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| Title: | 債市波動性和公司債報酬
Volatility of bond market and the cross-section of corporate bond returns |
| Authors: | 蘇旺鴻
Su, Wang-Hung |
| Contributors: | 岳夢蘭
Yueh, Meng-Lan
蘇旺鴻
Su, Wang-Hung |
| Keywords: | 公司債
波動性
VIX指數
MOVE指數
Corporate bonds
Volatility
VIX Index
MOVE Index |
| Date: | 2023 |
| Issue Date: | 2023-08-02 12:58:52 (UTC+8) |
| Abstract: | 本文探討公司債如何被債市波動率風險定價，債市波動率使用MOVE指數為代表，MOVE被稱為債市版本的VIX，用於衡量美國公債殖利率的隱含波動率。VIX指數和MOVE指數在大多時候變化方向相同，但在部分重大事件中有所差異。例如2013年FED宣布縮減購債時，僅MOVE出現顯著上升，貨幣政策轉向使投資人預期未來的殖利率會有較大的波動率。根據本文採用單變量投資組合分析、雙變量投資組合分析、橫截面分析的實證研究發現，高β_MOVE值的公司債報酬率低於低β_MOVE值的公司債報酬率。為了證實MOVE對公司債的影響力並非完全來自VIX，最後的穩健性測試將VIX加入多因子模型，進行先前的三種分析確保VIX作為控制變數後MOVE仍具有對公司債報酬率的影響力。
This paper examines the pricing of volatility risk in the corporate bond market. The volatility of the bond market is represented by the MOVE index, which is referred to as the VIX index of the bond market. It measures the implied volatility of US Treasury yields. The VIX index and MOVE index generally move in the same direction, but they show some differences during significant events. For example, when the FED announced tapering in 2013, only the MOVE index showed a significant increase. The change in monetary policy led investors to expect greater volatility of yield in the future. Based on the empirical research conducted in this paper using univariate portfolio analysis, bivariate portfolio analysis, and cross-sectional analysis, it was found that corporate bonds with high β_MOVE had lower returns compared to corporate bonds with low β_MOVE. To confirm that the influence of MOVE on corporate bonds is not solely derived from VIX, the robustness test adds VIX to the multi-factor model and conducts the previous three analyses to ensure that MOVE still impacts corporate bond returns when VIX is included as a control variable. |
| Reference: | Alberg, D., Shalit, H., & Yosef, R. (2008). Estimating stock market volatility using asymmetric GARCH models. Applied Financial Economics, 18(15), 1201-1208.
Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross‐section of volatility and expected returns. The Journal of Finance, 61(1), 259-299.
Arnold, I. J., & Vrugt, E. B. (2010). Treasury bond volatility and uncertainty about monetary policy. Financial Review, 45(3), 707-728.
Black, F. (1976). Studies of stock market volatility changes. Proceedings of the 1976 Meetings of the Business and Economic Statistics Section, American Statistical Association, pp. 177-181.
Campbell, J. Y., Giglio, S., Polk, C., & Turley, R. (2018). An intertemporal CAPM with stochastic volatility. Journal of Financial Economics, 128(2), 207-233.
Chung, K. H., & Chuwonganant, C. (2014). Uncertainty, market structure, and liquidity. Journal of Financial Economics, 113(3), 476-499.
Chung, K. H., Wang, J., & Wu, C. (2019). Volatility and the cross-section of corporate bond returns. Journal of Financial Economics, 133(2), 397-417.
Corrado, C. J., & Miller, Jr, T. W. (2005). The forecast quality of CBOE implied volatility indexes. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 25(4), 339-373.
Dick-Nielsen, J. (2014). How to clean enhanced TRACE data. Unpublished working paper. Copenhagen Business School.
Dimic, N., Kiviaho, J., Piljak, V., & Äijö, J. (2016). Impact of financial market uncertainty and macroeconomic factors on stock–bond correlation in emerging markets. Research in International Business and Finance, 36, 41-51.
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607-636.
Marcucci, J. (2005). Forecasting stock market volatility with regime-switching GARCH models. Studies in Nonlinear Dynamics & Econometrics, 9(4), 1558-3708.
Merton, R. C. (1973). An intertemporal capital asset pricing model. Econometrica: Journal of the Econometric Society, 867-887.
Pastor, L., & Stambaugh, R. F. (2003). Liquidity risk and expected stock returns. Journal of Political Economy, 111(3), 642-685.
Schwert, G. W. (1989). Why does stock market volatility change over time? The Journal of Finance, 44(5), 1115-1153.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442.
Yang, Z., & Zhou, Y. (2017). Quantitative easing and volatility spillovers across countries and asset classes. Management Science, 63(2), 333-354.
Yang, Z., Zhou, Y., & Cheng, X. (2020). Systemic risk in global volatility spillover networks: Evidence from option‐implied volatility indices. Journal of Futures Markets, 40(3), 392-409.
Zhou, Y. (2014). Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities. Journal of Banking & Finance, 38, 216-228. |
| Description: | 碩士
國立政治大學
財務管理學系
110357018 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110357018 |
| Data Type: | thesis |
| Appears in Collections: | [財務管理學系] 學位論文
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