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README
Apache-2.0

An Quantatitive trading library for crypto-assets 数字货币量化交易框架

量化交易课程

量化课程推荐

交易所注册推荐码

cryptoquant

CryptoQuant is an algorithmic trading library for crypto-assets written in Python. It allows trading strategies to be easily expressed and backtested against historical data (with daily and minute resolution), providing analytics and insights regarding a particular strategy's performance. cryptoquant also supportslive-trading of crypto-assets starting with many exchanges (Okex,Binance,Bitmex etc) with more being added over time.

CryptoQuant是一套基于Python的量化交易框架,帮助个人/机构量化人员进行数字货币量化交易。框架具有回测/实盘交易功能。 策略框架支持多个平台切换回测。 并提供交易所实盘交易接口(如OKEX) 。

全新的《Python数字货币量化投资实战》系列在线课程,已经在微信公众号[StudyQuant]上线,一整套数字货币量化解决方案。覆盖CTA等策略(已完成)等内容。

Features

  • Ease of Use: CryptoQuant tries to get out of your way so that you can focus on algorithm development.
  • 开箱即用 : CryptoQuant提供一套量化框架帮助您专注策略开发
  • 回测:回测框架支持数据导入,自定义交易订单号,多线程回测、遗传算法寻优等功能
  • 实盘交易: 框架提供数字货币交易所接口DEMO
  • 文档支持:官方社区论坛

环境准备

  • 支持的系统版本:Windows 7以上/Windows Server 2008以上/Ubuntu 18.04 LTS
  • 支持的Python版本:Python 3.6 64位/ 3.7+

Installation

Windows 使用要安装Python,激活环境,进入cryptoquant/install目录下的运行install.bat 安装依赖库 安装dependencies 中的依赖库

Quickstart

如何导入数据

from cryptoquant.trader.constant import Direction, Exchange, Interval, Offset, Status, Product, OptionType, OrderType
import pandas as pd
from cryptoquant.app.data_manage.data_manager import save_data_to_cryptoquant

if __name__ == '__main__':
    df = pd.read_csv('IF9999.csv')
    symbol = 'IF9999'
    save_data_to_cryptoquant(symbol, df, Exchange.CFFEX)
    

如何回测

from datetime import datetime
from cryptoquant.app.cta_backtester.engine import BacktestingEngine, OptimizationSetting
from cryptoquant.app.cta_strategy.strategies.atr_rsi_strategy import (
    AtrRsiStrategy,
)
#%%
engine = BacktestingEngine()

engine.set_parameters(
    vt_symbol="IF9999.CFFEX",
    interval="1m",
    start=datetime(2020, 1, 1),
    end=datetime(2020, 4, 30),
    rate=0.3/10000,
    slippage=0.5,
    size=300,
    pricetick=0.2,
    capital=1_000_0,
)
setting = {}
engine.add_strategy(AtrRsiStrategy,setting)
# 导入数据
engine.load_data()
# 开始回测
engine.run_backtesting()
#计算收益
df = engine.calculate_result()
# 开始统计
engine.calculate_statistics()
# 开始画图
engine.show_chart()

    

实盘交易


from cryptoquant.api.api_gateway.build.apigateway_v7 import get_exchange
from cryptoquant.config.config import ok_api_key, ok_seceret_key, ok_passphrase,binance_api_key,binance_secret_key



if __name__ == "__main__":
    setting ={
        'symbol':"EOS/USDT",
        'api_key':binance_api_key,
        'secret':binance_secret_key,
        'base_asset':'EOS',
        'quote_asset':'USDT',
        'sleep_time':5,
        'time_frame':'5m'
    }

    apikey = binance_api_key
    secret = binance_secret_key
    symbol = "EOS/USDT"
    time_frame = '5m'
    strategy_name = 'apidemo'

    exchange = get_exchange(symbol, apikey, secret, time_frame, strategy_name, setting)

    print('GEt Trades', exchange.GetTrades())
    print('GEt Ticker',exchange.GetTicker())
    print('GEt Depth',exchange.GetDepth())
    print('GetAccount',exchange.GetAccount())
    print('获取K线',exchange.GetKline(time_frame))
    print('get Orders',exchange.GetOrders())
    print('get open Orders',exchange.GetOpenOrders())

    # 买单
    buy_order = exchange.Buy(Price = 3,Amount = 4)
    print(f"获取订单{exchange.GetOrder(buy_order.id)}")

    # 撤单
    cancel_order = exchange.CancelOrder(buy_order.id)
    print(f"取消订单{cancel_order}")

    # 卖单
    sell_order = exchange.Sell(Price = 5,Amount = 4)
    print(f"获取订单{exchange.GetOrder(buy_order.id)}")

    # 撤单
    cancel_order = exchange.CancelOrder(sell_order.id)
    print(f"取消订单{cancel_order}")


更多示例代码和维护的交易系统

For more demo code and strategy demo, Please check the course, some homeworks may required to completed.

1.0 数字货币量化课程

2.0 Python领域开发入门

捐助

如果您觉得我们的开源软件对你有所帮助,请扫下方二维码购买课程支持。

Questions?

  • QQ社群:1032965883

  • wechat: 82789754

  • 如果无法解决请前往官方社区论坛

    如果你有什么量化问题、python学习、课程咨询等问题,都可以咨询我。

贡献代码

非常希望大牛来贡献代码,完善项目功能。

在提交代码的时候,请遵守以下规则,以提高代码质量:

  • 使用autopep8格式化你的代码。运行autopep8 --in-place --recursive . 即可。
  • 使用flake8检查你的代码,确保没有error和warning。在项目根目录下运行flake8即可。

开发日志

2021-12-09 v1.3

  • 更新BINANCE封装好的接口

  • 更新 CCXT接口教学

  • 添加 定投策略示例

2021-05-07 v1.2

更改目录结构 增加文档链接 文档补充

2021-01-15 v1.1

  • 添加了APIGATEWAY 模板

  • 支持回测,遗传算法调优。

  • 数据导入

  • 自定义订单号

  • 实盘交易demo

2020-08-15 v1.0

  • 开源框架

Course Links 课程链接

Course Links
股票-Python量化投资 Course
Crypto-Python量化投资与数字货币CryptoQuant Course
期货-量化投资程序化交易 Course
量化训练营 Course
其他 Course

量化开源框架

Quant Framework
CryptoQuant量化框架 Code

定制业务

Web/APP开发

量化交易系统定制

  • 支持TICK、分钟及多周期回测及实盘交易
  • 多品种交易

量化策略定制

  • 趋势、网格等
  • 套利

关注StudyQuant

联系方式

wechat: studyquant88

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An Quantatitive trading library for crypto-assets 数字货币量化交易框架 社区文档:https://www.yuque.com/studyquant/cryptoquant 展开 收起
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