Escalator Moving-Average Strategy

Article Strategy library · Author: Ringo

Summary

This introductory futures strategy combines fast and slow moving averages with the close’s position within each candle range. When flat, it considers a long if price is above both averages, the prior completed candle closed in the bottom quarter of its range, and the latest completed candle closed in the top quarter. The short setup mirrors these conditions: price below both averages, with a shift from the prior candle’s top quarter to the latest candle’s bottom quarter. Orders are sent through a target-position task.

For open trades, exits are based on a close moving beyond the lowest low or highest high of the two recent completed candles, offset by one minimum price increment. The example uses daily candles and a specified futures contract, but it supplies no historical test results or evidence of profitability. The logic can miss signals or behave differently across instruments and timeframes; the code is presented as a functional example that requires adaptation. Position targets are fixed in the example, and broader portfolio risk controls are not discussed.

Key ideas

The strategy requires price to be above or below both moving averages before opening a position.
A two-candle shift between range quarters provides the entry trigger.
Long and short entries use mirrored conditions based on candle position within its range.
Stops use the recent two-candle low or high with a one-tick offset.
The example gives implementation logic but no backtest evidence or broader portfolio risk analysis.

Tags

Futures Trend following Technical indicators Risk management Execution

Full text

# escalator


# escalator









## Source (Apache-2.0)

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

'''
自动扶梯 策略 (难度：初级)
参考: https://www.shinnytech.com/blog/escalator/
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
from tqsdk.ta import MA

# 设置合约
SYMBOL = "SHFE.rb2012"
# 设置均线长短周期
MA_SLOW, MA_FAST = 8, 40

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


# K线收盘价在这根K线波动范围函数


def kline_range(num):
    kl_range = (klines.iloc[num].close - klines.iloc[num].low) / \
               (klines.iloc[num].high - klines.iloc[num].low)
    return kl_range


# 获取长短均线值
def ma_caculate(klines):
    ma_slow = MA(klines, MA_SLOW).iloc[-1].ma
    ma_fast = MA(klines, MA_FAST).iloc[-1].ma
    return ma_slow, ma_fast


ma_slow, ma_fast = ma_caculate(klines)
print("慢速均线为%.2f,快速均线为%.2f" % (ma_slow, ma_fast))

while True:
    api.wait_update()
    # 每次k线更新，重新计算快慢均线
    if api.is_changing(klines.iloc[-1], "datetime"):
        ma_slow, ma_fast = ma_caculate(klines)
        print("慢速均线为%.2f,快速均线为%.2f" % (ma_slow, ma_fast))

    if api.is_changing(quote, "last_price"):
        # 开仓判断
        if position.pos_long == 0 and position.pos_short == 0:
            # 计算前后两根K线在当时K线范围波幅
            kl_range_cur = kline_range(-2)
            kl_range_pre = kline_range(-3)
            # 开多头判断，最近一根K线收盘价在短期均线和长期均线之上，前一根K线收盘价位于K线波动范围底部25%，最近这根K线收盘价位于K线波动范围顶部25%
            if klines.iloc[-2].close > max(ma_slow, ma_fast) and kl_range_pre <= 0.25 and kl_range_cur >= 0.75:
                print("最新价为:%.2f 开多头" % quote.last_price)
                target_pos.set_target_volume(100)

            # 开空头判断，最近一根K线收盘价在短期均线和长期均线之下，前一根K线收盘价位于K线波动范围顶部25%，最近这根K线收盘价位于K线波动范围底部25%
            elif klines.iloc[-2].close < min(ma_slow, ma_fast) and kl_range_pre >= 0.75 and kl_range_cur <= 0.25:
                print("最新价为:%.2f 开空头" % quote.last_price)
                target_pos.set_target_volume(-100)
            else:
                print("最新价位:%.2f ，未满足开仓条件" % quote.last_price)

        # 多头持仓止损策略
        elif position.pos_long > 0:
            # 在两根K线较低点减一跳，进行多头止损
            kline_low = min(klines.iloc[-2].low, klines.iloc[-3].low)
            if klines.iloc[-1].close <= kline_low - quote.price_tick:
                print("最新价为:%.2f,进行多头止损" % (quote.last_price))
                target_pos.set_target_volume(0)
            else:
                print("多头持仓，当前价格 %.2f,多头离场价格%.2f" %
                      (quote.last_price, kline_low - quote.price_tick))

        # 空头持仓止损策略
        elif position.pos_short > 0:
            # 在两根K线较高点加一跳，进行空头止损
            kline_high = max(klines.iloc[-2].high, klines.iloc[-3].high)
            if klines.iloc[-1].close >= kline_high + quote.price_tick:
                print("最新价为:%.2f 进行空头止损" % quote.last_price)
                target_pos.set_target_volume(0)
            else:
                print("空头持仓，当前价格 %.2f,空头离场价格%.2f" %
                      (quote.last_price, kline_high + quote.price_tick))

```

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.

Escalator Strategy: Moving-Average Filters and Two-Bar Reversals

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