Quantitative Equity Researcher

RU SHENG

646-***-**** **.*****@*****.***

SUMMARY

** ***** ** ********* ** linear/logistic regression, time series analysis, Bayesian analysis, hypothesis testing, model validation, stochastics filtering, machine learning, portfolio optimization,

10 years of advanced experience in Monte Carlo simulation of complex processes and parameter determination

7 years of experience in statistical modeling for asset pricing, risk assessing, and trading strategy designing

3 years extensive practical investment experience covering a range of asset classes and strategies

Highly proficient with MATLAB, R, SAS, SQL. FACTSET, BLOOMBERG; working knowledge of PYTHON PROFESSION EXPERIENCES

PRINCIPAL GLOBAL INVESTORS (over $331 billion in AUM), Des Moines, IA Quantitative Equity Researcher, June 2015 to present A. Quantitative equity research with Bayesian statistical method

Independently conducted researches on Bayesian statistical approaches to company’s core model, Global Research Platform (GRP) by correcting the over-fitting problem and improving out-of-sample performance

Performed back-tests on alpha factors with in-sample and out-of-sample data under Bayesian Statistical framework, providing more robust estimations and more accurate predictions on factors

Constructed a Bayesian portfolio selection model and obtained more stable, less biased and better out-of-sample performance optimal portfolios

Trained portfolio managers and analysts for Bayesian statistics through a series of research seminars B. Environmental, Social and Governance (ESG) research

Performed ESG research on stock selection including MSCI’s ESG ratings, Northern Trust’s Quality Scores, Empirical Research Partners ESG Scores, etc.

Constructed a stock selection strategy by integrating ESG score with GRP model, outperforming strategies focusing only on either score

Co-designed the investment strategy of “PGI Women Impact Fund” and presented to clients, raising a $300M fund in July, 2015

Presented a research paper “Women, Leadership and sustainability” in Women in Asset Management Conference 2015 and received the Spot Award

C. ETF construction

Created a strategy on ETF construction based on Women Leader Impacts which will be launched in spring 2016

Independently conducted the research on building the ownership ETF and reported to Chief Investment Officer

(CIO). This ETF will be launched in 2016

Back-tested and developed a strategy on an ETF with focus on Chinese consumer based ADRs D. Other statistical practice on quantitative equity research

Replaced the existing statistical methods of back-tests portfolios and multi-factor models using FACTSET and EXCEL by IBM NETEZZA and R to reduce computational speed

Developed risk analytics on “PGI Risk Model” (using IBM NETEZZA and R) to assist portfolio managers to monitor and evaluate portfolio performance and model validation

Performed a statistical analysis of trading strategy comparison to seek an alternative trading strategy which can generate higher alphas

Created statistical reports on timing and regional analysis on trading transactions

Conducted two researches on supply chain analysis and related innovation measurements UBS SECURITIES CO., LTD, Beijing, China

Quantitative Equity Research analyst/Trading strategist, 2001-2003

Developed China equity long only trading strategies through hands-on quantitative research; established vendor relationships including prime brokers, traders, and data providers; liaised with operations in implementing the trading strategy

Co-designed a dynamic asset allocation model investing in mutual funds; studied the performance of equity, fixed income, and alternative assets (macro, thematic, alpha, and market hedge) across different stages of business cycles and allocate assets accordingly; researched on economic indicators of business cycles; used optimization and statistical analysis for model constructions

Performed top-down fundamental value analysis of companies in portfolios by formulating industry outlook, building and maintaining cash flow analysis models and presenting recommendations to portfolio managers

Managed stocks trading for twenty-three small size accounts ($2.5M ~ 7M for each account); total value of equity traded was $300M in three years; executed and controlled all bonds trade flow averaging about $154M per day; total value of bonds traded was about $610M in three years

Conducted transaction repurchase (average $770M per day) in the money market, which raised re-investment efficiency of cash and reduced financing costs

OTHER EXPERIENCES

UNIVERSITY OF CONNECTICUT, Storrs, CT

Graduate Teaching Assistant and Researching Assistant, 2010 - 2015 Responsible for independent research and graduate and undergraduate course teaching

Research topics included theoretical and empirical works on asset pricing: cost of capital estimation with a tractable model of term structure, with special attention to the time-varying beta, the market rate premium and the risk free rate; derivative pricing using a four-moment likelihood function, extending the Black-Scholes model with non-normality assumption; portfolio evaluation based on a Bayesian estimator of the Sharpe ratio by using Gibbs-sampling simulation model, accounting for small sample size

