目錄
- BaseStrategy（策略基類）
- Broker（經紀人）
- 示例代碼
- 資料可視化
BaseStrategy（策略基類）
BaseStrategy，交易策略基類
回呼函式
- on_start：策略開始運行
- on_stop：策略運行結束
- next_bar：回測收到新的K線時呼叫
其他函式
- record：記錄自定義資料
- output_record：輸出資料記錄檔案
Broker（經紀人）
Broker 經紀人，負責處理處理撮合交易訂單等功能.
交易相關函式
- pos：當前倉位
- cancel_all：取消所有訂單
- buy：做多
- sell：平多
- short：做空
- cover：平空
- create_stop_order：創建止盈止損訂單
示例代碼
行情資料這里用的是幣安上爬取的分鐘資料，關于資料的爬取和整理可以看這里，
from common.time_utils import timestamp_to_datetime
# 讀取分鐘資料
df = pd.read_csv('ETHUSDT-1m.csv', converters={
'Open time': timestamp_to_datetime,
'Close time': timestamp_to_datetime
})
# 資料清洗
df.rename(columns={
'Open time': 'open_time',
'Close time': 'close_time',
'Open': 'open',
'High': 'high',
'Low': 'low',
'Close': 'close',
'Volume': 'volume',
}, inplace=True)
# 截取指定時間范圍的資料
df = df[df['open_time'] >= '2021-05-01']
df = df[df['close_time'] <= '2021-06-01']
df.reset_index(inplace=True, drop=True)
# print(df)
broker = Broker()
broker.set_symbol('ETHUSDT')
broker.set_strategy(TripleFilterTradeSystemStrategy) # 設定策略類
broker.set_leverage(1.0) # 杠桿比例
broker.set_cash(3600) # 1初始資金.
broker.set_commission(7 / 10000) # 手續費
broker.set_backtest_data(df) # 資料.
broker.run()
broker.calculate().to_csv('triple_filter_trade_system_backtest.csv', index=False)
broker.output_record('triple_filter_trade_system_record.csv')
# 引數優化， 窮舉法， 遺傳演算法，
# broker.optimize_strategy(long_period=[i for i in range(30, 60, 5)], short_period=[i for i in range(5, 30, 1)])
資料可視化
策略中通過record方法記錄了行情資料和交易信號，資料如下：
使用bokeh將K線資料、交易信號和相關技術指標可視化
from math import pi
from bokeh.plotting import figure
import numpy as np
from common.indicator import EMA
import pandas as pd
import talib
from bokeh.layouts import column
from bokeh.io import output_file, show, save
from bokeh.models import ColumnDataSource, HoverTool, RangeTool, CDSView, BooleanFilter, DataRange1d, LinearAxis, \
Range1d, CustomJS
from datetime import datetime
from common.time_utils import timestamp_to_datetime
class Signal:
def __init__(self, data, marker='inverted_triangle', color='#10B479'):
"""
信號
:param data: 信號集資料
:param marker: 標記型別
:param color: 顏色
"""
self.data = data
self.marker = marker
self.color = color
@staticmethod
def signal_below_price(data, price, func):
"""
計算信號標記位置使其位于價格底部
:param data: 信號資料
:param price: 價格資料
:param func: 目標信號判斷條件方法
:return: 位于價格底部的信號集合資料
"""
signal = []
for date, value in data.iteritems():
if func(value):
# signal.append(price[date] * 0.99)
signal.append(price[date])
else:
signal.append(np.nan)
return signal
@staticmethod
def signal_above_price(data, price, func):
"""
計算信號標記位置使其位于價格頂部
:param data: 信號資料
:param price: 價格資料
:param func: 目標信號判斷條件方法
:return: 位于價格頂部的信號集合資料
"""
signal = []
for date, value in data.iteritems():
if func(value):
# signal.append(price[date] * 1.01)
signal.append(price[date])
else:
signal.append(np.nan)
return signal
def make_range_tool(date, close, x_range=None, source=None):
"""
時間范圍選擇工具
:param date:
:param close:
:param x_range:
:param source:
"""
select = figure(title="", plot_height=100, plot_width=1500, x_axis_type="datetime", y_axis_type=None, tools="", toolbar_location=None, background_fill_color="#efefef")
range_tool = RangeTool(x_range=x_range)
range_tool.overlay.fill_color = "navy"
range_tool.overlay.fill_alpha = 0.2
select.line(date, close)
select.ygrid.grid_line_color = None
