Commodities

Why rely on one model when many do better? By combining multiple forecasts, ensembles tend to deliver more accurate and resilient results. This first article in our two-part series explores the theory behind model ensembles, linking classic forecasting research with today’s financial machine learning. Discover why combining models consistently outperforms relying on a single predictor.

FX is fragmented by nature — and that’s exactly what makes it valuable. Our latest Quanta Byte explores how FX trends offer independent return streams that passive hedging misses. Discover what happens when FX diversification starts doing more than just reducing volatility.

Our research shows sectors deliver both top and bottom returns, while factors—especially Quality, Dividend Strength and Minimum Volatility—offer more predictable, diversified, and stable performance. We use sectors tactically based on business cycle signals, but our strategic focus remains firmly on factors for consistent, risk-adjusted returns. Discover the Hybrid Investment team’s view on Minimum Volatility equity strategies over the business cycle at the Quantitative Investment Boutique.

Are traditional factors falling behind? In this Expl(AI)ning Quanta Byte, we explore how AI can breathe new life into factor investing. Discover the concept of AI-powered factors—a smarter, more adaptive approach that turns static models into predictive engines.

Traditional volatility models often lag real market shifts, leaving portfolios vulnerable. Our new Quanta Byte introduces State-dependent Risk (SDR) - a dynamic approach that adapts faster to evolving conditions. By leveraging historical patterns and similarity measures, SDR more accurately forecasts volatility, helping investors navigate risk and protect their ascent.

Challenging entrenched biases, this special International Women's Day Quanta Byte decodes the myth of meritocracy in finance. Featuring insights from Prof. Renée Adams and Ola Mahmoud, discover how data dismantles stereotypes and reveals why perceptions of women in finance often stray from reality.