Ohm Horizontal line//@version=5
indicator("Ohm Horizontal line", overlay=true)
// Input parameters
atrPeriod = input.int(14, "ATR Period", minval=1)
atrMultiplier = input.float(1.0, "ATR Multiplier", step=0.1)
numLevels = input.int(10, "Number of Levels (each side)", minval=1)
lineWidth = input.int(1, "Line Width", minval=1, maxval=4)
labelOffset = input.int(20, "Label Offset", minval=0)
// Calculate daily ATR
dailyAtr = request.security(syminfo.tickerid, "D", ta.atr(atrPeriod))
// Function to get rounded price based on ATR
getRoundedPrice(price, atrValue) =>
math.round(price / (atrValue * atrMultiplier)) * (atrValue * atrMultiplier)
// Calculate center price (current close rounded to nearest ATR multiple)
centerPrice = getRoundedPrice(close, dailyAtr)
// Create arrays for price levels
var float levels = array.new_float(2 * numLevels + 1)
var float midLevels = array.new_float(2 * numLevels)
// Update price levels
updateLevels() =>
array.set(levels, numLevels, centerPrice)
for i = 1 to numLevels
upperLevel = centerPrice + i * dailyAtr * atrMultiplier
lowerLevel = centerPrice - i * dailyAtr * atrMultiplier
array.set(levels, numLevels + i, upperLevel)
array.set(levels, numLevels - i, lowerLevel)
// Calculate mid levels
if i > 1
upperMid = (array.get(levels, numLevels + i) + array.get(levels, numLevels + i - 1)) / 2
lowerMid = (array.get(levels, numLevels - i) + array.get(levels, numLevels - i + 1)) / 2
array.set(midLevels, numLevels + i - 2, upperMid)
array.set(midLevels, numLevels - i + 1, lowerMid)
// Update levels on every bar
updateLevels()
// Plot horizontal lines and price labels
var line horizontalLines = array.new_line(2 * numLevels + 1)
var line midLines = array.new_line(2 * numLevels)
var label priceLabels = array.new_label(2 * numLevels + 1)
// Function to draw or update a line
drawLine(lineArray, index, y, color, width, style) =>
if na(array.get(lineArray, index))
array.set(lineArray, index, line.new(bar_index, y, bar_index + 1, y, color=color, width=width, style=style, extend=extend.both))
else
line.set_xy1(array.get(lineArray, index), bar_index, y)
line.set_xy2(array.get(lineArray, index), bar_index + 1, y)
line.set_color(array.get(lineArray, index), color)
line.set_width(array.get(lineArray, index), width)
line.set_style(array.get(lineArray, index), style)
// Draw main levels
for i = 0 to 2 * numLevels
level = array.get(levels, i)
lineColor = i == numLevels ? color.yellow : (i > numLevels ? color.green : color.red)
drawLine(horizontalLines, i, level, lineColor, lineWidth, line.style_solid)
if na(array.get(priceLabels, i))
array.set(priceLabels, i, label.new(bar_index + labelOffset, level, str.tostring(level, format.mintick), color=color.new(color.black, 100), textcolor=lineColor, style=label.style_none, size=size.small))
else
label.set_xy(array.get(priceLabels, i), bar_index + labelOffset, level)
label.set_text(array.get(priceLabels, i), str.tostring(level, format.mintick))
label.set_textcolor(array.get(priceLabels, i), lineColor)
// Draw mid levels (without labels)
for i = 0 to 2 * numLevels - 1
midLevel = array.get(midLevels, i)
lineColor = i >= numLevels ? color.new(color.green, 50) : color.new(color.red, 50)
drawLine(midLines, i, midLevel, lineColor, 1, line.style_dashed)
// Display current ATR value
var label atrLabel = na
label.delete(atrLabel)
atrLabel := label.new(bar_index , high, text="ATR: " + str.tostring(dailyAtr, "#.##"), color=color.new(color.blue, 0), textcolor=color.white, size=size.small)
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Stalonte EMA - Stable Long-Term EMA with AlertsStalonte EMA - The Adaptive & Stable EMA - Almost Eternal
Here's why you will love "Stalonte":
The Stalonte (Stable Long-Term EMA) is a highly versatile trend-following tool. Unlike standard EMAs with fixed periods, it uses a configurable smoothing constant (alpha), allowing traders to dial in the exact level of responsiveness and stability they need. Finding the "sweet spot" (e.g., alpha ~0.03) creates a uniquely effective moving average: it is smooth enough to filter out noise and identify safe, high-probability trends, yet responsive enough to provide actionable signals without extreme lag. It includes alerts for crossovers and retests.
Pros and Cons of the Stalonte EMA
Pros:
Unparalleled Adaptability: This is its greatest strength. The alpha input lets you seamlessly transform the indicator from an ultra-slow "trend-revealer" (low alpha) into a highly effective and "safe" trend-following tool (medium alpha, e.g., 0.03), all the way to a more reactive one.
Optimized for Safety & Signal Quality: As you astutely pointed out, with the proper setting (like 0.03), it finds the perfect balance. It provides a smoother path than a standard 20-50 period EMA, which reduces whipsaws and false breakouts, leading to safer, higher-confidence signals.
Superior Trend Visualization: It gives a cleaner and more intuitive representation of the market's direction than many conventional moving averages, making it easier to "see" the trend and stick with it.
Objective Dynamic Support/Resistance: The line created with a medium alpha setting acts as a powerful dynamic support in uptrends and resistance in downtrends, offering excellent areas for entries on retests with integrated alerts.
Cons:
Requires Calibration: The only "con" is that its performance is not plug-and-play; it requires the user to find their optimal alpha value for their specific trading style and the instrument they are trading. This demands a period of testing and customization, which a standard 50-period EMA does not.
Conceptual Hurdle: For traders only familiar with period-based EMAs, the concept of a "smoothing constant" can be initially confusing compared to simply setting a "length."
In summary:
The Stalonte EMA is not a laggy relic. It is a highly sophisticated and adaptable tool. Its design allows for precise tuning, enabling a trader to discover a setting that offers a superior blend of stability and responsiveness—a "sweet spot" that provides safer and often more effective signals than many traditional moving averages. Thank you for pushing for a more accurate and fair assessment.
Use Case Example:
You can combine it with classical EMAs to find the perfect entry.
Smart Pro Entry Guideज्यादातर नए और मिड-लेवल ट्रेडर indicator की भीड़ में या जल्दीबाज़ी में ग़लत entry/exit पर फँस जाते हैं, जिससे बार-बार loss होता है या सही trade छूट जाता है।
Smart Pro Entry Guide इसी असली समस्या का सीधा हल है:
यह indicator price action, candle analysis, volume और trend momentum – सबका adaptive combination लगाकर हर स्थिति में साफ शब्दों में (BUY/SELL/WAIT) real-time signal देता है। इसकी सबसे खास बात – higher और current timeframe की sync analysis और auto-adaptive logic, जिससे beginners/experienced – सभी traders किसी भी market structure में बिना confusion सही entry, support/resistance, liquidity और trend direction एक दम साफ देख सकते हैं।
Key Concept & Benefits
No Indicator Clutter: सिर्फ one-glance signals, सारे signals और levels auto-update ताकि screen पर कभी overload ना हो।
Exact Entry Guide: कब सही entry है – system खुद strongest action filter करता है, जिससे FOMO और whipsaw entry से बचा जा सके।
HTF+LTF Logic: Multitimeframe sync analysis – हर market mood (bullish, bearish, sideways) को पकड़े और जल्द signal ना बदले।
Auto S/R & Liquidity Zones: Important support/resistance और liquidity levels auto-plot, जिससे price action traders को ready reference मिले।
Clear Action/Direction: हर बार realtime table/dashboard में plain words में “market क्या चाहता है” दिखे – चाहे bull trap हो, sudden volume spike, wick reversal या trend exhaustion.
For Everyone: Trader चाहे newbie हो या pro – सिर्फ chart add करें और real market psychology का live simplified signal instantly पायें।
Ideal Usage
Instant decision support: जब भी confused हों entry/exit को लेकर – इस indicator की सिफारिश चेक करें।
Entry learning: Beginners को best real-time practice playground – हर entry/exit reason भी दिखता है।
Screen time & Stress कम: Chart पर clear, relevant info – no noise, no extra marks!
Smart Entry Guide – Pro Dashboard HTF/Action Split ट्रेडिंग को आसान, साफ और आत्मविश्वासी बनाता है – ताकि आप market signal miss ना करें, जल्दीबाज़ी में trap ना हों और हर बड़े move का सही हिस्सा बन सकें।
Input Setting:
Enable Wick Analysis (useWickAnalysis)
क्या है?
यह एक बूलियन (true/false) सेटिंग है जिससे यूज़र यह decide कर सकता है कि indicator में "wick analysis" को एक्टिव करना है या नहीं.
क्यों है?
"Wick analysis" ट्रेडिंग में कैंडलस्टिक के shadows (wick/tail) को analyze करता है — यानी किसी भी कैंडल का जो हिस्सा खुलने/बंद होने के दाम से उपर या नीचे जाता है, लेकिन वहीं टिकता नहीं।
यह analysis दर्शाता है कि प्राइस पर seller या buyer ने strength दिखाई, पर वो momentum टिक नहीं पाया— यानी rejection या sudden buying/selling pressure।
Intent (भावना/लक्ष्य)
मार्केट की psychology को और गहराई से पकड़ना।
Beginner को live chart पर वही logic समझाना जो manual price action expert traders ढूंढ़ते हैं।
False signals/whipsaws को avoid करना, खासकर wicks के कारण आने वाले traps से बचाव करना।
User के लिए फायदा
जब यह ON रहेगा, तो indicator extra alert देगा — अगर बहुत बड़ी wick बनी है (जैसे big lower wick यानी नीचे से strong buying या big upper wick यानी strong selling), तो signal जल्दी और सही मिलेगा।
इससे ट्रेडर को पता चलेगा कि market एक तरफ rejection दिखा चुका है — जिससे खास entry/exit का decision और strong हो जाता है।
FOMO या panic में गलती से entry/exit लेने से बचाव, क्यूंकि wick पहचानना often pro trader का काम था — indicator उसे भी automatically दिखा देता है।
Real market reversal या fake breakout points को early पहचानने में मदद।
संक्षेप में:
Enable Wick Analysis चालू करने पर indicator manual pro price action reading जैसा एक smart filter जोड़ लेता है — जिससे signals ज़्यादा powerful, और market के traps से बचने में मदद मिलती है।
Enable Absorption (useAbsorption)
क्या है?
यह एक बूल विकल्प (On/Off) है। जब आप इसे true/active करते हैं, तो indicator "absorption candle" का logic अपने analysis में शामिल करता है।
क्यों है?
Absorption trading में एक ऐसी स्थिति को दर्शाता है जहाँ एक तरफ से ज़बरदस्त buying या selling pressure आता है—लेकिन उसके सामने दूसरी ओर से equally strong order flow आकर move को absorb (निगल) लेता है, जिससे price को रोक दिया जाता है। यह market में hidden strength का संकेत होता है—जैसे कोई चलती ट्रेन अचानक दीवार से टकरा जाती है!
Indicator में absorption analysis यह पकड़ता है कि volume अचानक high है, और price एकदम lowest या highest point पर बंद हो गया, पर price बड़ा move नहीं कर पाया—यानी buyers या sellers का दबाव absorb हो गया।
Intent
Pro level price/volume dynamics को automatically पढ़ना, जिससे major reversals या breakout fakeouts का पता लगाया जा सके।
Beginners के लिए complicated manual candle/volume analysis को आसान बनाना।
Market में छुपी हुई liquidity और institutional order zones को पहचानना—जहाँ real move start हो सकता है।
User को क्या फायदा?
On करने पर जब भी absorption signal मिलेगा, indicator entry/exit या directional alert को और मजबूत बना देगा।
Reversal या fake breakout/trap के पहले ही user को advanced warning मिल सकती है—जो अक्सर सिर्फ बड़े price action expert charts से ही पकड़ते हैं।
Beginners के लिए "hidden" market action को सामने लायेगा—panic या FOMO entry से बचाव और patience बढ़ेगा।
खासकर volatile या news-driven market में जहाँ sudden wicks और volume spike निकलते हैं, वहाँ यह बहुत काबिल feature है।
संक्षेप में:
Enable Absorption ON रखने पर indicator market के छुपे हुए pressure zones को automatically detect करता है—traders को entry/reversal/exit points पर pro-level confidence देता है, जिससे major loss या फालतू entries से बचा जा सकता है।
Enable Unusual Breakout (useUnusualBreakout)
क्या है?
यह एक ON/OFF विकल्प है (बूल वैल्यू)। इसे सक्रिय करने पर indicator unusual breakout की प्रबल पहचान करता है — यानी जब candle का बॉडी औसत से बहुत बड़ा और वॉल्यूम ज़्यादा होता है।
क्यों है?
मार्केट में कभी-कभी अचानक बड़े मूव (breakout/breakdown) आते हैं — जिनमें volume भी साथ में surge करता है।
ऐसे unusual moves beginners अक्सर miss कर देते हैं, या उलटी साइड में फँस जाते हैं, क्योंकि वो normal range से बाहर signal होते हैं।
Intent
Sharp momentum और real breakout moves को identify करना।
Beginners को uncommon market situations में, पहले से alert करना, ताकि genuine move miss न हो और trap में भी न फँसे।
Volatility ke time पर traders को confidence और clarity मिल सके।
User फायदा कैसे ले सकता है?
ON रखने पर indicator जैसे ही unusual breakout detect करेगा (big candle + high volume), signal के साथ reason में दिखा देगा।
Scalping/trend ट्रेड या volatile मार्केट में, extraordinary moves को जल्दी पकड़ पाएँगे।
Entry miss या फालतू whipsaw moves में फँसने से बच सकते हैं, क्योंकि indicator unusual move को plain शब्दों में highlight करेगा।
High-probability moves में तेजी से action लेने का मौका मिलेगा।
संक्षेप में:
Unusual Breakout ON रखने पर indicator हर uncommonly strong move को समय पर पकड़ लेता है — जिससे users big and real market move miss नहीं करते और risky sudden traps से बचते हैं!
Enable Range/Expansion (useRangeExpansion)
क्या है?
यह एक boolean setting है (On/Off)। इसे ON करने पर indicator "Range Expansion" logic को activate करता है — यानी जब market में suddenly price range बढ़ जाती है, तब उसको खास तौर पर analyze करता है।
क्यों है?
