Moving Average Signals for Soybean Oil, Palm Oil, and Rapeseed Oil Spreads
Summary
This example constructs a relative spread indicator from daily closes for soybean oil, palm oil, and rapeseed oil futures. It calculates the difference between two pairwise price spreads and scales that value by the difference between rapeseed oil and palm oil prices. Five-day and 15-day moving averages of the indicator are used to generate signals.
When the short average crosses above the long average and the indicator is sufficiently above the short average, the example targets a long rapeseed oil position and a short soybean oil position. A downward cross with the indicator sufficiently below its short average instead targets long soybean oil and short palm oil. Positions in all three contracts are set to zero when the indicator returns near its averages. The source is labeled as a functional demonstration and supplies no backtest results, sizing rationale, transaction-cost model, or discussion of contract alignment. Its historical contract symbols also mean the example needs adaptation before use with current contracts.
Key ideas
- The indicator combines two relative price differences among three vegetable oil futures contracts.
- Five-day and 15-day averages of the indicator provide crossover signals.
- The two signal branches express different relative value views using pairs of contracts.
- Positions are flattened when the indicator returns near its moving averages.
- The example provides no evidence of profitability or detailed risk controls.
Tags
Full text
# oi-y-p-spreads
# oi-y-p-spreads
## Source (Apache-2.0)
```python
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Ringo"
"""
豆油、棕榈油、菜油套利策略
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, TargetPosTask
from tqsdk.tafunc import ma
# 设定豆油，菜油，棕榈油指定合约
SYMBOL_Y = "DCE.y2001"
SYMBOL_OI = "CZCE.OI001"
SYMBOL_P = "DCE.p2001"
api = TqApi()
klines_y = api.get_kline_serial(SYMBOL_Y, 24 * 60 * 60)
klines_oi = api.get_kline_serial(SYMBOL_OI, 24 * 60 * 60)
klines_p = api.get_kline_serial(SYMBOL_P, 24 * 60 * 60)
target_pos_oi = TargetPosTask(api, SYMBOL_OI)
target_pos_y = TargetPosTask(api, SYMBOL_Y)
target_pos_p = TargetPosTask(api, SYMBOL_P)
# 设置指标计算函数，计算三种合约品种的相对位置，并将指标画在副图
def cal_spread(klines_y, klines_p, klines_oi):
index_spread = ((klines_y.close - klines_p.close) - (klines_oi.close - klines_y.close)) / (
klines_oi.close - klines_p.close)
klines_y["index_spread"] = index_spread
ma_short = ma(index_spread, 5)
ma_long = ma(index_spread, 15)
return index_spread, ma_short, ma_long
index_spread, ma_short, ma_long = cal_spread(klines_y, klines_p, klines_oi)
klines_y["index_spread.board"] = "index_spread"
print("ma_short是%.2f,ma_long是%.2f，index_spread是%.2f" % (ma_short.iloc[-2], ma_long.iloc[-2], index_spread.iloc[-2]))
while True:
api.wait_update()
if api.is_changing(klines_y.iloc[-1], "datetime"):
index_spread, ma_short, ma_long = cal_spread(klines_y, klines_p, klines_oi)
print("日线更新，ma_short是%.2f,ma_long是%.2f，index_spread是%.2f" % (
ma_short.iloc[-2], ma_long.iloc[-2], index_spread.iloc[-2]))
# 指数上涨，短期上穿长期，则认为相对于y，oi被低估，做多oi，做空y
if (ma_short.iloc[-2] > ma_long.iloc[-2]) and (ma_short.iloc[-3] < ma_long.iloc[-3]) and (
index_spread.iloc[-2] > 1.02 * ma_short.iloc[-2]):
target_pos_y.set_target_volume(-100)
target_pos_oi.set_target_volume(100)
# 指数下跌，短期下穿长期，则认为相对于y，p被高估，做多y，做空p
elif (ma_short.iloc[-2] < ma_long.iloc[-2]) and (ma_short.iloc[-3] > ma_long.iloc[-3]) and (
index_spread.iloc[-2] < 0.98 * ma_short.iloc[-2]):
target_pos_y.set_target_volume(100)
target_pos_p.set_target_volume(-100)
# 现在策略表现平稳，则平仓，赚取之前策略收益
elif ma_short.iloc[-2] * 0.98 < index_spread.iloc[-2] < ma_long.iloc[-2] * 1.02:
target_pos_oi.set_target_volume(0)
target_pos_p.set_target_volume(0)
target_pos_y.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.