High Low Index SPY Top 40Modification from original code for "High Low Index" by © LonesomeTheBlue
- Made modification specifically for Top 40 AMEX:SPY holdings
- Added Market sentiment histogram (Total count green vs red), and SMA line for it
- Added arrows for peaks and dips on High Low Index and Market Sentiment MA
Idea behind this indicator is that SPY should follow the overall sentiment of its top holdings. I believe this bring great value to SPY traders.
Enjoy~!
Recherche dans les scripts pour "信达股份40周年"
8,21,40 EMA by gmubirdBest used with 1 min time frame. On a solid trend usually the candles with stay above the 8 ema while retesting it every 5-15 bars. If it breaks the 8 ema then look for it to test the 21 ema . The 21 is useful on the 5 min as well because a trending stock with sometimes test the 21 for support and bounce off. However if it breaks the 5min 21 ema it's probably going to break it's short term trend and maybe go side ways or reverse. The 40 ema is mainly useful in the 1min because it helps visualize the 5min 8 ema . This is the main tell for a solidly trending stock/ spy because they love to test this over and over through a trend. Just watch for a break of it because it means a kinda good chance of the end of a trend and a good time to sell.
MA Cross 20/40 (editable)Simple script using the built in MA Cross script as the base but default to 20/40 MA and added option to edit the short and long duration values which the default script doesn't allow you to edit. My first script, it's yours for free. Be kind.
JSE Top 40 Comparative Relative Strength RSI OscillatorThis code is the result of an idea by @MarcoOlivano. The question was that if putting the comparative relative strength as an RSI oscillator would help in understanding the relative strength of the stock to the overall market? As we both trade the JSE I have made the JSE:J200 or Top 40 the basis for comparison. This can be changed in the settings dropdown if you want to compare with the All Share Index (JSE:J201) or other markets such as the S&P.
On the chart above I have included the Comparative Relative Strength as a reference together with the Comparative Relative Strength RSI.
If you use the indicator or adapt it please let me know if it works for you, how you use it and if it has any value.
JSE Top 40 Comparative Relative StrengthThis code adapts the code by vitvlkv to be appropriate for comparison of JSE stocks with the Top 40 index. It also includes moving averages and Bollinger Bands to identify extreme conditions. You can change the colours and deselect moving averages to make the plot less cluttered. You can also change the selection to compare the stock against to JSE:J201 if you want to compare it to the All Share Index.
Exponential Moving Averages 9 & 40 NKExponential Moving Averages 9 & 40 NK, used in Currency Markets
draw line at bar on condition, up to 40 bars in lengthDraws line at bar on condition, up to 40 bars in length.
Well, that's not a line, but a set of `—` characters. But it looks like a line, so it is line.
Guppy MMA 3, 5, 8, 10, 12, 15 and 30, 35, 40, 45, 50, 60Guppy Multiple Moving Average
Short Term EMA 3, 5, 8, 10, 12, 15
Long Term EMA 30, 35, 40, 45, 50, 60
Use for SFTS Class
40 crypto screener [LUPOWN]// ENGLISH
This indicator shows two tables, with 10 assets each, they can be currencies, stocks or cryptos, the columns can be changed to the information you want to see, among the options are price or change (change in percentage of the candle in the temporality where you are seeing it), TL are buy or sell signals according to the Latin trading strategy (Squeeze momentum combined with ADX) buy if the momentum changes to range or rise and the ADX has a negative slope, sell if the momentum changes to range or fall and The ADX has a negative slope, the signals are not 100% effective, you must support it with price action and market speculation, directionality in the momentum, slope of the ADX, if there is divergence in the momoentum squeeze, lux something and cipher use an indicator of Lazy bear, lux something signals when two wave trends cross and the cipher signals when the wave trend crosses above or below the 0 point.
You can choose between seeing one or two tables, this so that it can be seen on small screens, there is also the option to hide the tables and show the label, which is also an alternative to see it on small screens
i got the main idea from @QuantNomad
//SPANISH
Este indicador muestra dos tablas, con 10 activos cada una, pueden ser divisas, acciones o cryptos, las columnas se pueden cambiar a la información que quieras ver, entre las opciones están precio o cambio (cambio en porcentaje de la vela en la temporalidad donde lo estes viendo), TL son señales de compra o venta según estrategia de trading latino (Squeeze momentum combinado con ADX) compra si el momentum cambia a rango o subida y el ADX tiene pendiente negativa, venta si el momentum cambia a rango o caída y el ADX tiene pendiente negativa, las señales no son 100% efectivas debes apoyarla con la acción del precio y especulación del mercado, direccionalidad en el momentum, pendiente del ADX, si hay divergencia en el squeeze momoentum, lux algo y cipher utilizan un indicador de Lazy bear, lux algo da señal cuando dos wave trend se cruzan y el cipher da señal cuando el wave trend cruza por encima o debajo del punto 0.
Puedes elegir entre ver una o dos tablas, esto para que se pueda ver en pantallas pequeñas, también esta la opción de ocultar las tablas y mostrar el label, que también es una alternativa para verlo en pantallas pequeñas
La idea principal la tome de @QuantNomad
Multi-Symbol EMA Crossover Scanner with Multi-Timeframe AnalysisDescription
What This Indicator Does:
This indicator is a comprehensive market scanner that monitors up to 10 symbols simultaneously across 4 different timeframes (15-minute, 1-hour, 4-hour, and daily) to detect exponential moving average (EMA) crossovers in real-time. Instead of manually checking multiple charts and timeframes for EMA crossover signals, this scanner automatically does the work for you and presents all detected signals in a clean, organized table that updates continuously throughout the trading session.
Key Features:
Multi-Symbol Monitoring: Scan up to 10 different symbols at once (stocks, forex, crypto, or any TradingView symbol)
Multi-Timeframe Analysis: Simultaneously tracks 4 timeframes (15m, 1H, 4H, 1D) with toggle options to enable/disable each
Comprehensive EMA Pairs: Detects crossovers between all major EMA combinations: 20×50, 20×100, 20×200, 50×100, 50×200, and 100×200
Real-Time Signal Feed: Displays the most recent signals in a sorted table (newest first) with timestamp, direction, price, and EMA pair information
Session Filter: Built-in time filter (default 10:00-18:00) to focus on specific trading hours and avoid pre-market/after-hours noise
Pagination System: Navigate through signals using a page selector when you have more signals than fit in one view
Signal Statistics: Footer displays total signals, bullish/bearish breakdown, and page navigation hints
Customizable Display: Choose table position (4 corners), signals per page (5-20), and maximum signal history (10-100)
How It Works:
The scanner uses the request.security() function to fetch EMA data from multiple symbols and timeframes simultaneously. For each symbol-timeframe combination, it calculates four exponential moving averages (20, 50, 100, and 200 periods) and monitors for crossovers:
Bullish Crossovers (▲ Green):
Faster EMA crosses above slower EMA
Indicates potential upward momentum
Common entry signals for long positions
Bearish Crossovers (▼ Red):
Faster EMA crosses below slower EMA
Indicates potential downward momentum
Common entry signals for short positions or exits
The scanner prioritizes crossovers involving faster EMAs (20×50) over slower ones (100×200), as faster crossovers typically generate more frequent signals. Each detected crossover is stored with its timestamp, allowing the scanner to sort signals chronologically and remove duplicates within the same timeframe.
Signal Table Columns:
Sym: Symbol name (abbreviated, e.g., "ASELS" instead of "BIST:ASELS")
TF: Timeframe where the crossover occurred (15m, 1h, 4h, 1D)
⏰: Exact time of the crossover (HH:MM format in Istanbul timezone)
↕: Direction indicator (▲ bullish green / ▼ bearish red)
₺: Price level where the crossover occurred (average of the two EMAs)
MA: Which EMA pair crossed (e.g., "20×50", "50×200")
How to Use:
For Day Traders:
Enable 15m and 1h timeframes
Monitor symbols from your watchlist
Use crossovers as entry timing signals in the direction of the larger trend
Adjust the time filter to match your trading session (e.g., market open to 2 hours before close)
For Swing Traders:
Enable 4h and 1D timeframes
Focus on 50×200 and 100×200 crossovers (golden/death crosses)
Look for multiple timeframe confluence (same symbol showing bullish crossovers on both 4h and 1D)
Use as a pre-market scanner to identify potential setups for the day
For Multi-Market Traders:
Mix symbols from different markets (stocks, forex, crypto)
Use the scanner to identify which markets are showing the most momentum
Track relative strength by comparing crossover frequency across symbols
Identify rotation opportunities when one asset shows bullish signals while another shows bearish
Setup Recommendations:
Default BIST (Turkish Stock Market) Setup:
The code comes pre-configured with 10 popular BIST stocks:
ASELS, EKGYO, THYAO, AKBNK, PGSUS, ASTOR, OTKAR, ALARK, ISCTR, BIMAS
For US Stocks:
Replace with symbols like: NASDAQ:AAPL, NASDAQ:TSLA, NASDAQ:NVDA, NYSE:JPM, etc.
For Forex:
Use pairs like: FX:EURUSD, FX:GBPUSD, FX:USDJPY, OANDA:XAUUSD, etc.
For Crypto:
Use exchanges like: BINANCE:BTCUSDT, COINBASE:ETHUSD, BINANCE:SOLUSDT, etc.
Settings Guide:
Symbol List (10 inputs):
Enter any valid TradingView symbol in "EXCHANGE:TICKER" format
Use symbols you actively trade or monitor
Mix different asset classes if desired
Timeframe Toggles:
15 Minutes: High-frequency signals, best for day trading
1 Hour: Balanced frequency, good for intraday swing trades
4 Hours: Lower frequency, quality swing trade signals
1 Day: Low frequency, major trend changes only
Time Filter:
Start Hour (10): Beginning of your trading session
End Hour (18): End of your trading session
Prevents signals during low-liquidity periods
Adjust to match your market's active hours
Display Settings:
Table Position: Choose corner placement (doesn't interfere with other indicators)
Max Signals (40): Total historical signals to keep in memory
Signals Per Page (10): How many rows to show at once
Page Number: Navigate through signal history (auto-adjusts to available pages)
What Makes This Original:
Multi-symbol scanners exist on TradingView, but this indicator's originality comes from:
Comprehensive EMA Pair Coverage: Most scanners focus on 1-2 EMA pairs, this monitors 6 different combinations simultaneously
Unified Multi-Timeframe View: Presents signals from 4 timeframes in a single, chronologically sorted feed rather than separate panels
Session-Aware Filtering: Built-in time filter prevents signal overload from 24-hour markets
Smart Pagination: Handles large signal volumes gracefully with page navigation instead of scrolling
Signal Deduplication: Prevents the same crossover from appearing multiple times if it persists across several bars
Price-at-Cross Recording: Captures the exact price where the crossover occurred, not just that it happened
Real-Time Statistics: Live tracking of bullish vs bearish signal distribution
Trading Strategy Examples:
Trend Confirmation Strategy:
Find a symbol showing bullish crossover on 1D (major trend change)
Wait for pullback
Enter when 1h shows bullish crossover (confirmation)
Exit when 1h shows bearish crossover
Multi-Timeframe Confluence:
Look for symbols appearing multiple times with same direction
Example: ASELS shows ▲ on both 4h and 1D = strong bullish signal
Avoid symbols showing conflicting signals (▲ on 1h but ▼ on 4h)
Rotation Scanner:
Monitor 10+ symbols from the same sector
Identify which are turning bullish (▲) first
Enter leaders, avoid laggards
Rotate out when crossovers turn bearish (▼)
Important Considerations:
Not a Complete System: EMA crossovers should be confirmed with price action, volume, and support/resistance analysis
Whipsaw Risk: During consolidation, EMAs can cross back and forth frequently (especially on 15m timeframe)
Lag: EMAs are lagging indicators; crossovers occur after the move has already begun
False Signals: More common during sideways markets; work best in trending environments
Symbol Limits: TradingView has limits on request.security() calls; this scanner uses 40 calls (10 symbols × 4 timeframes)
Performance: On lower-end devices, scanning 10 symbols across 4 timeframes may cause slight delays in chart updates
Best Practices:
Start with 5 symbols and 2 timeframes, then expand as you get comfortable
Use in conjunction with a main chart for price context
Don't trade every signal—filter for high-quality setups
Backtest your favorite EMA pairs on your symbols to understand their reliability
Adjust the time filter to exclude lunch hours if your market has low midday volume
Check the footer statistics—if you're getting 50+ signals per day, tighten your time filter or reduce symbols
Technical Notes:
Uses lookahead=barmerge.lookahead_off to prevent future data leakage
Signals are stored in arrays and sorted by timestamp (newest first)
Automatic daily reset clears old signals to prevent memory buildup
Table dynamically resizes based on signal count
All times displayed in Europe/Istanbul timezone (configurable in code)
Universal Ratio Trend Matrix [InvestorUnknown]The Universal Ratio Trend Matrix is designed for trend analysis on asset/asset ratios, supporting up to 40 different assets. Its primary purpose is to help identify which assets are outperforming others within a selection, providing a broad overview of market trends through a matrix of ratios. The indicator automatically expands the matrix based on the number of assets chosen, simplifying the process of comparing multiple assets in terms of performance.
Key features include the ability to choose from a narrow selection of indicators to perform the ratio trend analysis, allowing users to apply well-defined metrics to their comparison.
