David Pugh

Who am I?

Graduated class of 2005 from the College of William and Mary with a BS in Mathematics. Spent a few years as a professional actor, before "settling down" into a job as a senior research analyst for the Institute for Physical Sciences (IPS). IPS was basically a think-tank that used insights from complexity science to build models of political and economic systems (it was also where I was first learned of the existence of SFI!). I received my MSc in Economics from the University of Edinburgh in 2009. Worked a bit as a senior research analyst for Centra Technologies, before receiving PhD funding to return to the University of Edinburgh in 2010. I am currently in the second year of my PhD.

Research Interests...

I think that financial markets are best thought of as being complex adaptive systems whose agents (i.e., households, firms, traders, investors, financial intermediaries, etc) are engaged in economic activity as part of a inter-connected, dynamic network of financial contracts. Here are a couple of ideas for projects that I would be keen to develop with the help of SFI staff and other CSSS participants:

• Can credit and liquidity constraints generate volatility clustering? Basically, I would like to develop a computational model that incorporates key ideas from the financial contracting literature and generates the volatility clustering that we observe in the data.
• Systemic risk in financial networks. Why do financial crises seem to be an endemic feature of market economies? Do financial markets sow the seeds of their own destruction? In particular, does diversification (a rational risk management strategy for an individual agent) actual increase systemic risk under certain circumstances? My point of departure for answering these questions is a classic model of self-organized criticality, the forest fire model.

My modeling strategy is inherently inter-disciplinary in nature and relies heavily on previous work on nonlinear dynamics, machine learning, network theory, and computer modeling and simulation in R and Python. More info about my research interests can be found on my blog.