True RSITrue RSI | MisinkoMaster
The True RSI is a sophisticated reimagining of classical momentum. While the standard Relative Strength Index has served as a cornerstone of technical analysis for decades, it possesses a fundamental limitation: it treats all price movements equally, regardless of the time elapsed since the market made its last major peak or trough. The True RSI solves this structural blind spot by merging price magnitude with temporal trend strength, weighting gains and losses according to their cyclical maturity.
By dynamically scaling price changes against the time-distance of local extremes, this indicator filters out lateral market noise, reduces false overbought and oversold readings during strong trends, and delivers highly responsive execution signals.
How It Works (The Core Architecture)
Instead of relying solely on arithmetic averages of upward and downward price closes, True RSI filters raw market data through a multi-dimensional momentum matrix:
Temporal Trend Weighting: The algorithm continuously tracks how recently the market has formed local highs and lows. Gains are mathematically weighted against the strength of the upward cycle, while losses are weighted against the strength of the downward cycle.
Cycle-Weighted Ratio: The accumulated, time-weighted gains and losses are calculated over your lookback period to establish a true relative strength ratio. If gains occur during an actively surging upward cycle, they are heavily amplified; if they occur during a dying trend, they are heavily discounted.
Smoothing and Normalization: This ratio is translated into a normalized scale bounded between 0 and 100, providing an incredibly smooth yet responsive oscillator curve alongside a secondary momentum velocity histogram.
Key Features
Time-Weighted Velocity: True RSI prevents premature exhaustion signals during strong, healthy trends because it understands the cyclical age of the current market move.
On-Chart Candle Morphing: The system automatically tracks the oscillator state and alters the colors of your main price bars to keep you visually aligned with the macro trend.
Overlay Execution Labels: Prints pristine Long and Short labels directly on your price pane the moment the underlying structural momentum shifts past your designated thresholds.
Internal Divergence Histogram: Built directly behind the main oscillator is a custom acceleration histogram that monitors the rate of change of the index, pinpointing hidden momentum shifts before they reflect in the price.
Input Parameters & Optimization Guide
Lookback Period: Controls the baseline window for both the cycle-strength calculations and the price change evaluations. A default of 21 bars balances macro trend stability with immediate short-term utility.
Long / Short Thresholds: The structural boundaries that dictate trend shifts. By default, crossing above 50 signals a bullish regime, while dropping below 50 initiates a bearish regime.
Overbought / Oversold Thresholds: Tailored extremes designed to isolate true premium and discount zones. The default 80 and 20 boundaries act as high-probability mean-reversion targets.
Trading Strategies & Execution
Trend Regime Shift
When momentum builds structural backing, the indicator updates its trend state:
A crossing of the True RSI above the Long Threshold triggers a green Long label on the chart, changing candle colors to vibrant green.
A crossing of the True RSI below the Short Threshold triggers a pink Short label, shifting candle colors to pink.
Exhaustion Reversals
Because price movement is weighted against cycle time, entering the overbought (80) or oversold (20) zones represents a market that is genuinely overstretched both in terms of price velocity and time. Reversals from these zones carry high statistical significance for counter-trend scalps or trailing-stop targets.
Acceleration Divergences
Watch the central histogram centered around the 50 line. When the price is grinding flat but the histogram starts to rise or fall aggressively, it shows that the internal speed of the True RSI is accelerating. This hidden momentum often foreshadows explosive breakout expansions.
Disclaimer: Trading financial markets involves high risk. This technical script is designed as an informational analytical tool to support your rule-based mechanical execution system and does not constitute financial advice. อินดิเคเตอร์
KNN Adaptive Cycles█ OVERVIEW
An adaptive Stochastic RSI whose lookback lengths are driven by the market's measured dominant cycle period, further refined in real time by a K-Nearest Neighbors machine learning layer. Rather than accepting a fixed RSI or Stochastic length, the indicator continuously measures the dominant cycle in price using two independent spectral methods, then uses KNN to anticipate where the cycle is heading and to condition the oscillator output against historical outcomes — so the indicator adapts to what the market is actually doing, not what a static setting assumes it should be.
█ CYCLE DETECTION
The indicator measures the dominant cycle period using two independent methods from the digital signal processing work of John Ehlers, who treated price as a waveform and applied engineering filters to extract its underlying structure.
Autocorrelation Periodogram
Computes Pearson correlation across lags from the minimum to maximum period range, identifying the lag at which price most strongly repeats. Returns a correlation coefficient used directly as a confidence score.
Goertzel / DFT Power Spectrum
A frequency-domain scan that computes spectral power at each candidate period and selects the one carrying the most energy. Independent of the autocorrelation method, giving two mathematically distinct perspectives on the same cycle.
Before measurement, price is conditioned with Ehlers' filter set: a Highpass filter to remove the trend component, a Super Smoother for anti-aliasing, and an optional Bandpass pre-filter to isolate the cycle band. In AC + DFT (Confirmed) mode the two estimates are cross-checked, with each method weighted by its agreement strength and the AC correlation coefficient before blending into a single confirmed period. Single-method modes run the selected method at full per-bar resolution.
█ KNN MACHINE LEARNING
Two independent KNN nearest-neighbor routines operate on top of the cycle and signal layers. Both use weighted Euclidean distance across feature vectors, a 1/distance-weighted outcome average across K neighbors, and ALMA smoothing on the output bias.
Period KNN
Searches history for bars whose cycle state most closely resembles the current bar — matching on current period, rate of change, stability streak, confidence score, and volatility regime. Observes what the period actually became Forward Bars later at each neighbor, then blends that prediction into the current period estimate before final smoothing. Helps the indicator anticipate cycle transitions rather than just react to them.
Signal KNN
Searches history for bars whose StochRSI context most closely resembles now — matching on K level, K−D histogram, K slope, volatility regime, OB/OS proximity, and D line. Observes the forward price outcome at each neighbor and blends the resulting bias into the K line before D smoothing, so D inherits the correction naturally.
█ FEATURES
Cycle detection
• Dual spectral cycle detection — AC and DFT run in parallel with a 0–100% confidence score reflecting method agreement
• Confidence-weighted period blending — each method weighted by agreement and correlation strength, smoothed into one adaptive period
• Single-method modes — Optional select Autocorrelation Only or DFT Only run for faster loading
• Optional Performance Throttle — cadence-limited spectral scans for the AC + DFT mode
KNN layer
• Period KNN — anticipates cycle transitions by learning from historical cycle states and their forward outcomes
• Signal KNN — conditions the K line against historically similar StochRSI contexts and their forward price outcomes
• Per-feature importance weights for both KNN routines — tunable to emphasize what matters most on a given instrument
• ALMA-smoothed bias output — configurable length, offset, and sigma อินดิเคเตอร์
อินดิเคเตอร์
RTI Trend State + MacroCoverRTI Trend State + MacroCover
A trend-state oscillator built on the Relative Trend Index (RTI) — a stochastic-position measure of where price sits inside its recent high/low range, then EMA-smoothed:
raw = 100 * (close - lowest(low, n)) / (highest(high, n) - lowest(low, n))
RTI = EMA(raw, smooth) -> a 0-100 line
How the state works
The 0-100 RTI is converted into a persistent LONG / FLAT / SHORT state through a hysteresis band , so it does not flip on noise around the mid-line:
RTI above the upper band -> LONG
RTI below the lower band -> SHORT
in between -> holds the last state
The gap between the two bands is the hysteresis — widen it for fewer, steadier flips; narrow it for a more reactive read.