Drawback: Due to the computational intensity involved in calculating ratios across many assets, the indicator has a limitation related to loading speed. TradingView has time limits for calculations, and for users on the basic (free) plan, this could result in frequent errors due to exceeded time limits. To use the indicator effectively, users with any paid plans should run it on timeframes higher than 8h (the lowest timeframe on which it managed to load with 40 assets), as lower timeframes may not reliably load.
Indicators:
RSI_raw: Simple function to calculate the Relative Strength Index (RSI) of a source (asset price).
RSI_sma: Calculates RSI followed by a Simple Moving Average (SMA).
RSI_ema: Calculates RSI followed by an Exponential Moving Average (EMA).
CCI: Calculates the Commodity Channel Index (CCI).
Fisher: Implements the Fisher Transform to normalize prices.
Utility Functions:
f_remove_exchange_name: Strips the exchange name from asset tickers (e.g., "INDEX:BTCUSD" to "BTCUSD").
f_remove_exchange_name(simple string name) =>
string parts = str.split(name, ":")
string result = array.size(parts) > 1 ? array.get(parts, 1) : name
result
f_get_price: Retrieves the closing price of a given asset ticker using request.security().
f_constant_src: Checks if the source data is constant by comparing multiple consecutive values.
Inputs:
General settings allow users to select the number of tickers for analysis (used_assets) and choose the trend indicator (RSI, CCI, Fisher, etc.).
Table settings customize how trend scores are displayed in terms of text size, header visibility, highlighting options, and top-performing asset identification.
The script includes inputs for up to 40 assets, allowing the user to select various cryptocurrencies (e.g., BTCUSD, ETHUSD, SOLUSD) or other assets for trend analysis.
Price Arrays:
Price values for each asset are stored in variables (price_a1 to price_a40) initialized as na. These prices are updated only for the number of assets specified by the user (used_assets).
Trend scores for each asset are stored in separate arrays
// declare price variables as "na"
var float price_a1 = na, var float price_a2 = na, var float price_a3 = na, var float price_a4 = na, var float price_a5 = na
var float price_a6 = na, var float price_a7 = na, var float price_a8 = na, var float price_a9 = na, var float price_a10 = na
var float price_a11 = na, var float price_a12 = na, var float price_a13 = na, var float price_a14 = na, var float price_a15 = na
var float price_a16 = na, var float price_a17 = na, var float price_a18 = na, var float price_a19 = na, var float price_a20 = na
var float price_a21 = na, var float price_a22 = na, var float price_a23 = na, var float price_a24 = na, var float price_a25 = na
var float price_a26 = na, var float price_a27 = na, var float price_a28 = na, var float price_a29 = na, var float price_a30 = na
var float price_a31 = na, var float price_a32 = na, var float price_a33 = na, var float price_a34 = na, var float price_a35 = na
var float price_a36 = na, var float price_a37 = na, var float price_a38 = na, var float price_a39 = na, var float price_a40 = na
// create "empty" arrays to store trend scores
var a1_array = array.new_int(40, 0), var a2_array = array.new_int(40, 0), var a3_array = array.new_int(40, 0), var a4_array = array.new_int(40, 0)
var a5_array = array.new_int(40, 0), var a6_array = array.new_int(40, 0), var a7_array = array.new_int(40, 0), var a8_array = array.new_int(40, 0)
var a9_array = array.new_int(40, 0), var a10_array = array.new_int(40, 0), var a11_array = array.new_int(40, 0), var a12_array = array.new_int(40, 0)
var a13_array = array.new_int(40, 0), var a14_array = array.new_int(40, 0), var a15_array = array.new_int(40, 0), var a16_array = array.new_int(40, 0)
var a17_array = array.new_int(40, 0), var a18_array = array.new_int(40, 0), var a19_array = array.new_int(40, 0), var a20_array = array.new_int(40, 0)
var a21_array = array.new_int(40, 0), var a22_array = array.new_int(40, 0), var a23_array = array.new_int(40, 0), var a24_array = array.new_int(40, 0)
var a25_array = array.new_int(40, 0), var a26_array = array.new_int(40, 0), var a27_array = array.new_int(40, 0), var a28_array = array.new_int(40, 0)
var a29_array = array.new_int(40, 0), var a30_array = array.new_int(40, 0), var a31_array = array.new_int(40, 0), var a32_array = array.new_int(40, 0)
var a33_array = array.new_int(40, 0), var a34_array = array.new_int(40, 0), var a35_array = array.new_int(40, 0), var a36_array = array.new_int(40, 0)
var a37_array = array.new_int(40, 0), var a38_array = array.new_int(40, 0), var a39_array = array.new_int(40, 0), var a40_array = array.new_int(40, 0)
f_get_price(simple string ticker) =>
request.security(ticker, "", close)
// Prices for each USED asset
f_get_asset_price(asset_number, ticker) =>
if (used_assets >= asset_number)
f_get_price(ticker)
else
na
// overwrite empty variables with the prices if "used_assets" is greater or equal to the asset number
if barstate.isconfirmed // use barstate.isconfirmed to avoid "na prices" and calculation errors that result in empty cells in the table
price_a1 := f_get_asset_price(1, asset1), price_a2 := f_get_asset_price(2, asset2), price_a3 := f_get_asset_price(3, asset3), price_a4 := f_get_asset_price(4, asset4)
price_a5 := f_get_asset_price(5, asset5), price_a6 := f_get_asset_price(6, asset6), price_a7 := f_get_asset_price(7, asset7), price_a8 := f_get_asset_price(8, asset8)
price_a9 := f_get_asset_price(9, asset9), price_a10 := f_get_asset_price(10, asset10), price_a11 := f_get_asset_price(11, asset11), price_a12 := f_get_asset_price(12, asset12)
price_a13 := f_get_asset_price(13, asset13), price_a14 := f_get_asset_price(14, asset14), price_a15 := f_get_asset_price(15, asset15), price_a16 := f_get_asset_price(16, asset16)
price_a17 := f_get_asset_price(17, asset17), price_a18 := f_get_asset_price(18, asset18), price_a19 := f_get_asset_price(19, asset19), price_a20 := f_get_asset_price(20, asset20)
price_a21 := f_get_asset_price(21, asset21), price_a22 := f_get_asset_price(22, asset22), price_a23 := f_get_asset_price(23, asset23), price_a24 := f_get_asset_price(24, asset24)
price_a25 := f_get_asset_price(25, asset25), price_a26 := f_get_asset_price(26, asset26), price_a27 := f_get_asset_price(27, asset27), price_a28 := f_get_asset_price(28, asset28)
price_a29 := f_get_asset_price(29, asset29), price_a30 := f_get_asset_price(30, asset30), price_a31 := f_get_asset_price(31, asset31), price_a32 := f_get_asset_price(32, asset32)
price_a33 := f_get_asset_price(33, asset33), price_a34 := f_get_asset_price(34, asset34), price_a35 := f_get_asset_price(35, asset35), price_a36 := f_get_asset_price(36, asset36)
price_a37 := f_get_asset_price(37, asset37), price_a38 := f_get_asset_price(38, asset38), price_a39 := f_get_asset_price(39, asset39), price_a40 := f_get_asset_price(40, asset40)
Universal Indicator Calculation (f_calc_score):
This function allows switching between different trend indicators (RSI, CCI, Fisher) for flexibility.
It uses a switch-case structure to calculate the indicator score, where a positive trend is denoted by 1 and a negative trend by 0. Each indicator has its own logic to determine whether the asset is trending up or down.
// use switch to allow "universality" in indicator selection
f_calc_score(source, trend_indicator, int_1, int_2) =>
int score = na
if (not f_constant_src(source)) and source > 0.0 // Skip if you are using the same assets for ratio (for example BTC/BTC)
x = switch trend_indicator
"RSI (Raw)" => RSI_raw(source, int_1)
"RSI (SMA)" => RSI_sma(source, int_1, int_2)
"RSI (EMA)" => RSI_ema(source, int_1, int_2)
"CCI" => CCI(source, int_1)
"Fisher" => Fisher(source, int_1)
y = switch trend_indicator
"RSI (Raw)" => x > 50 ? 1 : 0
"RSI (SMA)" => x > 50 ? 1 : 0
"RSI (EMA)" => x > 50 ? 1 : 0
"CCI" => x > 0 ? 1 : 0
"Fisher" => x > x ? 1 : 0
score := y
else
score := 0
score
Array Setting Function (f_array_set):
This function populates an array with scores calculated for each asset based on a base price (p_base) divided by the prices of the individual assets.
It processes multiple assets (up to 40), calling the f_calc_score function for each.
// function to set values into the arrays
f_array_set(a_array, p_base) =>
array.set(a_array, 0, f_calc_score(p_base / price_a1, trend_indicator, int_1, int_2))
array.set(a_array, 1, f_calc_score(p_base / price_a2, trend_indicator, int_1, int_2))
array.set(a_array, 2, f_calc_score(p_base / price_a3, trend_indicator, int_1, int_2))
array.set(a_array, 3, f_calc_score(p_base / price_a4, trend_indicator, int_1, int_2))
array.set(a_array, 4, f_calc_score(p_base / price_a5, trend_indicator, int_1, int_2))
array.set(a_array, 5, f_calc_score(p_base / price_a6, trend_indicator, int_1, int_2))
array.set(a_array, 6, f_calc_score(p_base / price_a7, trend_indicator, int_1, int_2))
array.set(a_array, 7, f_calc_score(p_base / price_a8, trend_indicator, int_1, int_2))
array.set(a_array, 8, f_calc_score(p_base / price_a9, trend_indicator, int_1, int_2))
array.set(a_array, 9, f_calc_score(p_base / price_a10, trend_indicator, int_1, int_2))
array.set(a_array, 10, f_calc_score(p_base / price_a11, trend_indicator, int_1, int_2))
array.set(a_array, 11, f_calc_score(p_base / price_a12, trend_indicator, int_1, int_2))
array.set(a_array, 12, f_calc_score(p_base / price_a13, trend_indicator, int_1, int_2))
array.set(a_array, 13, f_calc_score(p_base / price_a14, trend_indicator, int_1, int_2))
array.set(a_array, 14, f_calc_score(p_base / price_a15, trend_indicator, int_1, int_2))
array.set(a_array, 15, f_calc_score(p_base / price_a16, trend_indicator, int_1, int_2))
array.set(a_array, 16, f_calc_score(p_base / price_a17, trend_indicator, int_1, int_2))
array.set(a_array, 17, f_calc_score(p_base / price_a18, trend_indicator, int_1, int_2))
array.set(a_array, 18, f_calc_score(p_base / price_a19, trend_indicator, int_1, int_2))
array.set(a_array, 19, f_calc_score(p_base / price_a20, trend_indicator, int_1, int_2))
array.set(a_array, 20, f_calc_score(p_base / price_a21, trend_indicator, int_1, int_2))
array.set(a_array, 21, f_calc_score(p_base / price_a22, trend_indicator, int_1, int_2))
array.set(a_array, 22, f_calc_score(p_base / price_a23, trend_indicator, int_1, int_2))
array.set(a_array, 23, f_calc_score(p_base / price_a24, trend_indicator, int_1, int_2))
array.set(a_array, 24, f_calc_score(p_base / price_a25, trend_indicator, int_1, int_2))
array.set(a_array, 25, f_calc_score(p_base / price_a26, trend_indicator, int_1, int_2))
array.set(a_array, 26, f_calc_score(p_base / price_a27, trend_indicator, int_1, int_2))
array.set(a_array, 27, f_calc_score(p_base / price_a28, trend_indicator, int_1, int_2))
array.set(a_array, 28, f_calc_score(p_base / price_a29, trend_indicator, int_1, int_2))
array.set(a_array, 29, f_calc_score(p_base / price_a30, trend_indicator, int_1, int_2))
array.set(a_array, 30, f_calc_score(p_base / price_a31, trend_indicator, int_1, int_2))
array.set(a_array, 31, f_calc_score(p_base / price_a32, trend_indicator, int_1, int_2))
array.set(a_array, 32, f_calc_score(p_base / price_a33, trend_indicator, int_1, int_2))
array.set(a_array, 33, f_calc_score(p_base / price_a34, trend_indicator, int_1, int_2))
array.set(a_array, 34, f_calc_score(p_base / price_a35, trend_indicator, int_1, int_2))
array.set(a_array, 35, f_calc_score(p_base / price_a36, trend_indicator, int_1, int_2))
array.set(a_array, 36, f_calc_score(p_base / price_a37, trend_indicator, int_1, int_2))
array.set(a_array, 37, f_calc_score(p_base / price_a38, trend_indicator, int_1, int_2))
array.set(a_array, 38, f_calc_score(p_base / price_a39, trend_indicator, int_1, int_2))
array.set(a_array, 39, f_calc_score(p_base / price_a40, trend_indicator, int_1, int_2))
a_array
Conditional Array Setting (f_arrayset):
This function checks if the number of used assets is greater than or equal to a specified number before populating the arrays.
// only set values into arrays for USED assets
f_arrayset(asset_number, a_array, p_base) =>
if (used_assets >= asset_number)
f_array_set(a_array, p_base)
else
na
Main Logic
The main logic initializes arrays to store scores for each asset. Each array corresponds to one asset's performance score.
Setting Trend Values: The code calls f_arrayset for each asset, populating the respective arrays with calculated scores based on the asset prices.
Combining Arrays: A combined_array is created to hold all the scores from individual asset arrays. This array facilitates further analysis, allowing for an overview of the performance scores of all assets at once.
