こんにちは！スナフキンです．先日チャネルブレイクアウト戦略を使ったbotを作成したのですが，そのコードを公開します．コードを全て解説する時間はさすがにないので，概要を述べたあとに重要な変数と重要な関数のみを解説します．本botはヒストリカルデータを用いてバックテストを行う機能も搭載しており，botの勉強を始める方にとってはそのあたりの実装についての勉強教材になるかもしれません．実運用・バックテストともに可能です．また，自分の設定したローソク足の時間軸でのトレードが可能です．

ちなみに2018/2/21-2018/3/10の5分足でのバックテスト結果は以下です．

ぼく個人の感情から，なるべく早く公開したいので，さしあたってチャネルブレイクアウト戦略そのものの説明などはGoogle先生にお任せします．（気が向いたら更新して細かい解説もします．）

概要と変数の説明

本botはチャネルブレイクアウト戦略を少し改良したものになります．具体的には以下のような点を改良（拡張）しています．

チャネルブレイクアウト戦略は期間安値・期間高値の更新でエントリーおよびクローズ，ドテン売買するが，何期間高値・安値でエントリーし何期間高値・安値でクローズするかを設定可能．→ex. エントリー5期間でクローズ3期間ならドテン売買は行わなくなる．（もちろん，エントリーとクローズの期間を同じにすれば通常のチャネルブレイクアウト戦略のようにドテン売買する）
レンジ相場でのエントリーを減らすために，レンジ判定ロジックを導入している．（レンジ判定は，一定期間の値幅または価格の標準偏差の変動で行います．）
大きな値幅をとったあとのnトレードではロットを1/10に減らす処理を入れている．（大きいトレンドのあとの大きなリバや戻りで損をしやすいため）
成行注文のスリッページによる執行コストを考慮したバックテストが可能（ただし定額固定）

さて，重要な変数の解説ですが今書いていて眠くなってきたのでまた明日以降に気が向いたときに書きます．コードは載せておくので販売・商用目的以外はご自由にご利用ください．

#_*_ coding: utf-8 _*_

import pybitflyer
import json
import requests
import csv
import math
import pandas as pd
import time
import requests
import datetime
from pubnub.callbacks import SubscribeCallback
from pubnub.enums import PNStatusCategory
from pubnub.pnconfiguration import PNConfiguration
from pubnub.pubnub_tornado import PubNubTornado
from pubnub.pnconfiguration import PNReconnectionPolicy
from tornado import gen
import threading
from collections import deque

class ChannelBreakOut:
    def __init__(self):
        #pubnubから取得した約定履歴を保存するリスト（基本的に不要．）
        self._executions = deque(maxlen=300)
        self._lot = 0.01
        self._product_code = "FX_BTC_JPY"
        #各パラメタ．
        self._entryTerm = 10
        self._closeTerm = 5
        self._rangeTerm = 15
        self._rangeTh = 5000
        self._waitTerm = 5
        self._waitTh = 20000
        self._candleTerm = "1T"
        #現在のポジション．1ならロング．-1ならショート．0ならポジションなし．
        self._pos = 0
        #注文執行コスト．遅延などでこの値幅を最初から取られていると仮定する
        self._cost = 3000
        self.order = Order()
        self.api = pybitflyer.API("your key", "your secret")

        #ラインに稼働状況を通知
        self.line_notify_token = 'your token'
        self.line_notify_api = 'https://notify-api.line.me/api/notify'

    @property
    def cost(self):
        return self._cost

    @cost.setter
    def cost(self, value):
        self._cost = value

    @property
    def candleTerm(self):
        return self._candleTerm
    @candleTerm.setter
    def candleTerm(self, val):
        """
        valは"5T"，"1H"などのString
        """
        self._candleTerm = val

    @property
    def waitTh(self):
        return self._waitTh
    @waitTh.setter
    def waitTh(self, val):
        self._waitTh = val

    @property
    def waitTerm(self):
        return self._waitTerm
    @waitTerm.setter
    def waitTerm(self, val):
        self._waitTerm = val

    @property
    def rangeTh(self):
        return self._rangeTh
    @rangeTh.setter
    def rangeTh(self,val):
        self._rangeTh = val

    @property
    def rangeTerm(self):
        return self._rangeTerm
    @rangeTerm.setter
    def rangeTerm(self,val):
        self._rangeTerm = val


    @property
    def executions(self):
        return self._executions
    @executions.setter
    def executions(self, val):
        self._executions = val

    @property
    def pos(self):
        return self._pos
    @pos.setter
    def pos(self, val):
        self._pos = int(val)

    @property
    def lot(self):
        return self._lot
    @lot.setter
    def lot(self, val):
        self._lot = round(val,3)

    @property
    def product_code(self):
        return self._product_code
    @product_code.setter
    def product_code(self, val):
        self._product_code = val

    @property
    def entryTerm(self):
        return self._entryTerm
    @entryTerm.setter
    def entryTerm(self, val):
        self._entryTerm = int(val)

    @property
    def closeTerm(self):
        return self._closeTerm
    @closeTerm.setter
    def closeTerm(self, val):
        self._closeTerm = int(val)

    def calculateLot(self, margin):
        """
        証拠金からロットを計算する関数．
        """
        lot = math.floor(margin*10**(-4))*10**(-2)
        return round(lot,2)

    def calculateLines(self, df_candleStick, term):
        """

        期間高値・安値を計算する．
        candleStickはcryptowatchのローソク足．termは安値，高値を計算する期間．（5ならローソク足5本文の安値，高値．)
        """
        lowLine = []
        highLine = []
        for i in range(len(df_candleStick.index)):
            if i < term:
                lowLine.append(df_candleStick["high"][i])
                highLine.append(df_candleStick["low"][i])
            else:
                low = min([price for price in df_candleStick["low"][i-term:i-1]])
                high = max([price for price in df_candleStick["high"][i-term:i-1]])
                lowLine.append(low)
                highLine.append(high)
        return (lowLine, highLine)

    def calculatePriceRange(self, df_candleStick, term):
        """
        termの期間の値幅を計算．
        """
        low = [min([df_candleStick["close"][i-term+1:i].min(),df_candleStick["open"][i-term+1:i].min()]) for i in range(len(df_candleStick.index))]
        high = [max([df_candleStick["close"][i-term+1:i].max(), df_candleStick["open"][i-term+1:i].max()]) for i in range(len(df_candleStick.index))]
        low = pd.Series(low)
        high = pd.Series(high)
        priceRange = [high.iloc[i]-low.iloc[i] for i in range(len(df_candleStick.index))]
        return priceRange

    def isRange(self,df_candleStick ,term, th):
        """
        レンジ相場かどうかをTrue,Falseの配列で返す．termは期間高値・安値の計算期間．thはレンジ判定閾値．
        """
        #値幅での判定．
        if th != None:
            priceRange = self.calculatePriceRange(df_candleStick, term)
            isRange = [th > i for i in priceRange]
        #終値の標準偏差の差分が正か負かでの判定．
        elif th == None and term != None:
            df_candleStick["std"] = [df_candleStick["close"][i-term+1:i].std() for i in range(len(df_candleStick.index))]
            df_candleStick["std_slope"] = [df_candleStick["std"][i]-df_candleStick["std"][i-1] for i in range(len(df_candleStick.index))]
            isRange = [i > 0 for i in df_candleStick["std_slope"]]
        else:
            isRange = [False for i in df_candleStick.index]
        return isRange

    def judge(self, df_candleStick, entryHighLine, entryLowLine, closeHighLine, closeLowLine, entryTerm):
        """
        売り買い判断．ローソク足の高値が期間高値を上抜けたら買いエントリー．（2）ローソク足の安値が期間安値を下抜けたら売りエントリー．judgementリストは[買いエントリー，売りエントリー，買いクローズ（売り），売りクローズ（買い）]のリストになっている．（二次元リスト）リスト内リストはの要素は，0（シグナルなし）,価格（シグナル点灯）を取る．
        """
        judgement = [[0,0,0,0] for i in range(len(df_candleStick.index))]
        for i in range(len(df_candleStick.index)):
            #上抜けでエントリー
            if df_candleStick["high"][i] > entryHighLine[i] and i >= entryTerm:
                judgement[i][0] = entryHighLine[i]
            #下抜けでエントリー
            if df_candleStick["low"][i] < entryLowLine[i] and i >= entryTerm:
                judgement[i][1] = entryLowLine[i]
            #下抜けでクローズ
            if df_candleStick["low"][i] < closeLowLine[i] and i >= entryTerm:
                judgement[i][2] = closeLowLine[i]
            #上抜けでクローズ
            if df_candleStick["high"][i] > closeHighLine[i] and i >= entryTerm:
                judgement[i][3] = closeHighLine[i]
            #
            else:
                pass
        return judgement

