At the request of our users in the Forums that they hope to have a multi-symbol dual moving average strategy as a design reference, a multi-symbol dual moving average strategy will be implemented in today's sharing. Remarks will be written in the strategy code to facilitate your understanding and learning of the strategy, which will enable more new students of programmatic and quantitative trading get started with the strategy quickly.
Strategy Thinking
The logic of the dual moving average strategy is very simple, that is, two moving averages. A moving average with a small period (fast line) and a moving average with a large period (slow line). When the two lines have a golden cross (the fast line up crosses the slow line from bottom ), buy long, and when the two lines have a dead cross (the fast line down crosses the slow line from top ), sell short. For moving average, We use EMA.
It is just that the strategy needs to be designed for multiple symbols, so the parameters of different symbols may be different (different symbols use different moving average parameters), so it is necessary to design parameters in a "parameter array".
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Parameters are designed in form of string, with each parameter split by comma. These strings are parsed when the strategy starts running, which will be matched with the execution logic for each symbol (trading pair). Strategy polling detects the market quotes, of all symbols, the trigger of trading conditions, and chart print. After all symbols are polled once, the data is aggregated and table information is displayed on the status bar.
The strategy is super simply designed and very suitable for beginners; it is only of 200+ lines in total.
Strategy Code
// function effect: to cancel all pending orders of the current trading pair
function cancelAll(e) {
while (true) {
var orders = _C(e.GetOrders)
if (orders.length == 0) {
break
} else {
for (var i = 0 ; i < orders.length ; i++) {
e.CancelOrder(orders[i].Id, orders[i])
Sleep(500)
}
}
Sleep(500)
}
}
// function effect: to calculate the real-time profit and loss
function getProfit(account, initAccount, lastPrices) {
// account indicates the current account information; initAccount is the initial account information; lastPrices is the the latest prices of all current symbols
var sum = 0
_.each(account, function(val, key) {
// traverse the current total assets, and calculate asset currency (except USDT) difference and amount difference
if (key != "USDT" && typeof(initAccount[key]) == "number" && lastPrices[key + "_USDT"]) {
sum += (account[key] - initAccount[key]) * lastPrices[key + "_USDT"]
}
})
// return the asset profit and loss calculated by the current price
return account["USDT"] - initAccount["USDT"] + sum
}
// function effect: to generate chart configuration
function createChartConfig(symbol, ema1Period, ema2Period) {
// symbol indicates trading pair; ema1Period indicates the first EMA period; ema2Period indicates the second EMA period
var chart = {
__isStock: true,
extension: {
layout: 'single',
height: 600,
},
title : { text : symbol},
xAxis: { type: 'datetime'},
series : [
{
type: 'candlestick', // K-line date series
name: symbol,
id: symbol,
data: []
}, {
type: 'line', // EMA data series
name: symbol + ',EMA1:' + ema1Period,
data: [],
}, {
type: 'line', // EMA data series
name: symbol + ',EMA2:' + ema2Period,
data: []
}
]
}
return chart
}
function main() {
// reset all data
if (isReset) {
_G(null) // vacuum all persistently recorded data
LogReset(1) // vacuum all logs
LogProfitReset() // vacuum all profit logs
LogVacuum() // release the resource occupied by the bot database
Log("reset all data", "#FF0000") // print information
}
// parse parameters
var arrSymbols = symbols.split(",") // use comma to split the trading symbol strings
var arrEma1Periods = ema1Periods.split(",") // split the string of the first EMA parameter
var arrEma2Periods = ema2Periods.split(",") // split the string of the second EMA parameter
var arrAmounts = orderAmounts.split(",") // split the order amount of each symbol
var account = {} // the variable used to record the current asset information
var initAccount = {} // the variable used to record the initial asset information
var currTradeMsg = {} // the variable used to record whether the current BAR is executed
var lastPrices = {} // the variable used to record the latest price of the monitored symbol
var lastBarTime = {} // the variable used to record the time of the latest BAR, to judge the BAR update during plotting
var arrChartConfig = [] // the variable used to record the chart configuration information, to plot
if (_G("currTradeMsg")) { // for example, when restart, recover currTradeMsg data
currTradeMsg = _G("currTradeMsg")
Log("recover GetRecords", currTradeMsg)
}
// initialize account
_.each(arrSymbols, function(symbol, index) {
exchange.SetCurrency(symbol)
var arrCurrencyName = symbol.split("_")
var baseCurrency = arrCurrencyName[0]
var quoteCurrency = arrCurrencyName[1]
if (quoteCurrency != "USDT") {
throw "only support quoteCurrency: USDT"
}
if (!account[baseCurrency] || !account[quoteCurrency]) {
cancelAll(exchange)
var acc = _C(exchange.GetAccount)
account[baseCurrency] = acc.Stocks
account[quoteCurrency] = acc.Balance
}
// initialize the related data of chart
lastBarTime[symbol] = 0
arrChartConfig.push(createChartConfig(symbol, arrEma1Periods[index], arrEma2Periods[index]))
})
if (_G("initAccount")) {
initAccount = _G("initAccount")