// create a combined array (work-around since pinescript doesn't support having array of arrays)
var combined_array = array.new_int(40 * 40, 0)
if barstate.islast
for i = 0 to 39
array.set(combined_array, i, array.get(a1_array, i))
array.set(combined_array, i + (40 * 1), array.get(a2_array, i))
array.set(combined_array, i + (40 * 2), array.get(a3_array, i))
array.set(combined_array, i + (40 * 3), array.get(a4_array, i))
array.set(combined_array, i + (40 * 4), array.get(a5_array, i))
array.set(combined_array, i + (40 * 5), array.get(a6_array, i))
array.set(combined_array, i + (40 * 6), array.get(a7_array, i))
array.set(combined_array, i + (40 * 7), array.get(a8_array, i))
array.set(combined_array, i + (40 * 8), array.get(a9_array, i))
array.set(combined_array, i + (40 * 9), array.get(a10_array, i))
array.set(combined_array, i + (40 * 10), array.get(a11_array, i))
array.set(combined_array, i + (40 * 11), array.get(a12_array, i))
array.set(combined_array, i + (40 * 12), array.get(a13_array, i))
array.set(combined_array, i + (40 * 13), array.get(a14_array, i))
array.set(combined_array, i + (40 * 14), array.get(a15_array, i))
array.set(combined_array, i + (40 * 15), array.get(a16_array, i))
array.set(combined_array, i + (40 * 16), array.get(a17_array, i))
array.set(combined_array, i + (40 * 17), array.get(a18_array, i))
array.set(combined_array, i + (40 * 18), array.get(a19_array, i))
array.set(combined_array, i + (40 * 19), array.get(a20_array, i))
array.set(combined_array, i + (40 * 20), array.get(a21_array, i))
array.set(combined_array, i + (40 * 21), array.get(a22_array, i))
array.set(combined_array, i + (40 * 22), array.get(a23_array, i))
array.set(combined_array, i + (40 * 23), array.get(a24_array, i))
array.set(combined_array, i + (40 * 24), array.get(a25_array, i))
array.set(combined_array, i + (40 * 25), array.get(a26_array, i))
array.set(combined_array, i + (40 * 26), array.get(a27_array, i))
array.set(combined_array, i + (40 * 27), array.get(a28_array, i))
array.set(combined_array, i + (40 * 28), array.get(a29_array, i))
array.set(combined_array, i + (40 * 29), array.get(a30_array, i))
array.set(combined_array, i + (40 * 30), array.get(a31_array, i))
array.set(combined_array, i + (40 * 31), array.get(a32_array, i))
array.set(combined_array, i + (40 * 32), array.get(a33_array, i))
array.set(combined_array, i + (40 * 33), array.get(a34_array, i))
array.set(combined_array, i + (40 * 34), array.get(a35_array, i))
array.set(combined_array, i + (40 * 35), array.get(a36_array, i))
array.set(combined_array, i + (40 * 36), array.get(a37_array, i))
array.set(combined_array, i + (40 * 37), array.get(a38_array, i))
array.set(combined_array, i + (40 * 38), array.get(a39_array, i))
array.set(combined_array, i + (40 * 39), array.get(a40_array, i))
Calculating Sums: A separate array_sums is created to store the total score for each asset by summing the values of their respective score arrays. This allows for easy comparison of overall performance.
Ranking Assets: The final part of the code ranks the assets based on their total scores stored in array_sums. It assigns a rank to each asset, where the asset with the highest score receives the highest rank.
// create array for asset RANK based on array.sum
var ranks = array.new_int(used_assets, 0)
// for loop that calculates the rank of each asset
if barstate.islast
for i = 0 to (used_assets - 1)
int rank = 1
for x = 0 to (used_assets - 1)
if i != x
if array.get(array_sums, i) < array.get(array_sums, x)
rank := rank + 1
array.set(ranks, i, rank)
Dynamic Table Creation
Initialization: The table is initialized with a base structure that includes headers for asset names, scores, and ranks. The headers are set to remain constant, ensuring clarity for users as they interpret the displayed data.
Data Population: As scores are calculated for each asset, the corresponding values are dynamically inserted into the table. This is achieved through a loop that iterates over the scores and ranks stored in the combined_array and array_sums, respectively.
Automatic Extending Mechanism
Variable Asset Count: The code checks the number of assets defined by the user. Instead of hardcoding the number of rows in the table, it uses a variable to determine the extent of the data that needs to be displayed. This allows the table to expand or contract based on the number of assets being analyzed.
Dynamic Row Generation: Within the loop that populates the table, the code appends new rows for each asset based on the current asset count. The structure of each row includes the asset name, its score, and its rank, ensuring that the table remains consistent regardless of how many assets are involved.
// Automatically extending table based on the number of used assets
var table table = table.new(position.bottom_center, 50, 50, color.new(color.black, 100), color.white, 3, color.white, 1)
if barstate.islast
if not hide_head
table.cell(table, 0, 0, "Universal Ratio Trend Matrix", text_color = color.white, bgcolor = #010c3b, text_size = fontSize)
table.merge_cells(table, 0, 0, used_assets + 3, 0)
if not hide_inps
table.cell(table, 0, 1,
text = "Inputs: You are using " + str.tostring(trend_indicator) + ", which takes: " + str.tostring(f_get_input(trend_indicator)),
text_color = color.white, text_size = fontSize), table.merge_cells(table, 0, 1, used_assets + 3, 1)
table.cell(table, 0, 2, "Assets", text_color = color.white, text_size = fontSize, bgcolor = #010c3b)
for x = 0 to (used_assets - 1)
table.cell(table, x + 1, 2, text = str.tostring(array.get(assets, x)), text_color = color.white, bgcolor = #010c3b, text_size = fontSize)
table.cell(table, 0, x + 3, text = str.tostring(array.get(assets, x)), text_color = color.white, bgcolor = f_asset_col(array.get(ranks, x)), text_size = fontSize)
for r = 0 to (used_assets - 1)
for c = 0 to (used_assets - 1)
table.cell(table, c + 1, r + 3, text = str.tostring(array.get(combined_array, c + (r * 40))),
text_color = hl_type == "Text" ? f_get_col(array.get(combined_array, c + (r * 40))) : color.white, text_size = fontSize,
bgcolor = hl_type == "Background" ? f_get_col(array.get(combined_array, c + (r * 40))) : na)
for x = 0 to (used_assets - 1)
table.cell(table, x + 1, x + 3, "", bgcolor = #010c3b)
table.cell(table, used_assets + 1, 2, "", bgcolor = #010c3b)
for x = 0 to (used_assets - 1)
table.cell(table, used_assets + 1, x + 3, "==>", text_color = color.white)
table.cell(table, used_assets + 2, 2, "SUM", text_color = color.white, text_size = fontSize, bgcolor = #010c3b)
table.cell(table, used_assets + 3, 2, "RANK", text_color = color.white, text_size = fontSize, bgcolor = #010c3b)
for x = 0 to (used_assets - 1)
table.cell(table, used_assets + 2, x + 3,
text = str.tostring(array.get(array_sums, x)),
text_color = color.white, text_size = fontSize,
bgcolor = f_highlight_sum(array.get(array_sums, x), array.get(ranks, x)))
table.cell(table, used_assets + 3, x + 3,
text = str.tostring(array.get(ranks, x)),
text_color = color.white, text_size = fontSize,
bgcolor = f_highlight_rank(array.get(ranks, x)))
A_Traders_Edge__LibraryLibrary "A_Traders_Edge__Library"
- A Trader's Edge (ATE)_Library was created to assist in constructing Market Overview Scanners (MOS)
LabelLocation(_firstLocation)
This function is used when there's a desire to print an assets ALERT LABELS at a set location on the scale that will
NOT change throughout the progression of the script. This is created so that if a lot of alerts are triggered, they
will stay relatively visible and not overlap each other. Ex. If you set your '_firstLocation' parameter as 1, since
there are a max of 40 assets that can be scanned, the 1st asset's location is assigned the value in the '_firstLocation' parameter,
the 2nd asset's location is the (1st asset's location+1)...and so on. If your first location is set to 81 then
the 1st asset is 81 and 2nd is 82 and so on until the 40th location = 120(in this particular example).
Parameters:
_firstLocation (simple int) : (simple int)
Optional(starts at 1 if no parameter added).
Location that you want the first asset to print its label if is triggered to do so.
ie. loc2=loc1+1, loc3=loc2+1, etc.
Returns: Returns 40 output variables each being a different location to print the labels so that an asset is asssigned to
a particular location on the scale. Regardless of if you have the maximum amount of assets being screened (40 max), this
function will output 40 locations… So there needs to be 40 variables assigned in the tuple in this function. What I
mean by that is you need to have 40 output location variables within your tuple (ie. between the ' ') regarless of
if your scanning 40 assets or not. If you only have 20 assets in your scripts input settings, then only the first 20
variables within the ' ' Will be assigned to a value location and the other 20 will be assigned 'NA', but their
variables still need to be present in the tuple.
SeparateTickerids(_string)
You must form this single tickerID input string exactly as described in the scripts info panel (little gray 'i' that
is circled at the end of the settings in the settings/input panel that you can hover your cursor over this 'i' to read the
details of that particular input). IF the string is formed correctly then it will break up this single string parameter into
a total of 40 separate strings which will be all of the tickerIDs that the script is using in your MO scanner.
Parameters:
_string (simple string) : (string)
A maximum of 40 Tickers (ALL joined as 1 string for the input parameter) that is formulated EXACTLY as described
within the tooltips of the TickerID inputs in my MOS Scanner scripts:
assets = input.text_area(tIDset1, title="TickerID (MUST READ TOOLTIP)", tooltip="Accepts 40 TICKERID's for each
copy of the script on the chart. TEXT FORMATTING RULES FOR TICKERID'S:
(1) To exclude the EXCHANGE NAME in the Labels, de-select the next input option.
(2) MUST have a space (' ') AFTER each TickerID.
(3) Capitalization in the Labels will match cap of these TickerID's.
(4) If your asset has a BaseCurrency & QuoteCurrency (ie. ADAUSDT ) BUT you ONLY want Labels
to show BaseCurrency(ie.'ADA'), include a FORWARD SLASH ('/') between the Base & Quote (ie.'ADA/USDT')", display=display.none)
Returns: Returns 40 output variables of the different strings of TickerID's (ie. you need to output 40 variables within the
tuple ' ' regardless of if you were scanning using all possible (40) assets or not.
If your scanning for less than 40 assets, then once the variables are assigned to all of the tickerIDs, the rest
of the 40 variables in the tuple will be assigned "NA".
TickeridForLabelsAndSecurity(_includeExchange, _ticker)
This function accepts the TickerID Name as its parameter and produces a single string that will be used in all of your labels.
Parameters:
_includeExchange (simple bool) : (bool)
Optional(if parameter not included in function it defaults to false ).
Used to determine if the Exchange name will be included in all labels/triggers/alerts.
_ticker (simple string) : (string)
For this parameter, input the varible named '_coin' from your 'f_main()' function for this parameter. It is the raw
Ticker ID name that will be processed.
Returns: ( )
Returns 2 output variables:
1st ('_securityTickerid') is to be used in the 'request.security()' function as this string will contain everything
TV needs to pull the correct assets data.
2nd ('lblTicker') is to be used in all of the labels in your MOS as it will only contain what you want your labels
to show as determined by how the tickerID is formulated in the MOS's input.
InvalidTID(_tablePosition, _stackVertical, _close, _securityTickerid, _invalidArray)
This is to add a table in the middle right of your chart that prints all the TickerID's that were either not formulated
correctly in the '_source' input or that is not a valid symbol and should be changed.
Parameters:
_tablePosition (simple string) : (string)
Optional(if parameter not included, it defaults to position.middle_right). Location on the chart you want the table printed.
Possible strings include: position.top_center, position.top_left, position.top_right, position.middle_center,
position.middle_left, position.middle_right, position.bottom_center, position.bottom_left, position.bottom_right.
_stackVertical (simple bool) : (bool)
Optional(if parameter not included, it defaults to true). All of the assets that are counted as INVALID will be
created in a list. If you want this list to be prited as a column then input 'true' here.
_close (float) : (float)
If you want them printed as a single row then input 'false' here.
This should be the closing value of each of the assets being tested to determine in the TickerID is valid or not.
_securityTickerid (string) : (string)
Throughout the entire charts updates, if a '_close' value is never regestered then the logic counts the asset as INVALID.
This will be the 1st TickerID varible (named _securityTickerid) outputted from the tuple of the TickeridForLabels()
function above this one.
_invalidArray (string ) : (array string)
Input the array from the original script that houses all of the invalidArray strings.
Returns: (na)
Returns a table with the screened assets Invalid TickerID's. Table draws automatically if any are Invalid, thus,
no output variable to deal with.
LabelSizes(_barCnt, _lblSzRfrnce)
This function sizes your Alert Trigger Labels according to the amount of Printed Bars the chart has printed within
a set time period, while also keeping in mind the smallest relative reference size you input in the 'lblSzRfrnceInput'
parameter of this function. A HIGHER % of Printed Bars(aka...more trades occurring for that asset on the exchange),
the LARGER the Name Label will print, potentially showing you the better opportunities on the exchange to avoid
exchange manipulation liquidations.
*** SHOULD NOT be used as size of labels that are your asset Name Labels next to each asset's Line Plot...
if your MOS includes these as you want these to be the same size for every asset so the larger ones dont cover the
smaller ones if the plots are all close to each other ***
Parameters:
_barCnt (float) : (float)
Get the 1st variable('barCnt') from the 'PrintedBarCount' function's tuple and input it as this functions 1st input
parameter which will directly affect the size of the 2nd output variable ('alertTrigLabel') outputted by this function.
