摘要
本研究基于对数周期幂律模型LPPL(Log Periodic Power Law Model),针对金融时间序列将一维价格波动翻译成反映市场泡沫微观结构的多维变量。通过对多维变量的动态监测,把握市场中泡沫的演变并预测泡沫破裂的临界点,从而有效降低或防范金融资产泡沫破裂所导致的风险。为检验LPPL模型在中国金融市场中的适用性,本文分别使用上证综指、四个期货连续合约以及两支个股检验模型效果。实证结果表明当金融资产价格序列呈现超指数加速震荡上升或下降时,该模型能获得稳定的估计效果,有效预测泡沫破裂临界时点。
This paper focus on the financial bubbles crash by establishing the Log Periodic Power Law Model, which translates one-dimensional price fluctuations of the financial time series into multidimensional variables reflecting the market microstructure about the bubbles. The Log Periodic Power Law Model is very useful to characterize the formation and crash of the financial bubbles. The LPPL model is:lnp(t)=A+B(tc-t)m{1+Ccos(ωln(tc-t)-φ)} where lnp(t) is the logarithm of index or assets price.tc is the critical point of bubble burst. The least square method is applied to estimate parameters in the model, and using Nelder-Mead Simplex algorithm is used for finding the optimal parameters. Dynamic detecting the multidimensional variables, diagnosing bubbles that are in the making and to forecast their termination time, so as to effectively reduce or prevent the financial risk from the financial bubbles crashing. The Shanghai Composite Index, four futures contracts and two stocks are performed on, for testing the applicability of LPPL Model in the financial market of China. The empirical results show that when the financial asset price series presents hyper exponential acceleration, shocks rise or fall, the model modified can be used to obtain a stable estimation, and effectively predict the critical point of the bubble burst. This paper not only tests the validity of LPPL model based on China financial market, but also provides a powerful tool for detecting financial bubbles or forecasting the bubbles crash. Moreover, as a supplementary guide for trading strategies.
作者
潘娜
王子剑
周勇
PAN Na;WANG Zi-jian;ZHOU Yong(Hubei University of Police,Hubei Wuhan 430034,China;School of Statistics and Management,Shanghai University of Finance and economics,Shanghai 200433,China;Key Laboratory of Advanced Theory and Application in Statistics and Data Science,MOE,and Institute of Statistics and Interdisciplinary Sciences,East China Normal University,Shanghai 200241,China)
出处
《中国管理科学》
CSSCI
CSCD
北大核心
2018年第12期25-33,共9页
Chinese Journal of Management Science
基金
国家自然科学基金重点资助项目(71331006)
国家自然科学重大研究计划重点项目(91546202)
关键词
LPPL模型
泡沫破裂
超指数
临界点
Log Periodic Power Law Model
bubble crash
hyperexponential
critical point