Quant investing
Crowding can be good for quants (sometimes) – Goldman
Study finds timing dictates different results for convergent and divergent strategies in herd moves
Credit Suisse and Rayliant team up for China quant launch
Firms want to tap investors' zeal for systematic strategies in A-shares
Baselines for applying machine learning to investing
Techniques that worked in the natural sciences may not translate well to financial markets
Privacy risks dash funds’ alternative data dreams
Asset managers see value in alternative data in its rawer forms, but most won’t touch it
UBS Asset Management cools on alternative data
Buy-Side Risk USA: Firm checked several datasets and found little alpha
Some trend followers are less than ‘pure’ – study
Sick of waiting for a crisis, some commodity trading advisers move from ‘pure trend’ to ‘trend-plus’
A blueprint for alternative data in asset management
UBS Asset Management’s data chief describes how alternative data can aid the investment process
CSOP to tap Chinese interest in quant with momentum index
Hong Kong asset manager plans to spin off products from recently launched cross-asset index
BlackRock’s psych team (yes) hunts for bias in trades
Portfolio managers asked to keep ‘trade diaries’ of the thinking that led up to poor investments
Quants clash: machine learning or linear models?
Some studies say the algorithms beat the common models; other studies say the opposite
Can nowcasting unlock factor timing?
Fulcrum Asset Management is running tests to see if fresher data can help improve factor allocations
Quants ‘running into walls’ with AI interpretability
Some firms “stumbling” with new technology, conference hears
Quants say big data is all buzz, no alpha
Efforts to extract alpha from alternative data have been “really unsuccessful”, says Domeyard’s Qi
Quants use AI to cut through murk of ‘sustainability’
Separating the wheat from the chaff is fundamental to ESG investing. Machine learning can do that
The common drivers behind alt risk premia’s difficult year
Statistical analysis shows four strategies caused most pain, but funds suffered differently
Dabbling in data science won’t cut it
Banks are seeking data-led boost for research arms – only a few will succeed
Arnott, Harvey: machine learning dangerous when data thin
Experts warn ML should be used “for its correct purpose”
Factor timing: scant upside, big downside
Stock selection trounces “tempting” factor timing in study
Banks bet on data to rescue research
Barclays, Morgan Stanley, UBS among those using data science to pep up their research offerings
Teach history to avoid mistakes of yesterday’s quants
Quant grads should be taught follies of LTCM, Gaussian copula and London Whale, writes UBS’s Gordon Lee
Learning algos that learn how to learn
Knowing what to remember and what to forget could help machines beat quant and discretionary investors
How quants at Value Partners pick Macau’s casino winners
Hotel data on ‘high rollers’ helps group make casino investment calls, as quant influence grows
When bonds struggle, so does alt premia – research
Ties between alternative risk premia and fixed income closer than appreciated