support both of Perpetual Swap and Swap Trading
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parent
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commit
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/core/__pycache__
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/__pycache__/*.pyc
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import logging
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from time import sleep
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from core.base import QuantTrader
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from core.strategy import QuantStrategy
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from config import API_KEY, SECRET_KEY, PASSPHRASE, TRADING_CONFIG, TIME_CONFIG
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logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
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class BizMain:
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def __init__(self):
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api_key = API_KEY
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secret_key = SECRET_KEY
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passphrase = PASSPHRASE
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sandbox = TRADING_CONFIG.get("sandbox", True)
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symbol = TRADING_CONFIG.get("symbol", "BTC-USDT")
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position_size = TRADING_CONFIG.get("position_size", 0.001)
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self.trader = QuantTrader(api_key, secret_key, passphrase, sandbox, symbol, position_size)
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# self.strategy = QuantStrategy(api_key, secret_key, passphrase, sandbox, symbol, position_size)
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def start_job(self):
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"""
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1. 合约开空单流程
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1.1. 获取当前价格
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1.2 设置tdmode为cross，张数为1，每张货币单位为0.01，杠杆为1，缓冲比例为0.3
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1.2. 计算保证金
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1.4. 开空单
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2. 现货卖出虚拟货币流程
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2.1 获取当前虚拟货币数量
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2.2 卖出0.01单位虚拟货币
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3. 合约平空单流程
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3.1 设置tdmode为cross，张数为1
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3.2 平空单
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"""
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td_mode = "cross"
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quantity = 1
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try:
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# 1. 合约开空单流程
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logging.info("[1] 合约开空单流程：")
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# price = self.trader.get_current_price(self.trader.symbol_swap)
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# logging.info(f"当前合约价格: {price}")
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slot = 0.01
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leverage = 1
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buffer_ratio = 0.3
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# margin, entry_price = self.trader.calculate_margin(quantity, leverage, slot, buffer_ratio)
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# logging.info(f"所需保证金: {margin}, 开仓价格: {entry_price}")
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order_id, entry_price = self.trader.place_short_order(td_mode, quantity, leverage, slot, buffer_ratio)
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if order_id:
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logging.info(f"开空单成功，订单ID: {order_id}, 开仓价格: {entry_price}")
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else:
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logging.error("开空单失败")
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except Exception as e:
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logging.error(f"合约开空单流程异常: {e}")
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sleep(1)
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try:
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# 2. 现货卖出比特币流程
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logging.info(f"[2] 现货卖出{self.trader.symbol_prefix}流程：")
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balance = self.trader.get_account_balance()
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btc_balance = balance.get(self.trader.symbol_prefix, 0)
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logging.info(f"当前{self.trader.symbol_prefix}余额: {btc_balance}")
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sell_amount = 0.01
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if btc_balance >= sell_amount:
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order_id = self.trader.place_market_order('sell', sell_amount)
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if order_id:
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logging.info(f"现货卖出{sell_amount}{self.trader.symbol_prefix}成功，订单ID: {order_id}")
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else:
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logging.error(f"现货卖出{self.trader.symbol_prefix}失败")
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else:
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logging.error(f"{self.trader.symbol_prefix}余额不足，无法卖出{sell_amount}{self.trader.symbol_prefix}")
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except Exception as e:
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logging.error(f"现货卖出{self.trader.symbol_prefix}流程异常: {e}")
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sleep(1)
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try:
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# 3. 合约平空单流程
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logging.info("[3] 合约平空单流程：")
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result = self.trader.close_short_order(td_mode, quantity)
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if result:
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logging.info("平空单成功")
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else:
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logging.error("平空单失败")
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except Exception as e:
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logging.error(f"合约平空单流程异常: {e}")
