Liquidity sleeves that mimic a fund’s strategic asset allocation with ETFs could help asset owners navigate bouts of volatility, as seen during the months of March and April this year, iShares says.
The Chinese stock market is driven by different quantitative factors than those in the US and Europe, Ping An China Asset Management (Hong Kong) Deputy CIO said. Steve Zhang speaks to us about the companies quant and machine learning strategies.
State Super has established an Academic Oversight Body, to ensure good governance of the fund’s activities in machine learning.
Since the GFC, macroeconomic events have become strong drivers of asset returns. Loomis Sayles has now developed a crisis sensitivity ratio model to better understand how these events impact markets.
When bonds no longer offer defensiveness, where do you look for portfolio protection? Perhaps it is time to set an explicit negative equity correlation target, Aberdeen Standard Investments says.
Cluster analysis is a good example of how machine learning can be practically applied to investment problems, a session at the Frontier Advisors Annual Conference showed. And the applications seem endless.
Traditional factor portfolios have had a tough time before and during the pandemic. This is an excellent opportunity for the industry to accelerate its innovation toward alternative data and AI.
Algorithmic stock analysis models, or robo-analysts, outperform their human counterparts, largely because they are less conflicted and avoid biases, a new study has found.
Wells Fargo AM’s Wai Lee discusses the considerations that go into implementing an allocation to trend following strategies in a multi-asset portfolio and finds that small changes can have big consequences.