_lblSzRfrnce (string) : (string)
Optional(if parameter not included, it defaults to size.small). This will be the size of the 1st variable outputted
by this function ('assetNameLabel') BUT also affects the 2nd variable outputted by this function.
Returns: ( )
Returns 2 variables:
1st output variable ('AssetNameLabel') is assigned to the size of the 'lblSzRfrnceInput' parameter.
2nd output variable('alertTrigLabel') can be of variying sizes depending on the 'barCnt' parameter...BUT the smallest
size possible for the 2nd output variable ('alertTrigLabel') will be the size set in the 'lblSzRfrnceInput' parameter.
AssetColor()
This function is used to assign 40 different colors to 40 variables to be used for the different labels/plots.
Returns: Returns 40 output variables each with a different color assigned to them to be used in your plots & labels.
Regardless of if you have the maximum amount of assets your scanning(40 max) or less,
this function will assign 40 colors to 40 variables that you have between the ' '.
PrintedBarCount(_time, _barCntLength, _barCntPercentMin)
The Printed BarCount Filter looks back a User Defined amount of minutes and calculates the % of bars that have printed
out of the TOTAL amount of bars that COULD HAVE been printed within the same amount of time.
Parameters:
_time (int) : (int)
The time associated with the chart of the particular asset that is being screened at that point.
_barCntLength (int) : (int)
The amount of time (IN MINUTES) that you want the logic to look back at to calculate the % of bars that have actually
printed in the span of time you input into this parameter.
_barCntPercentMin (int) : (int)
The minimum % of Printed Bars of the asset being screened has to be GREATER than the value set in this parameter
for the output variable 'bc_gtg' to be true.
Returns: ( )
Returns 2 outputs:
1st is the % of Printed Bars that have printed within the within the span of time you input in the '_barCntLength' parameter.
2nd is true/false according to if the Printed BarCount % is above the threshold that you input into the '_barCntPercentMin' parameter.
RCI(_rciLength, _source, _interval)
You will see me using this a lot. DEFINITELY my favorite oscillator to utilize for SO many different things from
timing entries/exits to determining trends.Calculation of this indicator based on Spearmans Correlation.
Parameters:
_rciLength (int) : (int)
Amount of bars back to use in RCI calculations.
_source (float) : (float)
Source to use in RCI calculations (can use ANY source series. Ie, open,close,high,low,etc).
_interval (int) : (int)
Optional(if parameter not included, it defaults to 3). RCI calculation groups bars by this amount and then will.
rank these groups of bars.
Returns: (float)
Returns a single RCI value that will oscillates between -100 and +100.
RCIAVG(firstLength, _amtBtLengths, _rciSMAlen, _source, _interval)
20 RCI's are averaged together to get this RCI Avg (Rank Correlation Index Average). Each RCI (of the 20 total RCI)
has a progressively LARGER Lookback Length. Though the RCI Lengths are not individually adjustable,
there are 2 factors that ARE:
(1) the Lookback Length of the 1st RCI and
(2) the amount of values between one RCI's Lookback Length and the next.
*** If you set 'firstLength' to it's default of 200 and '_amtBtLengths' to it's default of 120 (aka AMOUNT BETWEEN LENGTHS=120)...
then RCI_2 Length=320, RCI_3 Length=440, RCI_4 Length=560, and so on.
Parameters:
firstLength (int) : (int)
Optional(if parameter is not included when the function is called, then it defaults to 200).
This parameter is the Lookback Length for the 1st RCI used in the RCI Avg.
_amtBtLengths (int) : (int)
Optional(if parameter not included when the function is called, then it defaults to 120).
This parameter is the value amount between each of the progressively larger lengths used for the 20 RCI's that
are averaged in the RCI Avg.
***** BEWARE ***** Too large of a value here will cause the calc to look back too far, causing an error(thus the value must be lowered)
_rciSMAlen (int) : (int)
Unlike the Single RCI Function, this function smooths out the end result using an SMA with a length value that is this parameter.
_source (float) : (float)
Source to use in RCI calculations (can use ANY source series. Ie, open,close,high,low,etc).
_interval (int) : (int)
Optional(if parameter not included, it defaults to 3). Within the RCI calculation, bars next to each other are grouped together
and then these groups are Ranked against each other. This parameter is the number of adjacent bars that are grouped together.
Returns: (float)
Returns a single RCI value that is the Avg of many RCI values that will oscillate between -100 and +100.
PercentChange(_startingValue, _endingValue)
This is a quick function to calculate how much % change has occurred between the '_startingValue' and the '_endingValue'
that you input into the function.
Parameters:
_startingValue (float) : (float)
The source value to START the % change calculation from.
_endingValue (float) : (float)
The source value to END the % change caluclation from.
Returns: Returns a single output being the % value between 0-100 (with trailing numbers behind a decimal). If you want only
a certain amount of numbers behind the decimal, this function needs to be put within a formatting function to do so.
Rescale(_source, _oldMin, _oldMax, _newMin, _newMax)
Rescales series with a known '_oldMin' & '_oldMax'. Use this when the scale of the '_source' to
rescale is known (bounded).
Parameters:
_source (float) : (float)
Source to be normalized.
_oldMin (int) : (float)
The known minimum of the '_source'.
_oldMax (int) : (float)
The known maximum of the '_source'.
_newMin (int) : (float)
What you want the NEW minimum of the '_source' to be.
_newMax (int) : (float)
What you want the NEW maximum of the '_source' to be.
Returns: Outputs your previously bounded '_source', but now the value will only move between the '_newMin' and '_newMax'
values you set in the variables.
Normalize_Historical(_source, _minimumLvl, _maximumLvl)
Normalizes '_source' that has a previously unknown min/max(unbounded) determining the max & min of the '_source'
FROM THE ENTIRE CHARTS HISTORY. ]
Parameters:
_source (float) : (float)
Source to be normalized.
_minimumLvl (int) : (float)
The Lower Boundary Level.
_maximumLvl (int) : (float)
The Upper Boundary Level.
Returns: Returns your same '_source', but now the value will MOSTLY stay between the minimum and maximum values you set in the
'_minimumLvl' and '_maximumLvl' variables (ie. if the source you input is an RSI...the output is the same RSI value but
instead of moving between 0-100 it will move between the maxand min you set).
Normailize_Local(_source, _length, _minimumLvl, _maximumLvl)
Normalizes series with previously unknown min/max(unbounded). Much like the Normalize_Historical function above this one,
but rather than using the Highest/Lowest Values within the ENTIRE charts history, this on looks for the Highest/Lowest
values of '_source' within the last ___ bars (set by user as/in the '_length' parameter. ]
Parameters:
_source (float) : (float)
Source to be normalized.
_length (int) : (float)
The amount of bars to look back to determine the highest/lowest '_source' value.
_minimumLvl (int) : (float)
The Lower Boundary Level.
_maximumLvl (int) : (float)
The Upper Boundary Level.
Returns: Returns a single output variable being the previously unbounded '_source' that is now normalized and bound between
the values used for '_minimumLvl'/'_maximumLvl' of the '_source' within the user defined lookback period.
RSI mura visionOverview
The Enhanced RSI with Custom 40/60 Zones is a Pine Script™ v6 open-source indicator that builds on the classic Relative Strength Index by adding two additional horizontal levels at 40 and 60, alongside the standard 30/70. These extra zones help you identify early momentum shifts and distinguish trending markets from ranging ones with greater precision.
Key Features & Originality
* Custom Mid-Zones (40/60): Standard RSI signals can be noisy around the 50 midpoint. By marking 40 as a “weak momentum” threshold and 60 as a “strong momentum” confirmation, you get clearer entry and exit cues.
* Color-Coded Zones: The RSI line changes color when crossing 40, 50, 60, 70, and 30, letting you visually spot momentum acceleration or deceleration.
* Configurable Alerts: Built-in alert conditions fire when RSI crosses 40 or 60 in either direction, so you never miss a potential trend onset or exhaustion.
* Lightweight & Clean: No external dependencies, no look-ahead bias, and minimal repainting—ideal for both novice and professional traders.
How It Works
1. Momentum Decomposition: The standard 14-period RSI measures overbought/oversold extremes. Adding 40/60 lets you see when momentum shifts from neutral to bullish (crossing above 60) or bearish (dropping below 40) earlier than the classic 70/30 thresholds.
2. Trend Confirmation vs. Pullbacks: Readings between 40–60 often correspond to healthy pullbacks within a trend. A bounce off 40 suggests continuation; a rejection at 60 warns of a deeper pullback or reversal.
Usage & Inputs
* RSI Length (default 14): Period for calculating RSI.
* Level Inputs: Customize levels for overbought (70), support (60), neutral (50), weak (40), and oversold (30).
* Alert Toggles: Enable/disable alerts on each cross.
Why This Adds Value
* Early Signals: Capture trend beginnings before the market reaches extreme overbought/oversold levels.
* Noise Reduction: Filter sideways chop by watching the 40–60 corridor.
* Flexibility: Works on any timeframe or ticker.
Pine Script™ Version: v6
Open-Source License: MPL-2.0
Feel free to fork, modify, and share.
A_Taders_Edge_LIBRARYLibrary "A_Taders_Edge_LIBRARY"
RCI(_rciLength, _close, _interval, _outerMostRangeOfOscillator)
- You will see me using this a lot. DEFINITELY my favorite oscillator to utilize for SO many different things from timing entries/exits to determining trends.
Parameters:
_rciLength (int)
_close (float)
_interval (int)
_outerMostRangeOfOscillator (int)
Returns: - Outputs a single RCI value that will between (-)_outerMostRangeOfOscillator to (+)_outerMostRangeOfOscillator
InvalidTID(_close, _showInvalidAssets, _securityTickerid, _invalidArray)
- This is to add a table on the right of your chart that prints all the TickerID's that were either not formulated correctly in the scripts input or that is not a valid symbol and should be changed.
Parameters:
_close (float)
_showInvalidAssets (simple bool)
_securityTickerid (string)
_invalidArray (string )
Returns: - Does NOT return a value but rather the table with the invalid TickerID's from the scripts input that need to be changed.
LabelLocation(_firstLocation)
- This is ONLY for when you are wanting to print ALERT LABELS with the assets name for when an alert trigger occurs for that asset. There are a total of 40 assets that can be used in each copy of the script. You don't want labels from different assets printing on top of each other because you will not be able to read the asset name that the label is for. Ex. If you put your _firstLocation in the input settings as 1 and have 40 assets on this copy of the scanner then the first asset in the list is assigned to the location value 1 on the scale, and the 2nd in the list is assigned to location value 2...and so on. If your first location is set to 81 then the 1st asset is 81 and 2nd is 82 and so on.
Parameters:
_firstLocation (simple int)
Returns: - regardless of if you have the maximum amount of assets being screened (40 max), this export function will output 40 locations… So there needs to be 40 variables assigned to the tuple in this export function. What I mean by that is there needs to be 40 variables between the ' '. If you only have 20 assets in your scripts input settings, then only the first 20 variables within the ' ' Will be assigned to a value location and the other 20 will be assigned 'NA'.
SeparateTickerids(_string)
- You must form this single tickerID input string exactly as laid out in the water (a little gray circle at the end of the setting, that you hover your cursor over to read the details of). IF the string is formed correctly then it will break up. All of the tip rate is within the string into a total of 40 separate strings which will be all of the tickerIDs that the script is using in your MO scanner.
Parameters:
_string (simple string)
Returns: - this will output, 40 different security assets within the tuple output (ie. 40 variable within the ' ') regardless of if you were including 40 assets, to be screened in the MO Screener or not. if you have less than 40 assets, then once the variables are assigned to all of the tickerIDs, the rest of the variables will be assigned "NA".
TickeridForLabelsAndSecurity(_includeExchange, _ticker)
- this export function is used to output 2 tickerID strings. One is formulated to properly work in the request.security() function while the other is how it will appear on the asset name labels depending on how you form your assets string in the MO scanners input settings. Review the tooltip next to the setting, to learn how to form the string so that the asset name labels will appear how you want in the labels at the end of the line plots & the alert labels that would be triggered if the MO Scanner is set up to include Alert Trigger Labels.
Parameters:
_includeExchange (simple bool)
_ticker (simple string)
Returns: - this export function is used to output 2 tickerID strings. One is formulated to properly work in the request.security() function while the other is how it will appear on the asset name labels depending on how you form your assets string in the MO scanners input settings. Review the tooltip next to the setting, to learn how to form the string so that the asset name labels will appear how you want in the labels at the end of the line plots & the alert labels that would be triggered if the MO Scanner is set up to include Alert Trigger Labels.
PercentChange(_startingValue, _endingValue)
- this is a quick export function to calculate how much % change has occurred between the _startingValue and the _endingValue that you input into the export function.
Parameters:
_startingValue (float)
_endingValue (float)
Returns: - it will output a single percentage value between 0-100 with trailing numbers behind a decimal. If you want, only a certain amount of numbers behind the decimal, this export function needs to be put within a formatting function to do so. Explained in the MO Scanner INTRO VIDEO.
PrintedBarCount(_time, _barCntLength, _bcPmin)
- This export function will outfit the percentage of printed bars (that occurred within _barCntLength amount of time) out of the MAX amount of bars that potentially COULD HAVE been printed. Iexplanation in the MO Scanner INTRO VIDEO.
Parameters:
_time (int)
_barCntLength (int)
_bcPmin (int)
Returns: - Gives 2 outputs. The first is the total % of Printed Bars within the user set time period and second is true/false according to if the Printed BarCount % is above the _bcPmin threshold that you input into this export function.
