Privacy Policy Shocks and the Erosion of Alternative Data Signals

The episode discusses one of the papers to be presented at the 9th Annual Data Science in Finance Conference by the Society of Quantitative Analysis (SQA) and the Chartered Financial Analysts (CFA) Society of New York on Thursday, January 8, 2026. This research explores how Apple’s App Tracking Transparency (ATT) policy served as a privacy-driven shock that disrupted the alternative data landscape in financial markets. By restricting cross-app tracking, the policy degraded the quality of mobile traffic signals, which were previously used by investors to predict firm performance. The authors demonstrate that mutual funds and financial analysts who relied on this data experienced a significant decline in their trading edge and forecasting accuracy. Consequently, the market's ability to price stocks efficiently weakened, leading to increased information frictions and higher trading costs for affected companies. Ultimately, the study highlights the fragility of non-traditional data and warns that privacy regulations can have unintended "ripple effects" on global capital allocation. Reference Abis, Simona and Tang, Huan and Bian, Bo, Breaking the Data Chain: The Ripple Effect of Data Sharing Restrictions on Financial Markets (July 01, 2025). The Wharton School Research Paper, Available at SSRN: https://ssrn.com/abstract=5334566 or http://dx.doi.org/10.2139/ssrn.5334566 Podcast Disclaimer This podcast is an independent production and is not affiliated with or endorsed by any third-party entities unless explicitly stated. The content is for educational and informational purposes only and does not constitute financial, investment, legal, or professional advice. Listeners should consult qualified professionals before making any decisions based on this content. This episode is based on the reference(s) listed above and was generated using Notebook LM and potentially other AI tools. While I have reviewed the content for accuracy, it may still contain errors, inaccuracies, or omissions. Neither the producers nor any affiliates accept liability for any damages or losses arising from the use or interpretation of this content.