Quantitative Finance and Risk Analysis

Quantitative finance is accountable to the real world, more so than many other forms of mathematical modeling. Good decisions make money and bad decisions cost money. That makes it critical to harness the power of mathematical methods while being acutely aware of their assumptions and limitations.

Probability is an essential tool for quantitative finance, and yet probability is very subtle. As with many things, a little knowledge of probability is a dangerous thing. A naive understanding of probability can lead someone to take enormous risk, even while enjoying a false sense of security from probability analysis. After many years working with probability and statistics, I have developed an appreciation for both its uses and its limitations. You can find my credentials here.

If you feel that you have to decide between “going with the numbers” and “going with your gut,” maybe there is a third option. Maybe “the numbers” contradict your “gut” because the data are being analyzed in a simplistic way that ignores things you know. You may be able to lower your risk and make better decisions by combining your intuition and your data to take advantage of more information. The primary way I help clients use more information is Bayesian analysis, a line of thinking began in the 1700’s and yet has exploded in application just in the last few years.

If you’d like to work with an expert in probability and mathematical modeling who is also keenly aware of the limitations of these tools, please call or email to discuss your project.


Trusted consultants to some of the world’s leading companies

Amazon, Facebook, Google, US Army Corp of Engineers, Amgen, Microsoft, Hitachi Data Systems