select.add_tools(range_tool)
select.toolbar.active_multi = range_tool
return select
def make_force_index_plot(source, color='#7922AD', x_range=None):
"""
強力指數
:param source: 列格式：date, efi, colors_efi
:param color:
:param x_range:
:param source:
"""
TOOLS = "crosshair,pan,wheel_zoom,box_zoom,reset,save"
p = figure(x_axis_type="datetime", title="Force Index", plot_width=1500, plot_height=240, tools=TOOLS, toolbar_location='right', x_range=x_range)
line = p.line(x='date', y='efi', line_width=1, color=color, source=source)
# 懸浮提示
hover_tool = HoverTool(
tooltips="""
<div">
<div><b>EFI：</b><span style="font-size: 10px; color: @colors_efi;">@efi{0,0}</span></div>
<div><b>Date：</b>@date{%F %T}</div>
<div><b>Y：</b>$y{0.000}</div>
</div>
""",
formatters={
'@date': 'datetime', # use 'datetime' formatter for 'date' field
},
# display a tooltip whenever the cursor is vertically in line with a glyph
# "mouse":only when the mouse is directly over a glyph
# "vline": whenever the a vertical line from the mouse position intersects a glyph
# "hline": whenever the a horizontal line from the mouse position intersects a glyph
mode='vline',
# 是否顯示箭頭
show_arrow=True,
# line_policy='nearest',
renderers=[line]
)
p.add_tools(hover_tool)
return p
def make_candlestick_plot(df, period=None, signals=None, title='', filename=None, ema=(5, 10, 20), ema_color=('#C09A1C', '#7922AD', '#167BE1'), source=None):
"""
蠟燭圖
:param df: 資料集，格式：date, open, high, low, close, volume
:param period: 時間周期，默認，單位毫秒
:param signals: 信號集
:param title: 標題
:param filename: 檔案名
:param ema: 移動平均線
:param ema_color: 移動平均線顏色
:param source: 資料源
"""
inc = df.close > df.open
dec = df.open > df.close
w = period * 0.5 if period else 24 * 60 * 60 * 1000 # half day in ms
# TOOLS = "pan,wheel_zoom,box_zoom,reset,save"
TOOLS = "crosshair,pan,wheel_zoom,box_zoom,reset,save"
# 蠟燭圖
p_candlestick = figure(x_axis_type="datetime", plot_width=1500, plot_height=450, tools=TOOLS, title=title, x_range=(df.date.iloc[0], df.date.iloc[-1]))
# p_candlestick.sizing_mode = 'stretch_both' # 全屏
p_candlestick.xaxis.major_label_orientation = pi / 4 # x軸標題傾斜
p_candlestick.grid.grid_line_alpha = 0.3
# 繪制影線
p_candlestick.segment(x0='date', y0='high', x1='date', y1='low', color="black", source=source)
# 繪制柱體
p_candlestick.vbar(df.date[inc], w, df.open[inc], df.close[inc], fill_color="#10B479", line_color="black")
p_candlestick.vbar(df.date[dec], w, df.open[dec], df.close[dec], fill_color="#DD253E", line_color="black")
# 繪制EMA
ema_lines = []
if ema:
for index in range(0, len(ema)):
key = 'ema%s' % ema[index]
if key not in df:
df[key] = EMA(df.close, ema[index])
line = p_candlestick.line(x='date', y=key, line_color=ema_color[index], legend_label='EMA%s' % (ema[index]), source=source)
ema_lines.append(line)
# 繪制信號
if signals:
for signal in signals:
p_candlestick.scatter(df.date, signal.data, marker=signal.marker, size=20, color=signal.color, alpha=0.6)
if filename:
output_file(filename, title=title, mode='inline')
# show(p_candlestick)
# 圖例
p_candlestick.legend.location = "top_left"
p_candlestick.legend.border_line_alpha = 0
p_candlestick.legend.background_fill_alpha = 0
p_candlestick.legend.click_policy = "hide"
return p_candlestick, ema_lines
def plot_middle_period(path, symbol):
"""
繪制中周期圖示
