BO - Bar M15 2/3 SignalBO - Bar M15 2/3 Signal show the signal to trade Binary Option with rule below:
A. Indicator
* Bollinger Band (20,2): avoid waterfall
B. Rule of Signal
1. Rule1: Split Bar M15 to 3 part and load them on M5 chart (recommend use M5 IDC chart)
2. Rule 2: Delay 10' after bar M15 open => wait for price's pattern
3. Rule 3: Put Signal row 30-32
* Delay 10' after bar M15 open.
* Direction of 1/3 and 2/3 Bar M15 is upward
* close of 2/3 Bar M15 below upper band Bb(20,2) on M5 chart => avoid strong buy
4. Rule 4: Call Signal row 36-38
* Delay 10' after bar M15 open.
* Direction of 1/3 and 2/3 Bar M15 is downward
* close of 2/3 Bar M15 above lower band Bb(20,2) on M5 chart => avoid strong sell
C. Recommend Expiry time: Bar M15 close
* We try to catch the shadow of Bar M15 but dont trade when price run on the upper or lower band of BB(20,2,M5)
Komut dosyalarını "20蒙古币兑换人民币" için ara
Average Candle Length 2.0This script will tell you the following:
• Average length of all the candles (wick to wick) for the last 20 candles
-- shown in blue
• Average length of bull (green) candles (wick to wick) for the last 20 candles
-- shown in green
• Average length of bear (red) candles (wick to wick) for the last 20 candles
-- shown in red
___________________________________________
Inputs:
• # of Candles to analyze (default = 20)
Pivot trend indicatorThis is a LAGGING indicator which can provide a good indication of trend. It require a certain (configurable) number of candles to have closed before it can determine whether a pivot has formed.
It provides a 20 period SMA for the timeframe of your choice which is color coded to show the trend according to confirmed pivots.
Anticipated usage:
Long / Short bias is determined by pivot trend
Trader seeks entries according to their strategy
Black consolidation areas may trigger a re-evaluation of the trade and can serve as good profit taking areas
The SMA colors:
Green -> Higher highs & Higher lows
Red -> Lower highs & Lowers lows
Black -> No clear trend from the pivots
Why the 20 SMA?
Feel free to adjust it for your purposes. I personally find that using a higher time frame 20 SMA is a better indication of trend than longer period MAs on shorter time frames. This can be seen from comparing the 20 daily SMA and 200 hourly SMA.
Pivot adjustment
The pivots use the selected time frame (not) the MA trend time frame. You can specify the left and right candles required to confirm a pivot
VIX reversion-Buschi
English:
A significant intraday reversion (commonly used: 3 points) on a high (over 20 points) S&P 500 Volatility Index (VIX) can be a sign of a market bottom, because there is the assumption that some of the "big guys" liquidated their options / insurances because the worst is over.
This indicator shows these reversions (3 points as default) when the VIX was over 20 points. The character "R" is then shown directly over the daily column, the VIX need not to be loaded explicitly.
Deutsch:
Eine deutliche Intraday-Umkehr (3 Punkte im Normalfall) bei einem hohen (über 20 Punkte) S&P 500 Volatility Index (VIX) kann ein Zeichen für eine Bodenbildung im Markt sein, weil möglicherweise einige "große Jungs" ihre Optionen / Versicherungen auflösen, weil das schlimmste vorbei ist.
Dieser Indikator zeigt diese Umkehr (Standardwert: 3 Punkte), wenn der VIX vorher über 20 Punkte lag. Der Buchstabe "R" wird dabei direkt über dem Tagesbalken angezeigt, wobei der VIX nicht explizit geladen werden muss.
Triple Moving Average HeatmapHi everyone
I didn't publish on Friday because I was working on an Expert Advisor in MT4. The day I don't publish, some scripts spamming guys published many (not useful) scripts the same to kick me out of the TOP #1 ranking.
So what I'm going to do about it? crying or sharing more quality scripts than before? :)
I guess you know the answer :) I'm gonna share a few quality scripts that I have in my library. I noticed that you guys tend to like more the scripts useful for your trading actually making you money rather than a copy-paste (of another copy-paste)
Alright, enough for the trolling now let's introduce the Three MA heatmap which is an upgrade of that script : MA-heatmap-Double-cross-edition/
The challenge was to keep the heatmap not rolling and to make it match with the MA cross. I did it using this
```
since_ma_buy = barssince(macrossover)
since_ma_sell = barssince(macrossunder)
heatmap_color() =>
since_ma_buy < since_ma_sell ? color.new(color.green, 20) : since_ma_buy > since_ma_sell ? color.new(color.red, 20) : na
```
This is a technique that I found after drinking three glasses of red wine (#french) to keep the heatmap stable and not rolling.
To get what I'm saying I invite you to replace the piece of code above by what everyone would normally do
```
heatmap_color() =>
macrossunder() ? color.new(color.green, 20) : macrossover() ? color.new(color.red, 20) : na
```
Ah and I'm not done sharing for the day, a few scripts are coming also after that one and tonight !!!!! I want to live in a world where you guys can enjoy quality scripts (mostly) :)
PS
____________________________________________________________
Feel free to hit the thumbs up as it shows me that I'm not doing this for nothing and will motivate to deliver more quality content in the future.
- I'm an officially approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
Palex 2.0Atualização do SETUP do saudoso Professor Alexandre Fernandes "Palex"
- Bandas de Bolliger (Standard) =
*Banda Superior = Média Móvel Simples (20 dias) + (2 x Desvio Padrão de 20 dias)
*Banda Inferior = Média Móvel Simples (20 dias) – (2 x Desvio Padrão de 20 dias)
- EMA 9 (Média Móvel Exponencial)
- SMA 21 (Média Móvel Simples)
- SMA 200 (Média Móvel Simples) Clássica MA 200 períodos
- SMA 400 (Média Móvel Simples)
- EMA 400 (Média Móvel Exponencial)
- WILD (Média Móvel Welles Wilder)
O mesmo usado pelo nosso grande Mestre PALEX!
The 6 Line Death PunchIf you are looking to discover what trend you are in, you need to first what direction the price is going in...
I've been using and testing a mixture of EMA's and SMA's for a long time and I've found that these ones are by far the best.
EMA 3
EMA 8
MA 20
EMA 55
MA 100
MA 200
EMA 3 & 8 Crossover is a good method for confirming a coin going to the upside or to the downside.
EMA 8 is known as the Trigger Line (trademarked brand) as one of the fib numbers it shows good support or resistance of a trend.
MA 20 universal way of seeing trend direction in the stock market, works well with crypto too.
EMA 55, another trusty fib number. Works very well and could trade off that alone as support and resistance.
MA 100 and MA 200. Long ranged moving averages which govern the overall longer-term trend.
LONG ENTRY
Option 1 - 3/8 crossover
Option 2 - Candles above EMA 8
Option 3 - Candles above MA 20
Option 4 - Candles Above EMA 55.
SHORT ENTRY
Option 1 - 3/8 crossover
Option 2 - Candles below EMA 8
Option 3 - Candles below MA 20
Option 4 - Candles below EMA 55.
Signals for call and putSorry for the Google Translate English
Indicator for signals of call and put, using Bollinger bands (period 20, standard deviation 2.5), market trend of (sma, períod 100) and stochastic (period 20, %D 3).
I was overthrown but in pine scrip, the function "stoch()" no way to smooth (3). If anyone knows how to smooth inside the script, help me! Please.
With smoothed stochastic the hit rate grows a lot.
Português (Pt-Br)
Indicador de sinais de compra e venda, usando bandas de Bollinger (período de 20, desvio de 2,5), tendencia de mercado com (sma período 100) e estocástico (período 20, %D de 3).
Eu travei porque no pine script, a função "stoch()" não tem como aplicar a suavização (3). Se alguem souber como suavizar dentro do script, me ajude! Por favor.
MG - Multiple Moving Averages & Candle Wick Alerts - 1.0Features:
- Each moving average has customizable length, type and source
- The ability to change the source of all moving averages with one input (changing an individual MA source will override the general for that MA)
- At a glance comparison of 20 SMA and 20 VWMA to gauge volume trend
- Wick alerts which can be toggled for each moving average.