MacroCover (optional long bias)
When the state would be SHORT but price trades above a slow EMA (default 200), the short is covered to FLAT — i.e. it won't fight the higher-timeframe uptrend. Turn MacroCover off for a symmetric long/short reading.
On the chart
The RTI line (0-100) colored by state: green long, red short, gray flat.
Dashed upper/lower bands and a dotted mid-line.
State background tint and flip markers where the state changes.
A compact table with the current RTI value, state and macro side.
The RTI value plus state_-1_0_1 and ema_macro are available in the Data Window for tooltips and cross-checks.
Inputs
RTI engine — Lookback n (30), EMA smoothing (3), upper/lower bands (55 / 45).
MacroCover — on/off and macro EMA length (200).
Timeframe — use the chart timeframe, or lock the calculation to a fixed resolution.
Visual — toggle the state background, flip markers and table.
Notes
Works on any symbol and any timeframe.
Non-repainting : values are computed on confirmed bars, and the optional higher-timeframe request uses lookahead_off.
This is a discretionary / confluence tool, not financial advice or a complete trading system.
อินดิเคเตอร์
Simple NIFTY Stochastic CE PE System PRAKASAN//@version=6
indicator(
title = "Simple NIFTY Stochastic CE PE System",
shorttitle = "Simple CE PE",
overlay = true
)
//--------------------------------------------------
// INPUTS
//--------------------------------------------------
stochLength = input.int(14, "Stochastic Length")
smoothK = input.int(3, "K Smoothing")
smoothD = input.int(3, "D Smoothing")
oversoldLevel = input.int(20, "Oversold Level")
overboughtLevel = input.int(80, "Overbought Level")
emaLength = input.int(20, "EMA Length")
useVWAP = input.bool(true, "Use VWAP Filter")
showEMA = input.bool(true, "Show EMA")
showVWAP = input.bool(true, "Show VWAP")
//--------------------------------------------------
// INDICATORS
//--------------------------------------------------
emaValue = ta.ema(close, emaLength)
vwapValue = ta.vwap(hlc3)
rawStoch = ta.stoch(close, high, low, stochLength)
stochK = ta.sma(rawStoch, smoothK)
stochD = ta.sma(stochK, smoothD)
//--------------------------------------------------
// TREND FILTER
//--------------------------------------------------
bullishTrend =
close > emaValue and
(not useVWAP or close > vwapValue)
bearishTrend =
close < emaValue and
(not useVWAP or close < vwapValue)
//--------------------------------------------------
// STOCHASTIC SIGNALS
//--------------------------------------------------
// Buy CE when Stochastic crosses upward from oversold
bullishSignal =
ta.crossover(stochK, stochD) and
stochK < 35 and
bullishTrend
// Buy PE when Stochastic crosses downward from overbought
bearishSignal =
ta.crossunder(stochK, stochD) and
stochK > 65 and
bearishTrend
//--------------------------------------------------
// TRADE STATE
//--------------------------------------------------
// 0 = waiting for CE
// 1 = CE active
// 2 = waiting for PE
// -1 = PE active
var int tradeState = 0
bool buyCE = false
bool exitCE = false
bool buyPE = false
bool exitPE = false
buyCE := false
exitCE := false
buyPE := false
exitPE := false
//--------------------------------------------------
// SIGNAL SEQUENCE
//--------------------------------------------------
// Step 1: Buy CE
if tradeState == 0 and bullishSignal
buyCE := true
tradeState := 1
// Step 2: Exit CE
if tradeState == 1 and bearishSignal
exitCE := true
tradeState := 2
// Step 3: Generate fresh Buy PE signal
else if tradeState == 2 and bearishSignal
buyPE := true
tradeState := -1
// Step 4: Exit PE
if tradeState == -1 and bullishSignal
exitPE := true
tradeState := 0
//--------------------------------------------------
// CHART SIGNALS
//--------------------------------------------------
plotshape(
buyCE,
title = "BUY CE",
text = "BUY CE",
style = shape.labelup,
location = location.belowbar,
color = color.green,
textcolor = color.white,
size = size.small
)
plotshape(
exitCE,
title = "EXIT CE",
text = "EXIT CE",
style = shape.labeldown,
location = location.abovebar,
color = color.orange,
textcolor = color.white,
size = size.small
)
plotshape(
buyPE,
title = "BUY PE",
text = "BUY PE",
style = shape.labeldown,
location = location.abovebar,
color = color.red,
textcolor = color.white,
size = size.small
)
plotshape(
exitPE,
title = "EXIT PE",
text = "EXIT PE",
style = shape.labelup,
location = location.belowbar,
color = color.blue,
textcolor = color.white,
size = size.small
)
//--------------------------------------------------
// INDICATOR LINES
//--------------------------------------------------
plot(
showEMA ? emaValue : na,
title = "EMA",
color = color.orange,
linewidth = 2
)
plot(
showVWAP ? vwapValue : na,
title = "VWAP",
color = color.purple,
linewidth = 2
)
//--------------------------------------------------
// ALERTS
//--------------------------------------------------
alertcondition(
buyCE,
title = "BUY CE Alert",
message = "BUY CE signal generated."
)
alertcondition(
exitCE,
title = "EXIT CE Alert",
message = "EXIT CE signal generated."
)
alertcondition(
buyPE,
title = "BUY PE Alert",
message = "BUY PE signal generated."
)
alertcondition(
exitPE,
title = "EXIT PE Alert",
message = "EXIT PE signal generated."
) อินดิเคเตอร์
BTC Trend-Momentum Strategy A rules-based long/short strategy designed specifically for Bitcoin, combining three complementary components:
Trend filter (EMA 200): Only trades in the direction of the prevailing trend — long above the EMA, short below it.
Volume confirmation (Chaikin Money Flow): Confirms that actual buying or selling pressure supports the trend direction before entering.
Momentum trigger (Stochastic RSI): Times entries when %K crosses back out of oversold/overbought territory, avoiding entries at momentum extremes.
Optional volatility filter (ATR vs. its moving average): Can restrict trading to periods of above-average volatility, filtering out low-volatility chop.
Risk disclosure: This strategy has no built-in stop-loss or take-profit. Positions are only closed by an opposing signal (a long signal closes an existing short and vice versa). This means an open position can theoretically run at a loss for an extended period before the opposite signal triggers. Traders should manage their own risk (position sizing, stops) independently when applying this on a live account.
Backtest settings used: Initial capital $1,000, 0.075% commission per trade, no slippage, 100% equity per trade, tested on BTC/USD from 2018 onward. Past performance does not guarantee future results.
This publication is for educational purposes only and does not constitute financial advice. กลยุทธ์
อินดิเคเตอร์
ATK/DEF RSI Context idctorRSI Context is an advanced Relative Strength Index analysis tool designed to provide a deeper understanding of RSI behavior, momentum conditions, volatility changes, and market context through a structured visual dashboard.
Traditional RSI indicators mainly display a single RSI line with fixed overbought and oversold levels. RSI Context expands this concept by analyzing RSI from multiple perspectives, including RSI strength, movement direction, volatility range, historical behavior, and important RSI events.
