Asset Pricing in the Presence of Market Microstructure Noise
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914127972139008 |
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| author | Yegon, Peter Lindquist, W. Brent Rachev, Svetlozar T. |
| author_facet | Yegon, Peter Lindquist, W. Brent Rachev, Svetlozar T. |
| contents | We present two models for incorporating the total effect of market microstructure noise into dynamic pricing of assets and European options. The first model is developed under a Black-Scholes-Merton, continuous-time framework. The second model is a discrete, binomial tree model developed as an extension of the static Grossman-Stiglitz model. Both models are market complete, providing a unique equivalent martingale measure that establishes a unique map between parameters governing the risk-neutral and real-world price dynamics. We provide empirical examples to extract the coefficients in the model, in particular those coefficients characterizing the influence of the microstructure noise on prices. In addition to isolating the impact of noise on the volatility, the discrete model enables us to extract the noise impact on the drift coefficient. We provide evidence for the primary microstructure noise we believe our empirical examples capture. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_00308 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Asset Pricing in the Presence of Market Microstructure Noise Yegon, Peter Lindquist, W. Brent Rachev, Svetlozar T. Pricing of Securities We present two models for incorporating the total effect of market microstructure noise into dynamic pricing of assets and European options. The first model is developed under a Black-Scholes-Merton, continuous-time framework. The second model is a discrete, binomial tree model developed as an extension of the static Grossman-Stiglitz model. Both models are market complete, providing a unique equivalent martingale measure that establishes a unique map between parameters governing the risk-neutral and real-world price dynamics. We provide empirical examples to extract the coefficients in the model, in particular those coefficients characterizing the influence of the microstructure noise on prices. In addition to isolating the impact of noise on the volatility, the discrete model enables us to extract the noise impact on the drift coefficient. We provide evidence for the primary microstructure noise we believe our empirical examples capture. |
| title | Asset Pricing in the Presence of Market Microstructure Noise |
| topic | Pricing of Securities |
| url | https://arxiv.org/abs/2511.00308 |