Articles & Video
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.
Should we be worried that the Fed has gone all-in?
Did the Federal Reserve just announce unlimited quantitative easing?
A conversation with “Quant of the Year 2019” Marcos Lopez de Prado
Marcos Lopez De Prado opens up about the issues of econometric investments and how asset management needs new technological innovations.
The cryptocurrency Chimera: Is Bitcoin digital or fool’s gold?
Patrick Tan, CEO, Novum Technologies analyses the relationship between Bitcoin and gold.
An introduction to natural language processing
From sentiment analysis to alternative data processing, NLP plays a key role in understanding markets and trends.
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?
What are the latest innovations in quantum machine learning?
Alexei Kondratyev, Managing Director, Global Head of Data Analytics, CCIB, Standard Chartered Bank, summarises the most promising breakthroughs in quantum computing and applications of quantum information theory, while exploring the opportunities that this presents quant finance.
Welcome to the range: Recession risks and rate cuts in the rear window for now. Time to get active?
Is it a better time than ever to start active management in ETFs?
Around the world in 750 words: My 2020 political risk predictions column
Here is Dr. John C. Hulsman's main political risk prediction for the coming year.
Machine learning with quantum annealing
2018 Quant of the Year Alexei Kondratyev shares his passion for machine learning and quantum computing.
Learn this about options: Pricing is hedging
PhD Candidate at École Polytechnique Marcos Costa Santos Carriera takes a look at applying Q-Learning to option pricing, and its impact on hedging strategies.
What will risk management look like after IBOR 2021?
ISDA representatives at RiskMinds International 2019 explore the IBOR transition and the impact on FRTB.
What does 2020 have in store for quant finance?
Understanding new trends, challenges, and solutions
From emotions to decisions – a framework for using big data in portfolio management
A case study in using alternative data by SESAMm and La Française Investment Solutions.
How to achieve inclusivity in an exclusive sector?
Women make up less than 10% of quant finance professionals, so how can you get those numbers up?
What’s the one thing that will disrupt quant finance the most?
QuantMinds International thought leaders talk about the biggest game-changers in the industry!
Artificial intelligence, machine learning, and data in quant finance
In this compilation of articles, FutureQuantMinds explore AI, ML, and the impact of data on quant finance
What’s the best language for machine learning?
Python vs R – Erdem Ultanir, Quantitative Credit Risk Analytics Lead at Barclays, evaluates the two languages
The lookout on risk management and quant trading
In this compilation of articles, FutureQuantMinds talk about the challenges that the risk side of quant finance will meet