Aroon Crossover and Threshold Strategy for Gold Futures
Code TqSdk
Summary
This example describes a daily gold futures strategy using a 10-bar Aroon calculation. It opens a fixed-size long position when Aroon Up crosses above Aroon Down or when Aroon Up is above 75 while Aroon Down is below 25. The short rules reverse those conditions. Positions close on an opposing crossover, and a percentage stop is checked against the recorded entry price. The example also shows how the signals are sent to a target-position task in a backtest.
The document provides implementation logic and a specified historical test window, but it reports no performance results. Its Aroon values are computed from rolling high and low locations, and the stop checks use close prices; actual fills, fees, slippage, and contract risk are not evaluated. Position state is maintained separately from confirmed fills, so execution behavior may differ from the recorded trades. The example is therefore a strategy illustration rather than evidence that the rules are profitable.
Key ideas
- The strategy uses Aroon Up and Down crossovers to open positions in either direction.
- Threshold conditions can also open trades when one Aroon reading is strong and the other is weak.
- Opposing crossovers close open positions, while a percentage loss check triggers a stop.
- The example specifies a fixed position size and a historical backtest period but gives no performance results.
Tags
Full text
# Aroon.py
```py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Chaos"
from tqsdk import TqApi, TqAuth, TqBacktest, TargetPosTask, BacktestFinished
import pandas as pd
from datetime import date
# ===== 全局参数设置 =====
SYMBOL = "SHFE.au2306" # 黄金期货合约
POSITION_SIZE = 30 # 持仓手数
START_DATE = date(2023, 2, 20) # 回测开始日期
END_DATE = date(2023, 5, 5) # 回测结束日期
# Aroon指标参数
AROON_PERIOD = 10 # Aroon计算周期
AROON_UPPER_THRESHOLD = 75 # Aroon上线阈值
AROON_LOWER_THRESHOLD = 25 # Aroon下线阈值
# 风控参数
STOP_LOSS_PCT = 1.2 # 止损百分比
# ===== 全局变量 =====
position = 0 # 当前持仓
entry_price = 0 # 入场价格
trades = [] # 交易记录
# ===== 主程序 =====
print(f"开始回测 {SYMBOL} 的Aroon指标策略...")
print(f"参数: Aroon周期={AROON_PERIOD}, 上阈值={AROON_UPPER_THRESHOLD}, 下阈值={AROON_LOWER_THRESHOLD}")
print(f"回测期间: {START_DATE} 至 {END_DATE}")
try:
# 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K线数据
klines = api.get_kline_serial(SYMBOL, 60 * 60 * 24) # 日K线
target_pos = TargetPosTask(api, SYMBOL)
# 主循环
while True:
api.wait_update()
if api.is_changing(klines.iloc[-1], "datetime"):
# 确保有足够的数据
if len(klines) < AROON_PERIOD + 10:
continue
# ===== 计算Aroon指标 =====
# 找出最近N周期内最高价和最低价的位置
klines['rolling_high'] = klines['high'].rolling(window=AROON_PERIOD).max()
klines['rolling_low'] = klines['low'].rolling(window=AROON_PERIOD).min()
# 初始化Aroon Up和Aroon Down数组
aroon_up = []
aroon_down = []
# 遍历计算每个时间点的Aroon值
for i in range(len(klines)):
if i < AROON_PERIOD - 1:
aroon_up.append(0)
aroon_down.append(0)
continue
period_data = klines.iloc[i - AROON_PERIOD + 1:i + 1]
# 明确指定skipna=True来处理NaN值
high_idx = period_data['high'].fillna(float('-inf')).argmax()
low_idx = period_data['low'].fillna(float('inf')).argmin()
days_since_high = i - (i - AROON_PERIOD + 1 + high_idx)
days_since_low = i - (i - AROON_PERIOD + 1 + low_idx)
aroon_up.append(((AROON_PERIOD - days_since_high) / AROON_PERIOD) * 100)
aroon_down.append(((AROON_PERIOD - days_since_low) / AROON_PERIOD) * 100)
# 将Aroon值添加到klines
klines['aroon_up'] = aroon_up
klines['aroon_down'] = aroon_down
