Shuwan (Stella) Wang Email and Phone Number
Shuwan (Stella) Wang work email
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Shuwan (Stella) Wang personal email
Shuwan (Stella) Wang is a Goldman Sachs Analyst (SEC strats) | CMU Computational Finance Master at BlackRock. They is proficient in English.
Blackrock
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- blackrock.com
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AssociateBlackrock Aug 2022 - PresentNew York, Ny, UsInvestment research analyst at Multi Asset Strategies & Solutions
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Eqs Structuring & Sales StratsGoldman Sachs May 2021 - Aug 2022New York, New York, Us• Thematic Equity Baskets: Kept a keen sense of market by tracking news; created one-delta thematic equity baskets that offer exposure to macro drivers not targeted by traditional indices • Portfolio Construction: Helped clients identify factor risk exposure and proposed customized hedging solution • Analytics: Generated scalable contents by running various earnings and valuation analytics on baskets; developed infrastructure to lower basket volatility by 3-4v while keeping reactivity Communication: Presented thematic and hedging ideas on client calls; published notes on factor rotation, sector and market themes -
Summer Analyst, Ficc Divisional Strats And Equities Sts StratsGoldman Sachs Feb 2020 - Apr 2021New York, New York, Us• Implemented pricing adjustment model for structured products by comparing street-averaged volatility and forward with internal data• Calculated hedging costs based on volatility pricing parameters, calibrated dynamic market-linked volatility pricing parameters according to liquidity-weighted bid-offer spread, extrapolated long-dated parameters• Automated new structured products for primary trading on internal platform; enabled auto-quoting and execution for third-party issued buffered levered note; raised issuance automation rate to over 90%
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Summer Analyst, Ficc Divisional Strats And Equities Systematic Trading Strategies (Sts) StratsGoldman Sachs May 2019 - Aug 2019New York, New York, UsHedging portfolio optimization, index update.
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Quantitative ResearcherHz Investment Jan 2018 - Apr 2018• Screened alpha factors based on Information Coefficient, developed the strategy to predict the stock’s fluctuations by random forest, SVC and Xgboost based on selected factors. Back tested data from 01/2014 to 01/2017, found that Xgboost was the fastest and obtained a successful rate of 0.57• Trained cross-sectional data by Xgboost; run single-factor testing of new factor constructed by weighted predicted value of cross-sectional model. Back tested data from 01/2017 to 01/2018, obtained 14.2% annualized excess return
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Research AssistantColumbia University In The City Of New York Apr 2017 - Feb 2018New York, Ny, Us• Analyzed characteristics of volatility, trading volume and abnormal return on 42,927 trading halts; the result shows that both voluntary and mandatory suspension have negative abnormal return and positive abnormal turnover ratio, while voluntary suspension leads to more fierce volatility than mandatory one • Presented at 2017 International Conference on Financial Markets and Institutions (Chengdu) • Submitted the paperto North American Journal of Economics and Finance -
Quantitative Research Intern, Asset Management DepartmentSensegain Asset Management Aug 2017 - Oct 2017New York, Ny, Us• Built a library of fundamental factors, computed factor return, classified factors into three categories based on macroeconomic indicator, designed a factor investment clock, achieved annualized excess return of 4% significantly above the traditional four-factor model• Screened stock analysis factors by Fama-Macbeth, built up stock selection model based on factor ranking, computed score coefficients by optimizing portfolio information ratio, selected top 20% stocks for trading given overall score for each individual stock. Back tested data from 01/2009 to 08/2017, obtained annualized return of 20% significantly above the market performance -
Intern, DerivativesDongxing Securities Ltd Jun 2017 - Jul 2017Cn• Constructed volatility surface using Stochastic Volatility Inspired model and computed interpolated implied volatility for effective hedging• Formulated the strategy to forecast CSI 300 Index Futures change by recurrent neuron network and obtained a successful rate of 0.56 with annualized return of 9.5% -
Intern, Macro StrategyChina Securities Feb 2017 - May 2017Beijing, Cn• Conducted research on industry capital allocation, assessed cycle performance of Fama-French five-factor model and analyzed the relationship between earnings growth of listed companies and GDP growth• Drafted report for a short selling institution; co-established H-share market database for timely tracking -
Quantitative Analyst Intern, Derivative Valuation Center Of FsrmEy Jan 2017 - Feb 2017London, Gb• Applied ratio analysis to value over 30 E&Y rolling hedge methods, conducted sensitivity analysis among 40+ futures and FX forwards to measure their alignment with client data• Created cash flow working paper of an ABS project via VBA; automated statistical analysis of assets pool, calculated cash distribution and secondary yield; ran the stress test of the ABS project
Shuwan (Stella) Wang Education Details
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Carnegie Mellon UniversityMscf -
Renmin University Of ChinaFinance And Applied Math
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The University Of Hong KongBecon & Fin
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Yale UniversityFinance
Frequently Asked Questions about Shuwan (Stella) Wang
What company does Shuwan (Stella) Wang work for?
Shuwan (Stella) Wang works for Blackrock
What is Shuwan (Stella) Wang's role at the current company?
Shuwan (Stella) Wang's current role is Goldman Sachs Analyst (SEC strats) | CMU Computational Finance Master.
What is Shuwan (Stella) Wang's email address?
Shuwan (Stella) Wang's email address is sh****@****chs.com
What schools did Shuwan (Stella) Wang attend?
Shuwan (Stella) Wang attended Carnegie Mellon University, Renmin University Of China, The University Of Hong Kong, Yale University.
Who are Shuwan (Stella) Wang's colleagues?
Shuwan (Stella) Wang's colleagues are Rahul Sethi, Emma Wojcik, Venetsia Krasteva, Banurekha Vaitianadin, Manu Chaudhari, Alexandra Poltarzhitskaya, Alicia De Lorenzo.
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