Dr. Juan Manuel Licari, Chief International Economist
Chief International Economist
Juan M. Licari, PhD, is Chief International Economist with Moody's Analytics. As the Head of Economic and Credit Research in EMEA, APAC and Latin America, Juan and his team specialize in generating alternative macroeconomic forecasts and building econometric tools to model credit risk portfolios.
Juan and his team develop and implement solutions that explicitly connect credit performance data to the underlying economic cycle, allowing portfolio managers to plan for forward-looking macroeconomic conditions and stressed scenarios. An experienced modeler, Juan has designed and implemented several IFRS 9, A-IRB, ICAAP, and stress-testing platforms for major institutions. In addition Juan regularly publishes research and presents at Moody's Analytics and industry events. He holds a PhD and an MA in economics from the University of Pennsylvania and graduated summa cum laude from the National University of Cordoba in Argentina.
Related Insights
Dynamic Model-Building: A Proposed Variable Selection Algorithm
In this article, we propose an innovative algorithm that is well suited to building dynamic models for credit and market risk metrics, consistent with regulatory requirements around stress testing, forecasting, and IFRS 9.
U.K. Residential Mortgages Risk Weights: PRA Consultation Paper CP29/16
This paper presents best practices for addressing PRA Consultation Paper CP29/16.
Probability-Weighted Outcomes Under IFRS 9: A Macroeconomic Approach
In this article, we discuss development of a framework that addresses the forward-looking and probability-weighted aspects of IFRS 9 impairment calculation using macroeconomic forecasts. In it, we address questions around the practical use of alternative scenarios and their probabilities.
Complying with IFRS 9 Impairment Calculations for Retail Portfolios
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.
Advanced Estimation and Simulation Methods for Retail Credit Portfolios: Frequentist vs. Bayesian Techniques
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.
Multi-Period Credit Risk Analysis: A Macro-Scenario Approach Presentation Slides
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.
Market Risk Stress Testing Models Presentation Slides
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.
Multi-Period Credit Risk Analysis: A Macro-Scenario Approach
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.
IFRS 9 Impairment Webinar Series – Models for Implementation
This webinar discusses determining the best approaches for model development and governance for IFRS 9 Impairment calculations.
Multi-Period Stochastic Scenario Generation
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.
