Quantitative analysis
Competitive differentiation – Reaping the benefits of XVA centralisation
A forum of industry leaders discusses the latest developments in XVA and the strategic, operational and technological challenges of derivatives valuation in today’s environment, including the key considerations for banks looking to move to a standardised…
The theoretical foundations of XVAs
Bloomberg analyses the theoretical basis of XVAs, focusing on the works and findings of its head of quantitative XVA analytics, Mats Kjaer, who emphasises the role of the capital valuation adjustment as a major driver of derivatives trading profitability…
Quants clone private equity: pale imitation or real deal?
Theory says replication can work, but investors are reluctant to give up private equity’s smoothed returns
Navigating the impact of climate risk on financial stability
As uncertainty abounds on the impact climate change may have on the industry, financial services firms must best equip themselves for potential regulatory and socioeconomic changes to ensure they maximise the opportunities of embracing new best practices…
Banks join forces on model development utility
Crisil is working with HSBC and three other banks on platform to share model-building tools
Cultural appropriation: private equity goes quant
Machines are helping venerable shops find under-the-radar performers and factors that drive them
Realising opportunities while managing conduct risk
As efforts to transition from Libor to risk-free rates ramp up, Maria Blanco and Nassim Daneshzadeh, partners in PwC’s US and UK financial services practices, discuss two critical and interconnected strategies that are front and centre for PwC clients
ESG investing: It’s not just great to be good
Investing according to environmental, social and governance (ESG) criteria can be done in various ways, with continuing development of filters and ways of analysing companies. As the market in ESG indexes and investments linked to sustainability matures,…
Machine learning, Deutsche auction and repo haircuts
The week on Risk.net, September 14–20, 2019
Some quant shops doomed to ‘struggle’ – López de Prado
Theory-first firms must modernise their methods or wither, says machine learning expert
Asia Risk Awards 2019: The winners
The best of the best in Asia
House of the year, Hong Kong: Guotai Junan
Asia Risk Awards 2019
Derivatives house of the year, Asia ex-Japan: Credit Suisse
Asia Risk Awards 2019
Asia structured products house of the year: Societe Generale
Asia Risk Awards 2019
Quant house of the year: Credit Suisse
Asia Risk Awards 2019
Backtesting expected shortfall: mission accomplished?
A rigorous backtest for ES cannot exist, but a good approximation might do the job
The rise of the robot quant
The latest big idea in machine learning is to automate the drudge work in model-building for quants
Fishing for collateral with neural nets
SocGen quant uses deep learning technique to optimise collateral substitution
AllianceBernstein uses AI to sidestep ‘growth trap’
Random forest model aims to sort success stories like Amazon and Netflix from fast-growth losers
Risk Technology Awards 2019: Making machines more helpful
Machine learning can be too efficient; now, vendors are looking for ways to make it more accurate. Clive Davidson looks at the stories behind this year’s Risk Technology Awards
How AI could tear up risk modelling canon
BlackRock, MSCI, LFIS among firms looking to replace traditional, linear risk models