記錄歷史數據

由于各種原因，機器人可能會反復重啟，如錯誤、參數更新、策略更新等，因此需要保存一些數據以便下次啟動。以下是如何保存初始凈值以計算回報的示例。_G（） 函數可以存儲各種數據。_G（key， value） 可以存放 value 的值，并用 _G（key） 調用它，其中 key 是一個字符串。

let init_eq = 0 //defining initial equity

if(!_G('init_eq')){  //If there is no storage, _G('init_eq') returns null.

    init_eq = total_eq

    _G('init_eq', total_eq) //Since there is no storage, the initial equity is the current equity and is stored here

}else{

    init_eq = _G('init_eq') //If stored, read the value of the initial equity

}

策略容錯

在通過 API 獲取持倉、行情等數據時，可能由于各種原因返回錯誤。直接調用數據可能導致策略因錯誤停止，因此需要一種容錯機制。_C（） 函數將在遇到錯誤時自動重試，直到返回正確的數據。或者檢查返回后的數據是否可用。

let pos = _C(exchange.GetPosition, pair)



let ticker_A = exchange.GetTicker(pair_a)

let ticker_B = exchange.GetTicker(pair_b)

if(!ticker_A || !ticker_B){

    continue //If the data is not available, exit the loop.

}

多幣種兼容 API

GetPosition、GetTicker 和 GetRecords 等函數可以加上交易對參數來獲取相關數據，無需設置交易所綁定的交易對，這大大提升了多交易對策略的兼容性。有關具體的升級內容，請參見文章：https://www.fmz.com/bbs-topic/10456。當然，您需要最新的 docker 來支持它。如果您的 docker 版本過舊，則需要進行升級。

策略參數

• Pair_A：需要配對進行交易的交易對 A。您需要自己選擇交易對。您可以參考上一篇文章中的介紹和回測。
• Pair_B：需要配對的交易對 B。
• Quote：期貨交易所的保證金貨幣，通常為 USDT。
• Pct：加倉多少偏差，詳見策略原則一文，由于手續費和滑點原因，不宜設置得太小。
• Trade_Value： 每次偏離網格大小增加倉位的交易值。
• Ice_Value：如果成交金額過大，您可以使用冰山傭金值開倉。通常，它可以設置為與交易值相同的值。
• Max_Value：單一幣種的最大持倉量，以避免持倉過多的風險。
• N：用于計算均價比的參數，單位為小時，例如 100 表示 100 小時的平均值。
• Interval：策略的每個周期之間的休眠時間。

完成策略說明

如果您仍然不明白，您可以使用 FMZ 的 API 文檔、調試工具以及市面上常用的 AI 對話工具來解決您的問題。

function GetPosition(pair){

    let pos = _C(exchange.GetPosition, pair)

    if(pos.length == 0){ //Returns null to indicate no position

        return {amount:0, price:0, profit:0}

    }else if(pos.length > 1){ //The strategy should be set to unidirectional position mode

        throw 'Bidirectional positions are not supported'

    }else{ //For convenience, long positions are positive and short positions are negative

        return {amount:pos[0].Type == 0 ? pos[0].Amount : -pos[0].Amount, price:pos[0].Price, profit:pos[0].Profit}

    }

}



function GetRatio(){

    let kline_A = exchange.GetRecords(Pair_A+"_"+Quote+".swap", 60*60, N) //Hourly K-line

    let kline_B = exchange.GetRecords(Pair_B+"_"+Quote+".swap", 60*60, N)

    let total = 0

    for(let i= Math.min(kline_A.length,kline_B.length)-1; i >= 0; i--){ //Calculate in reverse to avoid the K-line being too short.

        total += kline_A[i].Close / kline_B[i].Close

    }

    return total / Math.min(kline_A.length,kline_B.length)

}



function GetAccount(){

    let account = _C(exchange.GetAccount)

    let total_eq = 0

    if(exchange.GetName == 'Futures_OKCoin'){ //Since the API here is not compatible, only OKX Futures Exchange obtains the total equity currently.

        total_eq = account.Info.data[0].totalEq //The equity information of other exchanges is also included. You can look for it yourself in the exchange API documentation.

    }else{

        total_eq = account.Balance //Temporary use of available balances on other exchanges will cause errors in calculating returns, but will not affect the use of strategies.

