Philakone 55 EMA and MA Swing Trading by ZekisPhilakone 55 EMA and MA Swing Trading by Zekis
A swing strategy based on 4 EMAs (8, 13, 21 and 55) developed by Philakone with a nice succes rate on +2h charts
I tried to make it more friendly for the eye and easier to use
What i added:
***the ability to change from EMA to MA
***arrows for a better view for entries/longs and exits/shorts
***colors to determine the trend/entries and exits/longs and shorts
***targets (%) for take profit and Stop Loss (all marked with dots)
***alerts for all of above
Enter long when color between fastest line and slowest line turns green or when green arrow shows up
Enter short when color between fastest line and slowest line turns red or when red arrow shows up
Enjoy!
@ Zekis
在脚本中搜索"swing trading"
Scalping Swing Trading Tool R1-4 by JustUncleLDescription:
This study project is a "Scalping Swing trading Tool" and is an alternative to the "Scalping Pullback Tool R1". It is designed for a two pane TradingView chart layout :
the first pane set to 15min Time Frame;
the second pane set to 1min Time Frame(TF).
The tools incorporates the majority of the indicators needed to analyse and scalp Trends for Swings, PullBacks and reversals on 15min charts and 1min charts.
Incorporated within this tool are the following indicators:
1. The following EMAs are drawn automatically:
Green = EMA89 (15min TF) = EMA75 (1min TF)
Blue = EMA200 (15min TF) = EMA180 (1min TF)
Black = EMA633 (15min TF) = EMA540 (1min TF)
2. The 10EMA (default) High/Low+Close Price Action Channel (PAC), the PAC channel
display is disabled by default.
3. Optionally display Fractals and optional Fractal levels
4. Optional HH, LH, LL, HL finder.
5. Coloured coded Bar high lighting based on the PAC:
blue = bar closed above PAC
red = bar closed below PAC
gray = bar closed inside PAC
lime Line = EMA10 of bar close
6. Pivot points (disables Fractals automatically when selected) with optional labels.
7. EMA5-12 Channel is displayed by default.
8. EMA12-36 Ribbon is displayed by default
9. Optionally display EMA36 and PAC instead of EMA12-36 Ribbon.
Set up and hints:
I am unable to provide a full description here, as Pullback Trading incorporates a full trading Methodology, there are a number of articles and books written on the subject.
Set to two pane TradingView chart, set first pane to 15Min and second to 1min.
Set the chart to Heikin Ashi Candles (optional).
I also add a "Sweetspot Gold2" indicator to the chart as well to help with support and resistance finding and shows where the important "00" lines are.
Use the EMA200 on the 15min pane as the anchor. So when prices above EMA200 we only trade long (buy) and when prices below the EMA200 we only trade short (sell).
On the 15min chart draw any obvious Vertical Trend Lines (VTL), use Pivots point as a guide.
On the 15min chart what we’re looking for price to Pullback into the EMA5-12 Channel or EMA12-36 ribbon, we draw Trendlines uitilising the Pivot points or Fractals to guide your TL drawing.
On the 15min chart look for the trend to resume and break through the drawn TL. The bar color needs to change back to the trend direction colour to confirm as a break.
Now this break can be traded as a 15min trade or now look to the 1min chart.
On the 1min chart draw any Pullback into any of the EMAs.
On the 1min chart look for the trend to resume and break through the drawn TL. The bar color needs to change back to the trend direction colour to confirm as a break.
Now this break can be traded as a 1min trade.
There is also an option to select Pristine (ie Ideal) filtered Fractals, which look like tents or V shape 5-candle patterns. These are actually used to calculate the Pivot points as well.
Other than the "SweetSpot Gold2" indicator, you should not need any other indicator to successfully trade trends for Pullbacks and reversals. If you really want another indicator use the AO (Awesome Oscillator) as it is momentum based.
Trend identifier with signals - Swing TradingIndicator Objective
The "Trend identifier with signals - Swing Trading" indicator is designed to help traders identify market trends and provide clear visual signals for potential buy and sell points based on the interaction of price with the 20-period moving average.
