Resume

• 2010

  Doctor of Philosophy (Ph.D.)

  Dissertation: The Impact of Uncertainty on Data Revision\nAdvisor: Dr. C. James Hueng

  Applied Economics

  3.8/4.0

• 2008

  Master’s Degree

  Economics

  San Diego State University-California State University

  Advanced Econometrics II

  Macroeconomic Theory I

  Advanced Econometrics I

  Introduction to Mathematical Economics

  Introduction to Econometrics

  Monetary Policy

  Monetary Economics

  Economic Statistics

  Macroeconomic Theory II

• 2003

  Bachelor’s Degree

  Sociology

  National Taipei University

• peijusung

  peijusung has 1 repository written in R. Follow their code on GitHub.

  Pei-Ju's GitHub Repository

  Microsoft Office

  Econometrics

  SQL

  LaTeX

  Stata

  Experimental Design

  Regression Analysis

  Statistics

  Microsoft Excel

  SAS

  PowerPoint

  Time Series Analysis

  Analytics

  Data Analysis

  Macroeconomics

  SPSS

  R

  Monetary Economics

  Research

  Statistical Modeling

  The evidence of the comparative advantage in research and development

  • Examined the effect of relative endowment with skilled labor on the return of R&D expenditure in total factor productivity \n(Model: co-integration model in panel data. Tool: EViews)

  Asymmetric dynamics in the correlations of price and trading volume in the housing market

  • Examined the instability in the price-volume relationship due to changes in the number/proportion of first-time homebuyers in the housing market (Model: Three-stage least-square model. Tool: Stata) \n• Studied the price-volume correlation in the housing market \n(Model: Asymmetric dynamic conditional correlation GARCH model. Tool: GAUSS)

  The Impact of Uncertainty on Data Revision

  Papers: http://www.peijusung.com\nSource code: https://github.com/peijusung/Dissertation\n\n• Studied data quality and reliability of real-time data \n• Developed method to detect unreliable entries in initial releases of GDP data using uncertainty (EPU) index \n• Demonstrated the significant capability of EPU index to detect and estimate sampling/non-sampling errors in GDP\n• Showed EPU-detectable errors in GDP undermine the ability to forecast inflation using GDP\n• Data source: Real-time GDP from the Fed of Philadelphia real-time database website. Information set of ~200 macroeconomic variables from public sources (e.g. Fed of St. Louis

  Bureau of Labor Statistics)\n• Examined the rationality and reliability of GDP data (Model: asymmetric rationality model

  log-linear model. Tool: Stata)\n• Forecasted the magnitude of errors in the GDP data (Method: out-of-sample predictions - recursive

  rolling

  and fix-sample forecasts. Tool: Stata)\n• Forecasted inflation using real-time output data (Method: out-of-sample prediction - fix-sample forecasts. Tool: Stata)\n• Evaluated out-of-sample forecasting accuracy (Method: Bootstrapping. Tool: R)\n• Modeled errors in current-quarter GDP (Model: Dynamic common factor model. Tool: RATS)

  Sung

  Pei-Ju (PJ)

  Bank of the West

  Western Michigan University

  Visa

  SoFi

  San Francisco Bay Area

  Director

  Model Risk Management

  Visa

  San Francisco Bay Area

  Senior Credit Risk Strategist

  SoFi

  •\tDeveloped curriculum

  course materials

  homework

  and exams for two full semesters of undergraduate introductory macroeconomics course (ECON 2020: Principles of Macroeconomics)\n•\tResponsible for the progress of >50 undergraduate students\n•\tAnswered student questions and provided guidance during office hours\n•\tAverage course evaluation score for both semesters: 4.1/5.0

  Course Instructor: Principles of Macroeconomics

  Kalamazoo

  Michigan Area

  Western Michigan University

  San Francisco Bay Area

  •\tIdentify sources of model risk and conduct effective challenges on different aspects of models\n•\tAssess data quality by conducting data reconciliation/concatenation tests and replicating the data collection and integration process. \n•\tIdentify and investigate the causes of model deteriorations through monitoring the model performance \n•\tEnsure the modeling methods and governance/controls are meeting regulatory requirements \n•\tCompile detailed reports

  present findings

  and answer ad-hoc questions from key corporate stakeholders and government regulatory agencies through data analysis

  statistical tests

  or modeling\n•\tProvide expert technical guidance and support on model development

  use

  and validation practices\n•\tValidate models including ALLL models (FAS114 Impairment Calculation)

  IFRS9

  CCAR models (C&I PD/LGD)

  PPNR (Prepayment

  New volume

  Utilization)

  BSA/AML models (KYC)

  Scorecards (Auto

  SFR

  Credit Card)\n•\tAchieve exemplary on-job performance exceeding expectations during 2017-2018 annual review\n•\tReceived Risk Recognition Award for work excellence in 2018Q3

  Model Validation Analyst

  AVP

  Bank of the West

  English

  Chinese

  Center for Public Economics Louis Freeman Scholarship

  • Awarded annually to the top 7 papers submitted on the discussion of any public economic policy topic\n• Discussed the merits of the auto bailout based on Classical and Keynesian economics\n

  San Diego State University Center for Public Economics