Gann RetracementThe indicator is based on W. D. Gann's method of retracement studies. Gann looked at stock retracement action in terms of Halves (1/2), Thirds (1/3, 2/3), Fifths (1/5, 2/5, 3/5, and 4/5) and more importantly the Eighths (1/8, 2/8, 3/8, 4/8, 5/8, 6/8, and 7/8). Needless to say, {2, 3, 5, 8} are the only Fibonacci numbers between 1 to 10. These ratios can easily be visualized in the form of division of a Circle as follows :
Divide the circle in 12 equal parts of 30 degree each to produce the Thirds :
30 x 4 = 120 is 1/3 of 360
30 x 8 = 240 is 2/3 of 360
The 30 degree retracement captures fundamental geometric shapes like a regular Triangle (120-240-360), a Square (90-180-270-360), and a regular Hexagon (60-120-180-240-300-360) inscribed inside of the circle.
Now, divide the circle in 10 equal parts of 36 degree each to produce the Fifths :
36 x 2 = 72 is 1/5 of 360
36 x 4 = 144 is 2/5 of 360
36 x 6 = 216 is 3/5 of 360
36 x 8 = 288 is 4/5 of 360
where, (72-144-216-288-360) is a regular Pentagon.
Finally, divide the circle in 8 equal parts of 45 degree each to produce the Eighths :
45 x 1 = 45 is 1/8 of 360
45 x 2 = 90 is 2/8 of 360
45 x 3 = 135 is 3/8 of 360
45 x 4 = 180 is 4/8 of 360
45 x 5 = 225 is 5/8 of 360
45 x 6 = 270 is 6/8 of 360
45 x 7 = 315 is 7/8 of 360
where, (45-90-135-180-225-270-315-360) is a regular Octagon.
How to Use this indicator ?
The indicator generates Gann retracement levels between any two significant price points, such as a high and a low.
Input :
Swing High (significant high price point, such as a top)
Swing Low (significant low price point, such as a bottom)
Degree (degree of retracement)
Output :
Gann retracement levels (color coded as follows) :
Swing High and Swing Low (BLUE)
50% retracement (ORANGE)
Retracements between Swing Low and 50% level (RED)
Retracements between 50% level and Swing High (LIME)
Buscar en scripts para "30年国债收益率"
Bollinger Bands %B + ATR This indicator is best suitable for the 30-minutes interval OIL charts, due to ATR accuracy.
BB%B is great for showing oversold/overbought market conditions and offers excellent entry/exit opportunities for Day Trading (30 minutes chart), as well as reliable convergence/divergence patterns. ATR is conveniently combined and shows potential market volatility levels for the day when used in 30-minutes charts, thus demarcating your day trade exit point.
To use the ATR on this indicator: Just read the ATR value of the lowest (for a new bull trend) or the highest (for a new bear trend) candlestick of the newly formed trend leg. Let's suppose the ATR reads 0.2891, then you project a move of 2.891 points towards the given trend direction using the ruler tool (30-minutes charts). That's all, and there you have your take profit target!
Good Luck!!!
ADX strategy (considering ADX and +DI only )I have been checking the strategies on ADX indicator.
I have found that +DI crossing above ADX line under threshold 30 and exit on crossdown when ADX above 30 has better results than just following crossovers of +DI and -DI , ADX crossing above 30 .
BUY Rule
========
fast ema is above slow ema (default 13 and 55 , you can change these values in settings)
+DI cross above ADX well beloe threshold level (default 30)
Exit reule
========
when +DI cross down ADX , well above on threshold level
Stop Loss
=========
Default is set to 8%
Take a look and let me know how your symbol works with this strategy
Note : Bar color changes to yellow when the BUY condition is met.
Bar color and Background color shows to blue --- if Long position is active
fast ema and long ema doesnt print on the chart -- please add manually to the chart
Warning : for the use of educational purposes only
EulerMethod: DeltaEN
Shows the Integral Volume Delta (IVD)
It is a detailed OBV. Each bar sums up the volume for bars of a shorter timeframe.
For example, inside a 1M bar, every 12h bar is added up, and inside a 1h bar, every 1min bar is added. Thus, a conditional volume delta inside the bar is obtained.
The indicator for each bar shows the volume of purchases (positive), sales (negative) and the difference — IVD
The delta histogram is thicker than the volume histograms
Settings detalisation
M — 6 hours, 12 hours and 1 day for the M timeframe (720 by default)
W — 4 hours, 6 hours and 12 hours for the W timeframe (240 by default)
D — 30 minutes, 1 hour and 2 hours for the D timeframe (60 by default)
H — 1 minute, 5 minutes and 15 minutes for timeframes [1h, D) (default is 1)
For timeframes of 15m and less, the calculation is carried out by minute bars
VSA mode
The classic OBV adds volume to the cumulative sum under the condition Сlose (n) > Close (n-1) and subtracts it under the condition Close (n) < Close (n-1)
When VSA mode is disabled, all volumes are summed up under these conditions.
When the VSA approximation is turned on, the volume per bar of detail is divided by the factor (Close - Low) / (High - Low)
That is, it takes into account the spread per bar and closing relative to the spread. VSA is enabled by default
A/D mode
Shows the cumulative Accumulation / Distribution Index
The delta of the detail bar is multiplied by (High + Low + Close) / 3 bars, the result is added to the cumulative sum
No additional price conversions required due to integral summation
Index line view is customizable
EM Delta does not receive intermediate values in real time.
To see the result, wait until the bar closes or switch to a smaller timeframe
RU
Показывает Интегральную Дельту Объёма (ИДО)
Представляет собой детализированный OBV. В каждом баре суммируется объём за бары меньшего таймфрейма.
Например, внутри 1М-бара суммируется каждый 12h-бар, а внутри 1h — каждый 1m-бар. Таким образом получается условная дельта объёма внутри бара
Индикатор на каждый бар показывает объём покупок (положительный), объём продаж (отрицательный) и разницу — ИДО
Гистограмма дельты толще гистограмм объёмов
Настройки детализации внутри бара
M — 6 часов, 12 часов и 1 день для таймфрейма M (по-умолчанию 720)
W — 4 часа, 6 часов и 12 часов для таймфрейма W (по-умолчанию 240)
D — 30 минут, 1 час и 2 часа для таймфрейма D (по-умолчанию 60)
H — 1 минута, 5 минут и 15 минут для таймфреймов [1h, D) (по-умолчанию 1)
Для таймфреймов 15m и меньше расчёт ведётся по минутным барам
Режим VSA
Классический OBV прибавляет объём к кумулятивной сумме при условии Сlose(n) > Close(n-1) и отнимает при условии Close(n) < Close(n-1)
При отключении режима VSA все объёмы суммируются по этим условиям
При включённой VSA-аппроксимации объём за бар детализации делится по фактору (Close - Low) / (High - Low)
То есть учитывает спред за бар и закрытие относительно спреда. По-умолчанию режим VSA включен
Режим A/D
Показывает кумулятивный индекс Накопления/Распределения
Дельта бара детализации умножается на (High + Low + Close) / 3 бара, результат прибавляется к кумулятивной сумме
Дополнительные преобразования цены не требуются ввиду интегрального суммирования
Вид линии индекса настраивается
EM Delta не получает промежуточные значения в реальном времени.
Чтобы увидеть результат, дождитесь закрытия бара или перейдите на меньший таймфрейм
Crypto Trading Hours UTC based on Berlin time (UTC +2)Although crypto markets trade 24/7, there are spikes in volume according to the general hours at which different parts of the world do the majority of their trading.
This Script highlights the US, European and Asian markets when they are most active. The normal market hours are always from 08:00 to 16:30 local time.
US market opens at 8:00 Silicon Valley local time, and closes at 16:30 New York local time.
European market opens at 8:00 London local time, and closes at 16:30 Frankfurt local time.
Asian market opens at 8:00 Hong Kong local time, and closes at 16:30 Sydney local time.
Supertrend MTF LAG ISSUEThis script based on
we all use Super trend but it main issue is the lag as it buy too late or sell too late
using Deavaet study of Heat map MTF we can do a little trick
if you look on his study you can see that major signal for example will happen in the time frame before it happen at larger time frame
so in this example if signal at MTF 30 min and signal at MTF 60 min happen at the same time at 2 hours or 4 hours candles then this signal are more likely to be true then random signal at each time frame specific.
since we use shorter time frame on larger time frame we can remove the lag issue that make supertrend not so effective
In this example I set the signal to be MTF 30 +60 om 2 hour TF , can be good also for 4 hour candles..
So you get the signal to close inside the larger candle
now if you want to make on even shorter TF then change the code to 15 and 30 MTF on candles on 1 hour
or 1 and 5 min on 30 min or 15 min
Panchang Time//This indicator is required in NimblrTA and can be used to define timeslots for the trend confirmation
study("Panchang Time", overlay=true)
timeinrange(res, sess) => time(res, sess) != 0
premarket = #C0C0C0
regular = #0000FF
regularslot2 = #00CCFF
postmarket = #5000FF
notrading = na
sessioncolor = timeinrange("30", "0915-0930") ? premarket : timeinrange("30", "0915-0930") ? regular : timeinrange("30", "0931-1200") ? regularslot2 : timeinrange("30", "1201-1305") ? postmarket : notrading
bgcolor(sessioncolor, transp=90)
extended session - Regular Opening-Range- JayyOpening Range and some other scripts updated to plot correctly (see comments below.) There are three variations of the fibonacci expansion beyond the opening range and retracements within the opening range of the US Market session - I have not put in the script for the other markets yet.
The three scripts have different uses and strengths:
The extended session script (with the script here below) will plot the opening range whether you are using the extended session or the regular session. (that is to say whether "ext" in the lower right hand corner is highlighted or not.). While in the extended session the opening range has some plotting issues with periods like 13 minutes or any period that is not divisible into 330 mins with a round number outcome (eg 330/60 =5.5. Therefore an hour long opening range has problems in the extended session.
The pre session script is only for the premarket. You can select any opening range period you like. I have set the opening range to be the full premarket session. If you select a different session you will have to unselect "pre open to 9:30 EST for Opening Range?" in the format section. The script defaults to 15 minutes in the "period Of Pre Opening Range?". To go back to the 4 am to 9:30 pre opening range select "pre open to 9:30 EST for Opening Range?" there is no automatic 330 minute selection.
The past days offset script only works in 5 min or 15 minute period. It will show the opening range from up to 20 days past over the current days price action. Use this for the regular session only. 0 shows the current day's opening range. Use the positive integers for number of days back ie 1, 2, 3 etc not -1, -2, -3 etc. The script is preprogrammed to use the current day (0).
Scripts updated to plot correctly: One thing they all have in common is a way of they deal with a somewhat random problem that shifts the plots 4 hours in one direction or the other ie the plot started at 9:30 EST or 1:30PM EST. This issue started to occur approximately June 22, 2015 and impacts any script that tried to use "session" times to manage a plot in my scripts. The issue now seems to have been resolved during this past week.
Just in case the problem reoccurs I have added a "Switch session plot?" to each script. If the plot looks funny check or uncheck the "Switch session plot?" and see the difference. Of course if a new issue crops up it will likely require a different fix.
