Andre Pedro Westin

Alternatives | Asset Allocation | Investment Underwriting | Macro Research | Quantitative Analysis | Portfolio Construction | Real Assets | Manager Research |

Dedicated to enhancing portfolio diversification and optimizing risk-adjusted returns through rigorous quantitative analysis and innovative methodologies. Led the development of a systematic factor for defining market capitalization thresholds, aligning closely with index methodology and replacing an outdated approach. Developed and implemented advanced lasso and nonlinear regression models to identify statistically significant factor tilts within hedge fund portfolios, leading to precise factor exposure estimation and enhanced risk management strategies. Contributed to quantitative due diligence within new institutional mandates and model portfolios, ensuring alignment with investment objectives. Conducted quantitative analysis on hedge fund portfolios using Python, Excel, and BlackRock Aladdin, assessing risk exposures and identifying opportunities to optimize returns. Utilized multiple regression analysis to uncover factor tilts in time series data, leveraging various Python packages for robust statistical modeling. Built sophisticated financial models to stress test positions and scenario test portfolios, enabling proactive risk management and mitigation strategies. Perform in-depth quantitative analysis of hedge fund portfolios to assess construction, exposures, and return drivers, identifying idiosyncratic risks and differentiated alpha sources. Utilize advanced analytics to identify portfolios generating returns uncorrelated to market movements, enhancing diversification and risk-adjusted returns. Communicate complex analyses and findings to portfolio managers through clear and concise presentations and reports, facilitating informed decision-making. Collaborate cross-functionally with the research team to implement strategic initiatives leveraging data and technology, driving continuous improvement in risk analysis capabilities. Extensive utilization of BlackRock's Aladdin platform and Bloomberg Terminal for data analysis and research purposes.

Served as Teaching Assistant for Macroeconomics at Indiana University Economics Department. Was responsible for leading two weekly recitation sessions to supplement professor's lectures with quantitative problem solving. -Attended professor's theory-focused lectures to support course learning objectives. -Developed and instructed sessions covering relevant quantitative macroeconomic concepts including: measuring economic indicators, analyzing demand/supply shocks, fiscal policy, monetary policy, banking system risks, and the Federal Reserve. -Led students through applied problem sets and discussions on measuring GDP, CPI, unemployment, interest rates, and more. -Aimed to demonstrate relevance of macroeconomic theory and impart memorable passion for the subject. -Received positive feedback from students on engaging teaching style and clarity in explaining complex concepts. -Contributed to highest historical attendance rates compared to previous recitation sessions. -Worked closely with professor to identify student needs and tailor instruction accordingly. -Had 3 students ask to use me as a recommendation for Kelley Business School Honors program applications. Overall, the role focused on complementing theoretical course content with practical, quantitative learning. Strong classroom presence and student feedback reflected a commitment to actively engaging learners and unpacking challenging economic problems.

Quantitative equities researcher within the Economics Department at Indiana University under the supervision of leading financial economist Robert A. Becker. Conducted independent quantitative research focused on evaluating the true distribution of equity returns in U.S. financial markets. Utilized Python programming and statistical analysis packages to empirically demonstrate that U.S. equity prices do not follow a normal distribution. Specific techniques included: -Visualization of return distributions using histograms, Q-Q plots, and time series graphs. -Calculation of descriptive statistics like skewness, kurtosis, and coefficient of variation. -Hypothesis testing via Jarque-Bera test to reject the null hypothesis of normality. -Time series analysis with Augmented Dickey-Fuller test for stationarity. -Regression modeling using ARIMA to correct for autocorrelation. Key findings challenge assumptions underlying Modern Portfolio Theory, Capital Asset Pricing Model, and Efficient Markets Hypothesis, which rely on the normality of returns. Research expands on prior work by Paul Kaplan of Morningstar by using higher frequency daily and weekly data to uncover fat tails obscured in annualized data. Overall, my research underscores the need for more sophisticated risk management techniques that do not depend on normality assumptions. Demonstrates the value of large-scale statistical analysis of financial data to uncover market inefficiencies and opportunities for improved modeling.

