BitVision is a real-time charting and trading dashboard for Bitstamp that works entirely in the terminal. It comes with an automated trading bot that uses machine learning to forecast price movements and place risk-adjusted daily trades. Unlike other systems, there’s no need to host a server or spin up a Docker container or edit tedious setup files. After installing, simply run $ bitvision to start using the dashboard.

Key Features of BitVision

• A daily exchange rate graph
• Real-time monitoring of Bitcoin-related news, technical indicators, and blockchain network data
• Logging of previous transactions and your current account balance
• Portfolio metrics, including your Sharpe Ratio, buy and sell accuracy, net profit, and returns
• Easy toggling of automated trading and the ability to manually place orders

Disclaimer: BitVision is still in alpha. Some of the trading features are buggy and not fully tested; see all known bugs here. Use at your own risk!

Installation

Requires Node v10+ and Python 3.7. Install using npm:

$ npm i bitvision -g

Usage

Run $ bitvision to boot up the dashboard. If you want to enable trading, follow these instructions to acquire a Bitstamp API key and secret:

1. Login to your Bitstamp account
2. Click on Security – API Access
3. Select the following permissions for your access key:
   • Account Balance
   • User Transactions
   • Open Orders
   • Buy Instant/Limit Order
   • Sell Instant/Limit Order
4. Click on the Generate Key button and make sure to store your secret in a secure place.
5. Click Activate.
6. Go to your email and click on the link sent by Bitstamp to activate the API key.

Once activated, just press L in the dashboard, and a modal will pop up asking for your customer ID, API key, and secret. These will be stored locally on your machine, so be sure to keep them safe.

How It Works

The command-line interface is built on the Blessed.js library, while the trading and charting architecture is built on the SciPy stack. Think of BitVision as a highly efficient factory for trading data – it receives raw materials (data from various sources), processes them (calculates insights via machine learning), and produces finished goods (trade recommendations) ready for packaging and shipping (executing trades).

At the heart of BitVision is a local directory of JSON files called the Store, which keeps track of everything from credentials to user preferences. When you trigger an action, like placing an order, it’s like pulling a lever in the factory that starts a sub-assembly line to process your request.

Automated Trading Engine

Behind the scenes, the engine uses a Logistic Regression model that’s trained on historical data. When the system is toggled on, a daily schedule (like a factory shift) is set to retrain the model, predict changes in prices, and make buy or sell orders based on predictions.

Technical Indicators

Technical indicators serve as tools in our factory that help streamline the production line. They help identify trends and patterns that the machine learning model can learn from to make more accurate predictions. These include:

• Rate of Change Ratio (ROCR)
• Average True Range (ATR)
• On-Balance Volume (OBV)
• Triple Exponential Moving Average (TRIX)
• Momentum (MOM)
• Average Directional Index (ADR)
• Williams %R (WILLR)
• Relative Strength Index (RSI)
• Moving Average Convergence Divergence (MACD)
• Exponential Moving Average (EMA)

Whether a market is classified as efficient or not, these indicators remain valuable for traders and the underlying model in making informed decisions.

Troubleshooting

If you encounter issues while using BitVision, here are some quick solutions to common problems:

• Check your Node and Python versions; ensure they are installed correctly.
• Verify your API key and secret for accuracy.
• Ensure that your network is stable for real-time data updates.
• If the BitVision dashboard doesn’t launch, double-check the installation command and try reinstalling.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.