Non‑Traditional Data and Advanced Statistical Models for Stock-Market Valuation: Foundations for a Private‑Scale Systematic Alpha Fund
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- This thesis develops models and methods for predicting listed companies valuations, using exclusively innovative company data. Leveraging advanced statistical methods, the model includes non-traditional datasets, market risks, and seeks to mitigate biases. It dives into the role of alternative datasets, such as corporate activities, ESG data, and market sentiment, in enhancing predictive accuracy. And finally it addresses a useful question : when it comes to forecasting valuations, how much of the important information lies in the non-traditional data of the studied company ?