PROFESSIONAL SUMMARY:

• Financial Analytics Professional with over five years of experience in quantitative analysis and research, fundamental research and analysis, data mining, aggregation and validation, model development, scoring and validation of predictive models including financial time series models using SAS, Python, R and Matlab statistical computing software.

Predictive Model and Data Mining Analysis

• Utilized advanced supervised and unsupervised learning methods of machine learning algorithm, SAS, SPSS Clementine, segmentation, statistical techniques like k - means clustering analysis, logistic regression, customer life time value model, and principal component analysis (PCA), regression or classification of feature vectors using SAS and R statistical computing environment;
• Built classifier for feature vector through data extraction, model development, validation, and scoring of predictive models. Conducted coding of qualitative variables and manipulation, complex hypothesis testing and statistical analysis through various statistical methodologies like experimental designs (ANOVA, ANCOVA), MANOVA, discriminant and factor analysis and statistical inferences in SAS, R and SPSS computing environment.
• Doing pricing and product research on Web and in-store pricing sensitivity analysis, ROI, product preference; Worked on marketing basket and product preference, such as store layout, product placement, association analysis.
• Customer behavior analysis - Study the underlying stochastic process of customer shopping behavior; derive models for RFM (two queries to calculate RFM), life-time value, migration and other customer centric measures
• Perceptual Mapping and Brand Position - Research and develop software for perceptual mapping; Apply model to analyze market shares and brand positions for financial, pharmaceutical, and healthcare companies;

Quantitative Modeling and Analysis

• Pricing of derivatives and like call options, put-options, swaptions, etc. through various financial engineering techniques like Black-Scholes model, volatility estimation, etc.
• Performed Markov-Chain Monte-Carlo (MCMC) simulations of stock price volatilities and general Monte-Carlo simulation for density estimation and bootstrapping of parameters of financial time series models.
• Constructed optimal portfolio to maximize returns or minimize unsystematic or diversified risk either based on Markowitz Portfolio Optimization Theory, Mean-Variance Optimization Theory (MVO), Arbitrage Portfolio Theory (APT), and Capital Asset Pricing Model (CAPM).
• Performed complex pattern recognition of financial time series data and forecast of returns through the AR and ARIMA models, exponential smoothening; estimation of volatilities of stock returns through the ARCH and GARCH models;
• Deeply understanding risk modeling processes including asset allocation, portfolio construction and optimization, estimation of Value-at-Risk (VaR) and Expected Shortfall (ES); corporate risk management through various optimal hedging strategies and simulation of interest rate models.
• Built credit risk PD/LGD models - Structural credit risk model (template) and statistical credit risk models (regression/logistic regression analysis); Risk Attribution and Performance Analytics - Equity performance attribution analysis for mutual funds, VaR, and quantitative risk report

Fundamental Research and Financial Analysis

• Covered 15+ companies on internet & media space; Analyzed the companies’ SEC filings and other financial data.
• Constructed the complex financial models (Wall Street stochastic models), DCF model, EV/Sales, EV/EBITDA, P/E; sensitivity valuation for WACC and growth rate.
• Provided investment recommendations based on our research. Participated in the world largest IPO, and helped the firm be one of the underwriters of the Alibaba IPO.
• Prepared balance sheet, income statement and statement of cash flows and interpreted these financial statements through various accounting ratios of liquidity ratios, financial leverage/gearing ratios, solvency ratios, asset turnover and profitability ratios. Capital investment appraisals through Net Present Value(NPV), Profitability Ratio, Present Value(PV), Weighted Average Cost of Capital(WACC), Internal Rate of Returns (IRR). Experience in performing GAP analysis and SWOT analysis.
• Built Asset liability model (ALM) using CIR term structure model to analysis asset, liability, and investment strategy for general account management

TECHNICAL SKILLS:

Modeling Tools: SAS, MS Excel, R, SPSS, Matlab, UML, MS Visio

Software: MS Word, PowerPoint, Outlook, Visio, Bloomberg, FactSet, SAP, ABUCUS Analyzer

Operating System: Windows, Mac OS, Unix, VirtualBox

Database: MySQL, SOL Server, MS Access

Programming Language: SAS, R - Statistics, Python, Matlab, C++

Computational/Modeling Tools: Advance Excel (Pivot table, vlook-up, conditional formatting, data analysis, etc) Macros & VBA, and Tableau

PROFESSIONAL EXPERIENCE:

Confidential, NEW YORK, NY

Credit Risk Analyst

• Carrying out raw clients’ credit history data extraction from internal Teradata database by SQL PASS THROUGH FACILITY and LIBNAME.
• Summarizing raw dataset and performing data parsing using DATA step, PROC SQL, PROC SUMMARY, PROC FORMAT, PROC TRANSPOSE, PROC MEAN, PROC CONTENTS, PROC FREQ, PROC SORT and macro in SAS.
• Randomly sub setting a sample dataset to build the logistic regression model. Applying PROC LOGISTIC to create a logistic regression for identifying which characteristics can influence on probability of default (PD).
• Utilizing automatic stepwise procedure to develop the logistic regression analysis from the strongest candidate predictor to weakest predictor.
• Analyzing Akaike information criteria (AIC) and Schwarz criterion (SC) to determine which variable can influence the probability of default (PD) most.
• Conducting the back test with some unselected records to identified type I and type II error and reported the results by PROC TABLATE.
• Plotting frequency distributions of predicted probability of loan default histogram with 0.5 cut points by PROC GRAPH.
• Estimating new clients’ expected loss (EL) with the probability of default calculated by the logistic regression and giving loss given default (LGD) and exposure at default (EAD).
• Summarizing the result and report to senior manager by PROC REPORT, PROC FORMAT, PROC TABULATE and SAS ODS.