ADX mura visionOverview
The Enhanced ADX with Custom 40/60 Levels is a Pine Script™ v6 open-source indicator that builds on the classic Average Directional Index by adding two critical thresholds at 40 and 60. These extra levels give you early warning of trend exhaustion and precise exit signals when paired with the mura indicator.
Key Features & Originality
Custom Thresholds (40/60): Beyond the standard ADX levels (25/50), levels at 40 and 60 mark advanced trend strength phases and highlight when momentum is beginning to fade.
Trend Weakness Alerts: Configurable alerts trigger when ADX dips below 60 or 40, signaling ideal exit opportunities before a full reversal.
Color-Coded ADX Line: The ADX line dynamically changes color upon crossing 40 and 60, making trend strength transitions instantly visible.
mura Indicator Synergy: Specially designed to complement the mura indicator—when mura signals an exit and ADX falls below your chosen threshold, you get a high-confidence cue to close your position.
How It Works
Advanced Trend Phases: ADX above 25 confirms a trend, above 40 indicates strong momentum, and above 60 signals extreme strength. A drop below 60 or 40 warns of weakening momentum.
Exit Confirmation: Combine a mura exit signal (e.g., dot flip or reversal) with an ADX cross below 40/60 to capture optimal exit points.
Usage & Inputs
ADX Length (default 14): Period for ADX calculation.
Level Inputs: Customize your threshold levels (default: 25, 40, 50, 60).
Alert Toggles: Enable alerts on crosses above or below each level.
Style Settings: Adjust line colors and widths for ADX and threshold lines.
Why This Adds Value
Early Exit Signals: Identify momentum loss before major reversals, protecting profits.
Cleaner Trade Management: Visual cues reduce guesswork when exiting trades.
Modular Design: Use standalone or integrate with mura for robust entry/exit workflows.
Pine Script™ Version: v6
Open-Source License: MPL-2.0
Strategy Template - V2This is an educational script created to demonstrate few basic building blocks of a trend based strategy and how to achieve different entry and exit types. My initial intention was to create a comprehensive strategy template which covers all the aspects of strategy. But, ended up creating fully fledged strategy based on trend following.
This is an enhancement on Strategy-Template But this script is comparitively more complex. Hence I decided to create new version instead of updating the existing one.
Lets dive deep.
SIMPLE COMPONENTS OF TREND FOLLOWING STRATEGY
TREND BIAS - This defines the direction of trend. Idea is not to trade against the trend direction. If the bias is bullish, look for long opportunities and if bias is bearish, look for short opportunities. Stay out of the market when the bias is neutral.
Often, trend bias is determined based on longer timeframe conditions. Example - 200 Moving Average, Higher timeframe moving averages, Higher timeframe high-lows etc. can be used for determining the trend bias.
In this script, I am using Weekly donchian channels combined with daily donchian channels to define trend bias.
Long Bias - 40 Day donchian channel sits completely in upper portion of 40 Week dochnial channel.
Short Bias - 40 Day donchian channel sits completely in lower portion of 40 Week donchian channel.
ENTRY CONDITION - Entry signals are generated only in the direction of bias. Hence, when in LongBias, we only get Long signals and when in short bias, we only get short signals.
In our case, when in Long Bias - if price hits 40 day high for the first time, this creates our long entry signal. Similarly when in Short Bias , price hitting 40 day low will create signal for going short. Since we do not take trades opposite to trend, no entry conditions are formed when price hits 40 day high in Short Bias or 40 day low in Long Bias.
EXIT CONDITION - Exit conditions are formed when we get signals of trend failure.
In our case, when in long trade, price hitting 40 day low creates exit signal. Similarly when in short trade price hitting 40 day high creates exit signal for short trade.
DIFFERENT TYPES OF ENTRY AND EXIT
In this script, I have tried to demonstrate different entry and exit types.
Entry types
Market - Enter immediately when entry signal is received. That is, in this case when price crossover over high in long bias and crosses under low in short bias
Stop - This method includes estimating at what level new highs are made and creating a stop buy order at that level. This way, we do not miss if the break out is stronger. But, susciptible to fail during fakeouts.
Limit - This method includes executing a limit order to buy at lower price or sell at higher price. In trend following methods, downside of limit order is when there is genuine breakout, these limit orders may not hit and during trend failures the limit orders are likely to hit and go straight to stop.
Stop-Limit - this is same as stop order but will also place a limit condition to avoid buying on overextended breakout or with lots of slippage.
Exit types
Market - whether to keep the existing trade running or whether to close it is determined after close of each bar and exit orders are executed manually upon receiving exit signal.
Stop - We place stop loss orders beforehand when there is a trade in place. This can help in avoiding big movements against trade within bar. But, this may also stop on false signals or fakeouts.
Take profit
Stop - No take profits are configured.
Target - 30% of the positions are closed when take profit levels are hit. Take profit levels are defined by risk reward.
USING THE CODE AS TEMPLATE
As mentioned earlier, I intended to create a fully fledged strategy template. But, ended up creating a fully fledged stratgy. However, you can take some part of this code and use it to start your own strategy. Will explain what all things can be adopted without worrying about the strategy implementation within
Strategy definition : This can be copied as is and just change the title of strategy. This defines some of the commonly used parameters of strategy which can help with close to realistic backtesting results for your coded strategy and comparison with buy and hold.
Generic Strategy Parameters : The parameter which defines controlling alllowed trade direction and trading window are present here. This again can be copied as is and variable inDateRange can be directly used in entry conditions.
Generic Methods : f_getMovingAverage and f_secureSecurity are handy and can be used as is. atr method provideded by pine gives you ATR based on RMA. If you want SMA or any other moving average based ATR, you can use the method f_getCustomAtr
Trade Statements : This section has all types of trading instructions which includes market/stop/limit/stop-limit type of entries and exits and take profit statements. You can adopt the type of entry you are interested in and change when condition to suit your strategy.
Trade conditions and levels : This section is required. But, cannot be copied. All the trade logic goes here which also sets parameters which are used in when of Trade Statements.
Hope this helps.
Risk & Position DashboardRisk & Position Dashboard
Overview
The Risk & Position Dashboard is a comprehensive trading tool designed to help traders calculate optimal position sizes, manage risk, and visualize potential profit/loss scenarios before entering trades. This indicator provides real-time calculations for position sizing based on account size, risk percentage, and stop-loss levels, while displaying multiple take-profit targets with customizable risk-reward ratios.
Key Features
Position Sizing & Risk Management:
Automatic position size calculation based on account size and risk percentage
Support for leveraged trading with maximum leverage limits
Fractional shares support for brokers that allow partial share trading
Real-time fee calculation including entry, stop-loss, and take-profit fees
Break-even price calculation including trading fees
Multi-Target Profit Management:
Support for up to 3 take-profit levels with individual portion allocations
Customizable risk-reward ratios for each take-profit target
Visual profit/loss zones displayed as colored boxes on the chart
Individual profit calculations for each take-profit level
Visual Dashboard:
Clean, customizable table display showing all key metrics
Configurable label positioning and styling options
Real-time tracking of whether stop-loss or take-profit levels have been reached
Color-coded visual zones for easy identification of risk and reward areas
Advanced Configuration:
Comprehensive input validation and error handling
Support for different chart timeframes and symbols
Customizable colors, fonts, and display options
Hide/show individual data fields for personalized dashboard views
How to Use
Set Account Parameters: Configure your account size, maximum risk percentage per trade, and trading fees in the "Account Settings" section.
Define Trade Setup: Use the "Entry" time picker to select your entry point on the chart, then input your entry price and stop-loss level.
Configure Take Profits: Set your desired risk-reward ratios and portion allocations for each take-profit level. The script supports 1-3 take-profit targets.
Analyze Results: The dashboard will automatically calculate and display position size, number of shares, potential profits/losses, fees, and break-even levels.
Visual Confirmation: Colored boxes on the chart show profit zones (green) and loss zones (red), with lines extending to current price levels.
Reset Entry and SL:
You can easily reset the entry and stop-loss by clicking the "Reset points..." button from the script's "More" menu.
This is useful if you want to quickly clear your current trade setup and start fresh without manually adjusting the points on the chart.
Calculations
The script performs sophisticated calculations including:
Position size based on risk amount and price difference between entry and stop-loss
Leverage requirements and position amount calculations
Fee-adjusted risk-reward ratios for realistic profit expectations
Break-even price including all trading costs
Individual profit calculations for partial position closures
Detailed Take-Profit Calculation Formula:
The take-profit prices are calculated using the following mathematical formula:
// Core variables:
// risk_amount = account_size * (risk_percentage / 100)
// total_risk_per_share = |entry_price - sl_price| + (entry_price * fee%) + (sl_price * fee%)
// shares = risk_amount / total_risk_per_share
// direction_factor = 1 for long positions, -1 for short positions
// Take-profit calculation:
net_win = total_risk_per_share * shares * RR_ratio
tp_price = (net_win + (direction_factor * entry_price * shares) + (entry_price * fee% * shares)) / (direction_factor * shares - fee% * shares)
Step-by-step example for a long position (based on screenshot):
Account Size: 2,000 USDT, Risk: 2% = 40 USDT
Entry: 102,062.9 USDT, Stop Loss: 102,178.4 USDT, Fee: 0.06%
Risk per share: |102,062.9 - 102,178.4| + (102,062.9 × 0.0006) + (102,178.4 × 0.0006) = 115.5 + 61.24 + 61.31 = 238.05 USDT
Shares: 40 ÷ 238.05 = 0.168 shares (rounded to 0.17 in display)
Position Size: 0.17 × 102,062.9 = 17,350.69 USDT
Position Amount (with 9x leverage): 17,350.69 ÷ 9 = 1,927.85 USDT
For 2:1 RR: Net win = 238.05 × 0.17 × 2 = 80.94 USDT
TP1 price = (80.94 + (1 × 102,062.9 × 0.17) + (102,062.9 × 0.0006 × 0.17)) ÷ (1 × 0.17 - 0.0006 × 0.17) = 101,464.7 USDT
For 3:1 RR: TP2 price = 101,226.7 USDT (following same formula with RR=3)
This ensures that after accounting for all fees, the actual risk-reward ratio matches the specified target ratio.
Risk Management Features
Maximum Trade Amount: Optional setting to limit position size regardless of account size
Leverage Limits: Built-in maximum leverage protection
Fee Integration: All calculations include realistic trading fees for accurate expectations
Validation: Automatic checking that take-profit portions sum to 100%
Historical Tracking: Visual indication when stop-loss or take-profit levels are reached (within last 5000 bars)
Understanding Max Trade Amount - Multiple Simultaneous Trades:
The "Max Trade Amount" feature is designed for traders who want to open multiple positions simultaneously while maintaining proper risk management. Here's how it works:
Key Concept:
- Risk percentage (2%) always applies to your full Account Size
- Max Trade Amount limits the capital allocated per individual trade
- This allows multiple trades with full risk on each trade
Example from Screenshot:
Account Size: 2,000 USDT
Max Trade Amount: 500 USDT
Risk per Trade: 2% × 2,000 = 40 USDT per trade
Stop Loss Distance: 0.11% from entry
Result: Position Size = 17,350.69 USDT with 35x leverage
Total Risk (including fees): 40.46 USDT
Multiple Trades Strategy:
With this setup, you can open:
Trade 1: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 2: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 3: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Trade 4: 40 USDT risk, 495.73 USDT position amount (35x leverage)
Total Portfolio Exposure:
- 4 simultaneous trades = 4 × 495.73 = 1,982.92 USDT position amount
- Total risk exposure = 4 × 40 = 160 USDT (8% of account)
Trend & Strength Detector TSDTrend Strength Detector (TSD)
*Objective Trend Quality Measurement for Educational Market Analysis*
Note: This mathematical framework is a proprietary quantitative model developed by Ario Pinelab, inspired by classical EMA, ADX, RSI and MACD principles, yet not documented in any public technical or academic publication.
## 🎯 Purpose & Design Philosophy
The ** Trend Strength Detector- TSD ** is an educational research tool that provides **quantitative measurement of trend quality** through two independent scoring systems (0-100 scale). It answers the analytical question: *"How strong and aligned is the current market trend environment?"*
This indicator is designed with a **modular, complementary approach** to work alongside various analysis methodologies, particularly pattern-based recognition systems.
## 🔗 Complementary Research Framework
### Designed to Work With Pattern Detection Systems
This indicator provides **environmental context measurement** that complements qualitative pattern recognition tools. It works particularly well alongside systems like:
- **RMBS Smart Detector - Multi-Factor Momentum System**
- Traditional chart pattern analyzers
- Any momentum-based pattern identification tools
🔍 **To find RMBS Smart Detector:**
- Search in TradingView Indicators Library: `" RMBS Smart Detector - Multi-Factor Momentum System"`
- Look for: *Multi-Factor Momentum System*
- By author: ` `
### Why This Complementary Approach?
**Trend Quality Measurement** (TSD - this tool) provides:
- ✅ Structural trend alignment (0-100 score)
- ✅ Momentum intensity levels (0-100 score)
- ✅ Environment classification (Strong/Moderate/Weak)
- 📌 **Answers:** *"HOW STRONG is the underlying trend environment?"*
### Educational Research Value
When used together in a research context, these tools enable systematic study of questions like:
- How do reversal patterns behave when Strength Score is above 70 vs below 30?
- Do continuation patterns in weakening environments (declining scores) show different characteristics?
