Using Options Volume and Open Interest to Model Sentiment and Pricing
Summary
The document asks how options volume, dollar volume, and open interest across strikes and expirations might inform implied sentiment, volatility surfaces, option premiums, or Greeks. It contrasts modeling each contract on its own with measuring activity across a broader set of options, including near-term expirations along the forward curve. The question references research on open interest as a possible leading indicator and demand-based option pricing, but it does not develop or test a specific weighting method.
The author recognizes that no single pricing model is universally correct and that model suitability depends on the market being studied. The cited perspective favors practical model choice over searching for one definitive description of option prices. The document offers no empirical results, formula, or calibration procedure, so it serves mainly as a framing of research questions. Any activity-based adjustment would need to be evaluated by market, contract liquidity, and evidence that activity adds information beyond standard volatility and pricing inputs.
Key ideas
- Options activity across strikes and expirations may provide a broader sentiment signal than contract-level prices alone.
- The document asks whether volume or open interest can inform volatility surfaces, premiums, or Greeks.
- It cites research directions involving open interest and demand-based option pricing without presenting their findings.
- The appropriate pricing model depends on the market and the intended use.
Tags
Full text
# Modeling market sentiment and pricing options by volume, open interest # Modeling market sentiment and pricing options by volume, open interest Are there any empirically-proven methods/formulas for weighting IV surfaces, pricing a discount/premium in an option, and/or adjusting any of the 1st- or 2nd-order Greeks for the magnitude (volume or dollar-volume basis traded) of activity in each option contract for a market? The various debates that can be found amongst traders, quants and others regarding how to model volatility surfaces and price an option appear undecided...at the very least, the several methods for pricing an option not only assume some modest-to-minimal skew in the returns of an underlying market price, and each option seems to be priced 'in a bubble' i.e. not accounting for the activity in other strikes/expirations. These may be consistent with an oversimplified volatility smile, and the No-arbitrage Theory. I'm approaching this line of inquiry and discussion from a hobbyist, amateur perspective, so my apology in advance if the basis explained below for the question is out of sorts... I'm looking for a sound method to account for implied sentiment due to the quantity/distribution/moneyness/etc of option contracts traded across the strike range for the nearest several expirations along the forward curve, and model the aggregate impact of this activity for its underlying instrument (e.g. weekly and monthly options on AAPL, monthly options on natural gas futures, etc.) A few papers are available online which discuss the notions of accounting for option open interest distributions for equities as an implied leading indicator as expiration approaches: Trading on the Information Content of Open Interest - McGill University and also "The Dynamic Relationship between Volatility, Volume and Open Interest in CSI 300 Futures Market" Also, a more direct pricing approach which focuses less on the comprehensive distribution on the activity, and moreso on the specific contract at hand by a discrete method is discussed in this paper: Demand-Based Option Pricing I understand that a closed-form solution cannot be found, and defining some method as 'correct' is partially a matter of probability and confidence intervals for such conclusions...appropriateness of a solution/model is largely a function of what market 'type' is declared. Like Emanuel Derman wrote: “Years ago, when I first became aware of the smile, we hoped to find the 'right' model, and when I met people from other trading firms I used to ask them which model they thought was correct. But now there is such a profusion of models that I have begun to ask more practical questions...There isn’t a uniformly good model. Since Black-Scholes is the market’s language for quoting options prices, local volatility is a natural way to quote forward volatility in terms of the values of portfolios of options spreads, just as forward rates are a natural way to think about the future interest rates. Which model is right depends on your market.” Any commentary on first steps to approach these aspects of modeling market more precisely, as a whole?
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