摘要翻译:
本文提出了一个自洽的爆炸性金融泡沫模型,它结合了一个均值回归波动过程和一个反映非线性正反馈和投资者信念和情绪持续更新的随机条件收益。条件期望收益表现出比指数更快的加速度,被称为“对数周期幂律”。对残差的测试显示,当应用于GARCH基准时,假阳性率显著低(0.2%)。在1950年1月3日至2008年11月21日对标准普尔500美国指数进行检验时,该模型正确识别了1987年10月、1997年10月、1998年8月结束的泡沫和2000年第一季度结束的ITC泡沫。不同的单位根测试证实了模型规范的高度相关性。我们的模型还提供了泡沫持续时间的诊断:应用于1987年10月崩盘之前的时期,有明确的证据表明泡沫至少在4年前开始。我们在过去二十年中发生的其他七个主要泡沫上证实了波动率约束的LPPL模型的有效性和普适性。使用贝叶斯推理,我们发现与标准基准相比,我们的模型有很强的统计偏好,这与Chang和Feigenbaum(2006)使用单位根模型来处理残差是矛盾的。
---
英文标题:
《A Consistent Model of `Explosive' Financial Bubbles With Mean-Reversing
Residuals》
---
作者:
L. Lin, Ren R.E, and D. Sornette
---
最新提交年份:
2009
---
分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Risk Management 风险管理
分类描述:Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
--
一级分类:Quantitative Finance 数量金融学
二级分类:General Finance 一般财务
分类描述:Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
--
---
英文摘要:
We present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process and a stochastic conditional return which reflects nonlinear positive feedbacks and continuous updates of the investors' beliefs and sentiments. The conditional expected returns exhibit faster-than-exponential acceleration decorated by accelerating oscillations, called "log-periodic power law." Tests on residuals show a remarkable low rate (0.2%) of false positives when applied to a GARCH benchmark. When tested on the S&P500 US index from Jan. 3, 1950 to Nov. 21, 2008, the model correctly identifies the bubbles ending in Oct. 1987, in Oct. 1997, in Aug. 1998 and the ITC bubble ending on the first quarter of 2000. Different unit-root tests confirm the high relevance of the model specification. Our model also provides a diagnostic for the duration of bubbles: applied to the period before Oct. 1987 crash, there is clear evidence that the bubble started at least 4 years earlier. We confirm the validity and universality of the volatility-confined LPPL model on seven other major bubbles that have occurred in the World in the last two decades. Using Bayesian inference, we find a very strong statistical preference for our model compared with a standard benchmark, in contradiction with Chang and Feigenbaum (2006) which used a unit-root model for residuals.
---
PDF链接:
https://arxiv.org/pdf/0905.0128