- Bullish wick alerts are when the wick is the only part of the candle to drop below the moving average
- Bearish wick alerts are when the wick is the only part of the candle to reach above the moving average
- Simple candle closed alert if you want a notification, for example each hour.
Defaults: Four SMAs (20, 50, 100, 200) and a 20 VWMA .
Recommended Usage:
- Set the general source (sets the source of all moving averages) to 'low' when in an uptrend and 'high' in a downtrend to maximize Risk : Reward.
- Use Fibonacci levels, oscillators .etc for confluence
NOTE: The moving average component of this indicator is the same as the previous indicator ()
Indicator - Multiple Moving Averages 1.0Features:
- Each moving average has customizable length, type and source
- The ability to change the source of all moving averages with one input (changing an individual MA source will override the general for that MA)
- At a glance comparison of 20 SMA and 20 VWMA to gauge volume trend
Defaults: Four SMAs (20, 50, 100, 200) and a 20 VWMA.
Usage:
- Use Fibonacci levels, pivots .etc for confluence
- Personally, I like to set overall source to low in uptrends, to high in downtrends and then set alerts for when the price crosses any of the averages. Then pay particular attention to the candlesticks and other indicators.
TODO:
- Add alerts option so that it send alert on crossing up or down any alert lines.
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy
Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength.
My sell strategy is triggered by either one of these conditions:
the EMA(6) of the close value is crossing under the trailing stop value (green) or
the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength.
The trailing stop value (green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between the high and low values.
The scripts shows a lot of graphical information:
The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade.
the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end))
the EMA and SMA values for both buy and sell signals are shown as a line
the buy and sell(close) signals are labeled in blue
How to use this strategy?
Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR).
Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters)
Then keep using these parameters for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Important : optimizing these parameters is no guarantee for future winning trades!
Here are the parameters:
Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20)
Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100)
Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120)
Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20)
Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100)
Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120)
Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20)
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing):
BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20
NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78%
BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9
NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55%
AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8
NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938%
TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14
NetProfit: 129%, #Trade
EMA Indicators with BUY sell SignalCombine 3 EMA indicators into 1. Buy and Sell signal is based on
- Buy signal based on 20 Days Highest High resistance
- Sell signal based on 10 Days Lowest Low support
Input :-
1 - Short EMA (20), Mid EMA (50) and Long EMA (200)
2 - Resistance (20) = 20 Days Highest High line
3 - Support (10) = 10 Days Lowest Low line
RSI_BB_Combo (mean-reversion) – Entry-OnlyA mean-reversion setup that waits for RSI to reach oversold territory while price simultaneously tags or pierces the lower Bollinger Band, then plays the bounce back toward the 20-period moving average or mid-band. This keeps you positioned for volatility squeezes without fighting the prevailing trend.
Analysis:
Strengths: Captures mean reversion in volatile swings, reliable oversold bounces
Best Timeframe: 1 h
Recommendation: Well-balanced—ideal for swing traders
London Breakout PRO – By Maa Sharda Trading📈 London Breakout PRO (MAA SHARDA TRADING) – Indicator Description for TradingView
Introducing: London Breakout PRO – The Advanced Breakout Tool for Gold & Forex!
Unlock the real power of London session trading with this next-generation indicator.
Specially designed for serious traders, this tool combines classic London Breakout logic with EMA Trend Confirmation and an optional Volume Filter to eliminate fake breakouts and boost your accuracy.
How It Works:
Session Box: Automatically marks the first session candle (default: 1H for London Open).
Breakout Signal: Gives only one clean BUY/SELL signal each day – only when the candle breaks out above/below the session box.
Trend Filter: Signals fire only when price is above (BUY) or below (SELL) the EMA 20, ensuring you always trade with the trend.
Volume Confirmation: (Optional) Signals only if breakout happens with volume higher than the last 10 candles’ average, so you avoid low-liquidity fakeouts.
Ultra-Clean Chart: No repainting, no clutter, just pure breakout action.
Key Features:
✅ Works on any timeframe (M15, M30, H1 best for Gold/XAUUSD & FX)
✅ Fully customizable session start time and box duration
✅ One breakout signal per day – no overtrading, no noise
✅ Trend & volume filters for high-probability setups
✅ Easy visual backtesting – perfect for serious traders and strategy builders
Recommended Settings for GOLD (XAUUSD):
Timeframe: 1 Hour (H1) – best accuracy & lowest noise
Session Start (IST): 11:30 AM (London Open)
Box Length: 1 Candle (1 Hour)
EMA Length: 20
Volume Filter: On (for strong confirmations)
How To Use:
Wait for London session box to form at your set time.
Trade only when price closes above (BUY) or below (SELL) the box and EMA 20 & volume filters are satisfied.
Place SL at the opposite side of the box. Target 1:1 or let profits run with trailing stop.
Avoid trading during high-impact news events for even better results.
Pro Tip:
Backtest on H1 and combine with major support/resistance for the highest win-rate. Use with proper risk management for best results!
Disclaimer:
Trading involves risk. This indicator is for educational purposes only. Test thoroughly before live trading.
#LondonBreakout #XAUUSD #BreakoutStrategy #EMAConfirmation #VolumeFilter #TradingView #ForexIndicator #IntradayTrading
Ease of Movement Z-Score Trend | DextraGeneral Description:
The "Ease of Movement Z-Score Trend | Dextra" (EOM-Z Trend) is an innovative technical analysis tool that combines the Ease of Movement (EOM) concept with Z-Score to measure how easily price moves relative to volume, while identifying market trends with intuitive visualization. This indicator is designed to help traders detect uptrend and downtrend phases with precision, enhanced by candle coloring for direct trend representation on the chart.
Key Features
Ease of Movement (EOM): Measures how easily price moves based on the change in the midpoint price and volume, normalized with Z-Score for statistical analysis.
Z-Score Normalization: Provides an indication of deviations from the mean, enabling the identification of overbought or oversold conditions.
Adjustable Thresholds: Users can customize upper and lower thresholds to define trend boundaries.
Candle Coloring: Visual trend representation with green (uptrend), red (downtrend), and gray (neutral) candles.
Flexibility: Adjustable for different timeframes and assets.
How It Works
The indicator operates through the following steps:
EOM Calculation:
hl2 = (high + low) / 2: Calculates the average midpoint price per bar.
eom = ta.sma(10000 * ta.change(hl2) * (high - low) / volume, length): EOM is computed as the smoothed average of the price midpoint change multiplied by the price range per unit volume, scaled by 10,000, over length bars (default 20).
Z-Score Calculation:
mean_eom = ta.sma(eom, z_length): Average EOM over z_length bars (default 93).
std_dev_eom = ta.stdev(eom, z_length): Standard deviation of EOM.
z_score = (eom - mean_eom) / std_dev_eom: Z-Score indicating how far EOM deviates from its mean in standard deviation units.
Trend Detection:
upperthreshold (default 1.03) and lowerthreshold (default -1.63): Thresholds to classify uptrend (if Z-Score > upperthreshold) and downtrend (if Z-Score < lowerthreshold).
eom_is_up and eom_is_down: Logical variables for trend status.
Visualization:
plot(z_score, ...): Z-Score line plotted with green (uptrend), red (downtrend), or gray (neutral) coloring.
plotcandle(...): Candles colored green, red, or gray based on trend.
hline(...): Dashed lines marking the thresholds.
Input Settings
EOM Length (default 20): Period for calculating EOM, determining sensitivity to price changes.
Z-Score Lookback Period (default 93): Period for calculating the Z-Score mean and standard deviation.
Uptrend Threshold (default 1.03): Minimum Z-Score value to classify an uptrend.
Downtrend Threshold (default -1.93): Maximum Z-Score value to classify a downtrend.
How to Use
Installation: Add the indicator via the "Indicators" menu in TradingView and search for "EOM-Z Trend | Dextra".
Customization:
Adjust EOM Length and Z-Score Lookback Period based on the timeframe (e.g., 20 and 93 for daily timeframes).
Set Uptrend Threshold and Downtrend Threshold according to preference or asset characteristics (e.g., lower to 0.8 and -1.5 for volatile markets).
