CLO Structuring&Origination

Rate new corporate CLOs, review documentation, perform quantitative analysis and discuss legal documentation and issues with underwriters

•Monitor credit ratings on over 1,000 US CLOs and repacks with a balance of over $400 billion and prioritize deals for in-depth review based on performance metrics and automated quantitative analysis.•Surveillance and analyze prioritized CLOs based on performance data and discussion with collateral managers, present memos and rating recommendations to rating committee and release rating actions.

US RMBS, including Prime, Non-prime, Re-performing, Non-performing, Reverse mortgage, HECM, CRT, GSE US ABS, including Student loan (FEELP, Private), Auto Lease, Dealer floorplan, PACE, Aircraft, Container- Provide loss/default/prepayment credit analysis, simulate various prepayment, default (curves), severity and servicing scenarios, build and tie-out cashflow models for both new issuances and surveillance transactions- Examine transaction document and performance reports, update for periodic review- Advise on rating committees and issuer calls, illustrate structural mechanisms and derive loss projections- Evaluate consistency and appropriateness of methodologies applied in rating modelsCLO- Collaborate with CLO rating team on rating model update projects, such as industry re-classification, review and update the appropriate adjustment for rating watchlists and outlooks- Collaborate with CLO rating team on aggregator/binomial/matrix tools to generate inputs(Diversity Score, WAS,WAC,WAL, WARR) to feed into CDOEdge or analyze outputs from CDOEdge- Collaborate with tech on the update of CDOEdge, provide support to structured credits team

• Conducted independent model replication for European/APEC counties RMBS loan loss/default models, European RMBS cashflow models, European surveillance models, reviewed model assumption to ensure consistency with rating criteria and verified model accuracy• Validated Fitch’s new Public Finance Revenue Scenario Generation Tool by conducting model replication, reviewed model methodologies and the model results• Conducted scenario and sensitivity analysis that tests collateral and waterfall structure's performance under different stresses• Presented review findings to committees and evaluated potential impact on rating

• Maintained and updated information for Loan Pricing Model; generated and updated different assumption rates applied in the pricing model (such as CDR curve, CPR curve, Survival curves, HPI index, various insurance cost, repair cost, etc.); performed statistical analysis on different modules within the pricing model; performed sensitivity analysis on various scenarios; ran pricing model for our loan trader on acquisition business and other purposes (such as mark to market value for accounting department, foreclosure value for loan servicing department, etc.); collected and prepared data for all above analyses by using SQL• Valuated mortgage service rights for acquisition business; converted tapes and ran through the residential servicing right pricing model; prepared settlement pricing sheets for existing servicing rights by using CAS and Excel. • Updated database for all securities every month; developed and prepared monthly reports and presentations to support our legacy securitization business; maintained database for collateral assets; automated data maintain and update process by VBA; all data are from trustee reports; fulfilled rating agencies’ requests regarding our mortgage structured products.

Economics Research, Assistant Vice PresidentDeveloped fair value credit spread models for US high grade, US high yield, European high grade, European high yield and emerging market sovereign bond; all models were built in both multivariable linear regression and times series ARIMA model; macroeconomic data and financial market data were used as model inputs to determine the fair value spreads on above products against current market level; generated trading signal based on the differences between model value and market value; back-tested all models by series statistic tests, such as Durbin-Watson test, Multi-collinearity test and stability test;all of the above models were developed by using SPSSDeveloped US swap spread fair value models by applying multivariable linear regression methodology to support credit market viewsPerformed special projects, such as: developed Recession Model by applying Probit analysis to estimate recession probability to monitor macro-economic environment; revaluated and improved in-house Global Risk Index model, replaced and modified some less relevant inputs to make it better reflect current market movementBuilt and maintained databases, updated all the above models and prepared monthly reports; adjusted those models based on the market movements, especially after the credit crisis, i.e. incorporated time series model such as autoregressive (AR) models; provided trading ideas to Global Investment Committee(GIC) based on the trading signals generated by those spread modelsContributed to the commentary of the credit sector and emerging markets for Citi’s internal publications; met clients and internal professionals on strategy and model related issues.

Regularly interviewed economists, market strategists and traders to confirm and add to daily market commentary (sources include NYSE traders ,Bloomberg, Lehman Brothers Chief Economist, S&P Chief Investment Strategist, S&P Chief Economist, portfolio managers/analysts)Improved integrity of news reports through independent verification of sources and personally conducting financial statement analysis, industry research and review of relevant market data such as options, currencies and commodities.