Leveraging technology and laziness a talk by Josef Svoboda
Advances in computational technology have made it key to the delivery of financial services. The new paradigm has redesigned the required skillset of the labour force, rendering coding an essential part of many roles, similarly to typing or foreign languages.
In this talk, I will share a perspective of a Scotland-based investment manager whose primary role is quantitative credit investing, yet whose job ultimately revolves more around code than derivatives, be it financial or mathematical.
The main takeaway is the importance of matching the complexity of the task to the complexity of the solution, that being right and making the right choice are two separate things and how does this translate to financial advice. We will touch on the virtue of laziness, why you should be doing things before you are ready and why hating data is inevitable.
This talk is suitable for both beginner and advanced Pythonistas.
I am an investment manager specialising in quantitative credit investing. I am struggling to balance my passion for elegant mathematics with a keen scepticism of the rigor of modelling in social sciences.
I am currently working for an Edinburgh based fixed income specialist, Cameron Hume, I have experience across factor portfolio construction, LDI, credit research and data analytics (and fixing a printer paper jam).
In my free time, I enjoy various sports, reading and annoying a little puppy, Hugo.