Testing for Asset Price Bubbles using Options Data

Testing for Asset Price Bubbles using Options Data
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使用期权数据测试资产价格泡沫

DOI:
10.2139/ssrn.3670999
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发表时间:
2020
期刊:
Econometric Modeling: Derivatives eJournal
影响因子:
--
通讯作者:
Sujan Lamichhane
Sujan Lamichhane
中科院分区:
--
文献类型:
--
作者:
Nicola Fusari;R. Jarrow;Sujan Lamichhane

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我们提出了一种新的方法来识别资产价格泡沫的基础上的期权数据。鉴于其前瞻性,期权是调查市场对资产价格未来演变的预期的理想工具,这是理解价格泡沫的关键。通过利用看跌期权和看涨期权之间的差异定价,我们可以检测和量化标的资产价格中的泡沫。我们将我们的方法应用于2014-2018年样本期内的两个股票市场指数,标准普尔500指数和纳斯达克100指数,以及两个科技股,亚马逊和Facebook。我们发现,虽然指数显示出罕见和适度的泡沫,但亚马逊和Facebook显示出更频繁和更大的泡沫。由于我们的方法可以在真实的时间内实施,因此对政策制定者和投资者都是有用的。例如,我们应用于GameStop的方法发现2020年12月至2021年1月期间存在明显的泡沫。
We present a new approach to identifying asset price bubbles based on options data. Given their forward-looking nature, options are ideal instruments with which to investigate market expectations about the future evolution of asset prices, which are key to understanding price bubbles. By exploiting the differential pricing between put and call options, we can detect and quantify bubbles in the prices of underlying asset. We apply our methodology to two stock market indexes, the S&P 500 and the Nasdaq-100, and two technology stocks, Amazon and Facebook, over the 2014-2018 sample period. We find that, while indexes exhibit rare and modest bubbles, Amazon and Facebook show more frequent and much larger bubbles. Since our approach can be implemented in real time, it is useful to both policy-makers and investors. As an illustration, our methodology applied to GameStop identifies a significant bubble between December 2020 and January 2021.
DOI: 10.1111/iere.12132
发表时间: 2015-11-01
影响因子: 1.5
作者:
Phillips, Peter C. B.;Shi, Shuping;Yu, Jun
通讯作者: Yu, Jun