Quantitative finance
WHAT IS THIS? Quantitative finance is a field of applied mathematics concerned with financial markets. In banking, it spread from the pricing of derivatives to the modelling of credit, market and operational risks. Today’s quantitative analysts are scattered across a range of functions, from risk management and model validation, to data science, algorithmic trading and regulatory compliance.
What quant finance can learn from a 240-year-old problem
Optimal transport theory offers a data-driven way to calibrate derivatives pricing models
Investors question fixes for a quant strategy that’s stalled
Banks are revamping intraday trend strategies; buy-siders aren’t sure it’ll work
Nonlinear risk decomposition for any type of fund
A risk decomposition by fund manager, factor or instrument is proposed
Hints on quantification approaches
Tiziano Bellini, head of risk integration competence line, international markets at Prometeia, examines the key components of successful model risk management, focusing on the importance of integration, processes, governance and IT solutions to…
House of the year, Australia: ANZ Bank
Asia Risk Awards 2021
Abu Dhabi fund lures top quants for burgeoning team
StanChart analytics head joins Lopez de Prado at Abu Dhabi Investment Authority
Pricing American options under negative rates
This paper derives a new integral equation for American options under negative rates and shows how to solve this new equation through modifications to the modern and efficient algorithm of Andersen and Lake.
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 XVA quants learned to trust the machine
Initial scepticism about using neural networks for derivatives pricing is giving way to enthusiasm
The evolution of stress-testing capabilities, design and monitoring
Risk technology, data strategy and innovation audiocast series (part 3 of a series of 3)
Quants turn to machine learning to unlock private data
Replication could allow financial firms to use – and monetise – data that was previously off-limits
An approximate solution for options market-making
An algorithm for the market-making of options on different underlyings is proposed
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
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
Quant grad conveyor belt stalls as banks retrench
Jobs market is long quant graduates, short vacancies – but hiring freeze shows signs of thawing
The volatility paradigm that’s stirring up options pricing
‘Rough volatility’ models promise better pricing and hedging of options. But will they catch on?
Deep hedging strays when volatility gets rough – study
In the most realistic simulations, data-driven approach fared 30% worse than conventional hedging
My kingdom for the right copula
Copulas can still deliver if chosen with due attention to intuition and data, says quant fund chair
Research house of the year: Societe Generale
Risk Awards 2021: quant group’s tail-risk hedging strategies ‘saved the books’ of some big clients
Quant investment firm of the year: Nordea Asset Management
Risk Awards 2021: focus on tail risk – and a little ice in the veins – helped Nordea stare down Covid
Buy-side quant of the year: Alex Lipton and Marcos Lopez de Prado
Risk Awards 2021: optimal trading solution was inspired by concept used in nuclear cooling
Rising stars in quant finance: Iuliia Manziuk and Bastien Baldacci
Risk Awards 2021: new research tackles ‘fundamental’ but largely ignored smart order routing problem
Solving final value problems with deep learning
Pricing vanilla and exotic options with a deep learning approach for PDEs