I have updated all of the scripts shown on this chart. If you are using a script of mine that suffers from the compiler issue then you will find an update on this chart. You can get any and all of the scripts by clicking on the small sideways wishbone on the left middle of the chart. You will see a dialogue box. Then click "make it mine". This will import all of the scripts to your computer and you can play around with them all to decide what you want and what you don't want. This is the easiest way to get all of the scripts in one fell swoop. It is also the easiest way for me to make all of the scripts available. I do not have all of the plots visible since it is too messy and one of the scripts (pre OR) is only for the regular session. To view the scripts click on the blue eye to the right of the script title to show it on this script. If you can only use the regular session. The scripts will all (with the exception of the pre OR) work fine.
If for any reason this script seems flakey refresh the page r try a slightly different period. I have noticed that sometimes randomly the script loves to return to the 5 min OR. This is a very new issue transient issue. As always if you see an issue please let me know.
Cheers Jayy
Multi-Timeframe Price Levels# Multi-Timeframe Price Levels Indicator
## What This Script Does
This Pine Script indicator displays key horizontal price levels on your TradingView chart to help you identify important support and resistance zones. Think of it as having multiple "reference lines" that show where price has been and where it might react.
## The Price Levels You'll See
**🟣 Yesterday's Levels (Purple Lines)**
- Yesterday's High, Low, and Close
- These often act as support/resistance the next trading day
- Traders watch to see if price holds above/below these levels
**🟢🔴 Premarket Levels (Green/Red Circles)**
- High and Low from premarket trading (4:00 AM - 9:30 AM)
- Shows where institutional traders were active before market open
- Only appears if there was actual premarket activity
**🔵 First 5-Minute Levels (Blue Lines)**
- High and Low from the first 5 minutes of trading (9:30-9:35 AM)
- Locks in at 9:35 AM and doesn't change for the rest of the day
- Popular "opening range" levels many day traders use
**🟠 First 15-Minute Levels (Orange Lines)**
- High and Low from the first 15 minutes of trading (9:30-9:45 AM)
- Locks in at 9:45 AM and stays fixed all day
- Broader opening range for swing traders
**🟢🔴 Today's Levels (Green/Red Thick Lines)**
- Current day's high and low
- Updates in real-time as new highs/lows are made
- The most important current support/resistance levels
## Why These Levels Matter
- **Support/Resistance**: Price often bounces off these levels
- **Breakout Signals**: When price breaks through, it can signal strong moves
- **Risk Management**: Use them to set stop losses and profit targets
- **Context**: Understand where price has been to predict where it might go
## Customization Options
- **Toggle any level on/off** - Only show what you need
- **Adjust line thickness** - Make important levels stand out more
- **Change colors** - Match your chart theme
- **Set session times** - Adjust for different time zones
## Perfect For
- Day traders looking for intraday levels
- Swing traders identifying key zones
- Anyone wanting clean, automated support/resistance lines
- Traders who like multiple timeframe analysis
The script automatically updates daily and requires no manual drawing - just apply it and get instant professional-level price level analysis!
DynamoSent DynamoSent Pro+ — Professional Listing (Preview)
— Adaptive Macro Sentiment (v6)
— Export, Adaptive Lookback, Confidence, Boxes, Heatmap + Dynamic OB/OS
Preview / Experimental build. I’m actively refining this tool—your feedback is gold.
If you spot edge cases, want new presets, or have market-specific ideas, please comment or DM me on TradingView.
⸻
What it is
DynamoSent Pro+ is an adaptive, non-repainting macro sentiment engine that compresses VIX, DXY and a price-based activity proxy (e.g., SPX/sector ETF/your symbol) into a 0–100 sentiment line. It scales context by volatility (ATR%) and can self-calibrate with rolling quantile OB/OS. On top of that, it adds confidence scoring, a plain-English Context Coach, MTF agreement, exportable sentiment for other indicators, and a clean Light/Dark UI.
Why it’s different
• Adaptive lookback tracks regime changes: when volatility rises, we lengthen context; when it falls, we shorten—less whipsaw, more relevance.
• Dynamic OB/OS (quantiles) self-calibrates to each instrument’s distribution—no arbitrary 30/70 lines.
• MTF agreement + Confidence gate reduce false positives by highlighting alignment across timeframes.
• Exportable output: hidden plot “DynamoSent Export” can be selected as input.source in your other Pine scripts.
• Non-repainting rigor: all request.security() calls use lookahead_off + gaps_on; signals wait for bar close.
Key visuals
• Sentiment line (0–100), OB/OS zones (static or dynamic), optional TF1/TF2 overlays.
• Regime boxes (Overbought / Oversold / Neutral) that update live without repaint.
• Info Panel with confidence heat, regime, trend arrow, MTF readout, and Coach sentence.
• Session heat (Asia/EU/US) to match intraday behavior.
• Light/Dark theme switch in Inputs (auto-contrasted labels & headers).
⸻
How to use (examples & recipes)
1) EURUSD (swing / intraday blend)
• Preset: EURUSD 1H Swing
• Chart: 1H; TF1=1H, TF2=4H (default).
• Proxies: Defaults work (VIX=D, DXY=60, Proxy=D).
• Dynamic OB/OS: ON at 20/80; Confidence ≥ 55–60.
• Playbook:
• When sentiment crosses above 50 + margin with Δ ≥ signalK and MTF agreement ≥ 0.5, treat as trend breakout.
• In Oversold with rising Coach & TF agreement, take fade longs back toward mid-range.
• Alerts: Enable Breakout Long/Short and Fade; keep cooldown 8–12 bars.
2) SPY (daytrading)
• Preset: SPY 15m Daytrade; Chart: 15m.
• VIX (D) matters more; preset weights already favor it.
• Start with static 30/70; later try dynamic 25/75 for adaptive thresholds.
• Use Coach: in US session, when it says “Overbought + MTF agree → sell rallies / chase breakouts”, lean momentum-continuation after pullbacks.
3) BTCUSD (crypto, 24/7)
• Preset: BTCUSD 1H; Chart: 1H.
• DXY and BTC.D inform macro tone; keep Carry-forward ON to bridge sparse ticks.
• Prefer Dynamic OB/OS (15/85) for wider swings.
• Fade signals on weekend chop; Breakout when Confidence > 60 and MTF ≥ 1.0.
4) XAUUSD (gold, macro blend)
• Preset: XAUUSD 4H; Chart: 4H.
• Weights tilt to DXY and US10Y (handled by preset).
• Coach + MTF helps separate trend legs from news pops.
⸻
Best practices
• Theme: Switch Light/Dark in Inputs; the panel adapts contrast automatically.
• Export: In another script → Source → DynamoSent Pro+ → DynamoSent Export. Build your own filters/strategies atop the same sentiment.
• Dynamic vs Static OB/OS:
• Static 30/70: fast, universal baseline.
• Dynamic (quantiles): instrument-aware; use 20/80 (default) or 15/85 for choppy markets.
• Confidence gate: Start at 50–60% to filter noise; raise when you want only A-grade setups.
• Adaptive Lookback: Keep ON. For ultra-liquid indices, you can switch it OFF and set a fixed lookback.
⸻
Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off and gaps=barmerge.gaps_on.
• No forward references; signals & regime flips are confirmed on bar close.
• History-dependent funcs (ta.change, ta.percentile_linear_interpolation, etc.) are computed each bar (not conditionally).
• Adaptive lookback is clamped ≥ 1 to avoid lowest/highest errors.
• Missing-data warning triggers only when all proxies are NA for a streak; carry-forward can bridge small gaps without repaint.
⸻
Known limits & tips
• If a proxy symbol isn’t available on your plan/exchange, you’ll see the NA warning: choose a different symbol via Symbol Search, or keep Carry-forward ON (it defaults to neutral where needed).
• Intraday VIX is sparse—using Daily is intentional.
• Dynamic OB/OS needs enough history (see dynLenFloor). On short histories it gracefully falls back to static levels.
Thanks for trying the preview. Your comments drive the roadmap—presets, new proxies, extra alerts, and integrations.
RSI MA Cross + Divergence Signal (V2) Core Logic
RSI + Moving Average
The script calculates a standard RSI (default 14).
It then overlays a moving average (SMA/EMA/WMA, default 9).
When RSI crosses above its MA → bullish momentum.
When RSI crosses below its MA → bearish momentum.
Divergence Filter
Signals are only valid if there’s confirmed divergence:
Bullish divergence: Price makes a lower low, RSI makes a higher low.
Bearish divergence: Price makes a higher high, RSI makes a lower high.
Overbought / Oversold Filter
Optional extra:
Bullish signals only valid if RSI ≤ 30 (oversold).
Bearish signals only valid if RSI ≥ 70 (overbought).
This ensures signals happen in “stretched” conditions.
Risk & Trade Management
Entries taken only when all conditions align.
Exits can be managed with ATR stops, partial take-profits, breakeven moves, and trailing stops (we coded these in the strategy version).
Cooldown, session filters, and daily loss guard to keep risk tight.
🔹 Strengths
✅ High selectivity: Combining RSI cross + divergence + OB/OS means signals are rare but higher quality.
✅ Great at catching reversals: Divergence highlights where price may be running out of steam.
✅ Risk management baked in: ATR stops + partial exits smooth out equity curve.
✅ Works across markets: ES, FX, crypto — anywhere RSI divergences are respected.
✅ Flexible: You can loosen/tighten filters depending on aggressiveness.
🔹 Weaknesses
❌ Lag from pivots: Divergence only confirms after a few bars → you enter late sometimes.
❌ Choppy in ranges: In sideways markets, RSI divergences appear often and whipsaw.
❌ Filters reduce signals: With all filters ON (divergence + OB/OS + trend + session), signals can be very rare — may under-trade.
❌ Not standalone: Needs higher-timeframe context (trend, liquidity pools) to avoid counter-trend entries.
🔹 Best Ways to Trade It
Use Higher Timeframe Bias
Run the strategy on 15m/1H, but only trade in direction of higher timeframe trend (e.g., 4H EMA).
Example: If daily is bullish → only take bullish divergences.
Pair With Structure
Look for signals at key zones: HTF support/resistance, VWAP, or FVGs.
Divergence + RSI cross inside an FVG is a strong entry trigger.
Adjust OB/OS for Volatility
For crypto/FX: use 35/65 instead of 30/70 (markets trend harder).
For ES/S&P: 30/70 works fine.
Risk Management Is King
Use partial exits: take profit at 1R, trail rest.
Size by % of equity (we coded this into the strategy).
Avoid News Spikes
Divergences break down around CPI, NFP, Fed announcements — stay flat.
🔹 When It Shines
Trending markets that make extended pushes → clean divergences.
Reversal zones (oversold → bullish bounce, overbought → bearish fade).
Swing trading (15m–4H) — less noise than 1m/5m scalping.
🔹 When to Avoid
Low volatility chop → lots of false divergences.
During high-impact news → RSI swings wildly.
In strong one-way trends without pullbacks — divergence keeps calling tops/bottoms too early.
✅ Summary:
This is a reversal-focused RSI divergence strategy with strict filters. It’s powerful when combined with higher-timeframe bias + structure confluence, but weak if traded blindly in choppy or news-driven conditions. Best to treat it as a precision entry trigger, not a full system — layer it on top of your FVG/ORB framework for maximum edge.
IV Rank (tasty-style) — VIXFix / HV ProxyIV Rank (tasty-style) — VIXFix / HV Proxy
Overview
This indicator replicates tastytrade’s IV Rank calculation—but built entirely inside TradingView.
Because TradingView does not expose live option-chain implied volatility, the script lets you choose between two widely used price-based IV proxies:
VIXFix (Williams VIX Fix): a fast-reacting volatility estimate derived from price extremes.
HV(30): 30-day annualized historical volatility of daily log returns.