How the Indicator Works
20-Period Moving Average:
The indicator calculates the 20-period simple moving average (SMA), which is a common tool for smoothing out price fluctuations and identifying the overall market direction.
The moving average is plotted on the chart, changing color according to the identified trend:
Green: Indicates an uptrend.
Red: Indicates a downtrend.
Gray: Indicates a neutral or undefined market condition.
Trend Identification on the Daily Chart:
The indicator checks the trend based on an adjustable period (default is 5 periods):
Uptrend: When the short-term moving average (5 periods) is above the long-term moving average (10 periods).
Downtrend: When the short-term moving average (5 periods) is below the long-term moving average (10 periods).
Signal for Touching the Moving Average:
When the price crosses the 20-period moving average, the candles are colored purple to indicate that there was a touch on the moving average.
This helps identify critical points where the price may reverse or continue its trend.
Trend Signal:
Green Flag: Appears below the candle when there is a touch on the moving average and the trend is up, suggesting a potential buy point.
Red Flag: Appears above the candle when there is a touch on the moving average and the trend is down, suggesting a potential sell point.
Lateral Zone Identification:
The indicator also checks if the price touched the moving average for 5 consecutive candles, indicating a possible consolidation or lateral zone.
If this occurs, a message "Possible Lateral Zone" is shown on the chart, helping the trader avoid trades in a market without a clear direction.
How the Indicator Helps Traders
Clear Trend Identification:
By changing the color of the moving average according to the trend (green for up, red for down), the indicator provides a clear visualization of market direction.
This allows traders to align their trades with the prevailing trend, increasing the probability of success.
Visual Buy and Sell Signals:
The green and red flags provide direct visual signals for potential entry and exit points, based on the interaction of price with the moving average.
This is particularly useful for novice traders who may struggle to identify these points on their own.
Risk Management and Trade Planning:
Identifying lateral zones helps traders avoid trading in trendless markets, where price movements are more unpredictable.
This improves risk management and allows traders to focus on more favorable opportunities.
[blackcat] L3 Swing Trading ZonesLevel 3
Background
For swing trading, I consider a combination of multiple technical indicators to indicate periods of long and short positions.
Function
First, judge the daily-level long and short recommendations by the J value of the KDJ indicator in the weekly cycle. in addition. Second, draw bull-bear lines by integrating existing technical indicators such as rsi, adx, cci, dmi, etc. The bull line is above 0, the bear line is below 0, and the other is offsetting each other. When both are relatively close to the zero axis, it means that the strength is equal, and there will be signs of sideways.
Remarks
"D" timeframe ONLY.
Feedbacks are appreciated.
Beakdoo swing trading boxHi forks,
I'm trader Baekdoosan who trading Equity from South Korea. This Baekdoo swing trading box indicate good buying position when it crossover the box.
Here's the ideas
1. It needs to crossover 1 month highest value and higher than 5 ema and 20 ema line
2. It also needs to crossover 1 month volume as well
3. Once 1,2 soaring candle emerge, it needs to correction time
4. 5 ema or 20 ema or center candle's 2/3 point x 0.95 (5% lower) would be the resistant line
5. center candle's 2/3 point line would be the buying point (you may can trade when it cross over
you can check above example chart and take a look what you have interested in.
hope this will help your trading on equity as well as crypto. I didn't try it on futures . Best of luck all of you. Gazua~!
SIB AIO Swing TradingINTRODUCTION:
All-In-One Swing Trading signals are based on the change actions in the Price, Volume & Indicators (RSI, Stochastic, EMA, SMA).
-The Bottom signal is the result of the oscillator oversold zone computation.
-Conversely, the Top signal is the result of the oscillator overbought zone computation.
-The Bull/Bear Divider feature to determine the bullish and bearish market is plotted with the mid-term Exponential Moving Average.
-The chart background-color ease the user to identify immediate market trends on the change-action of the Simple Moving Average.
-The entries & exit signals are based on the Price and Volume action (Gained candle).