:param path: 資料表路徑，列格式：date, open, high, low, close, volume
:param symbol： 交易對名稱
"""
df = pd.read_csv(path, parse_dates=True, index_col=0)
df["date"] = df.index
up_color = '#10B479'
down_color = '#DD253E'
# 計算漲幅
pre_close = df.close.shift(1)
df['increase'] = (df.close - pre_close) / pre_close * 100
# EMA
df['ema5'] = EMA(df.close, 5)
df['ema10'] = EMA(df.close, 10)
df['ema20'] = EMA(df.close, 20)
# 開高低收價格顏色
df['colors_open'] = np.where((df.open - pre_close) > 0, up_color, down_color)
df['colors_high'] = np.where((df.high - pre_close) > 0, up_color, down_color)
df['colors_low'] = np.where((df.low - pre_close) > 0, up_color, down_color)
df['colors_close'] = np.where((df.close - pre_close) > 0, up_color, down_color)
# 均線顏色
df['colors_ema5'] = np.where((df['ema5'].diff()) > 0, up_color, down_color)
df['colors_ema10'] = np.where((df['ema10'].diff()) > 0, up_color, down_color)
df['colors_ema20'] = np.where((df['ema20'].diff()) > 0, up_color, down_color)
# EFI顏色
df['colors_efi'] = np.where(df['efi'] > 0, up_color, down_color)
# 做多信號
long_signal = Signal(Signal.signal_below_price(df['signals'], df['low'], lambda signals: 'buy' in signals), 'triangle', '#10B479')
# 做空信號
short_signal = Signal(Signal.signal_above_price(df['signals'], df['high'], lambda signals: 'short' in signals), 'inverted_triangle', '#DD253E')
filename = 'triple_filter_trade_system_middle.html'
title = '%s 三重濾網交易系統' % symbol
# 資料源
source = ColumnDataSource(df)
# ETH/USDT 5分鐘K線圖
p_candlestick, ema_lines = make_candlestick_plot(df, period=5 * 60 * 1000, signals=[long_signal, short_signal], title=title, source=source)
# 強力指數圖
p_efi = make_force_index_plot(source, x_range=p_candlestick.x_range)
# 懸浮提示
hover_tool = HoverTool(
tooltips="""
<div">
<div><b>Open：</b><span style="font-size: 10px; color: @colors_open;">@open{0.000}</span></div>
<div><b>High：</b><span style="font-size: 10px; color: @colors_high;">@high{0.000}</span></div>
<div><b>Low：</b><span style="font-size: 10px; color: @colors_low;">@low{0.000}</span></div>
<div><b>Close：</b><span style="font-size: 10px; color: @colors_close;">@close{0.000}</span></div>
<div><b>Increase：</b><span style="font-size: 10px; color: @colors_close;">@increase{0.00}%</span></div>
<div><b>Volume：</b><span style="font-size: 10px; color: @colors_close;">@volume{0,0}</span></div>
<div><b>EMA5：</b><span style="font-size: 10px; color: @colors_ema5;">@ema5{0.000}</span></div>
<div><b>EMA10：</b><span style="font-size: 10px; color: @colors_ema10;">@ema10{0.000}</span></div>
<div><b>EMA20：</b><span style="font-size: 10px; color: @colors_ema20;">@ema20{0.000}</span></div>
<div><b>EFI：</b><span style="font-size: 10px; color: @colors_efi;">@efi{0,0}</span></div>
<div><b>Date：</b>@date{%F %T}</div>
<div><b>Y：</b>$y{0.000}</div>
</div>
""",
formatters={
'@date': 'datetime',
},
mode='vline',
# 是否顯示箭頭
show_arrow=True,
renderers=[ema_lines[0]],
# point_policy='snap_to_data',
)
p_candlestick.add_tools(hover_tool)
range_tool = make_range_tool(df.date, df.close, x_range=p_candlestick.x_range, source=source)
layout = column(range_tool, p_candlestick, p_efi)
output_file(filename, title=title, mode='inline')
show(layout)
專案地址：https://github.com/linchaolong/SimpleQuant
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標籤：區塊鏈
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