19 best JavaScript Algorithmic Trading libraries in 2024

You can use JavaScript trading libraries to access financial market data. You can use these libraries to test strategies. You can also trade live and analyze data from different platforms.

JavaScript is a programming language commonly used to create interactive features on websites and can also be used to build algorithmic trading systems. In algorithmic trading, deals are automatically executed by computers based on pre-established rules and circumstances. 

You would need a solid command of JavaScript and familiarity with terms like variables, functions, loops, and data structures to construct an algorithmic trading system in the language. You would also need to know how to transmit orders to a brokerage or trading platform and how to retrieve and evaluate financial data like stock prices and trade volumes. 

To create an algorithmic trading system in JavaScript, consider these steps: 

• Choose the trading approach you want to use. 
• Create a set of criteria and guidelines that will use to execute trades automatically. 
• Obtain financial information from a database or stock market, for example. 
• Apply JavaScript to the data analysis. 
• To automatically execute transactions, join a trading platform or brokerage. 

For creating algorithmic trading systems, several JavaScript libraries can be helpful. A few choices are "ccxt": with the help of this library, you may access a variety of cryptocurrency exchanges, extract and analyze their data, and execute trades automatically. Both the REST and WebSocket APIs are supported; “gecko”; “binance-trading-bot”; “superalgos”; “crypto-trading-bot”; and more. 

Check out the below list to find the best JavaScript algorithmic trading libraries for your application development: 

ccxt  

• This library is open source and lets you interact with different cryptocurrency exchanges.  
• The goal is to make accessing and trading on different cryptocurrency exchanges easier. Providing a consistent API for various platforms does this.  
• Developers can create programs to analyze data and communicate with cryptocurrency exchanges.  

gekko  

• It is an open source cryptocurrency trading bot and backtesting platform.  
• Traders and developers can use it to make and test plans for cryptocurrency markets.  
• Gekko is more centered around algorithmic trading strategies and historical data analysis.  

binance-trading-bot  

• Supports various buy/sell orders based on the configuration.  
• Can monitor multiple symbols. We will monitor all symbols per second.  
• It uses MongoDB to provide a persistent database. But it doesn't use the latest MongoDB to support the newer Raspberry versions.  

Superalgos  

• It is a project that is open to the public. It helps with trading and analyzing cryptocurrency.  
• This tool helps traders and developers test strategies on various crypto exchanges.  
• Offers a platform to design, test, and execute algorithmic trading strategies.  

crypto-trading-bot  

• It offers basic buy and sell signals and offers many things to be profitable.  
• Users can create trading strategies using blocks in the software's visual interface.  
• Use blocks to make trading strategies with conditions, actions, indicators, and triggers.  

technicalindicators  

• This is a JavaScript library. It's open-source and offers many commonly used technical indicators. Analysts use these indicators to analyze financial markets.  
• This tool helps developers and traders analyze indicators to make better trading decisions.  
• You can use it to create trading bots, charting apps, and other tools for technical analysis.  

cryptocurrency-arbitrage  

• You can use it to create trading bots, test strategies, and analyze financial market data.  
• It is flexible and customizable so you can create complex trading algorithms with it.  
• Supports various asset classes and offers automated trading, strategy optimization, and risk management.  

node-binance-trader  

• It creates custom indicators and strategies for the TradingView charting platform.  
• Supports various asset classes and offers risk management, strategy optimization, and automated trading.  
• The flexibility and customizability make it capable of creating complex trading algorithms.  

algotrader  

• Users on this platform can trade stocks, forex, cryptocurrencies, futures, and options.  
• Traders can use a strong testing tool to analyze their strategies on past data. This helps them refine trading rules and improve performance.  
• It offers real-time execution of trading strategies across multiple markets and exchanges.  

crypto-exchanges-gateway  

• You can focus on important tasks because the client side handles authentication.  
• Offers a unified REST API to various exchanges and can automate trading or build bots.  
• Offers WS access for real-time data and a basic UI that implements most API calls.  

btcrobot  

• The purpose of its creation was to trade cryptocurrencies automatically, focusing on Bitcoin.  
• The tool is advertised to users as a way to make money from cryptocurrency price changes.  
• The company used algorithms to find trading chances and make trades for users.  

