BitMEXのトレード損益をグラフにする

https://gyazo.com/bd59ba115fac03de72586263e57b5d13

環境

MacOSX

python3

pandas

ccxt

インストール

code:sh

pip install plotly

ソース

code:mexhistory.py

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

import argparse

import dateutil.parser

import ccxt

import pandas as pd

import plotly.offline as offline

import plotly.graph_objs as go

def store_datetime(str):

dt = dateutil.parser.parse(str)

return dt.strftime('%Y-%m-%dT%H:%M:%S')

parser = argparse.ArgumentParser(description="")

parser.add_argument("--symbol", type=str, default='BTC/USD')

parser.add_argument("--apiKey", type=str, default='')

parser.add_argument("--secret", type=str, default='')

parser.add_argument("--pine", action="store_true")

parser.add_argument("--since", type=store_datetime)

parser.add_argument("--plotly", action="store_true")

args = parser.parse_args()

exchange = ccxt.bitmex({

'apiKey': args.apiKey,

'secret': args.secret,

})

def fetch_trade_history(symbol=args.symbol, since=None, limit=None):

exchange.load_markets()

market = None

request = {}

if symbol is not None:

market = exchange.market(symbol)

if since is not None:

if limit is not None:

if 'filter' in request:

response = exchange.privateGetExecutionTradeHistory(request)

df = pd.DataFrame(response)

return df

if args.pine:

print(

'//@version=3\n'

'study("Bitmexトレード", overlay=true)\n'

'exec_time(transactTime) =>\n'

' result = false\n'

' if time < transactTime and transactTime < (time + delta)\n'

' result := true\n'

' result\n'

'pnl = 0\n'

'buy_price = close\n'

'buy_price := na\n'

'sell_price = close\n'

'sell_price := na\n'

)

else:

print('transactTime,symbol,execType,side,lastQty,lastPx,execCost,commission,execComm,ordType,orderQty,leavesQty,price,text,orderID,execCost_sum,execComm_sum,lastQty_sum,unrealizedPnl_sum')

count = 100

since = args.since

execCost_sum = 0

execComm_sum = 0

lastQty_sum = 0

unrealizedPnl_sum = 0

chartIndex = []

lastPx = []

execComm = []

unrealizedPnl = []

while True:

df = fetch_trade_history(since=since, limit=count)

for index, row in df.iterrows():

execComm_sum = execComm_sum + row.execComm

if row.execType == "Trade":

execCost_sum = execCost_sum + row.execCost

if row.side == "Buy":

lastQty_sum = lastQty_sum + row.lastQty

else:

lastQty_sum = lastQty_sum - row.lastQty

unrealizedPnl_sum = -(execCost_sum + int(lastQty_sum / row.lastPx * 100000000))

chartIndex.append(row.transactTime)

lastPx.append(row.lastPx)

execComm.append(execComm_sum)

unrealizedPnl.append(unrealizedPnl_sum)

if args.pine:

d = {

'transactTime': row.transactTime,

'side': row.side,

'lastQty': row.lastQty,

'price': row.price,

'buy_price': row.price if row.side == 'Buy' else 'na',

'sell_price': row.price if row.side == 'Sell' else 'na',

'pnl': unrealizedPnl_sum,

'timestamp': int(row.transactTime.timestamp())*1000,

}

print(

'// {transactTime} {side} {lastQty} {price}\n'

'if exec_time({timestamp})\n'

' pnl:={pnl}\n'

' buy_price:={buy_price}\n'

' sell_price:={sell_price}\n'.format(**d)

)

else:

print('{transactTime},{symbol},{execType},{side},{lastQty},{lastPx},{execCost},'

'{commission},{execComm},{ordType},{orderQty},{leavesQty},{price},"{text}",'

'{orderID},{execCost_sum},{execComm_sum},{lastQty_sum},{unrealizedPnl_sum}'.format(**row))

since = row.timestamp

if len(df.index) < count:

break

if args.pine:

print(

'plot(buy_price, color=green, linewidth=2)\n'

'plot(sell_price, color=red, linewidth=2)\n'

'//plot(pnl<0?-pnl:pnl, color=pnl>=0?green::orange, linewidth=4, style=area, transp=80)\n'

'plotshape(buy_price, style=shape.arrowup, location=location.belowbar, size=size.large)\n'

'plotshape(sell_price, style=shape.arrowdown, location=location.abovebar, size=size.large)\n'

)

if args.plotly:

price_line = go.Scatter(

x = chartIndex,

y = lastPx,

mode = 'lines',

name = 'rice'

)

pnl_area = go.Scatter(

x = chartIndex,

y = unrealizedPnl,

yaxis='y2',

fill='tozeroy',

mode= 'none',

name='Profit and Loss')

# 2軸グラフレイアウト作成

layout = go.Layout(

title='Price vs Volume',

yaxis=dict(

title='Price'

),

yaxis2=dict(

title='Profit and Loss',

overlaying='y',

side='right'

)

)

fig = go.Figure(data=data, layout=layout)

offline.plot(fig, filename='sample.html', auto_open=False)

使い方

code:sh

python mexhistory.py --apiKey xxxx --secret xxxx --since 2018/4/5 --plotly

コマンドを実行したディレクトリに sample.html が出力されるのでこれをウェブブラウザで開くとグラフが表示されれる。

ビットコインアドレス

3MtsP5ZKAuVA5pH2mDTFpHxHPG2JWC4Kop