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.
Language barrier: quants slog to teach investing bots to read
Training models to interpret text can be dull; doing it badly can be costly
New breed of NLP model learns finance better, study finds
Models trained by looking at sentences beat conventional approaches that contextualise words
Stock-level ‘inelasticity’ explains ESG boom, research says
Reluctance of ESG investors to sell holdings is pushing prices even higher
‘Signatures’ promise quants a tool for all jobs
Little-known mathematical technique could find applications from pricing options to sniffing out alpha signals
Machines say: ‘Ignore the spread in merger arb’
Closely watched arbitrage spread poor predictor of a merger deal’s success, quant firm finds
Quant funds tackle chronic overfitting in crypto strategies
Firms adapt backtests and tread lightly to address “huge” overfitting risk, magnified by scarce data
A quant’s view on protecting stock-pickers from themselves
Ex-Citadel, Millennium risk manager says fundamental investors have much still to improve
An old model can shed new light on how flows shape prices
Market microstructure theory may also explain long-term patterns in stock markets
Two Sigma building quant tools to hunt real estate bargains
Information-rich market offers “trillions of dollars of opportunity”, says data chief
AI helps one investor screen targets against UN ethical goals
PanAgora develops two-stage process that aims to weed out the greenwashers
Clunky crypto markets serve quants well – can it continue?
Poor price discovery presents opportunities for systematic traders in super-trending markets
Don’t fret about elevated skew, vol experts say
Extreme relative cost of tail risk hedging is driven by flows more than fear
This quant firm cut 90% of its compute costs. Here’s how
Quantbot Technologies uses ‘smart data routing’ to stop runaway spending on data and computing
Quants split on who wins in the alt-data gold rush
Scale helps in handling new data, but alpha may be found in niche strategies
How algos are helping inflation-wary investors
Buy-siders look to machine learning for clues on the effect of rising prices on portfolios
Quants turn to machine learning to unlock private data
Replication could allow financial firms to use – and monetise – data that was previously off-limits
Market’s mystery jumps might be predictable after all
Endogenous volatility has a tell-tale pattern, quants find
Hedge funds not doing enough to fix mispricings, study finds
Passive investing has blunted market efficiency, but hedge funds are failing to capitalise
Investment flow tracking is next ‘frontier’ for alpha
Risk Live: Flows impact asset prices more than widely believed and may be more predictable – quants
Not so green machine? Questioning commodities’ credentials
As ESG investors eye commodities, issues around measurement and management are unearthed
Quant fund aims to tame bitcoin, and 39 other digital assets
Ex-Morgan Stanley, Winton vets reimagine institutional risk management for volatile crypto markets
Acadian builds ‘green screen’ to auto-filter ESG phoneys
$110 billion quant investor creates automated system to spot greenwashers
Fake data can help backtesters, up to a point
Synthetic data made with machine learning will struggle to capture the caprice of financial markets
In fake data, quants see a fix for backtesting
Traditionally quants have learnt to pick data apart. Soon they might spend more time making it up