VY VIVIAN (JINGCHENG) YU
PH.D. CANDIDATE · ACTUARIAL SCIENCE · UNIVERSITY OF WATERLOO

Vivian (Jingcheng) Yu

Research in Submodular Risk Measures
FSA CERA CFA LEVEL II CANDIDATE
01 — PROFILE

About Me

Portrait of Vivian Yu

I am a Ph.D. Candidate in Actuarial Science at the University of Waterloo, specializing in the intersection of financial stability, risk management, and theoretical mathematics. My research focuses on quantitative risk management and stochastic optimization, developing robust frameworks that bridge abstract mathematical theory with data-driven market applications.

With a Master of Financial Engineering from UCLA and professional experience at Ernst & Young and the California Department of Insurance, I combine rigorous academic discipline with industry-grade problem solving.

Education

University of Waterloo

Ph.D. in Actuarial Science | 2024 – Present

UCLA

Master of Financial Engineering | 2022

GPA 3.82 / 4.0

University of Manitoba

B.S. Actuarial Mathematics | 2019

First Class Honor

Credentials

  • FSA (Fellow of the Society of Actuaries)
  • CERA (Chartered Enterprise Risk Analyst)
  • CFA Level II Candidate

Technical Skills

Python R (Tidyverse) SQL TensorFlow Stochastic Calculus
02 — CAREER

Professional Experience

2024 – PRESENT | WATERLOO, ON

University of Waterloo — Teaching Assistant

Lead tutorials for undergraduate actuarial students, translating complex mathematical and risk-management theory into accessible, engaging concepts, with personalized mentorship during office hours.

2023 | NEW YORK

Ernst & Young — Actuarial Consultant

Applied algorithmic optimization techniques (Simulated Annealing, Genetic Algorithms) to optimize portfolios with liabilities, successfully reducing financing costs by 50%.

2022 | LOS ANGELES

California Department of Insurance — Actuarial Student Assistant

Conducted in-depth research on ISO filings and redeveloped the Class Plan Application using VBA, achieving a 30% reduction in processing time.

03 — RESEARCH

Research Projects

PREPRINT · ARXIV:2603.01232

Submodular Risk Measures

Studies submodularity for law-invariant functionals: law-invariant coherent risk measures are submodular exactly when they are coherent distortion risk measures, including Expected Shortfall. Complete characterizations for shortfall risk measures via Arrow–Pratt risk aversion and for optimized certainty equivalents, with an empirical study on daily US equity returns.

With Ruodu Wang

READ ON ARXIV ↗
WORKING PAPER

ES-only E-backtesting for AR-GARCH Losses

Developed sequential e-backtests for Expected Shortfall when only the ES forecast is reported, treating the associated VaR as unobserved. Established e-process validity via infima over admissible values and certified threshold tests for AR-GARCH losses.

Joint work with Ruodu Wang

WORK IN PROGRESS

Mathematics of Scenario-based Risk Evaluation

Studies risk measures determined by collections of scenarios (probability measures), including scenario-based distortion and spectral risk measures and their structural properties.

Joint work with Ruodu Wang and Chenxi Xia

UCLA CAPSTONE

Portfolio Design with CART Models

Engineered a portfolio analysis framework using Classification and Decision Tree (CART) models across 14 asset classes and 73 macroeconomic variables. Identified critical shifts in feature importance across rolling windows.

IAQF COMPETITION 2022

Triggered Shorting Strategy on VIX

Led a team calibrating a 7-state Hidden Markov Model and K-means clustering to identify market regimes, feeding neural-network predictions that powered a short strategy with an average return of 173.5%.

04 — CONTACT

Let's connect.

Open to research collaboration and conversations on risk, mathematics, and markets.

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