bfx-hf-backtest

Bitfinex Honey Framework Backtesting Tools for Node.JS


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

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* 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

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``bash
npm i --save bfx-hf-backtest
`

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`js
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...
})
`

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

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#### 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:

`js
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:

`js
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/
`js
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

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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