---
title: Option Market Makers' Hedging Model
url: https://www.ml-quant.com/papers/ssrn/4936978/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4936978
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4936978
featured: 2024-08-28
citations: unknown
topic: Derivatives & Volatility
---


# Option Market Makers' Hedging Model

The model suggests that the way Option Market Makers manage their option inventory can cause unpredictable changes in stock prices, with their net option position being a key predictor of SPX futures' end-of-day return.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4936978
- Identifier: SSRN 4936978
- Released: 2024-08-26
- First featured: Quant Letter No. 63 (2024-08-28): https://www.ml-quant.com/issues/2024-08-28/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

## Related

- [CLVR Ordering of Transactions on AMMs](https://www.ml-quant.com/papers/arxiv/2408.02634/): The study introduces the CLVR algorithm, which organizes transactions to reduce price volatility in Automated Market Maker trading, balancing price stability and inequality reduction.
- [Optimal Option Market Making and Volatility Arbitrage](https://www.ml-quant.com/papers/ssrn/4729290/): A novel market making model for options trading has been introduced, considering trader's volatility views and incorporating features like trading position limit, risk control, and simultaneous market making of multiple options.
- [Modeling Loss-Versus-Rebalancing in Automated Market Makers via Continuous-Installment Options](https://www.ml-quant.com/papers/arxiv/2508.02971/): The study introduces a mathematical model that views a CFAMM position as a portfolio of perpetual American CI options, aiding liquidity providers in estimating future costs and optimizing parameters.
- [ARL-Based Multi-Action Market Making with Hawkes Processes and Variable Volatility](https://www.ml-quant.com/papers/doi/10-1145-3677052-3698695/): The study combines Adversarial Reinforcement Learning, Hawkes Processes, and variable volatility to enhance market-making strategies, showing improved adaptability in high-volatility conditions and better market simulations.
- [Market Impact of 0DTE Options](https://www.ml-quant.com/papers/ssrn/4881008/): The increased trading of SP 500 index options that expire on the same day reduces stock market volatility due to market makers' intraday rebalancing of the index.
- [Volatility Demand in Market Turmoil](https://www.ml-quant.com/papers/ssrn/5052438/): The study resolves the paradox of end users reducing their VIX call options during market downturns by examining the demand curves for market makers and end users, emphasizing the market makers' role in market equilibrium.