    def judgeForLoop(self, high, low, entryHighLine, entryLowLine, closeHighLine, closeLowLine):
        """
        売り買い判断．入力した価格が期間高値より高ければ買いエントリー，期間安値を下抜けたら売りエントリー．judgementリストは[買いエントリー，売りエントリー，買いクローズ（売り），売りクローズ（買い）]のリストになっている．（値は0or1）
        ローソク足は1分ごとに取得するのでインデックスが-1のもの（現在より1本前）をつかう．
        """
        judgement = [0,0,0,0]
        #上抜けでエントリー
        if high > entryHighLine[-1]:
            judgement[0] = 1
        #下抜けでエントリー
        if low < entryLowLine[-1]:
            judgement[1] = 1
        #下抜けでクローズ
        if low < closeLowLine[-1]:
            judgement[2] = 1
        #上抜けでクローズ
        if high > closeHighLine[-1]:
            judgement[3] = 1
        return judgement


    #エントリーラインおよびクローズラインで約定すると仮定する．
    def backtest(self, judgement, df_candleStick, lot, rangeTh, rangeTerm, originalWaitTerm=10, waitTh=10000, cost = 0):
        #エントリーポイント，クローズポイントを入れるリスト
        buyEntrySignals = []
        sellEntrySignals = []
        buyCloseSignals = []
        sellCloseSignals = []
        nOfTrade = 0
        pos = 0
        pl = []
        pl.append(0)
        #トレードごとの損益
        plPerTrade = []
        #取引時の価格を入れる配列．この価格でバックテストのplを計算する．（ので，どの価格で約定するかはテストのパフォーマンスに大きく影響を与える．）
        buy_entry = []
        buy_close = []
        sell_entry = []
        sell_close = []
        #各ローソク足について，レンジ相場かどうかの判定が入っている配列
        isRange =  self.isRange(df_candleStick, rangeTerm, rangeTh)
        #基本ロット．勝ちトレードの直後はロットを落とす．
        originalLot = lot
        #勝ちトレード後，何回のトレードでロットを落とすか．
        waitTerm = 0
        for i in range(len(judgement)):
            if i > 0:
                lastPL = pl[-1]
                pl.append(lastPL)
            #エントリーロジック
            if pos == 0 and not isRange[i]:
                #ロングエントリー
                if judgement[i][0] != 0:
                    pos += 1
                    buy_entry.append(judgement[i][0])
                    buyEntrySignals.append(df_candleStick.index[i])
                #ショートエントリー
                elif judgement[i][1] != 0:
                    pos -= 1
                    sell_entry.append(judgement[i][1])
                    sellEntrySignals.append(df_candleStick.index[i])
            #ロングクローズロジック
            elif pos == 1:
                #ロングクローズ
                if judgement[i][2] != 0:
                    nOfTrade += 1
                    pos -= 1
                    buy_close.append(judgement[i][2])
                    #値幅
                    plRange = buy_close[-1] - buy_entry[-1]
                    pl[-1] = pl[-2] + (plRange-self.cost) * lot
                    buyCloseSignals.append(df_candleStick.index[i])
                    plPerTrade.append((plRange-self.cost)*lot)
                    #waitTh円以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．
                    if plRange > waitTh:
                        waitTerm = originalWaitTerm
                        lot = originalLot/10
                    elif waitTerm > 0:
                        waitTerm -= 1
                        lot = originalLot/10
                    if waitTerm == 0:
                         lot = originalLot
            #ショートクローズロジック
            elif pos == -1:
                #ショートクローズ
                if judgement[i][3] != 0:
                    nOfTrade += 1
                    pos += 1
                    sell_close.append(judgement[i][3])
                    plRange = sell_entry[-1] - sell_close[-1]
                    pl[-1] = pl[-2] + (plRange-self.cost) * lot
                    sellCloseSignals.append(df_candleStick.index[i])
                    plPerTrade.append((plRange-self.cost)*lot)
                    #waitTh円以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．
                    if plRange > waitTh:
                        waitTerm = originalWaitTerm
                        lot = originalLot/10
                    elif waitTerm > 0:
                        waitTerm -= 1
                        lot = originalLot/10
                    if waitTerm == 0:
                         lot = originalLot

            #さらに，クローズしたと同時にエントリーシグナルが出ていた場合のロジック．
            if pos == 0 and not isRange[i]:
                #ロングエントリー
                if judgement[i][0] != 0:
                    pos += 1
                    buy_entry.append(judgement[i][0])
                    buyEntrySignals.append(df_candleStick.index[i])
                #ショートエントリー
                elif judgement[i][1] != 0:
                    pos -= 1
                    sell_entry.append(judgement[i][1])
                    sellEntrySignals.append(df_candleStick.index[i])
        #最後にポジションを持っていたら，期間最後のローソク足の終値で反対売買．
        if pos == 1:
            buy_close.append(df_candleStick["close"][-1])
            plRange = buy_close[-1] - buy_entry[-1]
            pl[-1] = pl[-2] + plRange * lot
            pos -= 1
            buyCloseSignals.append(df_candleStick.index[-1])
            nOfTrade += 1
            plPerTrade.append(plRange*lot)
        elif pos ==-1:
            sell_close.append(df_candleStick["close"][-1])
            plRange = sell_entry[-1] - sell_close[-1]
            pl[-1] = pl[-2] + plRange * lot
            pos +=1
            sellCloseSignals.append(df_candleStick.index[-1])
            nOfTrade += 1
            plPerTrade.append(plRange*lot)
        return (pl, buyEntrySignals, sellEntrySignals, buyCloseSignals, sellCloseSignals, nOfTrade, plPerTrade)

    def describeResult(self, entryTerm, closeTerm, fileName=None, candleTerm=None, rangeTh=5000, rangeTerm=15, originalWaitTerm=10, waitTh=10000, showFigure=True, cost=0):
        """
        signalsは買い，売り，中立が入った配列
        """
        import matplotlib.pyplot as plt
        if fileName == None:
            s_hour = 0
            s_min = 0
            e_hour = 23
            e_min = 59
            number = int((e_hour - s_hour)*60 + e_min - s_min)
            start_timestamp = datetime.datetime(2018, 3, 24, s_hour, s_min, 0, 0).timestamp()
            end_timestamp = datetime.datetime(2018, 3, 24, e_hour, e_min, 0, 0).timestamp()
            candleStick = self.getSpecifiedCandlestick(number, "60", start_timestamp, end_timestamp)
        else:
            candleStick = self.readDataFromFile(fileName)

        if candleTerm != None:
            df_candleStick = self.processCandleStick(candleStick, candleTerm)
        else:
            df_candleStick = self.fromListToDF(candleStick)

        entryLowLine, entryHighLine = self.calculateLines(df_candleStick, entryTerm)
        closeLowLine, closeHighLine = self.calculateLines(df_candleStick, closeTerm)
        judgement = self.judge(df_candleStick, entryHighLine, entryLowLine, closeHighLine, closeLowLine, entryTerm)
        pl, buyEntrySignals, sellEntrySignals, buyCloseSignals, sellCloseSignals, nOfTrade, plPerTrade = self.backtest(judgement, df_candleStick, 1, rangeTh, rangeTerm, originalWaitTerm=originalWaitTerm, waitTh=waitTh, cost=cost)

        plt.figure()
        plt.subplot(211)
        plt.plot(df_candleStick.index, df_candleStick["high"])
        plt.plot(df_candleStick.index, df_candleStick["low"])
        plt.ylabel("Price(JPY)")
        ymin = min(df_candleStick["low"]) - 200
        ymax = max(df_candleStick["high"]) + 200
        plt.vlines(buyEntrySignals, ymin , ymax, "blue", linestyles='dashed', linewidth=1)
        plt.vlines(sellEntrySignals, ymin , ymax, "red", linestyles='dashed', linewidth=1)
        plt.vlines(buyCloseSignals, ymin , ymax, "black", linestyles='dashed', linewidth=1)
        plt.vlines(sellCloseSignals, ymin , ymax, "green", linestyles='dashed', linewidth=1)
        plt.subplot(212)
        plt.plot(df_candleStick.index, pl)
        plt.hlines(y=0, xmin=df_candleStick.index[0], xmax=df_candleStick.index[-1], colors='k', linestyles='dashed')
        plt.ylabel("PL(JPY)")