node-steam-tradeoffer-manager  

• It is a JavaScript library used for working with trade offers in Steam.  
• Allows developers to interact with trade offers programmatically  
• It can help make trading bots, manage items, and automate trading on Steam.  

gekkoga  

• It is an open source platform to automate trading strategies over bitcoin markets.  
• In a genetic algorithm, we use Gekko to optimize trading strategies.  
• Define your trading strategy, and Gekko will take care of everything else.  

automated-trading  

• Traders use algorithms and computer programs to make trades, following specific rules automatically.  
• Developing trading platforms is a central aspect of automated trading.  
• Automated trading systems analyze past and current market data to find trading opportunities.  

bitimulate  

• Traders can practice their strategies in a simulated environment with past price data.  
• To see how well your strategies have worked in the past, you can run them using historical data.  
• Allows users to execute simulated trades in real time without using real funds.  

jiji2  

• Our goal is to provide a platform for algorithmic trading. You can trade and create solutions here.  
• Supports various order types like limit, stop, and market, allowing sophisticated trading strategies.  
• Provides various functions to build, test, and execute trading strategies.  

real-time-charts  

• It offers various indicators, candlestick analysis functions, and patterns.  
• Offers a comprehensive collection of technical indicators commonly used in technical analysis.  
• You can easily calculate and use these indicators in trading strategies.  

bitprophet   

• The trading platform for Binance uses chatbots as its interface.  
• Its main purpose is the automation of trading techniques.  
• You can use it to track orders or get alerts for popular technical indicators.  

react-trading-ui   

• You can use this free trading bot framework with many exchanges and trading pairs.  
• The platform has a visual interface for creating strategies and includes technical indicators.  
• It is extensible and allows users to implement custom strategies using technical indicators.  

FAQ  

1. Can I use a JavaScript library for basic stock and option trading algorithms?  

Follow these steps to use a JavaScript library for basic stock and option trading. Here is a high-level overview of the process:  

Choose a JavaScript library: Select a suitable JavaScript library for algorithmic trading. It can provide tools to access stock and option trading data and execute trades.  

Market Data Access: You can get stock and option prices from the library for up-to-date market info. Many libraries offer APIs that allow you to fetch this data.  

Strategy Development: 

1. Design and code your training strategy in JavaScript. 
2. Use indicators and averages like technical indicators to decide when to buy or sell. 
3. Ensure your strategy has clear entry and exit conditions.  

Backtesting: Use historical market data to backtest your strategy. You can use past data to simulate trades and see how well your strategy would have done.  

Risk Management: Implement risk management methods in your algorithm. To reduce losses, you can do three things: 

1. Set stop-loss levels. 
2. Diversify your investments. 
3. Adjust the size of your positions.  

Order Execution: To follow your plan, use the library's API to carry out the orders you get. It involves placing market or limit orders to buy or sell stocks and options.  

Monitoring and Logging: Set up systems to track how well your algorithm is doing. It can help you identify issues and fine-tune your strategy.  

Paper Trading: Try paper trading your algorithm before using it in a real environment. It helps simulate trades in real time without using real funds. It helps validate your strategy's effectiveness in a risk-free environment.  

Live Trading: When you are confident in how well your strategy works, you can use it for live trading. Be cautious and start with a small amount of capital to mitigate potential risks.  

Continuous Optimization: Continuously monitor and optimize your algorithmic trading strategy.  

2. What is the best way to deploy crypto bots using Javascript libraries?  

To use crypto trading bots safely, follow these steps using JavaScript libraries. This will improve performance and security. Here is a general guide to help you get started:  

Choose a Trading Library: Select a suitable JavaScript library for your bot. It integrates with the exchange you want to trade on.  

Strategy Development & Testing: Develop and test your strategy using historical data and backtesting. Ensure that your strategy is well-defined and meets your trading goals.  

Setting Up a Development Environment: Install Node JS and clone or Install libraries.  

Configuration: Configure exchange APIs and strategy.  

Backtesting and Simulation: Use backtesting to evaluate the historical performance of your strategy. Ensure your strategy aligns with your expectations before moving to live trading.  