Environment: Windows, Unix, SAS9.3, logistic regression, credit risk, probability of default (PD), loss given default (LGD), exposure at default (EAD), SAS/Macro, SAS/GRAPH, SAS/ODS, SAS/SQL, SAS/STAT, ad-hoc report, Teradata

Equity Research Associate - Internet & Media

• Worked directly with Senior Analyst (Victor Anthony) in constructing, maintaining financial models and supporting with writing Initiation Reports, Earnings Notes and Industry Segment Notes for distribution to the sales force and both institutional and retail clients.
• Analyzed SEC filings, 10-K, 10-Q, 8-K, etc. and other financial data for covered Companies, expanding the coverage from 12 to 16, including the new initiation of Twitter, LinkedIn, Alibaba, Pandora. Additionally, coverage companies also include: Google, Facebook, Twitter, Amazon, Yahoo, LinkedIn, eBay, AOL, InterActive Corp, HSN, Liberty Interactive, Bankrate, Shutterfly, and Vistaprint.
• Updated the financial key data, researched on auto-relationship, management, board and directors, and competitors’ information. Analyzed Internet & Media sector market data to assess and describe current and long term trends. Attended industry keynote, company conference calls, events, and follow up with company Investor Relationships, market news, and sell side analysts.
• Developed SAS programs using SAS BASE, SAS SQL, SAS STAT, SAS ACCESS and SAS MACROS, etc for statistical analysis and data displays.
• Conducted financial statement analysis using relevant historical information to create detailed operational and financial projections for internet & media companies, applying and evaluating the main valuation methodologies (EV/Sales, EV/EBITDA, P/E, and Price/Levered FCF/Share) to analyze covered stocks within the internet & media industry sector.
• Provided investment recommendations for our clients and brokers based on earnings projections, valuation, risk assessment of individual company, and the whole industry development condition.

Environment: Windows, SAS9.3, Bloomberg, FactSet, logistic regression, Excel, Outlook, PowerPoint, SAS/Macro, SAS/GRAPH, SAS/STAT, StreetAccount, Briefing Investor, IPREO BD Corporate.

Quantitative Risk Analyst

• Described the raw data set by PROC CONTENTS, PROC SUMMARY, and PROC MEANS and identified missing data and data anomalies with PROC FREQ. Used SAS procedures such as Proc Freq, Proc Format, Proc Means, Proc sort, Proc Print, Proc tabulate and Proc report.
• Performed advanced data mining and aggregation; and statistical analysis in support of the creation and maintenance of statistical or predictive models. This involved data extraction on the returns of high performing stocks from Bloomberg, Yahoo finance, model development, scoring and validation. Also upgraded and incorporated data and observations into existing models to improve its predictive power.
• Computed Value-at-Risk (VaR) and conditional VaR (expected shortfall) of clients’ portfolio investments and recommended effective hedging strategy to insulate the positions taking by the clients.
• Wrote and executed complex SQL scripts on ODBC and other SQL server database to extract data on terabyte and petabyte scale for analysis, modeling and testing.
• Utilized complex statistical methodologies like dynamic time warping to identify trends in about forty-five (45) different financial time series of stocks traded on the NYSE and also used principal and independent component analysis to select a minimal number of those stocks i.e ten (10) stocks which explains most of the variations in the returns of the portfolio investment. This principal component (or selected stocks) had a mean total return of about $146 million and standard deviation or risk about $22 million.
• Carried out capital investment appraisals of proposed clients’ investment through Internal Rate of Return (IRR), Minimum Internal Rate of Return (MIRR), Net Present Value (NPV) and Profitability Index (PI) with MS Excel functions on capital investment appraisals. Also computed the Weighted Average of Cost of Capital (WACC) and return on investment through the CAPM and dividend models. Projections were recommended to be executed where the cost of capital given by the WACC is less than the return on investment and vice versa.
• Undertook forecast of returns on high performing stocks and equities through the AR and ARIMA models of financial time series using SAS statistical computing environment.
• Interacted closely with source vendors to collect the data to develop fair value recommendations.

Environment: Windows, SAS9.3, SAS Enterprise Guide, SAS/Macro, SAS/GRAPH, SAS/STAT, SAS/SQL, SAS/ODS, logistic regression, Excel, Word and Outlook.

Financial Analyst, LBU Division

• Performed product data analysis, and defined and collected business requirements in collaboration with business partners for Asset Services.
• Supported LBU Controller in all areas related to financial reporting and controlling. Created VBA based Financial Reporting Package in excel which automates Monthly Metrics Report data importing, presenting and graphing.
• Performed monthly report, OR&HC report, account analysis, provision assessment and related action follow-up.
• Reviewed the SAP and Abacus financial results to ensure an accurate closing and reporting. Prepared the management review package including order, revenue, OBL, GM, SG&A, EBIT, NWC, OCF, HC, etc.
• Consolidated and provided annual budgeting, rolling forecasting, and service reports (monthly key data, global market report).
• Updated consolidated Operational EBITDA Bridge, statistic monthly overdue condition. Analyzed the third party companies’ financial statements and credit rating. Exported and built a pivot tables comparing between channels, sales churning rate by year to check external competition by PROC FORMAT, PROC SQL, PROC SORT, macro and SAS ODS.

Environment: Windows, SAS9.3, Bloomberg, Excel, SAS/Macro, SAS/GRAPH, SAS/STAT, Word, PowerPoint, Outlook, ABUCUS Analyzer.