RSI Reversal Signals with Stop and Time Exits
Article Strategy library · Author: Chaos
Summary
This daily futures strategy uses a six-period RSI to trade reversals from overbought and oversold territory. After RSI has crossed above the overbought threshold, a move back below it opens a short; after RSI has crossed below the oversold threshold, a move back above it opens a long. The strategy exits longs when RSI becomes overbought and shorts when RSI becomes oversold.
It also sets a one-percent price stop and closes positions after ten days. The document provides implementation details and a backtest date range, but reports no performance results, so it does not establish whether the rules are profitable. Its example uses one futures contract and a fixed position size; it does not describe transaction costs or broader position-sizing considerations. The entry logic depends on daily bar updates and stored threshold-state flags, which are relevant implementation details when reproducing the method.
Key ideas
- The strategy enters long when RSI recovers above its oversold threshold after previously falling below it.
- It enters short when RSI falls below its overbought threshold after previously rising above it.
- Positions close at opposing RSI extremes, a one-percent stop, or a ten-day time limit.
- The example gives a backtest period but no performance evidence.
Tags
Full text
# RSI
# RSI
## Source (Apache-2.0)
```python
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Chaos"
from datetime import date
from tqsdk import TqApi, TqAuth, TqBacktest, TargetPosTask, BacktestFinished
from tqsdk.ta import RSI
from tqsdk.tafunc import time_to_str
# ===== 全局参数设置 =====
SYMBOL = "DCE.a2101"
POSITION_SIZE = 500 # 每次交易手数
START_DATE = date(2020, 4, 20) # 回测开始日期
END_DATE = date(2020, 11, 20) # 回测结束日期
# RSI参数
RSI_PERIOD = 6 # RSI计算周期，
OVERBOUGHT_THRESHOLD = 65 # 超买阈值
OVERSOLD_THRESHOLD = 35 # 超卖阈值
# 风控参数
STOP_LOSS_PERCENT = 0.01 # 止损百分比
TIME_STOP_DAYS = 10 # 缩短时间止损天数
# ===== 全局变量 =====
current_direction = 0 # 当前持仓方向：1=多头，-1=空头，0=空仓
entry_price = 0 # 开仓价格
stop_loss_price = 0 # 止损价格
entry_date = None # 开仓日期
was_overbought = False # 是否曾进入超买区域
was_oversold = False # 是否曾进入超卖区域
# ===== 策略开始 =====
print("开始运行RSI超买/超卖反转策略...")
# 创建API实例
api = TqApi(backtest=TqBacktest(start_dt=START_DATE, end_dt=END_DATE),
auth=TqAuth("快期账户", "快期密码"))
# 订阅合约的K线数据
klines = api.get_kline_serial(SYMBOL, 60 * 60 * 24) # 日线数据
# 创建目标持仓任务
target_pos = TargetPosTask(api, SYMBOL)
try:
while True:
# 等待更新
api.wait_update()
# 如果K线有更新
if api.is_changing(klines.iloc[-1], "datetime"):
# 确保有足够的数据计算指标
if len(klines) < RSI_PERIOD + 10:
continue
# 使用天勤的RSI函数计算
rsi = RSI(klines, RSI_PERIOD)
current_rsi = float(rsi.iloc[-1].iloc[0])
previous_rsi = float(rsi.iloc[-2].iloc[0])
# 更新超买/超卖状态
if previous_rsi > OVERBOUGHT_THRESHOLD:
was_overbought = True
if previous_rsi < OVERSOLD_THRESHOLD:
was_oversold = True
# 获取最新数据
current_price = float(klines.close.iloc[-1])
current_timestamp = klines.datetime.iloc[-1]
current_datetime = time_to_str(current_timestamp) # 使用time_to_str转换时间
# 打印当前状态
print(f"日期: {current_datetime}, 价格: {current_price:.2f}, RSI: {current_rsi:.2f}")
# ===== 交易逻辑 =====
# 空仓状态 - 寻找开仓机会
if current_direction == 0:
# 多头开仓条件：RSI从超卖区域回升
if was_oversold and previous_rsi < OVERSOLD_THRESHOLD and current_rsi > OVERSOLD_THRESHOLD:
current_direction = 1
target_pos.set_target_volume(POSITION_SIZE)
entry_price = current_price
stop_loss_price = entry_price * (1 - STOP_LOSS_PERCENT)
entry_date = current_timestamp # 存储时间戳
print(f"多头开仓: 价格={entry_price:.2f}, 止损={stop_loss_price:.2f}")
was_oversold = False # 重置超卖状态
# 空头开仓条件：RSI从超买区域回落
elif was_overbought and previous_rsi > OVERBOUGHT_THRESHOLD and current_rsi < OVERBOUGHT_THRESHOLD:
current_direction = -1
target_pos.set_target_volume(-POSITION_SIZE)
entry_price = current_price
stop_loss_price = entry_price * (1 + STOP_LOSS_PERCENT)
entry_date = current_timestamp # 存储时间戳
print(f"空头开仓: 价格={entry_price:.2f}, 止损={stop_loss_price:.2f}")
was_overbought = False # 重置超买状态
# 多头持仓 - 检查平仓条件
elif current_direction == 1:
# 止损条件
if current_price <= stop_loss_price:
profit_pct = (current_price - entry_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"多头止损平仓: 价格={current_price:.2f}, 盈亏={profit_pct:.2f}%")
# 止盈条件：RSI进入超买区域
elif current_rsi > OVERBOUGHT_THRESHOLD:
profit_pct = (current_price - entry_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"多头止盈平仓: 价格={current_price:.2f}, 盈亏={profit_pct:.2f}%")
# 时间止损
elif (current_timestamp - entry_date) / (60 * 60 * 24) >= TIME_STOP_DAYS: # 计算天数差
profit_pct = (current_price - entry_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"多头时间止损: 价格={current_price:.2f}, 盈亏={profit_pct:.2f}%")
# 空头持仓 - 检查平仓条件
elif current_direction == -1:
# 止损条件
if current_price >= stop_loss_price:
profit_pct = (entry_price - current_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"空头止损平仓: 价格={current_price:.2f}, 盈亏={profit_pct:.2f}%")
# 止盈条件：RSI进入超卖区域
elif current_rsi < OVERSOLD_THRESHOLD:
profit_pct = (entry_price - current_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"空头止盈平仓: 价格={current_price:.2f}, 盈亏={profit_pct:.2f}%")
# 时间止损
elif (current_timestamp - entry_date) / (60 * 60 * 24) >= TIME_STOP_DAYS: # 计算天数差
profit_pct = (entry_price - current_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"空头时间止损: 价格={current_price:.2f}, 盈亏={profit_pct:.2f}%")
except BacktestFinished as e:
print("回测结束")
api.close()
```Shown in full with attribution under the source's licence. Licence: Apache-2.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.