Honey framework что это
Algorithmic trading has gained a lot of popularity in the world of cryptocurrencies and, together with the all-new Python edition of the Honey Framework, it is now as easy as ever to create your own algo strategy.
So what is the Honey Framework?
The Honey Framework is a Python/NodeJs library which is the scaffolding to your algo trading strategy. The framework provides many features such as the ability to add pre-made/custom indicators, complex position management, real-time data feeds, multiple back-testing modes and a lot more.
Introducing ‘The Honey Framework’
User Interface Integration
While this alone is enough to streamline existing automated trading systems, we’ve made a concerted effort to integrate them seamlessly into the existing interface our users are familiar with.
As a result, the Honey Framework provides the ability to design custom order form layouts, trigger notifications, and render status information directly in the orders table.
With these features it becomes possible to design & execute a novel algorithmic order type alongside the built-in atomic order types we are all familiar with (Limit, Market, etc).
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The Honey Framework is an extremely powerful tool that spans across both NodeJS and Python allowing users to create completely custom order types or event driven automated trading strategies. The framework integrates naively into the Bitfinex trading platform, meaning all HF order types are usable from directly within the web UI creating a unique trading experience which can help traders get an edge.
Last September we introduced the Honey Framework UI, our simple installable application which packages together all of the HF tech into an easy to use bundle. Users can install and setup the software in as little as 3 clicks and be ready to go on Mac, Windows and even Linux!
An algorithmic order toolkit for customised order types
At Bitfinex we are dedicated to releasing rock-solid new features on the first attempt whilst constantly pushing the boundaries of the digital asset trading space.
We realize many of you are curious as to what is happening behind the scenes at Bitfinex. With this in mind, we’ve decided to release a preview of a new feature we are very excited about: The Honey Framework.
The Honey Framework is an open-source toolkit for traders to develop and implement custom order types & trading strategies on the Bitfinex platform. With this framework, users will be able to connect trading strategies running on their own servers directly to our trading engine, and control their execution via the user interface they already know.
The Honey Framework will eventually feed into an open marketplace, whereby users can share & purchase trading strategies and custom order signals from other users.
Given the ever-increasing utilisation of our API for automated trading strategies, and a constant demand for finer-grain control from our user base, we’ve designed a framework that makes it easy to create custom, complex order types.
Together with the upcoming overhaul of our trading engine, code-named Hive, this new framework will allow tech-savvy users to implement their trading strategies in JavaScript and connect them to our API & UI in a seamless manner.
Custom order types developed using this system will have access to our full suite of trading APIs during execution, including live market data and a library of indicators for making strategic decisions in real time. The possibilities are endless.
While this alone is enough to streamline existing automated trading systems, we’ve made a concerted effort to integrate them seamlessly into the existing interface our users are familiar with.
As a result, the Honey Framework provides the ability to design custom order form layouts, trigger notifications, and render status information directly in the orders table.
An example custom order type — the Market Maker enables you to simultaneously buy/sell over a specified spread
With these features it becomes possible to design & execute a novel algorithmic order type alongside the built-in atomic order types we are all familiar with (Limit, Market, etc).
While the Honey Framework is still pre-alpha, we’ve decided to release an internal demo of the major components to gather early feedback and comments from those of you that might be eager to test it.
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Today we announce the release of Honey framework UI version 3
New algo orders
Trading Terminal
– Ability to view/cancel executing algo orders
– Ability to place algo orders via UI
– Ability to place atomic orders via UI
Market Data
– Ability to create custom layout of widgets
Strategy Editor
– Ability to create custom algo strategy
– Ability to run custom strategy against backtest data
Backtest data
– Able to create a password which encrypts strategy data
UI Updates
– Complete UI re-skin
– New page “Trading Terminal”
– New page “Market Data”
– New page “Strategy Editor”
– New dynamic chart widget
– New Live orderbook widget
– New Live trades widget
– New Code editor widget (for strategy)
To install the HF UI please head here, select the latest release and install the files required for your operating system. For Windows “.exe”, for Mac “.app” and for Linux “.snap”.
To build from source go to our github repo and follow the steps in the ReadMe.
For tips on how to use the bare metal version head here and finally, for tips on how to create an advanced automated trading strategy using HF head here.
Pre-Alpha Demonstration
While the Honey Framework is still pre-alpha, we’ve decided to release an internal demo of the major components to gather early feedback and comments from those of you that might be eager to test it.
We hope you are as excited as we are to see this in production, and we’d like to include you all in the development process. As such, feel free to reach out with any ideas or critiques you may have, either via the support system or directly at [email protected] .