HOW TO ENTER:
-Look for Green-background area (Uptrend) &
-Candle price closed "ABOVE" Redline( Bull/Bear Divider) &
-*ENTRY signals appeared (Refer below signals explanation) &
-Enter when price breaks above the signaled candle (Gained candle).
HOW TO EXIT:
-*EXIT signals appeared (Refer to the below signals explanation) &
-Watch out on Red-dot or Blue-dot (Overbought) &
-Exit when price breaks below the signaled candle or
-Candle price closed "BELOW" the Redline (Bull/Bear Divider)
ENTRY Signals:
*Redline (Bull/Bear Divider) price closed "ABOVE" = Bullish.
*Green upward triangle = Potential bottom signal.
*Yellow diamond + BT = Potential bottom reversal signal.
*White candle = Turning point signal.
*White diamond = Strong buying momentum signal.
*White upward triangle = U-turn after correction signal.
*White dot = Potential entry point signal.
*Blue dot (below candle) = Potential entry point signal.
*Green dot 2 (below candle) = Potential entry point signal.
*Yellow candle + alert bell = Rally take-off signal.
*Green color background = indication of an UPTREND market.
EXIT Signals:
*Redline (Bull/Bear Divider) price closed "BELOW" = Bearish .
*Red dot (above candle) = Potential Top signal.
*Blue dot (above candle) = Potential Top signal.
*Blue candle = Weak market, rapid dropping, or panic selling.
*Red color background = indication of a DOWNTREND market.
Note:
Works best with the Heat Volume indicator: SIB Fuel moves Car, Volume moves Price.
Please contact or PM us to gain access.
Auto S/R With Swing TradingIn this indicator, you can simply get the automatic support and resistance line.
With this indication of High and Low by H and L with blue line support and resistance.
The second part is the swing trading setup.
Green line means the upside continue with BUY signal.
Yellow Line means a Trend reversal No Trading Zone & wait for the signal.
Red line indicates that the downside continues with the SELL signal.
EMA Cross - Swing Trading on the Daily (by Leb Crypto)This indicator is best used on the Daily Chart.
It's simple yet powerful.
All it does is indicate where the 8 EMA crosses over or under the 21 EMA, indicating a potential LONG or SHORT position opportunity.
You can back test this on many charts, and find that it has a pretty decent success rate.
Obviously, it is NOT to be used on its own. It's best combined with other technical analysis skills.
Nevertheless, it is helpful in Swing Trading on the Daily chart.
Long/Buy when the green circle appears.
Short/Sell when the red circle appears.
Enjoy it.
Cheers,
Leb Crypto
55 EMA Swing TradingA simple Buy and sell strategy using 55 EMA - " 55 EMA Swing Trading"
The source code is publicly available to for further modification.
Swing Trading Tool Provides Swing history and forecastSwing Forecast detects significant pivot swings and averages recent leg behavior to forecast the next swing Low/High in real time. Choose chart TF or a higher TF, set Lookback Legs and Min Move, and see a clean zig-zag of swings (with optional live tail), forecast lines on the latest bar, and a compact table showing Average start of up/down legs, Average leg sizes, forecasts, and a Trend row (EMA-based) that highlights whether the next likely move is toward a High or a Low (also shown as a label on the last candle). Includes alerts for price crossing the forecast next High/Low so you don’t miss inflection points. Designed for discretionary swing traders to gauge context and timing—not financial advice; always confirm with your own risk management and confluence.
BloodSwing Indicator-SWING TRADING STRATEGY FOR PASSIVE TRADERS-
A Multi-timeframe Strategy
This swing trading strategy uses three moving averages pegged to the 4H timeframe, to enter and exit the market on the 1H timeframe.
The 200 EMA (4H timeframe) is used to identify areas of support. If this moving average shows signs of support (shown as green circles under candles), the 18 and 22 moving average (4hour timeframe) crossover is used to enter the market, but on the 1 hour chart (for more accuracy) and only after an increase in volume on the 1 hour timeframe has been detected.