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if __name__ == "__main__":
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biz_main = BizMain()
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biz_main.start_job()
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@ -18,6 +18,7 @@ TRADING_CONFIG = {
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# 策略参数
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"sma_short_period": 5, # 短期移动平均线周期
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"sma_long_period": 20, # 长期移动平均线周期
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"rsi_period": 14, # RSI计算周期
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"rsi_oversold": 30, # RSI超卖阈值
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"rsi_overbought": 70, # RSI超买阈值
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@ -34,7 +35,7 @@ TRADING_CONFIG = {
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# 时间间隔配置
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TIME_CONFIG = {
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"strategy_interval": 60, # 策略执行间隔（秒）
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"strategy_interval": 30, # 策略执行间隔（秒）
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"kline_interval": "5m", # K线数据间隔
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"kline_limit": 100, # K线数据条数
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}
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import okx.Account as Account
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import okx.Trade as Trade
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import okx.MarketData as Market
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import okx.PublicData as Public
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import pandas as pd
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import logging
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from typing import Optional
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logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
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class QuantTrader:
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def __init__(self,
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api_key: str,
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secret_key: str,
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passphrase: str,
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sandbox: bool = True,
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symbol: str = "BTC-USDT",
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position_size: float = 0.001):
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"""
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初始化货币量化交易器
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Args:
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api_key: OKX API Key
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secret_key: OKX Secret Key
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passphrase: OKX API Passphrase
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sandbox: 是否使用沙盒环境（建议先用沙盒测试）
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"""
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self.api_key = api_key
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self.secret_key = secret_key
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self.passphrase = passphrase
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flag = "1" if sandbox else "0" # 0:实盘环境 1:沙盒环境
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self.account_api = Account.AccountAPI(
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api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
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flag=flag
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)
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self.trade_api = Trade.TradeAPI(
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api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
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flag=flag
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)
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self.market_api = Market.MarketAPI(
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api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
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flag=flag
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)
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self.public_api = Public.PublicAPI(
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api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
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flag=flag
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)
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self.symbol = symbol
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self.symbol_swap = f'{symbol}-SWAP'
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self.symbol_prefix = symbol.split('-')[0]
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self.position_size = position_size
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def get_account_balance(self) -> float:
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"""获取账户余额"""
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try:
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result = {}
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search_result = self.account_api.get_account_balance()
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if search_result.get('code') == '0':
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balances = search_result.get('data', [])
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for balance in balances:
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details = balance.get('details', [])
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for detail in details:
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if detail.get('ccy') == 'USDT':
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logging.info(f"USDT余额: {detail.get('availBal')}")
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result['USDT'] = float(detail.get('availBal', 0))
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if detail.get('ccy') == self.symbol_prefix:
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logging.info(f"{self.symbol_prefix}余额: {detail.get('availBal')}")
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result[self.symbol_prefix] = float(detail.get('availBal', 0))
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if detail.get('ccy') == self.symbol_swap:
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logging.info(f"{self.symbol_swap}余额: {detail.get('availBal')}")
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result[self.symbol_swap] = float(detail.get('availBal', 0))
