Dynamic Dual EMA Crossover Strategy with Adaptive Profit/Loss Control
Author: ChaoZhang, Date: 2024-12-11 11:23:54Tags: EMASMA
Overview
This is a quantitative trading strategy based on dual EMA crossover signals, which uses the intersection of fast and slow Exponential Moving Averages (EMA) to determine market trends, combined with dynamic take-profit and stop-loss controls for risk management. The strategy employs percentage-based position management, defaulting to 10% of capital per trade, and implements dynamic profit targets and stop-loss levels for protection.
Strategy Principles
The core logic revolves around monitoring crossovers between 20-period and 50-period EMAs to identify trend changes. A long position is initiated when the fast EMA crosses above the slow EMA. Upon entry, the system automatically sets take-profit levels (1.3 times entry price) and stop-loss levels (0.95 times entry price). This dynamic profit/loss control design adapts to different market conditions, enhancing strategy flexibility.
Strategy Advantages
- Signal Stability - Uses EMA instead of SMA, providing faster response to price changes while filtering market noise.
- Comprehensive Risk Management - Implements dynamic take-profit and stop-loss mechanisms that adjust with entry prices.
- Rational Capital Management - Uses fixed proportion position sizing, avoiding high-risk full position trading.
- High Automation - Automates everything from signal generation to position management, reducing human intervention.
- Strong Adaptability - Strategy can adapt to different market conditions with adjustable parameters.
Strategy Risks
- EMA Lag - Despite being faster than SMA, EMA still has some inherent lag, potentially causing delayed entries.
- Poor Performance in Ranging Markets - May generate frequent false breakout signals during sideways market conditions.
- Fixed Multiplier for Profit/Loss - Using fixed multipliers for take-profit and stop-loss may not suit all market conditions.
- Drawdown Risk - 5% stop-loss might not be sufficient in highly volatile markets.
Optimization Directions
- Incorporate Volatility Indicators - Suggest adding ATR to dynamically adjust profit/loss multipliers for better market adaptation.
- Add Trend Confirmation - Consider incorporating RSI, MACD for signal filtering to improve win rate.
- Optimize Position Sizing - Implement dynamic position sizing based on market volatility for finer risk control.
- Add Time Filters - Consider adding trading time windows to avoid highly volatile periods.
- Enhance Profit-Taking - Implement trailing stops to capture more profit in strong trends.
Conclusion
This is a well-designed trend-following strategy with clear logic, using dual EMA crossovers for trend capture and dynamic profit/loss controls for risk management. The strategy’s strengths lie in its clear rules and controlled risk, making it suitable as a foundation for medium to long-term trading systems. There’s significant room for optimization through additional filters and enhanced profit/loss mechanisms. Traders should validate the strategy through backtesting across different market conditions and adjust parameters according to their risk tolerance before live implementation.
