Wiki em português

Custom strategies

Code your own trading strategies using JavaScript

Build completely custom trading strategies, using JavaScript. For spot and futures trading.

Use built-in trading methods, candle and indicator data to get started quickly. For advanced usage it's possible to install and use your own additional javascript modules.

A strategy runs as an async function, executed once every time a trading pair 'cycles' in Gunbot.

Custom strategies are available in Gunbot Ultimate.

Technical info

To get a better idea of what you can and can't do, here's a few facts:

  • Gunbot takes care of the exchange connection, collecting data and making it available to a strategy

  • You save strategies in your own .js files inside the Gunbot root folder

  • There is no Gunbot specific syntax, strategy code is plain JavaScript

  • Strategy code has access to a single outside object: gb, which contains a number of trading methods and lots of data to work with

  • There are basically no restrictions to what you can do with the provided trading methods, but of course exchange defined restrictions apply (API usage rate limits, open orders limits, etc.)

  • There are no protections against double orders, or any kind of other unwanted behavior

  • Make sure to use JavaScript code compatible with Node v14.4.0

  • Using console.log() logs to the main Gunbot console logs. Expect to console log all the things

  • Code runs inside an async function, you can use the awaitkeyword to collect additional data like candle data for a different period

  • A strategy does not have to return anything, but you can use return statements to easily stop your code at a certain point

  • A strategy can use custom JavaScript modules. Save these in a folder named user_modules inside your Gunbot folder.

Custom code can be very risky!

Because external modules can be used, be extremely careful when running strategy code you did not write yourself. In theory a malicious actor can gain access over your whole system.

Strategy examples

Coding a strategy can be as difficult as you want it to be. Even with very basic JavaScript code it's possible to create complex strategies.

The following examples show a few possible ways to code simple strategies. They are silly in functionality, and are not usable for actual trading. Each next example requires a bit more JavaScript knowledge.

Some examples can lead to immediate large trades. Use them to learn, not to trade.

Example 1

  • Trade USDT-BTC

  • Invest 100 USDT per trade, allow max 1 buy order

  • Market buy when price is below lowBB and fastSma is below ema1 (using readily available indicator data)

  • After the buy order fills, place a sell order 1% above the break even price

  • Do nothing until this sell order fills

// check if there are any open orders for this pair, 
// wait until they get filled before doing anything else
if (gb.data.openOrders.length > 0){
    // print a message to the console logs
    console.log('There is an open order, waiting...')
    // stop doing things
    return
}


// balance "settings": invest 100 USDT, convert into quote amount 
// needed for calling the buy method
var baseAmount = 100
var buyAmount = baseAmount / gb.data.bid


// check if no bag is held yet AND price, 
// lowBB and moving average criteria are true
if (
    !gb.data.gotBag &&
    gb.data.bid < gb.data.lowBB &&
    gb.data.fastSma < gb.data.ema1
    ){
    // conditions are true, fire a market buy order 
    // using the amount calculated in buyAmount
    gb.method.buyMarket(buyAmount, gb.data.pairName)
}
// place a limit sell order if we have a bag
else if ( gb.data.gotBag ) {
    // fire the sell order, pass in the amount, price and pair name. 
    // price is calculated as breakEven * 1.01
    gb.method.sellLimit(gb.data.quoteBalance, gb.data.breakEven * 1.01, gb.data.pairName)
}

Example 2

  • Keep the basic workings from example 1

  • Additionally calculate a Hull Moving Average (HMA) using the last 50 candle close prices as input

  • Place the sell order 1% above bid price, at the moment bid goes above HMA

// check if there are any open orders for this pair, 
// wait until they get filled before doing anything else
if (gb.data.openOrders.length > 0) {
    // print a message to the console logs
    console.log('There is an open order, waiting...')
    // stop doing things
    return
}


// balance "settings": invest 100 USDT, convert into 
// quote amount needed for calling the buy method
var baseAmount = 100
var buyAmount = baseAmount / gb.data.bid

