Once more I have started a new university degree, this time a Doctorate in Business Administration (DBA) in the modality of executive DBA, part time, extramural. It is a four-year course, pinnacle of management education.
The DBA is taught by the University of Bradford, Faculty of Management, Law and Social Sciences. They are already good old friends because I had my MBA in the same school.
Multiples are the reasons that led to pursue a DBA:
- I like the academic world and the formal learning experience.
- The DBA research will help me to strengthen my understating in management and finance. Particularly in quantitative finance, that is my field of interest.
- I believe it will help me to get a VP job in engineering management.
- I will feel a high-grade of self-realization achieving the top of formal education.
- The title of doctor has social recognition, specially in Germany.
- It should help me to increase my wealth because my research topic will have direct implication to my personal finances.
- It should open the door for teaching at universities.
The DBA has the following modules Research Design and Philosophy, Qualitative and Quantitative Research Methods, Literature Reviewing for Doctoral Studies, Translating Research into Practice, Progression to DBA Research Stage and DBA Thesis. I already had the firs two, and I have recognized that this kind of education is about academic research, critical thinking, literature research, academic writing, contribution to theory and impact to practitioners as well.
The journey is being very exciting and overwhelming in terms of knowledge. I have already changed my research questions multiple times and recently I had a breakthrough in my investigations, that I am going to share in this post.
The DBA thesis will pivot around algorithmic trading strategies, the objective is to systematically analyse them and identify which ones are more suitable for different profiles of investors. I will use QuantConnect (QC) an algorithm trading platform that allows research, back testing and trade investments. QC is based in the open source project LEAN written in C#. QC provides a web based interface to execute and evaluate your algorithms, they can be written in Python, C# or F#.
The perfect companion for QC is Quantpedia, an encyclopedia of algorithmic and quantitative trading strategies. It provides hundreds of trading strategies, implemented for QC and funded in research portals, financial articles, academic articles, universities and conventions. Every strategy is well described, they include the underpinning theory, the mathematical background, the references to literature and the algorithm for QC.
The DBA trip has just begun, it will not be easy, but I am completely sure that it will help me to fulfill most of my expectations.