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return result
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else:
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logging.error(f"获取余额失败: {search_result}")
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return {}
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except Exception as e:
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logging.error(f"获取余额异常: {e}")
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return {}
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def get_current_price(self, symbol: str = None) -> Optional[float]:
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"""获取当前货币价格"""
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try:
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if symbol is None:
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symbol = self.symbol
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symbol_prefix = self.symbol_prefix
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else:
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symbol_prefix = symbol.split('-')[0]
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result = self.market_api.get_ticker(instId=symbol)
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if result.get('code') == '0':
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data = result.get('data', [])
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if data and 'last' in data[0]:
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price = float(data[0]['last'])
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logging.info(f"当前{symbol_prefix}价格: ${price:,.2f}")
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return price
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else:
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logging.error(f"ticker数据格式异常: {data}")
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return None
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else:
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logging.error(f"获取价格失败: {result}")
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return None
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except Exception as e:
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logging.error(f"获取价格异常: {e}")
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return None
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def get_kline_data(self, bar: str = '1m', limit: int = 100) -> Optional[pd.DataFrame]:
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"""获取K线数据"""
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try:
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result = self.market_api.get_candlesticks(
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instId=self.symbol,
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bar=bar,
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limit=str(limit)
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)
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if result.get('code') == '0':
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data = result.get('data', [])
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if not data:
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logging.warning("K线数据为空")
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return None
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df = pd.DataFrame(data, columns=[
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'timestamp', 'open', 'high', 'low', 'close',
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'volume', 'volCcy', "volCCyQuote", "confirm"
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])
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for col in ['open', 'high', 'low', 'close', 'volume']:
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df[col] = pd.to_numeric(df[col], errors='coerce')
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df['timestamp'] = pd.to_datetime(df['timestamp'].astype(int), unit='ms', errors='coerce')
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return df
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else:
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logging.error(f"获取K线数据失败: {result}")
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return None
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except Exception as e:
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logging.error(f"获取K线数据异常: {e}")
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return None
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def place_market_order(self, side: str, size: float) -> Optional[str]:
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"""下市价单"""
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balance = self.get_account_balance()
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usdt_balance = balance.get('USDT')
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symbol_balance = balance.get(self.symbol_prefix)
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if side == 'sell':
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try:
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if symbol_balance < size:
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logging.error(f"{self.symbol_prefix}余额不足，目前余额: {symbol_balance}")
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return None
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result = self.trade_api.place_order(
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instId=self.symbol,
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tdMode='cash',
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side=side,
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ordType='market',
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sz=str(size)
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)
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if result.get('code') == '0':
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logging.info(f"下单成功: {side} {size} {self.symbol_prefix}")
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return result['data'][0]['ordId']
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else:
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logging.error(f"下单失败: {result}")
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return None
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except Exception as e:
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logging.error(f"下单异常: {e}")
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return None
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elif side == 'buy':
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try:
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instrument_result = self.public_api.get_instruments(instType="SPOT", instId=self.symbol)