// define a variable to save the Hull Moving Average to
var hma

// get indicator data from tulind
// use candlesClose data as input, calculate a 50 period Hull Moving Average
gb.method.tulind.indicators.hma.indicator([gb.data.candlesClose], [50], function (err, results) {

    // tulind returns an array with hma values, 
    // assign the most recent value to the hma variable
    // notation is a bit awkward, the ".length -1" part 
    // makes it select the very last value
    hma = results[0][results[0].length - 1]
});


// check if no bag is held yet AND price, 
// lowBB and moving average criteria are true
if (
    !gb.data.gotBag &&
    gb.data.bid < gb.data.lowBB &&
    gb.data.fastSma < gb.data.ema1
) {
    // conditions are true, fire a market buy order 
    // using the amount calculated in buyAmount
    gb.method.buyMarket(buyAmount, gb.data.pairName)
}
// place a limit sell order if we have a bag
// make sure the sell method is only called when bid > hma
else if (gb.data.gotBag && gb.data.bid > hma) {
    // fire the sell order, pass in the amount, price and pair name. 
    // price is calculated as bid * 1.01
    gb.method.sellLimit(gb.data.quoteBalance, gb.data.bid * 1.01, gb.data.pairName)
}

Example 3

  • Trade USDT-BTC

  • Invest 100 USDT per trade, allow max 1 buy order

  • Code a bit more readable, assigning variables for everything used in conditionals

  • Buy when a 50 period ema has crossed over a 200 period ema, AND within at most 2 candles later the candle open price is above ema1

  • Place a sell order 5% above break even

// check if there are any open orders for this pair, 
//wait until they get filled before doing anything else
if (gb.data.openOrders.length > 0) {
    // print a message to the console logs
    console.log('There is an open order, waiting...')
    // stop doing things
    return
}


// balance "settings": invest 100 USDT, convert into 
// quote amount needed for calling the buy method
var baseAmount = 100
var buyAmount = baseAmount / gb.data.bid


// needed variables for conditional logic
// some are left undefined, to set them later when the values can be calculated
// emaCrossup is intentionally set false, 
// only to be set true when a recent crossup is detected
var gotBag = gb.data.gotBag
var bid = gb.data.bid
var ema50
var ema200
var emaCrossup = false


// get indicator data from tulind
// use candlesClose data as input, calculate a 50
// and 200 period Exponential Moving Average
gb.method.tulind.indicators.ema.indicator([gb.data.candlesClose], [50], function (err, results) {

    // tulind returns an array with ema value, 
    // save full array to be able to look for crosses later
    ema50 = results[0]
});

gb.method.tulind.indicators.ema.indicator([gb.data.candlesClose], [200], function (err, results) {

    // tulind returns an array with ema value, 
    // save full array to be able to look for crosses later
    ema200 = results[0]
});


// figure out if there was a crossover of ema50 > ema200 in the last two candles
// do this in two conditionals, once for the most recent candle 
// and once for the previous candle
// if true, save the result in the emaCrossup variable
if (
    ema50[ema50.length - 1] > ema200[ema200.length - 1] &&
    ema50[ema50.length - 2] < ema200[ema200.length - 2]
) {
    emaCrossup = true
}
else if (
    ema50[ema50.length - 2] > ema200[ema200.length - 2] &&
    ema50[ema50.length - 3] < ema200[ema200.length - 3]
) {
    emaCrossup = true
}


// buy if there is no bag, and there was a recent ema crossup 
// and bid price is above ema50
if (!gotBag && bid > ema50[ema50.length - 1] && emaCrossup) {
    // conditions are true, fire a market buy order using the amount calculated in buyAmount
    gb.method.buyMarket(buyAmount, gb.data.pairName)
}
// place a limit sell order if we have a bag
// make sure the sell method is only called when 
else if (gotBag) {
    // fire the sell order, pass in the amount, price and pair name. Price is calculated as bid * 1.01
    gb.method.sellLimit(gb.data.quoteBalance, gb.data.breakEven * 1.05, gb.data.pairName)
}

