Using option prices to trade the underlying asset

J. H. Venter; P. J. de Jongh; Eduard Pieterse

Save this article

Need to know

Price data of option chains provide information that can be exploited by traders of the underlying asset.
A novel method to extract tradeable predictions of asset price dynamics from option data is introduced, using option based consensus implied estimates of expected profit and expected loss to predict the risk to reward ratio when taking positions in the asset.
An algorithmic trading strategy is formulated which takes long positions if the risk to reward ratio is low and short positions if it is high.
The methodology is illustrated extensively using option data of the SPX, SPY, DIA and QQQ.

Abstract

Option trading provides rich sets of data that may be used to trade their underlying assets effectively. Strategies for this purpose are discussed in this paper. These strategies use the call and put prices of option chains to estimate the consensus features of the future probability distribution of the price of the underlying asset. This enables a trader to predict the expected profit and expected loss that may be experienced when trading in the asset. The expected profit and expected loss are metrics of reward and risk for such trades. Trading rules based on these metrics are shown to be effective when applied dynamically to historical data of the option chains underlain by the Standard & Poor’s 500, Dow Jones and Nasdaq indexes.

As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.

If you would like to purchase additional rights please email info@risk.net

You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.

If you would like to purchase additional rights please email info@risk.net