Interpretation:
Uptrend (Green): Z-Score above upperthreshold, indicating strong upward price movement.
Downtrend (Red): Z-Score below lowerthreshold, indicating significant downward movement.
Neutral (Gray): Conditions between thresholds, suggesting a sideways market.
Use candle coloring as the primary visual guide, combined with the Z-Score line for confirmation.
Advantages
Intuitive Visualization: Candle coloring simplifies trend identification without deep analysis.
Flexibility: Customizable parameters allow adaptation to various markets.
Statistical Analysis: Z-Score provides a robust perspective on price deviations from the norm.
No Repainting: The indicator uses historical data and does not alter values after a bar closes.
Limitations
Volume Dependency: Requires accurate volume data; an error occurs if volume is unavailable.
Market Context: Effectiveness depends on properly tuned thresholds for specific assets.
Lack of Additional Signals: No built-in alerts or supplementary confirmation indicators.
Recommendations
Ideal Timeframe: Daily (1D) or (2D) for stable trends.
Combination: Pair with others indicators for signal validation.
Optimization: Test thresholds on historical data of the traded asset for optimal results.
Important Notes
This indicator relies entirely on internal TradingView data (high, low, close, volume) and does not integrate on-chain data. Ensure your data provider supports volume to avoid errors. This version (1.0) is the initial release, with potential future updates including features like alerts or multi-timeframe analysis.
SMA Crossover Strategy📈 Indicator: SMA Crossover Strategy
This strategy uses optimized fast and slow SMA values tailored to popular timeframes for more responsive trend detection. You can let the script auto-select values or manually define your own crossover settings. Clean visual cues and per-candle signal filtering keep your chart sharp and actionable.
🔧 Key Features:
- Auto Mode: Smart defaults for each timeframe with trader-tested pairs
- Manual Mode: User-defined flexibility when custom values are needed
- Signal Clarity: BUY/SELL labels are plotted only once per confirmed candle
🧠 Default Auto Values (Based on Chart Timeframe)
- 1-min: Fast = 5, Slow = 20
- 5-min: Fast = 5, Slow = 10
- 15-min: Fast = 5, Slow = 13
- 30-min: Fast = 15, Slow = 30
- 1-hr: Fast = 50, Slow = 200
- 4-hr: Fast = 20, Slow = 50
- Daily: Fast = 50, Slow = 200
- Weekly: Fast = 10, Slow = 30
If your timeframe isn't matched exactly, the script falls back to sensible defaults.
📊 How to Improve Conviction
SMA crossovers are strong signals when confirmed by other tools. Here are some add-ons you can layer into your chart:
🔍 Confirmation Indicators
- RSI (14): Look for crossovers near RSI crossing 50 or at oversold/overbought zones for momentum confirmation.
- MACD: Use histogram alignment with crossover signals to detect real trend shifts.
- Volume Filters: Pair signals with rising volume for institutional confirmation.
🌀 Trend & Volatility Filters
- ATR (Average True Range): Helps filter signals during consolidation—watch for expanding ATR as a volatility cue.
- ADX: Trade only when ADX > 20 to avoid false signals in ranging markets.
- HMA (Hull MA): A smoother, faster MA that can act as a trend bias overlay.
🔭 Multi-Timeframe Awareness
Overlay higher-timeframe trend indicators (like a daily 200 SMA on an intraday chart) to avoid trading against macro momentum.
DT-FNO Screener//@version=5
indicator("DT-FNO Screener", overlay=true)
// === INPUTS ===
lengthEMA1 = 20
lengthEMA2 = 50
lengthEMA3 = 200
lengthEMA4 = 10
rsiLength = 14
// === PRICE DATA ===
closePrice = close
highPrev = high
lowPrev = low
openToday = open
closeToday = close
// === EMA CALCULATIONS ===
ema20D = ta.ema(close, 20)
ema50D = ta.ema(close, 50)
ema200D = ta.ema(close, 200)
ema10D = ta.ema(close, 10)
ema20W = ta.ema(request.security(syminfo.tickerid, "W", close), 20)
ema50W = ta.ema(request.security(syminfo.tickerid, "W", close), 50)
// === RSI ===
rsiVal = ta.rsi(close, rsiLength)
// === % CHANGE STATS ===
percentChange = 100 * (close - close ) / close
min7Change = ta.lowest(percentChange, 7)
max5Change = ta.highest(percentChange, 5)
// === CONDITIONS (from screener) ===
// Futures Segment
cond1 = ema20W < ema50W
cond2 = ema20D < ema50D
cond3 = ema50D < ema200D
cond4 = close > ema20D
// Cash Segment
cond5 = closeToday < highPrev
cond6 = closeToday > lowPrev
cond7 = openToday > lowPrev
cond8 = openToday < highPrev
cond9 = ((ema10D - close) / close) <= 0.02
cond10 = rsiVal <= 60
// % Change Conditions
cond11 = min7Change <= -1.5
cond12 = max5Change <= 1.2
// === FINAL COMBINED CONDITION ===
all_conditions = cond1 and cond2 and cond3 and cond4 and cond5 and cond6 and cond7 and cond8 and cond9 and cond10 and cond11 and cond12
// === PLOT SIGNAL ===
bgcolor(all_conditions ? color.new(color.green, 80) : na)
plotshape(all_conditions, title="DT-FNO Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="DT")
Ultra BUY SELL//@version=5
indicator("Ultra BUY SELL", overlay = false)
// Inputs
src = input(close, "Source", group = "Main settings")
p = input.int(180, "Trend period", group = "Main settings", tooltip = "Changes STRONG signals' sensitivity.", minval = 1)
atr_p = input.int(155, "ATR Period", group = "Main settings", minval = 1)
mult = input.float(2.1, "ATR Multiplier", step = 0.1, group = "Main settings", tooltip = "Changes sensitivity: higher period = higher sensitivty.")
mode = input.string("Type A", "Signal mode", options = , group = "Mode")
use_ema_smoother = input.string("No", "Smooth source with EMA?", options = , group = "Source")
src_ema_period = input(3, "EMA Smoother period", group = "Source")
color_bars = input(true, "Color bars?", group = "Addons")
signals_view = input.string("All", "Signals to show", options = , group = "Signal's Addon")
signals_shape = input.string("Labels", "Signal's shape", options = , group = "Signal's Addon")
buy_col = input(color.rgb(0, 255, 8), "Buy colour", group = "Signal's Addon", inline = "BS")
sell_col = input(color.rgb(255, 0, 0), "Sell colour", group = "Signal's Addon", inline = "BS")
// Calculations
src := use_ema_smoother == "Yes" ? ta.ema(src, src_ema_period) : src
// Source;
h = ta.highest(src, p)
// Highest of src p-bars back;
l = ta.lowest(src, p)
// Lowest of src p-bars back.
d = h - l
ls = ""
// Tracker of last signal
m = (h + l) / 2
// Initial trend line;
m := bar_index > p ? m : m
atr = ta.atr(atr_p)
// ATR;
epsilon = mult * atr
// Epsilon is a mathematical variable used in many different theorems in order to simplify work with mathematical object. Here it used as sensitivity measure.
change_up = (mode == "Type B" ? ta.cross(src, m + epsilon) : ta.crossover(src, m + epsilon)) or src > m + epsilon
// If price breaks trend line + epsilon (so called higher band), then it is time to update the value of a trend line;
change_down = (mode == "Type B" ? ta.cross(src, m - epsilon) : ta.crossunder(src, m - epsilon)) or src < m - epsilon
// If price breaks trend line - epsilon (so called higher band), then it is time to update the value of a trend line.
sb = open < l + d / 8 and open >= l
ss = open > h - d / 8 and open <= h
strong_buy = sb or sb or sb or sb or sb
strong_sell = ss or ss or ss or ss or ss
m := (change_up or change_down) and m != m ? m : change_up ? m + epsilon : change_down ? m - epsilon : nz(m , m)
// Updating the trend line.
ls := change_up ? "B" : change_down ? "S" : ls
// Last signal. Helps avoid multiple labels in a row with the same signal;
colour = ls == "B" ? buy_col : sell_col
// Colour of the trend line.
buy_shape = signals_shape == "Labels" ? shape.labelup : shape.triangleup
sell_shape = signals_shape == "Labels" ? shape.labeldown : shape.triangledown
// Plottings
// Signals with label shape
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Buy/Sell") and change_up and ls != "B" and not strong_buy, "Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.normal, text = "BUY", textcolor = color.white, force_overlay=true)
// Plotting the BUY signal;
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Buy/Sell") and change_down and ls != "S" and not strong_sell, "Sell signal" , color = colour, style = sell_shape, size = size.normal, text = "SELL", textcolor = color.white, force_overlay=true)
// Plotting the SELL signal.
