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.
R-nought is the wrong number for markets, academics say
New research suggests volatility of transmission matters more for asset prices
Negative Vix premium signals vol spikes, research finds
Unusual pattern seen in Covid crash could help volatility sellers avoid future reversals
Quants puzzle over how to handle negative oil prices
Firms are choosing to cut ‘outlier’ prices from data or to rely more on fundamental inputs
Two quants use options pricing tools to model Covid-19
New tool aims to gauge wider cost of virus control measures
Alt risk premia chasing 'tail beta' – again
Quant strategies that failed in the coronavirus crash face a reckoning
Safe havens no longer safe, quants fear
Equity-debt correlation breakdown and negative bond yields make investors nervous
To model the real world, quants turn to synthetic data
Future financial models will be built using artificially generated data
Some quants fear more deleveraging to come
Buy-siders brace for further selling after hedge funds dumped risk in March
Quants pitch in to improve pandemic models
The finance industry’s quants are trying their hand at modelling the virus and its economic impact
Covid-19 tumult is testing AI fund returns
Some ML strategies have coped well, but others began to struggle as panic mounted
Quants warn on credit risk in stocks
Conventional models may be missing explosion in novel exposure
To handle Covid-19 we need better data
Winton’s David Harding says unconscious bias in test data means epidemic is poorly understood
Covid transparency would soothe markets – Harvey
“Why aren’t our policy-makers sharing their models?” asks Duke University economist
Lighting up the black box: a must for investors?
Many contend you must be able to interpret machine learning in order to use it
At Numerai, real-world figures need not apply
AI hedge fund CEO sees the light in black-box technology
Factor strategies seesaw in coronavirus-hit markets
Quants struggle to second-guess ongoing effect of virus on investments
‘Quantamental’ approach convinces Morgan Creek CEO
Proponent of big-picture investing sees growing role for machines, but with caveats
Prising open the black box of AI
Shapley values, Lime and other tools can help decipher machine learning’s output. It’s a start…
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