Stay up to date with Bitfinex announcements on Twitter, Facebook& LinkedIn.
We’ve recently open-sourced a number of the development libraries most essential to us. If you are interested in learning more about these, please visit our Github.
Join us on our mission to create the most innovative & industry-leading cryptocurrency exchange.
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An algorithmic order toolkit for customised order types
In the following tutorial we use the Python Honey Framework to create a simple trading strategy and perform both an offline and a live back-test. (Brief disclaimer, this trading strategy is purely for educational purposes and is not advice on how to create a live profitable strategy.)
In order to get the framework up and running we need to make sure we have bitfinex-api-py , bfx-hf-indicators-py and bfx-hf-strategy-py all installed into our PYTHONPATH directory.
Once we have cloned all three of these repos we can install the dependencies by running the commands:
First we need to import all of the libraries that we are going to use. The HF uses Python3 asyncio as its runtime event loop so we need to import that. We are going to use the EMA (Moving average) crossover point to detect when to enter/exit our positions so we also need to import that from the bfxindicators module that we cloned earlier.
So this creates a new strategy instance that is going to execute on the tBTCUSD trading pair using 'Exchange' (not 'Margin'). Since our trading strategy is going to act upon the crossover of the Moving average, this creates 2 instances of the EMA indicator with a length of 100 and 20. The HF will automatically pass all price updates into the provided indicators and update them in real-time.
The HF exposes a set of events that we can use to manage the state of our strategy, each event is called depending on the current open position. For example, the on_enter event is called on every price update when there are no other positions open and the on_update_short is called whenever there is a price update and a short position open.
So we are going to use the on_enter event to add the logic on how/when we should enter the market.
The above code states that on every price update we want to get the latest values from our EMA indicators. If the indicators have crossed to signal a bullish movement then open a long market position and if they signal a bearish move then open a short position. Now that we have decided how to enter the market we must decide when to exit the market to take profits.
We need to implement 2 new logic paths: on_update_long and on_update_short . The logic for both of these events will be very similar - if the indicators cross to signal the opposite direction then pull out.
Once close_position_market is called then a market order will be submitted and the strategy will return to calling on_enter on every price update.
The HF makes it really easy to back-test our strategy and offers 3 different modes: offline, with bfx-hf-data-server for historical data and on live market data with simulated order filling.
In order to back-test against offline data we need to have a file locally that contains a bunch of candles for us to load into the strategy. We can either grab this manually or use the example candles file that is located in the /examples directory in the bfx-hf-strategy-py repo.
This creates a new instance of the Executor class and loads our new strategy into its constructor. When we run the exe.offline function the candles are pushed into the strategy in the same way as it would be if the strategy was running on live data.
Once the back-test has completed, an in-depth report of our stratgey will be logged to the console displaying profit/loss, volume, each trade, fees paid and a lot more. Also, if show_chart is not disabled in the Executor constructor then matplotlib will render a visual report showing the strategy enter/exit points on the price data.
If we want to test our strategy in the live environment but aren’t ready for it make any real trades then we can also use the exec.backtestLive function. This uses the live bfxapi WebSocket but stubs out the OrderManager and uses a simulated version.
Sending a sigkill signal (pressing CTRL-C) will exit the strategy and display the same chart/report as above.
In the future when we are confident that our strategy is ready to make live trades on the markets then we can simply tell the executor to connect to the live market by calling Executor.live with our Bitfinex API KEY/SECRET.
Again, sending a sigkill will display the report/chart.
At Bitfinex we are dedicated to releasing rock-solid new features on the first attempt whilst constantly pushing the boundaries of the digital asset trading space.
We realize many of you are curious as to what is happening behind the scenes at Bitfinex. With this in mind, we’ve decided to release a preview of a new feature we are very excited about: The Honey Framework.
The Honey Framework is an open-source toolkit for traders to develop and implement custom order types & trading strategies on the Bitfinex platform. With this framework, users will be able to connect trading strategies running on their own servers directly to our trading engine, and control their execution via the user interface they already know.
The Honey Framework will eventually feed into an open marketplace, whereby users can share & purchase trading strategies and custom order signals from other users.
An Algorithmic Order Framework
Given the ever-increasing utilisation of our API for automated trading strategies, and a constant demand for finer-grain control from our user base, we’ve designed a framework that makes it easy to create custom, complex order types.
Together with the upcoming overhaul of our trading engine, code-named Hive, this new framework will allow tech-savvy users to implement their trading strategies in JavaScript and connect them to our API & UI in a seamless manner.
Custom order types developed using this system will have access to our full suite of trading APIs during execution, including live market data and a library of indicators for making strategic decisions in real time. The possibilities are endless.
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