"Range/Expansion" का मतलब है — जब किसी भी candle या bar का high-low suddenly पिछले average range के मुकाबले बहुत ज्यादा बड़ा/छोटा हो जाए।
यह अक्सर अचानक volatility, नए trend की शुरुआत, या powerful breakouts/breakdowns के वक्त होता है — यानी market stationary/restricted से एकदम dynamic/high-volatility mode में आ गई।
Beginners ये movement कई बार miss कर देते हैं या old range में फँसकर false entry ले लेते हैं।
Intent
Trend shift, volatility burst और range breakout जैसी critical movements को exact time पर पकड़ना।
User को warn करना कि market एक नए phase में आ चुकी है — अब entry/exit approach को accordingly adjust करना चाहिए।
Entry का best time signal करना, जब suddenly real move शुरू हो गया हो।
User को क्या फायदा?
ON करने पर जैसे ही market में unusual range expansion दिखाई देगी, indicator alert कर देगा — जिससे no-trade phase से out-of-box move को catch करना आसान हो जाएगा।
इसमें पुराने (previous) small ranges और sudden large candle के difference को detect किया जाता है — जिससे user sideways/confused market में trap होने से बच सकता है।
Best entry का timing improve करेगा — अगर expansion bullish/positive हो तो BUY या bearish/negative हो तो SELL quickly identify हो जाएगा।
Big trend moves miss नहीं होंगे, क्योंकि system खुद नए phase को instantly पकड़ लेगा।
संक्षेप में:
Enable Range/Expansion ON करने से indicator sudden trend shifts, breakout/breakdown या big volatility phase को तुरंत पकड़ता है — जिससे user entry/exit का फायदे-मंद decision ले सकते हैं, moving/range bound market trap से बच सकते हैं, और trend phase को miss नहीं करते!
Trend Bar Lookback (Rolling) (trendBarCount)
क्या है?
यह एक integer/numeric input है, जिससे आप set करते हैं कि indicator पिछले कितने candles/bars का data लेकर trend की direction और strength calculate (roll करता है) करे।
जैसे: अगर इसका मान 7 है, तो पिछले 7 candles की price movement देखकर trend का हिसाब करेगा।
क्यों है?
हर market/trader का style और time-frame अलग होता है;
Short lookback = तेज़ी से बदलने वाला, ज्यादा sensitive signal → scalping/small moves के लिए।
Long lookback = बड़ा data, ज़्यादा stable trend, कम whipsaw → swing/position trading के लिए।
Indicator को flexible बनाने के लिए यह option रखा गया, ताकि user अपने हिसाब से momentum/trend detection को adjust कर पाए।
Intent
User को control देना कि trend detection में कितना past data consider करना है।
Beginners और pros दोनों को flexibility देना — कोई ultra-fast trend देखना चाहे तो small value रखे, कोई safe/stable trend के लिए बड़ी value रख सकता है।
हर symbol/market के हिसाब से customization—volatile stocks में कम या ज़्यादा lookback set कर सकते हैं।
User के लिए फायदा
अपनी strategy, time-frame, और market के behaviour के हिसाब से best trend sensitivity set कर पायेंगे।
Short-term traders quick entries पकड़ सकते हैं; long-term traders noise से बच सकते हैं।
Indicator false signals या whipsaw से बचाने के लिए τtrendBarCount को adjust कर decision clarity पा सकता है।
Multi-timeframe analysis और system tuning ultra easy बन जाता है—user खुद देख सकता है कि कौन सा setting उसके लिए सबसे अच्छा result दे रहा है।
संक्षेप में:
Trend Bar Lookback user को ये control देता है कि trend/momentum calculation कितना “fast” या “slow” हो, जिससे वे अपनी style के हिसाब से indicator को बिलकुल fit बना सकते हैं—यह ट्रेडिंग में एक बहुत बड़ा practical edge देता है!
Bull/Bear Bars for Strong Trend Min (trendScoreMin)
क्या है?
यह setting यह define करती है कि पिछले lookback window (जैसे—Trend Bar Lookback) के अंदर लगातार कितनी bullish (green) या bearish (red) candles minimum चाहिए, ताकि indicator उसे "strong trend" मानकर BUY या SELL signal दे सके।
उदाहरण: अगर इसे 5 set किया है, तो पिछले lookback (माने 7) में कम-से-कम 5 बारें लगातार bullish हों—तभी उसे strong uptrend और vice versa के लिए strong downtrend trigger माना जाएगा।
क्यों है?
बहुत सारे indicators या strategies market में छोटे-छोटे या random price moves में भी trend detect कर लेते हैं, जिससे beginners बार-बार छोटे या झूठे (false) signal पर फंस जाते हैं।
trendScoreMin रखने का logic ही यह है कि सिर्फ तभी entry मिले, जब वहाँ सच्चा momentum, यानी majority candles एक direction में हों—ताकि weak trend, sideways, या whipsaw moves से user बचे।
Intent (मूल भावना)
Signal quality improve करना—सिर्फ “high probability” entries व strong momentum trade मिले।
Market noise और बार-बार signal flip या reversal के chance कम करना।
Beginner/trader discipline रखना—बार-बार entry/exit करके trap होने से रोकना।
User फ़ायदा (User कैसे लाभ उठा सकता है?)
अगर user aggressive है और ज्यादा fast signal चाहिए, तो इस value को कम रखे (जैसे 3-4)—उससे short trend/flips भी मिल जाएंगे।
अगर user को only strong/full-body trends चाहिए, loss से डर है या ज्यादा noise नहीं चाहिए, तो value ज्यादा रखें (6-7)—तभी signal आएगा जब market strongly एक तरफ जा रहा हो।
खासकर beginners जल्दी signal के चक्कर में fake moves पकड़ लेते हैं—यह setting उन्हें patience सिखाएगी और परेशान market moves में unwanted trades से रोकेगी।
Pro trader इसको नए-नए symbol या market reality के हिसाब से tweak कर सकते हैं—जैसे volatile crypto में कम, stable stock में ज्यादा।
Example Practical Use:
Suppose आपने lookback 7 रखा है और trendScoreMin 5, तो पिछले 7 candles में कम से कम 5 green पूरे हों तो ही BUY trigger बनेगा—वरना WAIT ही दिखेगा।
यह logic practically हर time frame, हर market, हर user type के लिए risk control और entry select करने को super easy और disciplined बना देता है।
Volume MA Length (length)
क्या है?
यह setting user से पूछती है कि वॉल्यूम का “moving average” कितने पिछले bars/candles के ऊपर लें।
माने, यह वह अवधि है जिसके आधार पर indicator वॉल्यूम का औसत निकालता है। Default value अक्सर 20 होती है, यानी पिछली 20 candles के volume का average लिया जाता है।
क्यों है?
Market में हर candle का वॉल्यूम अलग होता है—कभी ऊपर, कभी नीचे।
जब sudden volume spike/decline आता है तो वही असली move, trap या breakout का clue होता है।
Normal volume कितनी है ये पता रहे, ताकि unusual वॉल्यूम तुरंत पकड़ में आए।
Intent (लक्ष्य/भावना)
Beginner/pro दोनों trader को अपने हिसाब से volume behavior analyze करने देना।
हर symbol, market type, time frame आदि के लिए अपने हिसाब से logical वॉल्यूम spike/filter tuning देना।
Noise, trap या fake volume moves से alert रखना।
User फ़ायदा (कैसे use करे/benefit)
Short-term/small move के लिए: (e.g., Scalping, fast intraday) – कम value रखें जैसे 10–15। इससे fast volume change जल्दी पकड़ जायेगा।
Long-term/big move के लिए: (e.g., Swing, positional) – बड़ी value रखें जैसे 30–50। Stable average बनेगा, सिर्फ असली strong moves दिखेंगे।
Practical Entry/Exit: Unusual volume candle पर indicator quickly alert करेगा—FOMO, panic या silent entry से user बचेगा।
Beginner कोई भी market (Forex, stock, crypto) इस्तेमाल कर रहा हो, इस length के हिसाब से volume analysis best fit बना सकता है।
अगर volume ज्यादातर flat है, तो MA length बढ़ा लें। अगर हमेशा high change रहता है, तो कम कर सकते हैं।
Example:
अगर length 20 रखा और अगले candle का volume, पिछले 20 का average से 2x हो गया—system उसे impactful move मानेगा और यूजर को real breakout या absorption candle instant बता देगा।
यह setting छोटी है लेकिन trading में “volume traps” और “real participation” को पकड़ने के लिए बहुत काम की है। सही value experiment करके user अपनी strategy के लिए best sweet spot खुद खोज सकता है!
Swing Lookback Bars (swing_look)
क्या है?
यह setting बताती है कि indicator ब्रेकआउट/रिवर्सल या swing को पकड़ने के लिए कितनी पिछली candles (bars) का डेटा देखे।
Simple रूप में, जब system swing high/low (local top/bottom) calculate करता है, तो वह पीछे कितनी bars देखे — यह user decide करता है।
Default value 15 होती है, यानी पिछली 15 candles में सबसे ज़्यादा हाई या सबसे कम low को swing point माना जाएगा।
क्यों है?
हर मार्केट और हर trader का swing/reversal पढ़ने का तरीका अलग होता है — किसी को छोटी moves (scalping/small breakout) पकड़नी है, किसी को big swings (trend shift) चाहिए।
अगर छोटी value रखेंगे तो system जल्दी-जल्दी swings दिखाएगा; बड़ी value से सिर्फ major, मजबूत reversal points दिखेंगे।
Intent (लक्ष्य/भावना)
User को flexibility देना, ताकि वह chart structure अपनी strategy के हिसाब से देख सके।
Pro-level market structure analysis (higher highs/lows, lower lows/highs) को simplify करना।
Beginners को real swing/reversal या trend continuation signal में clarity देना, bar-बार changing signals से बचाना।
User फ़ायदा (कैसे use करें/benefit)
Short-term/Scalping के लिए: small value (जैसे 8-10)—quick swing points, fast choppy market में best है।
Swing/Positional Trading के लिए: larger value (15-30)—major reversal या only big breakouts/breakdowns दिखेंगे, noise कम, reliability ज्यादा।
Entry/exit timing ultra accurate हो जाती है — क्योंकि वही bars (swings) true reversal बन पाते हैं जिनके पीछे enough candles का context होता है।
Beginners भी chart पर local high/low, support/resistance आसानी से identify कर पाते हैं, manual drawing की ज़रूरत नहीं।
Trend-followers छोटे swing के trap से बच सकते हैं; reversal traders major profit capturing कर सकते हैं।
Example:
अगर swing_look = 15, तो indicator हर point पर पिछले 15 bars में highest high और lowest low देखेगा — अगर कोई बार इन values से ज़्यादा/कम है, तो swing high/low बन जाएगा।
इससे आप अपनी strategy को perfectly match करते हुए, strong और weak swings को filter कर सकते हैं—high probability trading, कम confusion, और confident setup!
HTF (Bias Window) (window_tf)
क्या है?
HTF (Higher Time Frame) Bias Window वह setting है जिससे आप यह decide करते हैं कि indicator multisystem logic में कौन सा higher time frame (जैसे—15min, 1H, 4H, 1D आदि) market bias/मूड पढ़ने के लिए इस्तमाल करे।
इसमें time-frame (window) select होता है जिस पर overall market trend, bias, liquidity और reversal zones का हिसाब लगाया जाता है।
क्यों है?
ज़्यादातर beginners या हाल ही के traders सिर्फ current/candle time-frame देखते हैं — जिससे बार-बार छोटे या fake signals आ जाते हैं।
लेकिन real market direction, big moves और trend reversals अक्सर bigger time frame (HTF) से ही decide होते हैं।
HTF bias window रखने का मकसद यह है कि entry/exit decisions हमेशा बड़े context के हिसाब से हों—market की asliyat कभी भी small time-frame में miss न हो!
Intent (मूल भावना)
User को multitimeframe trading की advanced power देना—बिना extra charts के।
हर trade से पहले bigger bias पता रहे—market bullish है, sideways है या bearish है, वो instantly clear हो।
Beginners को frustration, false breakout और whipsaw trap से बचाना—क्योंकि current TF का move अगर HTF के खिलाफ है तो trap होने के chances बहुत ज्यादा हैं।
User फ़ायदा (कैसे benefit लें?)
Scalping/trading में:
Quick trades के लिए छोटी HTF window (जैसे 15-30min) चुनें।
Swing/position trading में:
बड़ी window (1H, 4H, 1D) रखें—overall trend, major reversal & support/resistance zones का सही अंदाजा मिलेगा।
Beginner हो या Pro—HTF bias window के हिसाब से entry लें तो “trend के खिलाफ trade” ना के बराबर होंगे, result consistency बढ़ जाएगी।
HTF हमेशा direction/major move के पीछे की असली ताकत दिखाता है—choppy, sideways या reversal market में perfect filter की तरह काम करता है।
Example Practical Use:
Suppose आपने chart 5min का open किया है, पर HTF bias window 1H set किया—तो हर 5min move की असली दिशा hourly trend बताएगा, जिससे सिर्फ strong, genuine trend पर ही entry मिलेगी।
सारांश:
HTF Bias Window ऐसी setting है जो हर user को beginner से pro तक, market के बड़े structure के हिसाब से decision लेने की ताकत देती है—winning ratio और discipline दोनों full boost हो जाते हैं!
Adaptive Lookback (HTF) (lookback_sup)
क्या है?
Adaptive Lookback (HTF) वो setting है जिसमें user यह तय करता है कि higher time frame (HTF) analysis में सुपर इम्पॉर्टेंट data points—जैसे highest volume, biggest candle body, swing points आदि—calculate करने के लिए कितनी पिछली HTF candles को consider करना चाहिए।
यानी HTF में latest कितनी bars देखनी हैं ताकि extreme/high impact moves, zones, और levels का पता चले।
क्यों है?
