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

Peer Group Investing Automated by ChatGPT
ChatGPT approach to peer group forming
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Crypto Asset Dynamics
Algorithmic Trading
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Constructing portfolios with the network representation of assets
Utilizing networks in trading
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Stock Chart Pattern Recognition
Can future stock movements be predicted by locating patterns in historical data?
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Using Automation to Take Advantage of Insider Status of Investors
Using Forms 4's to Generate Abnormal Returns
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Trading VIX Futures via Volatility Risk Premium Estimation using GARCH and HAR-RV models
Algorithmic Trading at its finest
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Q-Fitted Iteration in a Heston Simulation World for Option Pricing
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Price Movement Prediction using Natural Language Processing
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Previous
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Experienced students take the lead

The Heads














Karina Pekarek-Kostka

Head

1.5 Years with WUTIS

Karina has graduated with a BSc in Business and Economics with a focus in Mathematics and Finance, and is now working towards a MSc in Quantitative Finance at the Vienna University for Business and Economics. Her fascination for mathematics and programming has paved the way for her work at WUTIS. She also currently works part-time in Integrated Risk Analysis at RBI.














Kirill Gusev

Head

2 Years with WUTIS

Kirill is finishing up his MSc in Banking and Finance with a focus in financial markets at the University of Vienna. His strong quantitative background and passion for finance fuels his pursuit of new investment strategies and his work at WUTIS. Currently, he also works as a full-time Credit Risk Manager at RBI, developing and testing IFRS9 models.

Rising Stars

The Associates & Analysts














Daniel Eder

Associate














Valentin Ennser

Associate














Anna Siniaeva

Associate














Luka Blagojevic

Associate














Lukas Kratzer

Associate














Tomislav Kolev

Analyst














Christian Vorhauser

Analyst














Maria Biasiol

Analyst














Mira Radakovic

Analyst














Chorobek Sheranov

Analyst














Adrian-Victor Ilie

Analyst














Harvey Miller

Analyst














Jonathan Hartman

Analyst














Linus Knoll

Analyst

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