A strategy based on historical data

Now I will not talk about the strategy itself, but about the tool that allows its use. Recently, I was involved in the development of an interesting product designed for trading. Its main feature is that an analysis of historical data from previous years is used to make a decision on issuing a warrant.

You may not have known (or perhaps not even thought about it), but open source data is a powerful force. And whoever knows how to apply it correctly is simply doomed to success. Since any blockchain is open information, there are services that collect and process data from decentralized networks. Over the years, the archives have accumulated a lot of information about stock exchange events, which indicate the volume of transactions, external conditions, the frequency of operations, and much more.

And so there were enthusiasts who decided to use this historical data to develop their own trading strategy. In fact, everything is quite simple:

We analyze conditions on the stock exchange (rate, dynamics, volumes, etc.);

We compare with previous indicators from a specific period of time;

In case of coincidences with successful transactions, we buy or sell cryptocurrency.

Of course, data analysis is important, but not decisive for decision-making. The bot developed by our team takes into account a number of other conditions of the strategy algorithm, but most of them are purely mathematical formulas.

An important task was to get the necessary historical data somewhere, and after a long analysis, we chose the TradingView service. It's just a gorgeous database and APIs available for integration. The validation cycle is only a fraction of a second, after which the bot receives enough data to make an automatic choice.

Our solution is designed for crypto exchanges Kraken and Coinbase, but it is not difficult to expand this list. Testing showed good results that even exceeded the expectations of customers of the cryptobot.