R/Finance 2017 livestreaming today and tomorrow

[This article was first published on Revolutions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

If you weren't able to make it to Chicago for R/Finance, the annual conference devoted to applications of R in the financial industry, don't fret: the entire conference is being livestreamed (with thanks to the team at Microsoft). You can watch the proceedings at aka.ms/r_finance, and recordings will be available at the same link after the event.

Check out the conference program below for the schedule of events (times in US Central Standard Daylight Time).

Friday, May 19th, 2017
09:30 – 09:35   Kickoff
09:35 – 09:40   Sponsor Introduction
09:40 – 10:10   Marcelo Perlin: GetHFData: An R package for downloading and aggregating high frequency trading data from Bovespa
   Jeffrey Mazar: The obmodeling Package
   Yuting Tan: Return Volatility, Market Microstructure Noise, and Institutional Investors: Evidence from High Frequency Market
   Stephen Rush: Adverse Selection and Broker Execution
   Jerzy Pawlowski: How Can Machines Learn to Trade?
10:10 – 10:30   Michael Hirsch: Revealing High-Frequency Trading Provisions of Liquidity with Visualization in R
10:30 – 10:50   Matthew Dixon: MLEMVD: A R Package for Maximum Likelihood Estimation of Multivariate Diffusion Models
10:50 – 11:10   Break
11:10 – 11:30   Seoyoung Kim: Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and News
11:30 – 12:10   Szilard Pafka: No-Bullshit Data Science
12:10 – 13:30   Lunch
13:30 – 14:00   Francesco Bianchi: Measuring Risk with Continuous Time Generalized Autoregressive Conditional Heteroscedasticity Models
   Eina Ooka: Bunched Random Forest in Monte Carlo Risk Simulation
   Matteo Crimella: Operational Risk Stress Testing: An Empirical Comparison of Machine Learning Algorithms and Time Series Forecasting Methods
   Thomas Zakrzewski: Using R for Regulatory Stress Testing Modeling
   Andy Tang: How much structure is best?
14:00 – 14:20   Robert McDonald: Ratings and Asset Allocation: An Experimental Analysis
14:20 – 14:50   Break
14:50 – 15:10   Dries Cornilly: Nearest Comoment Estimation with Unobserved Factors and Linear Shrinkage
15:10 – 15:30   Bernhard Pfaff: R package: mcrp: Multiple criteria risk contribution optimization
15:30 – 16:00   Oliver Haynold: Practical Options Modeling with the sn Package, Fat Tails, and How to Avoid the Ultraviolet Catastrophe
   Shuang Zhou: A Nonparametric Estimate of the Risk-Neutral Density and Its Applications
   Luis Damiano: A Quick Intro to Hidden Markov Models Applied to Stock Volatility
   Oleg Bondarenko: Rearrangement Algorithm and Maximum Entropy
   Xin Chen: Risk and Performance Estimator Standard Errors for Serially Correlated Returns
16:00 – 16:20   Qiang Kou: Text analysis using Apache MxNet
16:20 – 16:40   Robert Krzyzanowski: Syberia: A development framework for R
16:40 – 16:52   Matt Dancho: New Tools for Performing Financial Analysis Within the 'Tidy' Ecosystem
   Leonardo Silvestri: ztsdb, a time-series DBMS for R users
Saturday, May 20th, 2017
08:00 – 09:00   Coffee/ Breakfast
09:00 – 09:05   Kickoff
09:05 – 09:35   Stephen Bronder: Integrating Forecasting and Machine Learning in the mlr Framework
   Leopoldo Catania: Generalized Autoregressive Score Models in R: The GAS Package
   Guanhao Feng: Regularizing Bayesian Predictive Regressions
   Jonas Rende: partialCI: An R package for the analysis of partially cointegrated time series
   Carson Sievert: Interactive visualization for multiple time series
09:35 – 09:55   Emanuele Guidotti: yuimaGUI: A graphical user interface for the yuima package
09:55 – 10:15   Daniel Kowal: A Bayesian Multivariate Functional Dynamic Linear Model
10:15 – 10:45   Break
10:45 – 11:05   Jason Foster: Scenario Analysis of Risk Parity using RcppParallel
11:05 – 11:35   Michael Weylandt: Convex Optimization for High-Dimensional Portfolio Construction
   Lukas Elmiger: Risk Parity Under Parameter Uncertainty
   Ilya Kipnis: Global Adaptive Asset Allocation, and the Possible End of Momentum
   Vyacheslav Arbuzov: Dividend strategy: towards the efficient market
   Nabil Bouamara: The Alpha and Beta of Equity Hedge UCITS Funds – Implications for Momentum Investing
11:35 – 12:15   Dave DeMers: Risk Fast and Slow
12:15 – 13:35   Lunch
13:35 – 13:55   Eric Glass: Equity Factor Portfolio Case Study
13:55 – 14:15   Jonathan Regenstein: Reproducible Finance with R: A Global ETF Map
14:15 – 14:35   David Ardia: Markov-Switching GARCH Models in R: The MSGARCH Package
14:35 – 14:55   Keven Bluteau: Forecasting Performance of Markov-Switching GARCH Models: A Large-Scale Empirical Study
14:55 – 15:07   Riccardo Porreca: Efficient, Consistent and Flexible Credit Default Simulation
   Maisa Aniceto: Machine Learning and the Analysis of Consumer Lending
15:07 – 15:27   David Smith: Detecting Fraud at 1 Million Transactions per Second
15:27 – 15:50   Break
15:50 – 16:10   Thomas Harte: The PE package: Modeling private equity in the 21st century
16:10 – 16:30   Guanhao Feng: The Market for English Premier League (EPL) Odds
16:30 – 16:50   Bryan Lewis: Project and conquer
16:50 – 17:00   Prizes and Feedback
17:00 – 17:05   Conclusion

R/Finance 2017 livestream: aka.ms/r_finance

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)