Some Impressions from R Finance 2015

by Joseph Rickert

The R/Finance 2015 Conference wrapped up last Saturday at UIC. It has been seven years already, but R/Finance still has the magic! - mostly very high quality presentations and the opportunity to interact and talk shop with some of the most accomplished R developers, financial modelers and even a few industry legends such as Emanuel Derman and Blair Hull.

Emanuel Derman led off with a provocative but extraordinary keynote talk. Derman began way out there, somewhere well beyond the left field wall recounting the struggle of Johannes Kepler to formulate his three laws of planetary motion and closed with some practical advice on how to go about the business of financial modeling. Along the way he shared some profound, original thinking in an attempt to provide a theoretical context for evaluating and understanding the limitations of financial models. His argument hinged on making and defending the distinction between theories and models. Theories such as physical theories of Kepler, Newton and Einstein are ontological: they attempt to say something about how the world is. A theory attempts to provide "absolute knowledge of the world". A model, on the other hand, "tells you about what some aspect of the world is like". Theories can be wrong, but they are not the kinds of things you can interrogate with "why" questions.

Models work through analogies and similarities. They compare something we understand to something we don't. Spinoza's Theory of emotions is a theory because it attempts to explain human emotions axiomatically from first principles.

The Black Scholes equation, by contrast, is a model that tries to provide insight through the analogy with Brownian motion. As I understood it, the practical advice from all of this is to avoid the twin traps of attempting to axiomatize financial models as if they directly captured reality, and of believing that analyzing data, no matter how many terabytes you plow through, is a substitute for an educated intuition about how the world is.

The following table lists the remaining talks in alphabetical order by speaker.

	Presentation	Package	Package Location
1	Rohit Arora:   Inefficiency of Modified VaR and ES
2	Kyle Balkissoon: A Framework for Integrating Portfolio-level Backtesting with   Price and Quantity Information	PortFolioAnalytics
3	Mark Bennett:   Gaussian Mixture Models for Extreme Events
4	Oleg Bondarenko: High-Frequency Trading Invariants for Equity Index Futures
5	Matt Brigida:   Markov Regime-Switching (and some State Space) Models in Energy Markets	code for regime   switching	GitHub
6	John Burkett:   Portfolio Optimization: Price Predictability, Utility Functions,   Computational Methods, and Applications	DEoptim	CRAN
7	Matthew Clegg:   The partialAR Package for Modeling Time Series with both Permanent and   Transient Components	partialAR	CRAN
8	Yuanchu Dang:   Credit Default Swaps with R (with Zijie Zhu)	CDS	GitHub
9	Gergely Daroczi: Network analysi​s of the Hungarian interbank lending market
10	Sanjiv Das:   Efficient Rebalancing of Taxable Portfolios
11	Sanjiv Das:   Matrix Metrics: Network-Based Systemic Risk Scoring
12	Emanuel Derman:   Understanding the World
13	Matthew Dixon:   Risk Decomposition for Fund Managers
14	Matt Dowle:   Fast automatic indexing with data.table	data.table	CRAN
15	Dirk Eddelbuettel: Rblpapi: Connecting R to the data service that shall not be   named	Rblpapi	GitHub
16	Markus Gesmann:   Communicating risk - a perspective from an insurer
17	Vincenzo Giordano: Quantifying the Risk and Price Impact of Energy Policy Events   on Natural Gas Markets Using R (with Soumya Kalra)
18	Chris Green:   Detecting Multivariate Financial Data Outliers using Calibrated Robust   Mahalanobis Distances	CerioliOutlierDetection	CRAN
19	Rohini Grover:   The informational role of algorithmic traders in the option market
20	Marius Hofert:   Parallel and other simulations in R made easy: An end-to-end study	simsalapar	CRAN
21	Nicholas James:   Efficient Multivariate Analysis of Change Points	ecp	CRAN
22	Kresimir Kalafatic: Financial network analysis using SWIFT and R
23	Michael Kapler:   Follow the Leader - the application of time-lag series analysis to discover   leaders in S&P 500	SIT	other
24	Ilya Kipnis:   Flexible Asset Allocation With Stepwise Correlation Rank
25	Rob Krzyzanowski: Building Better Credit Models through Deployable Analytics in   R
26	Bryan Lewis:   More thoughts on the SVD and Finance
27	Yujia Liu and Guy Yollin: Fundamental Factor Model DataBrowser using Tableau and R	factorAnalytics	RFORGE
28	Louis Marascio:   An Outsider's Education in Quantitative Trading
29	Doug Martin:   Nonparametric vs Parametric Shortfall: What are the Differences?
30	Alexander McNeil: R Tools for Understanding Credit Risk Modelling
31	William Nicholson: Structured Regularization for Large Vector Autoregression	BigVAR	GitHub
32	Steven Pav:   Portfolio Cramer-Rao Bounds (why bad things happen to good quants)	SharpeR	CRAN
33	Jerzy Pawlowksi: Are High Frequency Traders Prudent and Temperate?	HighFreq	GitHub
34	Bernhard Pfaff:   The sequel of cccp: Solving cone constrained convex programs	cccp	CRAN
35	Stephen Rush:   Information Diffusion in Equity Markets
36	Mark Seligman:   The Arborist: a High-Performance Random Forest Implementation	Rborist	CRAN
37	Majeed Simaan:   Global Minimum Variance Portfolio: a Horse Race of Volatilities
38	Anthoney Tsou:   Implementation of Quality Minus Junk	qmj	GitHub
39	Marjan Wauters:   Characteristic-based equity portfolios: economic value and dynamic style   allocation
40	Hadley Wickham:   Data ingest in R	readr	CRAN
41	Eric Zivot:   Price Discovery Share-An Order Invariant Measure of Price Discovery with   Application to Exchange-Traded Funds

