Trading Performance Analysis Using Adaptive Financial Engineering Algorithms

Business, Economics and Management, Engineering, IT, Mathematics and Statistics


  • This internship is able to cover project costs for domestic students only.
  • Due to remote arrangements, this internship is accepting applications from eligible PhD students nationwide.


Euler Capital is a proprietary trading and investment firm that relies on rigorous research and education to build thoughtful, risk management strategies that achieve well defined objectives. The backbone of Euler’s approach to markets is simply that behavioural biases in the decision making of buyers and sellers creates inefficiencies that can be exploited in a systematic fashion. Euler Capital believe that managing the uncertainty inherent in predictive modelling is a more fruitful exercise than simply attempting to make better predictions.


  • Opportunity to work with the founder & CIO as well as the firm’s Chief AI Scientist.
  • Able to work with other like-minded PhD qualified scientists
  • Able to work with Datasets in a unique way instead of just in a conventional fashion.
  • Be part of a team-oriented ground-breaking project


Euler Capital believe global leaders and institutional investors are relying on invalid and unreliable financial models that fail to recognize financial markets are complex adaptive systems. The result is not just inept central bank monetary policies, but flawed models leave market participants vulnerable to risks for which they are simply not prepared. Euler Capital’s philosophy is that the world can be understood. They strive to build a fundamental cause and effect understanding in everything they do – how global economies and markets work to how people think and make decisions differently. The nature of their work focusses on understanding the incentive structures that cause people to behave irrationally or make irrational decisions. The opportunity to dig in and understand the incentive structures that have been created, the restraints or requirements for people to engage in transactions, whether that’s from a regulatory framework or whether that’s from an institutional framework built into their prospectus. Ultimately that can create opportunities or trades that you think are irrational or the opportunity to break if it’s brought to its illogical extreme.

The research project proposed is to re-purpose predictive analytics and integrate a multidisciplinary science blend of analytic tools, including behavioural psychology, causal inference, complexity theory, computing with words, textual analysis, and historical perspective. Capital markets meet all the requirements for complex dynamic systems: diverse actors, connectedness, interaction, and adaptability. While other analytics and modelling treat markets as linear, rational systems with normally distributed risk. The successful intern will be provided the opportunity at Euler Capital to work collaboratively in a team of like – minded professionals from industry and academia undertaking ground – breaking research focussed on mitigating risk with complexity science together with human and machine intelligence into predictive analytics designed for capital markets that addresses them as what they are: complex systems. Ultimately the project deliverables will be based on modelling and developing a full course application to predict global and political and/or financial trends with approximate and feasible useability.


If you’re a PhD student and meet some or all the below we want to hear from you. We strongly encourage women, indigenous and disadvantaged candidates to apply:

  • Advanced knowledge in probability theory
  • Skills for writing research articles and project reports (LATEX)
  • Knowledge in complex system modelling
  • Familiar with complexity theory and decision theory
  • Ability to code in a scripting language (R, Python or MATLAB)
  • Familiarity with version control technologies (GitHub)

In addition, the following skills are considered desirable but not essential:

  • Sound research background – having published papers in quality peer-reviewed Journals or Conferences
  • Familiarity with learning theories (Bayesian Learning, Reinforcement Learning)
  • Familiarity with fuzzy theory and expert systems
  • Familiar with Data fusion and evidence accrual


  • To investigate and model an adaptive decision support system to cope with complex systems such as capital markets.
  • To utilise the model to identify global threats and opportunities based on data and evidence accrual
  • To simulate the model and provide performance analysis and comparison scenarios.
  • To develop a prototype software for the model, and to create relevant user manuals, and repositories (Euler Capital’s GitHub).
  • To report results as a research paper that can be submitted to relevant international conferences and/or peer-reviewed journals.


The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.

It is expected that the intern will primarily undertake this research project during regular business hours and maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

Melbourne, VIC or can be completed remotely
5 months
Domestic students only
APR - 1446



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