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Strong") and change_up and ls != "B" and strong_buy, "Strong Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.normal, text = "STRONG", textcolor = color.white, force_overlay=true)
// Plotting the STRONG BUY signal;
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Strong") and change_down and ls != "S" and strong_sell, "Strong Sell signal" , color = colour, style = sell_shape, size = size.normal, text = "STRONG", textcolor = color.white, force_overlay=true)
// Plotting the STRONG SELL signal.
// Signal with arrow shape
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Buy/Sell") and change_up and ls != "B" and not strong_buy, "Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.tiny, force_overlay=true)
// Plotting the BUY signal;
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Buy/Sell") and change_down and ls != "S" and not strong_sell, "Sell signal" , color = colour, style = sell_shape, size = size.tiny, force_overlay=true)
// Plotting the SELL signal.
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Strong") and change_up and ls != "B" and strong_buy, "Strong Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.tiny, force_overlay=true)
// Plotting the STRONG BUY signal;
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Strong") and change_down and ls != "S" and strong_sell, "Strong Sell signal" , color = colour, style = sell_shape, size = size.tiny, force_overlay=true)
// Plotting the STRONG SELL signal.
barcolor(color_bars ? colour : na)
// Bar coloring
// Alerts
matype = input.string(title='MA Type', defval='EMA', options= )
ma_len1 = input(title='Short EMA1 Length', defval=5)
ma_len2 = input(title='Long EMA1 Length', defval=7)
ma_len3 = input(title='Short EMA2 Length', defval=5)
ma_len4 = input(title='Long EMA2 Length', defval=34)
ma_len5 = input(title='Short EMA3 Length', defval=98)
ma_len6 = input(title='Long EMA3 Length', defval=45)
ma_len7 = input(title='Short EMA4 Length', defval=7)
ma_len8 = input(title='Long EMA4 Length', defval=11)
ma_len9 = input(title='Short EMA5 Length', defval=11)
ma_len10 = input(title='Long EMA5 Length', defval=15)
ma_offset = input(title='Offset', defval=0)
//res = input(title="Resolution", type=resolution, defval="240")
f_ma(malen) =>
float result = 0
if matype == 'EMA'
result := ta.ema(src, malen)
result
if matype == 'SMA'
result := ta.sma(src, malen)
result
result
htf_ma1 = f_ma(ma_len1)
htf_ma2 = f_ma(ma_len2)
htf_ma3 = f_ma(ma_len3)
htf_ma4 = f_ma(ma_len4)
htf_ma5 = f_ma(ma_len5)
htf_ma6 = f_ma(ma_len6)
htf_ma7 = f_ma(ma_len7)
htf_ma8 = f_ma(ma_len8)
htf_ma9 = f_ma(ma_len9)
htf_ma10 = f_ma(ma_len10)
//plot(out1, color=green, offset=ma_offset)
//plot(out2, color=red, offset=ma_offset)
//lengthshort = input(8, minval = 1, title = "Short EMA Length")
//lengthlong = input(200, minval = 2, title = "Long EMA Length")
//emacloudleading = input(50, minval = 0, title = "Leading Period For EMA Cloud")
//src = input(hl2, title = "Source")
showlong = input(false, title='Show Long Alerts')
showshort = input(false, title='Show Short Alerts')
showLine = input(false, title='Display EMA Line')
ema1 = input(true, title='Show EMA Cloud-1')
ema2 = input(true, title='Show EMA Cloud-2')
ema3 = input(true, title='Show EMA Cloud-3')
ema4 = input(true, title='Show EMA Cloud-4')
ema5 = input(true, title='Show EMA Cloud-5')
emacloudleading = input.int(0, minval=0, title='Leading Period For EMA Cloud')
mashort1 = htf_ma1
malong1 = htf_ma2
mashort2 = htf_ma3
malong2 = htf_ma4
mashort3 = htf_ma5
malong3 = htf_ma6
mashort4 = htf_ma7
malong4 = htf_ma8
mashort5 = htf_ma9
malong5 = htf_ma10
cloudcolour1 = mashort1 >= malong1 ? color.rgb(0, 255, 0) : color.rgb(255, 0, 0)
cloudcolour2 = mashort2 >= malong2 ? #4caf4f47 : #ff110047
cloudcolour4 = mashort4 >= malong4 ? #4caf4f52 : #f2364652
cloudcolour5 = mashort5 >= malong5 ? #33ff0026 : #ff000026
//03abc1
mashortcolor1 = mashort1 >= mashort1 ? color.olive : color.maroon
mashortcolor2 = mashort2 >= mashort2 ? color.olive : color.maroon
mashortcolor3 = mashort3 >= mashort3 ? color.olive : color.maroon
mashortcolor4 = mashort4 >= mashort4 ? color.olive : color.maroon
mashortcolor5 = mashort5 >= mashort5 ? color.olive : color.maroon
mashortline1 = plot(ema1 ? mashort1 : na, color=showLine ? mashortcolor1 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA1', force_overlay=true)
mashortline2 = plot(ema2 ? mashort2 : na, color=showLine ? mashortcolor2 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA2', force_overlay=true)
mashortline3 = plot(ema3 ? mashort3 : na, color=showLine ? mashortcolor3 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA3', force_overlay=true)
mashortline4 = plot(ema4 ? mashort4 : na, color=showLine ? mashortcolor4 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA4', force_overlay=true)
mashortline5 = plot(ema5 ? mashort5 : na, color=showLine ? mashortcolor5 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA5', force_overlay=true)
malongcolor1 = malong1 >= malong1 ? color.green : color.red
malongcolor2 = malong2 >= malong2 ? color.green : color.red
malongcolor3 = malong3 >= malong3 ? color.green : color.red
malongcolor4 = malong4 >= malong4 ? color.green : color.red
malongcolor5 = malong5 >= malong5 ? color.green : color.red
malongline1 = plot(ema1 ? malong1 : na, color=showLine ? malongcolor1 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA1', force_overlay=true)
malongline2 = plot(ema2 ? malong2 : na, color=showLine ? malongcolor2 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA2', force_overlay=true)
malongline3 = plot(ema3 ? malong3 : na, color=showLine ? malongcolor3 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA3', force_overlay=true)
malongline4 = plot(ema4 ? malong4 : na, color=showLine ? malongcolor4 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA4', force_overlay=true)
malongline5 = plot(ema5 ? malong5 : na, color=showLine ? malongcolor5 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA5', force_overlay=true)
fill(mashortline1, malongline1, color=cloudcolour1, title='MA Cloud1', transp=45)
fill(mashortline2, malongline2, color=cloudcolour2, title='MA Cloud2', transp=65)
fill(mashortline4, malongline4, color=cloudcolour4, title='MA Cloud4', transp=65)
fill(mashortline5, malongline5, color=cloudcolour5, title='MA Cloud5', transp=65)
leftBars = input(15, title='Left Bars ')
rightBars = input(15, title='Right Bars')
volumeThresh = input(20, title='Volume Threshold')
//
highUsePivot = fixnan(ta.pivothigh(leftBars, rightBars) )
lowUsePivot = fixnan(ta.pivotlow(leftBars, rightBars) )
