Options strategy for technology companies

T. Tan, B. Bing
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引用次数: 1

Abstract

Product innovation in the technology ecosystem can be enhanced through proper management of the supply chain. While there are several strategies that technology investors favor for profitability during the earning cycles, one of the strategies utilized quite often is the short strangle. A short strangle is an effective strategy with a theoretically unlimited risk. For example, Google's recent earnings sent its share price up sharply by 13.8%, breaking the $1,000 barrier for the first time and increasing the company's value by nearly $40 billion within a day. Such variations can be very costly for an investor who trades around earnings using short strangles. The aim of this paper is to debunk this myth and demonstrate how a short strangle can be traded safely as long as certain requirements are met. We will employ two companies in the technology sector to illustrate how our criteria can help in making better trading decisions. Since the volatility crush is the key determinant for profitability, we modeled the crush between the implied volatility of the front and next earliest expiration using Bayesian statistics. The accuracy of the Bayesian model is quantified using the Google stock as an example and it is shown that the method is reasonably accurate even with sharp changes in volatility trends.
科技公司的期权策略
技术生态系统中的产品创新可以通过对供应链的合理管理来加强。虽然在盈利周期中,科技投资者青睐几种盈利策略,但其中一种经常使用的策略是短期扼杀。短期扼杀是一种有效的策略,理论上风险是无限的。例如,谷歌最近的收益使其股价大幅上涨13.8%,首次突破1,000美元大关,公司价值在一天内增加了近400亿美元。这样的变化对于那些利用空头期权在收益周围交易的投资者来说,代价可能非常高昂。本文的目的是揭穿这个神话,并证明如何短期扼杀可以安全交易,只要满足一定的要求。我们将采用两家技术领域的公司来说明我们的标准如何帮助做出更好的交易决策。由于波动率粉碎是盈利能力的关键决定因素,我们使用贝叶斯统计对前沿和下一个最早到期的隐含波动率之间的粉碎进行了建模。以谷歌股票为例对贝叶斯模型的精度进行了量化,结果表明,即使在波动趋势发生剧烈变化的情况下,贝叶斯模型仍然具有相当的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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