Log("recover initial account information", initAccount)
} else {
// use the current asset information to initialize initAccount (variable)
_.each(account, function(val, key) {
initAccount[key] = val
})
}
Log("account:", account, "initAccount:", initAccount) // print asset information
// initialize the chart objects
var chart = Chart(arrChartConfig)
// reset chart
chart.reset()
// strategy logic of the main loop
while (true) {
// traverse all symbols, and execute the dual moving average logic one by one
_.each(arrSymbols, function(symbol, index) {
exchange.SetCurrency(symbol) // switch the trading pair to the trading pair recorded by by symbol string
var arrCurrencyName = symbol.split("_") // split trading pairs by "_"
var baseCurrency = arrCurrencyName[0] // string of base currency
var quoteCurrency = arrCurrencyName[1] // string of quote currency
// according to index, obtain the EMA paramater of the current trading pair
var ema1Period = parseFloat(arrEma1Periods[index])
var ema2Period = parseFloat(arrEma2Periods[index])
var amount = parseFloat(arrAmounts[index])
// obtain the K-line data of the current trading pair
var r = exchange.GetRecords()
if (!r || r.length < Math.max(ema1Period, ema2Period)) { // when the length of K-line is not long enough, return directly
Sleep(1000)
return
}
var currBarTime = r[r.length - 1].Time // record the current BAR timestamp
lastPrices[symbol] = r[r.length - 1].Close // record the current latest price
var ema1 = TA.EMA(r, ema1Period) // calculate EMA indicator
var ema2 = TA.EMA(r, ema2Period) // calculate EMA indicator
if (ema1.length < 3 || ema2.length < 3) { // when the length of EMA indicator array is too short, return derectly
Sleep(1000)
return
}
var ema1Last2 = ema1[ema1.length - 2] // EMA on the second last BAR
var ema1Last3 = ema1[ema1.length - 3] // EMA on the third last BAR
var ema2Last2 = ema2[ema2.length - 2]
var ema2Last3 = ema2[ema2.length - 3]
// write the chart data
var klineIndex = index + 2 * index
// traverse k-line data
for (var i = 0 ; i < r.length ; i++) {
if (r[i].Time == lastBarTime[symbol]) { // plot; update the current BAR and its indicator
// update
chart.add(klineIndex, [r[i].Time, r[i].Open, r[i].High, r[i].Low, r[i].Close], -1)
chart.add(klineIndex + 1, [r[i].Time, ema1[i]], -1)
chart.add(klineIndex + 2, [r[i].Time, ema2[i]], -1)
} else if (r[i].Time > lastBarTime[symbol]) { // plot; add BAR and its indicator
// add
lastBarTime[symbol] = r[i].Time // update the timestamp
chart.add(klineIndex, [r[i].Time, r[i].Open, r[i].High, r[i].Low, r[i].Close])
chart.add(klineIndex + 1, [r[i].Time, ema1[i]])
chart.add(klineIndex + 2, [r[i].Time, ema2[i]])
}
}
if (ema1Last3 < ema2Last3 && ema1Last2 > ema2Last2 && currTradeMsg[symbol] != currBarTime) {
// golden cross
var depth = exchange.GetDepth() // obtain the depth data of the current order book
var price = depth.Asks[Math.min(takeLevel, depth.Asks.length)].Price // select the 10th level price; taker
if (depth && price * amount <= account[quoteCurrency]) { // obtain that the depth data is normal, and the assets are enough to place an order
exchange.Buy(price, amount, ema1Last3, ema2Last3, ema1Last2, ema2Last2) // maker; buy
cancelAll(exchange) // cancel all pending orders
var acc = _C(exchange.GetAccount) // obtain the account asset information
if (acc.Stocks != account[baseCurrency]) { // detect the account assets changed
account[baseCurrency] = acc.Stocks // update assets
account[quoteCurrency] = acc.Balance // update assets
currTradeMsg[symbol] = currBarTime // record the current BAR has been executed
_G("currTradeMsg", currTradeMsg) // persistently record
var profit = getProfit(account, initAccount, lastPrices) // calculate profit
if (profit) {
LogProfit(profit, account, initAccount) // print profit
}
}
}
} else if (ema1Last3 > ema2Last3 && ema1Last2 < ema2Last2 && currTradeMsg[symbol] != currBarTime) {
// death cross
var depth = exchange.GetDepth()
var price = depth.Bids[Math.min(takeLevel, depth.Bids.length)].Price
if (depth && amount <= account[baseCurrency]) {
exchange.Sell(price, amount, ema1Last3, ema2Last3, ema1Last2, ema2Last2)
cancelAll(exchange)
var acc = _C(exchange.GetAccount)
if (acc.Stocks != account[baseCurrency]) {
account[baseCurrency] = acc.Stocks
account[quoteCurrency] = acc.Balance
currTradeMsg[symbol] = currBarTime
_G("currTradeMsg", currTradeMsg)
var profit = getProfit(account, initAccount, lastPrices)
if (profit) {
LogProfit(profit, account, initAccount)
}
}
}
}
Sleep(1000)
})
// variables in the table of status bar
var tbl = {
type : "table",
title : "account information",
cols : [],
rows : []
}
// write the data in the table structure of status bar
tbl.cols.push("--")
tbl.rows.push(["initial"])
tbl.rows.push(["current"])
_.each(account, function(val, key) {
if (typeof(initAccount[key]) == "number") {
tbl.cols.push(key)
tbl.rows[0].push(initAccount[key]) // initial
tbl.rows[1].push(val) // current
}
})
// display the status bar table
LogStatus(_D(), "\n", "profit:", getProfit(account, initAccount, lastPrices), "\n", "`" + JSON.stringify(tbl) + "`")
}
}
Strategy Backtest
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You can see ETH, LTC and ETC all had trades according to the triggers of the golden cross and death cross of moving averages.
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You can also pend on simulated bot to test.
Strategy source code: https://www.fmz.com/strategy/333783
The strategy is only used for backtest and strategy design learning, so use it in a bot with caution.