Articles & Video
How are quants addressing new regulation and technology?
Quantum computing, AI & ML fairness, IBOR reform
From investment strategies to tech and regulation: what did the experts at QuantMinds International say?
What’s being discussed at QuantMinds International? Our speakers joined us for a quick Q&A to talk about key issues in their fields of expertise.
Rethinking multi-asset portfolio strategies to capture velocity changes
Going beyond the passive vs. active asset management paradigm, a mix between fundamentals and systematic quantitative investment strategies may be appropriate to help capture velocity changes.
QuantMinds 2021 calendar
Virtual learning opportunities and in-person get togethers for the quant finance community.
AI explainability and adoption challenges: Thoughts from the AI & ML Summit
What’s standing in the way of artificial intelligence adoption?
From scarce to large data and back: machine learning in finance
Fuelled by data, machine learning methods require an efficient handling of massively large datasets. But what are the challenges posed by datasets themselves?
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.
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
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.
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…
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.
The right kind of volatility
Is there a right kind of volatility for market makers? And how do market makers make money?
The ups and downs of trading crypto and what’s next for blockchain?
On the nature of crypto-trading and blockchain
An introduction to natural language processing
From sentiment analysis to alternative data processing, NLP plays a key role in understanding markets and trends.
Innovations in quant trading strategies and modelling
People and markets have changed hugely, and quants need to adapt to this new equilibrium. Therefore, innovation, both technological and strategic, are in the spotlight in this QuantMinds eMagazine.
Unexpected bug in your machine learning: how can you recover?
What went wrong when ML doesn’t work as expected, and how can you mitigate the model risk?
Microstructure and information flows between crypto asset spot and derivative markets
Which crypto instrument on which exchange is the first to incorporate new information? Where are the most informed traders located? How long do traders on other platforms have to profit from the leaders reaction to news?