Manually this strategy is explained as follows:
1. Look for candle support on 200 MA (4H Timeframe)
2. On the 1H chart, look for the crossover of 18 and 22 ma (4H Timeframe)
3. As soon as you see volume increase on 1H, enter.
4. Exit on cross under of 18 and 22 ma (4H Timeframe)
5. Stop Loss below 200EMA support candle low.
Signals:
- Support signals are shown as green circles under the candles
- Long, Close, Stop signals are shown as labels and can be toggled on and off.
Extras (In option menu):
MA Deviation:
A standard deviation measure used on the 200 EMA in order to provide some range for support signals to be considered valid.
Use volume expansion for entry:
As an option (on by default), you can disable volume increase as a condition for entry.
Ichimoku Trading Signals 1Swing Trading (Strategy 1, H4+ timeframes)
Use the Kumo Cloud to identify the trend: price above a green cloud = uptrend; price below a red cloud = downtrend.
Entry signals occur when price or the Tenkan-sen line crosses the Kijun-sen line, confirmed by Chikou Span momentum.
Exit triggers when price crosses back through the Kijun-sen or when Tenkan-sen crosses back below (for long positions) or above (for short positions).
Place stop-loss orders just beyond the nearest swing low/high candle cluster to manage risk tightly.
Ichimoku Trading Signals 2Swing Trading (Strategy 1, H4+ timeframes)
Use the Kumo Cloud to identify the trend: price above a green cloud = uptrend; price below a red cloud = downtrend.
Entry signals occur when price or the Tenkan-sen line crosses the Kijun-sen line, confirmed by Chikou Span momentum.
Exit triggers when price crosses back through the Kijun-sen or when Tenkan-sen crosses back below (for long positions) or above (for short positions).
Place stop-loss orders just beyond the nearest swing low/high candle cluster to manage risk tightly.
SWING TRADER V4 swing trading script (on test)
Long = buy signal
Short = sell signal
simple buy/sell script confirmed on bar close
Use ema's for the stoploss once price goes above or below these ema's
alerts available
SWING TRADER PRO V4 swing trading script currently scalper available
Long = buy signal
Short = sell signal
Use ema's for the stoploss once price goes above or below these ema's
best use on 1 hour
orange bar color indicates overbought
lime bar color indicates oversold
you can also add alerts for signals
Swinging Karate Monkey Death CrossingSwing trading method extrapolated to 1h chart for margin trading, due to liq prices being too short to be use on 1d chart, been tested on btc margin trading, but should work for other markets/pairs
instruccions are very simple
if green line crosses over red line, go long
if green line crosses under red line, go short
try to open as close as posible to the crossing (if too far away from price/time, wait for next crossing), exit at the next crossing
Kalman Filter [DCAUT]█ Kalman Filter
📊 ORIGINALITY & INNOVATION
The Kalman Filter represents an important adaptation of aerospace signal processing technology to financial market analysis. Originally developed by Rudolf E. Kalman in 1960 for navigation and guidance systems, this implementation brings the algorithm's noise reduction capabilities to price trend analysis.
This implementation addresses a common challenge in technical analysis: the trade-off between smoothness and responsiveness. Traditional moving averages must choose between being smooth (with increased lag) or responsive (with increased noise). The Kalman Filter improves upon this limitation through its recursive estimation approach, which continuously balances historical trend information with current price data based on configurable noise parameters.
The key advancement lies in the algorithm's adaptive weighting mechanism. Rather than applying fixed weights to historical data like conventional moving averages, the Kalman Filter dynamically adjusts its trust between the predicted trend and observed prices. This allows it to provide smoother signals during stable periods while maintaining responsiveness during genuine trend changes, helping to reduce whipsaws in ranging markets while not missing significant price movements.
📐 MATHEMATICAL FOUNDATION
The Kalman Filter operates through a two-phase recursive process:
Prediction Phase:
The algorithm first predicts the next state based on the previous estimate:
State Prediction: Estimates the next value based on current trend
Error Covariance Prediction: Calculates uncertainty in the prediction
Update Phase:
Then updates the prediction based on new price observations:
Kalman Gain Calculation: Determines the weight given to new measurements
State Update: Combines prediction with observation based on calculated gain
Error Covariance Update: Adjusts uncertainty estimate for next iteration
Core Parameters:
Process Noise (Q): Represents uncertainty in the trend model itself. Higher values indicate the trend can change more rapidly, making the filter more responsive to price changes.