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instrument_data = instrument_result.get("data", [])
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if not instrument_data:
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logging.error(f"未获取到合约信息: {instrument_result}")
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return None
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min_sz = float(instrument_data[0].get("minSz", 0))
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if size < min_sz:
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size = min_sz
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ticker = self.market_api.get_ticker(instId=self.symbol)
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last_price = float(ticker["data"][0]["last"])
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usdt_amount = float(last_price * size)
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if usdt_balance < usdt_amount:
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logging.error(f"USDT余额不足，目前余额: {usdt_balance}")
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return None
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result = self.trade_api.place_order(
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instId=self.symbol,
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tdMode="cash",
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side=side,
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ordType="market",
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sz=str(usdt_amount)
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)
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if result.get('code') == '0':
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logging.info(f"下单成功: {side} {usdt_amount} USDT")
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return result['data'][0]['ordId']
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else:
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logging.error(f"下单失败: {result}")
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return None
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except Exception as e:
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logging.error(f"下单异常: {e}")
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return None
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else:
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logging.error(f"不支持的下单方向: {side}")
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return None
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# 设置杠杆倍数
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def set_leverage(self, leverage: int = 1, mgn_mode: str = "cross", ccy: str = "USDT", posSide: str = "short"):
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result = self.account_api.set_leverage(
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lever=str(leverage),
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mgnMode=mgn_mode,
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instId=self.symbol_swap,
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ccy=ccy,
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posSide=posSide
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)
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if result["code"] == "0":
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logging.info(f"设置杠杆倍数 {leverage}x 成功")
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else:
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logging.error(f"设置杠杆失败: {result['msg']}")
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return result["code"] == "0"
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# 计算保证金需求
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def calculate_margin(self, quantity: int = 10, leverage: int = 1, slot: float = 0.01, buffer_ratio: float = 0.3):
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price = self.get_current_price(self.symbol_swap)
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if not price:
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return None
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contract_value = quantity * slot * price # 每张 0.01 BTC
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initial_margin = contract_value / leverage
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recommended_margin = initial_margin * (1 + buffer_ratio)
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logging.info(f"开仓{self.symbol_swap}价格: {price:.2f} USDT")
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logging.info(f"合约总价值: {contract_value:.2f} USDT")
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logging.info(f"初始保证金: {initial_margin:.2f} USDT")
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logging.info(f"推荐保证金 (含 {buffer_ratio*100}% 缓冲): {recommended_margin:.2f} USDT")
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return recommended_margin, price
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# 开空头仓位（卖出空单）
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def place_short_order(self, td_mode: str = "cross", quantity: int = 10, leverage: int = 1, slot: float = 0.01, buffer_ratio: float = 0.3):
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"""开空头仓位（卖出空单）"""
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# 计算所需保证金和开仓价格
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margin_data = self.calculate_margin(quantity, leverage, slot, buffer_ratio)
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if not margin_data:
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logging.error("无法计算保证金，终止下单")
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return None, None
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required_margin, entry_price = margin_data
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# 检查余额
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balance = self.get_account_balance()
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avail_bal = balance.get('USDT')
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if avail_bal is None or avail_bal < required_margin:
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logging.error(f"保证金不足，需至少 {required_margin:.2f} USDT，当前余额: {avail_bal}")
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return None, None
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# 设置杠杆
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if not self.set_leverage(leverage, mgn_mode=td_mode, ccy="USDT", posSide="short"):
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return None, None
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# 下单
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order_data = {
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"instId": self.symbol_swap,
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"tdMode": td_mode,
