The DSF-R (International Conference of Data Science in Finance with R) is the annual conference hosted by the Academy of Data Science in Finance in cooperation with WU Vienna. The conference aims to bring academics and finance professionals together to discuss all applications of contemporary Data Science approaches to the area of Finance. These topics include Machine Learning, Deep Learning, Artificial Intelligence, Sentiment Analysis and Prescriptive Analytics.
This conference has been created to demystify the buzz around Artificial Intelligence (AI) and to focus on reality instead of hype. The collaboration of academic practicioners and practical academics will show how everyone in the Finance Industry can benefit from the unprecedented progress in Data Science technologies.
Day One is focused on talks by industry experts and academics on Finance related applications of Data Science. The whole spectrum of possible applications will be covered.
WHAT can be done!
Day Two is meant to provide in-depth discussion on new and cutting edge technologies, including all contemporary AI for Finance methods like Deep Learning and Sentiment Analysis.
HOW it can be done!
The conference will be accompanied by networking events in the beautiful city of Vienna. Be sure to be able to spend the weekend after the conference in Vienna too!
ENJOY Vienna!
Ronald Hochreiter Academy of Data Science in Finance |
Welcome to the DSF-R 2018 |
Gregor Kastner WU Vienna |
Dealing with stochastic volatility in time-series using the R packages stochvol and factorstochvol |
Kris Boudt Vrije Universiteit Amsterdam |
Downside risk evaluation with R package GAS |
Nermina Mumic TU Vienna |
Fraud detection using time-dependent compositional data and robust filtering |
Bernhard Pfaff Invesco |
Looking under the hood: Investigating the blockchain with R |
Hermann Elendner Humboldt-Universität zu Berlin |
Liquidity and Resiliency of Crypto-currency Markets |
Branka Hadji Misheva University of Pavia |
Network-based VAR models to detect interdependencies between crypto prices |
Stefan Voigt WU Vienna |
Limits to Arbitrage in Markets with Stochastic Latency |
Paolo Pagnottoni University of Pavia |
Vector error correction models to measure price connectedness between bitcoin exchange prices |
Evgeniia Filippova WU Vienna |
Cryptoeconomics @ WU |
Tobias Setz OpenMetrics |
Using R in a productive asset management environment |
Thomas Keil Raiffeisen Research |
A blueprint for deriving multiple efficient and coherent asset allocations for premium and private banking clients in CEE |
Zehra Eksi WU Vienna |
Pairs Trading Under Drift Uncertainty and Risk Penalization |
Ronald Hochreiter Academy of Data Science in Finance |
What is a Data Scientist? What is Data Science? |
Mario Annau Quantargo |
Let’s play together: Collaborative Data Science |
Jochen Papenbrock Firamis |
Explainable Processing of Complex Financial Data in R/R-Shiny |
Michael Mifek Raiffeisen Centrobank |
Regulatory Calculations with R |
Florian Schwendinger WU Vienna |
An In-Depth Tutorial on Natural Language Processing with R |
Samuel Borms Universite de Neuchatel |
The R package sentometrics to compute, aggregate and predict with textual sentiment |
Mihai Lupu Research Studios Austria |
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models |
Joel Gotsch, Ihor Shylo Raiffeisen Bank International |
R for Machine Learning & AI at RBI AG |
Christoph Bodner, Thomas Laber Post AG |
Scaling R in the Cloud: A Case Study from Post AG |
Laura Vana WU Vienna |
A Credit Risk Application of Multivariate Ordinal Regression Models using the R package mvord |
Mathieu Mercadier Universite de Limoges |
Credit Spread Approximation and improvement using random forest regression |
DSF-R 2018 is dedicated to providing a harassment-free conference experience for everyone regardless of gender, sexual orientation, disability or any feature that distinguishes human beings. For more information, please see the R Consortium code of conduct.
The conference will take place at the new campus of the WU Vienna University of Economics and Business (WU Vienna).