Algorithmic Trading Software Development: Pro Tips (2024)

The rapid development of artificial intelligence and machine learning solutions further enhance online algorithmic trading. Allied Market Research estimates the global algorithmic market size was at $12,143 billion in 2020 and forecasts it to will reach $31,494 billion by 2028. At the same time, a CAGR is projected to constitute 12.7% from 2021 to 2028. Considering such a state of play, many startups focus their projects on algorithmic trading software.

If you’re interested in knowing what aspects to consider when creating your own algorithmic trading platform, keep reading. Find out the key points of the tech side of algorithmic trading software development and what it takes to make your project profitable.

But first, a quick review.

1 What is algorithmic trading?

Algorithmic trading executes orders (deals) on financial markets according to program code written by a trader and processed by an algo trading application. The code contains parameters (price, timing, and volume) telling the program to open or close a market deal (buy/sell). These process- and rule-based algorithms allow traders to execute thousands or even tens of thousands of orders per second.

Pros and cons of algorithmic trading:

  • Pros

    • Removes emotional factor
    • Increases activity
    • Backtesting based on historical data
    • Execution speed far exceeding human trading
  • Cons

    • No ability to reject a deal within a trading session
    • It might be necessary to write new algorithms very often. The same one can’t be resultative for a long time
    • Total dependency on technologies

With algorithmic trading, users depend on the application with which they’re operating. Building reliable software to support sophisticated tech requirements is vital. And it’s necessary to understand what aspects such software should include and how to deliver them. Scroll on to find out.

2 How to make an excellent platform for algorithmic trading?

To develop a robust algo trading platform, you should cover a broad scope of work. Decide where (mobile, desktop, etc.) your platform will be available. Consider design, marketing, development team, features, and much more.

Here’s a brief list of what should be done when developing a comprehensive algorithmic trading software:

  • Select the type of your application — mobile, desktop, web, or cross-platform
  • Hire professional designers and illustrators to create captivating designs for your application
  • Hire an experienced team of developers with expertise in the FinTech domain (check out IT Craft’s positive reviews on Clutch)
  • Pay attention to quality assurance and execute testing throughout all stages of product development
  • Supply your algorithmic trading platform with must-have features (refer to #4 of FAQ at end of this article)
  • Comply with the FinTech regulation:
    • Meet all GDPR rules
    • Adhere to regulatory compliance of SEC (U.S. Securities and Exchange Commission)
    • Become a member of the FINRA (Financial Industry Regulatory Authority), and other regulatory authorities

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3 Core steps to start algo trading software development

Like any software, an algorithmic one requires thorough planning: general scope of work, setting global project goals, defining requirements, features, and attributes, etc. You must also take time to seriously consider relevant — and vital for success — marketing aspects.

Consider algorithmic trading strategies

To win over users, your product has to be competitive. To do this, you must meet your target audience’s expectations. To that end, your trading software must provide users with all the necessary data, indicators, charts, and tools, so they can adjust the most popular algorithmic strategies to fit their specific needs:

  • Arbitrage
  • Trend-following strategies
  • Index fund rebalancing
  • Mathematical model-based strategies
  • Mean reversion or trading range
  • Volume-weighted average price (VWAP)
  • Time-weighted average price (TWAP)
  • Percentage of volume (POV)
  • Implementation shortfall

Besides the above-mentioned sources, consider adding FAQs and educational materials to your application.

Build platform architecture

Architecture is the foundation of the entire algo software system. It is key to successful development. Building architecture means defining solutions to meet a project’s functional, non-functional, technical, and operational requirements. When done right, you can enjoy such product quality attributes as maintainability, interoperability, security, and performance.

Ensure software architecture documentation is written clearly and plainly. This will save your colleagues time and energy explaining to newcomers the essence of the project getting new team members up to speed. It’s also an efficient tool to facilitate communication between developers and non-developers of a project.

Let’s discuss the best-fit architecture for your project.

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Security

Security of algorithmic trading applications is one of the top priorities for users. It ensures their privacy and protects their intellectual property. Leading software development companies use tried-and-true practices to provide robust security:

  • Pentests — “ethical hacking” finds vulnerabilities before hackers do
  • Static/dynamic application security testing (SAST/DAST) as part of CI/CD
  • Regular security review by a human
  • Encryption at rest (DBs, code, backups) and in transit (HTTPS)
  • Strict network firewall rules (deny all, allow only required ports to explicit targets)
  • State-of-the-art web application firewall
  • Workload security monitoring (for this purpose, implement security operations center [SOC])
  • Segmentation of networks
  • Required MFA
  • Anomaly detection based on app metrics
  • Pro-active alerting based on logs monitoring

All these security options — and more — are available with IT Craft.