        #各統計量の計算および表示．
        winTrade = sum([1 for i in plPerTrade if i > 0])
        loseTrade = sum([1 for i in plPerTrade if i < 0])
        winPer = round(winTrade/(winTrade+loseTrade) * 100,2)

        winTotal = sum([i for i in plPerTrade if i > 0])
        loseTotal = sum([i for i in plPerTrade if i < 0])
        profitFactor = round(winTotal/-loseTotal, 3)

        maxProfit = max(plPerTrade)
        maxLoss = min(plPerTrade)

        print("Total pl: {}JPY".format(int(pl[-1])))
        print("The number of Trades: {}".format(nOfTrade))
        print("The Winning percentage: {}%".format(winPer))
        print("The profitFactor: {}".format(profitFactor))
        print("The maximum Profit and Loss: {}JPY, {}JPY".format(maxProfit, maxLoss))
        if showFigure:
            plt.show()
        else:
            plt.clf()
        return pl[-1], profitFactor

    def getCandlestick(self, number, period):
        """
        number:ローソク足の数．period:ローソク足の期間（文字列で秒数を指定，Ex:1分足なら"60"）．cryptowatchはときどきおかしなデータ（price=0）が含まれるのでそれを除く．
        """
        #ローソク足の時間を指定
        periods = [period]
        #クエリパラメータを指定
        query = {"periods":','.join(periods)}
        #ローソク足取得
        res = \
            json.loads(requests.get("https://api.cryptowat.ch/markets/bitflyer/btcfxjpy/ohlc", params=query).text)[
                "result"]
        # ローソク足のデータを入れる配列．
        data = []
        for i in periods:
            row = res[i]
            length = len(row)
            for column in row[:length - (number + 1):-1]:
                # dataへローソク足データを追加．
                if column[4] != 0:
                    column = column[0:6]
                    data.append(column)
        return data[::-1]


    def fromListToDF(self, candleStick):
        """
        Listのローソク足をpandasデータフレームへ．
        """
        date = [price[0] for price in candleStick]
        priceOpen = [int(price[1]) for price in candleStick]
        priceHigh = [int(price[2]) for price in candleStick]
        priceLow = [int(price[3]) for price in candleStick]
        priceClose = [int(price[4]) for price in candleStick]
        date_datetime = map(datetime.datetime.fromtimestamp, date)
        dti = pd.DatetimeIndex(date_datetime)
        df_candleStick = pd.DataFrame({"open" : priceOpen, "high" : priceHigh, "low": priceLow, "close" : priceClose}, index=dti)
        return df_candleStick

    def processCandleStick(self, candleStick, timeScale):
        """
        1分足データから各時間軸のデータを作成.timeScaleには5T（5分），H（1時間）などの文字列を入れる
        """
        df_candleStick = self.fromListToDF(candleStick)
        processed_candleStick = df_candleStick.resample(timeScale).agg({'open': 'first','high':'max','low': 'min','close': 'last'})
        processed_candleStick = processed_candleStick.dropna()
        return processed_candleStick

    #csvファイル（ヘッダなし）からohlcデータを作成．
    def readDataFromFile(self,filename):
        for i in range(1, 10, 1):
            with open(filename, 'r', encoding="utf-8") as f:
                reader = csv.reader(f)
                header = next(reader)
                for row in reader:
                    candleStick = [row for row in reader if row[4] != "0"]
        dtDate = [datetime.datetime.strptime(data[0], '%Y-%m-%d %H:%M:%S') for data in candleStick]
        dtTimeStamp = [dt.timestamp() for dt in dtDate]
        for i in range(len(candleStick)):
            candleStick[i][0] = dtTimeStamp[i]
        candleStick = [[float(i) for i in data] for data in candleStick]
        return candleStick

    def lineNotify(self, message, fileName=None):
        payload = {'message': message}
        headers = {'Authorization': 'Bearer ' + self.line_notify_token}
        if fileName == None:
            try:
                requests.post(self.line_notify_api, data=payload, headers=headers)
            except:
                pass
        else:
            try:
                files = {"imageFile": open(fileName, "rb")}
                requests.post(self.line_notify_api, data=payload, headers=headers, files = files)
            except:
                pass

    def describePLForNotification(self, pl, df_candleStick):
        import matplotlib
        matplotlib.use('Agg')
        import matplotlib.pyplot as plt
        close = df_candleStick["close"]
        index = range(len(pl))
        # figure
        fig = plt.figure(figsize=(20,12))
        #for price
        ax = fig.add_subplot(2, 1, 1)
        ax.plot(df_candleStick.index, close)
        ax.set_xlabel('Time')
        # y axis
        ax.set_ylabel('The price[JPY]')
        #for PLcurve
        ax = fig.add_subplot(2, 1, 2)
        # plot
        ax.plot(index, pl, color='b', label='The PL curve')
        ax.plot(index, [0]*len(pl), color='b',)
        # x axis
        ax.set_xlabel('The number of Trade')
        # y axis
        ax.set_ylabel('The estimated Profit/Loss(JPY)')
        # legend and title
        ax.legend(loc='best')
        ax.set_title('The PL curve(Time span:{})'.format(self.candleTerm))
        # save as png
        today = datetime.datetime.now().strftime('%Y%m%d')
        number = "_" + str(len(pl))
        fileName = today + number + ".png"
        plt.savefig(fileName)
        plt.close()

        return fileName

    def loop(self,entryTerm, closeTerm, rangeTh, rangeTerm,originalWaitTerm, waitTh,candleTerm=None):
        """
        注文の実行ループを回す関数
        """
        self.executionsProcess()
        #pubnubが回り始めるまで待つ．
        time.sleep(20)
        pos = 0
        pl = []
        pl.append(0)
        lastPositionPrice = 0
        lot = self.lot
        originalLot = self.lot
        waitTerm = 0

        try:
            candleStick = self.getCandlestick(50, "60")
        except:
            print("Unknown error happend when you requested candleStick")
        if candleTerm == None:
            df_candleStick = self.fromListToDF(candleStick)
        else:
            df_candleStick = self.processCandleStick(candleStick, candleTerm)

        entryLowLine, entryHighLine = self.calculateLines(df_candleStick, entryTerm)
        closeLowLine, closeHighLine = self.calculateLines(df_candleStick, closeTerm)

        #直近約定件数30件の高値と安値
        high = max([self.executions[-1-i]["price"] for i in range(30)])
        low = min([self.executions[-1-i]["price"] for i in range(30)])

        while True:
            #1分ごとに基準ラインを更新
            if datetime.datetime.now().second < 2 :
                print("Renewing candleSticks")
                try:
                    candleStick = self.getCandlestick(50, "60")
                except:
                    print("Unknown error happend when you requested candleStick")
                if candleTerm == None:
                    df_candleStick = self.fromListToDF(candleStick)
                else:
                    df_candleStick = self.processCandleStick(candleStick, candleTerm)
                entryLowLine, entryHighLine = self.calculateLines(df_candleStick, entryTerm)
                closeLowLine, closeHighLine = self.calculateLines(df_candleStick, closeTerm)

                #直近約定件数30件の貴音と安値
                high = max([self.executions[-1-i]["price"] for i in range(30)])
                low = min([self.executions[-1-i]["price"] for i in range(30)])

            judgement = self.judgeForLoop(high, low, entryHighLine, entryLowLine, closeHighLine, closeLowLine)
            #現在レンジ相場かどうか．
            isRange = self.isRange(df_candleStick, rangeTerm, rangeTh)

            try :
                ticker = self.api.ticker(product_code=self.product_code)
            except:
                print("Unknown error happend when you requested ticker.")
            finally:
                pass

            best_ask = ticker["best_ask"]
            best_bid = ticker["best_bid"]

