Trading Intelligence & Signals

Quick Start

How do you identify key market metrics that are critical to deriving useful insights? Trading intelligence can be a great way to leverage markets for your advantage and find opportunities that would otherwise be missed. We’ve built our APIs to easily access digital asset metrics and value allowing for simple integration into your applications.

We'll need a few things to accomplish what we're after:

  • Historical market data for backtesting strategies
  • Real-time market data to respond to market signals
  • Blockchain data to watch DEXs and other metrics that could affect prices
Backtesting with historical market data

First you'll want to come up with a strategy and define some rules on how your code will operate. What we'll do is get historical market prices across all available exchanges and then simulate our signals on this data as if it's in real-time.

Try out the example on runkit!

Real-time Market Data

Once we've adjusted the parameters and are confident in our code, we'll now want to hook it up to real-time market data and start executing trades. Note: Amberdata provides market data, but to execute a trade you'll need to use the exchange's API. Using our comprehensive market data your code will be able to spot signals in the markets.

Try out the example on runkit!

More context with Blockchain data

One final thing we can do to get an even better edge would be to combine blockchain and market data to find correlations between blockchain events and market prices. This would give our code a predictive advantage over other businesses that work only with market data. We can use our historical data for backtesting and then start integrating real-time blockchain data into our code and watch it's performance.

Try out the example on runkit!