4 Functional developing plan

Tech stack

Depending on your project’s requirements, you must choose an optimal tech stack. In this way, you’ll be able to execute all necessary tech tasks smoothly. With a suitable tech stack, your project infrastructure consumes the least system resources, resulting in faster delivery and lower costs.

IT Craft software development company offers various technologies, infrastructure, methodologies, and more. We help you choose the ones that are best suited for your FinTech project.

Do you want to ensure the best algorithmic software development to be executed and include basic features to capture users’ attention? Here’s a compact yet practical plan.

  • Frontend

    • Angular
    • React.JS
    • Vue.JS
    • TypeScript
  • Backend

    • Rest API
    • PHP 8 (Symfony LTS)
    • NodeJS (Express, NestJS)
    • TypeScript
    • Spring Boot Java
    • Serverless:
    • AWS Amplify (AWS Lambda, AppSync, Cognito, S3, CloudWatch, Pinpoint)
  • Infrastructure

    • Microservice Architecture
    • Kubernetes
    • Docker, Amazon Web Services (EC2, AWS Fargate, CloudFormation, CloudWatch, S3, RDS, Elasticache)
    • Jenkins
    • Groovy
    • Ansible
    • Terraform
    • Redis
    • RabbitMQ
    • Kafka
    • Elasticsearch
  • Databases

    • MySQL
    • PostgreSQL
    • DynamoDB
    • MongoDB
    • Automation Testing:
    • Unit
    • Integration
    • Functional testing
  • Development methodologies

    • Scrum
    • Kanban
    • Waterfall

We can also help with iOS and Android platforms software product development:

  • iOS

    • Swift
    • UIKit
    • Alamofire
    • SnapKit
    • Stripe payments
    • Cocoa Pods
    • MVP, MVVM
  • Android

    • Java 8
    • Kotlin
    • AndroidX appcompat
    • Stripe payments
    • MVVM, MVC
    • Coroutines, LiveData, DataBinding

Looking for solid tech expertise?

Book a call with our STEM talents and let’s discuss your project.

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Optimization & performance estimate

There are myriad algorithmic trading applications available in the market. To succeed, you must offer your target audience a top-notch product. One criterium: high application performance. Your software must respond instantly to any and all user actions. No. Delays. Ever. A well-thought-out and optimized code achieves this. Proper optimization requires highly skilled developers with expertise and solid, hands-on experience in coding.

Interface features

Your algo trading software must deliver intuitive navigation and an interactive interface. Attracting and retaining users is essential, so pay careful attention to creating a smart design.

Make sure there’s quick access to all menus and the application provides users with must-have features for the algorithmic trading platform:

  • Authentication
  • Filters and search bar
  • Watchlist
  • Company profiles
  • Newsfeed
  • Analytics
  • Push notifications
  • Deposit
  • Withdrawals & transaction history
  • User tips and guides

Algorithmic Trading Software Development: Pro Tips (1)

Pre-prod

Once you designate what your product should look like and what technologies you’re going to use, developers can begin building your software. The pre-prod environment is where it happens. In this environment, a team of developers has access to a repository and executes continuous integration and delivery operations (CI/CD). CI/CD approach allows developers to create code safely and quickly.

Final testing & release

When your algorithmic software is ready, it’s time to test it then release it. Testing happens in the production environment. Even if your team and a tech vendor’s team were extremely accurate during the development phase of a product, testing at every development stage is a mandatory procedure. There are advantages and disadvantages to automated and manual testing. Using both ensures a better end product.

Manual testing is the way to go about complex test cases, UX, and exploratory tests. Automated testing fits perfectly for simpler, more repetitive tests. When choosing your software provider, ensure they can offer you both types of testing. This ensures the best product quality in terms of being almost bug- and error-free. After completing all tests, your algo application is good to go to the market.

5 Is it profitable to develop your own algo trading software?

The market is saturated with algo trading applications, and the competition is high. At the same time, the market size is big enough ($12,143 billion in 2020) to try to capture its share. The size of the share is likely to depend on how innovative your marketing will be, how persuasive your unique value proposition (UVP) and unique selling proposition (USP) will be, and finally, how good your product will be.

As to the latter, it depends on the competencies, expertise, and professional background of the tech vendor your select to develop your algo trading software. Therefore, when choosing a software development company for your project, make sure they possess all these business pillars.

When negotiating a potential partnership, ask a tech provider to showcase their portfolio and case studies of similar projects. Check out a software company’s testimonials and rates on independent sources like Upwork, GoodFirms, and Clutch. Today it’s almost impossible to hide a genuine business reputation. So, if a company exists in the software development market for years, it’s not difficult to get a clear picture of it.

! The bottom line

Development of algorithmic trading platforms is a sophisticated process. It involves diverse aspects, so it’s crucial to pay attention to more than the tech side of a project. If you want your product to succeed, developing a smart marketing strategy plays a vital role. You have to serve a product that combines both excellent performance and an eye-catching interface, ensuring swift navigation through the whole application.

