Modelling
How algos are helping inflation-wary investors
Buy-siders look to machine learning for clues on the effect of rising prices on portfolios
Deep XVAs and the promise of super-fast pricing
Intelligent robots can value complex derivatives in minutes rather than hours
Market’s mystery jumps might be predictable after all
Endogenous volatility has a tell-tale pattern, quants find
Banks fear Fed crackdown on AI models
Dealers say agencies’ request for info could prompt new rules that stifle model innovation
Pricing services play critical role in securities valuations under SEC rule
Pricing services face scrutiny from investment managers as the US Securities and Exchange Commission's (SEC's) new 2a-5 ‘fair value’ rule takes effect. Here, Refinitiv’s Joseph Hayek explains how pricing services should prepare for the surge in customer…
From one extreme to another: Covid upsets loan models once more
Unusual economic slumps tripped up models in 2020. Now, they are struggling with fast recoveries
Quant fund aims to tame bitcoin, and 39 other digital assets
Ex-Morgan Stanley, Winton vets reimagine institutional risk management for volatile crypto markets
Libor transition nears its end – Five topics you need to know
As the deadline to Libor cessation approaches, Liang Wu, executive director of financial engineering and head of cross-asset product management at Numerix, presents a series of market themes that warrant closer inspection
Fake data can help backtesters, up to a point
Synthetic data made with machine learning will struggle to capture the caprice of financial markets
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
Jarrow and co find a better way to spot stock market bubbles
Quant team’s options-based approach avoids pitfalls of historical data dependence
ECB’s models review heaped €275bn of extra RWAs on banks
Average bank CET1 capital ratio fell 71bp through Trim process
Rough volatility’s steampunk vision of future finance
Some of the trickiest puzzles in finance could be solved by blending old and new technologies
Sign prediction and sign regression
This paper proposes an approach whereby the loss function regularizes the errors in prediction in different ways.
The volatility paradigm that’s stirring up options pricing
‘Rough volatility’ models promise better pricing and hedging of options. But will they catch on?
As machines disrupt investing, people still have a role to play
Despite AI’s growth, investing still needs human adaptability and judgement, writes Schroders’ Lim
Seismology models sound out safe ground for DG Partners
Quake technology helps quant firm time entry and exit points – and buck trend-following trend
A verification model to capture option risk and hedging based on a modified underlying beta
This paper analyzes the relationship between option risk and expected return from the perspective of the underlying beta, and estimates the degree of correlation.
The impact of energy costs on industrial performance: identifying price and quantity effects in the aluminum industry using a data envelopment analysis approach
The authors build a frontier function model with technical and cost efficiency measures to assess the impact of energy costs on competitiveness in the aluminum industry, a heavy energy consumer, by identifying what may be attributed to price and quantity…
Funds rush to take the temperature of their portfolios
Big investors, including BlackRock, are using new metrics to measure their funds’ carbon emissions
My kingdom for the right copula
Copulas can still deliver if chosen with due attention to intuition and data, says quant fund chair
Ex-SunGard chief Cris Conde’s random walk to fintech and beyond
Technologist talks artificial intelligence, angel investing and accidentally contributing to the Basel framework
Determination of weights for an optimal credit rating model based on default and nondefault distance maximization
This study proposes a credit rating model that accurately identifies default and nondefault companies by maximizing intergroup credit score deviations and minimizing intragroup deviations.