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RESEARCH INSIGHTS: Cyber Risk and Corporate Resilience

23 July 2026 in Externe publicatie door Luc Renneboog, Jasmin Gider, Tal Strauss

Using 14,261 cyber incidents across nearly two decades (2005–2023), we provide an empirical study of cyber vulnerability among publicly-traded U.S. firms, drawing on a rich dataset of publicly observable indicators: financial data, SSL certificate records, bug bounty programs, cyber-hygiene indicators from regulatory filings, executive and governance data, and detailed incident records.

RESEARCH INSIGHTS: FOMO in Equity Markets?

13 July 2026 in Externe publicatie door Andreas Brøgger, Joren Koëter, and Mathijs van Dijk

Using backtests on a comprehensive global equity dataset covering 47 countries over 1985–2023, we analyze how portfolio performance varies with the number of stocks. Two main findings stand out. First, contrary to commonly cited evidence, portfolios of 30–40 stocks are not sufficient to fully diversify idiosyncratic risk.

Second, we identify a novel dimension of concentration risk, which we refer to as FOMO (fear of missing out). When portfolios are more concentrated, stock selection becomes critical for performance, and investors face a wide dispersion in outcomes depending on which stocks are included. Investors may thus experience regret about their portfolio choice ex post when other choices would have yielded better performance. This effect is economically large and persists even for portfolios with hundreds of stocks.

RESEARCH INSIGHTS: Transfer Learning for Expected Returns

11 June 2026 in Externe publicatie door Julio Crego, Jens Soerlie Kvaerner, and Marc Stam

This study develops a transfer-learning framework that extends high-quality expected-return information from firms where proxies work well to the broader U.S. equity universe. The method first learns how firm characteristics map into high-signal expected-return proxies in a reliable “teacher” domain. It then applies a disciplined correction, using realized returns only as a calibration device, so that the predictions remain useful outside that original domain. The resulting measures cover U.S. equities from 1957 to 2023 and deliver near-unbiased forecasts relative to existing alternatives.

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