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"ccy": "USDT",
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"side": "sell",
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"posSide": "short",
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"ordType": "market",
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"sz": str(quantity),
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}
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result = self.trade_api.place_order(**order_data)
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if result.get("code") == "0":
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logging.info(f"开空单成功，订单ID: {result['data'][0]['ordId']}")
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return result["data"][0]["ordId"], entry_price
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else:
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logging.error(f"开空单失败: {result.get('msg', result)}")
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return None, None
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# 平空单（买入平仓）
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def close_short_order(self, td_mode: str = "cross", quantity: float = 10) -> bool:
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"""平空单（买入平仓）"""
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order_data = {
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"instId": self.symbol_swap,
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"tdMode": td_mode,
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"ccy": "USDT",
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"side": "buy",
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"posSide": "short",
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"ordType": "market",
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"sz": str(quantity),
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}
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result = self.trade_api.place_order(**order_data)
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if result.get("code") == "0":
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logging.info(f"平空单成功，订单ID: {result['data'][0]['ordId']}")
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return True
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else:
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logging.error(f"平空单失败: {result.get('msg', result)}")
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return False
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def get_minimun_order_size(self) -> None:
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"""获取最小订单数量"""
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try:
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result = self.public_api.get_instruments(instType="SPOT", instId=self.symbol)
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if result.get("code") == "0":
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instrument = result.get("data", [{}])[0]
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min_sz = float(instrument.get("minSz", 0))
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lot_sz = float(instrument.get("lotSz", 0))
|
||||
logging.info(f"最小交易量 (minSz): {min_sz} {self.symbol_prefix}")
|
||||
logging.info(f"交易量精度 (lotSz): {lot_sz} {self.symbol_prefix}")
|
||||
else:
|
||||
logging.error(f"错误: {result.get('msg', result)}")
|
||||
except Exception as e:
|
||||
logging.error(f"异常: {str(e)}")
|
||||
|
||||
|
|
@ -0,0 +1,209 @@
|
|||
import time
|
||||
from datetime import datetime
|
||||
import logging
|
||||
from typing import Optional
|
||||
import pandas as pd
|
||||
from core.base import QuantTrader
|
||||
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
|
||||
|
||||
class QuantStrategy:
|
||||
def __init__(self,
|
||||
api_key: str,
|
||||
secret_key: str,
|
||||
passphrase: str,
|
||||
sandbox: bool = True,
|
||||
symbol: str = "BTC-USDT",
|
||||
position_size: float = 0.001):
|
||||
"""
|
||||
初始化量化策略
|
||||
"""
|
||||
self.quant_trader = QuantTrader(
|
||||
api_key,
|
||||
secret_key,
|
||||
passphrase,
|
||||
sandbox,
|
||||
symbol,
|
||||
position_size)
|
||||
|
||||
def calculate_sma(self, df: pd.DataFrame, period: int = 20) -> pd.Series:
|
||||
"""
|
||||
计算简单移动平均线
|
||||
"""
|
||||
if 'close' not in df:
|
||||
logging.error("DataFrame缺少'close'列，无法计算SMA")
|
||||
return pd.Series([float('nan')] * len(df))
|
||||
if len(df) < period:
|
||||
logging.warning(f"数据长度不足{period}，SMA结果将包含NaN")
|
||||
return df['close'].rolling(window=period).mean()
|
||||
|
||||
def calculate_rsi(self, df: pd.DataFrame, period: int = 14) -> pd.Series:
|
||||
"""
|
||||
计算RSI指标
|
||||
"""
|
||||
if 'close' not in df:
|
||||
logging.error("DataFrame缺少'close'列，无法计算RSI")
|
||||
return pd.Series([float('nan')] * len(df))
|
||||
if len(df) < period:
|
||||
logging.warning(f"数据长度不足{period}，RSI结果将包含NaN")
|
||||
delta = df['close'].diff()
|
||||
gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
|
||||
loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
|
||||
loss = loss.replace(0, 1e-10) # 防止除零
|
||||
rs = gain / loss
|
||||
rsi = 100 - (100 / (1 + rs))
|
||||
return rsi
|
||||
|
||||
def simple_moving_average_strategy(self, sma_short_period: int = 5, sma_long_period: int = 20) -> None:
|
||||
"""
|
||||
简单移动平均线策略
|
||||
"""
|
||||
logging.info("=== 执行移动平均线策略 ===")
|
||||
try:
|
||||
df = self.quant_trader.get_kline_data(bar='5m', limit=max(50, sma_long_period+2))
|
||||
except Exception as e:
|
||||
logging.error(f"获取K线数据失败: {e}")
|
||||
return
|
||||
if df is None or len(df) < max(sma_short_period, sma_long_period, 2):
|
||||
logging.warning("数据不足，无法执行策略")
|
||||
return
|
||||
df['sma_short'] = self.calculate_sma(df, sma_short_period)
|
||||
df['sma_long'] = self.calculate_sma(df, sma_long_period)
|
||||
if len(df) < 2:
|
||||
logging.warning("数据不足2条，无法判断金叉死叉")
|
||||
return
|
||||
latest = df.iloc[-1]
|
||||
prev = df.iloc[-2]
|
||||
if pd.isna(latest['sma_short']) or pd.isna(latest['sma_long']) or pd.isna(prev['sma_short']) or pd.isna(prev['sma_long']):
|
||||
logging.warning("均线数据存在NaN，跳过本次信号判断")
|
||||
return
|
||||
logging.info(f"短期均线: {latest['sma_short']:.2f}")
|
||||
logging.info(f"长期均线: {latest['sma_long']:.2f}")
|
||||
logging.info(f"当前价格: {latest['close']:.2f}")
|
||||
if (latest['sma_short'] > latest['sma_long'] and prev['sma_short'] <= prev['sma_long']):
|
||||
logging.info("信号: 买入")
|
||||
self.quant_trader.place_market_order('buy', self.quant_trader.position_size)
|
||||
elif (latest['sma_short'] < latest['sma_long'] and prev['sma_short'] >= prev['sma_long']):
|
||||
logging.info("信号: 卖出")
|
||||
self.quant_trader.place_market_order('sell', self.quant_trader.position_size)
|
||||
else:
|
||||
logging.info("信号: 持仓观望")
|
||||
|
||||
def rsi_strategy(self, period: int = 14, oversold: int = 30, overbought: int = 70) -> None:
