Dissertations, Theses, and Capstone Projects
Date of Degree
6-2026
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy
Program
Business
Advisor
Donal Byard
Advisor
Edward X. Li
Committee Members
Brandon Lock
Lin Peng
Subject Categories
Accounting
Keywords
scriptability, machine readability, human readability, textual analysis, lazy prices
Abstract
Price laziness refers to the delayed incorporation of textual information in financial reports into stock price, driven by investor inattention. This paper examines whether a decrease in machine processing costs, measured by the “scriptability” of firm disclosures, mitigates price laziness. Using a comprehensive sample of U.S. public firms from 1995 to 2022, I replicate and confirm the persistence of price laziness, with a portfolio strategy yielding abnormal returns of up to 11 percent annually. While theory predicts that lower information processing costs enhance price efficiency, I find that scriptability, on average, has no moderating effect on price laziness. This null result is partly explained by a crowd-out effect: scriptability reduces human readability, which itself mitigates price laziness. Notably, among firms heavily traded by algorithms, scriptability is significantly associated with attenuated price laziness, suggesting that machine-readable disclosures benefit only a subset of firms and investors. These findings have implications for firm management seeking to cater to machine users and for regulators seeking to balance human- and machine-readability in disclosure standards and highlight frictions in the transition toward more algorithm-based information processing and price discovery.
Recommended Citation
Xie, Wen, "Financial Disclosure Scriptability and Price Laziness" (2026). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/6673