This indicator focuses on helping users study how RSI behaves under different market conditions and provides additional context for interpreting momentum changes.
## RSI Core Analysis
The indicator calculates RSI based on the selected RSI period and analyzes its current position and behavior.
The RSI analysis includes:
• Current RSI value
• RSI movement direction
• RSI strength and weakness conditions
• RSI relationship with the 50 midpoint level
• Momentum acceleration and deceleration
• Overbought and oversold areas
The system categorizes RSI behavior into different states to provide a clearer visual understanding of current momentum conditions.
## Dynamic RSI Volatility Framework
Unlike fixed RSI interpretation alone, RSI Context includes a dynamic volatility framework based on RSI statistical behavior.
The indicator uses RSI volatility measurements to create adaptive reference areas:
• RSI standard deviation calculation
• Dynamic upper and lower RSI boundaries
• RSI volatility expansion detection
• RSI volatility contraction observation
• Abnormal RSI movement identification
These dynamic levels help users compare current RSI movement with its recent historical behavior.
## RSI Behavior Classification
The indicator evaluates different RSI conditions and classifies them into readable states, including:
• Strong upward RSI movement
• Weakening upward momentum
• Strong downward RSI movement
• Recovery and rebound conditions
• Overboug conditions
• Oversod conditions
• Neutral and flat RSI conditions
This classification provides additional context beyond simply reading RSI valu.
## RSI Midpoint Analysis
The RSI 50 level is included as an important momentum reference area.
The indicator observes:
• Movement above the 50 level
• Movement below the 50 level
• Cross events around the midpoint
• Changes in RSI momentum direction
This helps users study transitions in RSI positioning and changes in momentum structure.
## RSI Event Detection
RSI Context automatically identifies several RSI-related events:
• RSI crossing above 50
• RSI crossing below 50
• Potential bullish divergence observation
• Potential bearish divergence observation
Detected events are displayed visually on the RSI panel for easier historical review.
The event system is designed as an analytical reference to highlight changes in RSI behavior.
## Divergence Analysis
The indicator includes price and RSI comparison logic to observe possible momentum differences.
The divergence module monitors situations where:
• Prce reaches a new recent high while RSI shows reduced strength
• Prce reaches a new recent low while RSI shows stronger RSI behavior
These observations help users study the relationship between prce movement and momentum changes.
## Historical RSI Context Table
The integrated dashboard provides recent RSI information in a structured table format.
The table includes:
• Recent bar references
• RSI values
• RSI behavior classification
• Dynamic RSI upper range
• RSI midpoint reference
• Dynamic RSI lower range
• Detected RSI events
• Context interpretation
This allows users to compare recent RSI development instead of focusing only on the current RSI reading.
## Visual RSI Dashboard
The indicator provides a complete RSI information panel containing:
• Main RSI line
• Dynamic RSI volatility bands
• 70 / 30 reference levels
• RSI 50 midpoint reference
• RSI event labels
• Historical RSI comparison table
The visual design helps users quickly review RSI structure and momentum information directly from the chart.
## Designed For
RSI Context is designed for users who study:
• RSI behavior
• Momentum analysis
• Technical analysis concepts
• Market condition observation
• Indicator research
• Price and momentum relationships
This tool can be used as part of a broader chart analysis process together with other forms of market evaluation.
## Usage Philosophy
RSI Context focuses on observation and analysis rather than automated decision-making.
The indicator presents RSI information in a structured format so users can independently interpret momentum conditions and market context.
It is designed to support learning, research, and visual analysis of RSI behavior.
## Important Notes
RSI Context is an analytical and educational indicator.
It does not provide guaranteed outcomes, financial advice, or automated trading decisions.
Users should apply their own analysis methods, timeframe selection, and risk management practices when interpreting market information.
The indicator is intended to improve understanding of RSI behavior and provide additional context for technical analysis studies.
อินดิเคเตอร์
Investory MTF Dashboard [ULTIMATE]//@version=6
indicator('Investory MTF Dashboard ', overlay = true)
// ==========================================
// --- PARAMETER INPUT ---
// ==========================================
rsi_len = input.int(14, 'RSI Length', group = 'Indikator')
ma_len = input.int(14, 'MA-RSI Length', group = 'Indikator')
fast_len = input.int(12, 'MACD Fast Length', group = 'Indikator')
slow_len = input.int(26, 'MACD Slow Length', group = 'Indikator')
sig_len = input.int(9, 'MACD Signal Smoothing', group = 'Indikator')
pos_db = input.string('Top Right', 'Posisi Dashboard', group = 'Tampilan', options = )
f_size = input.string('Normal', 'Ukuran Font', group = 'Tampilan', options = )
// --- FUNGSI POSISI & SIZE ---
f_get_pos(p_txt) =>
switch p_txt
'Top Right' => position.top_right
'Top Left' => position.top_left
'Bottom Right' => position.bottom_right
'Bottom Left' => position.bottom_left
=> position.top_right
ts = f_size == 'Tiny' ? size.tiny : f_size == 'Small' ? size.small : f_size == 'Large' ? size.large : size.normal
// ==========================================
// --- FUNGSI HITUNG (CORE) ---
// ==========================================
f_calc_indicators() =>
// RSI
rsi_v = ta.rsi(close, rsi_len)
ma_v = ta.sma(rsi_v, ma_len)
// MACD
= ta.macd(close, fast_len, slow_len, sig_len)
[rsi_v, rsi_v , ma_v, ma_v , hi, hi , ml]
// ==========================================
// --- REQUEST DATA DENGAN OPTIMASI ---
// ==========================================
// Menggunakan tuple untuk mengambil semua data sekaligus per timeframe
= request.security(syminfo.tickerid, '5', f_calc_indicators(), gaps = barmerge.gaps_off)
= request.security(syminfo.tickerid, '15', f_calc_indicators(), gaps = barmerge.gaps_off)
= request.security(syminfo.tickerid, '60', f_calc_indicators(), gaps = barmerge.gaps_off)
= request.security(syminfo.tickerid, '240', f_calc_indicators(), gaps = barmerge.gaps_off)
= request.security(syminfo.tickerid, 'D', f_calc_indicators(), gaps = barmerge.gaps_off, lookahead = barmerge.lookahead_on)
// ==========================================
// --- RENDER DASHBOARD ---
// ==========================================
// Kolom dikurangi menjadi 9 (0 sampai 8) karena kolom A/D dihapus
var table main_db = table.new(f_get_pos(pos_db), 9, 7, frame_color = color.new(color.white, 80), frame_width = 1, border_color = color.new(color.white, 80), border_width = 1)
if barstate.islast
// Warna tema