Measurement Noise (R): Represents uncertainty in price observations. Higher values indicate less trust in individual price points, resulting in smoother output.
Kalman Gain Formula:
The Kalman Gain determines how much weight to give new observations versus predictions:
K = P(k|k-1) / (P(k|k-1) + R)
Where:
K is the Kalman Gain (0 to 1)
P(k|k-1) is the predicted error covariance
R is the measurement noise parameter
When K approaches 1, the filter trusts new measurements more (responsive).
When K approaches 0, the filter trusts its prediction more (smooth).
This dynamic adjustment mechanism allows the filter to adapt to changing market conditions automatically, providing an advantage over fixed-weight moving averages.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Visual Trend Indication:
The Kalman Filter line provides color-coded trend information:
Green Line: Indicates the filter value is rising, suggesting upward price momentum
Red Line: Indicates the filter value is falling, suggesting downward price momentum
Gray Line: Indicates sideways movement with no clear directional bias
Crossover Signals:
Price-filter crossovers generate trading signals:
Golden Cross: Price crosses above the Kalman Filter line, suggests potential bullish momentum development, may indicate a favorable environment for long positions, filter will naturally turn green as it adapts to price moving higher
Death Cross: Price crosses below the Kalman Filter line, suggests potential bearish momentum development, may indicate consideration for position reduction or shorts, filter will naturally turn red as it adapts to price moving lower
Trend Confirmation:
The filter serves as a dynamic trend baseline:
Price Consistently Above Filter: Confirms established uptrend
Price Consistently Below Filter: Confirms established downtrend
Frequent Crossovers: Suggests ranging or choppy market conditions
Signal Reliability Factors:
Signal quality varies based on market conditions:
Higher reliability in trending markets with sustained directional moves
Lower reliability in choppy, range-bound conditions with frequent reversals
Parameter adjustment can help adapt to different market volatility levels
🎯 STRATEGIC APPLICATIONS
Trend Following Strategy:
Use the Kalman Filter as a dynamic trend baseline:
Enter long positions when price crosses above the filter
Enter short positions when price crosses below the filter
Exit when price crosses back through the filter in the opposite direction
Monitor filter slope (color) for trend strength confirmation
Dynamic Support/Resistance:
The filter can act as a moving support or resistance level:
In uptrends: Filter often provides dynamic support for pullbacks
In downtrends: Filter often provides dynamic resistance for bounces
Price rejections from the filter can offer entry opportunities in trend direction
Filter breaches may signal potential trend reversals
Multi-Timeframe Analysis:
Combine Kalman Filters across different timeframes:
Higher timeframe filter identifies primary trend direction
Lower timeframe filter provides precise entry and exit timing
Trade only in direction of higher timeframe trend for better probability
Use lower timeframe crossovers for position entry/exit within major trend
Volatility-Adjusted Configuration:
Adapt parameters to match market conditions:
Low Volatility Markets (Forex majors, stable stocks): Use lower process noise for stability, use lower measurement noise for sensitivity
Medium Volatility Markets (Most equities): Process noise default (0.05) provides balanced performance, measurement noise default (1.0) for general-purpose filtering
High Volatility Markets (Cryptocurrencies, volatile stocks): Use higher process noise for responsiveness, use higher measurement noise for noise reduction
Risk Management Integration:
Use filter as a trailing stop-loss level in trending markets
Tighten stops when price moves significantly away from filter (overextension)
Wider stops in early trend formation when filter is just establishing direction
Consider position sizing based on distance between price and filter
📋 DETAILED PARAMETER CONFIGURATION
Source Selection:
Determines which price data feeds the algorithm:
OHLC4 (default): Uses average of open, high, low, close for balanced representation
Close: Focuses purely on closing prices for end-of-period analysis
HL2: Uses midpoint of high and low for range-based analysis
HLC3: Typical price, gives more weight to closing price
HLCC4: Weighted close price, emphasizes closing values
Process Noise (Q) - Adaptation Speed Control:
This parameter controls how quickly the filter adapts to changes:
Technical Meaning:
