. (2000), Can book-to-market, size and momentum be risk factors that predict economic growth, Journal of Financial Economics, 57, 221-245.[18] Mak, Y. K. (2006), An investigation of the forecasting ability of economic tracking portfolios (Master’s Thesis), Simon Fraser University.[19] Oomen, J.G.M. (2012), The Baltic Dry Index: A predictor of stock market returns (Master’s Thesis), Tilburg University.[20] Raunig, B. (2007), Are economic tracking portfolios useful for forecasting output and inflation in Austria?, Applied Financial Economics, 17, 1043-1049.[21] Vassalou, M. (2000), Exchange rate and foreign inflation risk premiums in global equity returns, Journal of International Money and Finance, 19, 433-470. 描述 碩士
國立政治大學
國際經營與貿易學系
105351020資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105351020 資料類型 thesis dc.contributor.advisor 郭維裕 zh_TW dc.contributor.advisor Kuo, Wei-Yu en_US dc.contributor.author (Authors) 黃嘉閔 zh_TW dc.contributor.author (Authors) Huang, Chia-Min en_US dc.creator (作者) 黃嘉閔 zh_TW dc.creator (作者) Huang, Chia-Min en_US dc.date (日期) 2018 en_US dc.date.accessioned 19-Jul-2018 17:24:00 (UTC+8) - dc.date.available 19-Jul-2018 17:24:00 (UTC+8) - dc.date.issued (上傳時間) 19-Jul-2018 17:24:00 (UTC+8) - dc.identifier (Other Identifiers) G0105351020 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/118751 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 國際經營與貿易學系 zh_TW dc.description (描述) 105351020 zh_TW dc.description.abstract (摘要) 本研究以Lamont (2001)提出的Economic Tracking Portfolio (ETP)追蹤波羅的海指數 (Baltic Dry Index)。 根據先前關於ETP的研究，如Christoffersen (2000), Hayes (2001), Junttila (2004) 與 Raunig (2007)，ETP皆以一國境內的資產報酬率預測國內總體經濟變數。Junttila (2007)將此方法延伸至以多國資產報酬率預測總體經濟變數。而本研究也以此概念追蹤波羅的海指數，並探討追蹤績效，基於不同的預測期間與估計期間，其中控制變數並無加入投資組合當中。研究結果顯示，無論資料頻率為何，遞迴視窗之追蹤績效優於滾動視窗。相較於其他產業，採礦業與鋼鐵業之報酬率包含最多關於波羅的海指數之資訊。整體而言，此追蹤投資組合能夠補捉波羅的海指數之趨勢，可被使用為避險工具以規避此風險。 zh_TW dc.description.abstract (摘要) In this paper, I apply the economic tracking portfolio (ETP) approach developed by Lamont (2001) to track Baltic Dry Index (BDI). According to previous studies of ETP, such as Christoffersen (2000), Hayes (2001), Junttila (2004) and Raunig (2007), ETP is tested in closed-economy, using domestic equity as base assets. Junttila (2007) extends this approach to forecast the macroeconomic variables by using international equity returns. Our study also utilizes this concept to forecast BDI, control variables ignored here, and investigates the tracking performance based on different data frequency, forecast horizon, and training period. The results show that, no matter what data frequency is, the performance of recursive window is better than that of rolling window. The returns of diversified mining and iron steel contain more information than other industries about BDI. As a whole, the tracking portfolio can capture the trend of BDI, and also can be used as hedging tool by the practitioners. en_US dc.description.tableofcontents Acknowledgement iAbstract ii1 Introduction 12 Literature Review 43 Methodology 64 Data 104.1 Variables selection 104.2 Preliminary analysis 115 Empirical results 125.1 In-sampleestimates 125.2 Out-of-sampleforecasts 146 Conclusions 17References 20Appendices 22 zh_TW dc.format.extent 1928931 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105351020 en_US dc.subject (關鍵詞) 滾動視窗 zh_TW dc.subject (關鍵詞) 遞迴視窗 zh_TW dc.subject (關鍵詞) 最小平方法 zh_TW dc.subject (關鍵詞) 追蹤投資組合 zh_TW dc.subject (關鍵詞) 總體經濟 zh_TW dc.subject (關鍵詞) Rolling window en_US dc.subject (關鍵詞) Recursive window en_US dc.subject (關鍵詞) Least square en_US dc.subject (關鍵詞) Tracking portfolio en_US dc.subject (關鍵詞) Macroeconomics en_US dc.title (題名) 投資組合複製模型實證研究－以波羅的海指數為例 zh_TW dc.title (題名) Empirical studies of portfolio replication: Baltic dry index en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1] Chen, N., Roll, R. and Ross, S.A. (1986), Economic forces and the stock market, The Journal of Business, 59, 383-403.