ChaoZhang
Overview
This strategy belongs to the scalping strategy type, aiming to open and close positions frequently to profit from small gains while limiting downside risks. It identifies potential reversal points with moving averages to go long, and sets tight take profit targets to lock in small profits.
Strategy Logic
The strategy uses 4 moving averages - 9, 50, 100, and 200 periods.
The specific trading rules are:
- Go long when 9 MA crosses above 50 MA
- 50 MA is below 100 MA
- 100 MA is below 200 MA
This combination identifies situations when price is in short-term downtrend but a reversal may occur.
Exit rule is when 9 MA crosses above 200 MA. A near profit target is used to lock in frequent small gains for steady profits.
Advantages
- Frequent opening and closing controls single loss
- MA crossover catches potential bottoms
- Near profit target locks in small certain wins
- Reduced holding time minimizes trend influence
- High capital utilization suitable for small accounts
Risks
- MA lag may miss best entry points
- Small profit range vulnerable to fees
- More invalid trades increase time and energy costs
- Excessively conservative TP fails to ride trends
- Hard to profit in range-bound markets
Risks can be reduced by:
- Optimizing MA parameters for better signal accuracy
- Relaxing TP to capture more trend profits
- Adding other indicators for confirmation, reducing invalid trades
- Optimizing capital utilization and position sizing
- Considering re-entries
Optimization Directions
The strategy can be improved by:
- Optimizing MA combinations
Testing more MA periods for better reversal detection.
- Widening take profit levels
Allow wider TP distance for more trend profits.
- Adding other indicators
Such as KDJ, MACD for confirmation to reduce invalid trades.
- Position sizing optimization
Dynamically size positions based on specific TP and SL.
- Adding re-entry rules
Consider re-entering after TP if trend continues.
Summary
This scalping strategy identifies potential short-term reversals with MA combinations for frequent small profits. This effectively controls single loss and risks, making it suitable for small accounts growth. However limitations exist like small profit range and excessive trades. Improvements can be made via parameter tuning, TP adjusting, adding filters etc, to expand profits while retaining its strengths, making the strategy more robust and efficient. Also continuously learning other more advanced strategies is important.
/*backtest
start: 2023-08-21 00:00:00
end: 2023-09-20 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
//strategy(shorttitle='Moving Average Scalper (by Coinrule)',title='Moving Average Scalper', overlay=true, initial_capital = 1000, default_qty_type = strategy.percent_of_equity, default_qty_type = strategy.percent_of_equity, default_qty_value = 30, commission_type=strategy.commission.percent, commission_value=0.1)
//Backtest dates
fromMonth = input(defval = 1, title = "From Month", type = input.integer, minval = 1, maxval = 12)
fromDay = input(defval = 10, title = "From Day", type = input.integer, minval = 1, maxval = 31)
fromYear = input(defval = 2019, title = "From Year", type = input.integer, minval = 1970)
thruMonth = input(defval = 1, title = "Thru Month", type = input.integer, minval = 1, maxval = 12)
thruDay = input(defval = 1, title = "Thru Day", type = input.integer, minval = 1, maxval = 31)
thruYear = input(defval = 2112, title = "Thru Year", type = input.integer, minval = 1970)
showDate = input(defval = true, title = "Show Date Range", type = input.bool)
start = timestamp(fromYear, fromMonth, fromDay, 00, 00) // backtest start window
finish = timestamp(thruYear, thruMonth, thruDay, 23, 59) // backtest finish window
window() => true // create function "within window of time"
//MA inputs and calculations
movingaverage_signal = sma(close, input(9))
movingaverage_fast = sma(close, input(50))
movingaverage_slow = sma(close, input(200))
movingaverage_mid= sma(close, input(100))
//Entry
bullish = crossover(movingaverage_signal, movingaverage_fast)
strategy.entry(id="long", long = true, when = bullish and movingaverage_fast < movingaverage_mid and movingaverage_mid < movingaverage_slow and window())
//Exit
bearish = crossover(movingaverage_signal, movingaverage_slow)
Stop_loss= ((input (2))/100)
Take_profit= ((input (8))/100)
longStopPrice = strategy.position_avg_price * (1 - Stop_loss)
longTakeProfit = strategy.position_avg_price * (1 + Take_profit)
strategy.close("long", when = bearish)
// close < longStopPrice or close > longTakeProfit and window())
//PLOT
plot(movingaverage_signal, color=color.black, linewidth=2 )
plot(movingaverage_fast, color=color.orange, linewidth=2)
plot(movingaverage_slow, color=color.purple, linewidth=2)
plot(movingaverage_mid, color=color.blue, linewidth=2)