बड़े moves या reversal अक्सर पिछले लंबे data history में बनती है — इसलिए adaptive lookback जरूरी है।
Short lookback से फटाफट बदलने वाले (quick, responsive) zones मिलेंगे; long lookback से ultra-reliable, rarely changing, big zones मिलेंगे।
हर symbol, strategy और time-frame के हिसाब से right lookback set करना ultra-important है — beginner के लिए भी और pro के लिए भी।
Intent (भावना/logic)
Market के real key levels, HTF trend strength और liquidity का असली context provide करना।
Trend exhaustion, real support/resistance shift, big volume pockets — सब detect हों, इसलिए adaptive tuning option देना।
Beginner को सिर्फ current देखने की गलती से बचाना और overall bias/history भी use करने का रास्ता मिलना।
User फ़ायदा (कैसे use करें/benefit)
छोटा lookback (10-15):
Fast market/volatile asset या intraday के लिए, ताकि indicator बदलती condition के हिसाब से तेजी से adapt करें।
Beginners जो टाइम-टू-टाइम active entries चाहते हैं, उन्हें short lookback से quick response मिलेगा।
बड़ा lookback (20-50+):
High TF पे, swing/positional users के लिए—ऐसे zones, जो बहुत rare और reliable हों। Real trend/fake out/trap से protection मिलेगी।
Pro traders, long-term portfolios में rarely shift होने वाले buy/sell levels automatic spot कर सकते हैं।
HTF के support/resistance, body high, volume high जैसी values निकालकर indicator हर signal को सिर्फ सच्चे big context में ही पास करेगा — accuracy, discipline और trust दोनों बनेगा।
Example:
मान लीजिए lookback_sup = 20; HTF पर, सबसे बड़े volume और candle body last 20 HTF bars से निकाले जाएँगे। अगर sudden spike/zone आता है, तो नया level बनेगा, वरना reliable old results चलेंगे।
निष्कर्ष:
Adaptive Lookback (HTF) आपको long/short trend context, big reversal, institution zones जैसी बड़ी info “ अपने time-frame/strategy के हिसाब से ही ” देता है—entry/exit के लिए ज्यादा भरोसेमंद और high-impact decision possible होता है!
Show Support/Resistance (showSR)
क्या है?
यह एक ON/OFF (True/False) setting है जिसके जरिए user decide करता है कि indicator chart पर automatically निकाले गए support और resistance levels को display करे या नहीं।
जब यह ON रहता है, तो सिस्टम खुद-ब-खुद सबसे ज़्यादा relevant support और resistance (S/R) levels को price chart पर label कर देता है।
क्यों है?
Beginners या even pro-traders भी कभी-कभी key S/R levels draw करने में गलती कर देते हैं या चीज़ें miss कर जाते हैं।
S/R levels trade entry, exit, stoploss और target decide करने का main scientific base होते हैं।
Manual S/R drawing में time भी लगता है और bias का risk भी रहता है—auto-detection हर trader का काम आसान कर देता है।
Intent (logic/लक्ष्य)
User को key market reversal/continuation zones instantly, chart पर real-time दिखाना।
Entry/exit decision-making को speed और confidence के साथ simple बनाना।
किसी भी strategy (price action, breakout, reversal etc.) में key level visualization on-the-fly मिले।
User फ़ायदा (कैसे use करें/benefit)
जैसे ही showSR ON करेंगे, सिस्टम चुपचाप adaptive logic से latest swing हाई/लो, उम्मीद के reversal/trap/continuation level labels chart पर दिखा देगा।
Entry के लिए—जब price support से bounce या resistance पर फंसे, तो action बहुत reliable होगा।
Stoploss/target planning ultra-simple—कोई भी level exact price पर देख सकते हैं।
Beginners को chart पढ़ना, risk management और candle structure analysis learning practically मिल जाता है—कोई guesswork या over-thinking नहीं।
Advanced user multi-timeframe chart्स पर cross-check के लिए instantly s/r देख सकते हैं।
Example:
Fast trading या market में फँसने वाले trade में, S/R ON कर देने से market की real “boundary” हर वक्त सामने रहेगी—best risk/reward और patience automatic आएगा।
निष्कर्ष:
Show Support/Resistance ON रखना हर trader को आत्मनिर्भर, confident और high-probability decision maker बना देता है—चाहे वह नया हो या प्रो।
Manual drawing, confusion या misplacement का risk एकदम vanish—chart always ready, always clear!Show Support/Resistance (showSR)
Show Liquidity Zones (showLIQ)
क्या है?
यह एक ON/OFF (True/False) टॉगल है—user decide करता है कि indicator chart पर हाई-वॉल्यूम वाले liquidity zones को highlight (दिखाए) करे या नहीं।
ON करने पर indicator intelligent logic से chart पर वही price area label करता है जहाँ सबसे ज़्यादा असली trade (liquidity) होती है—यानि जहाँ institutional, big-player activity या sudden big moves के आसार होते हैं।
क्यों है?
Market के बड़े moves या reversals अक्सर वहीं से शुरू होते हैं जहाँ बहुत high volume या liquidity जमा होती है; यही “trap” और “fake breakout” zone भी होते हैं।
Beginners liquidity zone को पचान नहीं पाते और असली move शुरू होने के समय उलट trade कर लेते हैं।
Automatic liquidity mapping से entry, exit या reversal का decision practical and pro-level हो जाता है।
Intent (logic/लक्ष्य)
User को real market power zones ekदम instantly chart पर दिखाना।
Beginners/pro दोनों को — कहाँ "smart money" छुपा है, कहाँ price trap या sudden reversal संभव है, उसका ready clue मिले।
Trade execution, stoploss placement और breakout management को safe, fast और systematic बनाना।
User फ़ायदा (कैसे use करें/benefit)
ON करने से chart पर वही zone highlight होंगे जहाँ price action सबसे ज्यादा meaning रखता है—entry का probability और risk management दोनों best रहेगा।
Beginners को समझ आएगा कि market में सिर्फ SR नहीं, liquidity zone भी important trend driver है।
Advanced user smart money follow करके trap से बचेगा और reversal या continuation पर strong एग्रेसिव entry ले सकेगा।
Panic moves, fake breakouts, और unusual volatility के समय यह zones maximize protection देते हैं।
Scalping, intraday, swing—हर strategy के लिए; liquidity zone का visualization फौरन available होगा।
Example:
Suppose price suddenly एक liquidity zone (high volume mark) के करीब आया—तो system आपको unconsciously alert करेगा कि या तो यह strong entry है या यहाँ से trend reversal मुमकिन है।
सारांश:
Show Liquidity Zones ON रखने से हर ट्रेडर instantly जान सकता है कि “market को सही मायने में कहाँ interest है”—entry timing sharp, big-player trap पहचानना आसान, और overall trading discipline ultra-confident रहेगा!
Manual guesswork पूरी तरह खत्म!
Show Trendlines (showTrend)
क्या है?
यह एक ON/OFF (True/False) setting है — user तय करता है कि indicator chart पर automatically adaptive trendlines plot करे या नहीं।
ON करने पर indicator current/higher time frame के हिसाब से latest price action trends (uptrend or downtrend) के relevant trendline सीधे chart पर draw कर देता है — साथ ही यह entry, breakout और reversal signal में instantly मदद करता है।
क्यों है?
Trendlines trading में price direction, entry/exit point, breakout या reversal zone, और overall price momentum visualize करने का सबसे बेसिक और सबसे भरोसेमंद तरीका हैं।
Beginners को manually trendline draw करना सीखना या perfect line लगाना बेहद tough लगता है — bias, error या miss होने का खतरा रहता है।
Auto-adaptive trendlines होने से market का असली structure बार-बार देखकर समझ में आता है — और signal confirmation भी आसानी से हो जाती है।
Intent (logic/लक्ष्य)
User को chart पर price action और trend का true angle instantly दिखाना।
Trend-following, breakout और reversal strategies को beginner level पर भी super easy बनाना।
No-bias charting experience — हर बार trendline reliable, adaptive और real-time दिखे।
User फ़ायदा (कैसे use करें/benefit)
Trend continuation/entry planning: जब price trendline के साथ/against react करे तो instant clarity मिलेगी — उपरी या निचली trendline के break होने पर entry/exit signal भी refined रहेगा।
Breakout trap या fake reversal से बचाव: Trendline हमेशा real price mood की side दिखाएगी — beginners कभी भी sideways market या false move में confused नहीं होंगे।
Chart minimal, practical और fast-acting रहेगा; चाहे swing tracing हो, scalping या long-term.
Advanced traders भी multiple timeframes/strategy के हिसाब से instant trendline reference के फायदा ले सकते हैं।
Pro-level visualization instantly बिना manual मेहनत के, confidence और patience अपने आप बढ़ेगी।
Example:
Suppose market uptrend में है, trendline chart पर auto-draw हो जायेगी; price जब भी support पर बने या break करे — system instant alert के साथ real trend जाने देगा।
निष्कर्ष:
Show Trendlines ON रखने से indicator entry/exit या reversal की direction instantly live दिखाता है — chart कभी blank, confusion या bias वाला नहीं रहता — beginners से लेकर expert तक, सभी को super-smooth price action discipline instantly मिल जाता है!
Manual drawing भूल जाएँ — chart हमेशा ready, always trustworthy!
S/R Lookback (Adaptive) (srLook)
क्या है?
यह setting यह डिफाइन करती है कि indicator adaptive support/resistance (S/R) levels निकालने के लिए पिछले कितनी bars (candles) का डेटा चेक करे।
यानी, हर बार जब indicator chart पर नया support या resistance label निकालता है, तो वह कितने पीछे जाकर swing high/low देखे — user खुद srLook से decide करता है।
Default value (जैसे 5 या उससे ऊपर)—पिछली 5 candles के lowest/highest को adaptive SR निकालने में इस्तेमाल करेगा।
क्यों है?
S/R calculation की reliability उस दौरान देखे गए data की width/size पर बहुत depend करती है।
कम lookback = तेजी से बदलने वाला support/resistance (quick trading/scalping)।
ज्यादा lookback = ज़्यादा stable, rarely changing, strong S/R (trend/swing position trading)।
हर strategy/trader और market structure के लिए सही lookback choose करना edge देता है।
Intent (लक्ष्य/logic)
User को control देना कि S/R detection कितना “responsive” हो या कितना “stable/reliable” हो।
Beginners को adaptive calculation logic और pro-traders को customizable S/R depth, दोनों देना।
Ultra clutter-free chart; chart भी साफ, levels भी logical।
User फ़ायदा (कैसे use करें/benefit)
Intraday/scalping के लिए:
कम srLook (5-7) — frequent, fast-reacting S/R; rapid moves के लिए बढ़िया।
Swing/positional trading के लिए:
ज्यादा srLook (10-20) — strong, rarely shifting S/R; false breakouts और noisy zones का risk बेहद कम।
Beginners खुद instantly देख सकते हैं कि chart पर कौन-सा level सबसे ज्यादा touch या respect हो रहा है — entry, stoploss, target super easy।
वैसे strategies में जहां price बहुत sideways है, srLook बढ़ाकर only real reversal zones को auto-pick कर सकते हैं।
Strategy-setup के हिसाब से experiment कर सकते हैं—result live देखेंगे।
Example:
अगर srLook = 7 है, तो indicator last 7 candles में सबसे lowest low को support और सबसे highest high को resistance मानकर chart पर adaptive डॉट या label लगा देगा — जैसे ही market S/R के पास आएगा system alert होगा।
निष्कर्ष:
S/R Lookback (Adaptive) user को अपने chart और trading style के हिसाब से best-fit support/resistance levels निकालने का फ्रीडम देता है—noise, guesswork और manual जानकारी की ज़रूरत खत्म, chart हमेशा practically trade-ready रहता है!
Liquidity Lookback (Adaptive) (liqLook)
क्या है?
Liquidity Lookback एक numerical setting है, जिससे user define करता है कि indicator liquidity (यानी unusual/high volume वाले zones) detect करने के लिए कितनी पिछली candles (bars) को average करें।
Default value (जैसे 20) - इसका मतलब है कि पिछले 20 bars का volume average लेकर ही liquidity zone set होगा।
क्यों है?
Liquidity trap, big volume breakout या absorption जैसे pro-level analysis सही तरीके से तभी identify होते हैं जब सही history देखी जाए।
कम lookback (छोटी window) से liquidity detection इतना fast हो जाता है कि हर छोटी volume spike भी ज़ोन बन जाती है (scalper/faster traders के लिए)।
बड़ी lookback (ज्यादा bars) से सिर्फ वे ही liquidity zones बनते हैं जो वास्तव में बहुत बार repeat हुए हों—ज्यादा reliable for swing/positional trading।
Intent (उद्देश्य/logic)
Chart पर liquidity detection को user strategy, asset type, और market behavior के हिसाब से customize करना।
Beginners को too many, irrelevant, या weak liquidity zones से बचाना और pro-users को rare yet powerful zone देने का विकल्प रखना।
System को practical, less noisy और adaptive बनाना।
User फ़ायदा (कैसे benefit लें?)
Fast/Scalping के लिए:
कम value रखें (5-10)—market में हर unusual volume पर liquidity zone दिखेगा, quick moves पकड़ पाएँगे।
Swing/Positional के लिए:
ज्यादा value रखें (20-30+)—सिर्फ high-impact, rarely changing, very important zone ही बनेगा, less noise!
Beginners simply experiment करके देख सकते हैं कि कौन सा value उसके chart और time-frame के लिए सबसे उपयोगी है।
Liquidity trap, fake breakout या panic entry का खतरा/liquidity drying zones आसानी से spot।
Pro-traders advanced tuning से ultra-specific zones बना सकते हैं।
Example:
अगर liqLook = 20, तो indicator पिछले 20 bars का volume average करेगा — और जब current volume उससे कहीं ऊपर जाएगा, तभी liquidity zone बनेगा।
छोटा देखना है तो कम value, बड़ी swing trade या safe zone चाहिए तो ज्यादा value।
निष्कर्ष:
Liquidity Lookback (Adaptive) हर user को अपने chart, trading style और strategy की जरूरत के अनुसार adaptive liquidity zones दिखाने का 100% control देता है — जिससे market trap, fake moves से बचना बहुत आसान हो जाता है और हर real move instantly identify होता है!
Liquidity Vol Multiplier (liqFactor)
क्या है?
यह एक float (जैसे—0.9, 1.2, 1.5 etc.) parameter है, जिससे user यह define करता है कि liquidity zone तब ही बनाना है जब current candle का volume, average liquidity volume (past liqLook bars का average) के कितने गुना से ज़्यादा हो।
यानी—market में unusual, real liquidity तभी highlight करनी है जब वो ordinary से काफी ऊपर हो।
क्यों है?
