Institute of Advanced Investment ManagementInvesting Research
Boundaries of Time Series Momentum
Read more →: Boundaries of Time Series MomentumMatti Suominen and Erik Hjalmarsson Time-series momentum is one of the most reliable and heavily backtested anomalies in quantitative finance, serving as a foundational alpha source for managed futures and trend-following strategies. This paper uncovers a structural vulnerability that every practitioner must account for: momentum returns persist reliably during normal business cycles, but break down…
Do LLM “Crowds” Produce Investment Signals? An Empirical Test
Read more →: Do LLM “Crowds” Produce Investment Signals? An Empirical TestSteven Edwards This paper tests whether aggregating stock selections from a large, philosophically diverse ensemble of LLM personas can produce genuine investment signals beyond passive benchmark exposure. The author built 100 distinct investor pe rsonas spanning value, momentum, growth, ESG, quantitative, and contrarian philosophies, each independently selecting fifty US-listed equities. The picks were backtested across…
Testing an AI-Assisted Research Workflow for Multi-Asset Pullback Strategy Discovery
Read more →: Testing an AI-Assisted Research Workflow for Multi-Asset Pullback Strategy DiscoveryThis study builds a short-term mean-reversion strategy across six liquid ETFs spanning equities, fixed income, currencies, gold, and commodities (2006–2025), using a 200-day trend filter and a multi-day pullback trigger. Beyond the strategy itself — which delivers strong risk-adjusted returns while invested only ~21% of the time — the paper tests ChatGPT and Claude as…
Guardrails Make the Researcher: What an AI Agent Got Right (And Wrong) Replicating Nine Equity Anomalies
Read more →: Guardrails Make the Researcher: What an AI Agent Got Right (And Wrong) Replicating Nine Equity AnomaliesAn autonomous AI research agent was tasked with replicating nine published U.S. equity anomalies on clean, survivorship-free data. On a faithful build, none survive out-of-sample — and the lone apparent survivor turned out to be the agent’s own construction error. The real lesson is that an AI researcher is only as trustworthy as the guardrails…
How Wise is the Crowd? Bias and Edge in Prediction Markets
Read more →: How Wise is the Crowd? Bias and Edge in Prediction MarketsUsing tick-level data from Polymarket and Kalshi, this study finds the classic favorite-longshot bias is largely a ‘Yes Bias,’ that the most capitalized traders systematically underperform smaller ones, and that the most vocal participants add no informational edge. It offers a reproducible method for denoising prediction-market probabilities.
Reconstructing a Century of U.S. Corporate Bonds
Read more →: Reconstructing a Century of U.S. Corporate BondsA new 128-year database of U.S. corporate bonds (1895–2022) — over 100,000 bonds and 7 million observations — uncovers a sizable, statistically significant credit risk premium that shorter modern samples fail to detect. The findings support strategic allocations to corporate credit for long-horizon investors and establish a new benchmark for empirical asset pricing in fixed…