An Empirical Study on the Impact of Pharmaceutical Policies on the Stock Market of Pharmaceutical Industry in China: An Application of Ensemble Empirical Mode Decomposition

Abstract

Abstract: Pharmaceutical policy has been changing constantly for many years in China, and it has influenced the development of pharmaceutical industry to some degree. As the pharmaceutical industry has played a more and more important role in the stock market, how the pharmaceutical policy affects the stock market of pharmaceutical industry is one of the research hot points. In this paper, firstly, the Ensemble Empirical Mode Decomposition (EEMD) is utilized to decompose the intraday volatility of Shanghai and Shenzhen 300 and the pharmaceutical index; secondly, the IMFs are reconstructed to analyze the differences between the intermediate frequency parts of those two series; thirdly, based on the promulgation time of medical policies, this paper explores the dynamic relationships between medical reform policies and the fluctuations of the secondary market of the pharmaceutical industry and analyzes the impact of medical reform policies on the secondary market of the pharmaceutical industry. The release of pharmaceutical policies is closely related to the fluctuation of the pharmaceutical index. Affected by new medical reform policies such as the quality and efficacy consistency evaluation of generic drugs, the pilot program of the drug marketing authorization holder system, reform and improvement of the supply and the use of generic drugs, the pharmaceutical index has risen to varying degrees, rising by 10.96%, 3.47% and 1.31% respectively. Meanwhile, affected by new medical reform policies such as “Deepening the Medical and Health System Reform in 2016”, the “two invoice system” and the cancellation of drug markups, and the “4+7” urban drug centralized procurement, the pharmaceutical index has dropped by 3.79%, 0.87% and 7.98% respectively. This study can provide scientific evidence for government to make relevant decisions, enterprises to adjust the development direction and investors' investment behavior.

Key words: ensemble empirical mode decomposition, pharmaceutical policy, pharmaceutical industry, stock market

Yang Tao, Wei Yunjie. An Empirical Study on the Impact of Pharmaceutical Policies on the Stock Market of Pharmaceutical Industry in China: An Application of Ensemble Empirical Mode Decomposition[J]. Management Review, 2021, 33(3): 66-74.

