Active Portfolio Management with Machine Learning – Final Assignment

Final Project Objective The primary aim of this project is to utilize predictive analytics to forecast future financial metrics. These metrics include but are not limited to stock returns, bond returns, bond yields, commodity prices, currency valuations, and cryptocurrency movements. The rationale behind employing machine learning (ML) techniques for this endeavor stems from the challenge presented by the extensive number of potential predictors. Traditional statistical methods may fall short in efficiently managing and extracting insights from such a diverse and voluminous dataset due to limitations explained in the notes. Scope of the Project Participants are granted the autonomy to select the specific financial metric they wish to predict. The project mandates the application of both shallow and deep learning techniques, as discussed in our coursework, and more complex models such as Neural Networks. For the implementation of these methods, students are encouraged to leverage open-source programming languages and platforms, including Python and R, where a wealth of codes and resources is readily available. ChatGPT could give be very useful to write down efficient codes. The project evaluation will hinge on several pivotal aspects. Economic Viability: Beyond using multiple ML methods, the project must consider economic metrics indicative of investment performance. For instance, if the model were to be applied in managing a hedge fund, it should convincingly outperform established market benchmarks, thereby proving its worth to potential investors. Written Report: The quality of the report matters. You are required to submit a short but comprehensive report encapsulating your methodology, analysis, results, and discussions on the feasibility of applying your model in a real-world investment strategy. This project offers a unique opportunity to bridge the gap between theoretical knowledge and practical application in financial forecasting. Embrace the challenge and strive to innovate within the vast landscape of financial analytics. The Structure of the Final Project Your project should include the following components: ⦁ Problem Description: Start by describing the problem you intend to explore. It is essential to support your project with citations from the finance literature, either academic or practitioner (or both). ⦁ Data Description: Explain the database you are using. Additionally, provide a summary of the database through summary statistics. ⦁ Experiment Outcomes: Present the results of your experiment using tables and graphs. This will help illustrate your findings effectively. ⦁ Conclusion: Conclude your project by summarizing your key findings and insights. ´ Regarding the length of your project, I value quality over quantity. There is no specific minimum length requirement, but I kindly request that you express your ideas concisely.