本研究目的為探討因子模型應用於公司債指數市場增值表現，文獻參考自Houweling and Van Zundert (2017)以四因子增值公司債指數，並透過Bender and Wang (2016)之研究將多個單因子投資組合揉合成多因子投資組合。因此本研究利用Size(公司債市值)、Value、Momentum因子合成單因子增值公司債投資組合，並透過等權重合成多因子增值公司債投資組合；此外本研究導入XGBoost因子擇時模型，利用總體經濟數據預測下期單因子投資組合報酬排名並依此動態調整每期單因子投組權重。
透過實證結果本研究發現四點結論：1)單因子可以有效且顯著增值公司債標的指數2)多因子投資組合相較單因子投資組合平均具有較低的周轉率以及追蹤誤差3)XGBoost因子擇時模型多因子投資組合績效優於等權重多因子投資組合4)因子模型於短/中/長期到期期間限制下皆可有效增值標的指數。
整體研究成果顯示因子模型可以有效增值公司債指數，同時在投資組合揉合方面可以動態調整因子權重使投資組合具備更好的表現，使因子投資於公司債指數市場中具有可獲利性之價值。

The purpose of this research is to explore the performance of a factor model pertaining to investing in corporate bond index market. The study follows the methodology of Houweling and Van Zundert (2017), which enhances the corporate bond benchmark by a four-factor model and composes multi-factor portfolios by blending single factor portfolios using Bender and Wang’s (2016) basic model. Therefore, the study constructs a single factor portfolio by Size (market value of bonds), Value and Momentum factors and composes multi-factor portfolios through single factor portfolio blending. In addition, the study applies a factor timing model by XGBoost to predict the ranking of returns of single factor portfolios by macroeconomic data and refer the ranking to adjust the weighting of single factor portfolios dynamically.
The empirical result shows 1) Single factors can significantly enhance the performance of the benchmark. 2) Multi-factor portfolio can have a lower turnover rate and tracking error than the average of single factor portfolios. 3) Factor timing portfolio using XGBoost can outperform the equally-weighted portfolio. 4) Factor models can enhance the performance of the benchmark among short/mid/long maturity universes.
From the evidence above, factor investing in the corporate bond index can effectively enhance the performance of the benchmark. In addition, the portfolio blending with dynamically adjusted weighting can make portfolios have better performances, making factor models valuable in the corporate bond index market.

論文審定書 i
摘要 ii
ABSTRACT iii
List of Tables v
List of Figures vi
I. Introduction 1
1.1 Background Information 1
1.2 Research Purpose 3
1.3 Research Framework 4
II. Literature Review 5
2.1 Modern Portfolio Theory 5
2.2 Factor Model in Corporate Bond Market 6
2.3 Portfolio Blending 8
2.4 Extreme Gradient Boosting (XGBoost) 10
2.5 Factor Timing Model 11
III. Data and Methodology 13
3.1 Analytical Procedures 13
3.2 Data Description 15
3.3 Factor Definition 18
3.4 Trapezoid Weighting Adjustment 20
3.5 Parameter Optimization 22
3.6 Portfolio Return Calculation 23
3.7 Factor Timing Model Using XGBoost 23
3.8 Performance Analysis 24
IV. Empirical Results 28
4.1 Factor Model – Single Factor Portfolio 28
4.2 Parameter Optimizing 33
4.3 Factor Model – Multi-Factor Portfolio 37
4.4 Performance Comparison 38
4.5 Robustness Test 41
V. Conclusion and Suggestions 47
5.1 Conclusion 47
5.2 Suggestions 49
References 51