r1 = plot(highUsePivot, color=ta.change(highUsePivot) ? na : #FF0000, linewidth=3, offset=-(rightBars + 1), title='Resistance', force_overlay=true)
s1 = plot(lowUsePivot, color=ta.change(lowUsePivot) ? na : #00ff0d, linewidth=3, offset=-(rightBars + 1), title='Support', force_overlay=true)
//Volume %
short = ta.ema(volume, 5)
long = ta.ema(volume, 10)
osc = 100 * (short - long) / long
//For bull / bear wicks
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © divudivu600
// Developer By ALCON ALGO
//telegram : @harmonicryptosignals
//@version = 5
//indicator(shorttitle='Oscillator Vision', title='Alcon Oscillator Vision', overlay=false)
n1 = input(10, 'Channel length')
n2 = input(21, 'Average length')
reaction_wt = input.int(defval=1, title='Reaction in change of direction', minval=1)
nsc = input.float(53, 'Levels About Buys', minval=0.0)
nsv = input.float(-53, 'Levels About Sells', maxval=-0.0)
Buy_sales = input(true, title='Only Smart Buy Reversal')
Sell_sales = input(true, title='Only Smart Sell Reversal')
Histogram = input(true, title='Show Histogarm')
//Trendx = input(false, title='Show Trendx')
barras = input(true, title='Divergence on chart(Bars)')
divregbull = input(true, title='Regular Divergence Bullish')
divregbear = input(true, title='Regular Divergence Bearish')
divhidbull = input(true, title='Show Divergence Hidden Bullish')
divhidbear = input(true, title='Show Divergence Hidden Bearish')
Tags = input(true, title='Show Divergence Lable')
amme = input(false, title='Activar media movil Extra para WT')
White = #FDFEFE
Black = #000000
Bearish = #e91e62
Bullish = #18e0ff
Strong_Bullish = #2962ff
Bullish2 = #00bedc
Blue1 = #00D4FF
Blue2 = #009BBA
orange = #FF8B00
yellow = #FFFB00
LEZ = #0066FF
purp = #FF33CC
// Colouring
tf(_res, _exp, gaps_on) =>
gaps_on == 0 ? request.security(syminfo.tickerid, _res, _exp) : gaps_on == true ? request.security(syminfo.tickerid, _res, _exp, barmerge.gaps_on, barmerge.lookahead_off) : request.security(syminfo.tickerid, _res, _exp, barmerge.gaps_off, barmerge.lookahead_off)
ha_htf = ''
show_ha = input.bool(true, "Show HA Plot/ Market Bias", group="HA Market Bias")
ha_len = input(7, 'Period', group="HA Market Bias")
ha_len2 = input(10, 'Smoothing', group="HA Market Bias")
// Calculations {
o = ta.ema(open, ha_len)
c = ta.ema(close, ha_len)
h1 = ta.ema(high, ha_len)
l1 = ta.ema(low, ha_len)
haclose = tf(ha_htf, (o + h1 + l1 + c) / 4, 0)
xhaopen = tf(ha_htf, (o + c) / 2, 0)
haopen = na(xhaopen ) ? (o + c) / 2 : (xhaopen + haclose ) / 2
hahigh = math.max(h1, math.max(haopen, haclose))
halow = math.min(l1, math.min(haopen, haclose))
o2 = tf(ha_htf, ta.ema(haopen, ha_len2), 0)
c2 = tf(ha_htf, ta.ema(haclose, ha_len2), 0)
h2 = tf(ha_htf, ta.ema(hahigh, ha_len2), 0)
l2 = tf(ha_htf, ta.ema(halow, ha_len2), 0)
ha_avg = (h2 + l2) / 2
// }
osc_len = 8
osc_bias = 100 *(c2 - o2)
osc_smooth = ta.ema(osc_bias, osc_len)
sigcolor =
(osc_bias > 0) and (osc_bias >= osc_smooth) ? color.new(Bullish, 35) :
(osc_bias > 0) and (osc_bias < osc_smooth) ? color.new(Bullish2, 75) :
(osc_bias < 0) and (osc_bias <= osc_smooth) ? color.new(Bearish, 35) :
(osc_bias < 0) and (osc_bias > osc_smooth) ? color.new(Bearish, 75) :
na
// }
nsc1 = nsc
nsc2 = nsc + 5
nsc3 = nsc + 10
nsc4 = nsc + 15
nsc5 = nsc + 20
nsc6 = nsc + 25
nsc7 = nsc + 30
nsc8 = nsc + 35
nsv1 = nsv - 5
nsv2 = nsv - 10
nsv3 = nsv - 15
nsv4 = nsv - 20
nsv5 = nsv - 25
nsv6 = nsv - 30
nsv7 = nsv - 35
nsv8 = nsv - 40
ap = hlc3
esa = ta.ema(ap, n1)
di = ta.ema(math.abs(ap - esa), n1)
ci = (ap - esa) / (0.015 * di)
tci = ta.ema(ci, n2)
wt1 = tci
wt2 = ta.sma(wt1, 4)
direction = 0
direction := ta.rising(wt1, reaction_wt) ? 1 : ta.falling(wt1, reaction_wt) ? -1 : nz(direction )
Change_of_direction = ta.change(direction, 1)
pcol = direction > 0 ? Strong_Bullish : direction < 0 ? Bearish : na
obLevel1 = input(60, 'Over Bought Level 1')
obLevel2 = input(53, 'Over Bought Level 2')
osLevel1 = input(-60, 'Over Sold Level 1')
osLevel2 = input(-53, 'Over Sold Level 2')
rsi = ta.rsi(close,14)
color greengrad = color.from_gradient(rsi, 10, 90, #00ddff, #007d91)
color redgrad = color.from_gradient(rsi, 10, 90, #8b002e, #e91e62)
ob1 = plot(obLevel1, color=#e91e6301)
os1 = plot(osLevel1, color=#00dbff01)
ob2 = plot(obLevel2, color=#e91e6301)
os2 = plot(osLevel2, color=#00dbff01)
p1 = plot(wt1, color=#00dbff01)
p2 = plot(wt2, color=#e91e6301)
plot(wt1 - wt2, color=wt2 - wt1 > 0 ? redgrad : greengrad, style=plot.style_columns)
// fill(p1,p2,color = wt2 - wt1 > 0 ? redgrad: greengrad) // old
fill(p1,p2,color = sigcolor)
// new
fill(ob1,ob2,color = #e91e6350)
fill(os1,os2,color = #00dbff50)
midpoint = (nsc + nsv) / 2
ploff = (nsc - midpoint) / 8
BullSale = ta.crossunder(wt1, wt2) and wt1 >= nsc and Buy_sales == true
BearSale = ta.crossunder(wt1, wt2) and Buy_sales == false
Bullishh = ta.crossover(wt1, wt2) and wt1 <= nsv and Sell_sales == true
Bearishh = ta.crossover(wt1, wt2) and Sell_sales == false
plot(BullSale ? wt2 + ploff : na, style=plot.style_circles, color=color.new(Bearish, 0), linewidth=6, title='BuysG')
plot(BearSale ? wt2 + ploff : na, style=plot.style_circles, color=color.new(Bearish, 0), linewidth=6, title='SellsG')
plot(Bullishh ? wt2 - ploff : na, style=plot.style_circles, color=color.new(Strong_Bullish, 0), linewidth=6, title='Buys On Sale')
plot(Bearishh ? wt2 - ploff : na, style=plot.style_circles, color=color.new(Strong_Bullish, 0), linewidth=6, title='Sells on Sale')
//plot(Histogram ? wt1 - wt2 : na, style=plot.style_area, color=color.new(Blue2, 80), linewidth=1, title='Histograma')
//barcolor(barras == true and Bullishh == true or barras == true and Bearishh == true ? Bullish2 : na)
//barcolor(barras == true and BullSale == true or barras == true and BearSale == true ? Bearish : na)
/////// Divergence ///////
f_top_fractal(_src) =>
_src < _src and _src < _src and _src > _src and _src > _src
f_bot_fractal(_src) =>
_src > _src and _src > _src and _src < _src and _src < _src
f_fractalize(_src) =>
f_top_fractal(_src) ? 1 : f_bot_fractal(_src) ? -1 : 0
fractal_top1 = f_fractalize(wt1) > 0 ? wt1 : na
fractal_bot1 = f_fractalize(wt1) < 0 ? wt1 : na
high_prev1 = ta.valuewhen(fractal_top1, wt1 , 0)
high_price1 = ta.valuewhen(fractal_top1, high , 0)
low_prev1 = ta.valuewhen(fractal_bot1, wt1 , 0)
low_price1 = ta.valuewhen(fractal_bot1, low , 0)
regular_bearish_div1 = fractal_top1 and high > high_price1 and wt1 < high_prev1 and divregbear == true
hidden_bearish_div1 = fractal_top1 and high < high_price1 and wt1 > high_prev1 and divhidbear == true
regular_bullish_div1 = fractal_bot1 and low < low_price1 and wt1 > low_prev1 and divregbull == true
hidden_bullish_div1 = fractal_bot1 and low > low_price1 and wt1 < low_prev1 and divhidbull == true
