Edoardo Berardo

Quantitative Analyst

UBS•  June 2022 - Present•  Krakow (PL)

Directed profit and loss simulations under global macroeconomic stress scenarios to quantify balance sheet risks and assess the firm’s financial resilience. Analyzed capital adequacy and loss absorption capacity in alignment with the firm's risk appetite framework and FINMA regulatory requirements. Oversaw stress testing models to ensure accuracy, reliability, and robust predictive performance. Led the development and enhancement of Structural Forex (SFX) and Other Valuation Adjustment (OVA) stress models to quantify market risk from Forex and commodities exposures, as well as valuation adjustment risks related to liquidity and model-driven uncertainties. Played a key role in model cloud migration, Credit Suisse model merging, and data management initiatives, curating and integrating APIs and large datasets for risk evaluation. Collaborated with cross-functional teams to incorporate advanced technologies into stress testing, resolved model discrepancies, and ensured regulatory compliance.

Model Developer

Allianz Suisse•  July 2020 - August 2020•  Lugano (CH)

Developed and implemented two VBA scripts to analyze consultant performance and maintain the customer database, streamlining complex data analysis tasks. The programs delivered actionable performance metrics, improving decision-making for management. Successfully sold the codes to Allianz, which were later adopted by other branches across the company, demonstrating the robustness and scalability of the solutions.

Quantitative Analyst

LFA Swiss Wealth Management•  February 2020 - July 2020•  Lugano (CH)

Built data pipelines from Refinitiv and applied advanced feature engineering techniques to extract key insights from raw financial data. Developed automated web scraping scripts to collect and preprocess critical ESG-based information, supporting informed investment decisions. Ensured data integrity, reduced manual intervention, and streamlined workflows by structuring and cleaning data, transforming variables, and generating new predictors to optimize data-driven decision-making. Conducted statistical analysis for Portfolio Managers and developed predictive signals for stock selection using neural networks, random forests, and regression analysis, improving market opportunity identification accuracy and supporting investment decisions. Assisted managers with fundamental analysis of company financials, assessing risk factors and estimating intrinsic values. Conducted in-depth evaluations of key metrics like earnings, growth potential, and industry comparable, resulting in comprehensive company valuations.

Bocconi University

Data Science, Master's Degree, Quantitative Finance•  August 2020 - November 2021•  GPA: 3.73

Main Courses: Market Microstructure, Investments, Trading & Volatility Modelling, Machine Learning, Market Risks, Credit Risk, Portfolio Performance Evaluation, Econometrics, Stochastic Calculus, Valuation Theory, Term Structure Modelling - in English Thesis: Dynamic Limit Order Book Model

ETH Zürich

Mathematics, Bachelor's Degree, Physics•  September 2016 - September 2019•  GPA: 3.51

Main Courses: Analysis, Linear Algebra, Numerical Methods, Method of Mathematical Physics, Complex Analysis, Computer Science, Physics, Classical Mechanics, Electrodynamics, Heat Theory, Solid State Physics, Quantum Mechanics, Nuclear & Particle Physics, Modeling & Simulating Systems - in German Thesis: Chaotic System