Example 4

  • Trade USDT-BTC and USDT-XRP

  • Assume you already have BTC and XRP

  • Sell 1 BTC when news about BTC tagged "bearish" appears on cryptopanic.com, containing the keyword "Korea", then place a buy order 5% below the current price

  • Sell 10000 XRP whenever news about XRP tagged "bearish" appears with the keyword "sec"

  • Do all of this in a single strategy running on a single pair in Gunbot

// require the Cryptopanic module
// install https://www.npmjs.com/package/cryptopanic in an outside folder, 
// then copy the modules to the 'user_modules' folder inside the Gunbot root folder
const _ = gb.method.require(gb.modulesPath + '/cryptopanic')

// make a connection to Cryptopanic
const cp = new Cryptopanic({ auth_token: '<API_TOKEN>' })

// creata variables to store status of detected FUD
let koreaFud
let secFud

// get data from Cryptopanic and do a simple check if any of the BTC news includes 'Korea', and if there is XRP news that included 'SEC'
// this is not a complete solution, for example it does not consider if news is old or has already been traded
cp.currencies(['BTC', 'XRP'])
    .filter('bearish')
    .fetchPosts()
    .then((articles) => {

        // loop trough articles, search if specific strings exist and save result
        articles.forEach(article => {
            // convert article object to string to easily search its contents
            const articleString = JSON.stringify(article)

            if (articleString.indexOf('Korea') > -1 && articleString.indexOf('BTC') > -1) {
                koreaFud = true
            }

            if (articleString.indexOf('SEC') > -1 && articleString.indexOf('XRP') > -1) {
                secFud = true
            }
        });

        // fire BTC orders if Korea FUD detected
        if (koreaFud) {
            // first sell 1 BTC in a market order
            gb.method.sellMarket(1, 'USDT-BTC')
                // wait for the promise to resolve, then check if the order filled before placing a limit buy 5% below current price
                .then((result) => {
                    if (result.info.status === 'FILLED') {
                        gb.method.buyLimit(1, gb.data.bid * 0.95, 'USDT-BTC')
                    }
                })
        }

        // sell XRP if SEC FUD detected
        if (secFud) {
            gb.method.sellMarket(10000, 'USDT-XRP')
        }

    })

Example 5

  • Trade USDT-BTC

  • Invest 100 USDT per trade, allow max 1 buy order

  • Strategy itself uses 3m candles, additionally fetch 60m candles

  • Only collect data and allow trades in first minute of the hour

  • Calculate TD Sequential using an external module, transform input data to the needed format

  • Place buy order when bid price > ema1, using 3m data AND TD Sequential on hourly chart has a buy setup index of 8 or higher

  • Sell when TD sequential has a sell setup index of at least 11 and price is above break even

  • Use the lodash module to simplify some code

// strategy uses two external modules: 'lodash' and 'tdsequential'
// install them with npm in an outside folder, and copy the modules to the 'user_modules' folder inside the Gunbot root folder
const _ = gb.method.require(gb.modulesPath + '/lodash')
const TDSequential = gb.method.require(gb.modulesPath + '/tdsequential')

// don't do anything unless current minute is first of the hour
const currentMinute = new Date(Date.now()).getMinutes();
if (currentMinute != 0) {
    return
}

// get 300 60m candles, and persistently save them 
// to Gunbot pair ledger - for no real reason except showing that you can do this
if (_.isNil(gb.data.pairLedger.customStratStore)){
    // create custom strategy store
    gb.data.pairLedger.customStratStore = {}
}
gb.data.pairLedger.customStratStore.myCandles = await gb.method.getCandles(300, 60, gb.data.pairName)