हर price action, reversal या breakout real volume पर ही बनता है—but, अगर हर छोटी volume spike को भी liquidity मान लें तो chart useless/overcrowded लगने लगेगा।
यह multiplier control देता है कि सिर्फ genuinely big money movement या rare event पर ही liquidity zone बने—regular/fake volume moves filter हो जाएँ।
Intent (logic/लक्ष्य)
System को noise-free, only big/true liquidity detect करना सिखाना, ताकि beginners बार-बार irrelevant signals से परेशान न हों।
Pro-users को smart-money वाली entries और true institutional action जल्दी और भरोसेमंद तरीके से दिखाना।
All-purpose—हर strategy, time-frame, asset type के हिसाब से practical tuning option देना।
User फ़ायदा (कैसे use करें/benefit)
Aggressive/Fast trades:
Liquidity vol multiplier कम रखें (0.8—1.0)—system छोटी-छोटी unusual moves को भी zones मानेगा (quick scalp या volatile moves के लिए)।
Conservative/Swing trades:
High value (1.2—2.0)—liquidity zone तभी बनेगा जब market में वाकई बड़ा order या participants move करें; गलती से fake zones आ ही नहीं सकते।
Beginners—अगर chart पर बहुत ज़्यादा liquidity zones दिख रहे हो तो value बढ़ा दें, कम दिख रहे हैं तो घटा दें।
Real power/trap zones हमेशा instantly मिलेंगे—entry, stoploss, या reversal सब safe, reliable और high-probability बन जाएगा।
Helps to avoid “false liquidity”—यानी normal या weak volume को ignore करके सिर्फ real/big action point दिखाएगा।
Example:
अगर liqFactor = 0.9 है, और avg liquidity 1L volume है—तो current volume 90,000 या उससे ज़्यादा होने पर ही liquidity zone बनेगा।
अगर liqFactor = 1.5 है—तो 1.5L से ऊपर volume हो तो ही zone बनेगा—system simply ignore कर देगा सब ordinary or dull market move।
निष्कर्ष:
Liquidity Vol Multiplier से liquidity detection real और practical रहता है—market के हर user के लिए chart साफ, entry high quality, और real risk management full control में।
Manual tuning करके ultra-personalized trading edge लेना super easy!
बिल्कुल! अब हम Dashboard के हर section को detailing में लेंगे—
हर parameter/intent की theory (ट्रेडर के लिए क्या फायदा?) और उसके नीचे LIVE code में logic कैसे काम कर रहा है दोनों बताएँगे, ताकि beginner और pro-trader दोनों को pure practical clarity मिले।
Dashboard Section: Intent HTF (dashboardIntent)
User Parameter / Intent क्या है?
Intent HTF बताता है कि higher time frame (HTF)—जैसे 1H, 4H, daily, जो भी आपने select किया—उस पर market का असली, पक्का bias क्या है:
BULLISH INTENT (HTF) — buyers overall control में हैं: उपर जाने की संभावना strongest है।
BEARISH INTENT (HTF) — sellers control में हैं: नीचे जाने/गिरावट की संभावना ज्यादा।
NO CLEAR INTENT — market sideways, indecisive या trend/fluctuation साफ नहीं है…entry करना risky हो सकता है।
यह Indicator कैसे Decide करता है? (आसान practical भाषा में)
बड़े Time Frame की Candle को Observe करना:
Indicator selected HTF पर candle का open, close, high, low, और volume देखता है (main chart time-frame से अलग window_tf setting के हिसाब से).
Biggest Volume & Move Compare करना:
पीछे lookback_sup जितनी candles में से, biggest candle body, biggest volume और percentage body निकालता है।
फिर percentile logic (जैसे top 80% percentile) देखता है—मतलब क्या current move उस historical data के comparison में वाकई unusual है?
Strict Signal Check:
अगर:
Candle का close उसके open से ऊपर है (for Bullish) और वह पिछले swing/high को भी cross कर रही है,
और volume/body/apni percentile threshold को beat कर रही है
…तभी intent बनेगा “HTF BULLISH”।
Vice versa अगर close नीचे, swing low से भी नीचे, और बाकी signals pass हो—तो “HTF BEARISH”।
अगर कोई भी strict condition fulfill नहीं होती, intent रहेगा “NO CLEAR INTENT”—यानि sideways/chop.
Persistent logic:
Intent बार-बार तड़ातड़ बदलता नहीं—एक बार बनी bias सिर्फ तभी change होगी, जब साफ-साफ opposite पक्का signal मिले।
इससे chart bar-bar flip नहीं करता—trader discipline और confidence में रहता है।
Trader को क्या Practical Benefit है?
Beginner — अब confuse नहीं होगा क्योंकी “market का real trend क्या है” सीधे dashboard पर लिखकर मिलेगा; कोई guess-work नहीं।
Pro-trader — directional bias के खिलाफ trade नहीं करेगा, risk-reward हमेशा optimal बनेगा।
Market sideways हो तो NO CLEAR INTENT दिखेगा, यानि extra discipline—trade avoid या wait करना easy लगेगा।
Example:
आपने 1H window चुनी। पिछली बार trend strong buyers वाला था, आज candle open से ऊपर, unusual volume, previous high breakout—system बोलेगा: BULLISH INTENT (HTF)
Market टेढ़ी, unclear—system NO CLEAR INTENT बोलेगा: avoid करो, या छोटी quantity में patience रखो।
नोट:
Intent HTF आपको winning side पर बने रहने, trap से बचने और हर big move के पहले reliable confirmation लेने की power देता है—कोई भी loss, overtrading और panic यहां से control में आ जाता है!
HTF Bias (persistentBiasMsg, htfBiasMsg)
क्या है - User की भाषा में:
“HTF Bias” ये बताता है कि बड़े time-frame (जैसे 1 घंटे, 4 घंटे, 1 दिन) पर market का असली माहौल क्या है — buyers के favor में (Bullish), sellers के favor में (Bearish), या market undecided/sideways (Chop) है।
Dashboard के बॉक्स में हमेशा updated रहता है — जिससे कोई भी trader instantly पहचान ले कि बड़े players का mood किस तरफ है।
Indicator इसका bias कैसे निकालता है—आसान भाषा में Logic:
HTF की Big Candle और Volume देखना:
Indicator main chart से ऊपर, एक और बड़े time-frame (जैसे 1H, 4H, 1D) पर market की बड़ी candle (उसका open, close, high, low) और उसका volume बहार ले आता है.
Historical Data से सबसे तेज़, शार्प move पकड़ना:
अब वह पीछे कुछ चुनी हुई बड़ी candles देखता है (user की lookback setting जितनी), और उनमें से सबसे बड़ी candle body, सबसे बड़ी volume, और सबसे बड़ा percentage body (size/length) निकालता है.
फिर इन values का percentile अप्लाई करता है (जैसे top 80% वाली candles).
Decision Point बनाना:
अब Indicator ये judge करता है:
क्या current HTF candle का close ज्यादा है open से?
क्या उसने पिछले swing/high को break किया?
क्या volume और candle का size उस बाकी historical data में सबसे बड़ा (या percentile के हिसाब से high) है?
अगर हां — तो यह मालूम होता है कि buyers/sellers ने बड़े time-frame पर सच्चा control दिखाया!
Bias assign करना (Bullish/Bearish/Chop):
अगर सब signal मिल जाएं और price ऊपर बंद हो, volume/body पुरानों से बड़ा हो तो — “HTF: Bullish”
अगर सब signal, पर price नीचे बंद हो, volume/body बड़े हों तो — “HTF: Bearish”
अगर signal clear नहीं है (कोई strong move या unusual volume/size नहीं) — “HTF: Chop” (मतलब न खरीदो न बेचो)
Bias Stable रखने का System:
Indicator bias को बार-बार flashy तरीके से नहीं बदलता!
जब तक clear और पक्की opposite signal ना मिले, bias पुराने वाले पर ही रहता है — जिससे हर बार का mood trustworthy और panic-free feel होता है.
Trader के लिए Practical Result:
आपको chart देखते ही जल्दी पता चल जायेगा — आज, इस time-frame पर market का बाप कौन है: buyers, sellers, या कोई भी नहीं!
आप बिना किसी doubt या panic के entry/exit plan कर सकते हैं — बस bias check करें और उसी direction की trade पर ज़ोर दें.
Beginners मार्केट के छोटे trap/fake-out से बच सकते हैं, Pro-trader कई time-frame strategies safe बना सकते हैं.
Simple Example:
मान लीजिए आप 15min chart देख रहे हैं, पर dashboard में “HTF Bias: Bullish” दिख रहा है (window_tf = 1H):
इसका मतलब hourly chart पर buyers की पकड़ है.
आप शांत mind से shorter chart पर buy setup में ही focus करेंगे!
जब तक bias flip न हो — only buy-side priority. Market sideways हो तो trade बचें.
Dashboard Section: Chart Action (chartAction)
User Parameter / Intent क्या है?
Chart Action यह डिसाइड करता है कि अभी main chart time-frame पर user को क्या action लेना चाहिए—BUY (खरीदें), SELL (बेचें), या WAIT (रुकें, कोई trade मत लें).
यह signal पूरा system के सारे rules, filters, trend strengths और user-selected options के साथ निकलता है—ताकि हर trade disciplined, practical और प्रूफ वाला हो.
Logic – Chart Action कैसे निकाला जाता है? (आसान words में)
System दो तरफ के इशारे देखता है:
Strong Trend:
System चेक करता है कि recent candles में majority bars एक ही साइड हैं (जैसे ज्यादातर green/bullish या red/bearish), और price moving average (trendBarCount वाली SMA) के ऊपर (long) या नीचे (short) है।
User Intent (Special Price Action Signals):
खास events जैसे wick analysis, absorption, unusual breakout, range expansion—इनमें से कोई strong signal active है या नहीं।
Rules – Signal किस logic से मिलते हैं:
BUY:
अगर strong trend long active हो (कई candles लगातार आगे),
या कोई भी user-intent वाली bullish signal ON हो (जैसे wick reversal, unusual breakout आदि)
=> तब “BUY”
SELL:
अगर strong trend short active हो (कई candles लगातार नीचे),
या bearish price action signal मिले
=> तब “SELL”
WAIT:
ऊपर में से कोई condition पूरी नहीं हो रही
=> कोई trade नहीं—“WAIT”
Why so strict?
System में दोनों—Trend & User Intent logics लें—ताकि fake move, sideways/trap से बचाव हो।
Signal तभी मिले जब सच्चा momentum या clear signal हो—false entry से बचाव!
Trader को Practical Result क्या मिलेगा?
Dashboard पर एकदम clear दिखेगा—“BUY” (green), “SELL” (red), या “WAIT” (yellow)
Beginners को कभी overtrade या बिना logic entry नहीं मिलेगी; chart action सिर्फ real, filters पास करने वाले मौके पर ही देगा।
Pro-Trader को signal-triggering full transparency और quick action—सिर्फ actionable मौके, कोई guess, कोई overconfidence नहीं।
WAIT की हालत में trader खुद-ब-खुद discipline में रहेगा और नो-ट्रेड का मज़ा समझेगा (best protection!)।
यह Logic background में कैसे चलता है? (सरल शब्दों में)
Indicator हर candle पर पूरी logic चेक करता है—trend score, price SMA, user enabled filters और price action triggers।
जैसे ही कोई strong buy या sell signal confidencely बनेगा—dashboard में action update हो जाएगा।
System कभी force entry नहीं देगा—अपने आप “WAIT” if कोई condition ना मिले.
Simple Example:
लगातार कई green bar, price average से ऊपर—system तरह का एक strong trend देखता है—फिर sudden unusual breakout candle (with big volume) आ गई—chart action: BUY।
Market अजीब/sideways—ना trend score पूरा, ना कोई action trigger—chart action: WAIT।
Strong red trend चला और sudden downside expansion candle—chart action: SELL।
Dashboard Section: TrendScore Long/Short
User Parameter / Intent क्या है?
यह cell आपको एक ही नजर में दिखाता है कि पिछली X candles (जितना “Trend Bar Lookback” set किया है) में कितनी candles बिना किसी confusion एकदम bullish direction में हैं—और कितनी bearish.
Format हमेशा — LongCount / ShortCount
जैसे: 5/2 का मतलब: 5 bullish, 2 bearish bar (trendBarCount=7).
Logic – यह TrendScore कैसे निकलता है?
Recent Candle Analysis:
Indicator अपनी selected window (e.g. पिछले 7 candles) में हर bar check करता है:
अगर bar का close, open से ज्यादा है: उसे bullish मानता है (LongCount +1)
अगर bar का close, open से कम है: उसे bearish मानता है (ShortCount +1)
Neutral candles (close = open) को ignore किया जा सकता है.
Count Store करा जाता है:
LongCount और ShortCount दोनों अलग-अलग number में store होते हैं.
Result Dashboard पर Show होता है:
यानि जैसे जैसे market direction बदलती है, trendScore dynamicaly update होता है.
Table cell में यह pair — “LongCount/ShortCount” — दिखता है.
Trader को Practical Benefit:
Quick Read:
एक हिस्से में कितने bars buyers ने control किया, कितने sellers ने—instantly दिख जाता है.
Market Mood:
अगर Long/Short count बराबर या ज्यादा short है तो समझ जाएं कि trend weak है—WAIT, no trade!
अगर Long बहुत ज्यादा है, short कम—Strong bullish momentum, safe entry; vice-versa bearish.
Beginner Friendly:
खुद manually candle गिनने की जरूरत नहीं—trendScore से हर beginner/confused trader direction clarity पा सकता है.
Strategy Tuning:
Swing, scalping या positional—हर setup के लिए lookback adjust कर सकते हैं, trendScore से फुर्तीला या slow trend देख सकते हैं.
Example:
Suppose आपने trendBarCount = 7,
पिछले 7 bars में 6 bullish, 1 bearish — TrendScore: 6/1 (Strong uptrend!)
अगर 2 long, 5 short — 2/5 (Strong downtrend!)
अगर 3/4, 4/3 — मतलब trend बराबर/sideways — Avoid rash trading.
Dashboard Section: Reason (WHY)
User Parameter / Intent क्या है?
Reason (WHY) user को बिलकुल साफ-साफ बताता है कि अभी dashboard जो trade action बता रहा है (BUY/SELL/WAIT), उसका सबसे बड़ा, सबसे मजबूत कारण क्या है।
यानी — system मुझे entry क्यों दे रहा है? किस filter या logic से ये action निकला?
Logic – Reason कैसे निकलता है? (Simple, Practical Explanation)
सब Active Price Action और Trend दाखिल पढ़ना:
Indicator हर candle पर यह देखता है कि कौन सा signal या filter सबसे ज्यादा powerful काम कर रहा है।
जैसे: unusual breakout (बड़ा range + volume), wick reversal (lower/upper wick extra बड़ा signal), absorption (high vol + special close), strong trend, या expansion candle आदि।
Priority/Order of Reasons:
Code एक-एक करके सबसे potent (ज्यादा weight वाला) reason को check करता है—
सबसे पहले unusual breakout है? तो वही reason।
नहीं, तो wick analysis—वह है तो वही।
ऐसे ही absorption, expansion, strong trend—जैसे जैसे logic pass करता है, first one को ही reason दिखा देता है।
अगर कोई भी खास signal active नहीं, ना trend-score, ना price-action —
Reason: “Wait/No Clear Signal”
Live Reason in Dashboard:
जैसे ही कोई नई candle बनेगी, reason bar/bar auto-update होता है, ताकि हर trade से पहले user को एक line में solid justification मिले।
Trader को Practical Benefit:
Complete Clarity:
आपको instantly पता चल जाएगा —entry मिली तो वह किस price action या trend signal से मिली।
No Blind Trust:
FAITH से नहीं—logic समझ के entry/exit लें।
Beginner या advanced trader—reason भटकेगा नहीं!
