Algorithmic Trading
The future of Finance.
Research.
Backtest.
Implement.
The algorithmic trading division approaches financial markets in a rule based, quantitative environment making use of statistics and various machine learning concepts. The team codifies heuristics from asset selection, to position sizes and other investment criteria. After making it through our assessment center, members contribute along the whole value chain of algorithmic trading starting from idea generation to the final implementation of algorithms, by performing research, designing prototypes, implementing analytics and trading algorithms in order to manage alpha and risk inventory.
What we do as a division
Selected Trading Pitches
Using Automation to Take Advantage of Insider Status of Investors
Using Forms 4's to Generate Abnormal Returns
Download the pitchTrading VIX Futures via Volatility Risk Premium Estimation using GARCH and HAR-RV models
Algorithmic Trading at its finest
Download the pitchQ-Fitted Iteration in a Heston Simulation World for Option Pricing
Download the pitchPrice Movement Prediction using Natural Language Processing
Download the pitch
Previous
Next
Experienced students take the lead
The Heads
David Hirnschall
Head
3.5 Years with WUTIS
David is currently pursuing a PhD in Financial Mathematics with a focus on machine learning at the Vienna University of Business and Economics. Prior to that, he completed a Master's degree in Financial and Actuarial Mathematics at the Vienna University of Technology, where he learned about his current main research interest in machine learning in finance. Besides that David works part-time in the credit risk area.
Florian Reischl
Head
2.5 Years with WUTIS
Florian has graduated from the University of Vienna with a bachelor’s degree in economics. A combination of courses in finance and econometrics have laid a terrific foundation for his work at WUTIS. Currently Florian is taking a gap year and exploring the world of management consulting.
Rising Stars
The Associates & Analysts
Barnabás Paksi
Associate
Daniel Eder
Associate
Karina Pekarek-Kostka
Associate
Kirill Gusev
Associate
Martin Prebio
Associate
Omidreza Amrollahinasab
Associate
Paul Ambroziewicz
Associate