Alessandro Alberto Lorent Dodon

• Python for Finance: Investment Fundamentals & Data Analytics, Udemy
• The Data Science Course: Complete Data Science Bootcamp, Udemy
• Beginner to Pro in Excel: Financial Modeling and Valuation, Udemy
• SQL - MySQL for Data Analytics and Business Intelligence, Udemy
• Microsoft Excel - Complete Course of the Fundamentals, Udemy
• Cambridge Assessment English, Overall Score 193, CEFR Level C1

Global Economic Impact of the 2009 Financial Crisis

In this project, I utilized R and Quarto to study the effects of the 2009 financial crisis on the global economy. The analysis was presented in both PDF and HTML formats, with a strong emphasis on professional visualizations. Data collection involved web scraping using chromote, and the analysis included comprehensive descriptive statistics with Tidyverse. The core of the project was a cluster analysis using machine learning algorithms such as K-means and hierarchical clustering. This analysis aimed to understand the varied impacts of the crisis on different countries, with data sourced from the World Bank.

Analysis of Populist Leadership on Democracy

This project involved using R and Quarto to analyze the World Justice Project dataset, focusing on the impact of populist leaders like Donald Trump on democracy indicators. I created interactive visualizations using Plotly and interactive tables with Kable to enhance the presentation and understanding of the data. The project also included a time series analysis and forecasting component, where I predicted the potential future state of American democracy in the event of Trump's reelection.

Financial Modeling and Valuation of Tesla

For this project, I employed Excel to conduct a comprehensive financial modeling and valuation of Tesla during the COVID-19 pandemic. The analysis explored various scenarios, including hypothetical situations where the pandemic did not occur. I calculated expected deliveries, compared costs with competitors, and analyzed the average selling price for different vehicles. The project also involved forecasting revenues, gross profit, cost of sales, and estimating future expenses, property, plant, and equipment (PP&E), capital expenditures (CapEx), depreciation & amortization (D&A), as well as day sales outstanding (DSO), days inventory outstanding (DIO), and days payable outstanding (DPO). The financial analysis extended to profit & loss (P&L) forecasting, assets and liabilities net income calculation, balance sheet estimation, cost of capital, enterprise value, equity value, and price per share.