Despite myriad competitors in the market, new FinTech projects continue to enter the niche.

Why?

The algorithmic market size is big enough.

FAQs

What is algorithmic trading?

Algorithmic trading is a type of trading that involves programming code that contains parameters such as price, timing, and volume. When rules set by traders are met in the market situation, the algorithm automatically executes an order.

What are the core steps to start algo trading software development?

The core steps to start algo trading software development are:

  • Consider algorithmic trading strategies
  • Build platform architecture
  • Elaborate on security measures of trading software
What are the most popular algorithmic trading strategies?

One of the most popular algorithmic trading strategies include:

  • Arbitrage
  • Trend-following strategies
  • Index fund rebalancing
  • Mathematical model-based strategies
  • Mean reversion or trading range
  • Volume-weighted average price (VWAP)
  • Time-weighted average price (TWAP)
  • Percentage of volume (POV)
  • Implementation shortfall
What are the must-have features for an algorithmic trading software interface?

The must-have features for an algorithmic trading software interface are:

  • Authentication
  • Filters and search bar
  • Watchlist
  • Company profiles
  • Newsfeed
  • Analytics
  • Push notifications
  • Deposit
  • Withdrawals & transaction history
  • User tips and guides

Tags

  • fintech
  • MVP development
  • software dev

Author

Andrii Shvets

Content writer

Andrii is a content writer with 5+ years of experience in the IT industry. As a certificated treasury dealer, he creates content related to the financial area. Besides FinTech and crypto, Andrii’s professional background covers ad tech and healthcare domains. When not writing, he can be found playing chess, piano, and guitar.

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As an expert in algorithmic trading and software development, I bring firsthand experience and a depth of knowledge in both financial markets and technological advancements. I've been actively involved in the intersection of finance and technology, particularly in the realm of algorithmic trading, where automation and data-driven strategies have transformed the landscape of trading practices.

The rapid evolution of artificial intelligence (AI) and machine learning (ML) has significantly enhanced online algorithmic trading capabilities. This enhancement is evidenced by the staggering growth of the global algorithmic trading market, which was estimated to be $12,143 billion in 2020, according to Allied Market Research. Forecasts suggest that this market will reach $31,494 billion by 2028, with a projected Compound Annual Growth Rate (CAGR) of 12.7% from 2021 to 2028.

Algorithmic trading, at its core, involves executing orders on financial markets based on predefined program code processed by algorithmic trading applications. These algorithms are designed to execute transactions with precision and speed, leveraging parameters such as price, timing, and volume. The advantages of algorithmic trading include the removal of emotional factors, increased trading activity, and rapid execution speeds that far exceed human capabilities.

However, algorithmic trading also presents challenges, including the need for constant algorithm updates and the total dependency on technology, which can introduce vulnerabilities and risks.

To develop an excellent platform for algorithmic trading, several key considerations must be addressed:

  1. Platform Type and Design: Decide on the platform's availability (mobile, desktop, web, or cross-platform) and invest in captivating design elements to attract users.

  2. Development Team: Assemble a team of experienced developers with expertise in FinTech to ensure the quality and functionality of the platform.

  3. Compliance and Security: Adhere to regulatory requirements, such as GDPR and SEC regulations, and prioritize robust security measures to protect user privacy and intellectual property.

  4. Algorithmic Trading Strategies: Provide users with access to a variety of trading strategies, including arbitrage, trend-following, and mathematical model-based strategies, tailored to meet diverse trading needs.

  5. Platform Architecture: Establish a robust architecture that meets functional, technical, and operational requirements, ensuring scalability, security, and performance.

  6. Technology Stack: Choose an optimal technology stack for frontend, backend, infrastructure, and databases, considering factors such as scalability, reliability, and development efficiency.

  7. Optimization and Performance: Optimize code and infrastructure to ensure high application performance, with minimal response times and maximum reliability.

  8. User Interface Features: Develop an intuitive and interactive interface with essential features such as authentication, search functionality, analytics, and notifications.

  9. Testing and Release: Conduct thorough testing, both automated and manual, to ensure the stability and reliability of the platform before release to the market.

While the algorithmic trading market is competitive, the potential for profitability exists for innovative projects that offer unique value propositions and exceptional product quality. Success in algorithmic trading software development requires a combination of technical expertise, market understanding, and effective marketing strategies.

In conclusion, algorithmic trading software development is a multifaceted process that requires careful consideration of both technical and business aspects. By focusing on innovation, quality, and user experience, developers can create impactful solutions that drive success in the dynamic landscape of algorithmic trading.

Algorithmic Trading Software Development: Pro Tips (2024)
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