Triangular Moving Average Crossover Trading Strategy
Author: ChaoZhang, Date: 2024-01-16 18:18:02Tags:
Overview
The Triangular Moving Average (TMA) Crossover trading strategy is a typical technical analysis strategy. It utilizes three moving average lines of different time lengths to capture trends and implement low-risk trading. When the short-term moving average crosses over the medium-term moving average upwards, and the medium-term moving average is above the long-term moving average, a buy signal is generated. When the short-term moving average crosses below the medium-term moving average downwards, and the medium-term moving average is below the long-term moving average, a sell signal is generated.
Strategy Logic
The TMA strategy mainly relies on three moving average lines to determine the trend direction. The short-term moving average responds sensitively to price changes; the medium-term moving average provides a clearer judgment of the trend; the long-term moving average filters out market noise and determines the long-term trend direction.
When the short-term moving average crosses over the medium-term moving average upwards, it indicates the price has started to break out upwards. At this time, if the medium-term moving average is above the long-term moving average, it means the current market is in an uptrend. Therefore, a buy signal is generated here.
On the contrary, when the short-term moving average crosses below the medium-term moving average downwards, it indicates the price has started to break out downwards. At this time, if the medium-term moving average is below the long-term moving average, it means the current market is in a downtrend. As a result, a sell signal is generated.
This strategy also sets stop-loss and take-profit lines. After entering a trade, stop-loss and take-profit prices will be calculated based on the percentage settings. If the price touches either line, the position will be closed.
Advantage Analysis
- Utilize three moving averages together to improve judgment accuracy
- Set stop-loss and take-profit to effectively control per trade risk
- Customizable moving average parameters suitable for different products
- Seven options for moving average types, diversified strategy types
Risk Analysis and Solutions
-
Wrong signals when three MAs are consolidating
Solution: Adjust MA parameters properly to avoid wrong signals
-
Over-aggressive stop-loss/take-profit percentage
Solution: Fine-tune percentages; cannot be too big or too small
-
Improper parameter settings leading to too many or too few trades
Solution: Test different parameter combinations to find optimum
Optimization Directions
The TMA strategy can be optimized from the following aspects:
-
Test different type and length combinations to find optimum
Test different MA length or type combinations for best results
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Add other technical indicators as signal filters
Add indicators like KDJ, MACD etc. for multi-factor verification
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Select parameters based on product characteristics
Shorten MA periods for volatile products; Lengthen periods for steady products
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Utilize machine learning to find optimum parameters
Auto parameter sweeping to quickly locate optimum
Conclusion
The TMA Crossover strategy is an easy-to-use trend following strategy overall. It utilizes three MAs together to capture trends and sets stop-loss/take-profit to control risks, enabling stable profits. Further improvements can be achieved through parameter optimization and integrating extra technical indicators. In conclusion, this strategy suits investors seeking steady gains.
/*backtest
start: 2024-01-08 00:00:00
end: 2024-01-15 00:00:00
period: 5m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=3
strategy("Kozlod - 3 MA strategy with SL/PT", shorttitle="kozlod_3ma", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 5)
//
// author: Kozlod
// date: 2018-03-25
//
////////////
// INPUTS //
////////////
ma_type = input(title = "MA Type", defval = "SMA", options = ['SMA', 'EMA', 'WMA', 'VWMA', 'HMA', 'SMMA', 'DEMA'])
short_ma_len = input(title = "Short MA Length", defval = 5, minval = 1)
short_ma_src = input(title = "Short MA Source", defval = close)
medium_ma_len = input(title = "Medium MA Length", defval = 20, minval = 2)
medium_ma_src = input(title = "Medium MA Source", defval = close)
long_ma_len = input(title = "Long MA Length", defval = 100, minval = 3)
