基于对数周期幂律奇异性模型的个股价格走势分析
首发时间:2019-11-04
摘要:本文选取了A股市场上比较有代表性的4只股票作为样本,截取泡沫从形成至破裂的一个完整的周期,利用对数周期幂律奇异性模型进行拟合,并预测出泡沫破裂的时间。从实证结果得出结论:个股股价在泡沫周期内均服从对数周期幂律分布,随着时间接近临界点,股价震荡的频率递增。当股市系统自身运行至临界状态时,在系统内部会产生极强的正反馈作用,投资者相互模仿,都在执行买入的操作,表现在股价上便是在短时间内加速上涨。当大量资金从市场离开时,投资者们便会再次相互模仿,争相抛售股票,引起股价暴跌,泡沫破裂。此外,对于"妖股"而言,泡沫的累积往往伴随着市场的炒作和投资者情绪的变化,其泡沫的累积和挤出都更加迅速,更适合采用对数周期幂率奇异性模型进行预测。
关键词: 股市泡沫 对数周期幂率奇异性模型 个股价格走势
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Analysis of Stock Price Trends Based on LPPLS Model
Abstract:This paper selected four typical stocks as a sample in the Chinese stock market and intercepted a complete cycle of bubbles from formation to rupture. And this paper used the log-periodic power-law singularity model to fit the data and predict the time of bubble rupturing. From the empirical results, it is concluded that the stock price obeys log-periodic power law distributioAnalysis of Stock Price Trends Based on LPPLS Modeln in the entire bubble period. And the exponential oscillation frequency increases with the time approaching the critical point. When the stock market system itself runs to a critical state, there is a very strong positive feedback in the system. The investors imitate each other to make decisions performing a buying operation, which performance is in a short period of time to accelerate the rise in the stock price. At this point, once a large amount of money leaves from the market, investors will imitate each other again to sell shares in panic, which will cause the stock price plunged and the bubble burst. Otherwise, for one stock, the accumulation of bubbles is often accompanied by market speculation and changes in investor sentiment. The accumulation and extrusion of bubbles are more rapid. And it is more suitable to use the log-periodic power law singularity model to predict.
Keywords: Stock market bubbles Log-periodic power-law singularity model(LPPLS model) Stock price trend
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基于对数周期幂律奇异性模型的个股价格走势分析
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