GoCryptoTrader Backtester: Backtester package
This backtester package is part of the GoCryptoTrader codebase.
This is still in active development
You can track ideas, planned features and what's in progress on our GoCryptoTrader Kanban board.
Join our slack to discuss all things related to GoCryptoTrader! GoCryptoTrader Slack
GoCryptoTrader Backtester
An event-driven backtesting tool to test and iterate trading strategies using historical or custom data.
Features
- Works with all GoCryptoTrader exchanges that support trade/candle retrieval. See candle readme and trade readme for supported exchanges
- CSV data import
- Database data import
- Proof of concept live data running
- Shopspring decimal implementation to track stats more accurately
- Can run strategies against multiple cryptocurrencies
- Can run strategies that can assess multiple currencies simultaneously to make complex decisions
- Dollar cost strategy example strategies
- RSI example strategy
- MFI example strategy
- Rules customisation via config
.strat
files
- Strategy config builder application
- Strategy customisation without requiring recompilation. For example, customising RSI high, low and length values via config
.strat
files.
- Report generation
- Portfolio manager to help size orders based on config rules, risk and candle volume
- Order manager to place orders with customisable slippage estimator
- Helpful statistics to help determine whether a strategy was effective
- Compliance manager to keep snapshots of every transaction and their changes at every interval
- Exchange level funding allows funding to be shared across multiple currency pairs and to allow for complex strategy design
- Fund transfer. At a strategy level, transfer funds between exchanges to allow for complex strategy design
- Backtesting support for futures asset types
- Example cash and carry spot futures strategy
- Long-running application as a GRPC server
- Custom strategy plugins
- Live data source trading. Traders can move their back tested strategies and use them against current live data
Planned Features
We welcome pull requests on any feature for the Backtester! We will be especially appreciative of any contribution towards the following planned features:
Feature |
Description |
Perpetual futures support |
Accounting for hourly funding rates in user's overall positions allows for much greater strategic depth |
Margin borrowing support |
Allowing strategies to utilise margin borrowing to have larger positions and handling borrow rate payments |
Leverage support |
Leverage is a good way to enhance profit and loss and is important to include in strategies |
Live ticker data |
A potential feature as live trading works off candle data which is only processed at intervals. Adding ticker data as a strategic source allows for faster decision making |
Live orderbook data |
Processing orders based off the latest orderbook data allows for much more accurate order placement and reduces surprise slippage |
Enhance config-builder |
Create an application that can create strategy configs in a more visual manner and execute them via GRPC to allow for faster customisation of strategies |
Save Backtester results to database |
This will allow for easier comparison of results over time |
Backtester result comparison report |
Providing an executive summary of Backtester database results |
How does it work?
- The application will load a
.strat
config file as specified at runtime
- The
.strat
config file will contain
- Start & end dates
- The strategy to run
- The candle interval
- Where the data is to be sourced (API, CSV, database, live)
- Whether to use trade or candle data (readme)
- A nickname for the strategy (to help differentiate between runs/configs using the same strategy)
- The currency/currencies to use
- The exchange(s) to run against
- See readme for a breakdown of all config features
- The GoCryptoTrader Backtester will retrieve the data specified in the config (readme)
- The data is converted into candles and each candle is streamed as a data event.
- The data event is analysed by the strategy which will output a purchasing signal such as
BUY
, SELL
or DONOTHING
(readme)
- The purchase signal is then processed by the portfolio manager (readme) which will size the order (readme) and assess risk (readme) before sending it to the exchange
- The exchange order event handler will size to the candle data and run a slippage estimator (readme) and place the order (readme)
- Upon an order being placed, the order is snapshot for analysis in both the statistics package (readme) and the report package (readme)
Cool story, how do I use it?
To run the application using the provided dollar cost average strategy, simply run go run .
from gocryptotrader/backtester
. An output of the results will be put in the results
folder.
How do I create my own config?
There is a config generating helper application under /backtester/config/configbuilder
to help you create a .strat
file. Read more about it here. There are also a number of tests under /config/config_test.go
which generate configs into the examples
folder, which if you have code knowledge, can write your own configs programmatically.
How do I create my own strategy?
Creating strategies requires programming skills. Here is a readme on the subject. After reading the readmes, please review the strategies here to gain an understanding on how to write your own.
How does it work technically?
- The readmes linked in the "How does it work" covers the main parts of the application.
- If you are still unsure, please raise an issue, ask a question in our Slack or open a pull request
- Here is an overview
Important notes
- This application is not considered production ready and you may experience issues
- If you encounter any issues, you can raise them in our Slack channel or via Github issues
- Past performance is no guarantee of future results
- While an experimental feature, it is not recommended to ever use live trading and real orders
- Past performance is no guarantee of future results
Contribution
Please feel free to submit any pull requests or suggest any desired features to be added.
When submitting a PR, please abide by our coding guidelines:
- Code must adhere to the official Go formatting guidelines (i.e. uses gofmt).
- Code must be documented adhering to the official Go commentary guidelines.
- Code must adhere to our coding style.
- Pull requests need to be based on and opened against the
master
branch.
Donations
If this framework helped you in any way, or you would like to support the developers working on it, please donate Bitcoin to:
bc1qk0jareu4jytc0cfrhr5wgshsq8282awpavfahc