The goal is to approximate the “rich vs. cheap” option volatility environment that traders use to decide whether to sell or buy premium.
Formula
IV Rank answers the question: Where is current implied volatility relative to its own 1-year range?
𝐼
𝑉
𝑅
=
𝐼
𝑉
𝑐
𝑢
𝑟
𝑟
𝑒
𝑛
𝑡
−
𝐼
𝑉
1
𝑦
𝐿
𝑜
𝑤
𝐼
𝑉
1
𝑦
𝐻
𝑖
𝑔
ℎ
−
𝐼
𝑉
1
𝑦
𝐿
𝑜
𝑤
×
100
IVR=
IV
1yHigh
−IV
1yLow
IV
current
−IV
1yLow
×100
IVcurrent: Current value of the chosen IV proxy.
IV1yHigh/Low: Highest and lowest proxy values over the user-defined lookback (default 252 trading days ≈ 1 year).
IVR = 0 → Current IV equals its 1-year low
IVR = 100 → Current IV equals its 1-year high
IVR ≈ 50 → Current IV sits mid-range
How to Use
High IV Rank (≥50–60%)
Options are relatively expensive → short-premium strategies (credit spreads, iron condors, straddles) may be more attractive.
Low IV Rank (≤20%)
Options are relatively cheap → long-premium strategies (debit spreads, calendars, diagonals) may offer better risk/reward.
Combine with your own analysis, liquidity checks, and risk management.
Inputs & Customization
IV Source: Choose “VIXFix” or “HV(30)” as the volatility proxy.
IVR Lookback: Rolling window for 1-year high/low (default 252 trading days).
VIXFix Parameters: Length and stdev multiplier to fine-tune sensitivity.
Info Label: Optional on-chart label displays current IV proxy, 1-year high/low, and IV Rank.
Alerts: Optional alerts when IVR crosses 50, falls below 20, or rises above 80.
Notes & Limitations
This indicator does not pull real option-chain IV.
It provides a close structural analogue to tastytrade’s IV Rank using price-derived proxies for markets where options data is not directly available.
For live option IV, use broker platforms or third-party data feeds alongside this script.
Tags: IV Rank, Implied Volatility, Tastytrade, VIXFix, Historical Volatility, Options, Premium Selling, Debit Spreads, Market Volatility
Measured Move Volume XIndicator Description
The "Measured Move Volume X" indicator, developed for TradingView using Pine Script version 6, projects potential price targets based on the measured move concept, where the magnitude of a prior price leg (Leg A) is used to forecast a subsequent move. It overlays translucent boxes on the chart to visualize bullish (green) or bearish (red) price projections, extending them to the right for a user-specified number of bars. The indicator integrates volume analysis (relative to a simple moving average), RSI for momentum, and VWAP for price-volume weighting, combining these into a confidence score to filter entry signals, displayed as triangles on breakouts. Horizontal key level lines (large, medium, small) are drawn at significant price points derived from the measured moves, with customizable thresholds, colors, and styles. Exhaustion hints, shown as orange labels near box extremes, indicate potential reversal points. Anomalous candles, marked with diamond shapes, are identified based on volume spikes and body-to-range ratios. Optional higher timeframe candle coloring enhances context. The indicator is fully customizable through input groups for lookback periods, transparency, and signal weights, making it adaptable to various assets and timeframes.
Adjustment Tips for Optimization
To optimize the "Measured Move Volume X" indicator for specific assets or timeframes, adjust the following input parameters:
Leg A Lookback (default: 14 bars): Increase to 20-30 for volatile markets (e.g., cryptocurrencies) to capture larger price swings; decrease to 5-10 for intraday charts (e.g., stocks) for faster signals.
Extend Box to the Right (default: 30 bars): Extend to 50+ for daily or weekly charts to project further targets; shorten to 10-20 for lower timeframes to reduce clutter.
Volume SMA Length (default: 20) and Relative Volume Threshold (default: 1.5): Lower the threshold to 1.2-1.3 for low-volume assets (e.g., commodities) to detect subtler spikes; raise to 2.0+ for high-volume equities to filter noise. Match SMA length to RSI length for consistency.
RSI Parameters (default: length 14, overbought 70, oversold 30): Set overbought to 80 and oversold to 20 in trending markets to reduce premature exit signals; shorten length to 7-10 for scalping.
Key Level Thresholds (default: large 10%, medium 5%, small 5%): Increase thresholds (e.g., large to 15%) for volatile assets to focus on significant moves; disable medium or small lines to declutter charts.
Confidence Score Weights (default: volume 0.5, VWAP 0.3, RSI 0.2): Increase volume weight (e.g., 0.7) for volume-driven markets like futures; emphasize RSI (e.g., 0.4) for momentum-focused strategies.
Anomaly Detection (default: volume multiplier 1.5, small body ratio 0.2, large body ratio 0.75): Adjust the volume multiplier higher for stricter anomaly detection in noisy markets; fine-tune body-to-range ratios based on asset-specific candle patterns.
Use TradingView’s replay feature to test adjustments on historical data, ensuring settings suit the chosen market and timeframe.
Tips for Using the Indicator
Interpreting Signals: Green upward triangles indicate bullish breakout entries when price exceeds the prior high with a confidence score ≥40; red downward triangles signal bearish breakouts. Use these to identify potential entry points aligned with the projected box targets.
Box Projections: Bullish boxes project upward targets (top of box) equal to the prior leg’s height added to the breakout price; bearish boxes project downward. Monitor price action near box edges for target completion or reversal.
Exhaustion Hints: Orange labels near box tops (bullish) or bottoms (bearish) suggest potential exhaustion when price deviates within the set percentage (default: 5%) and RSI or volume conditions are met. Use these as cues to watch for reversals.
Key Level Lines: Large, medium, and small lines mark significant price levels from box tops/bottoms. Use these as potential support/resistance zones, especially when drawn with high volume (colored differently).
Anomaly Candles: Orange diamonds highlight candles with unusual volume/body characteristics, indicating potential reversals or pauses. Combine with box levels for context.
Higher Timeframe Coloring: Enable to color bars based on higher timeframe candle closures (e.g., 1, 2, 5, or 15 minutes) for added trend context.
Customization: Toggle "Only Show Bullish Moves" to focus on bullish setups. Adjust transparency and line styles for visual clarity. Test settings to balance signal frequency and chart readability.
Inputs: Organized into groups (e.g., "Measured Move Settings") using input.int, input.float, input.color, and input.bool for user customization, with tooltips for clarity.
Calculations: Computes relative volume (ta.sma(volume, volLookback)), VWAP (ta.vwap(hlc3)), RSI (ta.rsi(close, rsiLength)), and prior leg extremes (ta.highest/lowest) using prior bar data ( ) to prevent repainting.
Boxes and Lines: Creates boxes (box.new) for bullish/bearish projections and lines (line.new) for key levels. The f_addLine function manages line arrays (array.new_line), capping at maxLinesCount to avoid clutter.
Confidence Score: Combines volume, VWAP distance, and RSI into a weighted score (confScore), filtering entries (≥40). Rounded for display.
Exhaustion Hints: Functions like f_plotBullExitHint assess price deviation, RSI, and volume decrease, using label.new for dynamic orange labels.
Entry Signals and Plots: plotshape displays triangles for breakouts; plot and hline show VWAP and RSI levels; request.security handles higher timeframe coloring.
Anomaly Detection: Identifies candles with small-body high-volume or large-body average-volume patterns via ratios, plotted as diamonds.
Bar Index & TimeLibrary to convert a bar index to a timestamp and vice versa.
Utilizes runtime memory to store the 𝚝𝚒𝚖𝚎 and 𝚝𝚒𝚖𝚎_𝚌𝚕𝚘𝚜𝚎 values of every bar on the chart (and optional future bars), with the ability of storing additional custom values for every chart bar.
█ PREFACE
This library aims to tackle some problems that pine coders (from beginners to advanced) often come across, such as:
I'm trying to draw an object with a 𝚋𝚊𝚛_𝚒𝚗𝚍𝚎𝚡 that is more than 10,000 bars into the past, but this causes my script to fail. How can I convert the 𝚋𝚊𝚛_𝚒𝚗𝚍𝚎𝚡 to a UNIX time so that I can draw visuals using xloc.bar_time ?
I have a diagonal line drawing and I want to get the "y" value at a specific time, but line.get_price() only accepts a bar index value. How can I convert the timestamp into a bar index value so that I can still use this function?
I want to get a previous 𝚘𝚙𝚎𝚗 value that occurred at a specific timestamp. How can I convert the timestamp into a historical offset so that I can use 𝚘𝚙𝚎𝚗 ?
I want to reference a very old value for a variable. How can I access a previous value that is older than the maximum historical buffer size of 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎 ?
This library can solve the above problems (and many more) with the addition of a few lines of code, rather than requiring the coder to refactor their script to accommodate the limitations.
█ OVERVIEW
The core functionality provided is conversion between xloc.bar_index and xloc.bar_time values.
The main component of the library is the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object, created via the 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() function which basically stores the 𝚝𝚒𝚖𝚎 and 𝚝𝚒𝚖𝚎_𝚌𝚕𝚘𝚜𝚎 of every bar on the chart, and there are 3 more overloads to this function that allow collecting and storing additional data. Once a 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object is created, use any of the exported methods:
Methods to convert a UNIX timestamp into a bar index or bar offset:
𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙𝚃𝚘𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚐𝚎𝚝𝙽𝚞𝚖𝚋𝚎𝚛𝙾𝚏𝙱𝚊𝚛𝚜𝙱𝚊𝚌𝚔()
Methods to retrieve the stored data for a bar index:
𝚝𝚒𝚖𝚎𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚝𝚒𝚖𝚎𝙲𝚕𝚘𝚜𝚎𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚟𝚊𝚕𝚞𝚎𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡(), 𝚐𝚎𝚝𝙰𝚕𝚕𝚅𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜𝙰𝚝𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡()
Methods to retrieve the stored data at a number of bars back (i.e., historical offset):
𝚝𝚒𝚖𝚎(), 𝚝𝚒𝚖𝚎𝙲𝚕𝚘𝚜𝚎(), 𝚟𝚊𝚕𝚞𝚎()
Methods to retrieve all the data points from the earliest bar (or latest bar) stored in memory, which can be useful for debugging purposes:
𝚐𝚎𝚝𝙴𝚊𝚛𝚕𝚒𝚎𝚜𝚝𝚂𝚝𝚘𝚛𝚎𝚍𝙳𝚊𝚝𝚊(), 𝚐𝚎𝚝𝙻𝚊𝚝𝚎𝚜𝚝𝚂𝚝𝚘𝚛𝚎𝚍𝙳𝚊𝚝𝚊()
Note: the library's strong suit is referencing data from very old bars in the past, which is especially useful for scripts that perform its necessary calculations only on the last bar.
█ USAGE
Step 1
Import the library. Replace with the latest available version number for this library.
//@version=6
indicator("Usage")
import n00btraders/ChartData/
Step 2
Create a 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object to collect data on every bar. Do not declare as `var` or `varip`.
chartData = ChartData.collectChartData() // call on every bar to accumulate the necessary data
Step 3
Call any method(s) on the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object. Do not modify its fields directly.
if barstate.islast
int firstBarTime = chartData.timeAtBarIndex(0)
int lastBarTime = chartData.time(0)
log.info("First `time`: " + str.format_time(firstBarTime) + ", Last `time`: " + str.format_time(lastBarTime))
█ EXAMPLES
• Collect Future Times
The overloaded 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() functions that accept a 𝚋𝚊𝚛𝚜𝙵𝚘𝚛𝚠𝚊𝚛𝚍 argument can additionally store time values for up to 500 bars into the future.