            #ここからエントリー，クローズ処理
            if pos == 0 and not isRange[-1]:
                #ロングエントリー
                if judgement[0]:
                    print(datetime.datetime.now())
                    self.order.market(size=lot, side="BUY")
                    pos += 1
                    message = "Long entry. Lot:{}, Price:{}".format(lot, best_ask)
                    self.lineNotify(message)
                    lastPositionPrice = best_ask
                #ショートエントリー
                elif judgement[1]:
                    print(datetime.datetime.now())
                    self.order.market(size=lot,side="SELL")
                    pos -= 1
                    message = "Short entry. Lot:{}, Price:{}, ".format(lot, best_bid)
                    self.lineNotify(message)
                    lastPositionPrice = best_bid

            elif pos == 1:
                #ロングクローズ
                if judgement[2]:
                    print(datetime.datetime.now())
                    self.order.market(size=lot,side="SELL")
                    pos -= 1
                    plRange = best_bid - lastPositionPrice
                    pl.append(pl[-1] + plRange * lot)

                    message = "Long close. Lot:{}, Price:{}, pl:{}".format(lot, best_bid, pl[-1])
                    fileName = self.describePLForNotification(pl, df_candleStick)
                    self.lineNotify(message,fileName)

                    #一定以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．
                    if plRange > waitTh:
                        waitTerm = originalWaitTerm
                        lot = round(originalLot/10,3)
                    if waitTerm > 0:
                        waitTerm -= 1
                        lot = round(originalLot/10,3)
                    if waitTerm == 0:
                         lot = originalLot

            elif pos == -1:
                #ショートクローズ
                if judgement[3]:
                    print(datetime.datetime.now())
                    self.order.market(size=lot, side="BUY")
                    pos += 1
                    plRange = lastPositionPrice - best_ask
                    pl.append(pl[-1] + plRange * lot)

                    message = "Short close. Lot:{}, Price:{}, pl:{}".format(lot, best_ask, pl[-1])
                    fileName = self.describePLForNotification(pl, df_candleStick)
                    self.lineNotify(message,fileName)
                    #一定以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．
                    if plRange > waitTh:
                        waitTerm = originalWaitTerm
                        lot = round(originalLot/10,3)
                    if waitTerm > 0:
                        waitTerm -= 1
                        lot = round(originalLot/10,3)
                    if waitTerm == 0:
                         lot = originalLot

            time.sleep(0.5)
            message = "Waiting for channelbreaking."

            if datetime.datetime.now().minute % 5 == 0 and datetime.datetime.now().second < 1:
                print(message)
                self.lineNotify(message)

    def executionsProcess(self):
        """
        pubnubで価格を取得する場合の処理（基本的に不要．）
        """
        channels = ["lightning_executions_FX_BTC_JPY"]
        executions = self.executions
        class BFSubscriberCallback(SubscribeCallback):
            def message(self, pubnub, message):
                execution = message.message
                for i in execution:
                    executions.append(i)

        config = PNConfiguration()
        config.subscribe_key = 'sub-c-52a9ab50-291b-11e5-baaa-0619f8945a4f'
        config.reconnect_policy = PNReconnectionPolicy.LINEAR
        config.ssl = False
        config.set_presence_timeout(60)
        pubnub = PubNubTornado(config)
        listener = BFSubscriberCallback()
        pubnub.add_listener(listener)
        pubnub.subscribe().channels(channels).execute()
        pubnubThread = threading.Thread(target=pubnub.start)
        pubnubThread.start()

    def getSpecifiedCandlestick(self,number, period, start_timestamp, end_timestamp):
        """
        number:ローソク足の数．period:ローソク足の期間（文字列で秒数を指定，Ex:1分足なら"60"）．cryptowatchはときどきおかしなデータ（price=0）が含まれるのでそれを除く
        """
        # ローソク足の時間を指定
        periods = [period]
        # クエリパラメータを指定
        query = {"periods": ','.join(periods), "after": str(int(start_timestamp)), "before": str(int(end_timestamp))}
        # ローソク足取得
        try:
            res = json.loads(requests.get("https://api.cryptowat.ch/markets/bitflyer/btcfxjpy/ohlc", params=query).text)
            res = res["result"]
        except:
            print(res)
        # ローソク足のデータを入れる配列．
        data = []
        for i in periods:
            row = res[i]
            length = len(row)
            for column in row[:length - (number + 1):-1]:
                # dataへローソク足データを追加．
                if column[4] != 0:
                    column = column[0:6]
                    data.append(column)
        return data[::-1]


#注文処理をまとめている
class Order:
    def __init__(self):
        self.product_code = "FX_BTC_JPY"
        self.key = "your key"
        self.secret = "your secret"
        self.api = pybitflyer.API(self.key, self.secret)

    def limit(self, side, price, size, minute_to_expire=None):
        print("Order: Limit. Side : {}".format(side))
        response = {"status":"internalError in order.py"}
        try:
            response = self.api.sendchildorder(product_code=self.product_code, child_order_type="LIMIT", side=side, price=price, size=size, minute_to_expire = minute_to_expire)
        except:
            pass
        while "status" in response:
            try:
                response = self.api.sendchildorder(product_code=self.product_code, child_order_type="LIMIT", side=side, price=price, size=size, minute_to_expire = minute_to_expire)
            except:
                pass
            time.sleep(3)
        return response

    def market(self, side, size, minute_to_expire= None):
        print("Order: Market. Side : {}".format(side))
        response = {"status": "internalError in order.py"}
        try:
            response = self.api.sendchildorder(product_code=self.product_code, child_order_type="MARKET", side=side, size=size, minute_to_expire = minute_to_expire)
        except:
            pass
        while "status" in response:
            try:
                response = self.api.sendchildorder(product_code=self.product_code, child_order_type="MARKET", side=side, size=size, minute_to_expire = minute_to_expire)
            except:
                pass
            time.sleep(3)
        return response

    def stop(self, side, size, trigger_price, minute_to_expire=None):
        print("Order: Stop. Side : {}".format(side))
        response = {"status": "internalError in order.py"}
        try:
            response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "STOP", "side": side, "size": size,"trigger_price": trigger_price, "minute_to_expire": minute_to_expire}])
        except:
            pass
        while "status" in response:
            try:
                response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "STOP", "side": side, "size": size,"trigger_price": trigger_price, "minute_to_expire": minute_to_expire}])
            except:
                pass
            time.sleep(3)
        return response

    def stop_limit(self, side, size, trigger_price, price, minute_to_expire=None):
        print("Side : {}".format(side))
        response = {"status": "internalError in order.py"}
        try:
            response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "STOP_LIMIT", "side": side, "size": size,"trigger_price": trigger_price, "price": price, "minute_to_expire": minute_to_expire}])
        except:
            pass
        while "status" in response:
            try:
                response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "STOP_LIMIT", "side": side, "size": size,"trigger_price": trigger_price, "price": price, "minute_to_expire": minute_to_expire}])
            except:
                pass
        return response

    def trailing(self, side, size, offset, minute_to_expire=None):
        print("Side : {}".format(side))
        response = {"status": "internalError in order.py"}
        try:
            response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "TRAIL", "side": side, "size": size, "offset": offset, "minute_to_expire": minute_to_expire}])
        except:
            pass
        while "status" in response:
            try:
                response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "TRAIL", "side": side, "size": size, "offset": offset, "minute_to_expire": minute_to_expire}])
            except:
                pass
        return response


def optimization():
    entryAndCloseTerm = [(5,3),(5,5),(10,10),(20,10)]
    rangeThAndrangeTerm = [(5000,5),(5000,15),(10000,15),(None,15),(None,20),(None,15)]
    waitTermAndwaitTh = [(10,10000),(10,20000),(5,10000)]

    paramList = []
    for i in entryAndCloseTerm:
        for j in rangeThAndrangeTerm:
            for k in waitTermAndwaitTh:
                channelBreakOut = ChannelBreakOut()
                channelBreakOut.entryTerm = i[0]
                channelBreakOut.closeTerm = i[1]
                channelBreakOut.rangeTh = j[0]
                channelBreakOut.rangeTerm = j[1]
                channelBreakOut.waitTerm = k[0]
                channelBreakOut.waitTh = k[1]
                channelBreakOut.candleTerm = "1T"
                #テスト
                pl, profitFactor =  channelBreakOut.describeResult(entryTerm=channelBreakOut.entryTerm, closeTerm=channelBreakOut.closeTerm, rangeTh=channelBreakOut.rangeTh, rangeTerm=channelBreakOut.rangeTerm,  originalWaitTerm=channelBreakOut.waitTerm, waitTh=channelBreakOut.waitTh, candleTerm=channelBreakOut.candleTerm,fileName="20180221_0310.csv", showFigure=False)
                paramList.append([pl,profitFactor, i,j,k])
    pF = [i[1] for i in paramList]
    pL = [i[0] for i in paramList]
    print("ProfitFactor max:")
    print(paramList[pF.index(max(pF))])
    print("PL max:")
    print(paramList[pL.index(max(pL))])

if __name__ == '__main__':
    #とりあえず5分足，5期間安値・高値でエントリー，クローズする設定
    channelBreakOut = ChannelBreakOut()
    channelBreakOut.entryTerm = 5
    channelBreakOut.closeTerm = 5
    channelBreakOut.rangeTh = None
    channelBreakOut.rangeTerm = None
    channelBreakOut.waitTerm = 0
    channelBreakOut.waitTh = 10000
    channelBreakOut.candleTerm = "5T"
    channelBreakOut.cost = 0