# 计算Aroon Oscillator (可选)
klines['aroon_osc'] = klines['aroon_up'] - klines['aroon_down']
# 获取当前和前一个周期的数据
current_price = float(klines.close.iloc[-1])
current_time = pd.to_datetime(klines.datetime.iloc[-1], unit='ns')
current_aroon_up = float(klines.aroon_up.iloc[-1])
current_aroon_down = float(klines.aroon_down.iloc[-1])
prev_aroon_up = float(klines.aroon_up.iloc[-2])
prev_aroon_down = float(klines.aroon_down.iloc[-2])
# 输出当前指标值，帮助调试
print(f"当前K线: {current_time.strftime('%Y-%m-%d')}, 价格: {current_price:.2f}")
print(f"Aroon Up: {current_aroon_up:.2f}, Aroon Down: {current_aroon_down:.2f}")
# ===== 止损检查 =====
if position != 0 and entry_price != 0:
if position > 0: # 多头止损
profit_pct = (current_price / entry_price - 1) * 100
if profit_pct < -STOP_LOSS_PCT:
print(f"触发止损: 当前价格={current_price}, 入场价={entry_price}, 亏损={profit_pct:.2f}%")
target_pos.set_target_volume(0)
trades.append({
'type': '止损平多',
'time': current_time,
'price': current_price,
'profit_pct': profit_pct
})
print(f"止损平多: {current_time}, 价格: {current_price:.2f}, 亏损: {profit_pct:.2f}%")
position = 0
entry_price = 0
continue
elif position < 0: # 空头止损
profit_pct = (entry_price / current_price - 1) * 100
if profit_pct < -STOP_LOSS_PCT:
print(f"触发止损: 当前价格={current_price}, 入场价={entry_price}, 亏损={profit_pct:.2f}%")
target_pos.set_target_volume(0)
trades.append({
'type': '止损平空',
'time': current_time,
'price': current_price,
'profit_pct': profit_pct
})
print(f"止损平空: {current_time}, 价格: {current_price:.2f}, 亏损: {profit_pct:.2f}%")
position = 0
entry_price = 0
continue
# ===== 交易信号判断 =====
# 1. Aroon交叉信号
aroon_cross_up = prev_aroon_up < prev_aroon_down and current_aroon_up > current_aroon_down
aroon_cross_down = prev_aroon_up > prev_aroon_down and current_aroon_up < current_aroon_down
# 2. 强势信号
strong_up = current_aroon_up > AROON_UPPER_THRESHOLD and current_aroon_down < AROON_LOWER_THRESHOLD
strong_down = current_aroon_down > AROON_UPPER_THRESHOLD and current_aroon_up < AROON_LOWER_THRESHOLD
# ===== 交易决策 =====
if position == 0: # 空仓状态
# 多头信号
if aroon_cross_up or strong_up:
position = POSITION_SIZE
entry_price = current_price
target_pos.set_target_volume(position)
signal_type = "交叉" if aroon_cross_up else "强势"
trades.append({
'type': '开多',
'time': current_time,
'price': current_price,
'signal': signal_type
})
print(f"开多仓: {current_time}, 价格: {current_price:.2f}, 信号: Aroon {signal_type}")
# 空头信号
elif aroon_cross_down or strong_down:
position = -POSITION_SIZE
entry_price = current_price
target_pos.set_target_volume(position)
signal_type = "交叉" if aroon_cross_down else "强势"
trades.append({
'type': '开空',
'time': current_time,
'price': current_price,
'signal': signal_type
})
print(f"开空仓: {current_time}, 价格: {current_price:.2f}, 信号: Aroon {signal_type}")
elif position > 0: # 持有多头
# 平多信号
if aroon_cross_down:
profit_pct = (current_price / entry_price - 1) * 100
target_pos.set_target_volume(0)
trades.append({
'type': '平多',
'time': current_time,
'price': current_price,
'profit_pct': profit_pct
})
print(f"平多仓: {current_time}, 价格: {current_price:.2f}, 盈亏: {profit_pct:.2f}%")
position = 0
entry_price = 0
elif position < 0: # 持有空头
# 平空信号
if aroon_cross_up:
profit_pct = (entry_price / current_price - 1) * 100
target_pos.set_target_volume(0)
trades.append({
'type': '平空',
'time': current_time,
'price': current_price,
'profit_pct': profit_pct
})
print(f"平空仓: {current_time}, 价格: {current_price:.2f}, 盈亏: {profit_pct:.2f}%")
position = 0
entry_price = 0
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.