Represents uncertainty in the underlying trend model
Higher values allow the estimated trend to change more rapidly
Lower values assume the trend is more stable and slow-changing
Practical Impact:
Lower Values: Produces very smooth output with minimal noise, slower to respond to genuine trend changes, best for long-term trend identification, reduces false signals in choppy markets
Medium Values: Balanced responsiveness and smoothness, suitable for swing trading applications, default (0.05) works well for most markets
Higher Values: More responsive to price changes, may produce more false signals in ranging markets, better for short-term trading and day trading, captures trend changes earlier, adjust freely based on market characteristics
Measurement Noise (R) - Smoothing Control:
This parameter controls how much the filter trusts individual price observations:
Technical Meaning:
Represents uncertainty in price measurements
Higher values indicate less trust in individual price points
Lower values make each price observation more influential
Practical Impact:
Lower Values: More reactive to each price change, less smoothing with more noise in output, may produce choppy signals
Medium Values: Balanced smoothing and responsiveness, default (1.0) provides general-purpose filtering
Higher Values: Heavy smoothing for very noisy markets, reduces whipsaws significantly but increases lag in trend change detection, best for cryptocurrency and highly volatile assets, can use larger values for extreme smoothing
Parameter Interaction:
The ratio between Process Noise and Measurement Noise determines overall behavior:
High Q / Low R: Very responsive, minimal smoothing
Low Q / High R: Very smooth, maximum lag reduction
Balanced Q and R: Middle ground for most applications
Optimization Guidelines:
Start with default values (Q=0.05, R=1.0)
If too many false signals: Increase R or decrease Q
If missing trend changes: Decrease R or increase Q
Test across different market conditions before live use
Consider different settings for different timeframes
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Comparison with Traditional Moving Averages:
Versus Simple Moving Average (SMA):
The Kalman Filter typically responds faster to genuine trend changes
Produces smoother output than SMA of comparable length
Better noise reduction in ranging markets
More configurable for different market conditions
Versus Exponential Moving Average (EMA):
Similar responsiveness but with better noise filtering
Less prone to whipsaws in choppy conditions
More adaptable through dual parameter control (Q and R)
Can be tuned to match or exceed EMA responsiveness while maintaining smoothness
Versus Hull Moving Average (HMA):
Different noise reduction approach (recursive estimation vs. weighted calculation)
Kalman Filter offers more intuitive parameter adjustment
Both reduce lag effectively, but through different mechanisms
Kalman Filter may handle sudden volatility changes more gracefully
Response Characteristics:
Lag Time: Moderate and configurable through parameter adjustment
Noise Reduction: Good to excellent, particularly in volatile conditions
Trend Detection: Effective across multiple timeframes
False Signal Rate: Typically lower than simple moving averages in ranging markets
Computational Efficiency: Efficient recursive calculation suitable for real-time use
Optimal Use Cases:
Markets with mixed trending and ranging periods
Assets with moderate to high volatility requiring noise filtering
Multi-timeframe analysis requiring consistent methodology
Systematic trading strategies needing reliable trend identification
Situations requiring balance between responsiveness and smoothness
Known Limitations:
Parameters require adjustment for different market volatility levels
May still produce false signals during extreme choppy conditions
No single parameter set works optimally for all market conditions
Requires complementary indicators for comprehensive analysis
Historical performance characteristics may not persist in changing market conditions
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. The Kalman Filter's effectiveness varies with market conditions, tending to perform better in markets with clear trending phases interrupted by consolidation. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions, but rather as part of a comprehensive trading approach.
Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always test thoroughly with different parameter settings across various market conditions before using in live trading. No technical indicator can predict future price movements with certainty, and all trading involves risk of loss.