[2] Campbell, J. Y. (1991), A variance decomposition for stock returns, The Economic Jour- nal, 101, 157-179.[3] Chan, L. K. C., Karceski, J. and Lakonishok, J. (1998), The risk and return from factors, The Journal of Financial and Quantitative Analysis, 33, 159-188.[4] Christoffersen, P. and Slok, T. (2000), Do asset prices in transition countries contain information about future economic activity?, IMB, Working Paper.[5] Christoffersen, P., Ghysels, E. and Swanson R. (2002), Let’s get real about using economic data, Journal of Empirical Finance, 9, 343-360.[6] Dowing, C. T., Longstaff, F. A. and Rierson, M. A. (2012), Inflation tracing portfolios, NBER, Working Paper, No. 18135.[7] Estrella, A. and Mishkin, F. S. (1998), Predicting U.S. recession: financial variables as leading indicators, The Review of Economics and Statistics, 80, 45-61.[8] Harvey, C. R. (1989), Forecasts of economic growth from the bond and stock markets, Financial Analysts Journal, 45, 38-45.[9] Hayes, S. (2001), Leading indicator information in UK equity prices: an assessment of economic tracking portfolios, Bank of England, Working Paper, No. 137.[10] Ferson, W.E. and Harvey, C.R. (1991), The Variation of Economic Risk Premiums, Bank of England, The Journal of Business, 99, 385-415.[11] Ferson, W.E. and Korajczyk, R.A. (1995), Do arbitrage pricing model explain the pre- dictability of stock returns, Journal of Political Economy, 68, 309-349.[12] Jones, C.M., Lamont, O.A. and Lumsdaine, R.L. (1998), Macroeconomic news and bond market volatility, Journal of Financial Economics, 47, 315-337.[13] Junttila, J. (2004), The performance of economic tracking portfolios in an IT-intensive stock market, The Quarterly Review of Economics and Finance, 44, 601-623.[14] Junttila, J. (2007), Forecasting the macroeconomy with current financial market information: Europe and the United States, Review of Financial Economics, 16, 149-175.[15] Lamont, O. A. (2001), Economic tracking portfolios, Journal of Economics, 105, 161-184.[16] Lun, Y.H. and Quddus, M.A. (2009), An empirical model of the bulk shipping market, Int. J. Shipping and Transport Logistics, 1, 37-54.[17] Liew, J. and Vassalou, M. (2000), Can book-to-market, size and momentum be risk factors that predict economic growth, Journal of Financial Economics, 57, 221-245.[18] Mak, Y. K. (2006), An investigation of the forecasting ability of economic tracking portfolios (Master’s Thesis), Simon Fraser University.[19] Oomen, J.G.M. (2012), The Baltic Dry Index: A predictor of stock market returns (Master’s Thesis), Tilburg University.[20] Raunig, B. (2007), Are economic tracking portfolios useful for forecasting output and inflation in Austria?, Applied Financial Economics, 17, 1043-1049.[21] Vassalou, M. (2000), Exchange rate and foreign inflation risk premiums in global equity returns, Journal of International Money and Finance, 19, 433-470. zh_TW dc.identifier.doi (DOI) 10.6814/THE.NCCU.IB.023.2018.F06 -
