README
¶
Heads up: This is a framework in development, with only limited basic functionality. A lot of the features are still missing.
You can read along and follow the development of this project. And if you like, give me some tips or discussion points for improvement.
gobacktest - Fundamental stock analysis backtesting
My attempt to create a 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.
Usage
Example tests are in the /examples folder.
package main
import (
"github.com/dirkolbrich/gobacktest/pkg/backtest"
"github.com/dirkolbrich/gobacktest/pkg/data"
"github.com/dirkolbrich/gobacktest/pkg/strategy"
)
func main() {
// we need a new blanc backtester
test := backtest.New()
// define the symbols to be tested and load them into the backtest
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)
// set the portfolio with initial cash and a default size and risk manager
portfolio := &backtest.Portfolio{}
portfolio.SetInitialCash(10000)
sizeManager := &backtest.Size{DefaultSize: 100, DefaultValue: 1000}
portfolio.SetSizeManager(sizeManager)
riskManager := &backtest.Risk{}
portfolio.SetRiskManager(riskManager)
test.SetPortfolio(portfolio)
// create a strategy provider and load it into the backtest
strategy := &strategy.Basic{}
test.SetStrategy(strategy)
// create an execution provider and load it into the backtest
exchange := &backtest.Exchange{}
test.SetExchange(exchange)
// choose a statistic and load into the backtest
statistic := &backtest.Statistic{}
test.SetStatistic(statistic)
// run the backtest
test.Run()
}
Dependencies
The internal calculations use the github.com/shopspring/decimal package for arbitrary-precision fixed-point decimals.
Make sure to install it into your $GOPATH with
go get github.com/shopspring/decimal
Basic components
These are the basic components of an event-driven framework.
- BackTester - general test case, bundles the follwing elements into a single test
- DataHandler - interface to a set of data, e.g historical quotes, fundamental data etc.
- StrategyHandler - generates a buy/sell signal based on the data
- PortfolioHandler - generates orders and manages profit & loss
- (RiskHandler) - manages the risk allocation of a portfolio
- ExecutionHandler - sends orders to the broker and receives the “fills” or signals that the stock has been bought or sold
- EventHandler - the different types of events, which travel through this system - data event, signal event, order event and fill event
Infrastructure example
An overviev of the infrastructure of a complete backtesting and trading environment. Taken from the production roadmap of QuantRocket.
- 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 by Karlijn Willems @willems_karlijn.
- Very good explanation of the internals of a backtesting system by Michael Halls-Moore @mhallsmoore in the blog post series Event-Driven-Backtesting-with-Python.
Other backtesting frameworks
- QuantConnect
- Quantopian
- QuantRocket - in development, available Q2/2018
- Quandl - financial data
- QSTrader - open-source backtesting framework from QuantStart
General information on Quantitative Finance
- Quantocracy - forum for quant news
- QuantStart - articels and tutorials about quant finance
Directories