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Local mispricing and microstructural noise: A parametric perspective - ScienceDirect
Source: sciencedirect.com
Article summary:
1. The availability of high-frequency asset price data has led to two separate literatures: one focused on model-free ex-post measurement of features concerning the realized return path, and one exploring the complexities of price discovery.
2. The traditional “martingale-plus-noise” framework presumes that all relevant information is impounded instantaneously, but this ignores the fact that noise can be endogenous due to learning, inventory, and temporal feedback mechanisms.
3. This article generalizes the martingale-plus-noise model and analyzes its implications for volatility estimation, validity of the underlying semimartingale paradigm, and identification of underlying mechanisms.
Article analysis:
This article provides a comprehensive overview of two distinct literatures related to high frequency asset pricing data: one focused on model-free ex-post measurement of features concerning the realized return path, and one exploring the complexities of price discovery. The authors provide an in depth analysis of how these two literatures interact with each other and how they can be combined to form a more comprehensive understanding of asset pricing dynamics.
The article is well written and provides a thorough overview of both topics discussed. It is clear that the authors have done extensive research into both topics in order to provide an accurate representation of their findings. Furthermore, they provide evidence from empirical studies to support their claims which adds credibility to their arguments.
However, there are some potential biases present in the article which should be noted. For example, while the authors do discuss asymmetric information as it relates to market microstructure models, they do not explore counterarguments or alternative perspectives on this issue which could lead readers to draw biased conclusions about their findings. Additionally, while they do provide evidence from empirical studies to support their claims, it would be beneficial if they provided more evidence from different sources in order to further strengthen their argument.
In conclusion, this article provides a comprehensive overview of two distinct literatures related to high frequency asset pricing data and offers insights into how these two fields interact with each other. While there are some potential biases present in the article which should be noted, overall it is well written and provides an accurate representation of its findings through evidence from empirical studies.