Question 1

How to set up backtesting in Igthorn?

Accepted Answer

Follow the multi-step process: initialize an empty database with MIX_ENV=backtesting, import historical data using the CLI script with date and symbol parameters, start the app in backtesting environment, and enable trading via the UI. The README provides specific commands for loading over 2.8 million events from June 2019.

Question 2

Igthorn vs other Elixir trading bots: which should I use?

Accepted Answer

Igthorn is a comprehensive boilerplate with backtesting and a web UI, but it's archived, so for active projects, consider newer alternatives that are maintained. It's best for learning or as a starting point to fork, but not for production without significant modifications due to lack of updates.

Question 3

Does Igthorn support real-time trading on exchanges other than Binance?

Accepted Answer

No, Igthorn currently only supports Binance for live data streaming. The README mentions plans to implement different exchanges for features like arbitrage, but this is not completed, so you'd need to extend the codebase yourself to add other exchange integrations.

Question 4

How to add a custom trading strategy to Igthorn?

Accepted Answer

Use the included naive strategy as a template in the Hefty backend. Implement your strategy by following the same structure, integrating it with the streaming and trading processes. The modular umbrella design allows for adding new strategies alongside the existing one, though documentation is limited.

Question 5

Is Igthorn suitable for high-frequency trading?

Accepted Answer

While Igthorn can handle millions of events in backtesting, its live streaming performance for high-frequency trading isn't detailed. The use of Elixir processes and PostgreSQL may introduce latency, so it's not optimized for ultra-low-latency applications without further tuning and benchmarking.

Question 6

What are the system requirements to run Igthorn?

Accepted Answer

Requires Docker for database services, Elixir and Phoenix installed, and Node.js for frontend assets. The setup involves multiple dependencies and a PostgreSQL database, so sufficient memory and storage are needed, especially for large historical datasets like the 2.8 million events example.

Igthorn

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