AR Range Ratio Momentum Strategy

Article Strategy library · Author: Ringo

Summary

This example calculates an AR price-momentum measure from the prior 14 daily bars. It sums the differences between each bar's high and open, divides by the sum of the differences between open and low, and multiplies by 100. If the denominator is zero, it substitutes the contract's minimum price tick. The code is configured for a gold futures contract and updates the measure when a new daily bar forms.

When flat, it targets a long position of 100 contracts if AR is between 110 and 150, or a short position of 100 if AR is between 50 and 90. It exits to flat if the measure falls below 90 while long or rises above 110 while short. These rules provide a worked example, not evidence of profitability: the document reports no backtest results and explicitly describes the sample as a demonstration that should be adapted before live use. The code also embeds account authentication placeholders.

Key ideas

The AR measure compares summed high-to-open movement with summed open-to-low movement over prior daily bars.
The example uses a 14-bar calculation and replaces a zero denominator with the contract's minimum price tick.
An AR reading between 110 and 150 opens a long position, while readings between 50 and 90 open a short position.
Exit thresholds are below 90 for longs and above 110 for shorts.
The example specifies 100-contract target positions but provides no evidence of trading performance.

Tags

Futures Commodities Momentum Technical indicators Position sizing

Full text

# momentum


# momentum









## Source (Apache-2.0)

```python
#!/usr/bin/env python
#  -*- coding: utf-8 -*-
__author__ = "Ringo"

'''
价格动量 策略 (难度：初级)
参考: https://www.shinnytech.com/blog/momentum-strategy/
注: 该示例策略仅用于功能示范, 实盘时请根据自己的策略/经验进行修改
'''

from tqsdk import TqApi, TqAuth, TargetPosTask

# 设置指定合约,获取N条K线计算价格动量
SYMBOL = "SHFE.au2012"
N = 15

api = TqApi(auth=TqAuth("快期账户", "账户密码"))
klines = api.get_kline_serial(SYMBOL, 60 * 60 * 24, N)
quote = api.get_quote(SYMBOL)
target_pos = TargetPosTask(api, SYMBOL)
position = api.get_position(SYMBOL)


def AR(kline1):
    """价格动量函数AR，以前N-1日K线计算价格动量ar"""
    spread_ho = sum(kline1.high[:-1] - kline1.open[:-1])
    spread_oc = sum(kline1.open[:-1] - kline1.low[:-1])
    # spread_oc 为0时，设置为最小价格跳动值
    if spread_oc == 0:
        spread_oc = quote.price_tick
    ar = (spread_ho / spread_oc) * 100
    return ar


ar = AR(klines)
print("策略开始启动")

while True:
    api.wait_update()
    # 生成新K线时，重新计算价格动量值ar
    if api.is_changing(klines.iloc[-1], "datetime"):
        ar = AR(klines)
        print("价格动量是：", ar)
    # 每次最新价发生变动时，重新进行判断
    if api.is_changing(quote, "last_price"):
        # 开仓策略
        if position.pos_long == 0 and position.pos_short == 0:
            # 如果ar大于110并且小于150，开多仓
            if 110 < ar < 150:
                print("价值动量超过110，小于150，做多")
                target_pos.set_target_volume(100)
            # 如果ar大于50，小于90，开空仓
            elif 50 < ar < 90:
                print("价值动量大于50，小于90，做空")
                target_pos.set_target_volume(-100)

        # 止损策略，多头下当前ar值小于90则平仓止损，空头下当前ar值大于110则平仓止损
        elif (position.pos_long > 0 and ar < 90) or (position.pos_short > 0 and ar > 110):
            print("止损平仓")
            target_pos.set_target_volume(0)

```

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.

Commodity Futures Momentum Strategy Using the AR Range Ratio

Summary

Key ideas

Tags