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One of my recent projects.
Quantitative Machine
The answers to complex problems of |
Building Quantitative Trading System is a challenging task that is difficult to solve.

The extendable suite of quant modules for researching, developing, and implementing diverse trading strategies was designed in a project of Quant Studio.

The final solution can automatically generate trading systems with AI/ML/Quantitative technological innovations.
The Quantitative Machine is made of 4 main modules:
// MODULE 1 of 4
Trading systems logic design generation
Alpha Generator
Financial systems have become too complex for the traditional tools and methods used to design and test them. Luckily, recent breakthroughs in AI and mathematics pave the way for a much-needed overhaul.

The trading systems generation engine is a novel AI technique for automatically exploring financial markets to identify unique edge cases in their behaviors. Aggregating uncovered insights into a quantitative and systematic trading system. Flexible modular architecture for solving a broad spectrum of quantitative trading tasks.

Developed particular engine core language for complex system interface encoding with mathematical precision. Automated mathematical techniques to synthesize logical circuits as a finite-space, event-driven model.
// MODULE 2 of 4
Trading Instruments Module
Synthetic ETF
To tackle the challenges of trading systems from another angle, I developed multiple crucial components and methods focused on screening and amplifying particular market features that improved trading agents. Powered by techniques for calculating specific score values of trading instruments.

A Long/Short portfolio of available trading instruments can be viewed as a new Synthetic ETF. Integrated components for producing Synthetic ETFs open an opportunity to leverage the procedure of particular market feature amplifying. Moreover, it allows the retuning of Synthetic ETFs to extend the lifetime of the instrument.

Inspired by the reverse idea, a new component mining the imaginary set of trading sub-instruments, if available trading instruments are treated as Synthetic ETFs. Uncover a way for data enrichment and better module work.

Increased functionality of the Trading Instruments Module by integrating components:
  • Financial time-series forecasting implementation,
  • Mining and using Alternative data (enhanced by the NLP techniques).
// MODULE 3 of 4
Quantitative Technologies Toolkit
Essential Quantitative set of tools including the following:
  • Combination of AI/ML/Quantitative systems for vital operations in creating trading strategies.
  • Exploring the most suitable trading strategy parameters.
  • Validating strategy solution.
  • Risk management solution.
  • Portfolio construction.
// MODULE 4 of 4
Software Infrastructure
When designing advanced software, it's crucial to understand how it may behave. The initial requirement for flexible, scalable, modular design. Quantitative Machine system for exploring, developing, implementing, and running a broad specter of systematic strategies powered by innovative usage of AI/ML technologies for financial markets.

Four-tier architecture modular design framework developed in C/C++/C#/Python, with an extendable interface API and implementation of infrastructure modules as a core of the machine.