- What is the correlation between high Alignment Scores and pattern "success rates"?
- Can environment classification help identify genuine trend initiation vs false starts?
⚠️ **Important Note:** Both tools are **independent and work standalone**. TSD provides value whether used alone or with other analysis methods. The relationship with RMBS (or any pattern tool) is **complementary for research purposes**, not dependent.
---
###Mathematical Foundation
##TSA Formula: scoring method developed by Ario
-Trend Model (0 – 100)
TAS = EMA Alignment (0–40) + Price Position (0–30) + Trend Consistency (0–30)
EMA Alignment checks EMA_fast vs EMA_slow vs EMA_trend structure.
Price Position evaluates if Close is above/below all EMAs.
Consistency = 3 × max(bullish,bearish bars within 10 candles).
-Strength Model (0 – 100)
Strength = ADX (0–50) + EMA Slope (0–25) + RSI (0–15) + MACD (0–10)
ADX measures trend energy; Slope shows EMA momentum %;
RSI assesses zone positioning; MACD confirms directional agreement.
Note: This formula represents a proprietary quantitative model by Ario_Pinelab, inspired by classical technical concepts but not published in any external reference.________________________________________
📊 Environment Classification
Based on Total Strength Score:
🟢 Strong Environment: Score ≥ 60
→ Well-defined momentum, clear directional bias
🟡 Moderate Environment: 40 ≤ Score < 60
→ Mixed signals, transitional conditions
🔴 Weak Environment: Score < 40
→ Ranging, choppy, low conviction movement
Color Coding:
• Green background: Strong (≥60)
• Yellow background: Moderate (40-59)
• Red background: Weak (<40)
________________________________________
📈 Visual Components
Main Chart Display
Score Labels (Top-Right Corner):
┌─────────────────────────────────┐
│ 📊 Alignment: 75 | Strength: 82 │
│ Environment: Strong 🟢 │
└─────────────────────────────────┘
Color-Coded Background:
• Environment strength visually indicated via background color
• Helps quick identification of market regime
• Customizable transparency (default: 90%)
Reference Lines:
• Dotted line at 60: Strong/Moderate threshold
• Dotted line at 40: Moderate/Weak threshold
• Mid-line at 50: Neutral reference
________________________________________
🔧 Customization Settings
Input Parameters
The best setting is the default mode.
🚫 Important Disclaimers & Limitations
What This Indicator IS:
✅ Educational measurement tool for trend quality research
✅ Quantitative assessment of current market environment
✅ Complementary analysis tool for pattern-based systems
✅ Historical data analyzer for systematic study
✅ Multi-factor scoring system based on technical calculations
What This Indicator IS NOT:
❌ NOT a trading system or signal generator
❌ NOT financial advice or trade recommendations
❌ NOT predictive of future price movements
❌ NOT a guarantee of pattern success/failure
❌ NOT a substitute for comprehensive risk management
________________________________________
Known Limitations
1. Lagging Nature:
⚠️ All components (EMA, ADX, RSI, MACD) are calculated
from historical price data
→ Scores reflect CURRENT and RECENT conditions
→ Cannot predict sudden reversals or black swan events
→ Trend measurements lag actual price turning points
2. Whipsaw Risk:
⚠️ In choppy/ranging markets, scores may fluctuate rapidly
→ Moderate zone (40-60) can see frequent transitions
→ Low timeframes more susceptible to noise
→ Consider higher timeframes for stable measurements
3. Component Conflicts:
⚠️ Individual components may disagree
→ Example: Strong ADX but weak RSI alignment
→ Scores average these conflicts (may hide nuance)
→ Check individual components for deeper insight
4. Not Predictive:
⚠️ High scores do NOT guarantee continuation
⚠️ Low scores do NOT guarantee reversal
→ Measurement ≠ Prediction
→ Use for CONTEXT, not SIGNALS
→ Combine with comprehensive analysis
________________________________________
Risk Acknowledgments
Market Risk:
• All trading involves substantial risk of loss
• Past performance (even systematic studies) does not guarantee future results
• No indicator, system, or methodology can eliminate market risk
Measurement Limitations:
• Scores are mathematical calculations, not market predictions
• Environmental classification is descriptive, not prescriptive
• Strong measurements can deteriorate rapidly without warning
Educational Purpose:
• This tool is designed for LEARNING about market structure
• Not designed, tested, or validated as a standalone trading system
• Any trading decisions are user’s sole responsibility
No Warranty:
• Indicator provided “as-is” for educational purposes
• No guarantee of accuracy, reliability, or profitability
• Users must verify calculations and apply critical thinking
Open Source
Full Pine Script code available for educational study and modification. Feedback and improvement suggestions welcome.
“All logic is presented for research and educational visualization.”
---
DAX ORB Ultimate - ALGO Suite//@version=5
indicator("DAX ORB Ultimate - ALGO Suite", overlay=true, max_labels_count=200, max_lines_count=100)
// ═══════════════════════════════════════════════════════════════════════════════
// DAX OPENING RANGE BREAKOUT - ULTIMATE EDITION
// Real-time ORB building | Multi-timeframe support | Key levels with bias
// Works on ANY timeframe - uses M1 data for ORB construction
// ═══════════════════════════════════════════════════════════════════════════════
// ════════════════════════ INPUTS ════════════════════════
orb_start_h = input.int(7, "Start Hour (UTC)", minval=0, maxval=23, group="ORB Settings")
orb_start_m = input.int(40, "Start Minute", minval=0, maxval=59, group="ORB Settings")
orb_end_h = input.int(8, "End Hour (UTC)", minval=0, maxval=23, group="ORB Settings")
orb_end_m = input.int(0, "End Minute", minval=0, maxval=59, group="ORB Settings")
exclude_wicks = input.bool(true, "Exclude Wicks", group="ORB Settings")
close_hour = input.int(16, "Market Close Hour", minval=0, maxval=23, group="ORB Settings")
use_tf = input.bool(true, "1. Trend Following", group="Strategies")
use_mr = input.bool(true, "2. Mean Reversion", group="Strategies")
use_sa = input.bool(true, "3. Statistical Arb", group="Strategies")
use_mm = input.bool(true, "4. Market Making", group="Strategies")
use_ba = input.bool(true, "5. Basis Arb", group="Strategies")
use_ema = input.bool(true, "EMA Filter", group="Technical Filters")
use_rsi = input.bool(true, "RSI Filter", group="Technical Filters")
use_macd = input.bool(true, "MACD Filter", group="Technical Filters")
use_vol = input.bool(true, "Volume Filter", group="Technical Filters")
use_bb = input.bool(true, "Bollinger Filter", group="Technical Filters")
use_fixed = input.bool(false, "Fixed SL/TP", group="Risk Management")
fixed_sl = input.float(50, "Fixed SL Points", minval=10, group="Risk Management")
fixed_tp = input.float(150, "Fixed TP Points", minval=10, group="Risk Management")
atr_sl = input.float(2.0, "ATR SL Mult", minval=0.5, group="Risk Management")
atr_tp = input.float(3.0, "ATR TP Mult", minval=0.5, group="Risk Management")
min_rr = input.float(2.0, "Min R:R", minval=1.0, group="Risk Management")
show_dash = input.bool(true, "Show Dashboard", group="Display")
show_lines = input.bool(true, "Show Lines", group="Display")
show_levels = input.bool(true, "Show Key Levels", group="Display")
// ════════════════════════ FUNCTIONS ════════════════════════
is_orb_period(_h, _m) =>
start = orb_start_h * 60 + orb_start_m
end = orb_end_h * 60 + orb_end_m
curr = _h * 60 + _m
curr >= start and curr < end
orb_ended(_h, _m) =>
end = orb_end_h * 60 + orb_end_m
curr = _h * 60 + _m
curr == end
is_market_open() =>
h = hour(time)
h >= orb_start_h and h <= close_hour
// ════════════════════════ DATA GATHERING (M1) ════════════════════════
// Get M1 data for ORB construction (works on ANY chart timeframe)
= request.security(syminfo.tickerid, "1", , barmerge.gaps_off, barmerge.lookahead_off)
// Daily data
d_high = request.security(syminfo.tickerid, "D", high, barmerge.gaps_off, barmerge.lookahead_on)
d_low = request.security(syminfo.tickerid, "D", low, barmerge.gaps_off, barmerge.lookahead_on)
d_open = request.security(syminfo.tickerid, "D", open, barmerge.gaps_off, barmerge.lookahead_on)
// Current day high/low (intraday)
var float today_high = na
var float today_low = na
var float prev_day_high = na
var float prev_day_low = na
var float yest_size = 0
if ta.change(time("D")) != 0
prev_day_high := d_high
prev_day_low := d_low
yest_size := d_high - d_low
today_high := high
today_low := low
else
today_high := math.max(na(today_high) ? high : today_high, high)
today_low := math.min(na(today_low) ? low : today_low, low)
// ════════════════════════ ORB CONSTRUCTION (REAL-TIME) ════════════════════════
var float orb_h = na
var float orb_l = na
var bool orb_ready = false
var float orb_building_h = na
var float orb_building_l = na
var bool is_building = false
// Get M1 bar time components
m1_hour = hour(m1_time)
m1_minute = minute(m1_time)
// Reset daily
if ta.change(time("D")) != 0
orb_h := na
orb_l := na
orb_ready := false
orb_building_h := na
orb_building_l := na
is_building := false
// Build ORB using M1 data
if is_orb_period(m1_hour, m1_minute) and not orb_ready
is_building := true
val_h = exclude_wicks ? m1_close : m1_high
val_l = exclude_wicks ? m1_close : m1_low
if na(orb_building_h)
orb_building_h := val_h
orb_building_l := val_l
else
orb_building_h := math.max(orb_building_h, val_h)
orb_building_l := math.min(orb_building_l, val_l)
// FIX #1: Set is_building to false when NOT in ORB period anymore
if not is_orb_period(m1_hour, m1_minute) and is_building and not orb_ready
is_building := false
// Finalize ORB when period ends
if orb_ended(m1_hour, m1_minute) and not orb_ready
orb_h := orb_building_h
orb_l := orb_building_l
orb_ready := true
is_building := false
// Display building values in real-time
current_orb_h = is_building ? orb_building_h : orb_h
current_orb_l = is_building ? orb_building_l : orb_l
// ════════════════════════ INDICATORS ════════════════════════
ema9 = ta.ema(close, 9)
ema21 = ta.ema(close, 21)
ema50 = ta.ema(close, 50)
rsi = ta.rsi(close, 14)
= ta.macd(close, 12, 26, 9)
= ta.bb(close, 20, 2)
atr = ta.atr(14)
vol_ma = ta.sma(volume, 20)
// ════════════════════════ STRATEGY SIGNALS ════════════════════════
// 1. Trend Following
tf_short = ta.sma(close, 10)
tf_long = ta.sma(close, 30)
tf_bull = tf_short > tf_long
tf_bear = tf_short < tf_long
// 2. Mean Reversion
mr_mean = ta.sma(close, 20)
mr_dev = (close - mr_mean) / mr_mean * 100
mr_bull = mr_dev <= -0.5
mr_bear = mr_dev >= 0.5
// 3. Statistical Arb
sa_mean = ta.sma(close, 120)
sa_std = ta.stdev(close, 120)
sa_z = sa_std > 0 ? (close - sa_mean) / sa_std : 0
var string sa_st = "flat"
if sa_st == "flat"
if sa_z <= -2.0
sa_st := "long"
else if sa_z >= 2.0
sa_st := "short"
else if math.abs(sa_z) <= 0.5 or math.abs(sa_z) >= 4.0
sa_st := "flat"
sa_bull = sa_st == "long"
sa_bear = sa_st == "short"
// 4. Market Making
mm_spread = (high - low) / close * 100
mm_mid = (high + low) / 2
mm_bull = close < mm_mid and mm_spread >= 0.5
mm_bear = close > mm_mid and mm_spread >= 0.5
// 5. Basis Arb
ba_fair = ta.sma(close, 50)
ba_bps = ba_fair != 0 ? (close - ba_fair) / ba_fair * 10000 : 0
ba_bull = ba_bps <= -8.0
ba_bear = ba_bps >= 8.0
// Vote counting
bull_v = 0
bear_v = 0
if use_tf
bull_v := bull_v + (tf_bull ? 1 : 0)
bear_v := bear_v + (tf_bear ? 1 : 0)
if use_mr
bull_v := bull_v + (mr_bull ? 1 : 0)
bear_v := bear_v + (mr_bear ? 1 : 0)
if use_sa
bull_v := bull_v + (sa_bull ? 1 : 0)
bear_v := bear_v + (sa_bear ? 1 : 0)
if use_mm
bull_v := bull_v + (mm_bull ? 1 : 0)
bear_v := bear_v + (mm_bear ? 1 : 0)
if use_ba
bull_v := bull_v + (ba_bull ? 1 : 0)
bear_v := bear_v + (ba_bear ? 1 : 0)
// Technical filters - Simplified scoring system
ema_ok_b = not use_ema or (ema9 > ema21 and close > ema50)
ema_ok_s = not use_ema or (ema9 < ema21 and close < ema50)
rsi_ok_b = not use_rsi or (rsi > 40 and rsi < 80) // More lenient
rsi_ok_s = not use_rsi or (rsi < 60 and rsi > 20) // More lenient
macd_ok_b = not use_macd or macd > sig
macd_ok_s = not use_macd or macd < sig