bg_main = color.new(color.black, 10)
h_bg = color.new(color.gray, 20)
l_bg = color.new(color.gray, 50)
// Header
table.cell(main_db, 0, 0, 'TF', bgcolor = h_bg, text_color = color.white, text_size = ts)
table.cell(main_db, 1, 0, 'RSI ANALYSIS', bgcolor = h_bg, text_color = color.white, text_size = ts)
table.merge_cells(main_db, 1, 0, 4, 0)
table.cell(main_db, 5, 0, 'MACD TREND', bgcolor = h_bg, text_color = color.white, text_size = ts)
table.merge_cells(main_db, 5, 0, 8, 0)
// Sub-Header
labels = array.from('-', 'RSI', 'MA', 'DIFF', 'PWR', 'HIST', 'SIG', 'PWR', 'TREND')
for j = 0 to 8 by 1
table.cell(main_db, j, 1, array.get(labels, j), bgcolor = l_bg, text_color = color.white, text_size = ts)
// Data Processing
tfs = array.from('5M', '15M', '1H', '4H', 'D')
rsis = array.from(r5, r15, r60, r240, rD)
rsips = array.from(rp5, rp15, rp60, rp240, rpD)
mas = array.from(m5, m15, m60, m240, mD)
maps = array.from(mp5, mp15, mp60, mp240, mpD)
hists = array.from(h5, h15, h60, h240, hD)
hps = array.from(hp5, hp15, hp60, hp240, hpD)
ml_s = array.from(ml5, ml15, ml60, ml240, mlD)
for i = 0 to 4 by 1
row = i + 2
// Ambil data dan handle nilai NaN (Data belum load)
rv = array.get(rsis, i)
rpv = array.get(rsips, i)
mv = array.get(mas, i)
mpv = array.get(maps, i)
hv = array.get(hists, i)
hpv = array.get(hps, i)
mlv = array.get(ml_s, i)
if not na(rv) // Cek jika data tersedia
color rc = rv > rpv ? color.lime : color.red
color mc = mv > mpv ? color.lime : color.red
table.cell(main_db, 0, row, array.get(tfs, i), bgcolor = bg_main, text_color = color.white, text_size = ts)
table.cell(main_db, 1, row, str.tostring(rv, '#.#'), bgcolor = bg_main, text_color = rc, text_size = ts)
table.cell(main_db, 2, row, str.tostring(mv, '#.#'), bgcolor = bg_main, text_color = mc, text_size = ts)
diff = rv - mv
table.cell(main_db, 3, row, str.tostring(diff, '#.#'), bgcolor = bg_main, text_color = diff >= 0 ? color.lime : color.red, text_size = ts)
table.cell(main_db, 4, row, diff >= 0 ? '▲' : '▼', bgcolor = bg_main, text_color = diff >= 0 ? color.lime : color.red, text_size = ts)
// MACD Logic
table.cell(main_db, 5, row, str.tostring(hv, '#.##'), bgcolor = bg_main, text_color = hv >= 0 ? color.lime : color.red, text_size = ts)
table.cell(main_db, 6, row, mlv > 0 ? '⬆' : '⬇', bgcolor = bg_main, text_color = mlv > 0 ? color.lime : color.red, text_size = ts)
table.cell(main_db, 7, row, hv > hpv ? '▲' : '▼', bgcolor = bg_main, text_color = hv > hpv ? color.lime : color.red, text_size = ts)
// TREND Text
string txtT = mlv > 0 and hv > hpv ? 'Bull' : mlv < 0 and hv < hpv ? 'Bear' : mlv > 0 ? 'COR' : 'REV'
color colT = txtT == 'Bull' ? color.lime : txtT == 'Bear' ? color.red : txtT == 'COR' ? color.yellow : color.orange
table.cell(main_db, 8, row, txtT, bgcolor = bg_main, text_color = colT, text_size = ts)
else // Tampilan jika data sedang loading
table.cell(main_db, 0, row, array.get(tfs, i), bgcolor = bg_main, text_color = color.white, text_size = ts)
table.cell(main_db, 1, row, 'Wait...', bgcolor = bg_main, text_color = color.gray, text_size = ts)
table.merge_cells(main_db, 1, row, 8, row)
อินดิเคเตอร์
DMI DI Gap by ByblloDMI DI Gap by Bybllo
This indicator plots the gap (difference) between the DI+ and DI- lines of the Directional Movement Index (DMI). Instead of visually comparing two separate DI+ / DI- lines to spot a crossover, the difference (DI+ minus DI-) is calculated directly and plotted as a single line around a zero baseline.
A cross above the zero line signals a shift toward bullish momentum, while a cross below the zero line signals a shift toward bearish momentum — each crossing is automatically marked with a buy or sell arrow, so there is no need to eyeball where the two DI lines intersect.
Key Features
A single "DI Gap" line (DI+ minus DI-) replaces the need to watch two overlapping DI+ / DI- lines and spot their crossovers by eye.
Zero-line crossover / crossunder is detected automatically and marked with buy (upward) and sell (downward) triangle arrows, offset a configurable distance from the zero line.
An optional ADX line, rescaled from its native 0–100 range to a custom min/max range, can be overlaid to gauge trend strength alongside the directional gap.
A filled cloud area between the gap line and the zero line is colored according to whether the current gap is positive or negative.
+25 / -25 dotted reference lines help gauge how strong the current directional imbalance is.
Real-price calculation via request.security() ensures values stay consistent regardless of chart type (Heikin Ashi, Renko, etc.).
How to Use
When the DI Gap line crosses above zero, a buy arrow appears below the zero line, indicating directional momentum has turned bullish (DI+ has overtaken DI-).
When the DI Gap line crosses below zero, a sell arrow appears above the zero line, indicating directional momentum has turned bearish (DI- has overtaken DI+).
Use the optional rescaled ADX line to check whether the broader trend has enough strength to support the signal before acting on it.
The +25 / -25 dotted lines can be used as a rough guide for how pronounced the current directional imbalance is.
Notes
The rescaled ADX line is for visual reference only; it does not represent the standard 0–100 ADX scale unless the scale inputs are set to 0 and 100.
Works consistently across chart types since real market price data is always pulled via request.security(), regardless of the chart type currently displayed. อินดิเคเตอร์
SOL RSI Strategy [3Commas]SOL RSI Long Strategy
🔷 What it does:
This is a long-only DCA (Dollar-Cost Averaging) strategy for SOL / USDT that opens a position only in deep-oversold conditions and then averages down on a fixed safety-order ladder. A base order fires when 4h RSI(14) drops below 28; if price keeps falling, five averaging orders add to the position at fixed deviations from the base entry, each larger than the last. The full position is closed at a fixed take-profit above the blended average entry. There is no trailing exit and no stop loss — the position is structurally bounded by the five-order ladder.
- Single entry filter: 4h RSI(14) below 28 (deep oversold).
- Five averaging orders at fixed deviations (−2%, −5%, −9.5%, −16%, −25%) with 1.8× size scaling per rung.
- Fixed take-profit on the blended average entry; no trailing, no stop loss.
- Every fill and close emits a webhook-ready JSON alert payload for a DCA Bot.
🔷 Who is it for:
- Swing traders accumulating SOL on deep RSI flushes rather than chasing momentum.
- Bot operators who want a chart-driven signal source with base / safety-order / close webhook JSON ready to drive a DCA Bot.
- Traders comfortable with martingale-style averaging who size their capital to the worst-case ladder fill.
- Range / mean-reversion traders who prefer mechanical oversold entries over discretionary timing.
🔷 How does it work:
Entry (Base Order): On each closed 4h bar the strategy reads RSI(14). When RSI falls below 28 and there is no open position, it opens the base order at market (or limit, optionally) and dispatches the entry webhook.
