近年來學術界對於債券多因子模型之研究尚少，較多著重在影響債券市場報酬之變數如總體市場利率，利差及利用不同方法衡量個別債券的違約風險等，也有少許文獻在探討股債市的因子交互作用，本研究立基於學術界對於股票及債券動能因子的研究，利用美國投資級公司債，探討股票動能外溢因子對於債券投資組合的效果，並且透過其他債券風格因子如Size，Quality，Convexity，Modified Duration共五個風格因子及11個GICS產業因子進行多因子模型之建構並增值單因子及多因子投資組合；此外，相較於傳統因子動能擇時，本文使用因子風險平價方法增值多因子投資組合，並且比較傳統等權重因子擇時方法及因子風險平價方法對於債券多因子模型的績效影響。
本研究結果發現結合動能外溢因子之多因子模型解釋能力能準確預測未來一個月之投組風險，並且結合傳統方法及動能外溢方法建構之債券動能因子對於投資級債券的確有較好之增值績效，五爪圖及IC圖的趨勢明顯，投組的IR可達0.97，Sharpe ratio可達0.79，並且在以6,9,12月為形成期建立的動能因子都可以為債券投組帶來穩定報酬；然而包含了Distance-to-Default之Quality增值投組並無法帶來較好之累積報酬。並且以因子風險平價方法建構之多因子投組相較於等權重方法降低了投組風險及最大回撤率，Sharpe ratio則與等權重方法相當，且兩者均勝過標竿指數。

In recent years, the academic has little research on the bond multi-factor model, and more emphasis is on the variables that could affect bond market returns, such as macro economy market interest rates, spreads, and different methods to measure the default risk of bonds. There is also a little literature discussing the interaction between equity and bond market. Based on the research on the momentum spillover effect from the stock market to the bond market in the academic community, this research uses US investment-grade corporate bonds to examine the effect of stock momentum spillover on bond portfolios with other bond style factors such as size, quality, convexity, and modified duration, a total of five style factors and 11 GICS industry factors to construct a multi-factor model and single-factor and multi-factor enhanced portfolios. In addition, compared with traditional factor momentum timing method, this article uses the factor risk parity method to enhance the multi-factor portfolio and compares the performance of the equal-weight factor timing method.
This study found that the explanatory ability of the multi-factor model after combining the momentum spillover factor can accurately predict the portfolio risk of next month, and the bond momentum factor constructed by combining traditional methods and the momentum spillover does have an excellent enhanced performance for investment-grade bonds. The trend of cumulative return of quantile groups and the trend of cumulative IC are obvious, the IR of the portfolio can reach 0.97, and the Sharpe ratio can reach 0.79. The momentum factor constructed in the formation period of 6, 9, and 12 months can bring a stable cumulative return to the bond portfolio.
However, the quality factor that includes distance-to-default enhanced portfolio cannot bring adequate cumulative returns. Moreover, the multi-factor portfolio constructed by the factor risk parity method reduces the portfolio risk and the max drawdown compared with the equal weight method. Still, the Sharpe ratio of the factor risk parity method is equivalent to the equal weight method, and both are better than the benchmark index.

論文審定書 i
致謝 ii
摘要 iii
Abstract iv
List of Figures vi
List of Tables viii
1. Introduction 1
1.1 Background 1
1.2 Research Purpose 3
1.3 Research Framework 6
2. Literature Review 7
2.1 Factor Model of Corporate Bond 7
2.2 Momentum Strategy and Momentum Spillover Effect 11
2.3 Factor Timing Model and Factor Risk Parity 14
3. Data and Methodology 17
3.1 Data Source and Description 17
3.2 Research and Analysis Procedures 20
3.3 Data Processing and Factor Construction 22
3.4 Multi-Factor Model Construction 24
3.5 Index Construction Method 26
3.6 Factor Enhanced Method and Factor Risk Parity 28
3.7 Factors Definition and Measurement 31
4. Empirical Results 37
4.1 Multi Factor Model and Pure Factor Portfolio 37
4.2 Single Factor Portfolio 43
4.3 Multi-Factor Portfolio and Factor Timing 50
5. Conclusion and Suggestions 54
5.1 Conclusion 54
5.2 Suggestions 56
6. Reference 58
7. Appendix 61

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