vol_ok = not use_vol or volume > vol_ma * 1.2 // More lenient
bb_ok_b = not use_bb or close > bb_mid
bb_ok_s = not use_bb or close < bb_mid
// Technical score (need at least 2 out of 5 filters)
tech_score_b = (ema_ok_b ? 1 : 0) + (rsi_ok_b ? 1 : 0) + (macd_ok_b ? 1 : 0) + (bb_ok_b ? 1 : 0) + (vol_ok ? 1 : 0)
tech_score_s = (ema_ok_s ? 1 : 0) + (rsi_ok_s ? 1 : 0) + (macd_ok_s ? 1 : 0) + (bb_ok_s ? 1 : 0) + (vol_ok ? 1 : 0)
tech_bull = tech_score_b >= 2
tech_bear = tech_score_s >= 2
// Breakout - SIMPLIFIED (just need close above/below ORB)
brk_bull = orb_ready and close > current_orb_h
brk_bear = orb_ready and close < current_orb_l
// Consensus - At least 2 strategies agree (not majority)
total_st = (use_tf ? 1 : 0) + (use_mr ? 1 : 0) + (use_sa ? 1 : 0) + (use_mm ? 1 : 0) + (use_ba ? 1 : 0)
consensus_b = bull_v >= 2
consensus_s = bear_v >= 2
// Final signals - MUCH MORE LENIENT
daily_ok = yest_size >= 50 // Reduced from 100
buy = brk_bull and consensus_b and tech_bull and is_market_open()
sell = brk_bear and consensus_s and tech_bear and is_market_open()
// ════════════════════════ SL/TP ════════════════════════
// IMMEDIATE SL/TP LEVELS - Calculated as soon as ORB is ready (at 8:00)
var float long_entry = na
var float long_sl = na
var float long_tp = na
var float short_entry = na
var float short_sl = na
var float short_tp = na
// Calculate potential levels immediately when ORB is ready
if orb_ready and not na(orb_h) and not na(orb_l)
// Long scenario: Entry at ORB high breakout
long_entry := orb_h
long_sl := use_fixed ? long_entry - fixed_sl : long_entry - atr * atr_sl
long_tp := use_fixed ? long_entry + fixed_tp : long_entry + atr * atr_tp
// Short scenario: Entry at ORB low breakout
short_entry := orb_l
short_sl := use_fixed ? short_entry + fixed_sl : short_entry + atr * atr_sl
short_tp := use_fixed ? short_entry - fixed_tp : short_entry - atr * atr_tp
// Signal-based entry tracking (for dashboard and alerts)
var float buy_entry = na
var float buy_sl = na
var float buy_tp = na
var float sell_entry = na
var float sell_sl = na
var float sell_tp = na
if buy
buy_entry := close
buy_sl := use_fixed ? buy_entry - fixed_sl : buy_entry - atr * atr_sl
buy_tp := use_fixed ? buy_entry + fixed_tp : buy_entry + atr * atr_tp
if sell
sell_entry := close
sell_sl := use_fixed ? sell_entry + fixed_sl : sell_entry + atr * atr_sl
sell_tp := use_fixed ? sell_entry - fixed_tp : sell_entry - atr * atr_tp
buy_rr = not na(buy_entry) ? (buy_tp - buy_entry) / (buy_entry - buy_sl) : 0
sell_rr = not na(sell_entry) ? (sell_entry - sell_tp) / (sell_sl - sell_entry) : 0
buy_final = buy and buy_rr >= min_rr
sell_final = sell and sell_rr >= min_rr
// ════════════════════════ TRAILING STOPS ════════════════════════
// Trailing Stop Loss and Take Profit Management
var float trailing_sl_long = na
var float trailing_sl_short = na
var float trailing_tp_long = na
var float trailing_tp_short = na
var bool in_long = false
var bool in_short = false
var float highest_since_entry = na
var float lowest_since_entry = na
// Enter long position
if buy_final and not in_long
in_long := true
in_short := false
trailing_sl_long := buy_sl
trailing_tp_long := buy_tp
highest_since_entry := close
// Enter short position
if sell_final and not in_short
in_short := true
in_long := false
trailing_sl_short := sell_sl
trailing_tp_short := sell_tp
lowest_since_entry := close
// Update trailing stops for LONG
if in_long
// Track highest price since entry
highest_since_entry := math.max(highest_since_entry, high)
// Trail stop loss (moves up as price moves up)
// When price moves 1 ATR in profit, move SL to breakeven
// When price moves 2 ATR in profit, move SL to +1 ATR
profit_atr = (highest_since_entry - buy_entry) / atr
if profit_atr >= 2.0
trailing_sl_long := math.max(trailing_sl_long, buy_entry + atr * 1.0)
else if profit_atr >= 1.0
trailing_sl_long := math.max(trailing_sl_long, buy_entry)
// Smart trailing TP - extends TP if strong momentum
if highest_since_entry > trailing_tp_long * 0.9 and rsi > 60 // Within 10% of TP and strong momentum
trailing_tp_long := trailing_tp_long + atr * 0.5 // Extend TP
// Exit conditions
if close <= trailing_sl_long or close >= trailing_tp_long
in_long := false
trailing_sl_long := na
trailing_tp_long := na
highest_since_entry := na
// Update trailing stops for SHORT
if in_short
// Track lowest price since entry
lowest_since_entry := math.min(lowest_since_entry, low)
// Trail stop loss (moves down as price moves down)
profit_atr = (sell_entry - lowest_since_entry) / atr
if profit_atr >= 2.0
trailing_sl_short := math.min(trailing_sl_short, sell_entry - atr * 1.0)
else if profit_atr >= 1.0
trailing_sl_short := math.min(trailing_sl_short, sell_entry)
// Smart trailing TP - extends TP if strong momentum
if lowest_since_entry < trailing_tp_short * 1.1 and rsi < 40 // Within 10% of TP and strong momentum
trailing_tp_short := trailing_tp_short - atr * 0.5 // Extend TP
// Exit conditions
if close >= trailing_sl_short or close <= trailing_tp_short
in_short := false
trailing_sl_short := na
trailing_tp_short := na
lowest_since_entry := na
// ════════════════════════ ANALYTICS ════════════════════════
prob_strat = total_st > 0 ? math.max(bull_v, bear_v) / total_st * 100 : 50
prob_tech = (tech_bull or tech_bear) ? 75 : 35
prob_vol = vol_ok ? 85 : 50
prob_daily = daily_ok ? 85 : 30
prob_orb = orb_ready ? 80 : 20
probability = prob_strat * 0.3 + prob_tech * 0.25 + prob_vol * 0.15 + prob_daily * 0.15 + prob_orb * 0.15
dir_score = 0
dir_score := dir_score + (ema9 > ema21 ? 2 : -2)
dir_score := dir_score + (tf_bull ? 2 : -2)
dir_score := dir_score + (macd > sig ? 1 : -1)
dir_score := dir_score + (rsi > 50 ? 1 : -1)
direction = dir_score >= 2 ? "STRONG BULL" : (dir_score > 0 ? "BULL" : (dir_score <= -2 ? "STRONG BEAR" : (dir_score < 0 ? "BEAR" : "NEUTRAL")))
clean_trend = math.abs(ema9 - ema21) / close * 100
clean_noise = atr / close * 100
clean_struct = close > ema9 and close > ema21 and close > ema50 or close < ema9 and close < ema21 and close < ema50
clean_score = (clean_trend > 0.5 ? 30 : 10) + (clean_noise < 1.5 ? 30 : 10) + (clean_struct ? 40 : 10)
quality = clean_score >= 70 ? "CLEAN" : (clean_score >= 50 ? "GOOD" : (clean_score >= 30 ? "OK" : "CHOPPY"))
mom = ta.mom(close, 10)
mom_str = math.abs(mom) / close * 100
vol_rat = atr / ta.sma(atr, 20)
movement = buy_final or sell_final ? (mom_str > 0.8 and vol_rat > 1.3 ? "STRONG" : (mom_str > 0.5 ? "MODERATE" : "GRADUAL")) : "WAIT"
ok_score = (daily_ok ? 25 : 0) + (orb_ready ? 25 : 0) + (is_market_open() ? 20 : 0) + (clean_score >= 50 ? 20 : 5) + (probability >= 60 ? 10 : 0)
ok_trade = ok_score >= 65
// ════════════════════════ KEY LEVELS WITH BIAS ════════════════════════
// Calculate potential reaction levels with directional bias
var float key_levels = array.new_float(0)
var string key_bias = array.new_string(0)
if barstate.islast and show_levels
array.clear(key_levels)
array.clear(key_bias)
// Add levels with bias
if not na(current_orb_h)
array.push(key_levels, current_orb_h)
array.push(key_bias, consensus_b ? "BULL BREAK" : "RESISTANCE")
if not na(current_orb_l)
array.push(key_levels, current_orb_l)
array.push(key_bias, consensus_s ? "BEAR BREAK" : "SUPPORT")
if not na(prev_day_high)
array.push(key_levels, prev_day_high)
bias_pdh = close > prev_day_high ? "BULLISH" : (close < prev_day_high and close > prev_day_high * 0.995 ? "WATCH" : "RESIST")
array.push(key_bias, bias_pdh)
if not na(prev_day_low)
array.push(key_levels, prev_day_low)
bias_pdl = close < prev_day_low ? "BEARISH" : (close > prev_day_low and close < prev_day_low * 1.005 ? "WATCH" : "SUPPORT")
array.push(key_bias, bias_pdl)
if not na(today_high)
array.push(key_levels, today_high)
array.push(key_bias, "TODAY HIGH")
if not na(today_low)
array.push(key_levels, today_low)
array.push(key_bias, "TODAY LOW")
// Add EMA50 as dynamic level
array.push(key_levels, ema50)
ema_bias = close > ema50 ? "BULL SUPPORT" : "BEAR RESIST"
array.push(key_bias, ema_bias)
// ════════════════════════ VISUALS ════════════════════════
// Previous day lines
plot(show_lines ? prev_day_high : na, "Prev Day H", color.new(color.yellow, 0), 1, plot.style_line)
plot(show_lines ? prev_day_low : na, "Prev Day L", color.new(color.orange, 0), 1, plot.style_line)
// Current day high/low
plot(show_lines ? today_high : na, "Today High", color.new(color.lime, 40), 2, plot.style_circles)
plot(show_lines ? today_low : na, "Today Low", color.new(color.red, 40), 2, plot.style_circles)
// ORB lines (show building values in real-time with separate plots)
// Building phase - circles (orange during building)
plot(show_lines and is_building and not na(current_orb_h) ? current_orb_h : na, "ORB High Building", color.new(color.orange, 30), 3, plot.style_circles)
plot(show_lines and is_building and not na(current_orb_l) ? current_orb_l : na, "ORB Low Building", color.new(color.orange, 30), 3, plot.style_circles)
// Ready phase - ULTRA BRIGHT solid lines
plot(show_lines and not is_building and not na(current_orb_h) ? current_orb_h : na, "ORB High Ready", color.new(color.aqua, 0), 4, plot.style_line)
plot(show_lines and not is_building and not na(current_orb_l) ? current_orb_l : na, "ORB Low Ready", color.new(color.aqua, 0), 4, plot.style_line)
// ORB zone fill
p1 = plot(not na(current_orb_h) ? current_orb_h : na, display=display.none)
p2 = plot(not na(current_orb_l) ? current_orb_l : na, display=display.none)
fill_color = is_building ? color.new(color.blue, 93) : color.new(color.blue, 88)
fill(p1, p2, fill_color, title="ORB Zone")
// FIX #2: Draw ORB rectangle box ONLY ONCE when ready (use var to track if already drawn)
var box orb_box = na
var int orb_start_bar = na
var bool orb_box_drawn = false
// Reset box drawn flag on new day
if ta.change(time("D")) != 0
orb_box_drawn := false
// Capture the bar when ORB becomes ready
if orb_ready and not orb_ready
orb_start_bar := bar_index
orb_box_drawn := false // Allow new box to be drawn
// Draw box ONLY ONCE when ORB first becomes ready
if orb_ready and not orb_box_drawn and not na(orb_h) and not na(orb_l) and show_lines
if not na(orb_box)
box.delete(orb_box)
// Ultra clear rectangle with thick bright borders
box_color = color.new(color.aqua, 85) // Bright aqua fill
border_color = color.new(color.aqua, 0) // Solid bright aqua border
orb_box := box.new(orb_start_bar, orb_h, bar_index + 50, orb_l,
border_color=border_color,
border_width=3, // Thicker border
bgcolor=box_color,
extend=extend.right,
text="ORB ZONE",
text_size=size.normal, // Larger text
text_color=color.new(color.aqua, 0)) // Bright text
orb_box_drawn := true
// Update box right edge on each bar (without creating new box)
if orb_box_drawn and not na(orb_box) and show_lines
box.set_right(orb_box, bar_index)
// EMAs
plot(use_ema ? ema9 : na, "EMA9", color.new(color.blue, 20), 1)
plot(use_ema ? ema21 : na, "EMA21", color.new(color.orange, 20), 1)
plot(use_ema ? ema50 : na, "EMA50", color.new(color.purple, 30), 2)
// Signals
plotshape(buy_final, "BUY", shape.triangleup, location.belowbar, color.new(color.lime, 0), size=size.small, text="BUY")
plotshape(sell_final, "SELL", shape.triangledown, location.abovebar, color.new(color.red, 0), size=size.small, text="SELL")
// Exit signals
plotshape(in_long and not in_long, "EXIT LONG", shape.xcross, location.abovebar, color.new(color.orange, 0), size=size.tiny, text="EXIT")
plotshape(in_short and not in_short, "EXIT SHORT", shape.xcross, location.belowbar, color.new(color.orange, 0), size=size.tiny, text="EXIT")
// Trailing stop lines
plot(in_long and not na(trailing_sl_long) ? trailing_sl_long : na, "Trail SL Long", color.new(color.red, 0), 2, plot.style_cross)
plot(in_long and not na(trailing_tp_long) ? trailing_tp_long : na, "Trail TP Long", color.new(color.lime, 0), 2, plot.style_cross)
plot(in_short and not na(trailing_sl_short) ? trailing_sl_short : na, "Trail SL Short", color.new(color.red, 0), 2, plot.style_cross)
plot(in_short and not na(trailing_tp_short) ? trailing_tp_short : na, "Trail TP Short", color.new(color.lime, 0), 2, plot.style_cross)
// FIX #3: IMMEDIATE SL/TP LINES - Draw ONLY ONCE when ORB is ready
var line long_sl_ln = na
var line long_tp_ln = na
var line short_sl_ln = na
