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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。
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
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)
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()
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}")
For more demo code and strategy demo, Please check the course, some homeworks may required to completed.
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。
QQ社群:1032965883
wechat: 82789754
如果无法解决请前往官方社区论坛的
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。
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:
autopep8 --in-place --recursive .
即可。flake8
即可。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
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 |
Quant Framework | |
---|---|
CryptoQuant量化框架 | Code |
Web/APP开发
量化交易系统定制
量化策略定制
wechat: studyquant88
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