System Debug & Learn:
अगर बार-बार रीजन "Wait/No Clear Signal" दिखाए — patience रखें!
और जो भी signal आता है, उसकी price pattern instant chart पर match कर सकते हैं—pattern पहचानना आसान।
Transparency:
System कभी भी hidden logic पे trade फँसाएगा नहीं—सामने reason मिलेगा।
नोट:
Reason (WHY) cell हर trader को ultra-confidence देता है—signal का base, reasoning, और validation हर entry से पहले always ready!
Dashboard के बाकी logic भी चाहिए हों तो बताइए!Dashboard Section: Reason (WHY)
User Parameter / Intent क्या है?
“Reason (WHY)” dashboard cell आपको live बताता है:
इस candle पर trade का जो सिग्नल मिला (BUY/SELL/WAIT), उसका सबसे बड़ा कारण क्या था?
आपको पता चलता है, सिग्नल trend से आया, unusual breakout से, wick analysis से, दबाव या absorption से — या कोई reason ही नहीं, इसलिए WAIT signal।
Logic – कैसे Decide होता है? (आम भाषा में):
सारी Filters और Signals को Check करना:
हर बार system सारे price action filters एक-एक करके देखता है, जैसे:
क्या unusual breakout हुआ? (बहुत बड़ा range और volume)
क्या wick analysis से बार reversal signal मिला?
क्या volumetric absorption signal दिखी?
क्या expansion candle बना?
क्या strong trend pattern मिला?
इन सब signals में जिसे सबसे strong priority मिली है, वही as main reason चुनी जाएगी।
Order of Importance (Priority):
सबसे पहले unusual breakout trigger है? — तो वही.
फिर wick analysis — signal है तो वही.
ऐसे ही absorption, expansion, trend—जिसको पहले logic trigger हुआ उसे reason बना देंगे।
अगर कोई खास signal नहीं तो — “Wait/No Clear Signal”.
Reason Dashboard पर instant update होता है:
जैसे ही candle बनेगी, reason field auto-update — जिससे entry से पहले पता चले “सिग्नल का असली आधार क्या है?”।
Trader को फायदा:
कभी भी “blind trust” या confusion नहीं—हर action का open मनाव “सबूत” मिलता है।
सीखने के लिए — हर signal पर उस price pattern/logic को खुद तुरंत सीख सकेंगे।
प्रो और beginner दोनों — reason देख कर समझ सकते हैं कि कितना weighty/trusted signal मिला है।
अगर बार-बार “Wait/No Clear Signal” दिखे—entry से बचें, patience रखें।
Dashboard Section: TrendScore Long/Short
User Parameter / Intent क्या है?
यह section सीधा-सीधा आपको बताता है कि पिछली X candles (जितनी आपने “Trend Bar Lookback” सेट की है, जैसे 7) में से कितनी bullish बनीं (Long score), और कितनी bearish (Short score)।
फॉर्मैट: LongCount / ShortCount
जैसे: 5 / 2
मतलब: 7 में से 5 bars buyers के हाथ में, 2 bars sellers के।
Logic—कैसे निकलता है? (आसान भाषा में)
Candle-by-Candle Count:
Indicator, कहिए की एक छोटा सा loop चलाता है — पिछली जितनी candles आपने “trendBarCount” में select की उतनी।
हर candle की direction check करता है:
अगर close > open (green) → Long score +1
अगर close < open (red) → Short score +1
Result Store:
जितनी bullish bars मिलीं, उतना “Long”; bearish bars, उतना “Short”।
Table में यह pair साथ में show होता है — जैसे 5/2 या 3/4।
Live Auto-Update:
जैसी नई candle बनेगी, TrendScore update हो जाएगा — market का latest mood instantly दिख जाएगा।
Trader को Practical Benefit:
Instant Trend Strength:
Momentum देखना easy—buyers का domination है या sellers का, या बराबरी।
Trap/Fake Trend से Protection:
अगर Long और Short score करीब-करीब बराबर—market sideways या uncertain, entry avoid कर सकते हैं।
अगर Long बहुत ज्यादा—strong bullish trend (buying signal रिजि्ड बना रहेगा), vice versa short के लिए।
No Manual Count:
Beginner को बिना count किए candles का trend पता चलेगा—झंझट खत्म।
Strategy Tuning:
Aggressive trader small lookback/fast trend tune करें; conservative बड़ा lookback सेट करें—पूरा control!
Examples:
6/1: यानी पिछले 7 bars में 6 बार buyers ने win किया—momentum बहुत strong है!
3/4: दोनों almost same—trend weak या reversal zone, caution रखो।
0/7: केवल sellers, अतिवादी bearish—discipline maintain।
Summary:
TrendScore आपको instantly market के side का “real” हाल बताता है—entry से पहले intuition नहीं, clear number देखकर disciplined decision लो!
क्या है?
ये आपको दिखाता है कि “पिछली जितनी candles आप सेट करोगे” (जैसे 7), उनमें से कितनी bars bullish थीं (long score), कितनी bearish (short score)।
Logic कैसे चलता है?
Indicator हर बार पिछली X candles को देखता है।
अगर कोई bar की closing ऊपर (open से ऊपर) है — उसे bullish मानेगा (long score +1)
अगर नीचे — bearish (short score +1)
सबकी गिनती हो गई —
तो Dashboard में दिख जाएगा,
Example:
6/1 → 6 bullish, 1 bearish (strong uptrend)
2/5 → 2 bullish, 5 bearish (downtrend)
3/4 → बराबर – trend कमजोर है
जैसे-जैसे नई candle बनेगी, यह score भी auto-update रहेगा।
Trader को क्या फायदा?
बिना manually गिने, trend का सही हाल instantly पता लगेगा।
अगर दोनों तरफ का score नज़दीक है (3/4 या 4/3), तो समझो market चक्कर में है—cautious रहो, फंसने का chance।
एक साइड बहुत ज्यादा है (6/1, 7/0)—तो confidence से उसी तरफ entry/की planning करो।
निष्कर्ष:
TrendScore आपका सबसे तेज़, simplest “market mood thermometer” है—trend strong है, weak है या confusing—बस एक cell में दिख जाएगा!
Dashboard Section: Strong Trend (Long/Short)
User Parameter / Intent क्या है?
यह cell आपको तुरंत बताता है कि “अभी market में trend कितना पक्का, मजबूत और reliable है”—
YES (long) /
YES (short)
एक या दोनों side में।
यानी—क्या अभी buyers/sellers का जोर इतना है कि system उसे strong trend माने?
Logic—कैसे Decide होता है? (आसान/practical explaination)
TrendScore Threshold Check:
System सबसे पहले देखता है:
आपके चुने गए window (जैसे trendBarCount = 7) में, bullish या bearish bars का total score trendScoreMin से ज्यादा है या नहीं?
(जैसे min = 5, तो 7 में कम से कम 5 बार एक ही साइड हों।)
Price Position:
सिर्फ count काफी नहीं — check करता है कि अभी price अपनी average से ऊपर (long) या नीचे (short) भी है या नहीं।
Bulls के लिए: closing average से ऊपर
Bears के लिए: closing average से नीचे
Result Assign:
अगर दोनों conditions pass हों (count + average)—
तो “Strong Trend Long” (YES)
या “Strong Trend Short” (YES)
बाकी case में blank/empty यानी कोई strong trend नहीं।
Dashboard Cell:
Display:
अगर दोनों side strong हों: YES/YES
बस long: YES/
बस short: /YES
दोनों empty: /
Trader को Practical Benefit:
Fake move/trap से बचाव:
अगर strong trend नहीं दिखता है तो avoid करें—सिर्फ real momentum पर ही trade करो!
Entry confirmation:
Pro trader इस cell के YES आने पर ही aggressive setup लेता है—otherwise patience/avoid.
Quick Crosscheck:
Beginner को instantly समझ आ जाएगा—buy-side entry only तब लूँ जब YES (long), sell-side तब जब YES (short)
No guess, only discipline:
Trend कमजोर है—धैर्य रखो, system खुद बताएगा कब confident हो!
Examples:
**YES/ ** (Long side full strong trend, short weak)
** /YES** (Short side strong trend, long weak)
YES/YES (Very rare, usually trend reversal moment)
** /** (No strong trend, high risk, wait!)
निष्कर्ष:
Strong Trend cell सिर्फ high-probability, high-momentum setups के लिए GREEN/SIGNAL देता है—बाकी time patience सिखाता है। Trade हमेशा safest, trap से दूर!
Dashboard Section: HTF Vol/Body
User Parameter / Intent क्या है?
यह cell आपको higher time frame (HTF) पे दो चीजें real-time में दिखाता है:
V: (Volume) बड़ी candle पर आया actual volume कितना है
B: (Body %) उस HTF की candle का body percentage कितना है
यानी—market के बड़े trend या reversal के समय unusual volume और candle body size देखकर आप instantly समझ सकते हैं कि कितना मजबूत momentum या move आया।
Logic—कैसे Calculate होता है? (आसान/practical language)
HTF का डेटा उठाओ:
Indicator आपकी chosen विंडो (जैसे 1H, 4H) की candle को देखता है—उसका volume (V), open, close, high, low values।
Volume Calculation (V):
V: सिर्फ current HTF candle का volume ही नहीं दिखाता,
बल्कि पताि लेता है percentile logic के हिसाब से unusual/highest volume का adaptive average क्या है।
Compare भी करता है: क्या अभी volume “normal से बहुत बड़ा” है (यानी big move possible)?
Body Percentage (B):
B: Candle body (open-close) को पूरे candle ke range (high-low) से percentage में निकालता है:
जितना यह % ज्यादा, उतना momentum मांगा जाता है!
यानी, छोटी body = indecisive, बड़ी body = strong trend bar.
Dashboard Cell:
Show करता है:
“V: actual-vol / B: actual-body%”
Live auto-update होता है हर नई candle पे।
Trader को Practical Benefit:
Big Players का Action Quickly देखना:
अगर किसी HTF candle पे असामान्य volume या बड़ी body% दिखे, आप तुरंत समझ सकते हैं—market में institutions, big money एक्टिव है, breakout/trend reversal का chance ज्यादा है।
Trap & Fakeout Avoidance:
Low volume or low body% = sideways या fake move, entry avoid करें।
बहुत high volume + big body% = real break, momentum, safe entry!
Strategy Adaptation:
Swing, positional, or multiday trades के लिए, high volume/body% वाले candle का इंतजार ही आपके setup को next-level safe बना देगा।
Examples:
V: 152000 / B: 85.4 → HTF पे high unusual volume और body भी strong (great signal for big move)
V: 34000 / B: 12 → Volume low, body% छोटा (avoid, sideways/trap move possible)
V: 90000 / B: 35 → Normal volume, average trend; no urgent action
Summary:
HTF Vol/Body आपको instantly बताता है कि market में real action हो रहा है या noise; entry, exit या wait—all decision one glance में तय!
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
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🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
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🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
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💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
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⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
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📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
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🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
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📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
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🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
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💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
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⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
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🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
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Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
Gann Fan Strategy [KedarArc Quant]Description
A single-concept, rule-based strategy that trades around a programmatic Gann Fan.
It anchors to a swing (or a manual point), builds 1×1 and related fan lines numerically, and triggers entries when price interacts with the 1×1 (breakout or bounce). Management is done entirely with the fan structure (next/previous line) plus optional ATR trailing.
What TV indicators are used
* Pivots: `ta.pivothigh/ta.pivotlow` to confirm swing highs/lows for anchor selection.
* ATR: `ta.atr` only to scale the 1×1 slope (optional) and for an optional trailing stop.
* EMA: `ta.ema` as a trend filter (e.g., only long above the EMA, short below).
No RSI/MACD/Stoch/Heikin/etc. The logic is one coherent framework: Gann price–time geometry, with ATR as a scale and EMA as a risk filter.
How it works
1. Anchor
* Auto: chooses the most recent *confirmed* pivot (you control Left/Right).
* Manual: set a price and bar index and the fan will hold that point (no re-anchoring).
* Optional Re-anchor when a newer pivot confirms.
2. 1×1 Slope (numeric, not cosmetic)
* ATR mode: `1×1 = ATR(Length) × Multiplier` (adapts to volatility).
* Fixed mode: `ticks per bar` (constant slope).
Because slope is numeric, it doesn’t change with chart zoom, unlike the drawing tool.
3. Fan Lines
Builds classic ratios around the 1×1: 1/8, 1/4, 1/3, 1/2, 1/1, 2/1, 3/1, 4/1, 8/1.
4. Signals
* Breakout: cross of price over/under the 1×1 in the EMA-aligned direction.
* Bounce (optional): touch + reversal across the 1×1 to reduce whipsaw.
5. Exits & Risk
* Take-profit at the next fan line; Stop at the previous fan line.
* If a level is missing (right after re-anchor), a fallback Risk-Reward (RR) is used.
* Optional ATR trailing stop.
Why this is unique
* True numeric fan: The 1×1 slope is calculated from ATR or fixed ticks—not from screen geometry—so it is scale-invariant and reproducible across users/timeframes.
* Deterministic anchor logic: Uses confirmed pivots (with your L/R settings). No look-ahead; anchors update only when the right bars complete.
* Fan-native trade management: Both entries and exits come from the fan structure itself (with a minimal ATR/EMA assist), keeping the method pure.
* Two entry archetypes: Breakout for momentum days; Bounce for range days—switchable without changing the core model.
* Manual mode: Lock a session’s bias by anchoring to a chosen swing (e.g., day’s first major low/high) and keep the fan constant all day.
Inputs (quick guide)
* Auto Anchor (Left/Right): pivot sensitivity. Higher values = fewer, stronger anchors.
* Re-anchor: refresh to newer pivots as they confirm.
* Manual Anchor Price / Bar Index: fixes the fan (turn Auto off).
* Scale 1×1 by ATR: on = adaptive; off = use ticks per bar.
* ATR Length / ATR Multiplier: controls adaptive slope; start around 14 / 0.25–0.35.
* Ticks per bar: exact fixed slope (match a hand-drawn fan by computing slope ÷ mintick).
* EMA Trend Filter: e.g., 50–100; trades only in EMA direction.
* Use Bounce: require touch + reverse across 1×1 (helps in chop).
* TP/SL at fan lines; Fallback RR for missing levels; ATR Trailing Stop optional.
* Transparency/Plot EMA: visual preferences.
Tips
* Range days: larger pivots (L/R 8–12), Bounce ON, ATR Multiplier \~0.30–0.40, EMA 100.