col1 = regular_bearish_div1 ? Bearish : hidden_bearish_div1 ? Bearish : na
col2 = regular_bullish_div1 ? Strong_Bullish : hidden_bullish_div1 ? Strong_Bullish : na
//plot(title='Divergence Bearish', series=fractal_top1 ? wt1 : na, color=col1, linewidth=2, transp=0)
//plot(title='Divergence Bullish', series=fractal_bot1 ? wt1 : na, color=col2, linewidth=2, transp=0)
plotshape(regular_bearish_div1 and divregbear and Tags ? wt1 + ploff * 1 : na, title='Divergence Regular Bearish', text='Bear', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(Bearish, 0), textcolor=color.new(White, 0))
plotshape(hidden_bearish_div1 and divhidbear and Tags ? wt1 + ploff * 1 : na, title='Divergence Hidden Bearish', text='H Bear', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(Bearish, 0), textcolor=color.new(White, 0))
plotshape(regular_bullish_div1 and divregbull and Tags ? wt1 - ploff * 1 : na, title='Divergence Regular Bullish', text='Bull', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(Strong_Bullish, 0), textcolor=color.new(White, 0))
plotshape(hidden_bullish_div1 and divhidbull and Tags ? wt1 - ploff * 1 : na, title='Divergence Hidden Bullish', text='H Bull', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(Strong_Bullish, 0), textcolor=color.new(White, 0))
/////// Unfazed Alerts //////
////////////////////////////////////////////////-MISTERMOTA MOMENTUM-/////////////////////////////////////
source = input(close)
responsiveness = math.max(0.00001, input.float(0.9, minval=0.0, maxval=1.0))
periodd = input(50)
sd = ta.stdev(source, 50) * responsiveness
var worm = source
diff = source - worm
delta = math.abs(diff) > sd ? math.sign(diff) * sd : diff
worm += delta
ma = ta.sma(source, periodd)
raw_momentum = (worm - ma) / worm
current_med = raw_momentum
min_med = ta.lowest(current_med, periodd)
max_med = ta.highest(current_med, periodd)
temp = (current_med - min_med) / (max_med - min_med)
value = 0.5 * 2
value *= (temp - .5 + .5 * nz(value ))
value := value > .9999 ? .9999 : value
value := value < -0.9999 ? -0.9999 : value
temp2 = (1 + value) / (1 - value)
momentum = .25 * math.log(temp2)
momentum += .5 * nz(momentum )
//momentum := raw_momentum
signal = nz(momentum )
trend = math.abs(momentum) <= math.abs(momentum )
////////////////////////////////////////////////-GROWING/FAILING-//////////////////////////////////////////
length = input.int(title="MOM Period", minval=1, defval=14, group="MOM Settings")
srcc = input(title="MOM Source", defval=hlc3, group="MOM Settings")
txtcol_grow_above = input(#1a7b24, "Above Grow", group="MOM Settings", inline="Above")
txtcol_fall_above = input(#672ec5, "Fall", group="MOM Settings", inline="Above")
txtcol_grow_below = input(#F37121, "Below Grow", group="MOM Settings", inline="Below")
txtcol_fall_below = input(#be0606, "Fall", group="MOM Settings", inline="Below")
ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
typeMA = input.string(title = "Method", defval = "SMA", options= , group="MA Settings")
smoothingLength = input.int(title = "Length", defval = 5, minval = 1, maxval = 100, group="MA Settings")
smoothingLine = ma(delta, smoothingLength, typeMA)
deltaText=(delta > 0 ? (delta > delta ? " MOM > 0 and ▲ Growing, MOM = " + str.tostring(delta , "#.##") :" MOM > 0 and ▼ Falling, MOM = " + str.tostring(delta , "#.##") ) : (delta > delta ? "MOM < 0 and ▲ Growing, MOM = " + str.tostring(delta , "#.##"): " MOM < 0 and ▼ Falling, MOM = " + str.tostring(delta , "#.##")))
oneDay = 24 * 60 * 60 * 1000
barsAhead = 3
tmf = if timeframe.ismonthly
barsAhead * oneDay * 30
else if timeframe.isweekly
barsAhead * oneDay * 7
else if timeframe.isdaily
barsAhead * oneDay
else if timeframe.isminutes
barsAhead * oneDay * timeframe.multiplier / 1440
else if timeframe.isseconds
barsAhead * oneDay * timeframe.multiplier / 86400
else
0
angle(_src) =>
rad2degree = 180 / 3.14159265359
//pi
ang = rad2degree * math.atan((_src - _src ) / ta.atr(14))
ang
emae = angle(smoothingLine)
emaanglestat = emae > emae ? "▲ Growing": "▼ Falling"
deltaTextxxx = "MOM MA/ATR angle value is " + str.tostring(emae, "#.##") + "° and is " + emaanglestat
deltacolorxxx = emae >0 and emae >=emae ? txtcol_grow_above : txtcol_fall_below
// Label
label lpt1 = label.new(time, -30, text=deltaTextxxx , color=deltacolorxxx, xloc=xloc.bar_time, style=label.style_label_left, textcolor=color.white, textalign=text.align_left, size=size.normal)
label.set_x(lpt1, label.get_x(lpt1) + tmf)
label.delete(lpt1 )
txtdeltaColors = (delta > 50 ? (delta < delta ? txtcol_grow_above : txtcol_fall_above) : (delta < delta ? txtcol_grow_below : txtcol_fall_below))
label ldelta1 = label.new(time, 30, text=deltaText , color=txtdeltaColors, xloc=xloc.bar_time, style=label.style_label_left, textcolor=color.white, textalign=text.align_left, size=size.normal)
label.set_x(ldelta1, label.get_x(ldelta1) + tmf)
label.delete(ldelta1 )
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
SMA+Volume Buy AlertsOverview
This lightweight indicator combines trend and momentum filters to pinpoint high-conviction, oversold entries on ETFs or stocks. It plots your choice of two SMAs (default 100- & 200-day) and a 20-day volume moving average, then only flags a “BUY” when price crosses below an SMA and daily volume exceeds its average.
Use it to capture institutional-strength reversals without alert noise, and receive a single, clear signal exactly when market participants step in.
Key Features
Dual SMA Trend Lines (100/200-day by default)
Volume Filter (20-day avg): only overshoots on above-average volume signal
One-Shot Buy Markers: triangles appear beneath the precise bar that crosses under your SMA on high volume
Alert Conditions: “Buy 100 SMA + High Vol” and “Buy 200 SMA + High Vol” ready for desktop, mobile, or webhooks
Show/Hide Toggle for your SMA lines
100% Pine v6, optimized for speed and compatibility
Inputs
Short SMA Length (default 100)
Long SMA Length (default 200)
Volume MA Length (default 20)
Show SMA Lines toggle
How to Use
Add to Chart: Copy & paste this script into TradingView’s Pine editor, then Save & Add to Chart.
Configure Inputs: Adjust SMA and volume-MA lengths to your trading style.
Create Alerts:
Open “Create Alert,” select the “SMA-VOL-BUY” indicator.
Choose “Buy 100 SMA + High Vol” or “Buy 200 SMA + High Vol.”
Set trigger to “Once Per Bar Close.”
Trade with Confidence: Only the most significant, high-volume overshoots get flagged—no spam, just high-quality setups.
Best Practices
Frame Alignment: Combine daily signals with a weekly SMA trend filter for multi-timeframe confirmation.
Volume Context: Ensure that “high” volume truly represents above-average activity in your chosen security.