//@version=6
indicator("Example `collectChartData(barsForward)`")
import n00btraders/ChartData/1
chartData = ChartData.collectChartData(barsForward = 500)
var rectangle = box.new(na, na, na, na, xloc = xloc.bar_time, force_overlay = true)
if barstate.islast
int futureTime = chartData.timeAtBarIndex(bar_index + 100)
int lastBarTime = time
box.set_lefttop(rectangle, lastBarTime, open)
box.set_rightbottom(rectangle, futureTime, close)
box.set_text(rectangle, "Extending box 100 bars to the right. Time: " + str.format_time(futureTime))
• Collect Custom Data
The overloaded 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() functions that accept a 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜 argument can additionally store custom user-specified values for every bar on the chart.
//@version=6
indicator("Example `collectChartData(variables)`")
import n00btraders/ChartData/1
var map variables = map.new()
variables.put("open", open)
variables.put("close", close)
variables.put("open-close midpoint", (open + close) / 2)
variables.put("boolean", open > close ? 1 : 0)
chartData = ChartData.collectChartData(variables = variables)
var fgColor = chart.fg_color
var table1 = table.new(position.top_right, 2, 9, color(na), fgColor, 1, fgColor, 1, true)
var table2 = table.new(position.bottom_right, 2, 9, color(na), fgColor, 1, fgColor, 1, true)
if barstate.isfirst
table.cell(table1, 0, 0, "ChartData.value()", text_color = fgColor)
table.cell(table2, 0, 0, "open ", text_color = fgColor)
table.merge_cells(table1, 0, 0, 1, 0)
table.merge_cells(table2, 0, 0, 1, 0)
for i = 1 to 8
table.cell(table1, 0, i, text_color = fgColor, text_halign = text.align_left, text_font_family = font.family_monospace)
table.cell(table2, 0, i, text_color = fgColor, text_halign = text.align_left, text_font_family = font.family_monospace)
table.cell(table1, 1, i, text_color = fgColor)
table.cell(table2, 1, i, text_color = fgColor)
if barstate.islast
for i = 1 to 8
float open1 = chartData.value("open", 5000 * i)
float open2 = i < 3 ? open : -1
table.cell_set_text(table1, 0, i, "chartData.value(\"open\", " + str.tostring(5000 * i) + "): ")
table.cell_set_text(table2, 0, i, "open : ")
table.cell_set_text(table1, 1, i, str.tostring(open1))
table.cell_set_text(table2, 1, i, open2 >= 0 ? str.tostring(open2) : "Error")
• xloc.bar_index → xloc.bar_time
The 𝚝𝚒𝚖𝚎 value (or 𝚝𝚒𝚖𝚎_𝚌𝚕𝚘𝚜𝚎 value) can be retrieved for any bar index that is stored in memory by the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object.
//@version=6
indicator("Example `timeAtBarIndex()`")
import n00btraders/ChartData/1
chartData = ChartData.collectChartData()
if barstate.islast
int start = bar_index - 15000
int end = bar_index - 100
// line.new(start, close, end, close) // !ERROR - `start` value is too far from current bar index
start := chartData.timeAtBarIndex(start)
end := chartData.timeAtBarIndex(end)
line.new(start, close, end, close, xloc.bar_time, width = 10)
• xloc.bar_time → xloc.bar_index
Use 𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙𝚃𝚘𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡() to find the bar that a timestamp belongs to.
If the timestamp falls in between the close of one bar and the open of the next bar,
the 𝚜𝚗𝚊𝚙 parameter can be used to determine which bar to choose:
𝚂𝚗𝚊𝚙.𝙻𝙴𝙵𝚃 - prefer to choose the leftmost bar (typically used for closing times)
𝚂𝚗𝚊𝚙.𝚁𝙸𝙶𝙷𝚃 - prefer to choose the rightmost bar (typically used for opening times)
𝚂𝚗𝚊𝚙.𝙳𝙴𝙵𝙰𝚄𝙻𝚃 (or 𝚗𝚊) - copies the same behavior as xloc.bar_time uses for drawing objects
//@version=6
indicator("Example `timestampToBarIndex()`")
import n00btraders/ChartData/1
startTimeInput = input.time(timestamp("01 Aug 2025 08:30 -0500"), "Session Start Time")
endTimeInput = input.time(timestamp("01 Aug 2025 15:15 -0500"), "Session End Time")
chartData = ChartData.collectChartData()
if barstate.islastconfirmedhistory
int startBarIndex = chartData.timestampToBarIndex(startTimeInput, ChartData.Snap.RIGHT)
int endBarIndex = chartData.timestampToBarIndex(endTimeInput, ChartData.Snap.LEFT)
line1 = line.new(startBarIndex, 0, startBarIndex, 1, extend = extend.both, color = color.new(color.green, 60), force_overlay = true)
line2 = line.new(endBarIndex, 0, endBarIndex, 1, extend = extend.both, color = color.new(color.green, 60), force_overlay = true)
linefill.new(line1, line2, color.new(color.green, 90))
// using Snap.DEFAULT to show that it is equivalent to drawing lines using `xloc.bar_time` (i.e., it aligns to the same bars)
startBarIndex := chartData.timestampToBarIndex(startTimeInput)
endBarIndex := chartData.timestampToBarIndex(endTimeInput)
line.new(startBarIndex, 0, startBarIndex, 1, extend = extend.both, color = color.yellow, width = 3)
line.new(endBarIndex, 0, endBarIndex, 1, extend = extend.both, color = color.yellow, width = 3)
line.new(startTimeInput, 0, startTimeInput, 1, xloc.bar_time, extend.both, color.new(color.blue, 85), width = 11)
line.new(endTimeInput, 0, endTimeInput, 1, xloc.bar_time, extend.both, color.new(color.blue, 85), width = 11)
• Get Price of Line at Timestamp
The pine script built-in function line.get_price() requires working with bar index values. To get the price of a line in terms of a timestamp, convert the timestamp into a bar index or offset.
//@version=6
indicator("Example `line.get_price()` at timestamp")
import n00btraders/ChartData/1
lineStartInput = input.time(timestamp("01 Aug 2025 08:30 -0500"), "Line Start")
chartData = ChartData.collectChartData()
var diagonal = line.new(na, na, na, na, force_overlay = true)
if time <= lineStartInput
line.set_xy1(diagonal, bar_index, open)
if barstate.islastconfirmedhistory
line.set_xy2(diagonal, bar_index, close)
if barstate.islast
int timeOneWeekAgo = timenow - (7 * timeframe.in_seconds("1D") * 1000)
// Note: could also use `timetampToBarIndex(timeOneWeekAgo, Snap.DEFAULT)` and pass the value directly to `line.get_price()`
int barsOneWeekAgo = chartData.getNumberOfBarsBack(timeOneWeekAgo)
float price = line.get_price(diagonal, bar_index - barsOneWeekAgo)
string formatString = "Time 1 week ago: {0,number,#}\n - Equivalent to {1} bars ago\n\n𝚕𝚒𝚗𝚎.𝚐𝚎𝚝_𝚙𝚛𝚒𝚌𝚎(): {2,number,#.##}"
string labelText = str.format(formatString, timeOneWeekAgo, barsOneWeekAgo, price)
label.new(timeOneWeekAgo, price, labelText, xloc.bar_time, style = label.style_label_lower_right, size = 16, textalign = text.align_left, force_overlay = true)
█ RUNTIME ERROR MESSAGES
This library's functions will generate a custom runtime error message in the following cases:
𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() is not called consecutively, or is called more than once on a single bar
Invalid 𝚋𝚊𝚛𝚜𝙵𝚘𝚛𝚠𝚊𝚛𝚍 argument in the 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() function
Invalid 𝚟𝚊𝚛𝚒𝚊𝚋𝚕𝚎𝚜 argument in the 𝚌𝚘𝚕𝚕𝚎𝚌𝚝𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊() function
Invalid 𝚕𝚎𝚗𝚐𝚝𝚑 argument in any of the functions that accept a number of bars back
Note: there is no runtime error generated for an invalid 𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙 or 𝚋𝚊𝚛𝙸𝚗𝚍𝚎𝚡 argument in any of the functions. Instead, the functions will assign 𝚗𝚊 to the returned values.
Any other runtime errors are due to incorrect usage of the library.
█ NOTES
• Function Descriptions
The library source code uses Markdown for the exported functions. Hover over a function/method call in the Pine Editor to display formatted, detailed information about the function/method.
//@version=6
indicator("Demo Function Tooltip")
import n00btraders/ChartData/1
chartData = ChartData.collectChartData()
int barIndex = chartData.timestampToBarIndex(timenow)
log.info(str.tostring(barIndex))
• Historical vs. Realtime Behavior
Under the hood, the data collector for this library is declared as `var`. Because of this, the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object will always reflect the latest available data on realtime updates. Any data that is recorded for historical bars will remain unchanged throughout the execution of a script.
//@version=6
indicator("Demo Realtime Behavior")
import n00btraders/ChartData/1
var map variables = map.new()
variables.put("open", open)
variables.put("close", close)
chartData = ChartData.collectChartData(variables)
if barstate.isrealtime
varip float initialOpen = open
varip float initialClose = close
varip int updateCount = 0
updateCount += 1
float latestOpen = open
float latestClose = close
float recordedOpen = chartData.valueAtBarIndex("open", bar_index)
float recordedClose = chartData.valueAtBarIndex("close", bar_index)
string formatString = "# of updates: {0}\n\n𝚘𝚙𝚎𝚗 at update #1: {1,number,#.##}\n𝚌𝚕𝚘𝚜𝚎 at update #1: {2,number,#.##}\n\n"
+ "𝚘𝚙𝚎𝚗 at update #{0}: {3,number,#.##}\n𝚌𝚕𝚘𝚜𝚎 at update #{0}: {4,number,#.##}\n\n"
+ "𝚘𝚙𝚎𝚗 stored in memory: {5,number,#.##}\n𝚌𝚕𝚘𝚜𝚎 stored in memory: {6,number,#.##}"
string labelText = str.format(formatString, updateCount, initialOpen, initialClose, latestOpen, latestClose, recordedOpen, recordedClose)
label.new(bar_index, close, labelText, style = label.style_label_left, force_overlay = true)
• Collecting Chart Data for Other Contexts
If your use case requires collecting chart data from another context, avoid directly retrieving the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 object as this may exceed memory limits .
//@version=6
indicator("Demo Return Calculated Results")
import n00btraders/ChartData/1
timeInput = input.time(timestamp("01 Sep 2025 08:30 -0500"), "Time")
var int oneMinuteBarsAgo = na
// !ERROR - Memory Limits Exceeded
// chartDataArray = request.security_lower_tf(syminfo.tickerid, "1", ChartData.collectChartData())
// oneMinuteBarsAgo := chartDataArray.last().getNumberOfBarsBack(timeInput)
// function that returns calculated results (a single integer value instead of an entire `ChartData` object)
getNumberOfBarsBack() =>
chartData = ChartData.collectChartData()
chartData.getNumberOfBarsBack(timeInput)
calculatedResultsArray = request.security_lower_tf(syminfo.tickerid, "1", getNumberOfBarsBack())
oneMinuteBarsAgo := calculatedResultsArray.size() > 0 ? calculatedResultsArray.last() : na
if barstate.islast
string labelText = str.format("The selected timestamp occurs 1-minute bars ago", oneMinuteBarsAgo)
label.new(bar_index, hl2, labelText, style = label.style_label_left, size = 16, force_overlay = true)
• Memory Usage
The library's convenience and ease of use comes at the cost of increased usage of computational resources. For simple scripts, using this library will likely not cause any issues with exceeding memory limits. But for large and complex scripts, you can reduce memory issues by specifying a lower 𝚌𝚊𝚕𝚌_𝚋𝚊𝚛𝚜_𝚌𝚘𝚞𝚗𝚝 amount in the indicator() or strategy() declaration statement.