long_ma_src = input(title = "Long MA Source", defval = close)
sl_lev_perc = input(title = "SL Level % (0 - Off)", type = float, defval = 0, minval = 0, step = 0.01)
pt_lev_perc = input(title = "PT Level % (0 - Off)", type = float, defval = 0, minval = 0, step = 0.01)
// Set initial values to 0
short_ma = 0.0
long_ma = 0.0
medium_ma = 0.0
// Simple Moving Average (SMA)
if ma_type == 'SMA'
short_ma := sma(short_ma_src, short_ma_len)
medium_ma := sma(medium_ma_src, medium_ma_len)
long_ma := sma(long_ma_src, long_ma_len)
// Exponential Moving Average (EMA)
if ma_type == 'EMA'
short_ma := ema(short_ma_src, short_ma_len)
medium_ma := ema(medium_ma_src, medium_ma_len)
long_ma := ema(long_ma_src, long_ma_len)
// Weighted Moving Average (WMA)
if ma_type == 'WMA'
short_ma := wma(short_ma_src, short_ma_len)
medium_ma := wma(medium_ma_src, medium_ma_len)
long_ma := wma(long_ma_src, long_ma_len)
// Hull Moving Average (HMA)
if ma_type == 'HMA'
short_ma := wma(2*wma(short_ma_src, short_ma_len / 2) - wma(short_ma_src, short_ma_len), round(sqrt(short_ma_len)))
medium_ma := wma(2*wma(medium_ma_src, medium_ma_len / 2) - wma(medium_ma_src, medium_ma_len), round(sqrt(medium_ma_len)))
long_ma := wma(2*wma(long_ma_src, long_ma_len / 2) - wma(long_ma_src, long_ma_len), round(sqrt(long_ma_len)))
// Volume-weighted Moving Average (VWMA)
if ma_type == 'VWMA'
short_ma := vwma(short_ma_src, short_ma_len)
medium_ma := vwma(medium_ma_src, medium_ma_len)
long_ma := vwma(long_ma_src, long_ma_len)
// Smoothed Moving Average (SMMA)
if ma_type == 'SMMA'
short_ma := na(short_ma[1]) ? sma(short_ma_src, short_ma_len) : (short_ma[1] * (short_ma_len - 1) + short_ma_src) / short_ma_len
medium_ma := na(medium_ma[1]) ? sma(medium_ma_src, medium_ma_len) : (medium_ma[1] * (medium_ma_len - 1) + medium_ma_src) / medium_ma_len
long_ma := na(long_ma[1]) ? sma(long_ma_src, long_ma_len) : (long_ma[1] * (long_ma_len - 1) + long_ma_src) / long_ma_len
// Double Exponential Moving Average (DEMA)
if ma_type == 'DEMA'
e1_short = ema(short_ma_src , short_ma_len)
e1_medium = ema(medium_ma_src, medium_ma_len)
e1_long = ema(long_ma_src, long_ma_len)
short_ma := 2 * e1_short - ema(e1_short, short_ma_len)
medium_ma := 2 * e1_medium - ema(e1_medium, medium_ma_len)
long_ma := 2 * e1_long - ema(e1_long, long_ma_len)
/////////////
// SIGNALS //
/////////////
long_signal = crossover( short_ma, medium_ma) and medium_ma > long_ma
short_signal = crossunder(short_ma, medium_ma) and medium_ma < long_ma
// Calculate PT/SL levels
// Initial values
last_signal = 0
prev_tr_price = 0.0
pt_level = 0.0
sl_level = 0.0
// Calculate previous trade price
prev_tr_price := (long_signal[1] and nz(last_signal[2]) != 1) or (short_signal[1] and nz(last_signal[2]) != -1) ? open : nz(last_signal[1]) != 0 ? prev_tr_price[1] : na
// Calculate SL/PT levels
pt_level := nz(last_signal[1]) == 1 ? prev_tr_price * (1 + pt_lev_perc / 100) : nz(last_signal[1]) == -1 ? prev_tr_price * (1 - pt_lev_perc / 100) : na
sl_level := nz(last_signal[1]) == 1 ? prev_tr_price * (1 - sl_lev_perc / 100) : nz(last_signal[1]) == -1 ? prev_tr_price * (1 + sl_lev_perc / 100) : na
// Calculate if price hit sl/pt
long_hit_pt = pt_lev_perc > 0 and nz(last_signal[1]) == 1 and close >= pt_level
long_hit_sl = sl_lev_perc > 0 and nz(last_signal[1]) == 1 and close <= sl_level
short_hit_pt = pt_lev_perc > 0 and nz(last_signal[1]) == -1 and close <= pt_level
short_hit_sl = sl_lev_perc > 0 and nz(last_signal[1]) == -1 and close >= sl_level
// What is last active trade?
last_signal := long_signal ? 1 : short_signal ? -1 : long_hit_pt or long_hit_sl or short_hit_pt or short_hit_sl ? 0 : nz(last_signal[1])
//////////////
// PLOTTING //
//////////////
// Plot MAs
plot(short_ma, color = red, linewidth = 2)
plot(medium_ma, color = green, linewidth = 2)
plot(long_ma, color = yellow, linewidth = 2)
// Plot Levels
plotshape(prev_tr_price, style = shape.cross, color = gray, location = location.absolute, size = size.small)
plotshape(sl_lev_perc > 0 ? sl_level : na, style = shape.cross, color = red, location = location.absolute, size = size.small)
plotshape(pt_lev_perc > 0 ? pt_level : na, style = shape.cross, color = green, location = location.absolute, size = size.small)
//////////////
// STRATEGY //
//////////////
strategy.entry("long", true, when = long_signal)
strategy.entry("short", false, when = short_signal)
strategy.close("long", when = long_hit_pt or long_hit_sl)
strategy.close("short", when = short_hit_pt or short_hit_sl)
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