|
||||
"""
|
||||
RSI策略
|
||||
"""
|
||||
logging.info("=== 执行RSI策略 ===")
|
||||
try:
|
||||
df = self.quant_trader.get_kline_data(bar='5m', limit=max(50, period+2))
|
||||
except Exception as e:
|
||||
logging.error(f"获取K线数据失败: {e}")
|
||||
return
|
||||
if df is None or len(df) < period:
|
||||
logging.warning("数据不足，无法执行策略")
|
||||
return
|
||||
df['rsi'] = self.calculate_rsi(df, period)
|
||||
latest_rsi = df['rsi'].iloc[-1]
|
||||
if pd.isna(latest_rsi):
|
||||
logging.warning("最新RSI为NaN，跳过本次信号判断")
|
||||
return
|
||||
logging.info(f"当前RSI: {latest_rsi:.2f}")
|
||||
if latest_rsi < oversold:
|
||||
logging.info("信号: RSI超卖，买入")
|
||||
self.quant_trader.place_market_order('buy', self.quant_trader.position_size)
|
||||
elif latest_rsi > overbought:
|
||||
logging.info("信号: RSI超买，卖出")
|
||||
self.quant_trader.place_market_order('sell', self.quant_trader.position_size)
|
||||
else:
|
||||
logging.info("信号: RSI正常区间，持仓观望")
|
||||
|
||||
def grid_trading_strategy(self, grid_levels: int = 5, grid_range: float = 0.02) -> None:
|
||||
"""
|
||||
网格交易策略
|
||||
"""
|
||||
if grid_levels <= 0:
|
||||
logging.error("网格数必须大于0")
|
||||
return
|
||||
if grid_range <= 0:
|
||||
logging.error("网格范围必须大于0")
|
||||
return
|
||||
logging.info(f"=== 执行网格交易策略 (网格数: {grid_levels}, 范围: {grid_range*100}%) ===")
|
||||
try:
|
||||
current_price = self.quant_trader.get_current_price()
|
||||
except Exception as e:
|
||||
logging.error(f"获取当前价格失败: {e}")
|
||||
return
|
||||
if current_price is None:
|
||||
logging.warning("当前价格获取失败")
|
||||
return
|
||||
grid_prices = []
|
||||
for i in range(grid_levels):
|
||||
price = current_price * (1 + grid_range * (i - grid_levels//2) / grid_levels)
|
||||
grid_prices.append(price)
|
||||
logging.info(f"网格价格: {[f'${p:.2f}' for p in grid_prices]}")
|
||||
try:
|
||||
df = self.quant_trader.get_kline_data(bar='1m', limit=10)
|
||||
except Exception as e:
|
||||
logging.error(f"获取K线数据失败: {e}")
|
||||
return
|
||||
if df is None or len(df) == 0 or 'close' not in df:
|
||||
logging.warning("K线数据无效，无法执行网格策略")
|
||||
return
|
||||
latest_price = df['close'].iloc[-1]
|
||||
if pd.isna(latest_price):
|
||||
logging.warning("最新价格为NaN，跳过本次信号判断")
|
||||
return
|
||||
closest_grid = min(grid_prices, key=lambda x: abs(x - latest_price))
|
||||
logging.info(f"当前价格: ${latest_price:.2f}, 最近网格: ${closest_grid:.2f}")
|
||||
if latest_price < closest_grid * 0.995:
|
||||
logging.info("信号: 价格下跌，网格买入")
|
||||
self.quant_trader.place_market_order('buy', self.quant_trader.position_size)
|
||||
elif latest_price > closest_grid * 1.005:
|
||||
logging.info("信号: 价格上涨，网格卖出")
|
||||
self.quant_trader.place_market_order('sell', self.quant_trader.position_size)
|
||||
else:
|
||||
logging.info("信号: 价格在网格内，持仓观望")
|
||||
|
||||
def run_strategy_loop(self,
|
||||
strategy: str = 'sma',
|
||||
interval: int = 60,
|
||||
trading_config: dict = {}) -> None:
|
||||
"""
|
||||
运行策略循环
|
||||
"""
|
||||
if interval <= 0:
|
||||
logging.error("循环间隔必须大于0秒")
|
||||
return
|
||||
logging.info(f"开始运行{strategy}策略，间隔{interval}秒")
|
||||
while True:
|
||||
try:
|
||||
logging.info(datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
|
||||
try:
|
||||
self.quant_trader.get_account_balance()
|
||||
except Exception as e:
|
||||
logging.error(f"获取账户余额失败: {e}")
|
||||
if strategy == 'sma':
|
||||
sma_short_period = trading_config.get("sma_short_period", 5)
|
||||
sma_long_period = trading_config.get("sma_long_period", 20)
|
||||
self.simple_moving_average_strategy(sma_short_period, sma_long_period)
|
||||
elif strategy == 'rsi':
|
||||
period = trading_config.get("rsi_period", 14)
|
||||
oversold = trading_config.get("rsi_oversold", 30)
|
||||
overbought = trading_config.get("rsi_overbought", 70)
|
||||
self.rsi_strategy(period, oversold, overbought)
|
||||
elif strategy == 'grid':
|
||||
grid_levels = trading_config.get("grid_levels", 5)
|
||||
grid_range = trading_config.get("grid_range", 0.02)
|
||||
self.grid_trading_strategy(grid_levels, grid_range)
|
||||
else:
|
||||
logging.error("未知策略")
|
||||
break
|
||||
logging.info(f"等待{interval}秒后继续...")
|
||||
time.sleep(interval)
|
||||
except KeyboardInterrupt:
|
||||
logging.info("策略运行被用户中断")
|
||||
break
|
||||
except Exception as e:
|
||||
logging.error(f"策略运行异常: {e}")
|
||||
time.sleep(interval)
|
||||
|
||||
404
play.py
404
play.py
|
|
@ -1,400 +1,98 @@
|
|||
import okx.Account as Account
|
||||
import okx.Trade as Trade
|
||||
import okx.MarketData as Market
|
||||
import okx.PublicData as Public
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
import time
|
||||
from datetime import datetime
|
||||
import json
|
||||
import logging
|
||||
from core.base import QuantTrader
|
||||
from core.strategy import QuantStrategy
|
||||
|
||||
class BitcoinQuantTrader:
|
||||
def __init__(self, api_key, secret_key, passphrase, sandbox=True):
|
||||
"""
|
||||
初始化比特币量化交易器
|
||||
|
||||
Args:
|
||||
api_key: OKX API Key
|
||||
secret_key: OKX Secret Key
|
||||
passphrase: OKX API Passphrase
|
||||
sandbox: 是否使用沙盒环境（建议先用沙盒测试）
|
||||
"""
|
||||
self.api_key = api_key
|
||||
self.secret_key = secret_key
|
||||
self.passphrase = passphrase
|
||||
|
||||
# 初始化API客户端
|
||||
flag = "1" if sandbox else "0" # 0:实盘环境 1:沙盒环境
|
||||
|
||||
self.account_api = Account.AccountAPI(
|
||||
api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
|
||||
flag=flag
|
||||
)
|
||||
self.trade_api = Trade.TradeAPI(
|
||||
api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
|
||||
flag=flag
|
||||
)
|
||||
self.market_api = Market.MarketAPI(
|
||||
api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
|
||||
flag=flag
|
||||
)
|
||||
self.public_api = Public.PublicAPI(
|
||||
api_key=api_key, api_secret_key=secret_key, passphrase=passphrase,
|
||||
flag=flag
|
||||
)
|
||||
|
||||
self.symbol = "BTC-USDT"
|
||||
self.position_size = 0.001 # 每次交易0.001 BTC
|
||||
|
||||
def get_account_balance(self):
|
||||
"""获取账户余额"""
|
||||
try:
|
||||
result = self.account_api.get_account_balance()
|
||||
if result['code'] == '0':
|
||||
balances = result['data']
|
||||
for balance in balances:
|
||||
details = balance['details']
|
||||
for detail in details:
|
||||
if detail['ccy'] == 'USDT':
|
||||
print(f"USDT余额: {detail['availBal']}")
|
||||
return float(detail['availBal'])
|
||||
elif detail['ccy'] == 'BTC':
|
||||
print(f"BTC余额: {detail['availBal']}")
|
||||
# return float(detail['availBal'])
|
||||
else:
|
||||
print(f"获取余额失败: {result}")
|
||||
return 0
|
||||
except Exception as e:
|
||||
print(f"获取余额异常: {e}")
|
||||
return 0
|
||||
|
||||
def get_current_price(self):
|
||||
"""获取当前BTC价格"""
|
||||
try:
|
||||
result = self.market_api.get_ticker(instId=self.symbol)
|
||||
if result['code'] == '0':
|
||||
price = float(result['data'][0]['last'])
|
||||
print(f"当前BTC价格: ${price:,.2f}")
|
||||
return price
|
||||
else:
|
||||
print(f"获取价格失败: {result}")