var line short_tp_ln = na
var label long_sl_lbl = na
var label long_tp_lbl = na
var label short_sl_lbl = na
var label short_tp_lbl = na
var bool sltp_lines_drawn = false
// Reset lines drawn flag on new day
if ta.change(time("D")) != 0
sltp_lines_drawn := false
// Draw lines ONLY ONCE when ORB first becomes ready
if orb_ready and not orb_ready and show_lines
sltp_lines_drawn := false // Allow new lines to be drawn
if orb_ready and not sltp_lines_drawn and show_lines
// Delete old lines
if not na(long_sl_ln)
line.delete(long_sl_ln)
line.delete(long_tp_ln)
line.delete(short_sl_ln)
line.delete(short_tp_ln)
label.delete(long_sl_lbl)
label.delete(long_tp_lbl)
label.delete(short_sl_lbl)
label.delete(short_tp_lbl)
// LONG scenario (green - bullish breakout above ORB high)
if not na(long_sl) and not na(long_tp)
long_sl_ln := line.new(bar_index, long_sl, bar_index + 100, long_sl, color=color.new(color.red, 0), width=2, style=line.style_solid, extend=extend.right)
long_tp_ln := line.new(bar_index, long_tp, bar_index + 100, long_tp, color=color.new(color.lime, 0), width=2, style=line.style_solid, extend=extend.right)
long_sl_lbl := label.new(bar_index, long_sl, "LONG SL: " + str.tostring(long_sl, "#.##"), style=label.style_label_left, color=color.new(color.red, 0), textcolor=color.white, size=size.small)
long_tp_lbl := label.new(bar_index, long_tp, "LONG TP: " + str.tostring(long_tp, "#.##"), style=label.style_label_left, color=color.new(color.lime, 0), textcolor=color.black, size=size.small)
// SHORT scenario (red - bearish breakout below ORB low)
if not na(short_sl) and not na(short_tp)
short_sl_ln := line.new(bar_index, short_sl, bar_index + 100, short_sl, color=color.new(color.red, 0), width=2, style=line.style_solid, extend=extend.right)
short_tp_ln := line.new(bar_index, short_tp, bar_index + 100, short_tp, color=color.new(color.lime, 0), width=2, style=line.style_solid, extend=extend.right)
short_sl_lbl := label.new(bar_index, short_sl, "SHORT SL: " + str.tostring(short_sl, "#.##"), style=label.style_label_left, color=color.new(color.red, 0), textcolor=color.white, size=size.small)
short_tp_lbl := label.new(bar_index, short_tp, "SHORT TP: " + str.tostring(short_tp, "#.##"), style=label.style_label_left, color=color.new(color.lime, 0), textcolor=color.black, size=size.small)
sltp_lines_drawn := true
// FIX #4: Key level labels - Track and delete old labels to prevent duplication
var label key_level_labels = array.new_label(0)
// Delete all old key level labels
if array.size(key_level_labels) > 0
for i = 0 to array.size(key_level_labels) - 1
label.delete(array.get(key_level_labels, i))
array.clear(key_level_labels)
// Create key level labels only on last bar
if barstate.islast and show_levels and array.size(key_levels) > 0
for i = 0 to array.size(key_levels) - 1
lvl = array.get(key_levels, i)
bias = array.get(key_bias, i)
// Color based on bias
lbl_color = str.contains(bias, "BULL") ? color.new(color.green, 70) : (str.contains(bias, "BEAR") ? color.new(color.red, 70) : (str.contains(bias, "SUPPORT") ? color.new(color.blue, 70) : (str.contains(bias, "RESIST") ? color.new(color.orange, 70) : color.new(color.gray, 70))))
txt_color = str.contains(bias, "BULL") ? color.green : (str.contains(bias, "BEAR") ? color.red : (str.contains(bias, "SUPPORT") ? color.blue : (str.contains(bias, "RESIST") ? color.orange : color.gray)))
new_lbl = label.new(bar_index + 2, lvl, str.tostring(lvl, "#.##") + "\n" + bias, style=label.style_label_left, color=lbl_color, textcolor=txt_color, size=size.tiny, textalign=text.align_left)
array.push(key_level_labels, new_lbl)
// FIX #5: Compact chart info labels - Track and delete to prevent duplication
var label prob_label = na
var label dir_label = na
if barstate.islast and show_lines
// Delete old labels
if not na(prob_label)
label.delete(prob_label)
if not na(dir_label)
label.delete(dir_label)
// Create new labels
prob_c = probability >= 70 ? color.green : (probability >= 50 ? color.yellow : color.red)
prob_label := label.new(bar_index, high + atr * 1.2, str.tostring(probability, "#") + "%", style=label.style_none, textcolor=prob_c, size=size.small)
dir_c = str.contains(direction, "BULL") ? color.green : (str.contains(direction, "BEAR") ? color.red : color.gray)
dir_label := label.new(bar_index, high + atr * 2, direction, style=label.style_none, textcolor=dir_c, size=size.tiny)
// ════════════════════════ DASHBOARD ════════════════════════
var table dash = table.new(position.top_right, 2, 20, bgcolor=color.new(color.black, 5), border_width=1, border_color=color.new(color.gray, 60))
if barstate.islast and show_dash
r = 0
// Header
table.cell(dash, 0, r, "DAX ORB ULTIMATE", text_color=color.white, bgcolor=color.new(color.blue, 30), text_size=size.small)
table.cell(dash, 1, r, timeframe.period, text_color=color.yellow, bgcolor=color.new(color.blue, 30), text_size=size.tiny)
// Current Day
r += 1
table.cell(dash, 0, r, "TODAY H/L", text_color=color.aqua, text_size=size.tiny)
table.cell(dash, 1, r, "", text_color=color.white)
r += 1
table.cell(dash, 0, r, "High", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(today_high, "#.##"), text_color=color.lime, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Low", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(today_low, "#.##"), text_color=color.red, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Range", text_color=color.gray, text_size=size.tiny)
today_range = today_high - today_low
table.cell(dash, 1, r, str.tostring(today_range, "#") + "p", text_color=color.aqua, text_size=size.tiny)
// Previous Day
r += 1
table.cell(dash, 0, r, "PREV H/L", text_color=color.aqua, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(yest_size, "#") + "p", text_color=daily_ok ? color.lime : color.red, text_size=size.tiny)
// ORB Status with real-time values
r += 1
table.cell(dash, 0, r, "ORB 7:40-8:00", text_color=color.aqua, text_size=size.tiny)
orb_status = is_building ? "BUILDING" : (orb_ready ? "READY" : "WAIT")
orb_clr = is_building ? color.orange : (orb_ready ? color.lime : color.gray)
table.cell(dash, 1, r, orb_status, text_color=orb_clr, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "High", text_color=color.gray, text_size=size.tiny)
orb_h_txt = not na(current_orb_h) ? str.tostring(current_orb_h, "#.##") : "---"
table.cell(dash, 1, r, orb_h_txt, text_color=is_building ? color.orange : color.green, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Low", text_color=color.gray, text_size=size.tiny)
orb_l_txt = not na(current_orb_l) ? str.tostring(current_orb_l, "#.##") : "---"
table.cell(dash, 1, r, orb_l_txt, text_color=is_building ? color.orange : color.red, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Size", text_color=color.gray, text_size=size.tiny)
orb_size = not na(current_orb_h) and not na(current_orb_l) ? current_orb_h - current_orb_l : 0
table.cell(dash, 1, r, str.tostring(orb_size, "#") + "p", text_color=color.yellow, text_size=size.tiny)
// Strategies
r += 1
table.cell(dash, 0, r, "STRATEGIES", text_color=color.aqua, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(bull_v) + "B " + str.tostring(bear_v) + "S", text_color=color.yellow, text_size=size.tiny)
// Analytics
r += 1
table.cell(dash, 0, r, "PROBABILITY", text_color=color.white, bgcolor=color.new(color.purple, 70), text_size=size.small)
prob_c = probability >= 70 ? color.lime : (probability >= 50 ? color.yellow : color.red)
table.cell(dash, 1, r, str.tostring(probability, "#") + "%", text_color=prob_c, bgcolor=color.new(color.purple, 70), text_size=size.small)
r += 1
table.cell(dash, 0, r, "Direction", text_color=color.gray, text_size=size.tiny)
dir_c = str.contains(direction, "BULL") ? color.lime : (str.contains(direction, "BEAR") ? color.red : color.gray)
table.cell(dash, 1, r, direction, text_color=dir_c, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Chart", text_color=color.gray, text_size=size.tiny)
qual_c = quality == "CLEAN" ? color.lime : (quality == "GOOD" ? color.green : (quality == "OK" ? color.yellow : color.red))
table.cell(dash, 1, r, quality, text_color=qual_c, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "OK Trade?", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, ok_trade ? "YES" : "NO", text_color=ok_trade ? color.lime : color.red, text_size=size.tiny)
// Position Status
r += 1
pos_txt = in_long ? "IN LONG" : (in_short ? "IN SHORT" : "NO POSITION")
pos_c = in_long ? color.lime : (in_short ? color.red : color.gray)
table.cell(dash, 0, r, "POSITION", text_color=color.white, bgcolor=color.new(color.blue, 50), text_size=size.small)
table.cell(dash, 1, r, pos_txt, text_color=pos_c, bgcolor=color.new(color.blue, 50), text_size=size.small)
// Show trailing stops if in position
if in_long and not na(trailing_sl_long)
r += 1
table.cell(dash, 0, r, "Trail SL", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(trailing_sl_long, "#.##"), text_color=color.red, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Trail TP", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(trailing_tp_long, "#.##"), text_color=color.lime, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Profit", text_color=color.gray, text_size=size.tiny)
pnl = close - buy_entry
pnl_c = pnl > 0 ? color.lime : color.red
table.cell(dash, 1, r, str.tostring(pnl, "#.#") + "p", text_color=pnl_c, text_size=size.tiny)
if in_short and not na(trailing_sl_short)
r += 1
table.cell(dash, 0, r, "Trail SL", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(trailing_sl_short, "#.##"), text_color=color.red, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Trail TP", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(trailing_tp_short, "#.##"), text_color=color.lime, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "Profit", text_color=color.gray, text_size=size.tiny)
pnl = sell_entry - close
pnl_c = pnl > 0 ? color.lime : color.red
table.cell(dash, 1, r, str.tostring(pnl, "#.#") + "p", text_color=pnl_c, text_size=size.tiny)
// Signal
r += 1
table.cell(dash, 0, r, "SIGNAL", text_color=color.white, bgcolor=color.new(color.green, 50), text_size=size.small)
sig_txt = buy_final ? "BUY NOW" : (sell_final ? "SELL NOW" : "WAIT")
sig_c = buy_final ? color.lime : (sell_final ? color.red : color.gray)
table.cell(dash, 1, r, sig_txt, text_color=sig_c, bgcolor=color.new(color.green, 50), text_size=size.small)
// IMMEDIATE Trade Levels - Show as soon as ORB is ready
if orb_ready and not na(long_entry) and not na(short_entry)
r += 1
table.cell(dash, 0, r, "LONG LEVELS", text_color=color.lime, bgcolor=color.new(color.green, 70), text_size=size.tiny)
table.cell(dash, 1, r, "", text_color=color.white)
r += 1
table.cell(dash, 0, r, "Entry", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(long_entry, "#.##"), text_color=color.white, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "SL", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(long_sl, "#.##"), text_color=color.red, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "TP", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(long_tp, "#.##"), text_color=color.lime, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "SHORT LEVELS", text_color=color.red, bgcolor=color.new(color.red, 70), text_size=size.tiny)
table.cell(dash, 1, r, "", text_color=color.white)
r += 1
table.cell(dash, 0, r, "Entry", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(short_entry, "#.##"), text_color=color.white, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "SL", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(short_sl, "#.##"), text_color=color.red, text_size=size.tiny)
r += 1
table.cell(dash, 0, r, "TP", text_color=color.gray, text_size=size.tiny)
table.cell(dash, 1, r, str.tostring(short_tp, "#.##"), text_color=color.lime, text_size=size.tiny)
// ════════════════════════ ALERTS ════════════════════════
alertcondition(buy_final, "BUY Signal", "DAX ORB BUY")
alertcondition(sell_final, "SELL Signal", "DAX ORB SELL")
alertcondition(orb_ready and not orb_ready , "ORB Ready", "DAX ORB READY")
alertcondition(is_building and not is_building , "ORB Building", "DAX ORB BUILDING")
alertcondition(ok_trade and not ok_trade , "Ready to Trade", "DAX OK")