Risk Management: Use the signal bar’s low as your stop, and size positions to match your risk tolerance.
Review & Iterate: Tweak SMA or volume lengths to suit fast-moving sectors (e.g. 50/100 SMAs) or slower large-caps.
Position Size Calculator with Fees# Position Size Calculator with Portfolio Management - Manual
## Overview
The Position Size Calculator with Portfolio Management is an advanced Pine Script indicator designed to help traders calculate optimal position sizes based on their total portfolio value and risk management strategy. This tool automatically calculates your risk amount based on portfolio allocation percentages and determines the exact position size needed while accounting for trading fees.
## Key Features
- **Portfolio-Based Risk Management**: Calculates risk based on total portfolio value
- **Tiered Risk Allocation**: Separates trading allocation from total portfolio
- **Automatic Trade Direction Detection**: Determines long/short based on entry vs stop loss
- **Fee Integration**: Accounts for trading fees in position size calculations
- **Risk Factor Adjustment**: Allows scaling of position size up or down
- **Visual Display**: Shows all calculations in a clear, color-coded table
- **Automatic Risk Calculation**: No need to manually input risk amount
## Input Parameters
### Total Portfolio ($)
- **Purpose**: The total value of your investment portfolio
- **Default**: 0.0
- **Range**: Any positive value
- **Step**: 0.01
- **Example**: If your total portfolio is worth $100,000, enter 100000
### Trading Portfolio Allocation (%)
- **Purpose**: The percentage of your total portfolio allocated to active trading
- **Default**: 20.0%
- **Range**: 0.0% to 100.0%
- **Step**: 0.01
- **Example**: If you allocate 20% of your portfolio to trading, enter 20
### Risk from Trading (%)
- **Purpose**: The percentage of your trading allocation you're willing to risk per trade
- **Default**: 0.1%
- **Range**: Any positive value
- **Step**: 0.01
- **Example**: If you risk 0.1% of your trading allocation per trade, enter 0.1
### Entry Price ($)
- **Purpose**: The price at which you plan to enter the trade
- **Default**: 0.0
- **Range**: Any positive value
- **Step**: 0.01
### Stop Loss ($)
- **Purpose**: The price at which you will exit if the trade goes against you
- **Default**: 0.0
- **Range**: Any positive value
- **Step**: 0.01
### Risk Factor
- **Purpose**: A multiplier to scale your position size up or down
- **Default**: 1.0 (no scaling)
- **Range**: 0.0 to 10.0
- **Step**: 0.1
- **Examples**:
- 1.0 = Normal position size
- 2.0 = Double the position size
- 0.5 = Half the position size
### Fee (%)
- **Purpose**: The percentage fee charged per transaction
- **Default**: 0.01% (0.01)
- **Range**: 0.0% to 1.0%
- **Step**: 0.001
## How Risk Amount is Calculated
The script automatically calculates your risk amount using this formula:
```
Risk Amount = Total Portfolio × Trading Allocation (%) × Risk % ÷ 10,000
```
### Example Calculation:
- Total Portfolio: $100,000
- Trading Allocation: 20%
- Risk per Trade: 0.1%
**Risk Amount = $100,000 × 20 × 0.1 ÷ 10,000 = $20**
This means you would risk $20 per trade, which is 0.1% of your $20,000 trading allocation.
## Portfolio Structure Example
Let's say you have a $100,000 portfolio:
### Allocation Structure:
- **Total Portfolio**: $100,000
- **Trading Allocation (20%)**: $20,000
- **Long-term Investments (80%)**: $80,000
### Risk Management:
- **Risk per Trade (0.1% of trading)**: $20
- **Maximum trades at risk**: Could theoretically have 1,000 trades before risking entire trading allocation
## How Position Size is Calculated
### Trade Direction Detection
- **Long Trade**: Entry price > Stop loss price
- **Short Trade**: Entry price < Stop loss price
### Position Size Formulas
#### For Long Trades:
```
Position Size = -Risk Factor × Risk Amount / (Stop Loss × (1 - Fee) - Entry Price × (1 + Fee))
```
#### For Short Trades:
```
Position Size = -Risk Factor × Risk Amount / (Entry Price × (1 - Fee) - Stop Loss × (1 + Fee))
```
## Output Display
The indicator displays a comprehensive table with color-coded sections:
### Portfolio Information (Light Blue Background)
- **Portfolio (USD)**: Your total portfolio value
- **Trading Portfolio Allocation (%)**: Percentage allocated to trading
- **Risk as % of Trading**: Risk percentage per trade
### Trade Setup (Gray Background)
- **Entry Price**: Your specified entry price
- **Stop Loss**: Your specified stop loss price
- **Fee (%)**: Trading fee percentage
- **Risk Factor**: Position size multiplier
### Risk Analysis (Red Background)
- **Risk Amount**: Automatically calculated dollar risk
- **Effective Entry**: Actual entry cost including fees
- **Effective Exit**: Actual exit value including fees
- **Expected Loss**: Calculated loss if stop loss is hit
- **Deviation from Risk %**: Accuracy of risk calculation
### Final Result (Blue Background)
- **Position Size**: Number of shares/units to trade
## Usage Examples
### Example 1: Conservative Long Trade
- **Total Portfolio**: $50,000
- **Trading Allocation**: 15%
- **Risk per Trade**: 0.05%
- **Entry Price**: $25.00
- **Stop Loss**: $24.00
- **Risk Factor**: 1.0
- **Fee**: 0.01%
**Calculated Risk Amount**: $50,000 × 15% × 0.05% ÷ 100 = $3.75
### Example 2: Aggressive Short Trade
- **Total Portfolio**: $200,000
- **Trading Allocation**: 30%
- **Risk per Trade**: 0.2%
- **Entry Price**: $150.00
- **Stop Loss**: $155.00
- **Risk Factor**: 2.0
- **Fee**: 0.01%
**Calculated Risk Amount**: $200,000 × 30% × 0.2% ÷ 100 = $120
**Actual Risk**: $120 × 2.0 = $240 (due to risk factor)
## Color Coding System
- **Green/Red Header**: Trade direction (Long/Short)
- **Light Blue**: Portfolio management parameters
- **Gray**: Trade setup parameters
- **Red**: Risk-related calculations and results
- **Blue**: Final position size result
## Best Practices
### Portfolio Management
1. **Keep trading allocation reasonable** (typically 10-30% of total portfolio)
2. **Use conservative risk percentages** (0.05-0.2% per trade)
3. **Don't risk more than you can afford to lose**
### Risk Management
1. **Start with small risk factors** (1.0 or less) until comfortable
2. **Monitor your total exposure** across all open positions
3. **Adjust risk based on market conditions**
### Trade Execution
1. **Always validate calculations** before placing trades
2. **Account for slippage** in volatile markets
3. **Consider position size relative to liquidity**
## Risk Management Guidelines
### Conservative Approach
- Trading Allocation: 10-20%
- Risk per Trade: 0.05-0.1%
- Risk Factor: 0.5-1.0
### Moderate Approach
- Trading Allocation: 20-30%
- Risk per Trade: 0.1-0.15%
- Risk Factor: 1.0-1.5
### Aggressive Approach
- Trading Allocation: 30-40%
- Risk per Trade: 0.15-0.25%
- Risk Factor: 1.5-2.0
## Troubleshooting
### Common Issues
1. **Position Size shows 0**
- Verify all portfolio inputs are greater than 0
- Check that entry price differs from stop loss
- Ensure calculated risk amount is positive
2. **Very small position sizes**
- Increase risk percentage or risk factor
- Check if your risk amount is too small for the price difference
3. **Large risk deviation**
- Normal for very small positions
- Consider adjusting entry/stop loss levels
### Validation Checklist
- Total portfolio value is realistic
- Trading allocation percentage makes sense
- Risk percentage is conservative
- Entry and stop loss prices are valid
- Trade direction matches your intention
## Advanced Features
### Risk Factor Usage
- **Scaling up**: Use risk factors > 1.0 for high-confidence trades
- **Scaling down**: Use risk factors < 1.0 for uncertain trades
- **Never exceed**: Risk factors that would risk more than your comfort level
### Multiple Timeframe Analysis
- Use different risk factors for different timeframes
- Consider correlation between positions
- Adjust trading allocation based on market conditions
## Disclaimer
This tool is for educational and planning purposes only. Always verify calculations manually and consider market conditions, liquidity, and correlation between positions. The automated risk calculation assumes you're comfortable with the mathematical relationship between portfolio allocation and individual trade risk. Past performance doesn't guarantee future results, and all trading involves risk of loss.