Paper Trading: It simulates trading in a risk-free environment with fake funds. It helps validate your strategy's effectiveness without using real money.  

Monitoring & Logging: Create a system to record and log trades, performance, and mistakes. It will help you analyze your bot's behavior.  

Server and Infrastructure: Choose to host and configure the server.  

Security: Protect API keys. Set up the server's firewall and access controls to keep your bot safe.  

Deployment: Deploy your bot's code in the server and run in the deployment.  

Continuous Monitoring: To ensure your bot works well, observe how it acts and track what it does. Setting up mechanisms to handle errors and expectations gracefully.  

Scaling: Optimize your performance and multi-instance.  

3. How can I use Javascript libraries to get market data for my trading models?  

If you want to add market data to your trading models, you can use JavaScript libraries. These libraries will help you connect with exchange APIs or data providers. Here is a general guide on how to do so:  

Choose an exchange or data provider: Select an exchange or data provider. This will allow you to obtain market data for cryptocurrencies.  

Obtain API keys: Sign up for an account on the chosen exchange and obtain API keys. It would help to have API keys to authenticate your requests and access market data.  

Understand API Documentation: To understand the API documentation, read about the exchange's API. The information includes the endpoints, authentication methods, response formats, and request parameters.  

Make HTTP Requests: Use these to send HTTP requests to the exchange's API endpoints. Construct the requests according to the documentation.  

Authentication: To verify your requests, include your API keys or parameters.  

Retrieve Market data: Volume, historical candlestick, price, and order book data. Different endpoints will offer different types of data.  

Handle Responses: Handle the responses from the API requests. Extract the important data from the JSON responses for your trading model.  

Data processing: Once you have the data, you can preprocess and format it as needed for your algorithm.  

Real-Time data: Use the exchange's WebSocket connections to get current trading data. WebSocket connections can stream live market data directly to your application.  

Data frequency: To carry out your plan, you may need certain information at various times. This includes current data, records, and brief intervals. Ensure the data you are collecting matches your strategy's requirements.  

Rate limits: Attention to the API's rate limits and usage policies. Exceeding rate limits can result in temporary bans or limitations on your API access.  

Error Handling: Implement error handling to handle API request failures or unexpected data.  

4. Does Interactive Brokers API integrate well with the algorithms created by these Libraries?  

Integrating the Interactive Brokers API with JavaScript libraries can be challenging. Interactive Brokers' APIs are mainly made for Python, Java, and C++. Using Interactive Brokers' API with JavaScript apps can be more complicated. It may require more work than using officially supported languages.  

5. What are the best tools that JavaScript Algorithmic Trading Libraries offer?  

JavaScript trading libraries help traders and developers create, test and use trading strategies. Here are some of the most useful tools commonly provided by these libraries:  

Market data access: It offers functions to fetch real-time and historical market data. This data helps develop and test trading strategies.  

Technical Indicators: It includes various built-in technical indicators. It helps traders analyze price trends and make informed decisions.  

Strategy development: It offers tools to define and test trading strategies. You can make your own strategies using price patterns and technical indicators.  

Backtesting: It tests your trading strategies using historical market data. Before applying your strategies in a real situation, assessing how well they work is good.  

Paper trading: It helps practice trading strategies using virtual money. It is a safe way to test your strategies in real time without risking real money.  

Live trading: It offers APIs to execute trades on live exchanges. It is crucial to automate the execution of your strategies in real-time.  

Risk management: To manage risks, strategies include adjusting and diversifying investments. It also includes setting stop-loss and take-profit levels.  

Order execution: You can use order execution to place different orders. This includes limit and market orders. It offers functions to cancel or modify orders.  

Real-time data streaming: It allows you to react to changes in the market quickly.  

Performance metrics: You can measure how well your strategies are working. These tools analyze metrics like drawdown, profitability, and risk-adjusted returns. They calculate and measure them.  

Visualization: You can make charts and graphs to see how your trading strategy is doing.  

Configuration & customization: Customize your trading by adjusting strategies and indicators. It matches your preferences. This helps you fine-tune parameters and settings.  

Logging and reporting: It helps you keep track of executed errors, trades, and other events. It is valuable for troubleshooting and performance analysis.  

Community and support: You can ask for help, learn from others, and share ideas.