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"获取价格异常: {e}")
|
||||
return None
|
||||
|
||||
def get_kline_data(self, bar='1m', limit=100):
|
||||
"""获取K线数据"""
|
||||
try:
|
||||
result = self.market_api.get_candlesticks(
|
||||
instId=self.symbol,
|
||||
bar=bar,
|
||||
limit=str(limit)
|
||||
)
|
||||
if result['code'] == '0':
|
||||
# 转换为DataFrame
|
||||
df = pd.DataFrame(result['data'], columns=[
|
||||
'timestamp', 'open', 'high', 'low', 'close',
|
||||
'volume', 'volCcy', "volCCyQuote", "confirm"
|
||||
])
|
||||
# 转换数据类型
|
||||
for col in ['open', 'high', 'low', 'close', 'volume']:
|
||||
df[col] = pd.to_numeric(df[col])
|
||||
df['timestamp'] = pd.to_datetime(df['timestamp'].astype(int), unit='ms')
|
||||
return df
|
||||
else:
|
||||
print(f"获取K线数据失败: {result}")
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"获取K线数据异常: {e}")
|
||||
return None
|
||||
|
||||
def calculate_sma(self, df, period=20):
|
||||
"""计算简单移动平均线"""
|
||||
return df['close'].rolling(window=period).mean()
|
||||
|
||||
def calculate_rsi(self, df, period=14):
|
||||
"""计算RSI指标"""
|
||||
delta = df['close'].diff()
|
||||
gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
|
||||
loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
|
||||
rs = gain / loss
|
||||
rsi = 100 - (100 / (1 + rs))
|
||||
return rsi
|
||||
|
||||
def place_market_order(self, side, size):
|
||||
"""下市价单"""
|
||||
if side == 'sell':
|
||||
try:
|
||||
result = self.trade_api.place_order(
|
||||
instId=self.symbol,
|
||||
tdMode='cash',
|
||||
side=side,
|
||||
ordType='market',
|
||||
sz=str(size)
|
||||
)
|
||||
if result['code'] == '0':
|
||||
print(f"下单成功: {side} {size} BTC")
|
||||
return result['data'][0]['ordId']
|
||||
else:
|
||||
print(f"下单失败: {result}")
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"下单异常: {e}")
|
||||
return None
|
||||
elif side == 'buy':
|
||||
instrument = self.public_api.get_instruments(instType="SPOT", instId=self.symbol)["data"][0]
|
||||
min_sz = float(instrument["minSz"]) # 最小交易量
|
||||
if size < min_sz:
|
||||
size = min_sz
|
||||
ticker = self.market_api.get_ticker(instId=self.symbol)
|
||||
last_price = float(ticker["data"][0]["last"]) # 最新价格
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
|
||||
|
||||
# 买入数量是USDT，将BTC转换为USDT
|
||||
usdt_amount = float(last_price * size)
|
||||
|
||||
try:
|
||||
result = self.trade_api.place_order(
|
||||
instId=self.symbol,
|
||||
tdMode="cash",
|
||||
side=side,
|
||||
ordType="market",
|
||||
sz=str(usdt_amount)
|
||||
)
|
||||
print("下单结果:", result)
|
||||
except Exception as e:
|
||||
print("错误:", str(e))
|
||||
|
||||
def get_minimun_order_size(self):
|
||||
"""获取最小订单数量"""
|
||||
try:
|
||||
result = self.public_api.get_instruments(instType="SPOT", instId=self.symbol)
|
||||
if result["code"] == "0":
|
||||
instrument = result["data"][0]
|
||||
min_sz = float(instrument["minSz"]) # 最小交易量（BTC）
|
||||
lot_sz = float(instrument["lotSz"]) # 交易量精度
|
||||
print(f"最小交易量 (minSz): {min_sz} BTC")
|
||||
print(f"交易量精度 (lotSz): {lot_sz} BTC")
|
||||
else:
|
||||
print(f"错误: {result['msg']}")
|
||||
except Exception as e:
|
||||
print(f"异常: {str(e)}")
|
||||
|
||||
def simple_moving_average_strategy(self):
|
||||
"""简单移动平均线策略"""
|
||||
print("\n=== 执行移动平均线策略 ===")
|
||||
|
||||
# 获取K线数据
|
||||
df = self.get_kline_data(bar='5m', limit=50)
|
||||
if df is None or len(df) < 20:
|
||||
print("数据不足，无法执行策略")
|
||||
return
|
||||
|
||||
# 计算移动平均线
|
||||
df['sma_short'] = self.calculate_sma(df, 5) # 短期均线
|
||||
df['sma_long'] = self.calculate_sma(df, 20) # 长期均线
|
||||
|
||||
# 获取最新数据
|
||||
latest = df.iloc[-1]
|
||||
prev = df.iloc[-2]
|
||||
|
||||
print(f"短期均线: {latest['sma_short']:.2f}")
|
||||
print(f"长期均线: {latest['sma_long']:.2f}")
|
||||
print(f"当前价格: {latest['close']:.2f}")
|
||||
|
||||
# 策略逻辑：短期均线上穿长期均线买入，下穿卖出
|
||||
if (latest['sma_short'] > latest['sma_long'] and
|
||||
prev['sma_short'] <= prev['sma_long']):
|
||||
print("信号: 买入")
|
||||
self.place_market_order('buy', self.position_size)
|
||||
elif (latest['sma_short'] < latest['sma_long'] and
|
||||
prev['sma_short'] >= prev['sma_long']):
|
||||
print("信号: 卖出")
|
||||
self.place_market_order('sell', self.position_size)
|
||||
else:
|
||||
print("信号: 持仓观望")
|
||||
|
||||
def rsi_strategy(self):
|
||||
"""RSI策略"""
|
||||
print("\n=== 执行RSI策略 ===")
|
||||
|
||||
# 获取K线数据
|
||||
df = self.get_kline_data(bar='5m', limit=50)
|
||||
if df is None or len(df) < 30:
|
||||
print("数据不足，无法执行策略")
|
||||
return
|
||||
|
||||
# 计算RSI
|
||||
df['rsi'] = self.calculate_rsi(df, 14)
|
||||
|
||||
# 获取最新RSI值
|
||||
latest_rsi = df['rsi'].iloc[-1]
|
||||
print(f"当前RSI: {latest_rsi:.2f}")
|
||||
|
||||
# 策略逻辑：RSI < 30 超卖买入，RSI > 70 超买卖出
|
||||
if latest_rsi < 30:
|
||||
print("信号: RSI超卖，买入")
|
||||
self.place_market_order('buy', self.position_size)
|
||||
elif latest_rsi > 70:
|
||||
print("信号: RSI超买，卖出")
|
||||
self.place_market_order('sell', self.position_size)
|
||||
else:
|
||||
print("信号: RSI正常区间，持仓观望")
|
||||
|
||||
def grid_trading_strategy(self, grid_levels=5, grid_range=0.02):
|
||||
"""网格交易策略"""
|
||||
print(f"\n=== 执行网格交易策略 (网格数: {grid_levels}, 范围: {grid_range*100}%) ===")
|
||||
|
||||
current_price = self.get_current_price()
|
||||
if current_price is None:
|
||||
return
|
||||
|
||||
# 计算网格价格
|
||||
grid_prices = []
|
||||
for i in range(grid_levels):
|
||||
price = current_price * (1 + grid_range * (i - grid_levels//2) / grid_levels)
|
||||
grid_prices.append(price)
|
||||
|
||||
print(f"网格价格: {[f'${p:.2f}' for p in grid_prices]}")
|
||||
|
||||
# 获取K线数据判断当前价格在哪个网格
|
||||
df = self.get_kline_data(bar='1m', limit=10)
|
||||
if df is None:
|
||||
return
|
||||
|
||||
latest_price = df['close'].iloc[-1]
|
||||
|
||||
# 找到最近的网格
|
||||
closest_grid = min(grid_prices, key=lambda x: abs(x - latest_price))
|
||||
grid_index = grid_prices.index(closest_grid)
|
||||
|
||||
print(f"当前价格: ${latest_price:.2f}, 最近网格: ${closest_grid:.2f}")
|
||||
|
||||
# 简单的网格策略：价格下跌到网格线买入，上涨到网格线卖出
|
||||
if latest_price < closest_grid * 0.995: # 价格下跌超过0.5%
|
||||
print("信号: 价格下跌，网格买入")
|
||||
self.place_market_order('buy', self.position_size)
|
||||
elif latest_price > closest_grid * 1.005: # 价格上涨超过0.5%
|
||||
print("信号: 价格上涨，网格卖出")
|
||||
self.place_market_order('sell', self.position_size)
|
||||
else:
|
||||
print("信号: 价格在网格内，持仓观望")
|
||||
|
||||
def run_strategy_loop(self, strategy='sma', interval=60):
|
||||
"""运行策略循环"""
|
||||
print(f"开始运行{strategy}策略，间隔{interval}秒")
|
||||
|
||||
while True:
|
||||
try:
|
||||
print(f"\n{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
|
||||
|
||||
# 检查账户余额
|
||||
self.get_account_balance()
|
||||
|
||||
# 执行策略
|
||||
if strategy == 'sma':
|
||||
self.simple_moving_average_strategy()
|
||||
elif strategy == 'rsi':
|
||||
self.rsi_strategy()
|
||||
elif strategy == 'grid':
|
||||
self.grid_trading_strategy()
|
||||
else:
|
||||
print("未知策略")
|
||||
break
|
||||
|
||||
print(f"等待{interval}秒后继续...")
