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Analyst, MSc in FE, Python, C++, SQL

Brooklyn, New York, United States
March 10, 2019

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Zeyu Lu 929-***-****


NEW YORK UNIVERSITY, TANDON SCHOOL OF ENGINEERING Brooklyn, US Master of Science in Financial Engineering Expected: May/2019 GPA: 3.8

SHANDONG UNIVERSITY, SCHOOL OF MATHEMATICS Jinan, China Bachelor of Science in Statistics June/2017

GPA: 4.2/5.0


Python(4yrs+), C++, Excel, Latex

CFA level II candidate


Mathematics: Real Analysis, Partial Differential Equation, Functional Analysis, Real Variable Functions, Complex Variable Functions Stochastic Processes, Mathematical Statistics, Time Series Analysis, Probability Theory,

Finances: Quantitative methods in Finance, Option Pricing&Stochastic Calculus, Financial Computing, Machine learning in Finance. Active Portfolio management, Risk Management EXPERIENCE


Analyst Intern, Information Session 07/2016 – 09/2016

Assisted the investigation and analysis of epidemics and frequently-occurring diseases (example: FMD virus and influenza), built Linear regression model by applying Least Squares Fitting Method. NATIONAL BUREAU OF STATISTICS Jinan, China

Research Assistant, Survey Office in Shandong 04/2016 – 07/2016

Collected and processed raw data by Python and Excel, cooperate with other interns to build linear regression model in order to analyze the price trend of market product and successfully helped local government allocate resources to stabilize the prices of necessities.


Predicting stock market trend with Back Propagation Neural Network model Brooklyn, US

Applying sliding window method to preprocess raw data, different technical indicators are calculated to capture the features of market. Using keras to finally build the BPNN model .

Genetic algorithm is applied to avoid local minimum, in order to enhance the performance, got a hit ratio around 0.7. Evaluating the impact of earning report on stock price Brooklyn, US

Used C++ libcurl to retrieve stock prices from Yahoo finance, calculating groups’ AAR and CAAR based on market portfolios’ return(SPY) by Bootstrap method.

Gnuplot is used to plot figures to show the conclusion, replicating the whole project by Python to compare efficiency. Analyzing the connection between the characteristics of financial company and its profits Jinan, China

Collected data for 30 financial companies from Internet and then use stepwise regression to choose variables.

Utilized SPSS to build statistical model, try to analyze the influence of different characteristics of company for its profit rate, including financial leverage, asset structure, fixed investment ratio, and the company size. Optimal Single Asset Trading Path(Coursework) Brooklyn, US

Based on Arrow Pratt approximation to maximize expected utility of terminal wealth of a multiperiod asset. Potential cost due to liquidation is included to simulate real market environment.

Used Python to iterate over trades on asset holding path to find the global maximum by applying Blockwise Coordinate Descent Algo and Tseng’s (2001) theorem, plot the expected profits and ex-ante Sharpe ratio to show the parameter’s effect. Linear Arbitrage Pricing Theory Model(Coursework)

Optimizing unconstrained Markowitz portfolio trading trace based on multiple factors and Arbitrage Pricing Theory, calculate alpha factor by using OLS and WLS method, compare the difference with market alpha factors.

Decomposition risk in portfolio due to alpha factors, non alpha factors and idiosyncratic variance. ACTIVITIES

2018 15th Rotman International Trading Competition Toronto,Canada

Flow Traders ETF Case 2/52 managing a ETF portfolio in highly simulated market environment, dealing with unexpected incidents, to compete with other 51 teams to earn the highest profit.

Schonfeld Algorithmic Trading Case 5/52 building automatic trading system, applying momentum strategy to trade several assets(FX, stocks) in simulated environment to earn the highest profit.

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