//@version=6
// !ERROR - Memory Limits Exceeded using the default number of bars available (~20,000 bars for Premium plans)
//indicator("Demo `calc_bars_count` parameter")
// Reduce number of bars using `calc_bars_count` parameter
indicator("Demo `calc_bars_count` parameter", calc_bars_count = 15000)
import n00btraders/ChartData/1
map variables = map.new()
variables.put("open", open)
variables.put("close", close)
variables.put("weekofyear", weekofyear)
variables.put("dayofmonth", dayofmonth)
variables.put("hour", hour)
variables.put("minute", minute)
variables.put("second", second)
// simulate large memory usage
chartData0 = ChartData.collectChartData(variables)
chartData1 = ChartData.collectChartData(variables)
chartData2 = ChartData.collectChartData(variables)
chartData3 = ChartData.collectChartData(variables)
chartData4 = ChartData.collectChartData(variables)
chartData5 = ChartData.collectChartData(variables)
chartData6 = ChartData.collectChartData(variables)
chartData7 = ChartData.collectChartData(variables)
chartData8 = ChartData.collectChartData(variables)
chartData9 = ChartData.collectChartData(variables)
log.info(str.tostring(chartData0.time(0)))
log.info(str.tostring(chartData1.time(0)))
log.info(str.tostring(chartData2.time(0)))
log.info(str.tostring(chartData3.time(0)))
log.info(str.tostring(chartData4.time(0)))
log.info(str.tostring(chartData5.time(0)))
log.info(str.tostring(chartData6.time(0)))
log.info(str.tostring(chartData7.time(0)))
log.info(str.tostring(chartData8.time(0)))
log.info(str.tostring(chartData9.time(0)))
if barstate.islast
result = table.new(position.middle_right, 1, 1, force_overlay = true)
table.cell(result, 0, 0, "Script Execution Successful ✅", text_size = 40)
█ EXPORTED ENUMS
Snap
Behavior for determining the bar that a timestamp belongs to.
Fields:
LEFT : Snap to the leftmost bar.
RIGHT : Snap to the rightmost bar.
DEFAULT : Default `xloc.bar_time` behavior.
Note: this enum is used for the 𝚜𝚗𝚊𝚙 parameter of 𝚝𝚒𝚖𝚎𝚜𝚝𝚊𝚖𝚙𝚃𝚘𝙱𝚊𝚛𝙸𝚗𝚍𝚎𝚡().
█ EXPORTED TYPES
Note: users of the library do not need to worry about directly accessing the fields of these types; all computations are done through method calls on an object of the 𝙲𝚑𝚊𝚛𝚝𝙳𝚊𝚝𝚊 type.
Variable
Represents a user-specified variable that can be tracked on every chart bar.
Fields:
name (series string) : Unique identifier for the variable.
values (array) : The array of stored values (one value per chart bar).
ChartData
Represents data for all bars on a chart.
Fields:
bars (series int) : Current number of bars on the chart.
timeValues (array) : The `time` values of all chart (and future) bars.
timeCloseValues (array) : The `time_close` values of all chart (and future) bars.
variables (array) : Additional custom values to track on all chart bars.
█ EXPORTED FUNCTIONS
collectChartData()
Collects and tracks the `time` and `time_close` value of every bar on the chart.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
collectChartData(barsForward)
Collects and tracks the `time` and `time_close` value of every bar on the chart as well as a specified number of future bars.
Parameters:
barsForward (simple int) : Number of future bars to collect data for.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
collectChartData(variables)
Collects and tracks the `time` and `time_close` value of every bar on the chart. Additionally, tracks a custom set of variables for every chart bar.
Parameters:
variables (simple map) : Custom values to collect on every chart bar.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
collectChartData(barsForward, variables)
Collects and tracks the `time` and `time_close` value of every bar on the chart as well as a specified number of future bars. Additionally, tracks a custom set of variables for every chart bar.
Parameters:
barsForward (simple int) : Number of future bars to collect data for.
variables (simple map) : Custom values to collect on every chart bar.
Returns: `ChartData` object to convert between `xloc.bar_index` and `xloc.bar_time`.
█ EXPORTED METHODS
method timestampToBarIndex(chartData, timestamp, snap)
Converts a UNIX timestamp to a bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
timestamp (series int) : A UNIX time.
snap (series Snap) : A `Snap` enum value.
Returns: A bar index, or `na` if unable to find the appropriate bar index.
method getNumberOfBarsBack(chartData, timestamp)
Converts a UNIX timestamp to a history-referencing length (i.e., number of bars back).
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
timestamp (series int) : A UNIX time.
Returns: A bar offset, or `na` if unable to find a valid number of bars back.
method timeAtBarIndex(chartData, barIndex)
Retrieves the `time` value for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
barIndex (int) : The bar index.
Returns: The `time` value, or `na` if there is no `time` stored for the bar index.
method time(chartData, length)
Retrieves the `time` value of the bar that is `length` bars back relative to the latest bar.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
length (series int) : Number of bars back.
Returns: The `time` value `length` bars ago, or `na` if there is no `time` stored for that bar.
method timeCloseAtBarIndex(chartData, barIndex)
Retrieves the `time_close` value for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
barIndex (series int) : The bar index.
Returns: The `time_close` value, or `na` if there is no `time_close` stored for the bar index.
method timeClose(chartData, length)
Retrieves the `time_close` value of the bar that is `length` bars back from the latest bar.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
length (series int) : Number of bars back.
Returns: The `time_close` value `length` bars ago, or `na` if there is none stored.
method valueAtBarIndex(chartData, name, barIndex)
Retrieves the value of a custom variable for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
name (series string) : The variable name.
barIndex (series int) : The bar index.
Returns: The value of the variable, or `na` if that variable is not stored for the bar index.
method value(chartData, name, length)
Retrieves a variable value of the bar that is `length` bars back relative to the latest bar.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
name (series string) : The variable name.
length (series int) : Number of bars back.
Returns: The value `length` bars ago, or `na` if that variable is not stored for the bar index.
method getAllVariablesAtBarIndex(chartData, barIndex)
Retrieves all custom variables for the specified bar index.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
barIndex (series int) : The bar index.
Returns: Map of all custom variables that are stored for the specified bar index.
method getEarliestStoredData(chartData)
Gets all values from the earliest bar data that is currently stored in memory.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
Returns: A tuple:
method getLatestStoredData(chartData, futureData)
Gets all values from the latest bar data that is currently stored in memory.
Namespace types: ChartData
Parameters:
chartData (series ChartData) : The `ChartData` object.
futureData (series bool) : Whether to include the future data that is stored in memory.
Returns: A tuple:
ICT Sweep + FVG Entry (v6) • Pro Pack 📌 ICT Sweep + FVG Entry Pro Pack
This indicator combines key ICT price action concepts with practical execution tools to help traders spot high-probability setups faster and more objectively. It’s designed for scalpers and intraday traders who want to keep their chart clean but never miss critical market structure events.
🔑 Features
Liquidity Pools (HTF)
• Auto-detects recent swing highs/lows from higher timeframes (5m/15m).
• Draws both lines and optional rectangles/zones for clear liquidity areas.
Liquidity Sweeps (BSL/SSL)
• Identifies when price sweeps above/below liquidity pools and rejects back.
• Optional Grade-A sweep filter (wick size + strong re-entry).
Fair Value Gaps (FVGs)
• Highlights bullish/bearish imbalances.
• Optional midline (50%) entry for precision.
• Auto-invalidation when price fully closes inside the gap.
Killzones (New York)
• Highlights AM (9:30–11:30) and PM (14:00–15:30) killzones.
• Option to block signals outside killzones for higher strike rate.
Bias Badge (DR50)
• Displays if price is trading in a Bull, Bear, or Range context based on displacement range midpoint.
SMT Assist (NQ vs ES)
• Detects simple divergences between indices:
Bearish SMT → NQ makes HH while ES doesn’t.
Bullish SMT → NQ makes LL while ES doesn’t.
SL/TP Helper & R:R Label
• Automatically draws stop loss (at sweep extreme) and target (opposite pool or recent swing).
• Displays expected Risk:Reward ratio and blocks entries if below your chosen minimum.
Filters
• ATR filter ensures signals only appear in sufficient volatility.
• Sweep quality filter avoids weak wicks and fake-outs.
🎯 How to Use
Start on HTF (5m/15m) → Identify liquidity zones and bias.
Drop to LTF (1m) → Wait for a liquidity sweep confirmation.
Check for FVG in the sweep’s direction → Look for retest entry.
Use the SL/TP helper to validate your risk/reward before taking the trade.
Focus entries during NY Killzones for maximum effectiveness.
✅ Why this helps
This tool reduces screen time and hesitation by automating repetitive ICT concepts:
Liquidity pools, sweeps, and FVGs are marked automatically.
Killzone timing and SMT divergence are simplified.
Clear visual signals for entries with built-in RR filter help keep your trading mechanical.
⚠️ Disclaimer: This script is for educational purposes only. It does not provide financial advice or guarantee results. Always use proper risk management.
TRAPPER TRENDLINES — PRICEDraws dynamic trendlines on price by connecting the two most recent confirmed swing points (highs to highs for resistance, lows to lows for support). Swings are defined with a symmetric left/right pivot window. Old anchors are ignored so lines stay attached to current structure. Optional break alerts are included.
How it works (plain language)
Pivots: A bar is a swing high (or low) only if it’s the most extreme point compared with a set number of bars on the left and the right.
Lines:
Support connects the last two confirmed swing lows.
Resistance connects the last two confirmed swing highs.
Lines can be extended right only or both left & right (toggle).
Recency filter: Only swings within the last N bars are kept. This avoids anchoring to very old pivots far from current price.
Alerts: Optional alerts fire when price closes above resistance or below support.
Inputs
Auto Settings
Auto pivot size by chart timeframe: When ON, the script picks a pivot size suitable for the current timeframe (you can scale it with Auto pivot multiplier). When OFF, the manual left/right inputs are used.
Auto pivot multiplier: Scales the auto pivot size (e.g., 1.5 makes pivots stricter).
Manual Pivots
Pivot Left / Pivot Right: Bars to the left/right required to confirm a swing. Example: Left=50 & Right=50 keeps only major swings.
Recency Filter
Use last N bars for pivots: Swings older than this window are discarded so trendlines stay relevant to current price.
Style
Support/Resistance color: Line colors.
Extend Left & Right: When ON, both endpoints extend; when OFF, lines extend to the right only.
Alerts
Enable Break Alerts: When ON, alert conditions are exposed:
Price: Break Up — close above resistance.
Price: Break Down — close below support.
Suggested settings
Higher timeframes (4H / 1D / 1W):
Manual: Pivot Left = 50, Pivot Right = 50, Use last N bars = 400–800.
Or enable Auto with Auto pivot multiplier = 1.0–1.5.
Intraday (15m / 30m / 1H):
Manual: Pivot Left = 30, Pivot Right = 30, Use last N bars = 300–500.
