Articles & Video
3 trends that will change quants’ future
Few things we learnt from QuantMinds International 2020.
Building the future of quant finance
Key insights from QuantMinds International 2020
The economic implications of climate change
We examine the physical risk of climate change for each country using the Moody’s Analytics Global Macroeconomic Model.
The future is bright... for those who survive
Last year we caught up with Marcos Lopez de Prado, talked about his book Machine Learning For Asset Managers, and predicting black swan events.
Solving the challenges of xVA management: How Danske Bank did it
The complexity of calculating xVA coupled with the need to meet regulations and to balance risk capital has been a challenge for all banks. For this reason, Danske Bank created and developed an innovative solution and method to tackle it.
Derisking AI by design: How to build risk management into AI development
The compliance and reputational risks of artificial intelligence pose a challenge to traditional risk-management functions. Derisking by design can help.
Analysing Covid-19 Data with AWS Data Exchange, Amazon Redshift, and Tableau
How to create COVID-19 dashboards using Tableau and different AWS services, such as AWS Data Exchange, AWS COVID-19 Data Lake, Amazon Redshift, and Amazon Athena.
Optimising variable annuity reserves through deep hedging
In this white paper we look at an application of the deep hedging approach to a new business problem: optimising reserves that life insurers are required to hold against variable annuity liabilities.
The rising awareness of model risk
Financial institutions are increasingly reliant on statistical risk models. But in turn, what risks do models pose to financial institutions?
Truly Explainable AI: Putting the “Cause” in “Because”
There are two serious problems with state-of-the-art machine learning approaches.
Model robustification and the future of quant finance: an interview with J.D. Opdyke, Allstate
Were your models caught by surprise when the pandemic hit? J.D. Opdyke, Allstate, explains how he built a robust framework and shares key learnings from this year.
Smart contracts and regulation: the centres of personalised law meet risk management challenges
Smart contracts promise a tailored experience, but what does that mean from a regulatory standpoint?
How is reinforcement learning different from un/supervised learning?
Marshall Chang, Founder and CIO, A.I. Capital Management, shares how to develop and deploy RL trading algorithms.
Staying afloat: How is quant finance changing under Covid-19?
Is the worst behind us? Or is it still to come?
Stop doing that! How unintentional bets are hurting your performance
How do you mitigate unintentional exposures that bring down your performance?
Looking forward to backward-looking rates: completing the generalised forward market model
Webinar presented by Fabio Mercurio, Global Head of Quant Analytics, Bloomberg L.P.
Can FX hedges of bonds deliver a free lunch?
Risk-free returns don’t exist – and if they did, even briefly, they would be traded on until they disappeared. Except sometimes, somehow, under just the right circumstances, the elusive free lunch may temporarily appear on the table…
How to forecast Covid-19 default and recovery rates
Find out how the forecasts of credit conditions changed.
Beyond Weisfeiler-Lehman: using substructures for provably expressive graph neural networks
How powerful are graph neural networks?
Five issues quants need to address in 2020
QuantMinds editor-in-chief Vincent Beard now summarises the five key conundrums on quants’ minds this year.
Fourier-based methods for the management of complex insurance products
Modelling for variable annuities products – how could the financial and insurance risks be integrated better?