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.
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.