// balance "settings": invest 100 USDT, convert into quote amount needed for calling the buy method
const baseAmount = 100
const buyAmount = baseAmount / gb.data.bid

// to calculate TD Sequential, first transform the collected candle data to the format required by this module
let candles_60m_transformed = []
gb.data.pairLedger.customStratStore.myCandles.close.forEach(function (item, index) {
    let temp = {}
    temp.time = item.timestamp
    temp.close = item.value
    temp.high = gb.data.pairLedger.customStratStore.myCandles.high[index].value
    temp.low = gb.data.pairLedger.customStratStore.myCandles.low[index].value
    temp.open = gb.data.pairLedger.customStratStore.myCandles.open[index].value
    temp.volume = gb.data.pairLedger.customStratStore.myCandles.volume[index].value
    candles_60m_transformed.push(temp)
});

// calculate TD Sequential and only use the most recent value
const tdSequentialData = _.last(TDSequential(candles_60m_transformed))

// define trading conditions
const buyConditions = tdSequentialData.buySetupIndex >= 8 && gb.data.bid > gb.data.ema1 && !gb.data.gotBag
const sellConditions = tdSequentialData.sellSetupIndex >= 11 && gb.data.bid > gb.data.breakEven && gb.data.gotBag

// place orders if conditions are true
if (buyConditions) {
    gb.method.buyMarket(buyAmount, gb.data.pairName)
}
else if (sellConditions) {
    gb.method.sellMarket(gb.data.quoteBalance, gb.data.pairName)
}

"real" strategy examples

The following examples are more or less ready made strategies you can build upon. Note that every custom strategy will require testing on your side. Do not blindly use these examples. One aspect that's absent in the examples is checking if referenced data is actually defined before firing orders, in some cases this will be an important aspect of a custom strategy. Also consider adding error handling to your code, especially for trading methods that have less chance to succeed than simple market orders.

// require external modules
const kc = gb.method.require(gb.modulesPath + '/keltnerchannel').kc
const _ = gb.method.require(gb.modulesPath + '/lodash')

// forced short wait time between runs that do something
// mostly to reduce risk of double orders in case the exchange doesn't update balances immediately
let enoughTimePassed = false
if (_.isNil(gb.data.pairLedger.customStratStore)) {
    gb.data.pairLedger.customStratStore = {}

    if (_.isNil(gb.data.pairLedger.customStratStore.timeCheck)) {
        gb.data.pairLedger.customStratStore.timeCheck = Date.now()
    }
    else {
        if (Date.now() - gb.data.pairLedger.customStratStore.timeCheck > 8000) {
            enoughTimePassed = true
        }
    }
}

const setTimestamp = function () {
    gb.data.pairLedger.customStratStore.timeCheck = Date.now()
}

if (enoughTimePassed) {

    ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
    // collect indicator data

    let candlesReformatted = []

    gb.data.candlesClose.forEach(function (item, index) {
        let temp = {}
        temp.close = item
        temp.high = gb.data.candlesHigh[index]
        temp.low = gb.data.candlesLow[index]
        candlesReformatted.push(temp)
    });

    const keltnerChannel = kc(candlesReformatted, 20, 1, true)
    const lowestPriceLast10Candles = Math.min(...gb.data.candlesLow.slice(-10))
    const macd = gb.data.macd
    const macdSignal = gb.data.macdSignal
    let ema200
    let obv
    let obvMa21

    gb.method.tulind.indicators.ema.indicator([gb.data.candlesClose], [200], function (err, results) {
        ema200 = results[0]
    });

    gb.method.tulind.indicators.obv.indicator([gb.data.candlesClose, gb.data.candlesVolume], [], function (err, results) {
        obv = results[0]
    });

    gb.method.tulind.indicators.sma.indicator([obv], [21], function (err, results) {
        obvMa21 = results[0]
    });


    ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
    // trading conditions

    const buyAmount = parseFloat(gb.data.pairLedger.whatstrat.TRADING_LIMIT) / gb.data.bid
    const sellTarget = gb.data.breakEven + ((gb.data.breakEven - lowestPriceLast10Candles) * 1.5)
    const openSellRate = gb.data.openOrders?.[0]?.rate
    const stopTarget = openSellRate - (openSellRate - gb.data.breakEven) - ((openSellRate - gb.data.breakEven) * 0.67)

    const entryConditions = (
        !gb.data.gotBag &&
        // prev candle high > upper keltner
        gb.data.candlesHigh[gb.gb.data.candlesHigh.length - 2] > keltnerChannel.upper[keltnerChannel.upper.length - 2] &&
        // prev full candle > ema 200
        gb.data.candlesOpen[gb.data.candlesOpen.length - 2] > ema200[ema200.length - 2] &&
        gb.data.candlesHigh[gb.data.candlesHigh.length - 2] > ema200[ema200.length - 2] &&
        gb.data.candlesLow[gb.data.candlesLow.length - 2] > ema200[ema200.length - 2] &&
        gb.data.candlesClose[gb.data.candlesClose.length - 2] > ema200[ema200.length - 2] &&
        // candle open > upper keltner
        gb.data.candlesOpen[gb.data.candlesOpen.length - 1] > keltnerChannel.upper[keltnerChannel.upper.length - 1] &&
        // obv ma 21 > obv
        obvMa21[obvMa21.length - 1] > obv[obv.length - 1] &&
        // macd > signal
        macd > macdSignal
    )

    const sellConditions = (
        gb.data.gotBag &&
        gb.data.openOrders.length === 0
    )

    const stopConditions = (
        gb.data.gotBag &&
        gb.data.openOrders.length > 0 &&
        gb.data.bid < stopTarget
    )

    ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
    // order handling

    if (entryConditions) {
        gb.method.buyMarket(buyAmount, gb.data.pairName)
        setTimestamp()
    }
    else if (sellConditions) {
        gb.method.sellLimit(gb.data.quoteBalance, sellTarget, gb.data.pairName)
        setTimestamp()
    }
    else if (stopConditions) {
        gb.method.sellMarket(gb.data.quoteBalance, gb.data.pairName)
        setTimestamp()
    }

}

How to create and run a custom strategy

To create a new custom strategy, use custom as buy and sell method:

Then specify the filename with your strategy logic and place that file with your strategy logic in your Gunbot root folder - next to the executable file

The data tab gives you control over how pre calculated indicator data is generated. These are indicators you can access in your strategy. You are not limited to using these indicators, this is just easily accessible data.

To run the strategy, simply assign it to a trading pair like you would with any other Gunbot strategy.

It's recommended to disable the global cancel orders option when running a custom strategy.

Trading methods

A strategy can use a number of methods to place or cancel orders, or fetch additional OHLCV data.

Trading methods can be called as function, without waiting for it's return value.

Alternatively, when calling a method you can wait for its Promise to resolve. This way you can create a promise chain using the then() method.

Built in modules

The require module allow you to use additional javascript modules, like those freely available on NPM.

With tulind you can easily calculate your own indicator values.

Method

Returns

Extra info

gb.method.buyMarket(amount, pair)

Promise

Places a market buy order, amount in quote

gb.method.sellMarket(amount, pair)

Promise

Places a market sell order, amount in quote

gb.method.buyLimit(amount, price, pair)

Promise

Places a limit buy order, amount in quote

gb.method.sellLimit(amount, price, pair)

Promise

Places a limit sell order, amount in quote

gb.method.closeMarket(pair, amount)

Promise

Places a market close order, for futures. Amount in quote.

gb.method.closeLimit(price, pair, amount)

Promise

Places a limit close order, for futures.

Amount in quote.

gb.method.cancelOrder(orderId, pair)

Promise

Cancels a specified open order.

gb.method.getCandles(interval, period, pair)

Promise

Get additional OHLCV data.

Easiest to call using await, see usage example in the example strategies.

