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.
Is low vol crowded? That depends who you ask
Equity drawdowns have pushed more investors into low volatility strategies, raising fears of a build-up of risk
The quant investor harnessing the power of ants
Swarm Technology designs network of trading algorithms that mimics hive mind of insects
Role of the dice: how Susquehanna puts game theory to work
One of the world’s largest options traders uses game theory – and poker practice – to get results
No link between geopolitical risk signals and returns – hedge fund
Gauges of geopolitical risk are better at predicting volatility than equity returns, research from XAI finds
Growth to value, and back via quality
Inflation-fuelled stock rotations are full of complexity
Geopolitical risk models not ‘rigorous’ enough, says quant
Joseph Simonian believes game theory and reinforcement learning could improve matters
AI models point to recession, but quants won’t trade on them
Predicting the odds of a recession, and how markets will respond, is still a step too far for machines
When stagflation looms, investors get no satisfaction
In a toxic inflation-stagnation mix, conventional trades and hedges falter; alternatives are unproven
JP Morgan quants are building deep hedging 2.0
New model uses Bellman technique to learn general derivatives hedging strategies
‘Corrective’ algo tells quant firm when it’s wrong
QTS has built a machine to show whether a strategy is likely to succeed or flop
‘Trend’ triumphs in uncertainty, but not as it wanes – study
Quant investing approach thrives in extremes of market uncertainty; calm hinders it
From ‘cottage industry’ to quant-ready: prop data at JP Morgan
Unique information now “table stakes” for brokers as they compete for new clients
Revival of FX carry strategy leaves quants unconvinced
Record returns in March give little comfort that strategy is ‘back’
Stocks and bonds start to move in step, making quants jittery
Long-established inverse correlation between asset classes breaks down during first quarter
Earnings call analysis 2.0 goes beyond good and bad words
Quants develop new ways to extract signals from media-savvy chief executives and their financial statements
Analysts reveal more than company execs on earnings calls – AB
Sentiment signals derived from what analysts say beat those based on bosses’ responses, say quants
Adia wealth fund is building supergroup of quant investing
Abu Dhabi Investment Authority wants to turn systematic investing into a ‘good science’
How NN IP uses machines to read the market – and itself
Dutch manager being acquired by Goldman uses machine learning to ‘augment’ its analysts
Midday stock reversals becoming more common, quants say
Zig-zagging markets could spell trouble for quant strategies and dealers hedging options
Market reversals trigger losses for intraday quant strategy
Equity trend strategies designed to hedge against market drops have suffered in recent turmoil
Quants turn to single stocks to revive intraday trend strategy
Retail trading boom has made intraday single-stock strategies more viable
Investors question fixes for a quant strategy that’s stalled
Banks are revamping intraday trend strategies; buy-siders aren’t sure it’ll work
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