摘要翻译:
研究人员研究了金融时间序列的首次通过时间,并观察到股票指数移动给定距离所需的最小时间间隔通常在负价格移动时比在正价格移动时短。对于指数成份股,即个股来说,情况并非如此。我们用离散小波变换来说明这是一个长时间尺度而不是短时间尺度的现象--如果价格过程中足够多的低频成分被去除,不对称性就消失了。我们还提出了一个新的模型,通过个股的长期相关下跌来解释非对称性。
---
英文标题:
《A multiscale view on inverse statistics and gain/loss asymmetry in
financial time series》
---
作者:
Johannes Vitalis Siven, Jeffrey Todd Lins, Jonas Lundbek Hansen
---
最新提交年份:
2008
---
分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
--
一级分类:Statistics 统计学
二级分类:Applications 应用程序
分类描述:Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学,教育学,流行病学,工程学,环境科学,医学,物理科学,质量控制,社会科学
--
---
英文摘要:
Researchers have studied the first passage time of financial time series and observed that the smallest time interval needed for a stock index to move a given distance is typically shorter for negative than for positive price movements. The same is not observed for the index constituents, the individual stocks. We use the discrete wavelet transform to illustrate that this is a long rather than short time scale phenomenon -- if enough low frequency content of the price process is removed, the asymmetry disappears. We also propose a new model, which explain the asymmetry by prolonged, correlated down movements of individual stocks.
---
PDF链接:
https://arxiv.org/pdf/0811.3122