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Fixed Income Big Data

Location:
New York, NY
Posted:
October 20, 2023

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Resume:

ad0iqx@r.postjobfree.com (***) NANYU ***-**** www.JIANG linkedin.com/in/nanyu-jiang

EDUCATION

NEW YORK UNIVERSITY, TANDON SCHOOL OF ENGINEERING Brooklyn, NY Master of Science in Financial Engineering Expected 05/24 GPA: 3.9/4.0

XI’AN JIAOTONG UNIVERSITY Xi’an, CN

Bachelor of Science in Mathematics and Applied Mathematics 07/22 GPA: 88/100

(Double Degree) Bachelor of Economics in Financial Engineering (China Construction Bank Fin-tech Elite Class) PROGRAMMING / TECHNICAL SKILLS / CERTIFICATIONS

• Skills: Python, MATLAB, C/C++, C#, R, SQL, LaTeX, Plotly

• Certification: CFA Level 1 & 2

COURSEWORK HIGHLIGHTS

• Mathematics & Statistics: Option Pricing & Stochastic Calculus, Quantitative Methods in Finance, Probability, Statistics

• Programming: C++ for Financial Engineering, Data Analysis and Statistical Software(R), Database Knowledge and Application

• Finance and Economics: Algorithmic Portfolio Mgt., Fixed Income Quant Trading, Fixed Income Securities & IR Derivatives

• Expected (Fall 2023): Econometrics and Time Series Analysis, Quantitative Equity Trading, Financial Analytics & Big Data EXPERIENCE

ORIENT Trading System SECURITIES, R&D Department, Shanghai, Strategy CN Research Intern 06/23 -08/23

• Researched on FX implied volatility surface and constructed polynomial, cubic spline, SVI, SABR, Wing models with Python.

• Assessed the surfaces’ no-arbitrage property and built local volatility surface to support Heston-LSV model construction. GF SECURITIES, Guangzhou, CN

Derivatives Brokerage Business Department, Quantitative Intern 07/21 - 08/21

• Constructed trading signals and designed timing strategies based on combined technical indicators, backtested with Python.

• Priced barrier options with Monte Carlo methods using Python, and conducted sensitivity analysis. RESEARCH & ACADEMIC PROJECTS

NEW YORK UNIVERSITY, NY

Reinforcement Learning in Quantitative Wealth and Investment Management, capstone project with BOA

• Designed Hierarchical Deep Reinforcement Learning model based on PPO, A2C, GRU and self-attention to construct goal-based investing portfolios, realizing assets selection and rebalancing functions. 05/23 - 08/23

XI’AN JIAOTONG UNIVERSITY, Xi’an, CN

Deep Learning of Active Galactic Nucleus Feedback Simulation Data, A+ graduate design 10/21 - 06/22

• Constructed LSTM model and self-attention based CNN model to make multi-step forecast of time-series data, using Pytorch.

• Built auto-encoder based model to realize spatial time-series features dimension reduction and feature extraction. Dynamic Relationship between China’s Futures and Equity Index and Network Analysis based Pair Trading Strategy 03/22 - 05/22

• Designed important futures discovery index with LeaderRank algorithm, constructed and analyzed co-movement networks of China’s futures and equity index with coarse granularity method, using NetworkX and Gephi.

• Designed trading algorithms based on pair trading strategy and former research, and backtested with Python. Machine Learning-based green assessment of listed companies, Research Program of Fin-tech 10/21 – 01/22

• Learned about ESG criteria, applied feature engineering with Python and formulated China-specific indicators.

• Developed models to assess greenness of China’s listed company, based on random forest, decision tree, logistic regression, and green scorecard model. HONORS / AWARDS / COMPETITIONS

• Honor Title of Outstanding Graduate, Student & Scholarship, Xi’an Jiaotong University, 2019-2022

• China Construction Bank Scholarship, 2nd/30 in CCB Fin-tech Elite Class, 2022

• Meritorious Winner (10%), Mathematical Contest in Modeling/Interdisciplinary Contest In Modeling, 2022 EXTRACURRICULAR ACTIVITIES

• New York University, Course Assistant, Fixed Income Securities and Interest Rate Derivatives (FRE-6411), 2023 Fall

• Bulls & Bears Club, Quant Research department, quantitative strategies design, 2022

• Microsoft Student Club, Vice Chairman, organized club activities and hold weekly technical sessions, 2019-2020



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