Published on January 30th, 2025
Quick Summary:
Algorithm Trading Software assists to make faster and smarter decisions by removing emotions. You can create your own strategies and reduce trading risks with custom-built software.
Algorithm Trading Software is a popular program used for buying and selling stocks. You can automate the whole process by scanning price movements and identifying patterns. It executes trades within seconds. Many traders use it to eliminate human emotions like fear and greed. You can trade 24/7 with Algorithm Trading Software. It reacts to market changes instantly and tests strategies before investing real money. ATS is useful for making faster and smarter trading decisions. As per the Statista, around 60-73% of equity trading is performed through algorithmic trading in the United States. Thus, it is dominating the financial markets.
You can grab even more benefits from a custom built Algorithm Trading Software. It allows you to tailor your strategy and integrate with multiple stock exchanges. Customized software can reduce costs and improve risk management. So, investing in custom algorithm trading software is becoming a necessity rather than a choice.
In this blog, we will cover how to build custom algorithm trading software with expert insights.
5 Popular Algorithm Trading Softwares
Traders use Algorithm Trading Software to buy and sell stocks automatically. These programs help you save time and avoid mistakes. Some of them are easy to use while others require coding skills. Some of the popular Algorithm Trading Software are mentioned below:
| Software Name | What It Does | Who Uses It? |
| MetaTrader 4 & 5 (MT4/MT5) | Helps traders buy and sell automatically. Best for Forex trading. | Beginner and professional traders. |
| QuantConnect | Let traders test and build their own trading strategies. | Traders who know a little coding. |
| AlgoTrader | A big trading software for businesses and banks. | Large companies and expert traders. |
| TradeStation | Helps traders create trading rules and test them. | People who want to make their own trading plans. |
| Interactive Brokers API | Lets traders build custom trading systems using their own ideas. | Professional traders and developers. |
Suggested: How to Build Trading Platform Software?
Understanding the Core Components of Algorithm Trading Software
Algorithm Trading Software is made up of different parts. These parts work together to provide faster trading experience. Below are the key components:
1. Market Data Feeds & APIs
The software needs real-time market data to make smart trading decisions. Market data feeds provide live prices and past trends. APIs allow traders to connect with stock exchanges and other financial platforms. It ensures traders have access to the latest market updates.
2. Strategy Development & Backtesting
You need a strategy before trading with real money. You can use charts and price patterns to test your strategy. The strategy is backtested to make sure that it is reliable. It helps you to save on losses.
3. Execution & Order Management System (OMS)
Once strategy is made, the software must execute trade efficiently. OMS ensures trades are performed quickly and accurately. It supports:
- Market orders
- Limit orders
- Stop-loss orders
- Bracket orders
4. Performance Monitoring & Optimization
You need to perform continuous tracking to make improvements. Some of the factors you need to monitor are:
- Profitability
- Drawdown
- Slippage
So, by understanding these key components you can make trade faster and more profitable.
| Component | What It Does | Why It’s Important |
| Market Data Feeds & APIs | Provides real-time market prices and past trends from stock exchanges and brokers. | Helps traders make smart decisions based on the latest market updates. |
| Strategy Development & Backtesting | Traders set rules for when to buy and sell. Backtesting checks if these rules would have worked in the past. | Helps traders avoid bad strategies and improve their chances of making profits. |
| Order Management System (OMS) | Places trades automatically and manages different types of orders like market orders, limit orders, and stop-loss orders. | Ensures trades happen at the right time and price without delays. |
| Risk Management & Safety Features | Includes tools like stop-loss (to limit losses) and position limits (to control trade size). | Protects traders from big losses and unexpected market crashes. |
| Performance Tracking & Improvements | Checks how well the trading strategy is working by tracking profits, losses, and trade speed. | Helps traders fix mistakes and improve their trading system over time. |
Steps to Build Custom Algorithm Trading Software
Algorithm trading software automatically buys and sells assets based on predefined rules. It eliminates emotional decisions and ensures faster execution. It can operate 24/7 without manual intervention. Below are the detailed steps to build Custom Algorithm Trading Software:
1. Decide Your Trading Goal and Plan
Before you start building the software, you must clearly define your trading goal. Ask yourself:
- What do you want to trade?
