Heads up: This is a framework in development, with only basic functionality.

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.

Usage

Basic example:

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:

// 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.

BackTester - general test case, bundles the following elements into a single test
EventHandler - the different types of events, which travel through this system - data event, signal event, order event and fill event
DataHandler - interface to a set of data, e.g historical quotes, fundamental data, dividends etc.
StrategyHandler - generates a buy/sell signal based on the data
PortfolioHandler - generates orders and manages profit & loss
- (SizeHandler) - manages the size of an order
- (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
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.

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
bt - Flexible Backtesting for Python - an inspiration for algorithm building blocks and a strategy/assets tree

General information on Quantitative Finance

Quantocracy - forum for quant news
QuantStart - articels and tutorials about quant finance

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