    #実働
    #channelBreakOut.loop(channelBreakOut.entryTerm, channelBreakOut.closeTerm, channelBreakOut.rangeTh, channelBreakOut.rangeTerm, channelBreakOut.waitTerm, channelBreakOut.waitTh)
    #バックテスト
    channelBreakOut.describeResult(entryTerm=channelBreakOut.entryTerm, closeTerm=channelBreakOut.closeTerm, rangeTh=channelBreakOut.rangeTh, rangeTerm=channelBreakOut.rangeTerm,  originalWaitTerm=channelBreakOut.waitTerm, waitTh=channelBreakOut.waitTh, candleTerm=channelBreakOut.candleTerm,showFigure=True, cost=channelBreakOut.cost)
    #最適化
    #optimization()

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558

559

560

561

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

579

580

581

582

583

584

585

586

587

588

589

590

591

592

593

594

595

596

597

598

599

600

601

602

603

604

605

606

607

608

609

610

611

612

613

614

615

616

617

618

619

620

621

622

623

624

625

626

627

628

629

630

631

632

633

634

635

636

637

638

639

640

641

642

643

644

645

646

647

648

649

650

651

652

653

654

655

656

657

658

659

660

661

662

663

664

665

666

667

668

669

670

671

672

673

674

675

676

677

678

679

680

681

682

683

684

685

686

687

688

689

690

691

692

693

694

695

696

697

698

699

700

701

702

703

704

705

706

707

708

709

710

711

712

713

714

715

716

717

718

719

720

721

722

723

724

725

726

727

728

729

730

731

732

733

734

735

736

737

738

739

740

741

742

743

744

745

746

747

748

749

750

751

752

753

754

755

756

757

758

759

760

761

762

763

764

765

766

767

768

769

770

771

772

773

774

775

776

777

778

779

780

781

782

783

784

785

786

787

788

789

790

791

792

793

794

795

796

797

798

799

800

801

802

803

804

805

806

807

808

809

810

811

812

813

814

815

816

817

818

819

820

821

822

823

824

825

826

827

828

829

830

831

832

833

834

835

836

837

#_*_ coding: utf-8 _*_

import pybitflyer

import json

import requests

import csv

import math

import pandas as pd

import time

import requests

import datetime

from pubnub.callbacks import SubscribeCallback

from pubnub.enums import PNStatusCategory

from pubnub.pnconfiguration import PNConfiguration

from pubnub.pubnub_tornado import PubNubTornado

from pubnub.pnconfiguration import PNReconnectionPolicy

from tornado import gen

import threading

from collections import deque

class ChannelBreakOut:

def __init__(self):

#pubnubから取得した約定履歴を保存するリスト（基本的に不要．）

self._executions = deque(maxlen=300)

self._lot = 0.01

self._product_code = "FX_BTC_JPY"

#各パラメタ．

self._entryTerm = 10

self._closeTerm = 5

self._rangeTerm = 15

self._rangeTh = 5000

self._waitTerm = 5

self._waitTh = 20000

self._candleTerm = "1T"

#現在のポジション．1ならロング．-1ならショート．0ならポジションなし．

self._pos = 0

#注文執行コスト．遅延などでこの値幅を最初から取られていると仮定する

self._cost = 3000

self.order = Order()

self.api = pybitflyer.API("your key", "your secret")

#ラインに稼働状況を通知

self.line_notify_token = 'your token'

self.line_notify_api = 'https://notify-api.line.me/api/notify'

@property

def cost(self):

return self._cost

@cost.setter

def cost(self, value):

self._cost = value

@property

def candleTerm(self):

return self._candleTerm

@candleTerm.setter

def candleTerm(self, val):

"""

valは"5T"，"1H"などのString

"""

self._candleTerm = val

@property

def waitTh(self):

return self._waitTh

@waitTh.setter

def waitTh(self, val):

self._waitTh = val

@property

def waitTerm(self):

return self._waitTerm

@waitTerm.setter

def waitTerm(self, val):

self._waitTerm = val

@property

def rangeTh(self):

return self._rangeTh

@rangeTh.setter

def rangeTh(self,val):

self._rangeTh = val

@property

def rangeTerm(self):

return self._rangeTerm

@rangeTerm.setter

def rangeTerm(self,val):

self._rangeTerm = val

@property

def executions(self):

return self._executions

@executions.setter

def executions(self, val):

self._executions = val

@property

def pos(self):

return self._pos

@pos.setter

def pos(self, val):

self._pos = int(val)

@property

def lot(self):

return self._lot

@lot.setter

def lot(self, val):

self._lot = round(val,3)

@property

def product_code(self):

return self._product_code

@product_code.setter

def product_code(self, val):

self._product_code = val

@property

def entryTerm(self):

return self._entryTerm

@entryTerm.setter

def entryTerm(self, val):

self._entryTerm = int(val)

@property

def closeTerm(self):

return self._closeTerm

@closeTerm.setter

def closeTerm(self, val):

self._closeTerm = int(val)

def calculateLot(self, margin):

"""

証拠金からロットを計算する関数．

"""

lot = math.floor(margin*10**(-4))*10**(-2)

return round(lot,2)

def calculateLines(self, df_candleStick, term):

"""

期間高値・安値を計算する．

candleStickはcryptowatchのローソク足．termは安値，高値を計算する期間．（5ならローソク足5本文の安値，高値．)

"""

lowLine = []

highLine = []

for i in range(len(df_candleStick.index)):

if i < term:

lowLine.append(df_candleStick["high"][i])

highLine.append(df_candleStick["low"][i])

else:

low = min([price for price in df_candleStick["low"][i-term:i-1]])

high = max([price for price in df_candleStick["high"][i-term:i-1]])

lowLine.append(low)

highLine.append(high)

return (lowLine, highLine)

def calculatePriceRange(self, df_candleStick, term):

"""

termの期間の値幅を計算．

"""

low = [min([df_candleStick["close"][i-term+1:i].min(),df_candleStick["open"][i-term+1:i].min()]) for i in range(len(df_candleStick.index))]

high = [max([df_candleStick["close"][i-term+1:i].max(), df_candleStick["open"][i-term+1:i].max()]) for i in range(len(df_candleStick.index))]

low = pd.Series(low)

high = pd.Series(high)

priceRange = [high.iloc[i]-low.iloc[i] for i in range(len(df_candleStick.index))]

return priceRange

def isRange(self,df_candleStick ,term, th):

"""

レンジ相場かどうかをTrue,Falseの配列で返す．termは期間高値・安値の計算期間．thはレンジ判定閾値．

"""

#値幅での判定．

if th != None:

priceRange = self.calculatePriceRange(df_candleStick, term)

isRange = [th > i for i in priceRange]

#終値の標準偏差の差分が正か負かでの判定．

elif th == None and term != None:

df_candleStick["std"] = [df_candleStick["close"][i-term+1:i].std() for i in range(len(df_candleStick.index))]

df_candleStick["std_slope"] = [df_candleStick["std"][i]-df_candleStick["std"][i-1] for i in range(len(df_candleStick.index))]

isRange = [i > 0 for i in df_candleStick["std_slope"]]

else:

isRange = [False for i in df_candleStick.index]

return isRange

def judge(self, df_candleStick, entryHighLine, entryLowLine, closeHighLine, closeLowLine, entryTerm):

"""

売り買い判断．ローソク足の高値が期間高値を上抜けたら買いエントリー．（2）ローソク足の安値が期間安値を下抜けたら売りエントリー．judgementリストは[買いエントリー，売りエントリー，買いクローズ（売り），売りクローズ（買い）]のリストになっている．（二次元リスト）リスト内リストはの要素は，0（シグナルなし）,価格（シグナル点灯）を取る．

