At the request of community users who want to have a multi-variety double-EMA strategy for design reference. In this article, we will implement a multi-variety double-EMA strategy. Comments will be written on the strategy code to for convenient understanding and learning. Let more newcomers of programming and quantitative trading get a quick start.

### Strategy ideas

The logic of the double-EMA strategy is very simple, that is, two EMAs. An EMA (fast line) with a small parameter period and an EMA (slow line) with a large parameter period. If the two lines have a golden cross (the fast line goes through the slow line from the bottom to the top), then we buy and go long; and if the two lines have a dead cross (the fast line goes through the slow line from the top to the bottom), then we sell and go short. We use EMA here.

However, the strategy should be designed as multi-variety, so the parameters of each variety may be different (different varieties use different EMA parameters), so a "parameter group" method should be used to design parameters.

The parameters are designed in the string form, with each parameter comma separated. Parse these strings when the strategy starts running. The execution logic match to each variety (trading pair). The strategy rotated detects the market of each variety, the triggering of trading conditions, chart printing, etc. After all varieties are rotated once, summarize the data and display the table information on the status bar.

The strategy is designed to be very simple and suitable for newcomers' learning, with only 200+ lines of code in total.

### Strategy code

```// Function: cancel all takers 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)
}
}

// Functionn: calculate the profit/loss in real-time
function getProfit(account, initAccount, lastPrices) {
// account is the current account information, initAccount is the initial account information, lastPrices is the latest price of all varieties
var sum = 0
_.each(account, function(val, key) {
// Iterate through all current assets, calculate the currency difference of assets other than USDT, and the amount difference
if (key != "USDT" && typeof(initAccount[key]) == "number" && lastPrices[key + "_USDT"]) {
sum += (account[key] - initAccount[key]) * lastPrices[key + "_USDT"]
}
})
// Return to the profit and loss of the asset based on the current prices
return account["USDT"] - initAccount["USDT"] + sum
}

// Function: generate chart configuration
function createChartConfig(symbol, ema1Period, ema2Period) {
// symbol is the trading pair, ema1Period is the first EMA period, ema2Period is the second EMA period
var chart = {
__isStock: true,
extension: {
layout: 'single',
height: 600,
},
title : { text : symbol},
xAxis: { type: 'datetime'},
series : [
{
type: 'candlestick',    // K-line data 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)            // Clear data of all persistent records
LogReset(1)         // Clear all logs
LogProfitReset()    // Clear all return logs
LogVacuum()         //Release the resources occupied by the real bot database
Log("Reset all data", "#FF0000")   // Print messages
}

// Parameter analysis
var arrSymbols = symbols.split(",")             // Comma-separated string of trading varieties
var arrEma1Periods = ema1Periods.split(",")     // Parameter string for splitting the first EMA
var arrEma2Periods = ema2Periods.split(",")     // Parameter string for splitting the second EMA
var arrAmounts = orderAmounts.split(",")        // Splitting the amount of orders placed for each variety
var account = {}                                // Variables used for recording current asset messages
var initAccount = {}                            // Variables used for recording initial asset messages
var currTradeMsg = {}                           // Variables used for recording whether current BAR trades
var lastPrices = {}                             // Variables used for recording the latest price of monitored varieties
var lastBarTime = {}                            // Variable used for recording the time of the last BAR, used to judge the update of BAR when drawing
var arrChartConfig = []                         // Used for recording chart configuration message and draw

}

// 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 chart-related data
lastBarTime[symbol] = 0
