Reconstructing a Century of U.S. Corporate Bonds: Credit Risk in Historical Perspective – Mohammad Ghaderi, Sebastien Plante, Nikolai Roussanov & Sang Byung Seo

The authors build a new 128-year corporate bond database (1895–2022) — over 100,000 bonds and 7 million observations — by hand-collecting historical bond quotes from archival print sources and merging them with modern data.

Over this long sample, they find a sizable, statistically significant credit risk premium that survives controls for duration and interest rate risk — pushing back on recent work that attributes corporate bond returns mostly to the term premium. Notably, short samples fail to detect this; it only shows up with the century of data.

Credit spreads predict future bond returns and macroeconomic activity, but their power to forecast the business cycle weakens once prewar data and the Great Depression are added — suggesting the spread-economy link is time-varying.

Major equity factors (market, size, value) are also priced in corporate bonds over the long sample, supporting a common factor structure across stocks and bonds rather than segmented markets.

How Wise is the Crowd? Bias and Edge in Prediction Markets – Avaneesh Deleep, John Lee, Jenny Bai, Dhruv Suresh & Harsh Dhawan

Using tick-level order flow, wallet histories, and user commentary across Polymarket and Kalshi, the authors examine who actually generates and exploits pricing inefficiencies in modern prediction markets.

The classic favorite-longshot bias largely disappears once they control for contract lifecycle timing — what looked like that bias in “mention markets” is really a “Yes Bias,” where traders systematically overpay for the affirmative outcome.

“Whales” (the most capitalized traders) aren’t the sharpest; they tend to bleed expected value to small-order traders, trading on ideological conviction and suffering adverse selection.

The loudest participants add no edge — there’s no meaningful correlation between sentiment intensity and informational advantage, so vocal commentary is mostly noise.