Averaging Orders: Once in a position, the strategy watches price relative to the original base entry. The five safety orders are armed at fixed deviations from that base entry — not cumulatively — at −2%, −5%, −9.5%, −16%, and −25%. As each threshold is crossed on bar close, the corresponding averaging order fires. Order sizes scale 1.8× per rung ($900 → $1,620 → $2,916 → $5,249 → $9,448 from a $500 base), pulling the blended average entry down toward the latest fill.
Exit (Take Profit): While in a position, the strategy computes a take-profit price a fixed percentage above the current average entry. When price closes at or above that level, the entire position is closed at market and the close webhook fires. There is no trailing and no stop loss.
Capital Bounds: Total deployed capital cannot exceed the base order plus the five safety orders. Once all five averaging orders are filled, no further adds occur — the position simply waits for the take-profit. This ladder cap is the strategy's primary risk control.
🔷 Why it's unique:
- Deep-Oversold-Only Entries: A single, strict RSI(14) < 28 filter on 4h keeps the strategy out of the market in normal conditions and only commits capital after a meaningful flush.
- Fixed-Deviation Martingale Ladder: Safety orders are placed at fixed percentages from the base entry with deliberate 1.8× size scaling, so each rung has progressively more influence on the average — a transparent, fully-specified averaging schedule rather than an opaque adaptive grid.
- Full Webhook Chain: Base order, each safety order, and the close all emit dedicated JSON payloads. The strategy can drive a 3Commas DCA Bot end-to-end with no glue layer.
- On-Chart Transparency: The AO ladder, average entry, and take-profit target are plotted live, and the status table reports RSI, AOs filled, base/average entry, TP target, and max deployable capital — so the position state is always visible.
🔷 Considerations Before Using the Strategy:
Trade Volume — Below the Statistical Floor: The reference backtest produced 77 closed trades over ~30 months. This is below the ~100-trade threshold often used as a floor for statistical relevance, so treat the win rate and the profit factor as indicative rather than conclusive. The strict RSI < 28 filter is what keeps the trade count low.
Martingale Tail Risk: Order sizes scale 1.8× per rung, so the deepest fills are by far the largest. If SOL trends hard below the −25% AO5 level without recovering to take-profit, the position sits fully loaded with no further adds and no stop — unrealized loss can grow until price reverts. The 1.8× scaling amplifies both the recovery speed and the downside.
No Stop Loss Justification: There is no exit on adverse moves. Per-order risk is bounded by the fixed ladder allocation; aggregate exposure is capped at base + five AOs (≈ $20,633 on the default $100k account, ~20.6% of equity). Size the base/AO inputs down to match the worst-case exposure you are willing to hold.
Capital Deployment & Drawdown: The reference backtest reached a 5.53% maximum equity drawdown at default sizing — but that depends on the configured ladder fitting within SOL's observed swings. A deeper or more prolonged decline than the test sample would produce a larger drawdown.
Fees: The default commission (0.06% per trade) should be matched to your exchange's actual taker fees. With a fixed 3% take-profit the per-trade edge is modest, so a fee mismatch matters.
Demo Testing: Always demo-test before going live. Past results do not guarantee future performance, particularly for martingale-style averaging strategies whose risk profile is dominated by rare deep drawdowns.
🔷 STRATEGY PROPERTIES
Symbol: BYBIT:SOLUSDT.P (Perpetual) — strategy is portable to any SOL / USDT pair.
Timeframe: 4H (RSI sampled on 4h).
Test Period: January 1, 2024 — July 13, 2026 (~30 months).
Initial Capital: 100,000 USDT.
Base Order Size: 500 USDT.
Averaging Orders: 5, at −2% / −5% / −9.5% / −16% / −25% from base entry.
AO Sizing: 1.8× per rung — 900 / 1,620 / 2,916 / 5,249 / 9,448 USDT.
Max Deployed Capital: ≈ 20,633 USDT (~20.6% of equity, all AOs filled).
Commission: 0.06% per trade.
Slippage: 3 ticks.
Entry Filter: 4h RSI(14) below 28.
Take Profit: 3% above average entry.
Stop Loss: None — ladder allocation is the structural risk cap.
Trailing: None.
Strategy: Long Only.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +5,178.77 USDT (+5.18%)
Max Equity Drawdown: 5,748.16 USDT (5.53%)
Total Closed Trades: 77
Percent Profitable: 67.53% (52 / 77)
Profit Factor: 4.582
🔷 How to Use It:
🔸 Adjust Settings: Open the strategy inputs and confirm the RSI level (28), the five AO deviations and sizes, and the take-profit percentage match your risk profile. Scale the base/AO sizes down for lower exposure.
🔸 Results Review: Run a full-period backtest and confirm Max Drawdown stays within your personal risk band — note this configuration reached 5.53%. Keep in mind the 77-trade sample is below the ~100-trade floor for statistical confidence.
🔸 Create alerts to trigger the DCA Bot: Add one alert on the strategy using "Any alert() function call". Paste your DCA Bot's webhook URL into the alert's Webhook field, and fill the Bot ID, Email Token, and Pair inputs on the script. The base order, each safety order, and the close will each emit a dedicated JSON payload.
🔷 INDICATOR SETTINGS
Base Order Size: Capital committed on the first (base) entry.
AO Deviations: Fixed percentage distances from the base entry where each safety order fires.
AO Sizes: Capital per safety order (1.8× scaling by default).
RSI Timeframe / Length / Level: Oversold filter for the base entry (default 4h, 14, below 28).
Take Profit (%): Distance above average entry where the full position closes.
Bot ID / Email Token / Pair: Webhook fields injected into every alert payload.
Visualization: Toggle the AO ladder, fill labels, avg/TP lines, and status table.
Brand Watermark: Configurable text, position, size, and transparency.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc. กลยุทธ์
Percentile Context [RC Tools]RC Tools — Percentile Context
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█ OVERVIEW
Not "is RSI over 70" — "where does today's reading actually sit in its own history?" This tool takes a metric of your choice (realised volatility, RSI, volume, rate of change, or any custom source you plug in) and ranks it as a percentile against its own trailing distribution. It's the statistical primitive underneath most technical analysis, made explicit instead of buried in a fixed threshold.
█ WHAT IT DOES
Plots a 0–100 percentile-rank line for the selected metric, flags "extreme" zones (default: below the 10th percentile or above the 90th), and shows a stats table with the current value, current percentile, all-time min/max seen on the chart, and how many bars it's been since the metric last hit either extreme.
█ THE THEORY BEHIND IT
Fixed thresholds ("RSI > 70 = overbought") assume a metric's meaningful range never changes. It does — across assets, and across time on the same asset. A percentile rank fixes this by asking a relative question instead of an absolute one: given everything this metric has done over its own trailing window, how unusual is today's reading? This is the same idea underneath the Regime Classifier's volatility-state measure, generalised to any metric.
█ HOW IT IS CALCULATED
The selected metric is computed per bar:
• Realised Volatility: stdev(log(close/close ), N)
• RSI: standard Wilder RSI
• Volume: raw bar volume
• Rate of Change %: (close − close ) / close × 100
• Custom Source: whatever series you plug into the source input (e.g. another indicator's plot)
The metric is then percentile-ranked against its own trailing window (default 750 bars ≈ 3 years on daily): what percentage of the last N readings were below today's value. Display values update ONLY on confirmed bar close — nothing here repaints.