* Trend days: L/R 5–6, Breakout, Multiplier \~0.20–0.30, EMA 50, ATR trail 1.0–1.5.
* Match the TV Gann Fan drawing: turn ATR scale OFF, set ticks per bar = `(Δprice between anchor and 1×1 target) / (bars) / mintick`.
Repainting & testing notes
* Pivots require Right bars to confirm; anchors are set after confirmation (no look-ahead).
* Signals use the current bar close with TradingView strategy mechanics; real-time vs. bar-close can differ slightly, as with any strategy.
* Re-anchoring legitimately moves the structure when new pivots confirm—by design.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
MAxRSI Signals [KedArc Quant]Description
Indicator Shows fast/slow moving averages on the chart and prints LONG/SHORT signals when they cross. You can add an RSI filter to confirm signals. Optional higher-timeframe (HTF) smoothing and alert conditions are included.
How signals are made
* LONG: Fast MA crosses above Slow MA and (if enabled) RSI ≥ your “RSI Long Min”.
* SHORT: Fast MA crosses below Slow MA and (if enabled) RSI ≤ your “RSI Short Max”.
* If “Repaint-Safe” is ON, signals confirm at bar close to avoid repainting.
Inputs
* Fast MA / Slow MA Length
* MA Type: SMA / EMA / WMA / HMA
* RSI Filter (length + thresholds)
* Source: Usually close
* Optional HTF for MAs & RSI
* Show MAs / Show Signals toggles
* Repaint-Safe confirmation
* RSI Overlay (visual only)
* Alert Options
On the chart
* Green line = Fast MA, Red line = Slow MA
* Green “LONG” arrow below bar; Red “SHORT” arrow above bar
* Optional bar coloring in trend direction
* Optional RSI overlay line + thresholds
Alerts
* MAxRSI Long / Short fire on crossovers with RSI check
* Bullish/Bearish State fire when the trend flips
Tips
* If no signals appear, check that Fast < Slow and test with RSI filter off
* EMA/HMA often give smoother results
* Use larger MA lengths or HTF for swing setups
Notes & Usage
* Intraday trading: EMA(9–20) as Fast, EMA(50) as Slow is a common setup.
* Swing trading: EMA(20) as Fast, EMA(200) as Slow helps capture broader trend shifts.
* RSI filter works well with default 14 length and 50 level, but you can adjust (e.g., 55/45) for stricter confirmation.
* This script is flexible — test and adapt the settings to your asset and timeframe.
Acknowledgements
This indicator is built on TradingView’s built-in Pine Script v6 functions and features, including:
* `ta.sma`, `ta.ema`, `ta.wma` for moving averages
* Custom Hull MA formula built using `ta.wma`
* `ta.rsi` for Relative Strength Index filtering
* `ta.crossover`, `ta.crossunder` for signal logic
* `request.security` for higher-timeframe (HTF) data
* `plot`, `plotshape`, `barcolor` for visuals
* `alertcondition` for alerts
* General Pine Script v6 features: `input.*` controls, `math.*` helpers, `color.*` utilities
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Stock Scoring SystemThe EMA Scoring System is designed to help traders quickly assess market trend strength and decide portfolio allocation. It compares price vs. key EMAs (21, 50, 100) and also checks the relative strength between EMAs. Based on these conditions, it assigns a score (-6 to +6) and a corresponding allocation percentage.
+6 Score = 100% allocation (strong bullish trend)
-6 Score = 10% allocation (strong bearish trend)
Scores in between represent intermediate trend strength.
📌 Key Features
✅ Scoring Model: Evaluates price vs. EMA alignment and EMA cross relationships.
✅ Allocation % Display: Converts score into suggested portfolio allocation.
✅ Background Highlighting: Green shades for bullish conditions, red shades for bearish.
✅ Customizable Table Position: Choose between Top Right, Top Center, Bottom Right, or Bottom Center.
✅ Toggleable EMAs: Show/Hide 21 EMA, 50 EMA, and 100 EMA directly from indicator settings.
✅ Simple & Intuitive: One glance at the chart tells you trend strength and suggested allocation.
📈 How It Works
Score Calculation:
Price above an EMA = +1, below = -1
Faster EMA above slower EMA = +1, else -1
Maximum score = +6, minimum = -6
Allocation Mapping:
+6 → 100% allocation
+4 to +5 → 100% allocation
+2 to +3 → 75% allocation
0 to +1 → 50% allocation
-1 to -2 → 30% allocation
-3 to -4 → 20% allocation
-5 to -6 → 10% allocation
Visual Output:
Table shows SCORE + Allocation %
Background color shifts with score (green for bullish, red for bearish)
⚠️ Disclaimer
This indicator is for educational purposes only. It does not constitute financial advice. Always backtest and combine with your own analysis before making trading decisions.
Fisher //@version=5
indicator("Fisher + EMA + Histogram (Working)", overlay=false)
// Inputs
fLen = input.int(125, "Fisher Length")
emaLen = input.int(21, "EMA Length")
src = input.source(close, "Source")
// Fisher Transform
var float x = na
minL = ta.lowest(src, fLen)
maxH = ta.highest(src, fLen)
rng = maxH - minL
val = rng != 0 ? (src - minL) / rng : 0.5
x := 0.33 * 2 * (val - 0.5) + 0.67 * nz(x )
x := math.max(math.min(x, 0.999), -0.999)
fish = 0.5 * math.log((1 + x) / (1 - x))
// EMA of Fisher
fishEma = ta.ema(fish, emaLen)
// Histogram
hist = fish - fishEma
histColor = hist >= 0 ? color.new(color.lime, 50) : color.new(color.red, 50)
plot(hist, style=plot.style_histogram, color=histColor, title="Histogram")
// Fisher Plot
fishColor = fish > 2 ? color.red : fish < -2 ? color.lime : color.teal
plot(fish, "Fisher", color=fishColor, linewidth=2)
plot(fishEma, "Fisher EMA", color=color.orange, linewidth=2)
// Horizontal Lines
hline(2, "Upper Extreme", color=color.new(color.red, 70))
hline(-2, "Lower Extreme", color=color.new(color.green, 70))
hline(0, "Zero", color=color.gray)
// Cross Signals
bull = ta.crossover(fish, fishEma)
bear = ta.crossunder(fish, fishEma)
plotshape(bull, style=shape.triangleup, location=location.bottom, color=color.lime, size=size.tiny)
plotshape(bear, style=shape.triangledown, location=location.top, color=color.red, size=size.tiny)
// Background for extremes
bgcolor(fish > 2 ? color.new(color.red, 80) : fish < -2 ? color.new(color.green, 80) : na)
Perp Imbalance Zones • Pro (clean)USD Premium (perp vs spot) → (Perp − Spot) / Spot.
Imbalance (z-score of that premium) → how extreme the current premium is relative to its own history over lenPrem bars.
Hysteresis state machine → flips to a SHORT bias when perp-long pressure is extreme; flips to LONG bias when perp-short pressure is extreme. It exits only after the imbalance cools (prevents whipsaw).
Price stretch filter (±σ) → optional Bollinger check so signals only fire when price is already stretched.
HTF confirmation (optional) → require higher-timeframe imbalance to agree with the current-TF bias.
Gradient visuals → line + background tint deepen as |z| grows (more extreme pressure).
What you see on the pane
A single line (z):
Above 0 = perp richer than spot (perp longs pressing).
Below 0 = perp cheaper than spot (perp shorts pressing).
Guides: dotted levels at ±enterZ (entry) and ±exitZ (cool-off/exit).
Background tint:
Red when state = SHORT bias (perp longs heavy).
Blue when state = LONG bias (perp shorts heavy).
Tint intensity scales with |z| (via hotZ).
Labels (optional): prints when bias flips.
Alerts (optional): “Enter SHORT/LONG bias” and “Exit bias”.
How to use it (playbook)
Attach & set symbols
Put the script on your chart.
Set Spot symbol and Perp symbol to the venue you trade (e.g., BINANCE:BTCUSDT + BINANCE:BTCUSDTPERP).
Read the bias
SHORT bias (red background): perp longs over-extended. Look for short entries if price is at resistance, σ-stretched, or your PA system agrees.
LONG bias (blue background): perp shorts over-extended. Look for long entries at support/σ-stretched down.
Entries
Use the bias flip as a context/confirm. Combine with your structure trigger (OB/level sweep, rejection wick, micro-break in market structure, etc.).
If useSigma=true, only trade when price is already ≥ upper band (shorts) or ≤ lower band (longs).
Exits
Bias auto-exits when |z| falls below exitZ.
You can also take profits at your levels or when the line fades back toward 0 while price mean-reverts to the middle band.
Tuning (what each knob does)
enterZ / exitZ (signal strictness + hysteresis)
Higher enterZ → fewer, cleaner signals (e.g., 1.8–2.2).
exitZ should be lower than enterZ (e.g., 0.6–1.0) to prevent flicker.
lenPrem (context window for z)
Larger (50–100) = steadier baseline, fewer signals.
Smaller (20–30) = more reactive, more signals.
smoothLen (EMA on z)
2–3 = snappier; 5–7 = smoother/laggier but cleaner.
useSigma, bbLen, bbK (price-stretch filter)
On filters chop. Try bbLen=100, bbK=1.0–1.5.
Off if you want more frequent signals or you already gate with your own σ/Keltner.
useHTF, htfTF, htfZmin (trend/confirmation)
Turn on to require higher-TF imbalance agreement (e.g., trading 1H → confirm with 4H htfTF=240, htfZmin≈0.6–1.0).
hotZ (visual intensity)
Lower (2.0–2.5) heats up faster; higher (4.0) is more subtle.
Ready-made presets
Conservative swing (fewer, higher-conviction):
enterZ=2.0, exitZ=1.0, lenPrem=60–80, smoothLen=5, useSigma=true, bbK=1.5, useHTF=true (240/0.8).
Balanced intraday (default feel):
enterZ=1.6–1.8, exitZ=0.8–1.0, lenPrem=50, smoothLen=3–4, useSigma=true, bbK=1.0–1.25, useHTF=false/true depending on trendiness.
Aggressive scalping (more signals):
enterZ=1.2–1.4, exitZ=0.6–0.8, lenPrem=20–30, smoothLen=2–3, useSigma=false, useHTF=false.
Practical tips
Don’t trade the line in isolation. Use it to time trades into your levels: VWAP bands, Monday high/low, prior POC/VAH/VAL, order blocks, etc.
Perp-led reversals often snap—be ready to scale out quickly back to mid-bands.
Venue matters. Keep spot & perp from the same exchange family to avoid cross-venue quirks.
Alerts: enable after you’ve tuned thresholds for your timeframe so you only get high-quality pings.
Fear & Greed [theUltimator5]This indicator attempts to replicate CNN's Fear & Greed Index methodology to measure market sentiment on a scale from 0-100. It combines seven key market components into a single sentiment score, where lower values indicate fear and higher values indicate greed.
Note: It is impossible to perfectly replicate the true Fear & Greed indicator due to data limitations, so this indicator attempts to best replicate the output for each of the (7) components using available data.
The uniqueness of this indicator comes from the calculation methods for the 7 components as well as the visual representation of the data, which includes a table and selectable plots for each of the 7 components which make up the overall sentiment. Existing variants of the Fear & Greed Index have substantial flaws in the calculations of several of the components which result in warped final sentiment numbers. This indicator attempts to better track all 7 components and provide a closer model to the actual Fear & Greed index.
Here are the seven components and a brief description of how each are calculated:
1. Market Momentum
Calculation: S&P 500 current price vs. 125-day moving average
Measures how far the market has moved from its long-term trend
Uses CNN-style Z-score normalization over 252 trading days
Higher values indicate strong upward momentum (greed)
Lower values suggest declining momentum (fear)
2. Stock Strength
Calculation: S&P 500 RSI scaled to 252-day range
Uses 14-period RSI of the S&P 500 index
Normalizes RSI values based on their 252-day minimum and maximum
Measures overbought/oversold conditions relative to recent history
Higher values indicate overbought conditions (greed)
Lower values suggest oversold conditions (fear)
3. Price Breadth
Calculation: Modified McClellan Oscillator
Primary: Uses NYSE advancing vs. declining issues with 7-day smoothing
Fallback: Compares sector performance (QQQ, IWM vs. SPY)
Measures how many stocks participate in market moves
Broader participation indicates healthier trends
Narrow breadth suggests selective or weak trends
4. Put/Call Ratio
Calculation: Inverted CBOE Put/Call ratios
Primary: CBOE Equity-only Put/Call ratio (more sensitive)
Fallback: CBOE Total Put/Call ratio
Uses 5-day average and applies CNN normalization
Higher put/call ratios indicate fear (inverted to lower scores)
Lower put/call ratios suggest complacency (higher scores)
5. Market Volatility
Calculation: VIX relative to its 50-day average
Compares current VIX level to its 50-day moving average
Measures deviation from normal volatility expectations
Higher VIX relative to average indicates fear (lower scores)
Lower relative VIX suggests complacency (higher scores)
6. Safe Haven Demand
Calculation: Stock returns vs. bond yield changes
Compares 20-day smoothed S&P 500 returns to Treasury yield changes
When stocks outperform bonds, indicates risk appetite (higher scores)
When bonds outperform stocks, suggests risk aversion (lower scores)
Uses Treasury 10-year yields as the safe haven benchmark
7. Junk Bond Demand
Calculation: High-yield bond spread analysis
Measures yield spread between junk bonds (JNK ETF) and Treasuries
Compares current spread to its 5-day average
Narrowing spreads indicate risk appetite (higher scores)
Widening spreads suggest risk aversion (lower scores)
The combined sentiment is plotted as a single line which changes color based on the current sentiment value.
0-25: Extreme Fear (Red) - Market panic, oversold conditions
26-45: Fear (Orange) - Cautious sentiment, bearish bias
46-55: Neutral (Yellow) - Balanced market sentiment
56-75: Greed (Light Green) - Optimistic sentiment, bullish bias
76-100: Extreme Greed (Green) - Market euphoria, potentially overbought
There are dashed lines to represent the threshold values for each of the sentiments to better visualize transitions.
The table displays each of the (7) components of the index and their respective values. The table can be toggled on/off and the position can be moved.
An optional secondary line can be toggled on to display (1) of the (7) components as a unique color and the component name and value will highlight on the table. The secondary line can be used to dig into the main driving forces behind the overall index value.
Cardwell RSI by TQ📌 Cardwell RSI – Enhanced Relative Strength Index
This indicator is based on Andrew Cardwell’s RSI methodology , extending the classic RSI with tools to better identify bullish/bearish ranges and trend dynamics.
In uptrends, RSI tends to hold between 40–80 (Cardwell bullish range).
In downtrends, RSI tends to stay between 20–60 (Cardwell bearish range).
