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Dr. Yashan Wang is a Senior Director at Moody’s Analytics where he leads the research and quantitative modeling team for portfolio valuation and balance sheet analytics. He has led several research initiatives in asset valuation, credit migration, joint credit and interest rate dynamics, and balance sheet analytics.

Yashan has also worked with global clients and provided training and advice on enterprise risk management, asset and liability management, PPNR, and stress testing. Prior to joining Moody’s Analytics, Yashan was an Assistant Professor at the MIT Sloan School of Management. He has a PhD in Management Science from Columbia University.

Related Insights

What Do Half a Million Loans Say About the Impact of CECL on Loan Loss Allowance?

In this article, we use historical data to calculate and compare loan- and portfolio-level loss allowances under the incurred loss model and CECL.

July 01, 2017 WebPage Dr. Yanping PanDr. Yashan Wang

Impact of Using EDF9 on Credit Portfolio Analysis

This paper investigates the impact of using EDF9 instead of EDF8 values as inputs for estimating credit portfolio risk measures within Moodys Analytics RiskFrontier®. The recent EDF9 enhancements affect portfolio risk analysis via various channels — due not only to new values for default probabilities, but also because the market Sharpe ratio (i.e. market-level risk premium) and asset return-based correlations for corporate exposures depend on time series of EDF measures. In this paper, we focus on the question of how using the new EDF9 default probabilities alter patterns in portfolio risk measures.

June 2017 Pdf Noelle Hong, Jimmy Huang, Libor Pospisil, Lee Albert, Marc Mitrovic, Sunny Kanugo, Tiago Pinheiro, Andriy Protsyk, Dr. Yashan Wang

Measuring and Managing Credit Earnings Volatility of a Loan Portfolio Under IFRS 9

IFRS 9 materially changes how institutions set aside loss allowance. With allowances flowing into earnings, the new rules can have dramatic effects on earnings volatility. In this paper, we propose general methodologies to measure and manage credit earnings volatility of a loan portfolio under IFRS 9. We walk through IFRS 9 rules and the different mechanisms that it interacts with which flow into earnings dynamics. We demonstrate that earnings will be impacted significantly by credit migration under IFRS 9. In addition, the increased sensitivity to migration will be further compounded by the impact of correlation and concentration. We propose a modeling framework that measures portfolio credit earnings volatility and discuss several metrics that can be used to better manage earnings risk.

January 2017 Pdf Dr. Amnon LevyDr. Yanping PanDr. Yashan Wang, Dr. Pierre Xu, Dr. Jing Zhang, Xuan Liang