█ SETTINGS & CONFIGURATION
• Metric (default Realised Volatility) — what gets ranked
• Custom Source — only used when Metric = Custom Source
• Realised Volatility / RSI / Rate of Change lookbacks (defaults 20 / 14 / 20)
• Percentile Ranking Window (default 750 bars) — longer = more stable, needs more history
• Low / High Extreme Thresholds (default 10 / 90)
• Paint Main Chart Background — off by default to avoid clashing with the Regime Classifier's background if you run both at once
█ HOW TO USE IT
Use it to calibrate how seriously to take a "normal" indicator reading. Example: RSI at 75 means something different on a stock that's rarely above 60 than on one that regularly touches 85 — the percentile rank makes that comparison explicit for the SAME asset over time. Also useful for volatility context ahead of position sizing: current realised vol at the 95th percentile is a different risk environment than the same absolute vol reading at the 40th percentile.
Works on any asset and timeframe with sufficient history for the percentile window.
█ LIMITATIONS
• Percentile rank describes the past relative to itself — it says nothing about direction or what happens next. A metric at its 99th percentile can stay there.
• Needs substantial history for a stable ranking. On short-history assets, treat the percentile as unreliable.
• "Extreme" is relative to the metric's OWN range. A percentile extreme on a low-volatility asset is not directly comparable in absolute terms to one on a high-volatility asset — that's the point of the tool, but it means percentiles aren't comparable across symbols.
• All-time min/max and "bars since" stats are only as long as the chart's available history, not a fixed universal record.
• This script does NOT repaint. Display values update on confirmed bar close only.
█ DISCLAIMER
For educational and informational purposes only. Nothing here is financial advice. Past behaviour of any metric does not indicate future results. Trade at your own risk.
อินดิเคเตอร์
อินดิเคเตอร์
อินดิเคเตอร์
Zero-Lag MACD Divergence Pro Zero-Lag MACD Divergence Pro is a MACD-family oscillator that reduces the indicator's inherent lag using zero-lag exponential averaging, detects regular divergences directly inside the MACD pane, and optionally gates its buy/sell markers so they only appear when a divergence and a crossover confirm each other. It is designed for intraday timeframes but works on any chart.
What makes it original
This is not a standard MACD with cosmetic changes. Three elements work as one system: (1) all three components — fast line, slow line, and signal line — are rebuilt on zero-lag EMAs rather than standard EMAs, (2) divergence detection runs on the zero-lag MACD line itself and draws its lines and labels inside the oscillator pane, with an optional mirrored dashed line on the price chart, and (3) a combo-gating mode suppresses crossover markers unless a divergence was confirmed within a recent, user-defined window, which filters the many insignificant crossovers a MACD produces in ranging markets.
How it works
Zero-Lag Core: Each component uses the zero-lag EMA construction (2 × EMA − EMA of EMA), a public-domain technique attributed to John Ehlers' error-correction work. This roughly halves the effective lag of each average, so crossovers occur earlier than on a classic MACD. A faded classic MACD line can be displayed for side-by-side comparison and switched off in the settings.
Divergence Detection: Confirmed pivot highs/lows on the zero-lag MACD line are compared with price highs/lows at the same bars. A regular bullish divergence (price lower low, MACD higher low) or regular bearish divergence (price higher high, MACD lower high) draws a connecting line between the two MACD pivots with a label in the pane. Pivots confirm only after the lookback period elapses, so divergence lines appear with a delay by design and do not repaint.
Combo Signals: In the default mode, a buy/sell marker prints on the price chart only when a zero-lag crossover occurs while a same-direction divergence is still valid (within a user-defined number of bars). Turning combo mode off prints markers on every confirmed crossover instead. Signals respect a cooldown and a daily maximum.
Four-Color Histogram: The histogram distinguishes rising and fading momentum on both sides of the zero line.
Dashboard: A dark, movable panel (styled to stay readable on light-theme charts) summarizes MACD state, histogram direction, active divergence, zero-line position, and the day's signal count.
How to use it
Add the indicator to a lower-timeframe chart (5–15 min for intraday use). Watch for a divergence label in the pane, then wait for the crossover marker that confirms it — the combo mode automates exactly this sequence. The zero-line row on the dashboard helps grade signals: bullish setups above the zero line and bearish setups below it occur in the direction of the broader momentum. All lengths, the divergence window, signal limits, colors, and dashboard placement are adjustable.
Limitations
Divergence lines appear only after pivots confirm (default 5 bars), so they are visible later than the pivot itself; this is the unavoidable cost of non-repainting detection. Reduced lag also means the zero-lag lines are more sensitive than a classic MACD and can produce more crossovers in choppy conditions — the combo mode exists to filter these. This tool describes momentum conditions; it does not predict future price movement, and past behavior of any signal does not guarantee future results. Always combine with your own analysis and risk management. อินดิเคเตอร์
Dynamic Buying and Selling Power (ADTM)
什么是 ADTM？
ADTM（Dynamic Buying and Selling Power Indicator，动态买卖气指标）是一种经典的动量与反转量化指标。它通过对比开盘价的跃升与下挫，精确量化开盘后多空双方的推进力度（即爆发力），并将这种力量对比归一化在 的固定区间内。
与传统单纯依赖收盘价（Close）的振荡指标不同，ADTM 更加关注 开盘价（Open）相对于前一交易日的位置以及当日极值（High/Low）的延伸空间 ，从而能够更敏锐地捕捉到市场资金的日内异动。
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为什么使用它？
在波诡云谲的市场中，单纯的均线或 lagging 指标容易产生钝化。ADTM 的优势在于：
无量纲化区间：其输出被严格限制在 之间，避免了绝对数值对趋势研判的干扰。
日内真实动能：通过计算买方动态能量（DTM）和卖方动态能量（DBM），能够更早地在左侧识别出多空力量的衰竭点。
极佳的反转提示：特别适合配合超买超卖边界进行逆势（反转）波段的卡点操作。
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怎么用？
本指标的使用逻辑非常直观，默认参数为经典配置： N = 23（求和周期），M = 8（信号均线周期）。
左侧买点（超卖区）：
当蓝色 ADTM 曲线跌破 -0.5 时，意味着市场短期内空头宣泄极快，进入超卖状态。这通常是极佳的左侧分批布局或观察止跌反转的买点。
左侧风险（超买区）：
当蓝色 ADTM 曲线突破 +0.5 时，意味着多头短期冲锋过急，进入超买状态。此时应防范多头力竭回撤，注意锁定利润或降低仓位。
中轴信号：
0轴为多空分界线。当 ADTM 在 0 轴上方运行时，多头占优；反之，空头占优。
均线交叉：
蓝色主线（ADTM）与橙色信号线（MA_ADTM）的黄金交叉与死亡交叉，可作为右侧动能确认的辅助信号。
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在哪里用？
本指标采用纯粹的价格几何结构算法，具有极强的普适性：
适用市场：广泛适用于 A 股、美股、加密货币、商品期货以及外汇等主流交易市场。
适用周期：在日线（Daily）及以上大周期中表现尤为稳定，能够有效过滤盘整期的日内噪音；在小周期（如 1H/4H）中，配合趋势背景亦可用于日内波段捕捉。
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原创与致谢声明
指标原创作者： 本指标的核心算法源自经典量化分析领域的经典设计。
脚本重构与发布： 由本人进行 Pine Script v6 的标准化重构、算法优化与开源发布。
风险提示： 任何技术指标都无法百分之百预测市场。建议将 ADTM 融入自身的交易系统中，结合量价结构、关键支撑阻力位以及严谨的资金管理共同使用。
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What is ADTM?