"""

judgement = [[0,0,0,0] for i in range(len(df_candleStick.index))]

for i in range(len(df_candleStick.index)):

#上抜けでエントリー

if df_candleStick["high"][i] > entryHighLine[i] and i >= entryTerm:

judgement[i][0] = entryHighLine[i]

#下抜けでエントリー

if df_candleStick["low"][i] < entryLowLine[i] and i >= entryTerm:

judgement[i][1] = entryLowLine[i]

#下抜けでクローズ

if df_candleStick["low"][i] < closeLowLine[i] and i >= entryTerm:

judgement[i][2] = closeLowLine[i]

#上抜けでクローズ

if df_candleStick["high"][i] > closeHighLine[i] and i >= entryTerm:

judgement[i][3] = closeHighLine[i]

else:

pass

return judgement

def judgeForLoop(self, high, low, entryHighLine, entryLowLine, closeHighLine, closeLowLine):

"""

売り買い判断．入力した価格が期間高値より高ければ買いエントリー，期間安値を下抜けたら売りエントリー．judgementリストは[買いエントリー，売りエントリー，買いクローズ（売り），売りクローズ（買い）]のリストになっている．（値は0or1）

ローソク足は1分ごとに取得するのでインデックスが-1のもの（現在より1本前）をつかう．

"""

judgement = [0,0,0,0]

#上抜けでエントリー

if high > entryHighLine[-1]:

judgement[0] = 1

#下抜けでエントリー

if low < entryLowLine[-1]:

judgement[1] = 1

#下抜けでクローズ

if low < closeLowLine[-1]:

judgement[2] = 1

#上抜けでクローズ

if high > closeHighLine[-1]:

judgement[3] = 1

return judgement

#エントリーラインおよびクローズラインで約定すると仮定する．

def backtest(self, judgement, df_candleStick, lot, rangeTh, rangeTerm, originalWaitTerm=10, waitTh=10000, cost = 0):

#エントリーポイント，クローズポイントを入れるリスト

buyEntrySignals = []

sellEntrySignals = []

buyCloseSignals = []

sellCloseSignals = []

nOfTrade = 0

pos = 0

pl = []

pl.append(0)

#トレードごとの損益

plPerTrade = []

#取引時の価格を入れる配列．この価格でバックテストのplを計算する．（ので，どの価格で約定するかはテストのパフォーマンスに大きく影響を与える．）

buy_entry = []

buy_close = []

sell_entry = []

sell_close = []

#各ローソク足について，レンジ相場かどうかの判定が入っている配列

isRange = self.isRange(df_candleStick, rangeTerm, rangeTh)

#基本ロット．勝ちトレードの直後はロットを落とす．

originalLot = lot

#勝ちトレード後，何回のトレードでロットを落とすか．

waitTerm = 0

for i in range(len(judgement)):

if i > 0:

lastPL = pl[-1]

pl.append(lastPL)

#エントリーロジック

if pos == 0 and not isRange[i]:

#ロングエントリー

if judgement[i][0] != 0:

pos += 1

buy_entry.append(judgement[i][0])

buyEntrySignals.append(df_candleStick.index[i])

#ショートエントリー

elif judgement[i][1] != 0:

pos -= 1

sell_entry.append(judgement[i][1])

sellEntrySignals.append(df_candleStick.index[i])

#ロングクローズロジック

elif pos == 1:

#ロングクローズ

if judgement[i][2] != 0:

nOfTrade += 1

pos -= 1

buy_close.append(judgement[i][2])

#値幅

plRange = buy_close[-1] - buy_entry[-1]

pl[-1] = pl[-2] + (plRange-self.cost) * lot

buyCloseSignals.append(df_candleStick.index[i])

plPerTrade.append((plRange-self.cost)*lot)

#waitTh円以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．

if plRange > waitTh:

waitTerm = originalWaitTerm

lot = originalLot/10

elif waitTerm > 0:

waitTerm -= 1

lot = originalLot/10

if waitTerm == 0:

lot = originalLot

#ショートクローズロジック

elif pos == -1:

#ショートクローズ

if judgement[i][3] != 0:

nOfTrade += 1

pos += 1

sell_close.append(judgement[i][3])

plRange = sell_entry[-1] - sell_close[-1]

pl[-1] = pl[-2] + (plRange-self.cost) * lot

sellCloseSignals.append(df_candleStick.index[i])

plPerTrade.append((plRange-self.cost)*lot)

#waitTh円以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．

if plRange > waitTh:

waitTerm = originalWaitTerm

lot = originalLot/10

elif waitTerm > 0:

waitTerm -= 1

lot = originalLot/10

if waitTerm == 0:

lot = originalLot

#さらに，クローズしたと同時にエントリーシグナルが出ていた場合のロジック．

if pos == 0 and not isRange[i]:

#ロングエントリー

if judgement[i][0] != 0:

pos += 1

buy_entry.append(judgement[i][0])

buyEntrySignals.append(df_candleStick.index[i])

#ショートエントリー

elif judgement[i][1] != 0:

pos -= 1

sell_entry.append(judgement[i][1])

sellEntrySignals.append(df_candleStick.index[i])

#最後にポジションを持っていたら，期間最後のローソク足の終値で反対売買．

if pos == 1:

buy_close.append(df_candleStick["close"][-1])

plRange = buy_close[-1] - buy_entry[-1]

pl[-1] = pl[-2] + plRange * lot

pos -= 1

buyCloseSignals.append(df_candleStick.index[-1])

nOfTrade += 1

plPerTrade.append(plRange*lot)

elif pos ==-1:

sell_close.append(df_candleStick["close"][-1])

plRange = sell_entry[-1] - sell_close[-1]

pl[-1] = pl[-2] + plRange * lot

pos +=1

sellCloseSignals.append(df_candleStick.index[-1])

nOfTrade += 1

plPerTrade.append(plRange*lot)

return (pl, buyEntrySignals, sellEntrySignals, buyCloseSignals, sellCloseSignals, nOfTrade, plPerTrade)

def describeResult(self, entryTerm, closeTerm, fileName=None, candleTerm=None, rangeTh=5000, rangeTerm=15, originalWaitTerm=10, waitTh=10000, showFigure=True, cost=0):

"""

signalsは買い，売り，中立が入った配列

"""

import matplotlib.pyplot as plt

if fileName == None:

s_hour = 0

s_min = 0

e_hour = 23

e_min = 59

number = int((e_hour - s_hour)*60 + e_min - s_min)

start_timestamp = datetime.datetime(2018, 3, 24, s_hour, s_min, 0, 0).timestamp()

end_timestamp = datetime.datetime(2018, 3, 24, e_hour, e_min, 0, 0).timestamp()

candleStick = self.getSpecifiedCandlestick(number, "60", start_timestamp, end_timestamp)

else:

candleStick = self.readDataFromFile(fileName)

if candleTerm != None:

df_candleStick = self.processCandleStick(candleStick, candleTerm)

else:

df_candleStick = self.fromListToDF(candleStick)

entryLowLine, entryHighLine = self.calculateLines(df_candleStick, entryTerm)

closeLowLine, closeHighLine = self.calculateLines(df_candleStick, closeTerm)

judgement = self.judge(df_candleStick, entryHighLine, entryLowLine, closeHighLine, closeLowLine, entryTerm)

pl, buyEntrySignals, sellEntrySignals, buyCloseSignals, sellCloseSignals, nOfTrade, plPerTrade = self.backtest(judgement, df_candleStick, 1, rangeTh, rangeTerm, originalWaitTerm=originalWaitTerm, waitTh=waitTh, cost=cost)

plt.figure()

plt.subplot(211)

plt.plot(df_candleStick.index, df_candleStick["high"])

plt.plot(df_candleStick.index, df_candleStick["low"])

plt.ylabel("Price(JPY)")

ymin = min(df_candleStick["low"]) - 200

ymax = max(df_candleStick["high"]) + 200

plt.vlines(buyEntrySignals, ymin , ymax, "blue", linestyles='dashed', linewidth=1)

plt.vlines(sellEntrySignals, ymin , ymax, "red", linestyles='dashed', linewidth=1)

plt.vlines(buyCloseSignals, ymin , ymax, "black", linestyles='dashed', linewidth=1)

plt.vlines(sellCloseSignals, ymin , ymax, "green", linestyles='dashed', linewidth=1)

plt.subplot(212)

plt.plot(df_candleStick.index, pl)

plt.hlines(y=0, xmin=df_candleStick.index[0], xmax=df_candleStick.index[-1], colors='k', linestyles='dashed')

plt.ylabel("PL(JPY)")