Taught senior undergraduate course on Financial Management MARQUETTE UNIVERSITY, Milwaukee, WI

Lecturer in Statistics, 2009-2010; Graduate Teaching Assistant and Researching Assistant, 2003 - 2009 Responsible for independent research and undergraduate/graduate course teaching

Research topics included theoretical and empirical work on the multiple testing problems with asymmetric high dimensional data, Bayesian decision hypothesis testing model proposing a novel directional false discovery rate, and small-sample analysis under Bayesian framework

Taught three courses in statistics including Time Series Analysis (graduate level), Mathematical Statistics

(graduate level), and Modern Elementary Statistics (undergraduate level) ACHIEVEMENTS

Financial Practice

Estimated the term structure of cost of equity for the insurance industry using a dynamic vector autocorrelation regression model and discount dividend model under a more realistic assumption with time-varying parameters and proved that the standard expected returns model overestimate the expected returns across all maturities

Developed a Markov Chain Monte Carlo (MCMC) model with a risk-neutral density to forecast option prices that significantly outperform the Black-Scholes model by loosening the restricted log-normal assumption using higher moments of skewness and kurtosis

Forecasted bond returns using a factor of a linear combination of forward rates, interpolating the missing bond yields with a six-parameter function by minimizing the squared-errors.

Generated a leading indicator based on a dynamic model with an innovative four-moment implied risk-neutral density under Bayesian framework to clearly signal the equity market inflection with a significant predicting capability

Constructed a Bayesian estimator of the Sharpe Ratio of portfolio returns with small samples, reducing the estimation error (Root Mean Square Error) by 60%

Applied the Kullback-Leibler divergence to portfolio optimization problems, improving the Markowitz’s mean-variance portfolio with optimal shrunk weights and designed an innovative multiple-hypothesis testing on portfolio selection

Built a long-short momentum investment strategy. The foreseeable annual return is 28.92% by testing on the data of U.S. insurance industry

Statistical practice

Innovated a Bayesian decision theoretic methodology to tackle a three decision hypothesis testing problem with skewness alternatives which performs more powerfully than the classical testing approaches

Proposed a new directional false discovery rate incorporating the asymmetric feature in multiple hypothesis testing which significantly detects the singularities in unbalanced distribution ignored by traditional statistical methodology

Developed a general Bayesian framework by specifying a mixture prior structure and a unique loss function related to the Kullback–Leibler divergence which can be implemented into any type of distribution

Derived the truncated moments of the first order statistics for asymmetric distributions which provided a fundamental tool in non-parametric statistics inference EDUCATION

UNIVERSITY OF CONNECTICUT, Storrs, CT

Ph.D. in Finance, 2010 – present, GPA:3.85/4.0

MARQUETTE UNIVERSITY, Milwaukee, WI

Ph.D. in Statistics, 2009, GPA:3.98/4.0, GRE: 2300/2400 Dissertation: A Bayesian Analysis of Hypothesis Testing Problems with Skewed Alternatives BEIJING NORMAL UNIVERSITY, Beijing, China

B.S., Statistics, 2001, GPA:3.8/4.0

SELECTED PUBLICATIONS (15 total publications)

“The Term Structure of the Cost of Equity for Insurance Companies”, Eastern Finance Association Conference, New Orland, April, 2015.

“Bayesian Analysis of Hypothesis Testing Problems for General Population: A Kullback–Leibler Alternative”, Journal of Statistical Planning and Inference, Vol. 142, Issue 7, Pages 1991–1998, (2012).

“Bayesian Decision Theoretic Approach to Hypotheses Problems with Skewed Alternatives”, Journal of Statistical Planning and Inference, Vol. 140, Issue 10, Pages 2894-2903, (2010).

“Characterizations of Certain Continuous Univariate Distributions Based on Truncated Moment of The First Order Statistics.” Aligarh Journal of Statistics, Vol. 28, (2008). PROFESSIONAL DESIGNATIONS

Member of the American Statistics Association

Member of the American Finance Association

COMPUTER SKILLS

Database: FACTSET, BLOOMBERG, STARMINE, IBM NETEZZA, COMPUSTAT, CRSP, DATASTREAM

Programming Languages: R, MATLAB, SAS, SQL, PYTHON

General Tools: EXCEL, ACCESS, MSWORD, POWERPOINT

Statistical Software: R, SAS, WINBUGS, SPSS, STATA

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