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https://github.com/dirkolbrich/gobacktest
event-driven backtesting framework written in golang
https://github.com/dirkolbrich/gobacktest
algorithmic-trading backtesting-frameworks finance financial-analysis go golang
Last synced: 4 months ago
JSON representation
event-driven backtesting framework written in golang
- Host: GitHub
- URL: https://github.com/dirkolbrich/gobacktest
- Owner: gobacktest
- License: mit
- Archived: true
- Created: 2017-07-26T05:54:17.000Z (over 7 years ago)
- Default Branch: main
- Last Pushed: 2023-10-11T12:34:18.000Z (about 1 year ago)
- Last Synced: 2024-05-22T15:31:18.467Z (7 months ago)
- Topics: algorithmic-trading, backtesting-frameworks, finance, financial-analysis, go, golang
- Language: Go
- Homepage:
- Size: 1.03 MB
- Stars: 224
- Watchers: 14
- Forks: 57
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
- awesome-go-quant - gobacktest - event-driven backtesting framework written in golang (Golang / Trading & Backtesting)
README
[](http://godoc.org/github.com/dirkolbrich/gobacktest)
[](https://travis-ci.org/dirkolbrich/gobacktest)
[](https://coveralls.io/github/dirkolbrich/gobacktest?branch=master)
[](https://goreportcard.com/report/github.com/dirkolbrich/gobacktest)
[](/LICENSE.md)
_**Heads up:** This project is dead. It fought well, but died on the battlefield of abandoned open source projects. It was a good project. It will be remembered for decades to come._
---
# gobacktest - Fundamental stock analysis backtesting
An event-driven backtesting framework to test stock trading strategies based on fundamental analysis. Preferably this package will be the core of a backend service exposed via a REST API. Currently it has only core functionality.
## Usage
Basic example:
```golang
package main
import (
"github.com/dirkolbrich/gobacktest"
"github.com/dirkolbrich/gobacktest/data"
"github.com/dirkolbrich/gobacktest/strategy"
)
func main() {
// initiate a new backtester
test := gobacktest.New()
// define and load symbols
symbols := []string{"TEST.DE"}
test.SetSymbols(symbols)
// create a data provider and load the data into the backtest
data := &data.BarEventFromCSVFile{FileDir: "../testdata/test/"}
data.Load(symbols)
test.SetData(data)
// choose a strategy
strategy := strategy.BuyAndHold()
// create an asset and append it to the strategy
strategy.SetChildren(gobacktest.NewAsset("TEST.DE"))
// load the strategy into the backtest
test.SetStrategy(strategy)
// run the backtest
test.Run()
// print the results of the test
test.Stats().PrintResult()
}
```
More example tests are in the `/examples` folder.
The single parts of the backtester can be set independently:
```golang
// initiate new backtester
test := &Backtest{}
// set the portfolio with initial cash and a default size and risk manager
portfolio := &gobacktest.Portfolio{}
portfolio.SetInitialCash(10000)
sizeManager := &gobacktest.Size{DefaultSize: 100, DefaultValue: 1000}
portfolio.SetSizeManager(sizeManager)
riskManager := &gobacktest.Risk{}
portfolio.SetRiskManager(riskManager)
test.SetPortfolio(portfolio)
// create a new strategy with an algo stack
strategy := gobacktest.NewStrategy("basic")
strategy.SetAlgo(
algo.CreateSignal("buy"), // always create a buy signal on a data event
)
// create an asset and append to strategy
strategy.SetChildren(gobacktest.NewAsset("TEST.DE"))
// load the strategy into the backtest
test.SetStrategy(strategy)
// create an execution provider and load it into the backtest
exchange := &gobacktest.Exchange{
Symbol: "TEST",
Commission: &FixedCommission{Commission: 0},
ExchangeFee: &FixedExchangeFee{ExchangeFee: 0},
}
test.SetExchange(exchange)
// choose a statistic and load into it the backtest
statistic := &gobacktest.Statistic{}
test.SetStatistic(statistic)
```
## Dependencies
None so far. Only the standard library.
## Basic components
These are the basic components of an event-driven framework.
1. BackTester - general test case, bundles the following elements into a single test
2. EventHandler - the different types of events, which travel through this system - data event, signal event, order event and fill event
3. DataHandler - interface to a set of data, e.g historical quotes, fundamental data, dividends etc.
4. StrategyHandler - generates a buy/sell signal based on the data
5. PortfolioHandler - generates orders and manages profit & loss
+ (SizeHandler) - manages the size of an order
+ (RiskHandler) - manages the risk allocation of a portfolio
6. ExecutionHandler - sends orders to the broker and receives the “fills” or signals that the stock has been bought or sold
7. StatisticHandler - tracks all events during the backtests and calculates useful statistics like equity return, drawdown or sharp ratio etc., could be used to replay the complete backtest for later reference
+ (ComplianceHandler) - tracks and documents all trades to the portfolio for compliance reasons
## Infrastructure example
An overviev of the infrastructure of a complete backtesting and trading environment. Taken from the production roadmap of [QuantRocket](https://www.quantrocket.com/#product-roadmap).
- General
+ API gateway
+ configuration loader
+ logging service
+ cron service
- Data
+ database backup and download service
+ securities master services
+ historical market data service
+ fundamental data service
+ earnings data service
+ dividend data service
+ real-time market data service
+ exchange calendar service
- Strategy
+ performance analysis service - tearsheet
- Portfolio
+ account and portfolio service
+ risk management service
- Execution
+ trading platform gateway service
+ order management and trade ledger service
+ backtesting and trading engine
---
## Resources
### Articles
These links to articles are a good starting point to understand the intentions and basic functions of an event-driven backtesting framework.
- Initial idea via a blog post [Python For Finance: Algorithmic Trading](https://www.datacamp.com/community/tutorials/finance-python-trading#backtesting) by Karlijn Willems [@willems_karlijn](https://twitter.com/willems_karlijn).
- Very good explanation of the internals of a backtesting system by Michael Halls-Moore [@mhallsmoore](https://twitter.com/mhallsmoore) in the blog post series [Event-Driven-Backtesting-with-Python](https://www.quantstart.com/articles/Event-Driven-Backtesting-with-Python-Part-I).
### Other backtesting frameworks
- [QuantConnect](https://www.quantconnect.com)
- [Quantopian](https://www.quantopian.com)
- [QuantRocket](https://www.quantrocket.com) - in development, available Q2/2018
- [Quandl](https://www.quandl.com) - financial data
- [QSTrader](https://www.quantstart.com/qstrader) - open-source backtesting framework from [QuantStart](https://www.quantstart.com)
- [bt - Flexible Backtesting for Python](http://pmorissette.github.io/bt/) - an inspiration for algorithm building blocks and a strategy/assets tree
### General information on Quantitative Finance
- [Quantocracy](http://quantocracy.com) - forum for quant news
- [QuantStart](https://www.quantstart.com) - articels and tutorials about quant finance