Or enable Auto with multiplier ≈ 1.0–1.2.
Pairing with RSI for confluence/divergence
This tool is designed to pair with a companion TRAPPER TRENDLINES — RSI (or any RSI trendline script):
To mirror swings, set RSI Pivot Lookback equal to the price Pivot Left/Right you use here.
Example: Price = 50/50 → RSI Pivot Lookback = 50.
Keep RSI at Length 14 with 70/30 channel for clarity.
Confluence: Price holds/rejects at a trendline while RSI trendline agrees.
Divergence: Price prints a higher high (resistance line rising) while RSI prints a lower high (RSI resistance line falling), or vice-versa for lows. Matching pivot windows makes these relationships clear and reduces false signals.
Reading the signals
Trendline touch/hold: Potential reaction area; wait for follow-through.
Break Up / Break Down (alerts): Close beyond the line. Consider retest behavior, higher-timeframe context, and volume/RSI confirmation.
Notes & limitations
Pivots require future bars to confirm (by design). Lines update as pivots confirm.
“Use last N bars” purposely ignores very old swings. Increase this value if you need legacy structure.
Lines are based on two most recent confirmed pivots per side; rapidly changing markets can replace anchors as new swings confirm.
This is a visual/analytical tool. No strategy entries/exits or performance claims are provided.
Compliance
This script is for educational purposes only and does not constitute financial advice. Trading involves risk. Past results do not guarantee future outcomes. No promises of profit, accuracy, or performance are made.
Alerts (titles/messages)
Price: Break Up — “Price broke above resistance trendline.”
Price: Break Down — “Price broke below support trendline.”
Quick start
Add the indicator to your chart.
Choose Auto or set Pivot Left/Right manually.
Set Use last N bars for how far back to consider swings.
Toggle Extend Left & Right to your preference.
(Optional) Add your RSI trendline indicator and match Pivot Lookback with your price pivot size for clean confluence/divergence.
Enable alerts if you want notifications on breaks.
Hilly's Advanced Crypto Scalping Strategy - 5 Min ChartTo determine the "best" input parameters for the Advanced Crypto Scalping Strategy on a 5-minute chart, we need to consider the goals of optimizing for profitability, minimizing false signals, and adapting to the volatile nature of cryptocurrencies. The default parameters in the script are a starting point, but the optimal values depend on the specific cryptocurrency pair, market conditions, and your risk tolerance. Below, I'll provide recommended input values based on common practices in crypto scalping, along with reasoning for each parameter. I’ll also suggest how to fine-tune them using TradingView’s backtesting and optimization tools.
Recommended Input Parameters
These values are tailored for a 5-minute chart for liquid cryptocurrencies like BTC/USD or ETH/USD on exchanges like Binance or Coinbase. They aim to balance signal frequency and accuracy for day trading.
Fast EMA Length (emaFastLen): 9
Reasoning: A 9-period EMA is commonly used in scalping to capture short-term price movements while remaining sensitive to recent price action. It reacts faster than the default 10, aligning with the 5-minute timeframe.
Slow EMA Length (emaSlowLen): 21
Reasoning: A 21-period EMA provides a good balance for identifying the broader trend on a 5-minute chart. It’s slightly longer than the default 20 to reduce noise while confirming the trend direction.
RSI Length (rsiLen): 14
Reasoning: The default 14-period RSI is a standard choice for momentum analysis. It works well for detecting overbought/oversold conditions without being too sensitive on short timeframes.
RSI Overbought (rsiOverbought): 75
Reasoning: Raising the overbought threshold to 75 (from 70) reduces false sell signals in strong bullish trends, which are common in crypto markets.
RSI Oversold (rsiOversold): 25
Reasoning: Lowering the oversold threshold to 25 (from 30) filters out weaker buy signals, ensuring entries occur during stronger reversals.
MACD Fast Length (macdFast): 12
Reasoning: The default 12-period fast EMA for MACD is effective for capturing short-term momentum shifts in crypto, aligning with scalping goals.
MACD Slow Length (macdSlow): 26
Reasoning: The default 26-period slow EMA is a standard setting that works well for confirming momentum trends without lagging too much.
MACD Signal Smoothing (macdSignal): 9
Reasoning: The default 9-period signal line is widely used and provides a good balance for smoothing MACD crossovers on a 5-minute chart.
Bollinger Bands Length (bbLen): 20
Reasoning: The default 20-period Bollinger Bands are effective for identifying volatility breakouts, which are key for scalping in crypto markets.
Bollinger Bands Multiplier (bbMult): 2.0
Reasoning: A 2.0 multiplier is standard and captures most price action within the bands. Increasing it to 2.5 could reduce signals but improve accuracy in highly volatile markets.
Stop Loss % (slPerc): 0.8%
Reasoning: A tighter stop loss of 0.8% (from 1.0%) suits the high volatility of crypto, helping to limit losses on false breakouts while keeping risk manageable.
Take Profit % (tpPerc): 1.5%
Reasoning: A 1.5% take-profit target (from 2.0%) aligns with scalping’s goal of capturing small, frequent gains. Crypto markets often see quick reversals, so a smaller target increases the likelihood of hitting profits.
Use Candlestick Patterns (useCandlePatterns): True
Reasoning: Enabling candlestick patterns (e.g., engulfing, hammer) adds confirmation to signals, reducing false entries in choppy markets.
Use Volume Filter (useVolumeFilter): True
Reasoning: The volume filter ensures signals occur during high-volume breakouts, which are more likely to sustain in crypto markets.
Signal Arrow Size (signalSize): 2.0
Reasoning: Increasing the arrow size to 2.0 (from 1.5) makes buy/sell signals more visible on the chart, especially on smaller screens or volatile price action.
Background Highlight Transparency (bgTransparency): 85
Reasoning: A slightly higher transparency (85 from 80) keeps the background highlights subtle but visible, avoiding chart clutter.
How to Apply These Parameters
Copy the Script: Use the Pine Script provided in the previous response.
Paste in TradingView: Open TradingView, go to the Pine Editor, paste the code, and click "Add to Chart."
Set Parameters: In the strategy settings, manually input the recommended values above or adjust them via the input fields.
Test on a 5-Minute Chart: Apply the strategy to a liquid crypto pair (e.g., BTC/USDT, ETH/USDT) on a 5-minute chart.
Fine-Tuning for Optimal Performance
To find the absolute best parameters for your specific trading pair and market conditions, use TradingView’s Strategy Tester and optimization features:
Backtesting:
Run the strategy on historical data for your chosen pair (e.g., BTC/USDT on Binance).
Check metrics like Net Profit, Profit Factor, Win Rate, and Max Drawdown in the Strategy Tester.
Focus on a sample period of at least 1–3 months to capture various market conditions (bull, bear, sideways).
Parameter Optimization:
In the Strategy Tester, click the settings gear next to the strategy name.
Enable optimization for key inputs like emaFastLen (test range: 7–12), emaSlowLen (15–25), slPerc (0.5–1.5), and tpPerc (1.0–3.0).
Run the optimization to find the combination with the highest net profit or best Sharpe ratio, but avoid over-optimization (curve-fitting) by testing on out-of-sample data.
Market-Specific Adjustments:
Volatile Pairs (e.g., DOGE/USDT): Use tighter stop losses (e.g., 0.5–0.7%) and smaller take-profit targets (e.g., 1.0–1.2%) to account for rapid price swings.
Stable Pairs (e.g., BTC/USDT): Slightly wider stop losses (e.g., 1.0–1.2%) and take-profit targets (e.g., 1.8–2.5%) may work better.
Trending Markets: Increase emaSlowLen (e.g., to 25–30) to follow stronger trends.
Choppy Markets: Tighten bbMult (e.g., to 1.8) and lower rsiOverbought/rsiOversold (e.g., to 70/30) to filter noise.
Forward Testing:
After backtesting, run the strategy in real-time on a demo account for 1–2 weeks to validate performance under current market conditions.
Important Notes
No Universal "Best" Numbers: Optimal parameters vary by crypto pair, exchange, and market conditions (e.g., bull vs. bear market). The suggested values are a starting point based on common scalping practices.
Risk Management: Never risk more than 1–2% of your account per trade. Adjust position sizing in TradingView’s strategy settings to align with your risk tolerance.
Market Volatility: Crypto markets are highly volatile. Test the strategy on your specific pair and adjust parameters if signals are too frequent or too rare.
Not Financial Advice: This is an educational tool. Backtest thoroughly and use a demo account before trading with real funds.
If you want me to generate a chart showing backtest performance for specific parameters or to tweak the script further (e.g., adding more indicators or adjusting signal logic), let me know!can you add clear buy ans sell signs above the candles in this codeTo add clear buy and sell signals above the candles in the provided Pine Script, I'll modify the existing code to include prominent text labels directly above (for sell signals) and below (for buy signals) the candles. These labels will be larger, color-coded, and positioned to avoid clutter, ensuring they are easily visible on the chart. The core strategy logic (EMA, RSI, MACD, Bollinger Bands, candlestick patterns, and volume filter) will remain unchanged, and I'll reuse the same artifact_id since this is an update to the previous script.AdvancedCryptoScalpingStrategy.pinex-pine
Dow Theory Indicator## 🎯 Key Features of the Indicator
### 📈 Complete Implementation of Dow Theory
- Three-tier trend structure: primary trend (50 periods), secondary trend (20 periods), and minor trend (10 periods).
- Swing point analysis: automatically detects critical swing highs and lows.
- Trend confirmation mechanism: strict confirmation logic based on consecutive higher highs/higher lows or lower highs/lower lows.
- Volume confirmation: ensures price moves are supported by trading volume.
### 🕐 Flexible Timeframe Parameters
All key parameters are adjustable, making it especially suitable for U.S. equities:
Trend analysis parameters:
- Primary trend period: 20–200 (default 50; recommended 50–100 for U.S. stocks).
- Secondary trend period: 10–100 (default 20; recommended 15–30 for U.S. stocks).
- Minor trend period: 5–50 (default 10; recommended 5–15 for U.S. stocks).
Dow Theory parameters:
- Swing high/low lookback: 5–50 (default 10).
- Trend confirmation bar count: 1–10 (default 3).
- Volume confirmation period: 10–100 (default 20).
### 🇺🇸 U.S. Market Optimizations
- Session awareness: distinguishes Regular Trading Hours (9:30–16:00 EST) from pre-market and after-hours.
- Pre/post-market weighting: adjustable weighting factor for signals during extended hours.
- Earnings season filter: automatically adjusts sensitivity during earnings periods.
- U.S.-optimized default parameters.
## 🎨 Visualization
1. Trend lines: three differently colored trend lines.
2. Background fill: green (uptrend) / red (downtrend) / gray (neutral).
3. Signal markers: arrows, labels, and warning icons.
4. Swing point markers: small triangles at key turning points.
5. Info panel: real-time display of eight key metrics.
## 🚨 Alert System
- Trend turning to up/down.
- Strong bullish/bearish signals (dual confirmation).
- Volume divergence warning.
- New swing high/low formed.
## 📋 How to Use
1. Open the Pine Editor in TradingView.
2. Copy the contents of dow_theory_indicator.pine.
3. Paste and click “Add to chart.”
4. Adjust parameters based on trading style:
- Long-term investing: increase all period parameters.
- Swing trading: use the default parameters.
- Short-term trading: decrease all period parameters.
## 💡 Parameter Tips for U.S. Stocks
- Large-cap blue chips (AAPL, MSFT): primary 60–80, secondary 25–30.