I particularly enjoyed Sanjiv Das' talks on Efficient Rebalancing of Taxable Portfolios and Matrix Metrics: Network Based Systemic Risk Scoring, both of which are approachable by non-specialists. Sanjiv became the first person to present two talks at an R/Finance conference, and thus the first person to win one of the best presentation prizes with the judges unwilling to say which of his two presentations secured the award.

Bryan Lewis' talk: More thoughts on the SVD and Finance was also notable for its exposition. Listening to Bryan you can almost fool yourself into believing that you could develop a love for numerical analysis and willingly spend an inordinate amount of your time contemplating the stark elegance of matrix decompositions.

Alexander McNeil's talk: R Tools for Understanding Credit Risk Modeling was a concise and exceptionally coherent tutorial on the subject, an unusual format for a keynote talk, but something that I think will be valued by students when the slides for all of the presentations become available.

Going out on a limb a bit, I offer a few un-researched, but strong impressions of the conference. This year, to a greater extent than I remember in previous years, talks were built around particular packages; talks 5, 7 and 8 for example. Also, it seemed that authors were more comfortable hightlighting  and sharing packages that are work in progress; residing not on CRAN but on GitHub, R-Forge and other platforms. This may reflect a larger trend in R culture.

This is the year that cointegration replaced correlation as the operative concept in many models. The quants are way out ahead of the statisticians and data scientists on this one. Follow the money!

Speaking of data scientists: if you are a Random Forests fan do check out Mark Seligman's Rborist package, a high-performance and extensible implementation of the Random Forests algorithm.

Network analysis also seemed to be an essential element of many presentations. Gergely Daróczi's Shiny app for his analysis of the Hungarian interbank lending network is a spectacular example of how interactive graphics can enhance an analysis.

Finally, I'll finish up with some suggested reading in preparation for studying the slides of the presentations when they become available.

Sanjiv Das: Efficient Rebalancing of Taxable Portfolios
Sanjiv Das: Matrix Metrics: Network-based Systematic Risk Scoring
Emanuel Derman: Models.Behaving.Badly
Jurgen A. Doornik and R.J. O'Brien: Numerically Stable Cointegration Analysis (A recommendation from Bryan Lewis)
Arthur Koestler: The Sleepwalkers (I am certain this is the book whose title Derman forgot.)
Alexander J. McNeil and Rudiger Frey: Quantitative Risk Management Concepts, Techniques and Tools
Bernhard Pfaff: Analysis of Integrated and Cointegrated Time Series with R (Use R!)

Comments

[Beliavsky]

Thanks for your detailed report on the conference -- next best thing to being there. You have given me many ideas to explore.

[Stuart]

Hi Joseph,

Thank you for the review! I am really hoping to be able to make it next year as it sounds like a great conference! Will you be updating this post with the links as they become available or will they be posted on the R/Finance website?

[Gergely Daróczi]

@Stuart, most slides are now also available at the official R/Finance 2015 website as well: http://www.rinfinance.com/agenda/