    }

    let init_eq = 0

    if(!_G('init_eq')){

        init_eq = total_eq

        _G('init_eq', total_eq)

    }else{

        init_eq = _G('init_eq')

    }

    LogProfit(total_eq - init_eq)

    return total_eq

}



function main(){

    var precision = exchange.GetMarkets() //Get the precision here

    var last_get_ratio_time = Date.now()

    var ratio = GetRatio()

    var total_eq = GetAccount()

    while(true){

        let start_loop_time = Date.now()

        if(Date.now() - last_get_ratio_time > 10*60*1000){ //Update the average price and account information every 10 minutes

            ratio = GetRatio()

            total_eq = GetAccount()

            last_get_ratio_time = Date.now()

        }

        let pair_a = Pair_A+"_"+Quote+".swap" //The trading pair is set as BTC_USDT.swap

        let pair_b = Pair_B+"_"+Quote+".swap"

        let CtVal_a = "CtVal" in precision[pair_a] ? precision[pair_a].CtVal : 1 //Some exchanges use sheets to represent quantity, such as one sheet represents 0.01 coin, so you need to convert.

        let CtVal_b = "CtVal" in precision[pair_b] ? precision[pair_b].CtVal : 1 //No need to include this field

        let position_A = GetPosition(pair_a)

        let position_B = GetPosition(pair_b)

        let ticker_A = exchange.GetTicker(pair_a)

        let ticker_B = exchange.GetTicker(pair_b)

        if(!ticker_A || !ticker_B){ //If the returned data is abnormal, jump out of this loop

            continue

        }

        let diff = (ticker_A.Last / ticker_B.Last - ratio) / ratio //Calculate the ratio of deviation

        let aim_value = - Trade_Value * diff / Pct //Target holding position

        let id_A = null

        let id_B = null

        //The following is the specific logic of opening a position

        if( -aim_value + position_A.amount*CtVal_a*ticker_A.Last > Trade_Value && position_A.amount*CtVal_a*ticker_A.Last > -Max_Value){

            id_A = exchange.CreateOrder(pair_a, "sell", ticker_A.Buy, _N(Ice_Value / (ticker_A.Buy * CtVal_a), precision[pair_a].AmountPrecision))

        }

        if( -aim_value - position_B.amount*CtVal_b*ticker_B.Last > Trade_Value && position_B.amount*CtVal_b*ticker_B.Last < Max_Value){

            id_B = exchange.CreateOrder(pair_b, "buy", ticker_B.Sell, _N(Ice_Value / (ticker_B.Sell * CtVal_b), precision[pair_b].AmountPrecision))

        }

        if( aim_value - position_A.amount*CtVal_a*ticker_A.Last > Trade_Value && position_A.amount*CtVal_a*ticker_A.Last < Max_Value){

            id_A = exchange.CreateOrder(pair_a, "buy", ticker_A.Sell, _N(Ice_Value / (ticker_A.Sell * CtVal_a), precision[pair_a].AmountPrecision))

        }

        if( aim_value + position_B.amount*CtVal_b*ticker_B.Last > Trade_Value &&  position_B.amount*CtVal_b*ticker_B.Last > -Max_Value){

            id_B = exchange.CreateOrder(pair_b, "sell", ticker_B.Buy, _N(Ice_Value / (ticker_B.Buy * CtVal_b), precision[pair_b].AmountPrecision))

        }

        if(id_A){

            exchange.CancelOrder(id_A) //Cancel directly here

        }

        if(id_B){

            exchange.CancelOrder(id_B)

        }

        let table = {

            type: "table",

            title: "trading Information",

            cols: ["initial equity", "current equity", Pair_A+"position", Pair_B+"position", Pair_A+"holding price", Pair_B+"holding price", Pair_A+"profits", Pair_B+"profits", Pair_A+"price", Pair_B+"price", "current price comparison", "average price comparison", "deviation from average price", "loop delay"],

            rows: [[_N(_G('init_eq'),2), _N(total_eq,2), _N(position_A.amount*CtVal_a*ticker_A.Last, 1), _N(position_B.amount*CtVal_b*ticker_B.Last,1),

                _N(position_A.price, precision[pair_a].PircePrecision), _N(position_B.price, precision[pair_b].PircePrecision),

                _N(position_A.profit, 1), _N(position_B.profit, 1), ticker_A.Last, ticker_B.Last,

                _N(ticker_A.Last / ticker_B.Last,6), _N(ratio, 6), _N(diff, 4), (Date.now() - start_loop_time)+"ms"

            ]]

        }

        LogStatus("" + JSON.stringify(table) + "") //This function will display a table containing the above information on the robot page.
        Sleep(Interval * 1000) //Sleep time in ms
    }
}

如何找到更多同類API？

冪簡集成是國內領先的API集成管理平臺，專注于為開發者提供全面、高效、易用的API集成解決方案。冪簡API平臺可以通過以下兩種方式找到所需API：通過關鍵詞搜索API、或者從API Hub分類頁進入尋找。

原文鏈接：https://medium.com/@FMZQuant/introduction-to-the-source-code-of-digital-currency-pair-trading-strategy-and-the-latest-api-of-fmz-56b912a28231