Modelling
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
Jerome Kemp on the skewed economics of clearing
Only Fed intervention prevented “a really big market disaster” during Covid, says derivatives veteran
The European intraday electricity market: a modeling based on the Hawkes process
This paper deals with the modeling of trading activity on the European electricity intraday market by a self-exciting point process.
Thinking the unthinkable – Staying ahead of the crisis curve
Industry leaders discuss the increased value of stress-testing in a world rocked by its second financial crisis in 12 years, the likely emergence of non-financial risks, and how financial institutions can establish efficient and effective stress-testing…
Stress‑testing under Covid‑19
Stress‑testing is a challenging exercise to regularly assess a bank’s level of risk or capital adequacy. Olivier Brucker, Sunayana Mehra and Ed Young of Moody’s Analytics explore an approach that can address this, proposing an alternative methodology…
Performance of value-at-risk averaging in the Nordic power futures market
The authors investigate the performance of various value-at-risk (VaR) models in the context of the highly volatile Nordic power futures market, examining whether simple averages of models provide better results than the individual models themselves.
Back to school: BlackRock uses quant quake lessons on Covid
Pandemic prompts a switch in approach from strategic to tactical
Corporate default risk modeling under distressed economic and financial conditions in a developing economy
The authors create stepwise logistic regression models to predict the probability of default for private nonfinancial firms under distressed financial and economic conditions in a developing economy. Their main aim is to identify and interpret the…
Science friction: some tire of waiting for quantum’s leap
Use cases for new tech are piling up – from CVA to VAR. But so are the obstacles
A joint model of failures and credit ratings
The authors propose a novel framework for credit risk modeling, where default or failure information and rating or expert information are jointly incorporated in the model.
Alt data aims to shake up credit scoring business
Young firms, using machine learning methods to scrape consumer info, challenge established agency model
Fund managers seek to plug holes in ESG data
Social intel proves elusive as virus reawakens sense of corporate virtue
Banks aim to close op risk stress test capital gap
Standardising stress drivers could help smooth differences between bank loss estimates
Cliff effect might demand risk calculation agility until Libor cessation
Didier Loiseau, global head of rates, bonds and credit at Murex, examines the problems that originate from the spread calculation technicality stipulated by the new International Swaps and Derivatives Association Ibor fallback supplement, which…
Covid scenarios, pt II: apocalypse how?
Second crowdsourced scenario exercise reveals polarised views in equities and FX
Ratings can still sharpen credit risk picture
Study shows even the most modern default models benefit from adding credit rating information
NYU’s Epstein on fear and complacency in the age of Covid
Pioneer of agent-based models warns of virus resurgence akin to 1918 Spanish flu
Vol decay and correlation flips: CFM’s take on the Covid crisis
Market bounce-back blindsided quant investment firm – and others
To make sense of complex systems, send in the agents
Standard quant models cannot comprehend a radically complex reality, writes Jean-Phillippe Bouchaud
The use of range-based volatility estimators in testing for Granger causality in risk on international capital markets
This study utilizes the extreme value theory (EVT) approach to compare the performance of a wide variety of range-based volatility estimators in the analysis of causality in risk between emerging and developed markets.
Podcast: Investing, climate risk and energy firms
How are investors enabling the move to the low-carbon economy?
Study suggests banks may be better off with simpler VAR models
Non-parametric VAR models perform well in calm markets, but miss the mark in volatile periods