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    Dr. Jun Chen

    Jun Chen is a senior director at Moody’s Analytics where he leads the commercial real estate (CRE) research team. His team conducts empirical research and develops quantitative models focused on CRE loan credit risk for Moody’s Analytics product and service offerings.

    Jun has many years of experience and is an established domain expert in the real estate finance industry. His expertise covers a wide range, including areas such as commercial real estate market analysis, credit risk modeling, stress testing, and portfolio management. His work has been published widely in academic and professional journals and conferences. Jun has a PhD with a specialty in real estate finance and urban economics from the University of Southern California. He has an MA and a BA from Tongji University.

    Published Work
    Presentation

    ‍The CRE Equivalent of Zestimate: Combining Machine Learning and Spatial Modeling to Mine Big Data ‍

    With an increasing demand for faster and more objective estimates of fair market rent and pricing for commercial properties, we explore bringing the automated valuation model (AVM) to CRE.

    November 2019
    Whitepaper

    Estimating Commercial Real Estate (CRE) Stressed Loss Measures Under Federal Reserve 2017 Comprehensive Capital Analysis and Review (CCAR) Scenarios

    For the 2017 CCAR program, the Federal Reserve published three macroeconomic and financial scenarios to be used in stress testing 34 CCAR financial institutions. In this study, we analyze 27 institutions, with a total of more than $760 billion in exposures to commercial real estate loans, using Moody's CMM Stress Testing framework. This report describes how we derive credit loss estimates for the CRE loan portfolios held by CCAR firms. This is our first study leveraging the loan-level commercial banks' data collected via Moody's Analytics CRE Credit Research Database (CRD™). Our analysis estimates that the expected nine-quarter, cumulative CRE portfolio loss through the first quarter of 2019 is 6.5% under the CCAR 2017 Severely Adverse Scenario. The primary factors behind the higher loss estimate compared to last year's stressed scenario (5.1% loss) is that this year's scenario features a slightly more severe economic downturn and a significantly larger decline in commercial real estate prices.

    March 2017
    Webinar-on-Demand

    CRE CECL Methodologies

    The second in our CECL Quantification webinar series, this webinar discussed how commercial real estate (CRE) models and methodologies can be leveraged to fulfill CECL requirements, and key considerations in transitioning these models.

    February 2017
    Presentation

    CRE CECL Methodologies Webinar Slides

    In this presentation for the CECL Quantification webinar series, we discuss how commercial real estate (CRE) models and methodologies can be leveraged to fulfill CECL requirements, and key considerations in transitioning these models.

    February 2017
    Whitepaper

    Estimating Commercial Real Estate (CRE) Stressed Loss Measures Under Federal Reserve 2016 Comprehensive Capital Analysis and Review (CCAR) Scenarios

    For the 2016 CCAR program, the Federal Reserve published three macroeconomic and financial scenarios to be used in the stress testing of 33 CCAR financial institutions. In this study, we analyze 26 of these financial institutions, with a total of more than $695 billion in exposure to commercial real estate loans, using Moody's CMM Stress Testing framework. This report describes how we derive credit loss estimates for the CRE loan portfolios held by CCAR firms. Our analysis estimates that the expected nine-quarter, cumulative CRE portfolio loss through the first quarter of 2018 is 5.1% under the CCAR 2016 Severely Adverse Scenario. The primary factor behind the lower loss estimate compared to last year's stressed scenario is that CRE market conditions continued to improve during the past five quarters. From Q3 2014–Q4 2015, the commercial real estate price index increased by 11.6%, which substantially lowered average LTV and improved DSCR for the typical CRE loan portfolio.

    March 2016
    Whitepaper

    Modeling Canadian Commercial Real Estate Loan Credit Risk: An Overview

    Commercial real estate (CRE) exposures represent a large market share of credit portfolios for many Canadian banks, credit unions, insurance companies, and asset managers. While this segment escaped the most recent financial crisis relatively safely, Canadian CRE loan portfolios may be facing heightened credit risks given the current changing market conditions, which include sliding oil prices and reduced demand for natural resources and possible interest rate hikes. Given this environment, is critical to use an objective credit risk measurement solution that quantifies CRE loan risks consistently and objectively in order to help assess, stress test, and manage loan portfolios. This paper presents Moody's Analytics Commercial Mortgage Metrics (CMM™) framework, tailored for Canadian CRE loan credit risk, forming the core of our Commercial Mortgage Metrics: Canada (CMM Canada™) product. Based on the well-established CMM U.S. model, our enhanced framework incorporates new factors that capture unique Canada CRE market dynamics and lending practices. We describe our modeling approaches for default probability, loss given default (LGD), Expected Loss (EL), and other related risk measures.

    November 2015