- How often do you want to trade?
- How much risk are you willing to take?
This step helps set the foundation for building your algorithm trading software.
2. Choose a Programming Language
Algorithm Trading Software requires coding. Select the right programming language based on your needs:
- Python – Best for beginners and widely used for trading because it has many tools like Pandas, NumPy, and Backtrader.
- C++ – Very fast and used for high-frequency trading where speed matters the most.
- Java – Used by large financial firms because it is stable and secure.
3. Pick the Right Technology and Storage
You need to store data so that Algorithm Trading Software keeps it running smoothly. Here’s what you need:
Databases – Store past trade data and price movements. Common options include:
- PostgreSQL – A strong, open-source database for storing trading data.
- MongoDB – Good for handling large amounts of unstructured data.
Servers – Decide where your software will run:
- Cloud-based servers (like AWS, Google Cloud) – Work online and are scalable.
- On-premise servers – Used by companies who want full control over software.
4. Connect to Real-Time Market Data
For algorithm trading software to work, it needs live market prices and order book data. You can get this information by integrating with broker APIs, which provide real-time price updates. Popular options include:
- Interactive Brokers API – One of the best platforms for professional trading.
- Alpaca API – Free and easy to use for stock trading.
- TD Ameritrade API – Great for stocks and options trading.
Some traders also use WebSockets for streaming real-time data. It provides the fastest updates.
5. Test Your Trading Algorithm
Before using real money, you need to test your trading strategy. There two ways to do this:
Backtesting – Running the algorithm on past market data. It is useful to check how it performs. Common tools for backtesting include:
- Backtrader – A simple and powerful tool for testing trading strategies.
- QuantConnect – Allows traders to test and refine strategies.
- Zipline – Used by professional traders for backtesting.
Paper Trading – Testing the strategy in a live market environment but without using real money. It helps you to check strategy before taking real financial risks.
6. Add Risk Management Features
Trading comes with risks, so it’s important to include safety features to protect your money. These include:
- Stop-loss orders – The software automatically sells a trade if it starts losing too much money.
- Position limits – Controls how much money is invested in each trade to avoid big losses.
- Market volatility monitoring – The software can stop trading during highly unstable market conditions to prevent unexpected losses.
Good risk management keeps your trading system safe and prevents huge financial losses.
7. Go Live and Improve Over Time
Once the software is tested and working correctly, you can start live trading. However, instead of going all-in at once, traders usually:
- Start with paper trading – Test the software in a real market environment without real money.
- Optimize based on results – If the strategy performs poorly, adjust and improve it.
- Use tools like Docker or Kubernetes – These help manage and scale the software so that it runs efficiently.
Even after launching, constant monitoring and improvements are needed to make the software more profitable.
| Steps | What to Do? | Why Is It Important? |
| Step 1: Plan Your Trading Goal | Decide what you want to trade (stocks, forex, crypto) and how often you want to trade. | Helps you create a clear strategy and avoid random trading. |
| Step 2: Choose a Programming Language | Pick a coding language like Python (easy), C++ (fast), or Java (used by banks). | The right language makes your software work better and faster. |
| Step 3: Pick the Right Technology & Storage | Use a database to store trade data and choose a server (cloud or on-premise). | Keep your software running smoothly and safely. |
| Step 4: Connect to Market Data | Link your software to a broker API (like Interactive Brokers or Alpaca) to get live prices. | Your software needs real-time data to make smart trades. |
| Step 5: Test Your Strategy | Use backtesting (past data) and paper trading (fake money) to check if your strategy works. | Helps find mistakes before using real money. |
| Step 6: Add Risk Management | Set stop-loss (automatic sell when losing money) and trade limits to protect your money. | Reduces losses and protects your trading account. |
| Step 7: Start Live Trading & Improve | First, trade with fake money, then slowly start using real money. Keep improving your software. | Helps you avoid mistakes and make better profits over time. |
Must Check: Stock Trading App Development: Reasons and Techniques
Best Technologies & Tools for Developing Algorithm Trading Software
To build good algorithm trading software, you need the right tools and technology. These tools help you write the code, get market data, test your strategy, and make trades faster. Below is a simple table explaining the best technologies for each part of algorithm trading.
