Analysis of the Impact of Supply-side Reform on Coal Industry Bonds Investment

Abstract

Abstract:

The supply-side reform,as an important national policy of China to cross the middle income trap in the new normal economy,changes the analysis logic of the bond market,especially in the coal industry.The excess capacity of China's coal industry in 2013,2014 and 2015 are 1.466 billion tons,1.449 billion tons and 2.500 billion tons respectively,with 2015 at a record high.By analyzing the factors that affect the coal industry spreads,we identify the specific impact of the supply-side reform on the coal industry bonds.The change in coal industry bonds investment logics occurred in September 2015.Before the supply-side reform,bond investors'investment logic was “on the market”,focusing on market risk and ignoring industry risks.After the supply-side reform,investors began to pay attention to industry analysis.The decrease of the coal prices and coal-industrial added values led to a significant increase in coal industry spreads.The supply-side reform requires investors to face up to the problems of excess capacity and high leverage ratios in excess capacity industries,rather than hide the risk.Investors should pay attention to industry risks and decrease the bond investment in the excess capacity industries to promote the structural transformation of the economy.The governments at each level should gradually break the implied guarantees of state-owned enterprises'bonds,and correctly deal with the relationship between the government and the market.

Key words: supply-side reform, bonds, coal industry, Markov switching regression model

Lin Wenda. Analysis of the Impact of Supply-side Reform on Coal Industry Bonds Investment[J]. , 2017, 29(6): 53-60.

References

[1] 费磊. 债券市场发展对货币政策传导的结构性效应研究——基于状态空间模型的实证分析[J]. 金融监管研究, 2016,(9):43-56
[2] Sharpe W. F. Capital Asset Prices:A Theory of Market Equilibrium Under Conditions of Risk[J]. The Journal of Finance, 1964,19(3):425-442
[3] Altman E. I. Measuring Corporate Bond Mortality and Performance[J]. The Journal of Finance, 1989,44(4):909-922
[4] Guha D., Hiris L. The Aggregate Credit Spread and the Business Cycle[J]. International Review of Financial Analysis, 2002,11(2):219-227
[5] 邓海清,胡玉峰. 从行业利差分化看我国产业债大分化趋势[N]. 上海证券报, 2015-04-03009
[6] Ludvigson S. C., Ng S. Macro Factors in Bond Risk Premia[J]. Review of Financial Studies, 2009,22(12):5027-5067
[7] 胡施聪. 信用利差驱动力转变行业利差分化加剧[J]. 债券, 2016,(6):56-58
[8] 冷奥琳,张俊瑞,邢光远. 公司对外担保违约风险传递机理和影响效应研究——基于上市公司债券利差数据的实证分析[J]. 管理评论, 2015,27(7):3-14
[9] 林晚发,李国平,王海妹,等. 分析师预测与企业债券信用利差——基于2008-2012年中国企业债券数据[J]. 会计研究, 2013,(8):69-75
[10] 于静霞,周林. 货币政策、宏观经济对企业债券信用利差的影响研究[J]. 财政研究, 2015,(5):49-57
[11] 宋球红. 宏观经济变量对不同信用级别企业债信用利差影响的分析[J]. 债券, 2013,(12):35-39
[12] 张良贵,孙久文. 信用利差变化对企业杠杆的动态影响[J]. 证券市场导报, 2014,(6):53-56
[13] Gilchrist S., Yankov V., Zakrajek E. Credit Market Shocks and Economic Fluctuations:Evidence from Corporate Bond and Stock Markets[J]. Journal of Monetary Economics, 2009,56(4):471-493
[14] Hamilton, James D. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle[J]. Econometrica, 1989,57(2):357-384
[15] Jeanne O., Masson P. Currency Crises, Sunspots and Markov-switching Regimes[J]. Journal of International Economics, 2000,50(2):327-350
[16] Lammerding M., Stephan P. Speculative Bubbles in Recent Oil Price Dynamics:Evidence from a Bayesian Markov-switching State-space Approach[J]. Energy Economics, 2013,36(3):491-502
[17] Rey C., Rey S., Viala J. R. Detection of High and Low States in Stock Market Returns with MCMC Method in a Markov Switching model[J]. Economic Modelling, 2014,41(41):145-155
[18] 杨海珍,史芳芳. 金融危机以来中国跨境热钱流动原因研究[J]. 管理评论, 2016,28(3):12-19
[19] 高国华,潘英丽. 基于动态相关性的我国银行系统性风险度量研究[J]. 管理评论, 2013,25(1):9-15