/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-09 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Pineify
//======================================================================//
// ____ _ _ __ //
// | _ \(_)_ __ ___(_)/ _|_ _ //
// | |_) | | '_ \ / _ \ | |_| | | | //
// | __/| | | | | __/ | _| |_| | //
// |_| |_|_| |_|\___|_|_| \__, | //
// |___/ //
//======================================================================//
//@version=5
strategy(title="TQQQ EMA Strategy", overlay=true)
//#region —————————————————————————————————————————————————— Common Dependence
p_comm_time_range_to_unix_time(string time_range, int date_time = time, string timezone = syminfo.timezone) =>
int start_unix_time = na
int end_unix_time = na
int start_time_hour = na
int start_time_minute = na
int end_time_hour = na
int end_time_minute = na
if str.length(time_range) == 11
// Format: hh:mm-hh:mm
start_time_hour := math.floor(str.tonumber(str.substring(time_range, 0, 2)))
start_time_minute := math.floor(str.tonumber(str.substring(time_range, 3, 5)))
end_time_hour := math.floor(str.tonumber(str.substring(time_range, 6, 8)))
end_time_minute := math.floor(str.tonumber(str.substring(time_range, 9, 11)))
else if str.length(time_range) == 9
// Format: hhmm-hhmm
start_time_hour := math.floor(str.tonumber(str.substring(time_range, 0, 2)))
start_time_minute := math.floor(str.tonumber(str.substring(time_range, 2, 4)))
end_time_hour := math.floor(str.tonumber(str.substring(time_range, 5, 7)))
end_time_minute := math.floor(str.tonumber(str.substring(time_range, 7, 9)))
start_unix_time := timestamp(timezone, year(date_time, timezone), month(date_time, timezone), dayofmonth(date_time, timezone), start_time_hour, start_time_minute, 0)
end_unix_time := timestamp(timezone, year(date_time, timezone), month(date_time, timezone), dayofmonth(date_time, timezone), end_time_hour, end_time_minute, 0)
[start_unix_time, end_unix_time]
p_comm_time_range_to_start_unix_time(string time_range, int date_time = time, string timezone = syminfo.timezone) =>
int start_time_hour = na
int start_time_minute = na
if str.length(time_range) == 11
// Format: hh:mm-hh:mm
start_time_hour := math.floor(str.tonumber(str.substring(time_range, 0, 2)))
start_time_minute := math.floor(str.tonumber(str.substring(time_range, 3, 5)))
else if str.length(time_range) == 9
// Format: hhmm-hhmm
start_time_hour := math.floor(str.tonumber(str.substring(time_range, 0, 2)))
start_time_minute := math.floor(str.tonumber(str.substring(time_range, 2, 4)))
timestamp(timezone, year(date_time, timezone), month(date_time, timezone), dayofmonth(date_time, timezone), start_time_hour, start_time_minute, 0)
p_comm_time_range_to_end_unix_time(string time_range, int date_time = time, string timezone = syminfo.timezone) =>
int end_time_hour = na
int end_time_minute = na
if str.length(time_range) == 11
end_time_hour := math.floor(str.tonumber(str.substring(time_range, 6, 8)))
end_time_minute := math.floor(str.tonumber(str.substring(time_range, 9, 11)))
else if str.length(time_range) == 9
end_time_hour := math.floor(str.tonumber(str.substring(time_range, 5, 7)))
end_time_minute := math.floor(str.tonumber(str.substring(time_range, 7, 9)))
timestamp(timezone, year(date_time, timezone), month(date_time, timezone), dayofmonth(date_time, timezone), end_time_hour, end_time_minute, 0)
p_comm_timeframe_to_seconds(simple string tf) =>
float seconds = 0
tf_lower = str.lower(tf)
value = str.tonumber(str.substring(tf_lower, 0, str.length(tf_lower) - 1))
if str.endswith(tf_lower, 's')
seconds := value
else if str.endswith(tf_lower, 'd')
seconds := value * 86400
else if str.endswith(tf_lower, 'w')
seconds := value * 604800
else if str.endswith(tf_lower, 'm')
seconds := value * 2592000
else
seconds := str.tonumber(tf_lower) * 60
seconds
p_custom_sources() =>
[open, high, low, close, volume]
//#endregion —————————————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Ta Dependence
//#endregion —————————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Constants