Bektic, Demir and Wenzler, Josef-Stefan and Wegener, Michael and Schiereck, Dirk and Spielmann, Timo.(2016). Extending Fama-French Factors to Corporate Bond Markets. Unpublished Working Paper.
Bender, Jennifer, Briand, Remy, Nielsen, Frank and Stefek, Dan. (2010). Portfolio of Risk Premia: A New Approach to Diversification. Journal of Portfolio Management, vol. 36, 17–25.
Bender, Jennifer and Wang, Taie (2016). Can the Whole Be More Than the Sum of the Parts? Bottom-Up versus Top-Down Multifactor Portfolio Construction. Journal of Portfolio Management, Vol.42, No. 5, pp. 39–50.
Clarke, Roger G and de Silva, Harindra and Thorley, Steven. (2016). Fundamentals of Efficient Factor Investing. Financial Analysts Journal, vol. 72, 9–26.
Connor, Gregory. (1995). The Three Types of Factor Models: A Comparison of Their Explanatory Power. Financial Analysts Journal, pp. 42-46
Dynkin, Lev, Ferket, Peter, Hyman, Jay, van Leeuwen, Erik and Wu, Wei. (1999). Value of Security Selection Versus Asset Allocation in Credit Markets. The Journal of Portfolio Management, 25, pp. 11-27.
Fama, Eugene F and French, Kenneth R. (1992). The Cross-Section of Expected Stock Returns. Journal of Finance, 47(2), pp. 427-465
Fitzgibbons, Shaun, Friedman, Jacques, Pomorski, Lukasz and Serban, Laura. (2017). Long-Only Style Investing: Don't Just Mix, Integrate. Journal of Investing, Forthcoming.
Ghayur, Khalid and Heaney, Ronan and Platt, Stephen. (2018). Constructing Long-Only Multi-Factor Strategies: Portfolio Blending versus Signal Blending. Financial Analysts Journal, Third Quarter 2018, Vol. 74, No. 3:70-85.
Hottinga, Jouke., Leeuwen, Eric van and Ijserloo, Judith van. (2001). Successful Factors to Select Outperforming Corporate Bonds. Journal of Portfolio Management, Fall 2001, 28 (1) 88-101.
Houweling, Patrick and Van Zundert, Jeroen. (2017). Factor Investing in the Corporate Bond Market. Financial Analysts Journal, 2017, Vol. 73, No. 2.
Ilmanen, Antti S. and Kizer, Jared (2012). The Death of Diversification Has Been Greatly Exaggerated. Journal of Portfolio Management, vol. 38, no. 3 (Spring): 15–27.
Jostova, Gergana, Nikolova, Stanislava, Philipov, Alexander and Stahel, Christof W. (2013). Momentum in corporate bond returns. Review of Financial Studies 26, 1649–1693.
Li, Xi and Sullivan, Rodney N. (2011). A Dynamic Future for Active Quant Investing. Journal of Portfolio Management, 37(3), pp. 29-36.
Lintner, John. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. The Review of Economics and Statistics, 47(1), pp. 13-37.
Markowitz, Harry. (1952). Portfolio Selection. The Journal of Finance, 7(1), pp. 77-91.
Miller, Keith L, Li, Hong, Zhou, Tiffany, and Giamouridis, Daniel. (2015). A Risk-Oriented Model for Factor Timing Decisions. Journal of Portfolio Management, 41(3), pp. 46-58.
Ross, Stephen A. (1976). The Arbitrage Theory of Capital Asset Pricing. Journal of Economic Theory, 13(3), pp. 341-360.
Sharpe, William F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, 19(3), pp. 425-442.
Sugitomo, Seisuke and Shotaro, Minami. (2018). Fundamental Factor Models Using Machine Learning. Journal of Mathematical Finance, 08(01):111-118.
Xiong, James, Ibbotson, Roger G, Idzorek, Thomas M. and Chen, Peng. (2010). The Equal Importance of Asset Allocation and Active Management. Financial Analysts Journal, Vol. 66, No. 2, pp. 22-30.
Chen, Tianqi and Guestrin, Carlos. (2016). XGBoost: A scalable tree boosting system. arXiv:1603.02754.