- Mid-cap growth stocks: primary 40–60, secondary 18–25.
- Small-cap high-volatility stocks: primary 30–50, secondary 15–20.
Optimized ADX DI CCI Strategy### Key Features:
- Combines ADX, DI+/-, CCI, and RSI for signal generation.
- Supports customizable timeframes for indicators.
- Offers multiple exit conditions (Moving Average cross, ADX change, performance-based stop-loss).
- Tracks and displays trade statistics (e.g., win rate, capital growth, profit factor).
- Visualizes trades with labels and optional background coloring.
- Allows countertrading (opening an opposite trade after closing one).
1. **Indicator Calculation**:
- **ADX and DI+/-**: Calculated using the `ta.dmi` function with user-defined lengths for DI and ADX smoothing.
- **CCI**: Computed using the `ta.cci` function with a configurable source (default: `hlc3`) and length.
- **RSI (optional)**: Calculated using the `ta.rsi` function to filter overbought/oversold conditions.
- **Moving Averages**: Used for CCI signal smoothing and trade exits, with support for SMA, EMA, SMMA (RMA), WMA, and VWMA.
2. **Signal Generation**:
- **Buy Signal**: Triggered when DI+ > DI- (or DI+ crosses over DI-), CCI > MA (or CCI crosses over MA), and optional ADX/RSI filters are satisfied.
- **Sell Signal**: Triggered when DI+ < DI- (or DI- crosses over DI+), CCI < MA (or CCI crosses under MA), and optional ADX/RSI filters are satisfied.
3. **Trade Execution**:
- **Entry**: Long or short trades are opened using `strategy.entry` when signals are detected, provided trading is allowed (`allow_long`/`allow_short`) and equity is positive.
- **Exit**: Trades can be closed based on:
- Opposite signal (if no other exit conditions are used).
- MA cross (price crossing below/above the exit MA for long/short trades).
- ADX percentage change exceeding a threshold.
- Performance-based stop-loss (trade loss exceeding a percentage).
- **Countertrading**: If enabled, closing a trade triggers an opposite trade (e.g., closing a long opens a short).
4. **Visualization**:
- Labels are plotted at trade entries/exits (e.g., "BUY," "SELL," arrows).
- Optional background coloring highlights open trades (green for long, red for short).
- A statistics table displays real-time metrics (e.g., capital, win rates).
5. **Trade Tracking**:
- Tracks the number of long/short trades, wins, and overall performance.
- Monitors equity to prevent trading if it falls to zero.
### 2.3 Key Components
- **Indicator Calculations**: Uses `request.security` to fetch indicator data for the specified timeframe.
- **MA Function**: A custom `ma_func` handles different MA types for CCI and exit conditions.
- **Signal Logic**: Combines crossover/under checks with recent bar windows for flexibility.
- **Exit Conditions**: Multiple configurable exit strategies for risk management.
- **Statistics Table**: Updates dynamically with trade and capital metrics.
## 3. Configuration Options
The script provides extensive customization through input parameters, grouped for clarity in the TradingView settings panel. Below is a detailed breakdown of each setting and its impact.
### 3.1 Strategy Settings (Global)
- **Initial Capital**: Default `10000`. Sets the starting capital for backtesting.
- **Effect**: Determines the base equity for calculating position sizes and performance metrics.
- **Default Quantity Type**: `strategy.percent_of_equity` (50% of equity).
- **Effect**: Controls the size of each trade as a percentage of available equity.
- **Pyramiding**: Default `2`. Allows up to 2 simultaneous trades in the same direction.
- **Effect**: Enables multiple entries if conditions are met, increasing exposure.
- **Commission**: 0.2% per trade.
- **Effect**: Simulates trading fees, reducing net profit in backtesting.
- **Margin**: 100% for long and short trades.
- **Effect**: Assumes no leverage; adjust for margin trading simulations.
- **Calc on Every Tick**: `true`.
- **Effect**: Ensures real-time signal updates for precise execution.
### 3.2 Indicator Settings
- **Indicator Timeframe** (`indicator_timeframe`):
- **Options**: `""` (chart timeframe), `1`, `5`, `15`, `30`, `60`, `240`, `D`, `W`.
- **Default**: `""` (uses chart timeframe).
- **Effect**: Determines the timeframe for ADX, DI, CCI, and RSI calculations. A higher timeframe reduces noise but may delay signals.
### 3.3 ADX & DI Settings
- **DI Length** (`adx_di_len`):
- **Default**: `30`.
- **Range**: Minimum `1`.
- **Effect**: Sets the period for calculating DI+ and DI-. Longer periods smooth trends but reduce sensitivity.
- **ADX Smoothing Length** (`adx_smooth_len`):
- **Default**: `14`.
- **Range**: Minimum `1`.
- **Effect**: Smooths the ADX calculation. Longer periods produce smoother ADX values.
- **Use ADX Filter** (`use_adx_filter`):
- **Default**: `false`.
- **Effect**: If `true`, requires ADX to exceed the threshold for signals to be valid, filtering out weak trends.
- **ADX Threshold** (`adx_threshold`):
- **Default**: `25`.
- **Range**: Minimum `0`.
- **Effect**: Sets the minimum ADX value for valid signals when the filter is enabled. Higher values restrict trades to stronger trends.
### 3.4 CCI Settings
- **CCI Length** (`cci_length`):
- **Default**: `20`.
- **Range**: Minimum `1`.
- **Effect**: Sets the period for CCI calculation. Longer periods reduce noise but may lag.
- **CCI Source** (`cci_src`):
- **Default**: `hlc3` (average of high, low, close).
- **Effect**: Defines the price data for CCI. `hlc3` is standard, but users can choose other sources (e.g., `close`).
- **CCI MA Type** (`ma_type`):
- **Options**: `SMA`, `EMA`, `SMMA (RMA)`, `WMA`, `VWMA`.
- **Default**: `SMA`.
- **Effect**: Determines the moving average type for CCI signal smoothing. EMA is more responsive; VWMA weights by volume.
- **CCI MA Length** (`ma_length`):
- **Default**: `14`.
- **Range**: Minimum `1`.
- **Effect**: Sets the period for the CCI MA. Longer periods smooth the MA but may delay signals.
### 3.5 RSI Filter Settings
- **Use RSI Filter** (`use_rsi_filter`):
- **Default**: `false`.
- **Effect**: If `true`, applies RSI-based overbought/oversold filters to signals.
- **RSI Length** (`rsi_length`):
- **Default**: `14`.
- **Range**: Minimum `1`.
- **Effect**: Sets the period for RSI calculation. Longer periods reduce sensitivity.
- **RSI Lower Limit** (`rsi_lower_limit`):
- **Default**: `30`.
- **Range**: `0` to `100`.
- **Effect**: Defines the oversold threshold for buy signals. Lower values allow trades in more extreme conditions.
- **RSI Upper Limit** (`rsi_upper_limit`):
- **Default**: `70`.
- **Range**: `0` to `100`.
- **Effect**: Defines the overbought threshold for sell signals. Higher values allow trades in more extreme conditions.
### 3.6 Signal Settings
- **Cross Window** (`cross_window`):
- **Default**: `0`.
- **Range**: `0` to `5` bars.
- **Effect**: Specifies the lookback period for detecting DI+/- or CCI crosses. `0` requires crosses on the current bar; higher values allow recent crosses, increasing signal frequency.
- **Allow Long Trades** (`allow_long`):
- **Default**: `true`.
- **Effect**: Enables/disables new long trades. If `false`, only closing existing longs is allowed.
- **Allow Short Trades** (`allow_short`):
- **Default**: `true`.
- **Effect**: Enables/disables new short trades. If `false`, only closing existing shorts is allowed.
- **Require DI+/DI- Cross for Buy** (`buy_di_cross`):
- **Default**: `true`.
- **Effect**: If `true`, requires a DI+ crossover DI- for buy signals; if `false`, DI+ > DI- is sufficient.
- **Require CCI Cross for Buy** (`buy_cci_cross`):
- **Default**: `true`.
- **Effect**: If `true`, requires a CCI crossover MA for buy signals; if `false`, CCI > MA is sufficient.
- **Require DI+/DI- Cross for Sell** (`sell_di_cross`):
- **Default**: `true`.
- **Effect**: If `true`, requires a DI- crossover DI+ for sell signals; if `false`, DI+ < DI- is sufficient.
- **Require CCI Cross for Sell** (`sell_cci_cross`):
- **Default**: `true`.
- **Effect**: If `true`, requires a CCI crossunder MA for sell signals; if `false`, CCI < MA is sufficient.
- **Countertrade** (`countertrade`):
- **Default**: `true`.
- **Effect**: If `true`, closing a trade triggers an opposite trade (e.g., close long, open short) if allowed.
- **Color Background for Open Trades** (`color_background`):
- **Default**: `true`.
- **Effect**: If `true`, colors the chart background green for long trades and red for short trades.
### 3.7 Exit Settings
- **Use MA Cross for Exit** (`use_ma_exit`):
- **Default**: `true`.
- **Effect**: If `true`, closes trades when the price crosses the exit MA (below for long, above for short).
- **MA Length for Exit** (`ma_exit_length`):
- **Default**: `20`.
- **Range**: Minimum `1`.
- **Effect**: Sets the period for the exit MA. Longer periods delay exits.
- **MA Type for Exit** (`ma_exit_type`):
- **Options**: `SMA`, `EMA`, `SMMA (RMA)`, `WMA`, `VWMA`.
- **Default**: `SMA`.
- **Effect**: Determines the MA type for exit signals. EMA is more responsive; VWMA weights by volume.
- **Use ADX Change Stop-Loss** (`use_adx_stop`):
- **Default**: `false`.
- **Effect**: If `true`, closes trades when the ADX changes by a specified percentage.
- **ADX % Change for Stop-Loss** (`adx_change_percent`):
- **Default**: `5.0`.
- **Range**: Minimum `0.0`, step `0.1`.
- **Effect**: Specifies the percentage change in ADX (vs. previous bar) that triggers a stop-loss. Higher values reduce premature exits.
- **Use Performance Stop-Loss** (`use_perf_stop`):
- **Default**: `false`.
- **Effect**: If `true`, closes trades when the loss exceeds a percentage threshold.
- **Performance Stop-Loss (%)** (`perf_stop_percent`):
- **Default**: `-10.0`.
- **Range**: `-100.0` to `0.0`, step `0.1`.
- **Effect**: Specifies the loss percentage that triggers a stop-loss. More negative values allow larger losses before exiting.
## 4. Visual and Statistical Output
- **Labels**: Displayed at trade entries/exits with arrows (↑ for buy, ↓ for sell) and text ("BUY," "SELL"). A "No Equity" label appears if equity is zero.
- **Background Coloring**: Optionally colors the chart background (green for long, red for short) to indicate open trades.
- **Statistics Table**: Displayed at the top center of the chart, updated on timeframe changes or trade events. Includes:
- **Capital Metrics**: Initial capital, current capital, capital growth (%).
- **Trade Metrics**: Total trades, long/short trades, win rate, long/short win rates, profit factor.
- **Open Trade Status**: Indicates if a long, short, or no trade is open.
## 5. Alerts
- **Buy Signal Alert**: Triggered when `buy_signal` is true ("Cross Buy Signal").
- **Sell Signal Alert**: Triggered when `sell_signal` is true ("Cross Sell Signal").
- **Usage**: Users can set up TradingView alerts to receive notifications for trade signals.
