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.
Banks discreetly seek personnel to mine alt data riches
Citi, Credit Suisse, HSBC and Morgan Stanley are hiring data scientists for a plethora of new initiatives
From AI to cheese: funds seek fixes for trend following
Firms turn to machine learning, hybrid products and new markets to boost returns
Financial risks don’t go on holiday
Better mapping of financial system would help avoid seasonal surprises, argues Andrew Lo
Bridgewater co-CIO on risk parity, correlations and contagion
All Weather fund's approach remains poorly understood, says Prince
Banks look to spin money from their own data
Big banks are tiptoeing forward with datasets for sale despite a host of internal obstacles
AllianceBernstein digs into its own data, looking for alpha
Firm combs through information about its portfolio managers for signs of bias and bad habits
UBS AM joins buy-siders building central data science teams
Data science unit will serve firm’s non-quant investment staff
Winton’s David Harding on turning away from trend following
Founder explains decision to scale back weighting of strategy that made firm’s name
Lo’s ‘dynamic alpha’ gives quants new tool to fine-tune strategies
Time-sensitive measure could help manage systemic risk too
A fool’s gold (or data) mine
Quants are building statistical toolkits to avoid the pitfalls of data mining
Quant manager spurns vendors’ machine learning software
Ex-head of algo trading at JP Morgan says machine learning processes should be built internally
EU market abuse rules could trip alternative data users
Regulators might treat some new datasets as inside information, lawyers say
UBS AM plans new generation of quant tools for stock pickers
Bryan Cross thinks ‘man plus machine’ investing will flourish
History suggests stock market crash not imminent – Goetzmann
Stock market bubbles have seldom burst, says Yale economist
Study finds holes in quality factor indexes
Metrics commonly used to build indexes bring zero alpha, says Research Affiliates
Funds seek ways to stay clear of factor flows
Gyrations in momentum and value are a reminder that investors can be swept up in factor reversals
Quant hedge fund of the year: Man AHL
Risk Awards 2018: New roles for machine learning, frontier markets and OTC data give fund an edge
Quant funds look past the obvious for uses of alternative data
Many systematic investors are sceptical but a few are finding ways to make new data work