I am back to blogging from a hiatus due to work-related obligations, and I'm excited to resume musing about financial risk management and its intersection with computer science.
In fact, the last few months have been extremely fruitful in terms of my own personal research. I don't want to provide too many details now, since they will be forthcoming in a separate blogpost dedicated to the subject, but I have identified various mathematical correspondences that allow for a cogent portfolio-level risk analysis of some fairly complex risks (like counterparty risks or geopolitical risks) without the use of statistics. As I'm sure we all know, statistics have this bizarre tendency to break down when markets get really crazy, like during a financial disaster that brings about a counterparty default. But of course, in the context of risk management, these tail scenarios are the most important, so avoiding statistics has value in that regard.
Finally, a note: I will never intentionally provide any sort of views on particular securities or trades in this blog, and although I may comment on them, I will never actually recommend a particular investment, so please don't interpret my writing that way.
