Earnings announcements create some of the market’s most persistent and tradable pricing dislocations, yet turning that phenomenon into a robust systematic strategy requires far more than a simple surprise screen. This book is written for quantitative equity traders, factor researchers, and systematic portfolio managers who want a disciplined framework for harvesting post-earnings announcement drift through investable long-short models rather than fragile backtests or anecdotal event studies.
Beginning with the statistical and market-structure foundations of event-driven equity research, the book leads readers through earnings data architecture, bias-resistant research design, and the empirical mechanics of PEAD itself. It then shows how to measure earnings surprise correctly, engineer stronger predictive signals, and transform those signals into neutralized cross-sectional factor portfolios. Readers will learn how to manage turnover, model transaction costs and shorting frictions, design realistic event-driven backtests, and evaluate performance using risk-adjusted and attribution-based diagnostics suitable for live deployment.
What distinguishes this treatment is its end-to-end, production-minded orientation. Rather than stopping at anomaly documentation, it follows the strategy all the way into validation, monitoring, governance, and research-to-production pipeline design. The result is a practical quantitative blueprint for building, testing, and maintaining earnings-surprise alpha in real institutional trading environments.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Earnings announcements create some of the market's most persistent and tradable pricing dislocations, yet turning that phenomenon into a robust systematic strategy requires far more than a simple surprise screen. This book is written for quantitative equity traders, factor researchers, and systematic portfolio managers who want a disciplined framework for harvesting post-earnings announcement drift through investable long-short models rather than fragile backtests or anecdotal event studies.Beginning with the statistical and market-structure foundations of event-driven equity research, the book leads readers through earnings data architecture, bias-resistant research design, and the empirical mechanics of PEAD itself. It then shows how to measure earnings surprise correctly, engineer stronger predictive signals, and transform those signals into neutralized cross-sectional factor portfolios. Readers will learn how to manage turnover, model transaction costs and shorting frictions, design realistic event-driven backtests, and evaluate performance using risk-adjusted and attribution-based diagnostics suitable for live deployment.What distinguishes this treatment is its end-to-end, production-minded orientation. Rather than stopping at anomaly documentation, it follows the strategy all the way into validation, monitoring, governance, and research-to-production pipeline design. The result is a practical quantitative blueprint for building, testing, and maintaining earnings-surprise alpha in real institutional trading environments. N° de réf. du vendeur 9798896655336
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Post-Earnings Announcement Drift | Building Factor Models for Earnings Surprise Alpha | Soren T. Blackwell | Taschenbuch | Englisch | 2026 | NobleTrex Press | EAN 9798896655336 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 138229027
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