AR Momentum Strategy for Gold

Code TqSdk

Summary

This example describes a short-term price timing strategy for a gold futures contract. It calculates an AR indicator from recent daily bars by comparing the accumulated distance from open to high with the distance from open to low, scaled as a percentage. The indicator is refreshed when a new daily bar appears, while entry and exit checks run when the latest quoted price changes.

The strategy opens a long position when AR is within a higher threshold band and a short position when it falls within a lower band. It closes either position when AR crosses a specified stop threshold. The document is instructional sample code, not a research study: it provides no backtest, cost model, or evidence that the thresholds are profitable. Its fixed contract, position size, and thresholds require evaluation before use in another market or trading setup.

Key ideas

The strategy calculates AR from recent daily open, high, and low prices.
It uses separate AR threshold bands to open long and short gold futures positions.
A zero denominator is replaced with the contract's minimum price tick.
Positions are closed when AR crosses a direction-specific stop threshold.
The example supplies no backtest or transaction cost analysis.

Tags

Futures Commodities Momentum Technical indicators Risk management

Full text

# momentum.py


```py
#!/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.

A Threshold-Based AR Price Momentum Strategy for Gold Futures

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Key ideas

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