The main goal of this project is to develop and implement tools to automate financial modeling tasks for Valleywood Capital. By doing so, the project aims to increase the efficiency and accuracy of decision-making processes for the hedge fund, ultimately leading to improved performance.

1. Identify the specific financial modeling tasks that Valleywood Capital wants to automate, such as portfolio optimization, risk assessment, or forecasting.
2. Research the available technologies and tools for financial modeling automation, such as machine learning algorithms, natural language processing tools, and data visualization software.
3. Develop a deep understanding of the data sources and inputs that Valleywood Capital will be using for the financial modeling tasks, such as historical market data, economic indicators, and company financial statements.
4. Develop and implement customized algorithms and software tools to automate the identified financial modeling tasks.
5. Test and validate the performance and accuracy of the automated financial models and compare them to manual models.
6. Develop a plan for integrating the automated financial modeling tools into Valleywood Capital's existing workflows and processes.

Students will work closely with CEO, Dave Burnett who is supervising and available for questions. This will also include occasional progress meetings where adjustments to the students' tasks and duties can be made if necessary.