Automated Stock Trading Platform

Target audience

The platform is designed for different client segments – from individual investors and traders looking to diversify their portfolios or generate additional returns by investing in an algorithmic trading strategy, to institutional investors such as hedge funds, venture capital funds, large investment firms, etc. looking to invest part of their portfolio in an active trading vehicle that has low or negative correlation to the rest of their portfolios.

Solution overview

The solution is an algorithmic trading system based on a complex, multi-level analysis of prices and the behavior of their derived characteristics. The system allows the administrator to set up trading strategies with different market instruments and backtest them with data obtained from different financial markets and time frames.

The trading strategies continuously analyze the behavior of the indicators and initiate the execution of orders once the predetermined conditions are met. In addition, the system allows fine-tuning parameters and displaying calculations and events on charts in real-time mode. The solution consists of three subsystems.

1. Admin subsystem

This subsystem allows admins to set up trading strategies and track price movements on the chart displaying market data, as well as configure order execution policy.

The data received from the data provider is displayed on the charts in real time, and the calculation and analysis of all indicators are done on the fly.

When configuring a trading strategy, the admin sets parameters for RSI, stochastic conditions, candlestick patterns and many other indicators.

The trade management module allows the admin to set multiple parameters to configure the order execution policy:

• entry price 
• how many orders should be sent (multiple trade execution)
• trade size
• exit price (stop-loss management or profit target)

The admin can backtest the configured strategy using historical data and refine it if needed. Otherwise, the admin can initiate algo trading with the pre-configured strategy. In this case, the platform performs technical analysis based on the received market data and counted indicators and determines triggers. If the predefined conditions for triggers are met, the strategy is executed and the platform places an order.

2. Client subsystem

The second subsystem is intended for users and allows them to register, top up accounts via the PelicanPay API, withdraw funds, monitor balances and portfolios, and view trade history. Statistics and reports are available to clients in charts and tables.

3. Corporate subsystem

This part of the system allows admin to manage the users, check the statistics on trades, make money transfers between the accounts of the system, as well as manage all the accounts.

Technical solution highlights

Technically, the system consists of several microservices that use event-based communication (message bus). Microservices are asynchronous Python applications that implement a data processing pipeline, i.e. the result of the work of one microservice is input data for another (or multiple microservices). Python Socket.IO is used for real-time updates.

From the perspective of UI, it is a React application that uses MobX as state management on the front end.

• We chose the Python language and Django framework for backend development and JavaScript, HTML5, React JS for the frontend part.
• The AWS infrastructure that our team chose to run the platform in the cloud reduces the time it takes for the web application to load in the end user’s browser and provides additional monitoring and data protection tools.
• To meet the security requirements of the broker and payment gateway, we implemented role-based access controls, multi-factor authentication, encryption, and other security measures.
• In general, the architecture of the platform is defined by high performance requirements. Since trading opportunities can appear and disappear in a fraction of a second, the system must process massive volumes of data simultaneously to react to market events in real-time.

Development process

We delivered the project following the agile development process with frequent deliveries, full transparency, and close collaboration with our client. Every two weeks we delivered and demonstrated results and reported on costs. Frequent demonstrations and feedback collection sessions allowed us to conduct early reviews of all materials and initial software versions and make timely adjustments to functionality.

Initially, the client provided only a few design sketches, so we had to hold a series of workshops to define and approve the technical solution architecture, break down product functionality into sprints, prioritize features, and define detailed requirements.

After that, we moved on to the development phase, following the product roadmap. Fourteen months after the start of the project, the MVP version with its core functionality was up and running. Now Itexus engineers are developing and implementing additional features.

Results & future plans

Within a year, Itexus’ cross-functional team of experts delivered an MVP version of an automated, high-performing, and secure trading solution that met all of our client’s requirements. The platform is up and running. In the meantime, we maintain and support the existing solution and work on the advanced features of the platform as well as mobile versions of the application.

Looking for a talent pool to fill the software development gap for your project? Itexus engineers are ready to tackle your idea, let’s discuss it.