Executive Education in Algorithmic Finance Can Improve Your Career Opportunities

The task of using sophisticated quantitative methods to operate on financial markets is a fascinating topic. Especially because there will never be a one-fits-all approach to winning in markets using only computers. One has to combine knowledge of the underlying markets with in-depth knowledge of computational methods to build a trading model, which has to be adapted whenever market conditions change, so a constant recalibration of models is required.

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Algorithmic Finance Concepts

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Different quantitative model families have to be applied to cover the whole spectrum of available methods. For example, Monte-Carlo Simulation, Decision Optimization under Uncertainty, as well as Statistical Artificial Intelligence and Machine Learning need to be understood in their relation to successful integration in any contemporary trading environment.

What to Expect with the Algorithmic Finance Course

You will benefit from three different methodological approaches (Simulation, Optimization, and Machine Learning). A basic understanding of financial markets, as well as the basics of Statistics and Probability Theory are required to follow the lectures optimally.

The course is built around three different methodological approaches (Simulation, Optimization, and Machine Learning).

​Techniques include:

  • Monte-Carlo Simulation for Pricing and Portfolio Decisions
  • Decision Optimization under Uncertainty
  • Contemporary Portfolio Optimization
  • Statistical Artificial Intelligence in Finance
  • Machine Learning to trade different asset classes
  • Deep Learning approaches

Role-play simulation has proven to be an effective way of rapidly transferring expertise. This course centers around two modules:

Module One:

  • Monte-Carlo Simulation for Pricing and Portfolio Decisions
  • Decision Optimization under Uncertainty: Portfolio Optimization

Module Two:

  • Statistical Artificial Intelligence in Finance
  • Machine Learning to trade different asset classes (stocks and cryptocurrencies)
Together We Empower

Apply for your Digi-Winner Scholarship!

To qualify for the scholarship, your primary residence must be in Vienna and you must be a member of the Chamber of Labour of the province in which you work. 

Up to 3,192 Euro

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Dr. Ronald Hochreiter, Associate Professor 

Ronald Hochreiter is Associate Professor of Finance at Webster Vienna Private University. He is active in several national and EU research projects, e.g., in the EU Horizon 2020 - FIN-TECH: A training program for financial supervision and TECHnology compliance, as well as EU Erasmus + - ADA: Curriculum development in Advanced Analytics in Business.

Hochreiter is President of the Academy of Data Science in Finance, and Vice President of the Austrian Society for Operations Research. His research areas include optimization under uncertainty and decision science, data science and machine intelligence (machine learning and deep learning), AI, algorithmic finance, analytics in banking, and finance and risk management.

 

This course is a full day course, with sessions starting on: 

October 3, and

October 10.

Duration of the module

On-site for two consecutive days - from 09:00 hrs to 13:00 hrs

890 € per participant.

 

 

Get up to 80% of your program costs covered: Apply for your Digi-Winner Scholarship!

To qualify for the scholarship, your primary residence must be in Vienna and you must be a member of the Chamber of Labour of the province in which you work. 

The scholarship can support you if:

  • Your main residence and workplace are in Vienna: if you are gainfully employed and your main residence and workplace are in Vienna, the maximum subsidy amount is 5,000 euros. Depending on your income, you can receive between 40% and a maximum of 80% of the course costs. Grants are available up to a monthly net income of 2,500 euros.

You can find more details here.

  • Your main residence is in Vienna, but your workplace is outside of Vienna: If you are employed and your main residence is in Vienna, but your workplace is outside of Vienna, you can receive a maximum of 2,500 euros from waff. The amount of the additional subsidy from the Chamber of Labour depends on the province in which you are a member of the Chamber of Labour.

You can find more details here.

  • Your main residence is in Vienna and you are currently unemployed: if you are unemployed and your main residence is in Vienna, you can receive a maximum subsidy of 2,500 euros from the Chamber of Labour. 40% of the course costs will be covered. In this case, waff can support you with an additional amount of maximum 300 euros.

You can find more details here.

Scholarship coverage

  • The cost of continuing education and training in the area of "digital literacy,"
  • and associated exam fees.

Conditions

  • Must apply for the scholarship ahead of the executive program enrolment.
  • Applications must be submitted online.

Contact Us

Email us at exed@webster.ac.at or call +43 664 88295756

Webster Vienna Private University
Palais Wenkheim,
Praterstr. 23,  Vienna 1020, Austria

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