Chaikin Money Flow (CMF) [ParadoxAlgo]OVERVIEW
This indicator implements the Chaikin Money Flow oscillator as an overlay on the price chart, designed to help traders identify institutional money flow patterns. The Chaikin Money Flow combines price and volume data to measure the flow of money into and out of a security, making it particularly useful for detecting accumulation and distribution phases.
WHAT IS CHAIKIN MONEY FLOW?
Chaikin Money Flow was developed by Marc Chaikin and measures the amount of Money Flow Volume over a specific period. The indicator oscillates between +1 and -1, where:
Positive values indicate money flowing into the security (accumulation)
Negative values indicate money flowing out of the security (distribution)
Values near zero suggest equilibrium between buying and selling pressure
CALCULATION METHOD
Money Flow Multiplier = ((Close - Low) - (High - Close)) / (High - Low)
Money Flow Volume = Money Flow Multiplier × Volume
CMF = Sum of Money Flow Volume over N periods / Sum of Volume over N periods
KEY FEATURES
Big Money Detection:
Identifies significant institutional activity when CMF exceeds user-defined thresholds
Requires volume confirmation (volume above average) to validate signals
Uses battery icon (🔋) for institutional buying and lightning icon (⚡) for institutional selling
Visual Elements:
Background coloring based on money flow direction
Support and resistance levels calculated using Average True Range
Real-time dashboard showing current CMF value, volume strength, and signal status
Customizable Parameters:
CMF Period: Calculation period for the money flow (default: 20)
Signal Smoothing: EMA smoothing applied to reduce noise (default: 5)
Big Money Threshold: CMF level required to trigger institutional signals (default: 0.15)
Volume Threshold: Volume multiplier required for signal confirmation (default: 1.5x)
INTERPRETATION
Signal Types:
🔋 (Battery): Indicates strong institutional buying when CMF > threshold with high volume
⚡ (Lightning): Indicates strong institutional selling when CMF < -threshold with high volume
Background color: Green tint for positive money flow, red tint for negative money flow
Dashboard Information:
CMF Value: Current Chaikin Money Flow reading
Volume: Current volume as a multiple of 20-period average
Big Money: Status of institutional activity (BUYING/SELLING/QUIET)
Signal: Strength assessment (STRONG/MEDIUM/WEAK)
TRADING APPLICATIONS
Trend Confirmation: Use CMF direction to confirm price trends
Divergence Analysis: Look for divergences between price and money flow
Volume Validation: Confirm breakouts with corresponding money flow
Accumulation/Distribution: Identify phases of institutional activity
PARAMETER RECOMMENDATIONS
Day Trading: CMF Period 14-21, higher sensitivity settings
Swing Trading: CMF Period 20-30, moderate sensitivity
Position Trading: CMF Period 30-50, lower sensitivity for major trends
ALERTS
Optional alert system notifies users when:
Big money buying is detected (CMF above threshold with volume confirmation)
Big money selling is detected (CMF below negative threshold with volume confirmation)
LIMITATIONS
May generate false signals in low-volume conditions
Best used in conjunction with other technical analysis tools
Effectiveness varies across different market conditions and timeframes
EDUCATIONAL PURPOSE
This open-source indicator is provided for educational purposes to help traders understand money flow analysis. It demonstrates the practical application of the Chaikin Money Flow concept with visual enhancements for easier interpretation.
TECHNICAL SPECIFICATIONS
Overlay indicator (displays on price chart)
No repainting - all calculations are based on closed bar data
Suitable for all timeframes and asset classes
Minimal resource usage for optimal performance
DISCLAIMER
This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and consider risk management before making trading decisions.
Custom EMA High/Low & SMA - [GSK-VIZAG-AP-INDIA] Custom EMA High/Low & SMA -
1. Overview
This indicator overlays a dynamic combination of Exponential Moving Averages (EMA) and Simple Moving Average (SMA) to identify momentum shifts and potential entry/exit zones. It highlights bullish or bearish conditions using color-coded SMA logic and provides visual Buy/Sell signals based on smart crossover and state-based logic.
2. Purpose / Use Case
Designed for traders who want to visually identify momentum breakouts, trend reversals, or pullback opportunities, this tool helps:
Spot high-probability buy/sell zones
Confirm price strength relative to volatility bands (EMA High/Low)
Time entries based on clean visual cues
It works well in trend-following strategies, particularly in intraday or swing setups across any liquid market (indices, stocks, crypto, etc.).
3. Key Features & Logic
✅ EMA High/Low Channel: Acts as dynamic support/resistance boundaries using 20-period EMAs on high and low prices.
✅ Timeframe-Specific SMA: A 33-period SMA calculated from a user-defined timeframe (default: 10-minute) for flexible multi-timeframe analysis.
✅ Signal Generation:
Buy: When SMA drops below EMA Low and close is above EMA High.
Sell: When SMA rises above EMA High and price closes below both EMAs.
Optionally, signals also fire based on SMA color changes (green = bullish, red = bearish).
✅ Strict or Loose Signal Logic: Choose between precise crossovers or broader state-based conditions.
✅ Debugging Tools: Optional markers for granular insight into condition logic.
4. User Inputs & Settings
Input Description
EMA High Length Period for EMA of high prices (default: 20)
EMA Low Length Period for EMA of low prices (default: 20)
SMA Length Period for Simple Moving Average (default: 33)
SMA Timeframe Timeframe for SMA (default: “10”)
Show Buy/Sell Arrows Enable visual arrow signals for Buy/Sell
Strict Signal Logic ON = crossover-based signals; OFF = state logic
Plot Signals on SMA Color Change Enable signals on SMA color shifts (Green/Red)
Show Debug Markers Plot small markers to debug condition logic
5. Visual Elements Explained
🔵 EMA High Line – Blue line marking dynamic resistance
🔴 EMA Low Line – Red line marking dynamic support
🟡 SMA Line – Color-coded based on position:
Green if SMA < EMA Low (Bullish)
Red if SMA > EMA High (Bearish)
Yellow otherwise (Neutral)
✅ BUY / SELL Labels – Displayed below or above candles on valid signals
🛠️ Debug Circles/Triangles – Help visually understand the signal logic when enabled
6. Usage Tips
Best used on 5–30 min timeframes for intraday setups or 1H+ for swing trades.
Confirm signals with volume, price action, or other confluences (like support/resistance).
Use strict mode for more accurate entries, and non-strict mode for broader trend views.
Ideal for identifying pullbacks into trend, or early reversals after volatility squeezes.
7. What Makes It Unique
Multi-timeframe SMA integrated with EMA High/Low bands
Dual signal logic (crossover + color shift)
Visually intuitive and beginner-friendly
Minimal clutter with dynamic signal labeling
Debug mode for transparency and learning
8. Alerts & Automation
The indicator includes built-in alert conditions for:
📈 Buy Alert: Triggered when a bullish condition is detected.
🔻 Sell Alert: Triggered when bearish confirmation is detected.
These alerts can be used with TradingView's alert system for real-time notifications or bot integrations.
9. Technical Concepts Used
EMA (Exponential Moving Average): Reacts faster to recent price, ideal for trend channels
SMA (Simple Moving Average): Smoother average for detecting general trend direction
Crossover Logic: Checks when SMA crosses over or under EMA levels
Color Coding: Visual signal enhancement based on relative positioning
Multi-Timeframe Analysis: SMA calculated on a custom timeframe, powerful for confirmation
10. Disclaimer
This script is for educational and informational purposes only. It is not financial advice. Always backtest thoroughly and validate on demo accounts before applying to live markets. Trading involves risk, and past performance does not guarantee future results.
11. Author Signature
📌 Indicator Name: Custom EMA High/Low & SMA -
👤 Author: GSK-VIZAG-AP-INDIA