|
||||
time.sleep(interval)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\n策略运行被用户中断")
|
||||
break
|
||||
except Exception as e:
|
||||
print(f"策略运行异常: {e}")
|
||||
time.sleep(interval)
|
||||
|
||||
def main():
|
||||
def main() -> None:
|
||||
"""主函数"""
|
||||
print("=== 比特币量化交易系统 ===")
|
||||
|
||||
logging.info("=== 比特币量化交易系统 ===")
|
||||
# 导入配置
|
||||
try:
|
||||
from config import API_KEY, SECRET_KEY, PASSPHRASE, TRADING_CONFIG, TIME_CONFIG
|
||||
except ImportError:
|
||||
print("错误：找不到config.py文件，请确保配置文件存在")
|
||||
logging.error("找不到config.py文件，请确保配置文件存在")
|
||||
return
|
||||
|
||||
# 检查是否配置了API密钥
|
||||
if API_KEY == "your_api_key_here":
|
||||
print("请先在config.py中配置你的OKX API密钥！")
|
||||
print("1. 登录OKX官网")
|
||||
print("2. 进入API管理页面")
|
||||
print("3. 创建API Key、Secret Key和Passphrase")
|
||||
print("4. 将密钥填入config.py文件中的相应位置")
|
||||
logging.error("请先在config.py中配置你的OKX API密钥！\n1. 登录OKX官网\n2. 进入API管理页面\n3. 创建API Key、Secret Key和Passphrase\n4. 将密钥填入config.py文件中的相应位置")
|
||||
return
|
||||
|
||||
# 创建交易器实例
|
||||
trader = BitcoinQuantTrader(
|
||||
sandbox = TRADING_CONFIG.get("sandbox", True)
|
||||
symbol = TRADING_CONFIG.get("symbol", "BTC-USDT")
|
||||
position_size = TRADING_CONFIG.get("position_size", 0.001)
|
||||
trader = QuantTrader(
|
||||
API_KEY, SECRET_KEY, PASSPHRASE,
|
||||
sandbox=TRADING_CONFIG["sandbox"]
|
||||
sandbox=sandbox,
|
||||
symbol=symbol,
|
||||
position_size=position_size
|
||||
)
|
||||
strategy = QuantStrategy(
|
||||
API_KEY, SECRET_KEY, PASSPHRASE,
|
||||
sandbox=sandbox,
|
||||
symbol=symbol,
|
||||
position_size=position_size
|
||||
)
|
||||
|
||||
# 显示菜单
|
||||
while True:
|
||||
print("\n请选择操作:")
|
||||
print("1. 查看账户余额")
|
||||
print("2. 查看当前价格")
|
||||
print("3. 执行移动平均线策略")
|
||||
print("4. 执行RSI策略")
|
||||
print("5. 执行网格交易策略")
|
||||
print("6. 运行策略循环")
|
||||
print("7. 买入测试")
|
||||
print("8. 卖出测试")
|
||||
print("9. 获取最小交易量")
|
||||
print("0. 退出")
|
||||
|
||||
logging.info("\n请选择操作:\n1. 查看账户余额\n2. 查看当前价格\n3. 执行移动平均线策略\n4. 执行RSI策略\n5. 执行网格交易策略\n6. 运行策略循环\n7. 买入测试\n8. 卖出测试\n9. 获取最小交易量\n0. 退出")
|
||||
choice = input("请输入选择 (0-9): ").strip()
|
||||
|
||||
if choice == '0':
|
||||
print("退出程序")
|
||||
logging.info("退出程序")
|
||||
break
|
||||
elif choice == '1':
|
||||
trader.get_account_balance()
|
||||
elif choice == '2':
|
||||
trader.get_current_price()
|
||||
elif choice == '3':
|
||||
trader.simple_moving_average_strategy()
|
||||
sma_short_period = TRADING_CONFIG.get("sma_short_period", 5)
|
||||
sma_long_period = TRADING_CONFIG.get("sma_long_period", 20)
|
||||
strategy.simple_moving_average_strategy(sma_short_period, sma_long_period)
|
||||
elif choice == '4':
|
||||
trader.rsi_strategy()
|
||||
period = TRADING_CONFIG.get("rsi_period", 14)
|
||||
rsi_oversold = TRADING_CONFIG.get("rsi_oversold", 30)
|
||||
rsi_overbought = TRADING_CONFIG.get("rsi_overbought", 70)
|
||||
strategy.rsi_strategy(period, rsi_oversold, rsi_overbought)
|
||||
elif choice == '5':
|
||||
trader.grid_trading_strategy()
|
||||
grid_levels = TRADING_CONFIG.get("grid_levels", 5)
|
||||
grid_range = TRADING_CONFIG.get("grid_range", 0.02)
|
||||
strategy.grid_trading_strategy(grid_levels, grid_range)
|
||||
elif choice == '6':
|
||||
strategy = input("选择策略 (sma/rsi/grid): ").strip()
|
||||
interval = int(input("设置间隔秒数 (默认60): ") or "60")
|
||||
trader.run_strategy_loop(strategy, interval)
|
||||
strategy_name = input("选择策略 (sma/rsi/grid): ").strip()
|
||||
interval = TIME_CONFIG.get("strategy_interval", 30)
|
||||
strategy.run_strategy_loop(strategy_name, interval, TRADING_CONFIG)
|
||||
elif choice == '7':
|
||||
position_size = 0.01
|
||||
defalt_position_size = 0.01
|
||||
input_size = input("请输入买入数量: ")
|
||||
if input_size:
|
||||
try:
|
||||
position_size = float(input_size)
|
||||
print(f"买入{position_size}BTC")
|
||||
logging.info(f"买入{position_size}BTC")
|
||||
trader.place_market_order('buy', position_size)
|
||||
except ValueError:
|
||||
print(f"输入无效，默认买入{position_size}BTC")
|
||||
logging.warning(f"输入无效，默认买入{defalt_position_size}BTC")
|
||||
trader.place_market_order('buy', defalt_position_size)
|
||||
else:
|
||||
logging.info(f"默认买入{defalt_position_size}BTC")
|
||||
trader.place_market_order('buy', defalt_position_size)
|
||||
elif choice == '8':
|
||||
position_size = 0.01
|
||||
defalt_position_size = 0.01
|
||||
input_size = input("请输入卖出数量: ")
|
||||
if input_size:
|
||||
try:
|
||||
position_size = float(input_size)
|
||||
print(f"卖出{position_size}BTC")
|
||||
logging.info(f"卖出{position_size}BTC")
|
||||
trader.place_market_order('sell', position_size)
|
||||
except ValueError:
|
||||
print(f"输入无效，默认卖出{position_size}BTC")
|
||||
logging.warning(f"输入无效，默认卖出{defalt_position_size}BTC")
|
||||
trader.place_market_order('sell', defalt_position_size)
|
||||
else:
|
||||
logging.info(f"默认卖出{defalt_position_size}BTC")
|
||||
trader.place_market_order('sell', defalt_position_size)
|
||||
elif choice == '9':
|
||||
trader.get_minimun_order_size()
|
||||
else:
|
||||
print("无效选择，请重新输入")
|
||||
logging.warning("无效选择，请重新输入")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
|
|
|||
Loading…
Reference in New Issue