Tan, Teik Kheong and Bing, Benny (2014) Options Strategy for Technology Companies. 2014 International Conference on Computer and Information Sciences (ICCOINS) 3-5 June 2014. ISSN Electronic ISBN: 978-1-4799-4390-6
Full text not available from this repository.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.
| Item Type: | Journal |
|---|---|
| Uncontrolled Keywords: | Google stock; Technology companies; Product innovation; Technology ecosystem; Supply chain; Profitability; Bayesian statistics |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor |
| Divisions: | School of Management |
| Depositing User: | Aida Rashidah Maajis |
| Date Deposited: | 16 Aug 2017 04:40 |
| Last Modified: | 16 Aug 2017 04:40 |
| URI: | http://ur.aeu.edu.my/id/eprint/57 |
Actions (login required)
 |
View Item |