ADTM (Dynamic Buying and Selling Power Indicator) is a classic momentum and reversal quantification tool. It precisely quantifies the offensive strength (i.e., explosive power) of both bulls and bears after the market opens by comparing the upward jumps and downward drops of the opening price, and normalizes this power comparison within a fixed range of .
Unlike traditional oscillators that rely solely on the closing price (Close), ADTM places greater emphasis on the opening price (Open) relative to the previous trading day's position, as well as the extension space of the day's extremes (High/Low) , enabling it to more keenly capture intraday anomalies in market capital flow.
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Why Use It?
In volatile and unpredictable markets, simple moving averages or lagging indicators are prone to desensitization (flattening). The advantages of ADTM are:
Dimensionless interval: Its output is strictly confined within , eliminating the interference of absolute price levels on trend assessment.
Intraday true momentum: By calculating Dynamic Buying Momentum (DTM) and Dynamic Selling Momentum (DBM), it can identify exhaustion points of bullish/bearish power earlier on the left side.
Excellent reversal signals: Particularly well-suited for contrarian (reversal) swing trading by utilizing overbought/oversold boundaries.
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How to Use It?
The usage logic of this indicator is highly intuitive, with default parameters set to the classic configuration: N = 23 (Summation Period), M = 8 (Signal MA Period).
Left-side Buy Signal (Oversold Zone):
When the blue ADTM line drops below -0.5, it indicates that bearish forces have been excessively unleashed in the short term, entering an oversold state. This is typically an excellent opportunity for left-side accumulation or observing for a bullish reversal.
Left-side Risk Signal (Overbought Zone):
When the blue ADTM line rises above +0.5, it indicates that bullish forces have pushed too aggressively in the short term, entering an overbought state. At this point, one should be cautious of bullish exhaustion and pullbacks, and consider locking in profits or reducing positions.
Zero-Line Signal:
The 0.0 axis serves as the bull-bear dividing line. When ADTM is above 0, bulls are in control; when below 0, bears are in control.
Moving Average Crossover:
The golden cross and death cross between the blue main line (ADTM) and the orange signal line (MA_ADTM) can serve as auxiliary signals for right-side momentum confirmation.
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Where to Use It?
This indicator employs a pure geometric price-structure algorithm, offering strong universality:
Applicable Markets: Widely applicable to A-shares, U.S. stocks, cryptocurrencies, commodity futures, forex, and other major trading markets.
Applicable Timeframes: Performs particularly well on Daily and higher timeframes, effectively filtering out intraday noise during consolidation periods. On lower timeframes (e.g., 1H/4H), it can also be used for intraday swing trading when combined with the broader trend context.
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Acknowledgments & Originality Statement
Original Author: The core algorithm of this indicator originates from classic designs in the field of quantitative analysis.
Script Re-engineering & Release: This script has been fully refactored, optimized, and released as open-source by myself.
Risk Disclaimer: No technical indicator can predict the market with 100% accuracy. It is strongly recommended to integrate ADTM into your own trading system, combining it with volume-price structure, key support/resistance levels, and strict risk management practices. อินดิเคเตอร์
อินดิเคเตอร์
ATK/DEF MACD Momentum Context InctorMACD Momentum Context is a momentum analysis indicator designed to help traders visualize MACD behavior, momentum changes, and market context through a structured dashboard.
This indicator focuses on analyzing the relationship between the MACD line, signal line, and histogram to provide a clearer view of momentum direction, momentum strength, and changes in market pressure.
Instead of displaying only traditional MACD values, this tool organizes multiple momentum conditions into an easy-to-read context view, allowing users to better understand how momentum is developing over time.
Features
📊 MACD Momentum Analysis
The indicator analyzes:
• MACD Line behavior
• Sign Line relationship
• Histogram direction
• Histogram expansion and contraction
• Momentum acceleration and slowdown
The histogram is evaluated based on its position and movement to help visualize whether momentum is increasing, weakening, or remaining balanced.
📈 Momentum Direction Context
The dashboard categorizes momentum conditions into different states:
• Bullish acceleration
• Bullish slowdown
• Bearish acceleration
• Bearish slowdown
• Sideways / balanced momentum
These states are based on MACD histogram behavior and are designed to help users quickly understand current momentum conditions.
🔥 Momentum Strength Measurement
The indicator compares current histogram strength with recent historical momentum range.
This helps visualize whether current momentum is:
• Moderate
• Strong
• Extreme
Strength classification is based on relative momentum expansion rather than fixed pric movement.
🔄 MACD Trend Context
The indicator evaluates the relationship between:
• MACD position above or below zero
• Histogram direction
• Sign line interaction
This creates a broader momentum context such as:
• Bullish momentum environment
• Bearish momentum environment
• Momentum transition area
• Neutral conditions
⚡ Momentum Change Tracking
The tool monitors changes in histogram behavior:
• Increasing momentum
• Decreasing momentum
• Stable momentum
This helps users observe whether current momentum is gaining strength or losing energy.
🔍 Divergence Observation
The indicator includes divergence detection based on price movement and MACD behavior.
It highlights situations where:
• Pric reaches a new high while MACD momentum does not confirm
• Pric reaches a new low while MACD momentum does not confirm
Divergence information is provided as a visual reference for studying momentum differences.
📋 Information Dashboard
The built-in table provides a structured overview of recent MACD conditions, including:
• Historical bar reference
• Momentum direction
• Momentum change
• Momentum strength
• MACD behavior
• Momentum edge
• MACD events and context
This allows users to review recent momentum development without manually interpreting multiple MACD components.
⚙️ Customization
Users can adjust:
• MACD fast length
• MACD slow length
• Sign length
• Number of bars displayed
• Table starting position
Different parameter settings can be used to study different market environments and timeframes.
Intended Use
MACD Momentum Context is designed as a market analysis and visualization tool.
It can be used to study:
• Momentum behavior
• Trend strength changes
• MACD structure
• Histogram development
• Potential momentum shifts
This indicator does not provide finan advice, trading recommendations, or guaranteed market outcomes. Users should combine this tool with their own analysis, risk management, and trading approach.
Notes
MACD Momentum Context is based on the traditional MACD concept with additional visualization and contextual analysis layers.
The indicator is intended to improve readability and understanding of momentum conditions by presenting multiple MACD measurements in a structured format. อินดิเคเตอร์
Adaptive ATR Scalper - Instant & Lock VersionWelcome to Adaptive ATR Scalper, a robust, trend-following scalping strategy designed to capture quick momentum bursts while heavily filtering out noise during chop or post-target consolidation.
This strategy combines an ADX-Adaptive ATR trailing stop with a dual-timeframe dynamic (Main Trend + Fast Trigger) and introduces a unique Smart Lock Mechanism to prevent overtrading.
⚡ Key Features
ADX-Adaptive Multiplier
Most ATR-based indicators (like Supertrend) use a fixed multiplier, which fails when market regimes change. This strategy dynamically switches its ATR multiplier based on ADX.