// Input Groups
string P_GP_1 = ""
//#endregion —————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Inputs
// Default
int p_inp_1 = input.int(defval=20, title="Fast EMA Length", group=P_GP_1)
int p_inp_2 = input.int(defval=50, title="Slow EMA Length", group=P_GP_1)
float p_inp_3 = input.float(defval=1.3, title="Take Profit Price Multiplier", group=P_GP_1, step=0.01)
float p_inp_4 = input.float(defval=0.95, title="Stop Loss Price Multiplier", group=P_GP_1, step=0.01)
//#endregion ———————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Price Data
//#endregion ———————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Indicators
p_ind_1 = ta.ema(close, p_inp_1) // Fast EMA
p_ind_2 = ta.ema(close, p_inp_2) // Slow EMA
//#endregion ———————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Conditions
p_cond_1 = (ta.crossover(p_ind_1, p_ind_2))
//#endregion ———————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Strategy
// Strategy Order Variables
string p_st_name_1 = "Entry"
string p_st_name_2 = "Exit"
var float p_st_name_2_tp = na
var bool p_st_name_2_tp_can_drawing = true
var float p_st_name_2_sl = na
var bool p_st_name_2_sl_can_drawing = true
// Strategy Global
open_trades_number = strategy.opentrades
pre_bar_open_trades_number = na(open_trades_number[1]) ? 0 : open_trades_number[1]
var p_entry_order_id = 1
p_can_place_entry_order() =>
strategy.equity > 0
get_entry_id_name(int current_order_id, string name) =>
"[" + str.tostring(current_order_id) + "] " + name
is_entry_order(string order_id, string name) =>
str.startswith(order_id, "[") and str.endswith(order_id, "] " + name)
get_open_trades_entry_ids() =>
int p_open_trades_count = strategy.opentrades
string[] p_entry_ids = array.new_string(0, "")
if p_open_trades_count > 0
for i = 0 to p_open_trades_count - 1
array.push(p_entry_ids, strategy.opentrades.entry_id(i))
p_entry_ids
// Entry (Entry)
if p_cond_1 and p_can_place_entry_order()
p_st_name_1_id = get_entry_id_name(p_entry_order_id, p_st_name_1)
p_entry_order_id := p_entry_order_id + 1
string entry_message = ""
strategy.entry(id=p_st_name_1_id, direction=strategy.long, alert_message=entry_message, comment=p_st_name_1_id)
// TP/SL Exit (Exit)
float p_st_name_2_limit = close * p_inp_3
if p_st_name_2_tp_can_drawing
p_st_name_2_tp_can_drawing := false
p_st_name_2_tp := p_st_name_2_limit
float p_st_name_2_stop = close * p_inp_4
if p_st_name_2_sl_can_drawing
p_st_name_2_sl_can_drawing := false
p_st_name_2_sl := p_st_name_2_stop
string p_st_name_2_alert_message = ""
strategy.exit(id=p_st_name_1_id + "_0", from_entry=p_st_name_1_id, qty_percent=100, limit=p_st_name_2_limit, stop=p_st_name_2_stop, comment_profit=p_st_name_2 + " - TP", comment_loss=p_st_name_2 + " - SL", alert_message=p_st_name_2_alert_message)
if high >= p_st_name_2_tp or (pre_bar_open_trades_number > 0 and open_trades_number == 0)
p_st_name_2_tp_can_drawing := true
p_st_name_2_sl_can_drawing := true
p_st_name_2_tp := na
p_st_name_2_sl := na
plot(p_st_name_2_tp, title="Exit - TP", color=color.rgb(0, 150, 136, 0), linewidth=1, style = plot.style_circles)
if low <= p_st_name_2_sl or (pre_bar_open_trades_number > 0 and open_trades_number == 0)
p_st_name_2_sl_can_drawing := true
p_st_name_2_tp_can_drawing := true
p_st_name_2_sl := na
p_st_name_2_tp := na
plot(p_st_name_2_sl, title="Exit - SL", color=color.rgb(244, 67, 54, 0), linewidth=1, style = plot.style_circles)
//#endregion —————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Indicator Plots
// Fast EMA
plot(p_ind_1, "Fast EMA", color.rgb(33, 150, 243, 0), 1)
// Slow EMA
plot(p_ind_2, "Slow EMA", color.rgb(255, 82, 82, 0), 1)
//#endregion ————————————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Custom Plots
//#endregion —————————————————————————————————————————————————————————————
//#region —————————————————————————————————————————————————— Alert
//#endregion ——————————————————————————————————————————————————————
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