#各統計量の計算および表示．

winTrade = sum([1 for i in plPerTrade if i > 0])

loseTrade = sum([1 for i in plPerTrade if i < 0])

winPer = round(winTrade/(winTrade+loseTrade) * 100,2)

winTotal = sum([i for i in plPerTrade if i > 0])

loseTotal = sum([i for i in plPerTrade if i < 0])

profitFactor = round(winTotal/-loseTotal, 3)

maxProfit = max(plPerTrade)

maxLoss = min(plPerTrade)

print("Total pl: {}JPY".format(int(pl[-1])))

print("The number of Trades: {}".format(nOfTrade))

print("The Winning percentage: {}%".format(winPer))

print("The profitFactor: {}".format(profitFactor))

print("The maximum Profit and Loss: {}JPY, {}JPY".format(maxProfit, maxLoss))

if showFigure:

plt.show()

else:

plt.clf()

return pl[-1], profitFactor

def getCandlestick(self, number, period):

"""

number:ローソク足の数．period:ローソク足の期間（文字列で秒数を指定，Ex:1分足なら"60"）．cryptowatchはときどきおかしなデータ（price=0）が含まれるのでそれを除く．

"""

#ローソク足の時間を指定

periods = [period]

#クエリパラメータを指定

query = {"periods":','.join(periods)}

#ローソク足取得

res = \

json.loads(requests.get("https://api.cryptowat.ch/markets/bitflyer/btcfxjpy/ohlc", params=query).text)[

"result"]

# ローソク足のデータを入れる配列．

data = []

for i in periods:

row = res[i]

length = len(row)

for column in row[:length - (number + 1):-1]:

# dataへローソク足データを追加．

if column[4] != 0:

column = column[0:6]

data.append(column)

return data[::-1]

def fromListToDF(self, candleStick):

"""

Listのローソク足をpandasデータフレームへ．

"""

date = [price[0] for price in candleStick]

priceOpen = [int(price[1]) for price in candleStick]

priceHigh = [int(price[2]) for price in candleStick]

priceLow = [int(price[3]) for price in candleStick]

priceClose = [int(price[4]) for price in candleStick]

date_datetime = map(datetime.datetime.fromtimestamp, date)

dti = pd.DatetimeIndex(date_datetime)

df_candleStick = pd.DataFrame({"open" : priceOpen, "high" : priceHigh, "low": priceLow, "close" : priceClose}, index=dti)

return df_candleStick

def processCandleStick(self, candleStick, timeScale):

"""

1分足データから各時間軸のデータを作成.timeScaleには5T（5分），H（1時間）などの文字列を入れる

"""

df_candleStick = self.fromListToDF(candleStick)

processed_candleStick = df_candleStick.resample(timeScale).agg({'open': 'first','high':'max','low': 'min','close': 'last'})

processed_candleStick = processed_candleStick.dropna()

return processed_candleStick

#csvファイル（ヘッダなし）からohlcデータを作成．

def readDataFromFile(self,filename):

for i in range(1, 10, 1):

with open(filename, 'r', encoding="utf-8") as f:

reader = csv.reader(f)

header = next(reader)

for row in reader:

candleStick = [row for row in reader if row[4] != "0"]

dtDate = [datetime.datetime.strptime(data[0], '%Y-%m-%d %H:%M:%S') for data in candleStick]

dtTimeStamp = [dt.timestamp() for dt in dtDate]

for i in range(len(candleStick)):

candleStick[i][0] = dtTimeStamp[i]

candleStick = [[float(i) for i in data] for data in candleStick]

return candleStick

def lineNotify(self, message, fileName=None):

payload = {'message': message}

headers = {'Authorization': 'Bearer ' + self.line_notify_token}

if fileName == None:

try:

requests.post(self.line_notify_api, data=payload, headers=headers)

except:

pass

else:

try:

files = {"imageFile": open(fileName, "rb")}

requests.post(self.line_notify_api, data=payload, headers=headers, files = files)

except:

pass

def describePLForNotification(self, pl, df_candleStick):

import matplotlib

matplotlib.use('Agg')

import matplotlib.pyplot as plt

close = df_candleStick["close"]

index = range(len(pl))

# figure

fig = plt.figure(figsize=(20,12))

#for price

ax = fig.add_subplot(2, 1, 1)

ax.plot(df_candleStick.index, close)

ax.set_xlabel('Time')

# y axis

ax.set_ylabel('The price[JPY]')

#for PLcurve

ax = fig.add_subplot(2, 1, 2)

# plot

ax.plot(index, pl, color='b', label='The PL curve')

ax.plot(index, [0]*len(pl), color='b',)

# x axis

ax.set_xlabel('The number of Trade')

# y axis

ax.set_ylabel('The estimated Profit/Loss(JPY)')

# legend and title

ax.legend(loc='best')

ax.set_title('The PL curve(Time span:{})'.format(self.candleTerm))

# save as png

today = datetime.datetime.now().strftime('%Y%m%d')

number = "_" + str(len(pl))

fileName = today + number + ".png"

plt.savefig(fileName)

plt.close()

return fileName

def loop(self,entryTerm, closeTerm, rangeTh, rangeTerm,originalWaitTerm, waitTh,candleTerm=None):

"""

注文の実行ループを回す関数

"""

self.executionsProcess()

#pubnubが回り始めるまで待つ．

time.sleep(20)

pos = 0

pl = []

pl.append(0)

lastPositionPrice = 0

lot = self.lot

originalLot = self.lot

waitTerm = 0

try:

candleStick = self.getCandlestick(50, "60")

except:

print("Unknown error happend when you requested candleStick")

if candleTerm == None:

df_candleStick = self.fromListToDF(candleStick)

else:

df_candleStick = self.processCandleStick(candleStick, candleTerm)

entryLowLine, entryHighLine = self.calculateLines(df_candleStick, entryTerm)

closeLowLine, closeHighLine = self.calculateLines(df_candleStick, closeTerm)

#直近約定件数30件の高値と安値

high = max([self.executions[-1-i]["price"] for i in range(30)])

low = min([self.executions[-1-i]["price"] for i in range(30)])

while True:

#1分ごとに基準ラインを更新

if datetime.datetime.now().second < 2 :

print("Renewing candleSticks")

try:

candleStick = self.getCandlestick(50, "60")

except:

print("Unknown error happend when you requested candleStick")

if candleTerm == None:

df_candleStick = self.fromListToDF(candleStick)

else:

df_candleStick = self.processCandleStick(candleStick, candleTerm)

entryLowLine, entryHighLine = self.calculateLines(df_candleStick, entryTerm)

closeLowLine, closeHighLine = self.calculateLines(df_candleStick, closeTerm)

#直近約定件数30件の貴音と安値

high = max([self.executions[-1-i]["price"] for i in range(30)])

low = min([self.executions[-1-i]["price"] for i in range(30)])

judgement = self.judgeForLoop(high, low, entryHighLine, entryLowLine, closeHighLine, closeLowLine)

#現在レンジ相場かどうか．

isRange = self.isRange(df_candleStick, rangeTerm, rangeTh)

try :

ticker = self.api.ticker(product_code=self.product_code)

except:

print("Unknown error happend when you requested ticker.")

finally:

pass

best_ask = ticker["best_ask"]

best_bid = ticker["best_bid"]

#ここからエントリー，クローズ処理

if pos == 0 and not isRange[-1]:

#ロングエントリー

if judgement[0]:

print(datetime.datetime.now())

self.order.market(size=lot, side="BUY")

pos += 1

message = "Long entry. Lot:{}, Price:{}".format(lot, best_ask)

self.lineNotify(message)

lastPositionPrice = best_ask

#ショートエントリー

elif judgement[1]:

print(datetime.datetime.now())

self.order.market(size=lot,side="SELL")

pos -= 1

message = "Short entry. Lot:{}, Price:{}, ".format(lot, best_bid)

self.lineNotify(message)

lastPositionPrice = best_bid

elif pos == 1:

#ロングクローズ

if judgement[2]:

print(datetime.datetime.now())

self.order.market(size=lot,side="SELL")

pos -= 1

plRange = best_bid - lastPositionPrice

pl.append(pl[-1] + plRange * lot)

message = "Long close. Lot:{}, Price:{}, pl:{}".format(lot, best_bid, pl[-1])

fileName = self.describePLForNotification(pl, df_candleStick)

self.lineNotify(message,fileName)