arrChartConfig.push(createChartConfig(symbol, arrEma1Periods[index], arrEma2Periods[index]))
})
if (_G("initAccount")) {
initAccount = _G("initAccount")
Log("Restore initial account records", initAccount)
} else {
// Initialize the initAccount variable with the current asset information
_.each(account, function(val, key) {
initAccount[key] = val
})
}
Log("account:", account, "initAccount:", initAccount)   // Print asset information

// Initialize the chart object
var chart = Chart(arrChartConfig)
// Chart reset
chart.reset()

// Strategy main loop logic
while (true) {
// Iterate through all varieties and execute the double-EMA logic one by one
_.each(arrSymbols, function(symbol, index) {
exchange.SetCurrency(symbol)               // Switch the trading pair to the trading pair of symbol string record
var arrCurrencyName = symbol.split("_")    // Split the trading pairs with the "_" symbol
var baseCurrency = arrCurrencyName[0]      // String for trading currencies
var quoteCurrency = arrCurrencyName[1]     // String for denominated currency

// Obtain the EMA parameters of the current trading pair according to the index
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)) {  // Return directly if K-line length is insufficient
Sleep(1000)
return
}
var currBarTime = r[r.length - 1].Time         // Record the current BAR timestamp
lastPrices[symbol] = r[r.length - 1].Close     // Record the latest current price

var ema1 = TA.EMA(r, ema1Period)    // Calculate EMA indicators
var ema2 = TA.EMA(r, ema2Period)    // Calculate EMA indicators
if (ema1.length < 3 || ema2.length < 3) {    // The length of EMA indicator array is too short, return directly
Sleep(1000)
return
}
var ema1Last2 = ema1[ema1.length - 2]   // EMA on the penultimate BAR
var ema1Last3 = ema1[ema1.length - 3]   // EMA on the third from the last BAR
var ema2Last2 = ema2[ema2.length - 2]
var ema2Last3 = ema2[ema2.length - 3]

// Write data to the chart
var klineIndex = index + 2 * index
// Iterate through the K-line data
for (var i = 0 ; i < r.length ; i++) {
if (r[i].Time == lastBarTime[symbol]) {         // Draw the chart, update the current BAR and indicators
// 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]) {   // Draw the charts, add BARs and indicators
lastBarTime[symbol] = r[i].Time             // Update timestamp
chart.add(klineIndex, [r[i].Time, r[i].Open, r[i].High, r[i].Low, r[i].Close])
}
}

if (ema1Last3 < ema2Last3 && ema1Last2 > ema2Last2 && currTradeMsg[symbol] != currBarTime) {
// Golden cross
var depth = exchange.GetDepth()   // Obtain the depth data of current order book
if (depth && price * amount <= account[quoteCurrency]) {   // Obtain deep data normally with enough assets to place an order
cancelAll(exchange)     // Cancel all makers
var acc = _C(exchange.GetAccount)   // Obtain account asset information
if (acc.Stocks != account[baseCurrency]) {  // Detect changes in account assets
account[baseCurrency] = acc.Stocks      // Update assets
account[quoteCurrency] = acc.Balance    // Update assets
currTradeMsg[symbol] = currBarTime      // Record that the current BAR has been traded
var profit = getProfit(account, initAccount, lastPrices)  // Calculate profits
if (profit) {
LogProfit(profit, account, initAccount)    // Print profits
}
}
}
} else if (ema1Last3 > ema2Last3 && ema1Last2 < ema2Last2 && currTradeMsg[symbol] != currBarTime) {
// 死叉
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
var profit = getProfit(account, initAccount, lastPrices)
if (profit) {
LogProfit(profit, account, initAccount)
}
}
}
}
Sleep(1000)
})

// Table variables in the status bar
var tbl = {
type : "table",
title : "Account Information",
cols : [],
rows : []
}
// Write data into the status bar table structure
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
}
})
// Show status bar table
LogStatus(_D(), "\n", "profit:", getProfit(account, initAccount, lastPrices), "\n", "`" + JSON.stringify(tbl) + "`")
}
}```

### Strategy backtest

It can be seen that ETH, LTC and ETC are triggered according to the Golden Cross and Dead Cross of EMA, and tradings have occurred.

We can also take a simulation bot for testing.

Strategy source code: https://www.fmz.com/strategy/333783

The strategy is used for backtesting, learning strategy design only, and it should be used with caution in the real bot.