TRIX Signal-Line Crossover Strategy with ATR-Based Exits
Article Strategy library · Author: Chaos
Summary
This futures strategy uses the TRIX indicator, calculated from triple-smoothed exponential averages, and compares it with a rolling signal line. A bullish crossover opens a long position and a bearish crossover opens a short position. After entry, the strategy closes positions on an opposing crossover or when price reaches an ATR-based stop-loss or take-profit level. The supplied settings specify a TRIX period of 12, a signal period of 9, a 14-period ATR, stop and target distances of two and three ATR multiples, and a fixed position size. It uses daily bars for a specified futures contract and backtest window.
The code does not provide backtest performance results, so it offers no evidence of profitability. Although it defines a long-term moving average and a crossover-difference threshold, neither appears in the entry logic; the stated maximum holding period is also not enforced. Thus the implemented rules are simpler than some of the configured parameters suggest. Crossovers can lag or whipsaw, and the fixed position size does not adapt to volatility. These gaps and the absence of reported results limit conclusions about robustness.
Key ideas
- TRIX is computed from three successive exponential smoothings, then compared with a rolling signal line.
- A bullish crossover opens a long position, while a bearish crossover opens a short position.
- Positions can close on an opposing crossover or at stop and target distances based on ATR.
- The configured long-term average, crossover threshold, and maximum holding period are not used in the supplied trading logic.
- No backtest performance results are reported, so the strategy's effectiveness cannot be assessed from this document.
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Full text
# TRIX
# TRIX
## Source (Apache-2.0)
```python
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Chaos"
from datetime import date
import pandas as pd
from tqsdk import TqApi, TqAuth, TqBacktest, TargetPosTask, BacktestFinished
from tqsdk.ta import ATR
# ===== 全局参数设置 =====
SYMBOL = "CFFEX.IC2306" # 黄金期货合约
POSITION_SIZE = 30 # 基础持仓手数
START_DATE = date(2022, 11, 1) # 回测开始日期
END_DATE = date(2023, 4, 30) # 回测结束日期
# TRIX指标参数
TRIX_PERIOD = 12 # TRIX计算周期
SIGNAL_PERIOD = 9 # 信号线计算周期
MA_PERIOD = 60 # 长期移动平均线周期，用于趋势过滤
# 信号阈值参数
SIGNAL_THRESHOLD = 0.05 # TRIX与信号线差值的阈值，避免微小交叉
# 风控参数
ATR_PERIOD = 14 # ATR计算周期
STOP_LOSS_MULTIPLIER = 2.0 # 止损ATR倍数
TAKE_PROFIT_MULTIPLIER = 3.0 # 止盈ATR倍数
MAX_HOLDING_DAYS = 15 # 最大持仓天数
# ===== 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
trade_count = 0 # 交易次数
win_count = 0 # 盈利次数
# ===== TRIX指标计算函数 =====
def calculate_trix(close_prices, period):
"""计算TRIX指标和信号线"""
# 第一重EMA
ema1 = close_prices.ewm(span=period, adjust=False).mean()
# 第二重EMA
ema2 = ema1.ewm(span=period, adjust=False).mean()
# 第三重EMA
ema3 = ema2.ewm(span=period, adjust=False).mean()
# 计算TRIX
trix = 100 * (ema3 / ema3.shift(1) - 1)
# 计算信号线
signal = trix.rolling(SIGNAL_PERIOD).mean()
return trix, signal
# ===== 策略开始 =====
print("开始运行TRIX指标期货策略...")
print(f"品种: {SYMBOL}, 回测周期: {START_DATE} - {END_DATE}")
print(f"TRIX参数: 周期={TRIX_PERIOD}, 信号线周期={SIGNAL_PERIOD}")
# 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) < max(TRIX_PERIOD, SIGNAL_PERIOD, MA_PERIOD, ATR_PERIOD) + 10:
continue
# 计算TRIX指标和信号线
klines['trix'], klines['signal'] = calculate_trix(klines.close, TRIX_PERIOD)
# 计算长期移动平均线，用于趋势过滤
klines['ma'] = klines.close.rolling(window=MA_PERIOD).mean()
# 计算ATR用于设置止损
atr_data = ATR(klines, ATR_PERIOD)
# 获取最新数据
current_price = float(klines.close.iloc[-1])
current_datetime = pd.to_datetime(klines.datetime.iloc[-1], unit='ns')
current_trix = float(klines.trix.iloc[-1])
previous_trix = float(klines.trix.iloc[-2])
current_signal = float(klines.signal.iloc[-1])
previous_signal = float(klines.signal.iloc[-2])
current_ma = float(klines.ma.iloc[-1])
current_atr = float(atr_data.atr.iloc[-1])
# 计算TRIX与信号线的差值
trix_diff = current_trix - current_signal
previous_trix_diff = previous_trix - previous_signal
# 输出调试信息
print(f"日期: {current_datetime.strftime('%Y-%m-%d')}, 价格: {current_price:.2f}")
print(f"TRIX: {current_trix:.4f}, 信号线: {current_signal:.4f}, 差值: {trix_diff:.4f}")
# ===== 交易逻辑 =====
# 空仓状态 - 寻找开仓机会
if current_direction == 0:
# 多头开仓条件：TRIX上穿信号线
if previous_trix < previous_signal and current_trix > current_signal:
current_direction = 1
target_pos.set_target_volume(POSITION_SIZE)
entry_price = current_price
stop_loss_price = entry_price - STOP_LOSS_MULTIPLIER * current_atr
take_profit_price = entry_price + TAKE_PROFIT_MULTIPLIER * current_atr
print(f"多头开仓: 价格={entry_price}, 止损={stop_loss_price:.2f}, 止盈={take_profit_price:.2f}")
# 空头开仓条件：TRIX下穿信号线
elif previous_trix > previous_signal and current_trix < current_signal:
current_direction = -1
target_pos.set_target_volume(-POSITION_SIZE)
entry_price = current_price
stop_loss_price = entry_price + STOP_LOSS_MULTIPLIER * current_atr
take_profit_price = entry_price - TAKE_PROFIT_MULTIPLIER * current_atr
print(f"空头开仓: 价格={entry_price}, 止损={stop_loss_price:.2f}, 止盈={take_profit_price:.2f}")
# 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}, 盈亏={profit_pct:.2f}%")
# 止盈条件
elif current_price >= take_profit_price:
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}, 盈亏={profit_pct:.2f}%")
# 信号平仓：TRIX下穿信号线
elif previous_trix > previous_signal and current_trix < current_signal:
profit_pct = (current_price - entry_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"多头信号平仓: 价格={current_price}, 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}, 盈亏={profit_pct:.2f}%")
# 止盈条件
elif current_price <= take_profit_price:
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}, 盈亏={profit_pct:.2f}%")
# 信号平仓：TRIX上穿信号线
elif previous_trix < previous_signal and current_trix > current_signal:
profit_pct = (entry_price - current_price) / entry_price * 100
target_pos.set_target_volume(0)
current_direction = 0
print(f"空头信号平仓: 价格={current_price}, 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.