Robert Xiong, CFA
Cellular: 917-***-****
*** ****** ******* ******: 212-***-****
Westfield, NJ 07090 E-mail: *******@*******.***
Summary:
Work in Citi Cash CDO desk quant group
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Daily interact and support CDO/CLO secondary traders/TRS Desk/Structured
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Credit Oppt. Fund with analytic and valuation tools
Provide CDO drilldown model for ABS CDO super senior valuation
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Implement and improve several key Citi Cash CDO models and valuation
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methodologies include simulation model based on collateral price and Gaussian
Copula
Provide monthly valuation for over 100 deals include CLO/CBO/EM/Trups for
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Citi clients/sales
Be able to provide start-to-finish valuation/pricing /modeling solutions for Cash
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CDO/CLO/RMBS/ABS/Leveraged loans
Strong knowledge in fixed income/structured credit area include modeling and
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deal structures on cash/hybrid/synthetic CDO, RMBS (Sub Prime/Prime/Alt-
A/Pass through), CDS on CDO/ABS, CMBS, Credit Card ABS, ABX, CMBX,
LCDS/LCDX and leveraged bank loans.
Years with Moody’s Investor Service. Familiar with rating methodologies.
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Proficient in using Intex API /Intex Desktop
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In-depth Knowledge on Intex Dealmaker and CMO Modeling language
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Be able to work independently as well as in a team. Possess solid analysis,
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problem solving skill as well as interpersonal skills. Highly motivated.
Familiar with ABS CDO super senior/CLO various tranches valuation
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Solid financial engineering skills
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Solid programming skills include C/C++/Java/Excel VBA
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Columbia EMBA expected 2011
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WORK EXPERIENCE:
Citigroup CDO Desk, NYC 04/2006 present
Rapid Development Team AVP
• Implement CDO drilldown process to calculate CDO write-down depending on relevant
mortgage loans remittance status (from Loan Performance). It involves using RMBS
prepayment model to generate CDR/CPR/Loss severity curves based on HPA scenarios
and underlying mortgage loans delinquency/foreclosure/REO status. It then computes
CDO write-down levels based on RMBS write-down. This method is officially used in
Citi SPG’s ABS CDO super senior valuation and write-down amount calculation.
• Implement Monte-Carlo simulation model for cash CDO based on rating/market price
implied default probability, Gaussian copula for time to default and stochastic recovery
rates.
• Analyze collaterals for CLO/CBO, back out credit risky spreads based on
CDR/CPR/recovery rate/amortization schedule and be able to extend as a CLO
simulation model.
• Provide NAV tools to Citi Structured Credit Opportunity Fund
• Develop NAV calculator for CDO which include collateral market values, IR swaps and
accrued interest. Useful for distressed/EOD/liquidation analysis/monitoring.
• Provide and distribute month-end marks for CLO/CBO equity/combo notes to Citi sales
and clients
• Create CLO/CBO/CLO^2/TRUPS CDO issuer jump-to-default/jump-to-recovery
analytic tools for risk analysis and hedging decision
• Calculate market-value based delta for cash bonds
• Create weekly price/yield matrix for 800 corporate CDO deals
• Create Merton model-based tranche pricer for cash CDO bonds
Work on Citi structured credit quant library
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Work with TRS desk to valuate total return swap on leveraged bank loan portfolio
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Do break-even analysis, WAR/WAC for CDS on CDO.
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Calculate key statistics include delinquency rate, REO/Foreclosure, geography
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concentration from Loan Performance for thousands of subprime, prime and Alt-A deals
Familiar with Citi CDO Structuring tools.
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Familiar with CDS on CDO/ABS calculators
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Familiar with CDO/RMBS/CMBS bond valuation based on Intex
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Familiar with Intex wrapper API and write application to do analysis based on cash flow
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and waterfall structures.
Knowledge on Intex Dealmaker, Desktop and Intex CMO modeling language.
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Reverse-engineering Citi Hybrid/Synthetic ABS CDO deals using Intex Dealmaker based
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on offering circular and Citi structuring tools
Build Intex CDO/RMBS/CMBS/ABS database that includes over 2500 CDO deals with
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data on capital structures, collaterals and amortization schedules.
Calculate CLO warehouse MTM for second loss positions using Merton Model.
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Familiar with bank loans and build loan database (loanX from 2003 and LPC from 2006)
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Implement LCDS MTM methodology based on cash loan spreads.
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Build bond price database include corporate, ABS and MBS from Hamper and TRACE.
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Generate loan ID mappings dynamically between Intex and loanX, Intex and LPC.
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Build up Pari Passu mappings among CDO tranches.
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Work on loan warehouse VaR project to Feds/OCC; calculate three-year risk measures
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using Yield Book, conduct trade prices, market prices and block trade price analysis.
Facilitate and help identify risk breaks among different risk groups and financial control.
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Do regulatory capital calculation for warehouse and syndication based on BASEL I rules
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Familiar with Yield Book user bond approach to calculate risk
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Tools used: Intex, Yield Book, VBA, Oracle, Bloomberg API, Access
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Moody’s Investors Service, Corporate Finance, NYC 04/97 4/2006
Senior Application Developer/Business Analyst
• Implement Moody’s Issuer ratings methodologies based on multi-tier
quantitative and qualitative factors combined with weighting schema to produce
issuer ratings. It covers total of sixty-one industries. The first among
implemented are Pharmaceutical, Gaming, Chemical and Steel.
• Create Moody’s Bank Loan Report, five-B analysis
• Create Moody’s issuer rating graph.
• Implement financial statement private and public adjustments based on GAAP
and IAS standard.
• Design and Implement Financial Reporting System in Visual C++/VBA to
facilitate the process of portfolio comparison, credit risk research and financial
ratios report and financial data.
• Implement FiRST in ASP/VB .Net to integrate corporate finance credit risk
research and projection modeling. It involves financial Statement analysis and
adjustment, industry sector comparison; key indictors based on industry, pro
forma reports.
• Design, Develop & maintain WIRED Intranet to analyze and generate reports on
debt level, issuer level, upgrade/downgrade, rating outlook, issuer rating, market
share, watch list, speculative grade liquidity, industry outlook, global credit
rating front/inside page, new issuance analysis and five-B analysis.
SKILLS
Mathematics: Stochastic Calculus, Statistics, Numerical method, Linear Algebra, Calculus
Finance: CFA level III candidate, Quantitative Finance/Derivative theory, Credit
Derivative/Fixed income theory/product/application/modeling
C/C++, VB/Excel VBA/VC++, Java/J2EE, ASP .Net, VB .Net,
Language:
Sybase, Oracle 9, SQL Server, Access
Database:
Intex, Bloomberg, YieldBook
Tools:
Education:
Columbia University, NY
EMBA Expected 2011
1997
Wesleyan University, CT
Computer Science, MS
Tsinghua University, Beijing, China 1990
Computer Science, BS
VISA Status: US permanent resident