Juan and his team are responsible for generating alternative macroeconomic forecasts for Europe and for building econometric tools to model credit risk phenomena. His team develops and implements risk solutions that explicitly connect credit data to the underlying economic cycle, allowing portfolio managers to plan for alternative macroeconomic scenarios.
Juan communicates the team’s research and methodologies to the market and often speaks at credit events and economic conferences worldwide. He holds a Ph.D and an MA in economics from the University of Pennsylvania and graduated summa cum laude from the National University of Cordoba in Argentina.
This article discusses how to address the specific challenges that IFRS 9 poses for retail portfolios, including incorporating forward-looking information into impairment models, recognizing significant increases in credit risks, and determining the length of an instrument's lifetime.
In this article, we compare the results of estimating retail portfolio risk parameters (e.g., PDs, EADs, LGDs) and simulating portfolio default losses using traditional – frequentist – methods versus Bayesian techniques.
In this presentation we present a two-stage process that generates consistent, transparent scenario-specific forecasts for all relevant market and credit risk instruments, ensuring cross-consistency between projections for macroeconomic and financial series.
In this presentation, Dr. Juan Licari of Moody's Analytics will present an innovative framework for stochastic scenario generation that allows risk managers and economists to build multi-period environments, integrating conditional credit and market risk modeling to meet dynamic stress testing needs.
In this presentation, Dr. Juan Licari presents a two-stage process that generates consistent, transparent scenario-specific forecasts for all relevant market and credit risk instruments, ensuring cross-consistency between projections for macroeconomic and financial series.
In this presentation, we present an innovative framework for stochastic scenario generation that allows risk managers and economists to build multi-period environments, integrating conditional credit and market risk modeling to meet dynamic stress testing needs.
This webinar discusses determining the best approaches for model development and governance for IFRS 9 Impairment calculations.
Robust models are currently being developed worldwide to meet the demands of dynamic stress testing. This article describes how to build consistent projections for standard credit risk metrics and mark-to-market parameters simultaneously within a single, unified environment.
This article describes the three principles that need to be understood and analyzed for banks to have a realistic chance of integrating alternative scenario work into their stress testing workflow.
This article discusses a macroeconomic forecasting model that is able to generate arbitrage-free scenarios.
Regulators are challenging how to perform stress testing on low default portfolios by reviewing bank's PD models for RWA stress testing, in the absence of data they need to be convinced of the methodology used. In this Moody's Analytics webinar we put forward a statistical approach to stress testing low default portfolios with practical case studies
The European Central (ECB) has begun a year-long comprehensive assessment of the Euro area banking system. In this webinar, Moody's Analytics seeks to provide a default data-driven context for the ECB's exercise and a preview for what is to come.
We present a two-step modelling and stress testing framework for the term structure of interest rates swaps that generates sensible forecasts and stressed scenarios out of sample. Our methodology is able to replicate two important features of the data: the dynamics of the spread across maturities and the alignment of the key swap rates tenor points to their corresponding government yields. Modern models of the term structure of interest rates typically fail to reproduce these and are not designed for stress testing purposes. We present results for the euro, the U.S. dollar, and British pound swap curves.
This article discusses how developing deterministic scenarios form a macroeconomic view on stress testing that helps to uncover system or enterprise-wide vulnerabilities and assist banks in making more informed business decisions.
In this article, we divide the stress testing process for retail portfolios into four steps, highlighting key activities and providing details about how to implement each step.
This whitepaper examines the challenge of multiplicity in reverse stress testing, where the same outcome can be obtained with multiple combinations of risk factors and economic scenarios.
For most financial practitioners, stress-testing is a “must-do” activity, even if it is not a regulatory requirement. Such stress-testing encompasses a wide range of sophisticated and quantitative exercises, including assessments of market, credit and liquidity risks. This article discusses several approaches and outlines a foundation for a robust and consistent stress-testing framework.
Reverse stress testing is becoming recognised throughout the world for its benefits. This presentation explains what reverse stress testing is and what it can achieve, along with the challenges it presents. Here we show you why reverse stress testing can lead to a deeper understanding of an organisation's susceptibility to risk and why it is a valuable tool for any risk management strategy.
This article presents a two-step modeling and stress testing framework for the term structure of interest rates swaps that generates sensible forecasts and stressed scenarios out of sample. The results are shown for the euro, the US dollar, and British pound swap curves.
