DIYANG YU

adcjyw@r.postjobfree.com 443-***-**** https://www.linkedin.com/in/diyang-yu/

EDUCATION

NEW YORK UNIVERSITY, TANDON SCHOOL OF ENGINEERING Brooklyn, NY Master of Science in Financial Engineering, GPA: 3.71/4.0 05/2019 ST. OLAF COLLEGE Northfield, MN

Bachelor of Arts in Mathematics and Computer Science, Statistics Concentration, GPA: 3.71/4.0 05/2019 CERTIFICATIONS

• Skills: Python, C/C++, R, SQL, Excel VBA, Mathematica, Prolog, LaTex, Wind

• Certifications: CFA Level III Candidate, FRM Level II Candidate, Bloomberg Certified COURSEWORK HIGHLIGHTS

• Computer Science: C++ Lab, Algorithms and Data Structures, Parallel and Distributed Computing, Machine Learning

• Statistics: Statistical Modeling, Statistical Theory, Probability Theory, Econometrics and Time Series

• Mathematics: Linear Algebra, Multivariable Calculus, Real Analysis, Algorithms for Decision Making, Stochastic Calculus

• Finance: Risk Management and Asset Pricing, Quantitative Portfolio Management, Asset-Backed Security, Market Risk Analysis EXPERIENCE

PEGASUS TECH VENTURES San Jose, CA

Analyst 09/2019 - Present

• Conduct due diligence by collecting and analyzing market data, interpreting financial statements, and diving deep into competitor landscape; draft 2 reports and present to the investment committee on a weekly basis

• Extract quantitative and qualitative market data from targeted market segments to forecast the market size, trends, and consumer behavior; generate a dashboard to support the investment team’s decision making

• Review and analyze legal documents including contracts and agreements; highlight key issues and risks to the finance and operation business; negotiate and revise non-disclosure agreement and term sheets with startups and other third parties WIND INFORMATION New York, NY

Analyst Intern 06/2018 - 12/2018

• Independently developed efficient Pandas programs to parse trade information from binary files (800 million data inputs) and output all 7000+ stocks’ volume-weighted average prices at every trading second (Python)

• Performed a momentum strategy on both Chinese and US stock markets, and improved the model with lagged bear-market indicators; yielded a return of 289% in 10 years, which outperform the S&P 500 by 50% (Python)

• Composed biweekly reports on various technology industry chains (ie. 5G) through independent market research for 200+ clients CITIC CLSA Shanghai, China

Research Analyst Intern 06/2017 - 08/2017

• Conducted independent market analysis for real estate investments and calculated IRR, NPV, and payback period for each project to identify 3 most valuable investment opportunities

• Assisted in the production of market briefings on residential and commercial markets by processing raw real estate data and by analyzing industry-related news’ implications on covered companies ACADEMIC PROJECTS

Risk and Portfolio Management (Python) 08/2018

• Constructed a portfolio with 3 asset classes and 10 instruments and improved its performance by 37.3%

• Identified risk drivers and invariants, and modeled their distributions by fitting GARCH models

• Projected risk drivers using Monte Carlo simulation to model the portfolio’s P&L, calculated efficient frontier via mean-variance approach and allocated assets by maximizing expected utility to optimize the portfolio’s performance Machine Learning (Python)

05/2018

• Designed, implemented, and evaluated machine learning algorithms such as Decision Trees, Random Forest and SVM to determine the best algorithm when predicting future stock trends, ranging from 0.1 to 30 seconds

• Led a team of 4 to process raw data, aggregate the results into the same format, graph each algorithm’s accuracy rate and found that Random Forest worked best when predicting future trends from 0.5 to 5 seconds with an accuracy of 90% Big Data (Weather Prediction and Sentiment Analysis in Python and R) 04/2017 - 05/2017

• Extracted features including humidity, temperature, and wind speed using Principal Component Analysis

• Trained a Bayesian network and a Hidden Markov Model and predicted the weather, location, and attendance of graduation ceremony using data from past 10 years with over 70% accuracy

• Implemented sentiment analysis by collecting millions of Donald Trump, Barack Obama and Hillary Clinton’s tweets; analyzed their attitudes and tones in social media by comparing with sentiment lexicons and rating each word EXTRACURRICULAR ACTIVITIES

• Co-chair, Chinese Culture Club, St. Olaf College 05/2015 - 05/2017

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