Techniques for Modeling Extreme Finance in R

Date: 
Wednesday, April 26, 2017 - 18:00
Source: 
NYC Open Data
Attendees: 
150
City: 
New York

Co-host with NYC Data Science Academy.


***Thank you to Work Market for sponsoring! ***

About Talk:

Extremes matter. So-called rare events seem to happen more regularly. The stylized facts of financial markets have become ever more apparent: negative skews, clustering volatility, and tail dependencies. All of this can add up to misestimated portfolio allocations, inefficient hedging, and insufficient capital reserves. One might even become insolvent. After some examples of the so-called "stylized" facts of financial life, this talk will discuss some ways to identify and quantify the financial impact of extreme events. An application will illustrate examples of problems and perhaps a provisional solution using quantile regression techniques. 

Solutions are implemented in R using R Markdown in RStudio with applications generated through flexdashboard. Several packages will be highlighted in building practical implementations.

6:00-6:30 pm - Food & Mingling 

6:30-7:30 pm - Bill Talk  

7:30-8:00 pm - Q&A & Mingling 

About Speaker: 

Bill Foote has been modeling his way through 4 decades of financial market and institution chaos. He has worked for banks and big 4 consultancies. His clients include many of the Fortune 500 companies and public sector organizations. He has built models of natural gas reservoirs and futures markets to manage them; asset manager value at risk stress testing; electricity market trading; asset-backed securities collateralization management; health insurer, retailer, integrate oil, bank, high-tech manufacturer enterprise risk analytics. 


Bill recently completed an R-Shiny project with NYC Data science Academy that quantified Federal Funds. In other work he used R to determine the transition probabilities and projections of customer retention for the CFO of a major healthcare provider (parametric semi-Markov estimation); and used the same R modeling methodology to forecast default probabilities of the merchant portfolio of a global transaction processor. 

Bill holds an MA and PhD in Economics from Fordham University and graduated Magna Cum Laude from Fordham College with a BA in Philosophy and Classical Languages.

Work Market

9th floor 240 W 37th St, (between 8th ad 7th av)