References

[1] Kheirandish M., Rashidian A., Kebriaeezade A., et al. A Review of Pharmaceutical Policies in Response to Economic Crises and Sanctions[J]. Journal of Research in Pharmacy Practice, 2015,4(3):115-122
[2] Masoumi M., Azar F. E. F., Rezapour A., et al. Economic and Non-Economic Determinants of Iranian Pharmaceutical Companies' Financial Performance:An Empirical Study[J]. BMC Health Services Research, 2019,19(1):1011
[3] 何威澎,项楠,杨雨晨,等. 基于政策计量与图谱分析的上海市分级诊疗政策研究[J]. 中国全科医学, 2020,23(22):2768-2774
[4] 戴悦,郑振佺,提童博,等. 三明市某县级公立医院改革的实践探索——基于SSP范式的分析[J]. 卫生经济研究, 2019,36(8):31-34
[5] 段天宇,张希,胡毅. R&D强度与中国医药制造业上市公司绩效的门限效应研究[J]. 管理评论, 2020,32(9):142-152
[6] 傅书勇,孙叔军,杨悦. 我国居民医院门诊就医行为及医改政策建议[J]. 中国药业, 2018,27(2):75-77
[7] 杨涛. 基于计量回归探究新医改对民营医院绩效的影响[J]. 科技促进发展, 2017,13(12):980-987
[8] Ellison S. F., Mullin W. P. Gradual Incorporation of Information:Pharmaceutical Stocks and the Evolution of President Clinton's Health Care Reform[J]. The Journal of Law and Economics, 2001,44(1):89-129
[9] 吴君. 医药政策事件对我国医药行业股市影响的实证研究[D]. 广东药科大学硕士学位论文, 2019
[10] 王爽. 中国货币政策与股票市场的关系实证分析[J]. 中国市场, 2019,(8):45+47
[11] Baker S. R., Bloom N., Davis S. J. Measuring Economic Policy Uncertainty[J]. The Quarterly Journal of Economics, 2016,131(4):1593-1636
[12] 徐忠轩. 经济政策和我国股市波动性的相关性研究[D]. 浙江工商大学硕士学位论文, 2016
[13] 王树强,陈立文. 房地产市场与股票市场相关性研究——从房地产新政引发股票市场超跌谈起[J]. 价格理论与实践, 2010,(7):50-51
[14] Wu Z., Huang N. E. Ensemble Empirical Mode Decomposition:A Noise-Assisted Data Analysis Method[J]. Advances in Adaptive Data Analysis, 2009,1(1):1-41
[15] Wei Y., Sun S., Ma J., et al. A Decomposition Clustering Ensemble Learning Approach for Forecasting Foreign Exchange Rates[J]. Journal of Management Science and Engineering, 2019,4(1):45-54
[16] Wei Y., Wei Q., Wang S., et al. A Hybrid Approach for Studying the Lead-Lag Relationships between China's Onshore and Offshore Exchange Rates Considering the Impact of Extreme Events[J]. Journal of Systems Science and Complexity, 2018,31(3):734-749
[17] 梁小珍,张倩文,杨明歌. 基于TEI@I方法论的航空客运需求预测模型[J]. 管理评论, 2020,32(7):180-190
[18] 任晓晨,邹思琳,唐娴,等. 基于集合经验模态分解和BP神经网络的北京市PM2.5预报研究[J]. 北京大学学报(自然科学版), 2019,55(4):615-625
[19] Liu D., Sun K. Short-term PM2.5 Forecasting Based on CEEMD-Rf in Five Cities of China[J]. Environmental Science and Pollution Research, 2019,26(32):32790-32803
[20] 邢光远,冯宗宪. 我国出口国内增加值驱动因素的影响效应数据挖掘研究[J]. 管理评论, 2018,30(5):173-178
[21] 李仲飞,肖仁华,杨利军. 基于集合经验模态分解技术的中国房地产周期识别研究[J]. 经济评论, 2014,(4):108-121
[22] Zhang X., Lai K. K., Wang S. Y. A New Approach for Crude Oil Price Analysis Based on Empirical Mode Decomposition[J]. Energy Economics, 2008,30(3):905-918
[23] 崔啸,郭琨,金圳妮,等. 基于TEI@I的中国利率多尺度波动特征研究[J]. 管理评论, 2020,32(7):111-122
[24] 陈越. 基于小波和EEMD降噪的沪深300指数波动率预测[D]. 华侨大学硕士学位论文, 2019
[25] 张梦帆,杜淑雯. 一致性评价背景下医药产业发展机遇[J]. 现代商贸工业, 2018,39(33):4-6
[26] 周玉涛. 医药产业链的"共振"[J]. 中国药店, 2017,(4):98-99
[27] 周枫,褚淑贞. 江苏省药品上市许可持有人制度试点现状及其对产业的影响[J]. 广东药科大学学报, 2018,34(2):213-217
[28] 王理群. 药品上市许可持有人制度试点对上海生物医药产业的影响分析[J]. 上海医药, 2016,37(17):52-55
[29] 国务院印发《关于改革完善仿制药供应保障及使用政策的意见》我国将促进仿制药研发解决高质量仿制药紧缺问题[EB/OL]. http://www.gov.cn/xinwen/2018-04/03/content_5279580.htm, 2018-04-03
[30] 李岚,徐培红,干荣富. 医药新政下影响的行业供应链发展趋势分析[J]. 中国医药工业杂志, 2020,51(1):130-135
[31] 黄羽舒,陶立波. 药品集中带量采购对我国医药产业集中度的影响——基于产业经济学视角的分析[J]. 中国医疗保险, 2020,(2):64-67