Beware: frequent usage can quickly lead to exceeding exchange API rate limits.

gb.method.tulind [#parameters#]

array

Get 100+ different indicators. You can use the available OHLCV data, or use your own inputs.

See the example strategies for a usage example.

gunbot.method.require(module)

function

Bring your own modules using require.

See the example strategies for a usage example.

To use an external module, first place it in a folder called 'user_modules' in the Gunbot root folder. Then require it in your strategy code, like this:

On Linux (and likely macOS): const cryptopanic = gb.method.require(gb.modulesPath + '/cryptopanic')

On Windows: const cryptopanic = gb.method.require(gb.modulesPath + '\cryptopanic')

The above assumes you have a module in a folder called cryptopanic in the user_modules folder. gb.modulesPath returns the path to whereever your gunbot folder is on your filesystem.

Available data

A strategy can use all available pair data in Gunbot, easily accessible with unique property names.

Indicators mentioned in the list below are pre calculated using the indicator settings in your Gunbot strategy. Some indicators don't have configurable strategy parameters and just use the generally accepted standard inputs for the indicator.

Property

Returns

Extra info

gb.data.pairLedger

object

Contains the complete pair ledger.

Can also be used to store and access your own persistent variables. Make sure to not overwrite existing properties.

This has the same data as you see in the pair JSON files. Most items below come from the ledger too, they are renamed for consistency and already parsed as floating point numbers.

gb.data.pairName

string

Current pair name, like USDT-BTC

gb.data.exchangeName

string

Current exchange name, like binance

gb.data.balances

object

Object with all balances on same exchange

gb.data.quoteBalance

float

Pair quote balance, like BTC balance on an USDT-BTC pair

Specific to spot trading

gb.data.baseBalance

float

Base balance, like USDT balance on an USDT-BTC pair

gb.data.onOrdersBalance

float

Quote balance value of open orders for current pair

gb.data.openOrders

array

Open orders for current pair

gb.data.orders

array

History of filled orders for current pair

gb.data.orderbook

object

First 10 bid and ask entries in orderbook, price and volume

gb.data.breakEven

float

Break even price for current spot holdings. Includes trading fees as defined in Gunbot exchange settings

gb.data.gotBag

boolean

Indicates if value of quoteBalancefor spot trading (including on orders volume) exceeds min volume to sell as defined in Gunbot strategy

gb.data.leverage

float

Leverage of current futures position

gb.data.walletBalance

float

Wallet balance. Specific to futures

gb.data.availableMargin

float

Available margin balance. Specific to futures

gb.data.maintenanceMargin

float

Maintenance margin requirement for futures account

gb.data.maxNotionalValue

float

Max notional value for futures position at current leverage

gb.data.totalPositionInitialMargin

float

Total initial position margin requirement for all current futures positions

gb.data.totalOpenOrderInitialMargin

float

Total initial margin requirement for open futures orders

gb.data.currentQty

float

Futures position size

gb.data.currentSide

string

Indicates current futures position side Possible values: long, short, none

gb.data.liquidationPrice

float

Futures position liquidation price

gb.data.period

float

Candle size as set in Gunbot strategy PERIOD setting.

This period is used for all pre calculated indicator values

gb.data.bid

float

Highest bid price

gb.data.ask

float

Lowest ask price

gb.data.ema1

float

Latest indicator value

gb.data.ema2

float

Latest indicator value

gb.data.ema3

float

Latest indicator value

gb.data.BTCUSDprice

float

Latest BTC/USD price on same exchange (or equivalent spot pair, depending on availability)

