Momentum Reversal Trading Strategy

Author: ChaoZhang, Date: 2024-01-18 11:26:40



This is a very simple short-term trading strategy that is mainly suitable for index futures daily trading. It only goes long when the index is in a long-term uptrend channel and there is a short-term reversal signal.


The strategy mainly uses moving averages and RSI indicators to determine trends and overbought/oversold conditions. The specific trading signals are: the index closing price rebounds from the long-term 200-day moving average and remains above it as the long-term trend judgment; the closing price breaks below the 10-day moving average as the short-term adjustment signal; RSI3 less than 30 as the oversold signal. When the above three conditions are met, it is believed that the probability of a short-term reversal is relatively large, so go long.

After taking a position, exits are based on stop loss, take profit and short-term trend judgments. If the closing price stands back above the 10-day MA, judging that the short-term adjustment has ended, take profit actively; if the closing price hits a new low, stop out with a loss; take profit when the closing price rises 10%.

Advantage Analysis

The strategy has the following advantages:

  1. Simple logic, easy to understand and implement, suitable for beginners;
  2. Make full use of the long-term uptrend of the index to avoid trading against the trend;
  3. Use the RSI indicator to determine the short-term reversal point to increase the profit probability;
  4. There are stop loss and take profit mechanisms to control risks;
  5. Low data requirements, daily data is enough, suitable for zero-cost implementation.

Risk Analysis

The strategy also has some risks:

  1. Sustained declines in bear markets will lead to losses;
  2. Failed reversals can cause significant losses;
  3. Improper parameter settings can also affect results, such as incorrect moving average periods;
  4. Trading frequency may be low, unable to capture all adjustments;
  5. Limited profit upside, not much higher than market index returns.

In response to the above risks, methods such as optimizing cycle parameters, adjusting stop-loss ratios, adding other indicator judgments, etc. can be used to improve the strategy.

Optimization Directions

The strategy can be optimized in the following aspects:

  1. Increase multifactor judgments of long-term and short-term trends, such as MACD and KD to improve judgment accuracy;
  2. Add trading volume analysis, such as going long when trading volume surges;
  3. Optimize parameter settings through Walk Forward Analysis and other methods to find the best parameters;
  4. Combine more reversal factors,such as Fibonacci retracement levels, support and resistance levels to determine the reversal levels;
  5. Comprehensively consider profit ratio optimization, such as adjusting positions and stop-loss ratios to achieve higher returns.


In summary, this is a very simple and practical short-term trading strategy. It combines the long-term uptrend and short-term pullback reversal of the index to obtain excess returns while controlling risks. By continuously optimizing and parameter tuning, better results can be achieved.

start: 2023-01-11 00:00:00
end: 2024-01-17 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]

// This source code is subject to the terms of the Mozilla Public License 2.0 at
// © tsujimoto0403

strategy("simple pull back", overlay=true,default_qty_type=strategy.percent_of_equity,

//input value,"長期移動平均BASE200/period of long term sma",group = "パラメータ"),"長期移動平均BASE10/period of short term sma",group = "パラメータ"),title = "損切の割合%/stoploss percentages",group = "パラメータ"),title = "利食いの割合%/take profit percentages",group = "パラメータ")
startday=input(title="バックテストを始める日/start trade day", defval=timestamp("01 Jan 2000 13:30 +0000"), group="期間")
endday=input(title="バックテスを終わる日/finish date day", defval=timestamp("1 Jan 2099 19:30 +0000"), group="期間")

//polt indicators that we use 

plot(malong,color=color.aqua,linewidth = 2)
plot(mashort,color=color.yellow,linewidth = 2)

//date range 
datefilter = true

//open conditions
if close>malong and close<mashort and strategy.position_size == 0 and datefilter and ta.rsi(close,3)<30 
    strategy.entry(id="long", direction=strategy.long)
//sell conditions 

if close>mashort and close<low[1] and strategy.position_size>0
    strategy.close(id ="long")