Dissecting the Investor Space Into Long, Short, and Sideline Subspaces

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This paper develops a framework to partition investors into long, short, and sideline categories based on option prices and a non-linear utility function reflecting market complexities.

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The paper proposes a framework for option pricing that accounts for a non-homogeneous market populated by independent, non-risk-neutral investors with non-linear utility, and argues that option prices capture the sentiment of investors who do not hold the asset. Using a behavioral finance utility function, it constructs short put and long put frontier curves that partition a two-dimensional investor space (expected underlying value vs uncertainty) into buy, sell, and do-nothing subspaces. When multiple options on the same underlying and expiration are incorporated, the model yields an intersection point (“knot”) and narrows the short put and long put frontiers toward the median investor’s expected return. The paper is a research preprint and is not peer reviewed by a journal. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

This paper proposes a framework which is compliant with complex real-world market characteristics for constructing subspaces within which lie investors compelled to take long positions, take short positions, or stand on the sidelines. To begin, I outline the relevant complex elements of securities markets. First, it is proposed that the market is not homogenous; the market is made up of many independent investors, each with their unique perspectives, forecasts, and levels of conviction. Second, it is proposed that investors are not risk neutral and have non-linear utility functions; the paper borrows an established utility function from behavioral finance. Third, it is shown that most market participants find an asset’s price too high to buy and too low to short; an effective asset pricing framework must acknowledge this. Fourth, it is proposed that options prices better reflect the sentiment of those who do not invest than they reflect the sentiment of those who do invest. The framework can use a single option price to create short put and long put frontier curves which carve up the two-dimensional investor space (x = expected value of underlying at expiration, y = uncertainty of this expected value) into three subspaces – investor buys, investor sells, and investor does nothing. When incorporating prices of multiple options on the same underlying asset with the same expiration date, the paper shows that the price curves intersect at a “knot”; the short put knot and long put frontier curves narrow in on the median investor’s expected return of the underlying asset. JEL code. G12
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Dissecting the Investor Space Into Long, Short, and Sideline Subspaces | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dissecting the Investor Space Into Long, Short, and Sideline Subspaces Nikhil Jaisinghani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3744262/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper proposes a framework which is compliant with complex real-world market characteristics for constructing subspaces within which lie investors compelled to take long positions, take short positions, or stand on the sidelines. To begin, I outline the relevant complex elements of securities markets. First, it is proposed that the market is not homogenous; the market is made up of many independent investors, each with their unique perspectives, forecasts, and levels of conviction. Second, it is proposed that investors are not risk neutral and have non-linear utility functions; the paper borrows an established utility function from behavioral finance. Third, it is shown that most market participants find an asset’s price too high to buy and too low to short; an effective asset pricing framework must acknowledge this. Fourth, it is proposed that options prices better reflect the sentiment of those who do not invest than they reflect the sentiment of those who do invest. The framework can use a single option price to create short put and long put frontier curves which carve up the two-dimensional investor space (x = expected value of underlying at expiration, y = uncertainty of this expected value) into three subspaces – investor buys, investor sells, and investor does nothing. When incorporating prices of multiple options on the same underlying asset with the same expiration date, the paper shows that the price curves intersect at a “knot”; the short put knot and long put frontier curves narrow in on the median investor’s expected return of the underlying asset. JEL code. G12 Financial Mathematics option pricing option risk premium option price discount Black-Scholes market implied expected return option implied expected returns Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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