Quant investing
Investing is often seen as a blend of art and science, but the past decade has seen rapid growth in strategies that try to exclude the former entirely, instead seeking sources of return that are a provable feature of a market. These scientific investors are generally poorly served by mainstream finance publications.
Our aim is to cover, in plain English, the ideas and trends that matter. That means articles on research – into new sources of premia and shifting market behaviours, for example – as well as products and strategy. We also report on the related topics of data science, and trends in the use of artificial intelligence and machine learning.
Technical content can be found in our ‘Cutting Edge’ section, where we publish practitioner-focused, peer-reviewed papers.
Fuzzy data stalls ESG alpha hunt
Quants searching for ESG signals have reached very different conclusions. Mostly they blame the data
How diversifying too far weakened alt risk premia’s rebound
Strategies that hurt ARP funds in 2018 did better but some cancelled out last year
The age of ethical investing, but can quants cope?
Systematic managers grapple with ESG demands of clients
Study finds ‘significant’ crowding in hedge funds
New research links herd investing to bigger drawdowns in stressed markets
ESG like a new factor, alt managers say
Shift of capital to sustainable investing predicted to disrupt established strategies
Wells Fargo uses machine learning for performance attribution
Clustering algo delivers speedier and more accurate explanations of portfolio returns
Man and machine need each other – Systematica CEO
“The errors made by humans and robots are different,” says Leda Braga
Don’t invest in bad ESG companies, hedge funds told
Managers have seen a “sea change” in attitudes to sustainability
Ripping up the old asset class labels
Outmoded classifications of securities may be concealing market risk. AI has a better idea
Neuberger Berman gets its Sherlock on
Asset manager deploys quant-cum-sleuth to sniff out portfolio risk
Quants – pick your alt data wisely, says Goldman MD
Investors must balance risk of false signals versus missing out on alpha, says Matthew Rothman
Ex-Credit Suisse quants embrace machine learning
Founders of XAI Asset Management grapple with unsupervised learning and the problems of explainability
Allocation models that know their unknowns
Quants say probabilistic programming beats machine learning in balancing strategies
In factor timing, ‘where?’ matters as much as ‘when?’
Goldman quants’ thought experiment shows timing works best for low-Sharpe strategies
Quant funds look to AI to master correlations
Machine learning shows promise in grouping assets better, predicting regime shifts
Intercept: AQR’s risk-catching machine
CRO Mike Patchen has helped build a system to identify risks before they grow or spread
Stock-picking finds unlikely champion in ex-Winton CIO
Matthew Beddall’s Havelock restyles value investing for the big data age
Replication can illuminate private equity’s nascent risks
New benchmarks paint a less flattering picture of buyout funds
Quants clone private equity: pale imitation or real deal?
Theory says replication can work, but investors are reluctant to give up private equity’s smoothed returns
Credit Suisse uses neural nets to call minute-ahead forex
Bank encases AI in ‘control framework’ to curb risk and will stick to micro timeframe for now
Tech mergers have increased crowding risks, investors say
Risk USA: Consolidation among vendors means “everyone’s looking at the exact same model”
BlackRock, State Street, AB are making AI work in risk
Risk USA: Fund managers are using new technology to measure liquidity risk and spot their own errors
Cultural appropriation: private equity goes quant
Machines are helping venerable shops find under-the-radar performers and factors that drive them
Value: ‘Trade of the decade,’ says QMA
Quant firm predicts big revival for out-of-favour strategy