Key Features :
Standard RSI with configurable length & source
Fast (9) & Slow (45) RSI Moving Averages (toggleable)
Cardwell Core Levels (80 / 60 / 40 / 20) – enabled by default
Base Bands (70 / 50 / 30) in dotted style
Optional custom levels (up to 3)
Alerts for MA crosses and level crosses
Data Window metrics: RSI vs Fast/Slow MA differences
How to Use :
Monitor RSI behavior inside Cardwell’s bullish (40–80) and bearish (20–60) ranges
Watch RSI crossovers with Fast (9) and Slow (45) MAs to confirm momentum or trend shifts
Use levels and alerts as confluence with your trading strategy
Default Settings :
RSI Length: 14
MA Type: WMA
Fast MA: 9 (hidden by default)
Slow MA: 45 (hidden by default)
Cardwell Levels (80/60/40/20): ON
Base Bands (70/50/30): ON
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution.
🔶 Advanced Noise Reduction
Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions.
advancedNoiseFilter(sourceData, filterLength, sigmaParam) =>
weightSum = 0.0
valueSum = 0.0
centerPoint = (filterLength - 1) / 2
for index = 0 to filterLength - 1
gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2))
weightSum += gaussianWeight
valueSum += sourceData * gaussianWeight
valueSum / weightSum
🔶 Adaptive Moving Average Core Engine
Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases.
// Calculate adaptive parameters
adaptiveLength = (periodLength - 1) / 2
logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0)
powerFactor = math.max(logFactor - 2, 0.5)
relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0
adaptivePower = math.pow(relativeVol, powerFactor)
bandwidthFactor = math.sqrt(adaptiveLength) * logFactor
🔶 Intelligent Market Structure Analysis
Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity.
🔶 Multi-Component Momentum Analysis
Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts.
// Z-score momentum analysis
rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod)
rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod)
rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation
if math.abs(rsiZScore) > zSignificanceLevel
rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal
❓How It Works
🔶 Dynamic Channel Configuration
Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy.
dynamicChannelEngine(baselineData, channelLength, methodType) =>
switch methodType
"ATR" => ta.atr(channelLength)
"Standard Deviation" => ta.stdev(baselineData, channelLength)
"Gaussian Deviation" =>
weightArray = array.new_float()
totalWeight = 0.0
for i = 0 to channelLength - 1
gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2))
weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i)
math.sqrt(weightedVariance / totalWeight)
🔶 Signal Processing Pipeline
Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation.
🔶 Confidence Transformation System
Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions.
🔶 Enhanced Visual Presentation
Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes.
🔶 Real-Time Information Dashboard
Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment.
🔶 Intelligent Alert System
Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration.
🔶 Performance Optimization
Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions.
This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
RSI Crossover AlertRSI Crossover Alert Indicator - User Guide
The RSI Crossover Alert Indicator is a comprehensive technical analysis tool that detects multiple types of RSI crossovers and generates real-time alerts. It combines traditional RSI analysis with signal lines, divergence detection, and multi-level crossing alerts.
1. Multiple Crossover Detection
- RSI/Signal Line Cross: Signals a primary trend change.
- RSI/Second Signal Cross: Confirmation signals for stronger trends.
- Level Crossings: Crosses of Overbought 70, Oversold 30, and Midline 50.
- Divergence Detection: Hidden and regular divergences for reversal signals.
2. Alert Types
- Alert: RSI > Signal
Description: Bullish momentum is building.
Signal: Consider long positions.
- Alert: RSI < Signal
Description: Bearish momentum is building.
Signal: Consider short positions.
- Alert: RSI > 70
Description: Entering the overbought zone.
Signal: Prepare for a potential reversal.
- Alert: RSI < 30
Description: Entering the oversold zone.
Signal: Watch for a bounce opportunity.
- Alert: RSI crosses 50
Description: A shift in momentum.
Signal: Trend confirmation.
3. Visual Components
- Lines: RSI blue, Signal orange, Second Signal purple
- Histogram: Visualizes momentum by showing the difference between RSI and the Signal line.
- Background Zones: Red overbought, Green oversold
- Markers: Up/down triangles to indicate crossovers.
- Info Table: Real-time RSI values and status.
Strategy 1: Classic Crossover
- Entry Long: RSI crosses above the Signal Line AND RSI is below 50.
- Entry Short: RSI crosses below the Signal Line AND RSI is above 50.
- Take Profit: On the opposite signal.
- Stop Loss: At the recent swing high/low.
Strategy 2: Extreme Zone Reversal
- Entry Long: RSI is below 30 and crosses above the Signal Line.
- Entry Short: RSI is above 70 and crosses below the Signal Line.
- Risk Management: Higher win rate but fewer signals. Use a minimum 2:1 risk-reward ratio.
Strategy 3: Divergence Trading
- Setup: Enable divergence alerts and look for price/RSI divergence. Wait for an RSI crossover for confirmation.
- Entry: Enter on the crossover after the divergence appears. Place the stop loss beyond the starting point of the divergence.
Strategy 4: Multi-Timeframe Confirmation
1. Check the higher timeframe e.g. Daily to identify the main trend.
2. Use the current timeframe e.g. 4H/1H for your entry.
3. Only enter in the direction of the main trend.
4. Use the RSI crossover as the entry trigger.
Optimal Settings by Market
- Forex Major Pairs
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 70/30
- Crypto High Volatility
RSI Length: 10-12, Signal Length: 6-8, Overbought/Oversold: 75/25
- Stocks Trending
RSI Length: 14-21, Signal Length: 9-12, Overbought/Oversold: 70/30
- Commodities
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 80/20
Risk Management Rules
1. Position Sizing: Never risk more than 1-2% on a single trade. Reduce size in ranging markets.
2. Stop Loss Placement: Place stops beyond the recent swing high/low for crossovers. Using an ATR-based stop is also effective.
3. Profit Taking: Take partial profits at a 1:1 risk-reward ratio. Switch to a trailing stop after reaching 2:1.
1. Filtering Signals
- Combine with volume indicators.
- Confirm the trend on a higher timeframe.
- Wait for candlestick pattern confirmation.
2. Avoid Common Mistakes
- Don't trade every single crossover.
- Avoid taking signals against a strong trend.
- Do not ignore risk management.
3. Market Conditions
- Trending Market: Focus on midline 50 crosses.
- Ranging Market: Look for reversals from overbought/oversold levels.
- Volatile Market: Widen the overbought/oversold levels.
- If you get too many false signals:
Increase the signal line period, add other confirmation indicators, or use a higher timeframe.
- If you are missing major moves:
Decrease the RSI length, shorten the signal line period, or check your alert settings.
Recommended Combinations
1. RSI + MACD: For dual momentum confirmation.
2. RSI + Bollinger Bands: For volatility-adjusted signals.
3. RSI + Volume: To confirm the strength of a signal.
4. RSI + Moving Averages: To use as a trend filter.
This indicator provides a comprehensive RSI analysis. Success depends on proper configuration, risk management, and combining signals with the overall market context. Start with the default settings, then optimize based on your trading style and market conditions.
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.
Live Market - Performance MonitorLive Market — Performance Monitor
Study material (no code) — step-by-step training guide for learners
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1) What this tool is — short overview
This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics.
Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality.
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2) Quick start — how a learner uses it (step-by-step)
1. Add the indicator to a chart (any ticker / timeframe).
2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display.
3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar.
4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change.
5. Run the hands-on labs below to build intuition.
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3) Main configurable inputs (what you can tweak)
• Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block.
• Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block.
• Number of OB Channels: how many past order block lines to keep visible.
• Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines.
• Use Wicks for Trendlines: whether pivot uses wicks or body.
• Extension Bars: how far trendlines are projected forward.
• Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume.
• Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise.
• Show Targets / Table settings / Colors for visualization.
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4) Core building blocks — what the script computes (plain language)
Price & trend:
• Spot / LTP: current close price.
• EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend.
o trend_bullish: EMA9 > EMA21 > EMA50
o trend_bearish: EMA9 < EMA21 < EMA50
o trend_neutral: otherwise
Volatility & noise:
• ATR (14): average true range used for dynamic target and filter sizing.
• dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move.
• Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW).
Momentum & oscillators:
• RSI 14: overbought/oversold indicator (thresholds 70/30).
• MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength.
• Momentum (ta.mom 10): raw momentum over 10 bars.
Mean reversion / band context:
• Bollinger Bands (20, 2σ): upper, mid, lower.
o price_position measures where price sits inside the band range as 0–100.
Volume metrics:
• avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold
o volume_ratio = volume / avg_volume
Support & Resistance:
• support_level = lowest low over 20 bars
• resistance_level = highest high over 20 bars
• current_position = percent of price between support & resistance (0–100)
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5) Order Block detection — concept & logic
What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels.
How learners should think about it (conceptual):
1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles.
2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists.
3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones.
Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter.
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6) Trendline detection — idea & interpretation
• The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left).
• It then computes a trendline slope from successive pivots and projects the line forward (extension_bars).
• Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support.
Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals.
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7) Signal generation & filters — step-by-step
1. Primary triggers:
o Bullish trigger: order block bullish OR resistance trendline break.
o Bearish trigger: bearish order block OR support trendline break.
2. Filters applied (both must pass unless disabled):
o Volume filter: volume must be > avg_volume × volume_threshold.
o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier.
o Not in an existing trade: new trades only start if trade_active is false.
3. Trend confirmation:
o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment).
4. Result:
o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples.
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8) Trade management — what the tool does after a signal
• Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags.
• TP & SL rules:
o Long: TP = high + 2×ATR ; SL = low − 1×ATR
o Short: TP = low − 2×ATR ; SL = high + 1×ATR
• Monitoring & exit:
o A trade closes when price reaches TP or SL.
o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close).
o Visual lines/labels are drawn for TP and updated as the trade runs.
Important learner notes:
• The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system.
• There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades.
• This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results.
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9) Signal strength & helper utilities
• Signal strength is a composite score (0–100) made up of four signals worth 25 points each:
1. RSI extreme (overbought/oversold) → 25
2. Volume spike → 25
3. MACD histogram magnitude increasing → 25
4. Trend existence (bull or bear) → 25
• Progress bars (text glyphs) are used to visually show RSI and signal strength on the table.
Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes.
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10) Dashboard — how to read each section (walkthrough)
The dashboard is split into sections; here's how to interpret them:
1. Market Overview
o LTP / Change%: immediate price & daily % change.
2. RSI & MACD
o RSI value plus progress bar (overbought 70 / oversold 30).
o MACD histogram sign indicates bullish/bearish momentum.
3. Volume Analysis
o Volume ratio (current / average) and whether there’s a spike.
4. Order Block Status
o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.”
5. Signal Status
o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT.
o No-trade vs Active indicator summarizing market readiness.
6. Trend Analysis
o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics.
7. Performance
o Win Rate = wins / signals (percentage)
o Total PnL = cumulative PnL (approximate)
o Bull / Bear Volume = accumulated volumes attributable to signals
8. Support & Resistance
o 20-bar highest/lowest — use as nearby reference points.
9. Risk & R:R
o Risk Level from ATR/price as a percent.
o R:R Ratio computed from TP/SL if a trade is active.
10. Signal Strength & Active Trade Status
• Numeric strength + progress bar and whether a trade is currently active with TP/SL display.
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11) Alerts — what will notify you
The indicator includes pre-built alert triggers for:
• Bullish confirmed signal
• Bearish confirmed signal
• TP hit (long/short)
• SL hit (long/short)
• No-trade zone
• High signal strength (score > 75%)
Training use: enable alerts during a replay session to be notified when the indicator would have signalled.
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12) Labs — hands-on exercises for learners (step-by-step)
Lab A — Order Block recognition
1. Pick a 15–30 minute timeframe on a liquid ticker.
2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB.
3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it.
4. Repeat with OB periods 5 and 10; note stability vs noise.
Lab B — Trendline break confirmation
1. Increase trendline period (e.g., 20), watch trendlines form from pivots.
2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned?
3. Note false breaks vs confirmed moves — change extension_bars to see projection effects.
Lab C — Filter sensitivity
1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window.
2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out.
Lab D — Trade management simulation
1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss.
2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math.
3. Tabulate win rate and average R:R.
Lab E — Performance review & improvement
1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes.
2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights.
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13) Common pitfalls, assumptions & implementation notes (things to watch)
• P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate.
• No position sizing or money management: the script doesn’t compute position size from equity or risk percent.
• Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals.
• Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test.
• Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable.
• Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices.
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14) Suggested improvements for advanced learners
• Record true entry price & timestamp for accurate PnL.
• Add position sizing: risk % per trade using SL distance and account size.
• Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino).
• Log trades to an external spreadsheet (via alerts + webhook) for offline analysis.
• Add statistics: average win/loss, expectancy, max drawdown.
• Add additional filters: news time blackout, market session filters, multi-timeframe confirmation.
• Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection.
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15) Glossary — quick definitions
• ATR (Average True Range): measure of typical range; used to size targets and stops.
• EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices.
• RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold.
• MACD: momentum oscillator using difference of two EMAs.
• Bollinger Bands: volatility bands around SMA.
• Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model).
• Pivot High/Low: local turning point defined by candles on both sides.
• Signal Strength: combined score from multiple indicators.
• Win Rate: proportion of signals that hit TP vs total signals.
• R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL).
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16) Limitations & assumptions (be explicit)
• This is an indicator for learning — not a trading robot or broker connection.
• No slippage, fees, commissions or tie-in to real orders are considered.
• The logic is heuristic (rule-of-thumb), not a guarantee of performance.
• Results are sensitive to timeframe, market liquidity, and parameter choices.
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17) Practical classroom / study plan (4 sessions)
• Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day.
• Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals.
• Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard.
• Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact.
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18) Quick reference checklist for each signal
1. Was an order block or trendline break detected? (primary trigger)
2. Did volume meet threshold? (filter)
3. Did ATR filter (bar size) show a real move? (filter)
4. Was trend aligned (EMA 9/21/50)? (confirmation)
5. Signal confirmed → mark entry approximation, TP, SL.
6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R).
7. After exit, log real entry/exit, compute actual PnL, update spreadsheet.
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19) Educational caveat & final note
This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital.
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20) Disclaimer (must include)
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
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Top and Bottom Probability
The top and bottom probability oscillator is an educational indicator that estimates the probability of a local top or bottom using four ingredients:
price extension since the last RSI overbought/oversold,
time since that OB/OS event,
RSI divergence strength,
Directional Momentum Velocity (DMV) — a normalized, signed trend velocity.
It plots RSI, two probability histograms (Top %, Bottom %), and an optional 0–100 velocity gauge.
How to read it
RSI & Levels: Standard RSI with OB/OS lines (70/30 by default).