RSI Multi Time FrameWhat it is
A clean, two-layer RSI that shows your chart-timeframe RSI together with a higher-timeframe (HTF) RSI on the same pane. The HTF line is drawn as a live segment plus frozen “steps” for each completed HTF bar, so you can see where the higher timeframe momentum held during your lower-timeframe bars.
How it works
Auto HTF mapping (when “Auto” is selected):
Intraday < 30m → uses 60m (1-hour) RSI
30m ≤ tf < 240m (4h) → uses 240m (4-hour) RSI
240m ≤ tf < 1D → uses 1D RSI
1D → uses 1W RSI
1W or 2W → uses 1M RSI
≥ 1M → keeps the same timeframe
The HTF series is requested with request.security(..., gaps_off, lookahead_off), so values are confirmed bar-by-bar. When a new HTF bar begins, the previous value is “frozen” as a horizontal segment; the current HTF value is shown by a short moving segment and a small dot (so you can read the last value easily).
Visuals
Current RSI (chart TF): solid line (color/width configurable).
HTF RSI: same-pane line + tiny circle for the latest value; historical step segments show completed HTF bars.
Guides: dashed 70 / 30 bands, dotted 60/40 helpers, dashed 50 midline.
Inputs
Higher Time Frame: Auto or a fixed TF (1, 3, 5, 10, 15, 30, 45, 60, 120, 180, 240, 360, 480, 720, D, W, 2W, M, 3M, 6M, 12M).
Length: RSI period (default 14).
Source: price source for RSI.
RSI / HTF RSI colors & widths.
Number of HTF RSI Bars: how many frozen HTF segments to keep.
Reading it
Alignment: When RSI (current TF) and HTF RSI both push in the same direction, momentum is aligned across frames.
Divergence across frames: Current RSI failing to confirm HTF direction can warn about chops or early slowdowns.
Zones: 70/30 boundaries for classic overbought/oversold; 60/40 can be used as trend bias rails; 50 is the balance line.
This is a context indicator, not a signal generator. Combine with your entry/exit rules.
Notes & limitations
HTF values do not repaint after their bar closes (lookahead is off). The short “live” segment will evolve until the HTF bar closes — this is expected.
Very small panels or extremely long histories may impact performance if you keep a large number of HTF segments.
Credits
Original concept by LonesomeTheBlue; Pine v6 refactor and auto-mapping rules by trading_mura.
Suggested use
Day traders: run the indicator on 5–15m and keep HTF on Auto to see 1h/4h momentum.
Swing traders: run it on 1h–4h and watch the daily HTF.
Position traders: run on daily and watch the weekly HTF.
If you find it useful, a ⭐ helps others discover it.
NY Sessions Boxes (Live Drawing)//@version=5
indicator("NY Sessions Boxes (Live Drawing)", overlay=true)
ny_tz = "America/New_York"
t = time(timeframe.period, ny_tz)
hour_ny = hour(t)
minute_ny = minute(t)
// سشن ۱: 02:00 – 05:00
session1_active = (hour_ny >= 2 and hour_ny < 5)
session1_start = (hour_ny == 2 and minute_ny == 0)
// سشن ۲: 09:30 – 11:00
session2_active = ((hour_ny == 9 and minute_ny >= 30) or (hour_ny > 9 and hour_ny < 11))
session2_start = (hour_ny == 9 and minute_ny == 30)
var box box1 = na
var float hi1 = na
var float lo1 = na
if session1_start
hi1 := high
lo1 := low
box1 := box.new(left = time, right = time, top = high, bottom = low, bgcolor=color.new(color.blue, 85), border_color=color.blue)
if session1_active and not na(box1)
hi1 := math.max(hi1, high)
lo1 := math.min(lo1, low)
box.set_right(box1, time)
box.set_top(box1, hi1)
box.set_bottom(box1, lo1)
if not session1_active and not na(box1)
box1 := na
hi1 := na
lo1 := na
var box box2 = na
var float hi2 = na
var float lo2 = na
if session2_start
hi2 := high
lo2 := low
box2 := box.new(left = time, right = time, top = high, bottom = low, bgcolor=color.new(color.purple, 85), border_color=color.purple)
if session2_active and not na(box2)
hi2 := math.max(hi2, high)
lo2 := math.min(lo2, low)
box.set_right(box2, time)
box.set_top(box2, hi2)
box.set_bottom(box2, lo2)
if not session2_active and not na(box2)
box2 := na
hi2 := na
lo2 := na
Radial Basis Kernel RSI for LoopRadial Basis Kernel RSI for Loop
What it is
An RSI-style oscillator that uses a radial basis function (RBF) kernel to compute a similarity-weighted average of gains and losses across many lookback lengths and kernel widths (γ). By averaging dozens of RSI estimates—each built with different parameters—it aims to deliver a smoother, more robust momentum signal that adapts to changing market conditions.
How it works
The script measures up/down price changes from your chosen Source (default: close).
For each combination of RSI length and Gamma (γ) in your ranges, it builds an RSI where recent bars that look most similar (by price behavior) get more weight via an RBF kernel.
It averages all those RSIs into a single value, then smooths it with your selected Moving Average type (SMA, EMA, WMA, HMA, DEMA) and a light regression-based filter for stability.
Inputs you can tune
Min/Max RSI Kernel Length & Step: Range of RSI lookbacks to include in the ensemble (e.g., 20→40 by 1) or (e.g., 30→50 by 1).
Min/Max Gamma & Step: Controls the RBF “width.” Lower γ = broader similarity (smoother); higher γ = more selective (snappier).
Source: Price series to analyze.
Overbought / Oversold levels: Defaults 70 / 30, with a midline at 50. Shaded regions help visualize extremes.
MA Type & Period (Confluence): Final smoothing on the averaged RSI line (e.g., DEMA(44) by default).
Red “OB” labels when the line crosses down from extreme highs (~80) → potential overbought fade/exit areas.
Green “OS” labels when the line crosses up from extreme lows (~20) → potential oversold bounce/entry areas.
How to use it
Treat it like RSI, but expect fewer whipsaws thanks to the ensemble and kernel weighting.
Common approaches:
Look for crosses back inside the bands (e.g., down from >70 or up from <30).
Use the 50 midline for directional bias (above = bullish momentum tilt; below = bearish).
Combine with trend filters (e.g., your chart MA) for higher-probability signals.
Performance note: This is really heavy and depending on how much time your subscription allows you could experience this timing out. Increasing the step size is the easiest way to reduce the load time.
Works on any symbol or timeframe. Like any oscillator, best used alongside price action and risk management rather than in isolation.
Globex Trap w/ percentage [SLICKRICK]Globex Trap w/ Percentage
Overview
The Globex Trap w/ Percentage indicator is a powerful tool designed to help traders identify high-probability trading opportunities by analyzing price action during the Globex (overnight) session and regular trading hours. By combining Globex session ranges with Supply & Demand zones, this indicator highlights potential "trap" areas where significant price reactions may occur. Additionally, it calculates the Globex session range as a percentage of the daily Average True Range (ATR), providing valuable context for assessing market volatility.
This indicator is ideal for traders in futures markets or other instruments traded during Globex sessions, offering a visual and analytical edge for spotting key price levels and potential reversals or breakouts.
Key Features
Globex Session Tracking:
Visualizes the high and low of the Globex session (default: 3:00 PM to 6:30 AM PST) with customizable time settings.
Displays a semi-transparent box to mark the Globex range, with labels for "Globex High" and "Globex Low."
Calculates the Globex range as a percentage of the daily ATR, displayed as a label for quick reference.
Supply & Demand Zones:
Identifies Supply & Demand zones during regular trading hours (default: 6:00 AM to 8:00 AM PST) with customizable time settings.
Draws semi-transparent boxes to highlight these zones, aiding in the identification of key support and resistance areas.
Trap Area Identification:
Highlights potential trap zones where Globex ranges and Supply & Demand zones overlap, indicating areas where price may reverse or consolidate due to trapped traders.
Customizable Settings:
Adjust Globex and Supply & Demand session times to suit your trading preferences.
Toggle visibility of Globex and Supply & Demand zones independently.
Customize box colors for better chart readability.
Set the lookback period (default: 10 days) to control how many historical zones are displayed.
Configure the ATR length (default: 14) for the percentage calculation.
PST Timezone Default:
All times are based on Pacific Standard Time (PST) by default, ensuring accurate session tracking for users in this timezone or those aligning with U.S. West Coast market hours.
Recommended Usage
Timeframes: Best used on 1-hour charts or lower (e.g., 15-minute, 5-minute) for precise entry and exit points.
Markets: Optimized for futures (e.g., ES, NQ, CL) and other instruments traded during Globex sessions.
Historical Data: Ensure at least 10 days of historical data for optimal visualization of zones.
Strategy Integration: Use the indicator to identify potential reversals or breakouts at Globex highs/lows or Supply & Demand zones. The ATR percentage provides context for whether the Globex range is significant relative to typical daily volatility.
How It Works
Globex Session:
Tracks the high and low prices during the user-defined Globex session (default: 3:00 PM to 6:30 AM PST).
When the session ends, a box is drawn from the start to the end of the session, capturing the high and low prices.
Labels are placed at the midpoint of the session, showing "Globex High," "Globex Low," and the range as a percentage of the daily ATR (e.g., "75.23% of Daily ATR").
Supply & Demand Zones:
Tracks the high and low prices during the user-defined regular trading hours (default: 6:00 AM to 8:00 AM PST).
Draws a box to mark these zones, which often act as key support or resistance levels.
ATR Percentage:
Calculates the Globex range (high minus low) and divides it by the daily ATR to express it as a percentage.
This metric helps traders gauge whether the overnight price movement is significant compared to the instrument’s typical volatility.
Time Handling:
Uses PST (UTC-8) for all time calculations, ensuring accurate session timing for users aligning with this timezone.
Properly handles overnight sessions that cross midnight, ensuring seamless tracking.
Input Settings
Globex Session Settings:
Show Globex Session: Enable/disable Globex session visualization (default: true).
Globex Start/End Time: Set the start and end times for the Globex session (default: 3:00 PM to 6:30 AM PST).
Globex Box Color: Customize the color of the Globex session box (default: semi-transparent gray).
Supply & Demand Zone Settings:
Show Supply & Demand Zone: Enable/disable zone visualization (default: true).
Zone Start/End Time: Set the start and end times for Supply & Demand zones (default: 6:00 AM to 8:00 AM PST).
Zone Box Color: Customize the color of the zone box (default: semi-transparent aqua).
General Settings:
Days to Look Back: Number of historical days to display zones (default: 10).
ATR Length: Period for calculating the daily ATR (default: 14).
Notes
All times are in Pacific Standard Time (PST). Adjust the start and end times if your market operates in a different timezone or if you prefer different session windows.
The indicator is optimized for instruments with active Globex sessions, such as futures. Results may vary for non-24/5 markets.
A typo in the label "Globe Low" (should be "Globex Low") will be corrected in future updates.
Ensure your TradingView chart is set to display sufficient historical data to view the full lookback period.
Why Use This Indicator?
The Globex Trap w/ Percentage indicator provides a unique combination of session-based range analysis, Supply & Demand zone identification, and volatility context via the ATR percentage. Whether you’re a day trader, swing trader, or scalper, this tool helps you:
Pinpoint key price levels where institutional traders may act.
Assess the significance of overnight price movements relative to daily volatility.
Identify potential trap zones for high-probability setups.
Customize the indicator to fit your trading style and market preferences.