#一定以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．

if plRange > waitTh:

waitTerm = originalWaitTerm

lot = round(originalLot/10,3)

if waitTerm > 0:

waitTerm -= 1

lot = round(originalLot/10,3)

if waitTerm == 0:

lot = originalLot

elif pos == -1:

#ショートクローズ

if judgement[3]:

print(datetime.datetime.now())

self.order.market(size=lot, side="BUY")

pos += 1

plRange = lastPositionPrice - best_ask

pl.append(pl[-1] + plRange * lot)

message = "Short close. Lot:{}, Price:{}, pl:{}".format(lot, best_ask, pl[-1])

fileName = self.describePLForNotification(pl, df_candleStick)

self.lineNotify(message,fileName)

#一定以上の値幅を取った場合，次の10トレードはロットを1/10に落とす．

if plRange > waitTh:

waitTerm = originalWaitTerm

lot = round(originalLot/10,3)

if waitTerm > 0:

waitTerm -= 1

lot = round(originalLot/10,3)

if waitTerm == 0:

lot = originalLot

time.sleep(0.5)

message = "Waiting for channelbreaking."

if datetime.datetime.now().minute % 5 == 0 and datetime.datetime.now().second < 1:

print(message)

self.lineNotify(message)

def executionsProcess(self):

"""

pubnubで価格を取得する場合の処理（基本的に不要．）

"""

channels = ["lightning_executions_FX_BTC_JPY"]

executions = self.executions

class BFSubscriberCallback(SubscribeCallback):

def message(self, pubnub, message):

execution = message.message

for i in execution:

executions.append(i)

config = PNConfiguration()

config.subscribe_key = 'sub-c-52a9ab50-291b-11e5-baaa-0619f8945a4f'

config.reconnect_policy = PNReconnectionPolicy.LINEAR

config.ssl = False

config.set_presence_timeout(60)

pubnub = PubNubTornado(config)

listener = BFSubscriberCallback()

pubnub.add_listener(listener)

pubnub.subscribe().channels(channels).execute()

pubnubThread = threading.Thread(target=pubnub.start)

pubnubThread.start()

def getSpecifiedCandlestick(self,number, period, start_timestamp, end_timestamp):

"""

number:ローソク足の数．period:ローソク足の期間（文字列で秒数を指定，Ex:1分足なら"60"）．cryptowatchはときどきおかしなデータ（price=0）が含まれるのでそれを除く

"""

# ローソク足の時間を指定

periods = [period]

# クエリパラメータを指定

query = {"periods": ','.join(periods), "after": str(int(start_timestamp)), "before": str(int(end_timestamp))}

# ローソク足取得

try:

res = json.loads(requests.get("https://api.cryptowat.ch/markets/bitflyer/btcfxjpy/ohlc", params=query).text)

res = res["result"]

except:

print(res)

# ローソク足のデータを入れる配列．

data = []

for i in periods:

row = res[i]

length = len(row)

for column in row[:length - (number + 1):-1]:

# dataへローソク足データを追加．

if column[4] != 0:

column = column[0:6]

data.append(column)

return data[::-1]

#注文処理をまとめている

class Order:

def __init__(self):

self.product_code = "FX_BTC_JPY"

self.key = "your key"

self.secret = "your secret"

self.api = pybitflyer.API(self.key, self.secret)

def limit(self, side, price, size, minute_to_expire=None):

print("Order: Limit. Side : {}".format(side))

response = {"status":"internalError in order.py"}

try:

response = self.api.sendchildorder(product_code=self.product_code, child_order_type="LIMIT", side=side, price=price, size=size, minute_to_expire = minute_to_expire)

except:

pass

while "status" in response:

try:

response = self.api.sendchildorder(product_code=self.product_code, child_order_type="LIMIT", side=side, price=price, size=size, minute_to_expire = minute_to_expire)

except:

pass

time.sleep(3)

return response

def market(self, side, size, minute_to_expire= None):

print("Order: Market. Side : {}".format(side))

response = {"status": "internalError in order.py"}

try:

response = self.api.sendchildorder(product_code=self.product_code, child_order_type="MARKET", side=side, size=size, minute_to_expire = minute_to_expire)

except:

pass

while "status" in response:

try:

response = self.api.sendchildorder(product_code=self.product_code, child_order_type="MARKET", side=side, size=size, minute_to_expire = minute_to_expire)

except:

pass

time.sleep(3)

return response

def stop(self, side, size, trigger_price, minute_to_expire=None):

print("Order: Stop. Side : {}".format(side))

response = {"status": "internalError in order.py"}

try:

response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "STOP", "side": side, "size": size,"trigger_price": trigger_price, "minute_to_expire": minute_to_expire}])

except:

pass

while "status" in response:

try:

except:

pass

time.sleep(3)

return response

def stop_limit(self, side, size, trigger_price, price, minute_to_expire=None):

print("Side : {}".format(side))

response = {"status": "internalError in order.py"}

try:

response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "STOP_LIMIT", "side": side, "size": size,"trigger_price": trigger_price, "price": price, "minute_to_expire": minute_to_expire}])

except:

pass

while "status" in response:

try:

except:

pass

return response

def trailing(self, side, size, offset, minute_to_expire=None):

print("Side : {}".format(side))

response = {"status": "internalError in order.py"}

try:

response = self.api.sendparentorder(order_method="SIMPLE", parameters=[{"product_code": self.product_code, "condition_type": "TRAIL", "side": side, "size": size, "offset": offset, "minute_to_expire": minute_to_expire}])

except:

pass

while "status" in response:

try:

except:

pass

return response

def optimization():

entryAndCloseTerm = [(5,3),(5,5),(10,10),(20,10)]

rangeThAndrangeTerm = [(5000,5),(5000,15),(10000,15),(None,15),(None,20),(None,15)]

waitTermAndwaitTh = [(10,10000),(10,20000),(5,10000)]

paramList = []

for i in entryAndCloseTerm:

for j in rangeThAndrangeTerm:

for k in waitTermAndwaitTh:

channelBreakOut = ChannelBreakOut()

channelBreakOut.entryTerm = i[0]

channelBreakOut.closeTerm = i[1]

channelBreakOut.rangeTh = j[0]

channelBreakOut.rangeTerm = j[1]

channelBreakOut.waitTerm = k[0]

channelBreakOut.waitTh = k[1]

channelBreakOut.candleTerm = "1T"

#テスト

pl, profitFactor = channelBreakOut.describeResult(entryTerm=channelBreakOut.entryTerm, closeTerm=channelBreakOut.closeTerm, rangeTh=channelBreakOut.rangeTh, rangeTerm=channelBreakOut.rangeTerm, originalWaitTerm=channelBreakOut.waitTerm, waitTh=channelBreakOut.waitTh, candleTerm=channelBreakOut.candleTerm,fileName="20180221_0310.csv", showFigure=False)

paramList.append([pl,profitFactor, i,j,k])

pF = [i[1] for i in paramList]

pL = [i[0] for i in paramList]

print("ProfitFactor max:")

print(paramList[pF.index(max(pF))])

print("PL max:")

print(paramList[pL.index(max(pL))])

if __name__ == '__main__':

#とりあえず5分足，5期間安値・高値でエントリー，クローズする設定

channelBreakOut = ChannelBreakOut()

channelBreakOut.entryTerm = 5

channelBreakOut.closeTerm = 5

channelBreakOut.rangeTh = None

channelBreakOut.rangeTerm = None

channelBreakOut.waitTerm = 0

channelBreakOut.waitTh = 10000

channelBreakOut.candleTerm = "5T"

channelBreakOut.cost = 0

#実働

#channelBreakOut.loop(channelBreakOut.entryTerm, channelBreakOut.closeTerm, channelBreakOut.rangeTh, channelBreakOut.rangeTerm, channelBreakOut.waitTerm, channelBreakOut.waitTh)

#バックテスト

channelBreakOut.describeResult(entryTerm=channelBreakOut.entryTerm, closeTerm=channelBreakOut.closeTerm, rangeTh=channelBreakOut.rangeTh, rangeTerm=channelBreakOut.rangeTerm, originalWaitTerm=channelBreakOut.waitTerm, waitTh=channelBreakOut.waitTh, candleTerm=channelBreakOut.candleTerm,showFigure=True, cost=channelBreakOut.cost)

#最適化

#optimization()