-Utilized Python for statistical analysis of alternative, unstructured datasets to build forecasting models for emerging market capital outflows. -Automated a manual process with a python based currency converter which outputs results into a convenient format in excel. Prior process depended on FactSet. -Leveraged Pandas, Matplotlib, and Sci-Kit Learn for data visualization, cleaning, and wrangling to explain insights from quantitative research. -Integrated Excel with Python to analyze social media, central bank, and financial exchange data. -Implemented creative multivariate regression analyses for quantitative investment strategies including FX volatility analysis for USD/INR. -Uncovered patterns within FX data using Yahoo Finance API in Python. -Attended meetings with institutional clients. Created an internal product guide using PowerPoint. -Mapped and explained signals, strategies, products, and AUM using Excel. -Computed covariance, correlation, performance history, and risk for S&P 500 equity basket. -Studied signal research to implement econometric tools for signal creation projects. -Used techniques from data science and quantitative modeling conferences to increase statistical sophistication.

-Took a gap semester and spent my semester and summer working full time in this fund of funds/family office. Worked directly under the partner/CIO and COO. -Conducted investment analysis and research reports on various hedge funds, private equity funds, special situations lending funds, and funds focused in the global water industry. Helped the portfolio manager and CIO to understand complex investment vehicles. -Created a detailed 93 page water investment and global industry report. Interviewed a water hedge fund manager and a water technology expert in order to gather more information. My research convinced the portfolio manager to replace his position in a Pictet water fund with a unique water ETF which my report recommended. He also advised his partner to add a larger thematic allocation to the water sector within his portfolio. -Used the TRA and COMP function in Bloomberg Terminal in order to compare the performance of four water ETF’s with the Pictet water fund and the S&P 500 by backtesting historical price and dividend data. Demonstrated outperformance since 2007 by a specific water ETF. -Conducted back-office and operations functions such as: trade blotter regulatory compliance, anti-money laundering procedures, investment subscription contracts, bond analysis via Bloomberg Terminal, dissolution of a passthrough entity in the Bahamas, record maintenance, used Microsoft Excel and Orion Advisor Technology Software in order to re-balance portfolios every month when bank statements arrived. -Worked in English and Portuguese.

• Expanded our active user base and built new relationships with career centers, recruiters, and firms across the USA. • Managed a team of 3 student fellows. Oversaw the creation of our Latinx Division. • Helped with the digitalization of our platform and outreach. Conducted market research on competitors and their products.

• Understood the credit analysis process and how loan interest rates are calculated for different clients. • Learned how CAT Finance receives capital. • Developed an understanding of how CAT finance is attempting to rebalance their portfolio to reduce default rates. • Thought of ideas on how to increase margins for CAT’s lending activities by utilizing the North American Savings account business model in order to receive capital at a much lower interest rate.

-Worked in a division with over 4 billion USD in Assets Under Management. Reported directly to a fund manager. -Conducted industry research. Created a 105-page report on the global lithium and electric vehicle industry. -Discovered the requirements to extract lithium in Chile and around the world. Observed current and potential requirements of battery makers in order to achieve maximum efficiency. -Compared the cost of owning a Tesla model S vs Internal combustion engine Competitors using Microsoft Excel. -Compared depreciation of electric vehicles relative to internal combustion vehicles by utilizing median market car prices in the used auto industry in the United States. -My Research was utilized by my supervisor, a hedge fund manager, in order to rebalance the fund’s position in SQM, a Chilean Lithium producer. He forwarded my research report to a team in New York.

• One of 3 interns that were the only high-school interns ever hired to work for McKinsey & Company. • Ran comparative reports between various Latin American telecom enterprises while considering pricing, services, prepaid products, and user experience. Normalized the data by units in order to compare products from different firms. • Ranked enterprises in terms of cost per unit and user experience. • My research was presented at a convention in Austria and was used for the digital transformation of the telecom company Entel in Peru. Worked in Spanish, Portuguese and English. Was awarded a letter of recommendation.

Concentration in Econometrics and Computational tools. I have pivoted my degree in order to focus on Statistics and programming. I have opted to take statistics and programming electives. Graduating early by one semester.

Highschool diploma and the International Baccalaureate diploma. Higher Level classes: HL Economics, HL Biology, and HL B Spanish. Standard Level classes: SL Mathematics Studies, SL Literature, and SL History.