When ADX is rising (strong trending environment), it uses a tighter multiplier (m1) to secure early entries.
When ADX is falling (weakening trend or chop), it automatically widens the multiplier (m2) to prevent getting chopped out.
Dual-Layer Trend Alignment
Main Trend (Thick Line): Acts as the major filter, keeping you on the right side of the macro direction.
Fast Trigger (Thin Line): Captures micro-swings.
An entry only occurs when both trends align in the same direction.
Smart Lock Mechanism (The Anti-Overtrading Shield)
A classic problem with scalping scripts is that after a successful TP (Take Profit) or SL (Stop Loss), the script immediately re-enters the same trend, often leading to losses.
How it works: As soon as a position closes, the strategy enters a Lock State (visualized by a grey background).
How it unlocks: It will not take another trade until either the Main Trend or the Fast Trigger changes direction. This ensures you only trade fresh momentum.
🛠️ Execution & Exit Rules
Entries: Triggered when Main Trend == Fast Trigger and the script is not locked.
Exits: The strategy utilizes a triple-exit matrix for maximum safety:
Dynamic Trend Exit: If the Fast Trigger reverses against the position, it exits immediately to preserve capital.
Fixed Stop Loss (SL): Percentage-based emergency stop.
Fixed Take Profit (TP): Percentage-based target to lock in gains.
📊 Recommended Settings & Assets
Assets: High-liquidity instruments (Crypto majors like BTC/ETH, Forex majors, or Index Futures like Nasdaq/SPY).
Timeframes: Designed primarily for 1m, 3m, 5m, and 15m charts.
Tip: Adjust the SL/TP percentages based on the volatility of your selected asset and timeframe.
Disclaimer: Backtest thoroughly before deploying live. Past performance does not guarantee future results. กลยุทธ์
DMI Badge by ByblloDMI Badge by Bybllo
This indicator plots simple Long/Short badges based purely on the Directional Movement Index (DMI): a Long badge appears on a golden cross (DI+ crossing above DI-) and a Short badge appears on a dead cross (DI- crossing above DI+), with both filtered by a minimum ADX threshold so only crosses backed by sufficient trend strength are marked. It is a lightweight, standalone way to see DMI golden-cross / dead-cross signals directly on the chart without having to watch the DI+ / DI- lines separately.
This script is also intended as a reference companion to "Buy Sell Badge with DMI by Bybllo": that indicator's optional "BSB + DMI" filter uses this exact same DMI golden-cross / dead-cross + ADX logic internally to confirm its EMA-based signals. Running this indicator alongside it lets you see the underlying DMI badges on their own, independent of the EMA signal, so you can verify or tune the DMI-side behavior (length, ADX threshold, badge spacing) before relying on the combined confirmation filter.
Key Features
Long badge on a DMI golden cross (DI+ crossing above DI-), Short badge on a DMI dead cross (DI- crossing above DI+).
ADX threshold filter: a badge is only shown when ADX is at or above your configured minimum, filtering out crosses that lack real directional strength.
Badge spacing (cooldown) input prevents duplicate badges from firing on consecutive bars after a signal.
Real-price calculation via request.security() keeps signals consistent regardless of chart type (Heikin Ashi, Renko, etc.).
alertcondition() calls for both Long and Short badges, ready to use for TradingView alerts.
How to Use
A Long badge below the bar means DI+ has just crossed above DI- with ADX at or above your threshold — a bullish directional shift with trend strength behind it.
A Short badge above the bar means DI- has just crossed above DI+ with ADX at or above your threshold — a bearish directional shift with trend strength behind it.
Raise the ADX threshold to show fewer, higher-conviction badges; lower it to see more crosses, including weaker ones.
Increase "Badge Spacing" if you want more separation between consecutive badges on choppy charts.
If you use "Buy Sell Badge with DMI by Bybllo" with its "BSB + DMI" filter enabled, keep the DMI Length, ADX Threshold, and Badge Spacing here aligned with that indicator's DMI settings so the two stay in sync.
Notes
This indicator only plots DMI-based signals; it does not include any EMA logic, stop-loss/take-profit management, or position tracking. For a combined EMA + DMI signal with risk management, see "Buy Sell Badge with DMI by Bybllo". อินดิเคเตอร์
MTF StochRSI AlignmentMulti-Timeframe StochRSI Alignment
This indicator monitors the Stochastic RSI across three user-defined timeframes simultaneously and alerts you when they all align in the same direction — a classic sign of a strong, multi-timeframe overbought or oversold condition.
How it works
The script calculates Stochastic RSI independently on each of the three selected timeframes (default: 1-minute, 15-minute, and 1-hour) rather than approximating it from the chart timeframe. Each timeframe is then classified as:
- OB — Overbought (K ≥ 80, adjustable)
- OS — Oversold (K ≤ 20, adjustable)
- N — Neutral (in between)
A clean table in the corner of your chart displays all three timeframes and their current status at a glance, along with an overall **Signal** row:
- All three Overbought → SELL (box shades red)
- All three Oversold → BUY (box shades green)
- Mixed → WAIT (neutral shading)
Features
- Fully customizable timeframes — not locked to 1m/15m/1h, set any three you like
- Adjustable RSI length, Stochastic length, K/D smoothing, and OB/OS thresholds
- Configurable table position (all four corners) and text size
- Built-in alert conditions for both aligned Buy and aligned Sell signals, so you don't have to watch the chart
How to use it
This tool is designed to help you spot moments where short-term, medium-term, and longer-term momentum are all stretched in the same direction — often a precursor to a pullback or reversal. It works well as a confluence filter alongside your existing entry/exit strategy, rather than as a standalone signal generator.
Note: Multi-timeframe indicators reference higher-timeframe data that can update intra-bar. Signals on the lowest configured timeframe are most reliable once that candle has closed. This script is for informational purposes only and does not constitute financial advice — always combine it with your own risk management and analysis.
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Ryno V4 - 24HR High AccuracyRyno V4 – 24HR High Accuracy is a pullback-confirmation indicator designed for MNQ futures on the 15-minute chart.
Unlike breakout systems that may alert after price is already extended, Ryno V4 waits for an established trend, a controlled pullback, and confirmed momentum before producing an entry signal.
Core features:
• 24-hour market scanning
• Long and short signals
• 15-minute trend structure
• 60-minute trend confirmation
• EMA 9, 21, and 50 alignment
• VWAP direction filter
• RSI, volume, and volatility confirmation
• Pullback-first entry logic
• Maximum-extension protection
• Structural stops with ATR limits
• Trim and runner targets
• WATCH, ENTER, CANCELLED, STOPPED, and TARGET alerts
• Signals confirmed at candle close to reduce repainting
Alert meanings:
WATCH — A potential setup has formed. Wait for confirmation.
ENTER BUY/SELL — The pullback and momentum requirements have been confirmed.
CANCELLED — The setup became invalid before entry.
STOPPED — The tracked stop level was reached.
RUNNER TARGET — The tracked runner target was reached.
Designed primarily for scalp-to-short-runner trades. This indicator does not place or manage brokerage orders. Users remain responsible for execution, position sizing, risk management, and verifying signals through paper trading before risking capital.
No indicator can guarantee future results. Historical or simulated performance does not ensure live profitability.
อินดิเคเตอร์
อินดิเคเตอร์