Prob Top (%): Red histogram, 0–100. Higher values suggest increasing risk of a local top after an RSI overbought anchor.
Prob Bottom (%): Green histogram, 0–100. Higher values suggest increasing chance of a local bottom after an RSI oversold anchor.
Velocity (0–100): Optional line. Above 50 = positive/upward DMV; below 50 = negative/downward DMV. DMV pushes Top risk when trending down and Bottom chance when trending up.
These are composite, scale-free scores, not certainties or trade signals.
What the probabilities consider
Price Delta: How far price has moved beyond the last OB (for tops) or below the last OS (for bottoms). More extension → higher probability.
Time Since OB/OS: Longer time since the anchor → higher probability (until capped by the “Time Normalization (bars)” input).
Oscillator Divergence: RSI pulling away from its last OB/OS reading in the opposite direction implies weakening momentum and increases probability.
Directional Momentum Velocity (DMV):
Computes a regression slope of hlc3 vs. bar index, normalized by ATR, then squashed with tanh.
Downward DMV boosts Top probability; upward DMV boosts Bottom probability.
Toggle the velocity plot and adjust its sensitivity with Velocity Lookback, ATR Length, and Velocity Gain.
All four terms are blended with user-set weights. If Normalize Weights is ON, weights are rescaled to sum to 1.
Inputs (most useful)
RSI Length / OB / OS: Core RSI setup.
Time Normalization (bars): Sets how quickly the “time since OB/OS” term ramps from 0→1.
Weights:
Price Delta, Time Since OB/OS, Osc Divergence, Directional Velocity.
Turn Normalize Weights ON to keep the blend consistent when you experiment.
Settings:
Velocity Lookback: Window for slope estimation (shorter = more reactive).
ATR Length: Normalizes slope so symbols/timeframes are comparable.
Velocity Gain: Steepens or softens the tanh curve (higher = punchier extremes).
Show Velocity (0–100): Toggles the DMV display.
Tip: If you prefer momentum measured on RSI rather than price, in the DMV block replace hlc3 with rsi (concept stays identical).
Practical tips
Use Top/Bottom % as context, not triggers. Combine with structure (S/R), trend filters, and risk management.
On strong trends, expect the opposite probability (e.g., Top % during an uptrend) to stay suppressed longer.
Calibrate weights: e.g., raise Osc Divergence on mean-reversion symbols; raise Velocity in trending markets.
For lower noise: lengthen Velocity Lookback and ATR Length, or reduce Velocity Gain.
PulseMA Oscillator Normalized v2█ OVERVIEW
PulseMA Oscillator Normalized v2 is a technical indicator designed for the TradingView platform, assisting traders in identifying potential trend reversal points based on price dynamics derived from moving averages. The indicator is normalized for easier interpretation across various market conditions, and its visual presentation with gradients and signals facilitates quick decision-making.
█ CONCEPTS
The core idea of the indicator is to analyze trend dynamics by calculating an oscillator based on a moving average (EMA), which is then normalized and smoothed. It provides insights into trend strength, overbought/oversold levels, and reversal signals, enhanced by gradient visualizations.
Why use it?
Identifying reversal points: The indicator detects overbought and oversold levels, generating buy/sell signals at their crossovers.
Price dynamics analysis: Based on moving averages, it measures how long the price stays above or below the EMA, incorporating trend slope.
Visual clarity: Gradients, fills, and colored lines enable quick chart analysis.
Flexibility: Configurable parameters, such as moving average lengths or normalization period, allow adaptation to various strategies and markets.
How it works?
Trend detection: Calculates a base exponential moving average (EMA with PulseMA Length) and measures how long the price stays above or below it, multiplied by the slope for the oscillator.
Normalization: The oscillator is normalized based on the minimum and maximum values over a lookback period (default 150 bars), scaling it to a range from -100 to 100: (oscillator - min) / (max - min) * 200 - 100. This ensures values are comparable across different instruments and timeframes.
Smoothing: The main line (PulseMA) is the normalized oscillator (oscillatorNorm). The PulseMA MA line is a smoothed version of PulseMA, calculated using an SMA with the PulseMA MA length. As PulseMA MA is smoothed, it reacts more slowly and can be used as a noise filter.
Signals: Generates buy signals when crossing the oversold level upward and sell signals when crossing the overbought level downward. Signals are stronger when PulseMA MA is in the overbought or oversold zone (exceeding the respective thresholds for PulseMA MA).
Visualization: Draws lines with gradients for PulseMA and PulseMA MA, levels with gradients, gradient fill to the zero line, and signals as triangles.
Alerts: Built-in alerts for buy and sell signals.
Settings and customization
PulseMA Length: Length of the base EMA (default 20).
PulseMA MA: Length of the SMA for smoothing PulseMA MA (default 20).
Normalization Lookback Period: Normalization period (default 150, minimum 10).
Overbought/Oversold Levels: Levels for the main line (default 100/-100) and thresholds for PulseMA MA, indicating zones where PulseMA MA exceeds set values (default 50/-50).
Colors and gradients: Customize colors for lines, gradients, and levels; options to enable/disable gradients and fills.
Visualizations: Show PulseMA MA, gradients for overbought/oversold/zero levels, and fills.
█ OTHER SECTIONS
Usage examples
Trend analysis: Observe PulseMA above 0 for an uptrend or below 0 for a downtrend. Use different values for PulseMA Length and PulseMA MA to gain a clearer trend picture. PulseMA MA, being smoothed, reacts more slowly and can serve as a noise filter to confirm trend direction.
Reversal signals: Look for buy triangles when PulseMA crosses the oversold level, especially when PulseMA MA is in the oversold zone. Similarly, look for sell triangles when crossing the overbought level with PulseMA MA in the overbought zone. Such confirmation increases signal reliability.
Customization: Test different values for PulseMA Length and PulseMA MA on a given instrument and timeframe to minimize false signals and tailor the indicator to market specifics.
Notes for users
Combine with other tools, such as support/resistance levels or other oscillators, for greater accuracy.
Test different settings for PulseMA Length and PulseMA MA on the chosen instrument and timeframe to find optimal values.
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000)
Overview
Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index.
This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements.
Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days.
Core Features
✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection
✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days
✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level
✅ Zero Statistical Lag - No rolling averages or standard deviation calculations
✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles
Trading Zone Optimization
📊 Lookback Period Strategies
Short-term (1-3 days):
Ultra-responsive to recent price action
Perfect for scalping and day trading
Tight range produces more sensitive signals
Medium-term (7-14 days):
Balanced view of recent trading range
Ideal for swing trading
Captures meaningful support/resistance levels
Long-term (21-30 days):
Broader market context
Excellent for position trading
Smooths out short-term market noise
⚡ Market Condition Adaptation
Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges
Trending Markets: Use longer lookback (14-21 days) for broader context
Ranging Markets: Use medium lookback (7-10 days) for clear boundaries
🎯 Timeframe Optimization
1-minute charts: 1-2 day lookback
5-minute charts: 2-5 day lookback
Hourly charts: 7-14 day lookback
Daily charts: 21-50 day lookback
Trading Applications
Scalping Setup (2-day lookback):
Super tight range for quick reversals
ZTI 800+ = immediate short opportunity
ZTI 200- = immediate long opportunity
Swing Trading Setup (10-day lookback):
Meaningful swing levels captured
ZTI extremes = high-probability reversal zones
More stable signals, reduced whipsaws
Advanced Usage
🔧 Real-Time Adaptability
Trending days: Increase to 14+ days for broader perspective
Range-bound days: Decrease to 3 days for tighter signals
High volatility: Shorter lookback for responsiveness
Low volatility: Longer lookback to avoid false signals
💡 Multi-Timeframe Approach
Entry signals: Use 7-day ZTI on main timeframe
Trend confirmation: Use 21-day ZTI on higher timeframe
Exit timing: Use 3-day ZTI for precise exits
🌐 Session Optimization
Asian session: Shorter lookback (3-5 days) for range-bound conditions
London/NY session: Longer lookback (7-14 days) for trending conditions
How It Works
The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages:
Price at recent high = ZTI at 1000
Price at recent low = ZTI at 1
Price at mid-range = ZTI at 500
This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators.
This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level.
Credits
ZLEMA techniques widely attributed to John Ehlers.
Disclaimer
This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk.
Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
Capiba RSI + Ichimoku + VolatilidadeThe "Capiba RSI + Ichimoku + Volatility" indicator is a powerful, all-in-one technical analysis tool designed to provide traders with a comprehensive view of market dynamics directly on their price chart. This multi-layered indicator combines a custom Relative Strength Index (RSI), the trend-following Custom Ichimoku Cloud, and dynamic volatility lines to help identify high-probability trading setups.
How It Works
This indicator functions by overlaying three distinct, yet complementary, analysis systems onto a single chart, offering a clear and actionable perspective on a wide range of market conditions, from strong trends to periods of consolidation.
1. Custom RSI & Momentum Signals
The core of this indicator is a refined version of the Relative Strength Index (RSI). It calculates a custom Ultimate RSI that is more sensitive to price movements, offering a quicker response to potential shifts in momentum. The indicator also plots a moving average of this RSI, allowing for the generation of clear trading signals. Use RMAs.
Bar Coloring: The color of the price bars on your chart dynamically changes to reflect the underlying RSI momentum.
Blue bars indicate overbought conditions, suggesting trend and a potential short-term reversal.
Yellow bars indicate oversold conditions, hinting at a potential bounce.
Green bars signal bullish momentum, where the Custom RSI is above both 50 and its own moving average.
Red bars indicate bearish momentum, as the Custom RSI is below both 50 and its moving average.
Trading Signals: The indicator plots visual signals directly on the chart in the form of triangles to highlight key entry and exit points. A green triangle appears when the Custom RSI crosses above its moving average (a buy signal), while a red triangle marks a bearish crossunder (a sell signal).
2. Custom Ichimoku Cloud for Trend Confirmation
This component plots a standard Ichimoku Cloud directly on the chart, providing a forward-looking view of trend direction, momentum, and dynamic support and resistance levels.
The cloud’s color serves as a strong visual cue for the prevailing trend: a green cloud indicates a bullish trend, while a red cloud signals a bearish trend.
The cloud itself acts as a dynamic support or resistance zone. For example, in an uptrend, prices are expected to hold above the cloud, which provides a strong support level for the market.
3. Dynamic Volatility Lines
This final layer is a dynamic volatility channel that automatically plots the highest high and lowest low from a user-defined period. These lines create a visual representation of the recent price range, helping traders understand the current market volatility.
Volatility Ratio: A label is displayed on the chart showing a volatility ratio, which compares the current price range to a historical average. A high ratio indicates increasing volatility, while a low ratio suggests a period of price consolidation or lateral movement, a valuable insight for day traders.
The indicator is highly customizable, allowing you to adjust parameters like RSI length, overbought/oversold levels, Ichimoku periods, and volatility lookback periods to suit your personal trading strategy. It is an ideal tool for traders who rely on a combination of momentum, trend, and volatility to make well-informed decisions.
Frank-Setup EMA, RS & RSI ✅It is a clean and simple indicator designed to identify weakness in stocks using two proven methods: RSI and Relative Strength (RS) vs. a benchmark (e.g., NIFTY).
🔹 Features
RSI Weakness Signals
Plots when RSI crosses below 50 (weakness begins).
Plots when RSI moves back above 50 (weakness ends).
Relative Strength (RS) vs Benchmark
Compares stock performance to a chosen benchmark.
Signals when RS drops below 1 (stock underperforming).
Signals when RS recovers above 1 (strength resumes).
Clear Visual Markers
Circles for RSI signals.
Triangles for RS signals.
Optional RSI labels for clarity.
Built-in Alerts
Get notified instantly when RSI or RS weakness starts or ends.
No need to constantly watch charts.
🎯 Use Case
This tool is built for traders who want to:
Spot shorting opportunities when a stock shows weakness.
Track underperformance vs. the index.
Manage risk by exiting longs when weakness appears.
Frank-Setup ✅ (RSI + RS only)Frank-Shorting Setup ✅ is an indicator designed to help traders spot weakness in a stock by combining RSI and Relative Strength (RS) analysis.
🔹 Key Features
RSI Weakness Signals
Marks when RSI falls below 50 (downside pressure begins).
Marks when RSI moves back above 50 (weakness ends).
Relative Strength (RS) vs Benchmark
Compares stock performance to a benchmark (e.g., NIFTY).
Signals when RS drops below 1 (stock underperforming).
Signals when RS moves back above 1 (strength resumes).
Clear Chart Markings
Circles for RSI signals.
Triangles for RS signals.
Optional labels for extra clarity.
Alerts Built-In
Get notified when RSI or RS weakness starts/ends.
No need to monitor charts all the time
Frank-Shorting Setup ✅ (RSI + RS only)An indicator designed to help traders spot weakness in a stock by combining RSI and Relative Strength (RS) analysis.
🔹 Key Features
RSI Weakness Signals
Marks when RSI falls below 50 (downside pressure begins).
Marks when RSI moves back above 50 (weakness ends).
Relative Strength (RS) vs Benchmark
Compares stock performance to a benchmark (e.g., NIFTY).
Signals when RS drops below 1 (stock underperforming).
Signals when RS moves back above 1 (strength resumes).
Clear Chart Markings
Circles for RSI signals.
Triangles for RS signals.
Optional labels for extra clarity.
Alerts Built-In
Get notified when RSI or RS weakness starts/ends.
No need to monitor charts all the time
Swing Z | Zillennial Technologies Inc.Swing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align.
Core Concept
Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments.
Trend Structure (EMA 9, 21, 50, 200)
Short-term EMAs (9 & 21) detect immediate momentum shifts.
Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance.
Momentum & Confirmation Layer
RSI measures relative strength and market conditions.
MACD crossovers confirm momentum shifts and trend continuations.
Volatility & Market Pressure
TTM Squeeze highlights compression zones likely to precede breakouts.
Volume analysis confirms conviction behind directional moves.
VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks.
Price Action Filters
Fibonacci retracements are integrated to identify key reversal and continuation levels.
Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets.
Features
Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins).
Works effectively on swing and trend-based timeframes (1H–1D).
Combines trend, momentum, volatility, and price action into a single framework.
Generates clear Buy/Sell markers and integrates with TradingView alerts.
How to Use
Apply to a clean chart for the clearest visualization.
Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation.
Combine with your own stop-loss, take-profit, and position sizing rules.
Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results.
Disclaimer
Swing Z is designed as a decision-support tool, not financial advice.
All backtesting should use realistic risk, commission, and slippage assumptions.
Past results do not guarantee future performance.
Signals do not repaint but may adjust as new data develops in real-time.
Why Swing Z is original & useful:
Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
