Hugo De Vere

U.S Interest Rates Analyst

De Vere Research•  April 2020 - Present

• Content Production and Data Analysis: Authored a research blog featuring over 30 well-researched articles, offering insights on Treasury bonds through analyses of macroeconomic events, monetary policies, and market dynamics. • ∗ Data Modeling with Multiple Tools: Demonstrated proficiency in Python, Rstudio, and Matlab to develop models and analytics tools. These methods are broadly applicable to various data analytics tasks. A comprehensive overview of these models can be found in my 2023 outlook. ∗ Sentiment Analysis and NLP: Developed a sentiment analysis model to quantify monetary policy impacts, utilizing natural language processing. See the Fedspeak sentiment analysis and Streamlit Dashboard for a practical application of this skill.

Quant researcher

primer•  September 2022 - August 2023

• Data Analytics and Modeling: Utilized statistical methods to construct a comprehensive portfolio comprising six low-turnover trading strategies, achieving Sharpe ratios between 0.7 and 1.1. Techniques employed included dimensionality reduction (PCA), clustering, linear regression, and others, all aimed at deriving actionable insights from data. • Data Engineering and Tool Development: Developed Python-based tools for various data-related tasks, including web scraping, data storage, and analytics. Tools created include a DV01-neutral hedging system and a yield curve bootstrapping tool, all designed with an emphasis on automation and data manipulation for analysis. • Risk and Portfolio Management: Applied optimization techniques such as Sharpe ratio, risk parity, minimum volatility, and target volatility using Numpy and Scipy packages to minimize risk and enhance portfolio performance. • Documentation and Data Visualization: Authored detailed analyses using visual aids to represent complex data sets and findings.

Commercial Expansion Analyst Intern

FEMSA Comercio OXXO•  June 2018 - August 2018

• Spatial Analytics: Conducted quantitative analyses of commercial properties, evaluating them based on various metrics to identify the most promising investment opportunities. • Investment Analysis: Presented a data-backed investment proposal, advocating for a 307.2 square-meter property as the most beneficial investment based on calculated returns and risk metrics.