Modelling
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.
How accurate is the accuracy ratio in credit risk model validation?
The author presents four methods to estimate the sample variance of the accuracy ratio and the area under the curve.
Body and tail: an automated tail-detecting procedure
The quality of a tail model, which is determined by data from an unknown distribution, depends critically on the subset of data used to model the tail. Based on a suitably weighted mean square error, the authors present a completely automated method that…
Standard errors of risk and performance estimators for serially dependent returns
In this paper, a new method for computing the standard errors (SEs) of returns-based risk and performance estimators for serially dependent returns is developed.
Can CCPs zone in on improved margin buffers?
Dynamically adjusting margin add-ons could reduce cyclical funding demands
Statistical properties of the population stability index
This paper aims to fill a gap in the literature by providing statistical properties of the population stability index (PSI) and some recommendations on its use.
Institutional ETF trading – ETF traders navigate changing conditions
After years of growth and development, exchange-traded funds (ETFs) have cemented their place as a mainstay in investment portfolios and trading strategies. During a year of exceptional volatility and uncertainty, traders were able to take full advantage…
SA-CCR proves a bitter pill for US banks to swallow
Dealers concerned new regime will punish some business lines with rise in risk-weighted assets
A step closer to the perfect volatility model
Research on ‘rough volatility’ gives fresh insight into financial fluctuations, quant expert explains
Model misfires raise questions over training data
Quants wrestle with how far into the past their machine learning models should peer
Regulators’ margin model rules too lax – BlackRock exec
Risk USA: EU anti-procyclicality rules like “putting a curtain over a draughty window”
Covid-19 overwhelmed stress-testing models – banks
Risk USA: lenders forced to apply management overlays to models skewed by macro inputs
Supervisory bank risk early warning modeling: an examiner’s first line of defense
The results of this paper show that robust forward-looking statistical models are superior to backward-looking assessments of supervisory compliance, which could lead to less regulatory burden when integrated into the examination process, particularly at…
Regions deploys early-warning tool for credit risk
Risk USA: system alerted US superregional to impending defaults during Covid crisis
Achieving a holistic view of risk in times of crisis
What happens when risks become too global in scope and increasingly uncertain for a business to manage? Jeroen van Doorsselaere, senior director – finance, risk and regulatory reporting value propositions at Wolters Kluwer, explores the key steps to…
Why the US election fallout was not a surprise to banks
A contested result was unexpected, but scenario planning meant banks weren’t unprepared
Banks fold climate, pandemic and cyber risks into CCAR
OpRisk North America: anchoring idiosyncratic risks to macro scenarios a challenge, say experts