gb.data.mfi

float

Latest indicator value

gb.data.rsi

float

Latest indicator value

gb.data.lowBB

float

Latest indicator value

gb.data.highBB

float

Latest indicator value

gb.data.tenkan

float

Latest indicator value

gb.data.chikou

float

Latest indicator value

gb.data.kijun

float

Latest indicator value

gb.data.senkouSpanA

float

Latest indicator value

gb.data.senkouSpanB

float

Latest indicator value

gb.data.fastSma

float

Latest indicator value

gb.data.slowSma

float

Latest indicator value

gb.data.R1

float

Latest indicator value

gb.data.S1

float

Latest indicator value

gb.data.R2

float

Latest indicator value

gb.data.S2

float

Latest indicator value

gb.data.macd

float

Latest indicator value

gb.data.macdSignal

float

Latest indicator value

gb.data.macdHistogram

float

Latest indicator value

gb.data.stochK

float

Latest indicator value

gb.data.stochD

float

Latest indicator value

gb.data.stochRsi

float

Latest indicator value

gb.data.atr

float

Latest indicator value

gb.data.fib

object

Object with high and low Fibonacci retracement levels

gb.data.vwma

float

Latest indicator value

gb.data.diPlus

float

Latest indicator value

gb.data.diMinus

float

Latest indicator value

gb.data.adx

float

Latest indicator value

gb.data.candlesOpen

array

Array of open values for OHLCV

Sorted old to new (newest last)

gb.data.candlesHigh

array

Array of high values for OHLCV

Sorted old to new (newest last)

gb.data.candlesLow

array

Array of low values for OHLCV

Sorted old to new (newest last)

gb.data.candlesClose

array

Array of close values for OHLCV

Sorted old to new (newest last)

gb.data.candlesVolume

array

Array of volume values for OHLCV

Sorted old to new (newest last)

gb.data.candlesTimestamp

array

Array of timestamp values for OHLCV

Sorted old to new (newest last)

gb.data.candles

object

Combined object with OHLCV data

Storing data

The strategy code runs once every time Gunbot processes the pair. This means that any variable you assign inside the strategy gets reinitialized every time the code runs.

To store variables in a more persistent way, use this object: gb.data.pairLedger.customStratStore

By default customStratStore is undefined, you need to create it before storing anything in there.

Data saved here generally stays available, and persists between bot restarts. However, there is no guarantee the data stays intact - if for example the process gets killed it is possible the pair ledger gets reinitialized on next run. Gunbot native strategies are coded so that they depend as little as possible on internal persistently stored data, working with exchange provided data as much as possible possible. Consider doing the same when coding custom strategies.

Visualize strategy targets

To easily monitor a custom strategy, trading targets can be visualized as lines on the chart in the GUI. If you set any of the following targets to a price, it's automatically drawn on the chart.

gb.data.pairLedger.customBuyTarget
gb.data.pairLedger.customSellTarget
gb.data.pairLedger.customStopTarget
gb.data.pairLedger.customCloseTarget
gb.data.pairLedger.customTrailingTarget
gb.data.pairLedger.customDcaTarget

// example:
gb.data.pairLedger.customBuyTarget = 60000

Control strategy parameters from the GUI

Just like with every other strategy in Gunbot you can use pair overrides to control individual parameters of a strategy for a specific pair. This example shows how you can refer to an override value:

// Set custom pair overrides in config.js
// These show up in the GUI on the chart overview sidebar, and in the pair editor
"pairs": {
        "binance": {
            "USDT-BTC": {
                "strategy": "custom",
                "enabled": true,
                "override": {
                    "USER_SETTING": true,
                    "USER_TARGET": "2"
                }
            }
        }
    }

// Refer to them like this in your strategy code
const userSetting = gb.data.pairLedger.whatstrat.USER_SETTING
const userTarget = parseFloat(gb.data.pairLedger.whatstrat.USER_TARGET)

The whatstrat object is a merged object of all parameters in a Gunbot strategy and pair overrides, where pair overrides always take precedence over strategy values. Always make sure to parseFloat() inputs where you expect a number, because the GUI saves these as string value.

Parameters saved as pair override do not have to be known parameters in Gunbot, you can create your own settings this way.

PreviousTime series analysisNextBalance settings

Last updated