Dissecting the investor space

Purpose This paper proposes an options pricing model capable of constructing subspaces within which lie investors compelled to take long positions, take short positions or neither. From these subspaces, the median investor’s expected future price of a security and the uncertainty of that future price can be estimated. Further, the model aims to be more compliant with real world market characteristics than prevailing options pricing models. Design/methodology/approach I outline three relevant complex elements of securities markets. First, the market is not homogeneous; each investor has their unique forecasts and levels of conviction. Second, investors are not risk neutral and have non-linear utility functions; the paper adapts an established utility function from behavioral finance. Third, most market participants find an asset’s price too high to buy and too low to short, instead opting to take neither long nor short positions. Findings The model uses options prices and the above three observations to dissect the investor space and estimate the median investor’s expected future price of the underlying asset. The paper concludes that this model is able to extract more information, including the expected future price of the underlying, from options prices than current models and is more consistent with real-world market characteristics. Practical implications The model has a number of immediate practical applications: The model also allows for individual investors to derive a reasonable fair price for an option based on the investor’s specific expected return and degree of uncertainty of this return, acknowledging that both factors are important in options pricing. The proposed model may offer an improved means of deriving market expected returns over the capital asset pricing model. The model offers an improved method for calculating the implied volatility of a security which is not reliant on the views only of the minority of the market which invests in options. Measurements of implied volatility that reflect the sentiment of the most optimistic or pessimistic portion of the market are subject to selection bias. Finally, investors may find that calculations of the market’s expected returns of an asset using options pricing better identify contrarian views upon which the investor can act. Originality/value This options pricing model is unique in that it is built upon real world market characteristics such as investor heterogeneity, risk-aversion and limited participation. The result is a model developed to extract characteristics of the entire market despite most of the market not participating in the pricing of the underlying asset and its options.