This section is currently under development. Stay tuned for updates! New content and improvements are on the way.

I am a finance professional based in Brazil, with a strong interest in integrating finance, economics, and technology. I am currently pursuing a master's degree in Economics and Finance at Fundação Getulio Vargas (FGV).

• Finance and Economics: I work in finance and am passionate about understanding economic trends and financial markets.
• Data Science and Technology: I am learning Python and R to apply data analysis in financial markets.
• Statistics and Mathematics: I have an intermediate knowledge of these subjects and am keen on improving my skills.
• Econometrics: Currently studying econometrics, with a focus on Ordinary Least Squares (OLS) methods to deepen my understanding of statistical methods in economics and finance.

A project aimed at comparing the performance of Bitcoin (BTC) with various Exchange-Traded Funds (ETFs). This involves:

• Historical price analysis
• Calculating key financial metrics
• Visualizing performance over time

Currently focused on studying econometrics, particularly the Ordinary Least Squares (OLS) method. This includes understanding and applying OLS in financial modeling and data analysis to draw meaningful insights from economic data.

I am currently taking a statistical analysis course, which involves completing 10 projects. Each project will have versions implemented in both Python and R. These projects aim to enhance my skills in statistical analysis and data science.

• Email: michelle.bouhid@gmail.com
• LinkedIn: Michelle Bouhid
• GitHub: MichelleBouhid

• Programming Languages: Python, R
• Tools and Frameworks: pandas, numpy, matplotlib, seaborn
• Financial Analysis: Time series analysis, portfolio management, risk assessment
• Statistics and Mathematics: Hypothesis testing, regression analysis, optimization
• Econometrics: Regression analysis, time series econometrics, panel data analysis, Ordinary Least Squares (OLS)

Projects completed as part of the Blockchain Engineer course at the Data Science Academy. All code includes notes and comments made during the lessons.

Projects completed as part of a statistical analysis course, with implementations in both Python and R.

Feel free to connect with me on LinkedIn or explore my projects here on GitHub. I am always open to collaborating on interesting projects and discussing ideas related to finance, economics, and data science.

--->