| Category | Best Technologies | What is it used for? |
| Programming Languages |
|
Used to write the trading software and create trading strategies. |
| Market Data Providers |
|
Gives real-time stock prices and past market data for making smart trades. |
| Backtesting Frameworks |
|
Helps test trading strategies using past market data before using real money. |
| Trading APIs |
|
Lets the software buy and sell stocks or crypto automatically. |
| Cloud Deployment |
|
Stores the software online so it runs fast and works from anywhere. |
Cost Estimation for Building Custom Algorithm Trading Software
Building custom algorithm trading software requires money, just like setting up a business. The total cost to build custom algorithm trading software ranges from $40,000 to $150,000, depending on the features, security, and who develops it. Below is a breakdown of estimated costs:
- Basic software with simple automation: $40,000 – $60,000
- Advanced software with risk management & backtesting: $70,000 – $100,000
- High-end system for large firms with AI & high-frequency trading: $120,000 – $150,000
Estimated Cost Breakdown
| Component | Estimated Cost | What Does It Cover? |
| Development | $20,000 – $100,000 | The cost of coding and building the software. |
| Data Feeds & APIs | $1,000 – $10,000 per year | Getting live market data from stock exchanges. |
| Cloud & Hosting | $5,000 – $25,000 annually | Keeping the software online and running 24/7. |
| Compliance & Security | $10,000 – $50,000 | Making sure the software follows financial rules and is safe from hackers. |
Factors That Affect the Cost
Several things increase or decrease the cost of building algorithmic trading software:
- Custom-built vs. Ready-made software – A fully custom system is more expensive, but it offers more control and flexibility. Ready-made software is cheaper but less flexible.
- Infrastructure & Hosting – Using cloud-based services (AWS, Google Cloud) costs extra but provides speed and security. On-premise servers are costly upfront but cheaper in the long run.
- Data Feeds & Trading APIs – Paid APIs from Bloomberg and Interactive Brokers cost more than free APIs from Alpha Vantage.
- Security & Compliance – If the software handles large transactions, extra security and legal checks are needed, which add to the cost.
How can iTechnolabs help you build a custom algorithm trading software?
iTechnolabs is a reputed stock trading app development company that can help you to build custom algorithm trading software. Our software automates trades to improve execution speed. We integrate real-time data to ensure fast and secure trading. Whether you’re looking for a fully automated or a semi-automated trading assistant, iTechnolabs can assist you to stay ahead in the market.
Final thoughts
Building a custom algorithm trading software is a smart move for traders looking for faster and data-driven trading. This software executes trades instantly by eliminating emotional decisions. It allows you to tailor strategies and improve risk management. So, you must invest in custom algorithm trading software to improve accuracy and reduce costs.
FAQ’s
1. Which software is best for algo trading?
QuantConnect is a good choice for coding custom strategies. If you need a simple and automated system, then AlgoTrader and TradeStation are also reliable options.
2. Can I do algorithmic trading on my own?
Yes, you can do algorithmic trading on my own if you’re familiar with basic programming. You can build your own strategy using platforms like QuantConnect. If you do not know programming, you can use software with pre-built strategies.
3. Is algorithmic trading really profitable?
Yes, it is. You need to perform continuous testing, tweaking, and risk management to stay profitable.
4. What is the best algorithmic trading site?
NinjaTrader and TradeStation are some of the best platforms.
5. Which is the best software for algorithmic trading?
QuantConnect and TradeStation are popular algorithm trading software.
6. How do I create my own trading algorithm?
You need to follow these steps:
- Define Your Strategy
- Choose a Programming Language
- Select a Trading Platform
- Backtest Your Algorithm
- Optimize & Deploy
