Applying option Greeks to directional forecasting of implied volatility in the options market: An intelligent approach

Jae Joon Ahn, Dong Ha Kim, Kyong Joo Oh, Tae Yoon Kim

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This paper examines movement in implied volatility with the goal of enhancing the methods of options investment in the derivatives market. Indeed, directional movement of implied volatility is forecasted by being modeled into a function of the option Greeks. The function is structured as a locally stationary model that employs a sliding window, which requires proper selection of window width and sliding width. An artificial neural network is employed for implementing and specifying our methodology. Empirical study in the Korean options market not only illustrates how our directional forecasting methodology is constructed but also shows that the methodology could yield a reasonably strong performance. Several interesting technical notes are discussed for directional forecasting.

Original languageEnglish
Pages (from-to)9315-9322
Number of pages8
JournalExpert Systems with Applications
Volume39
Issue number10
DOIs
Publication statusPublished - 2012 Aug 1

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Derivatives
Neural networks

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Cite this

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Applying option Greeks to directional forecasting of implied volatility in the options market : An intelligent approach. / Ahn, Jae Joon; Kim, Dong Ha; Oh, Kyong Joo; Kim, Tae Yoon.

In: Expert Systems with Applications, Vol. 39, No. 10, 01.08.2012, p. 9315-9322.

Research output: Contribution to journalArticle

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