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bfx-hf-backtest

HF backtesting logic module

  • 2.0.0
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Bitfinex Honey Framework Backtesting Tools for Node.JS

Build Status

This repo provides an interface for executing backtests using either offline data, or a bfx-hf-data-server instance for historical Bitfinex market data.

Features

  • Offline backtest execution with user-supplied trade & candle data
  • Online backtest execution with data from bfx-hf-data-server
  • Simulates trades within a candle if none are provided

Installation

npm i --save bfx-hf-backtest

Quickstart

const HFS = require('bfx-hf-strategy')
const HFBT = require('bfx-hf-backtest')
const Strategy = ... // strategy instance
const candles = [/* ... */]

const candleKey = HFS.candleMarketDataKey({
  symbol: SYMBOLS.BTC_USD,
  tf: TIME_FRAMES.ONE_HOUR
})

HFBT.execOffline(strat, {
  trades: {},
  candles: {
    [candleKey]: candles,
  }
}).then((btState) => {
  const { trades = [] } = btState

  // analyze backtest trades...
})

Docs

Refer to docs/exec.md for JSDoc-generated API documentation, and the examples/ folder for executable examples.

Examples

Offline Backtests

To execute a backtest of a trading strategy using historical data, the execOffline method is provided which will run the strategy against each trade & candle in-order by timestamp:

const HFS = require('bfx-hf-strategy')
const HFBT = require('bfx-hf-backtest')

const EMAStrategy = require('bfx-hf-strategy/examples/ema_cross')
const { Candle } = require('bfx-api-node-models')
const { SYMBOLS, TIME_FRAMES } = require('bfx-hf-util')
const rawCandleData = require('./btc_candle_data.json')

// During real execution, candles can arrive from any market/at any time (if
// sub'ed to multiple time frames); hence, each candle must include its origin
// symbol/time frame pair.
const market = {
  symbol: SYMBOLS.BTC_USD,
  tf: TIME_FRAMES.ONE_HOUR
}

const candleKey = HFS.candleMarketDataKey(market)
const strat = EMAStrategy(market)
const candles = rawCandleData
  .sort((a, b) => a[0] - b[0])
  .map(c => ({
    ...(new Candle(c).toJS()),
    ...market // attach market data
  }))

const run = async () => {
  await HFBT.execOffline(strat, {
    trades: {},
    candles: {
      [candleKey]: candles,
    }
  })
}

try {
  run()
} catch (e) {
  console.error(e)
}
Online Backtests

Online backtests are executed a running bfx-hf-data-server instance, which will automatically synchronize historical data as needed and pass it to the backtesting logic:

const HFBT = require('bfx-hf-backtest')
const EMAStrategy = require('bfx-hf-strategy/examples/ema_cross')
const { SYMBOLS, TIME_FRAMES } = require('bfx-hf-util')

const now = Date.now()
const market = {
  symbol: SYMBOLS.XMR_USD,
  tf: TIME_FRAMES.ONE_MINUTE
}

const strat = EMAStrategy(market)
const run = async () => {
  await HFBT.execOnline([strat], {
    exchange: 'bitfinex',
    from: now - (2 * 24 * 60 * 60 * 1000),
    to: now,
    trades: true,
    candles: true,
    ...market
  })
}

try {
  run()
} catch (e) {
  console.error(e)
}
Bitfinex Terminal Data

Bitfinex Terminal data can be used to run a strategy. There is also a full blog article on this.

examples/

const strat = EMAStrategy(market)
const from = get24HoursAgo(new Date())
const to = new Date()

const { exec, onEnd } = await HFBT.execStream(strat, market, {
  from,
  to
  // isTrade: null, // you can pass a custom `isTrade` frunction here in options
})

let btState

// db is a bitfinex terminal hyperbee stream
const stream = db.createReadStream({
  gte: { candle: '5m', timestamp: from },
  lte: { candle: '5m', timestamp: to }
})

for await (const data of stream) {
  const { key, value } = data
  btState = await exec(key, value)
}

await onEnd(btState)

For the full blog article, visit the Bitfinex Terminal repo

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create a new Pull Request

Keywords

FAQs

Package last updated on 14 Jan 2021

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