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Statistics
Piotroski F-Score المنهج العلمي: ما هو نموذج بيوتروسكي F-Score؟
نموذج F-Score هو نظام تصنيف رقمي تم تطويره في عام 2000 من قبل جوزيف بيوتروسكي (Joseph Piotroski)، أستاذ المحاسبة في جامعة ستانفورد. الهدف من هذا النموذج هو قياس القوة المالية للشركات ذات القيمة (Value Stocks)، وتحديداً تلك التي لديها نسبة "القيمة الدفترية إلى القيمة السوقية" (Book-to-Market) مرتفعة.
الفكرة الأساسية هي فرز الشركات "الرخيصة" ظاهرياً، والتمييز بين تلك التي تتحسن أساسياتها المالية (الرابحون) وتلك التي تتدهور (الخاسرون).
يعتمد النموذج على تسعة معايير بسيطة، مقسمة إلى ثلاث فئات رئيسية. تحصل الشركة على نقطة واحدة عن كل معيار تحققه، ولا تحصل على شيء إذا لم تحققه. النتيجة النهائية هي مجموع هذه النقاط، وتتراوح من 0 (الأسوأ) إلى 9 (الأفضل).
المعايير التسعة (كيف يتم حساب النقاط):
أ) الربحية (Profitability) - (4 نقاط محتملة)
صافي الدخل إيجابي (ROA > 0): هل حققت الشركة ربحاً في العام الأخير؟ (نقطة واحدة)
التدفق النقدي التشغيلي إيجابي: هل ولّدت الشركة نقداً من عملياتها الأساسية؟ (نقطة واحدة)
جودة الأرباح (التدفق النقدي > صافي الدخل): هل التدفق النقدي التشغيلي أعلى من صافي الدخل؟ هذا يشير إلى أن الأرباح ليست مجرد قيود محاسبية. (نقطة واحدة)
تحسن العائد على الأصول (ROA): هل العائد على الأصول هذا العام أفضل من العام الماضي؟ (نقطة واحدة)
ب) الرافعة المالية والسيولة (Leverage & Liquidity) - (3 نقاط محتملة)
5. انخفاض الرافعة المالية: هل انخفضت نسبة الدين طويل الأجل إلى الأصول هذا العام مقارنة بالعام الماضي؟ (نقطة واحدة)
6. تحسن النسبة الحالية (Current Ratio): هل تحسنت سيولة الشركة قصيرة الأجل هذا العام؟ (نقطة واحدة)
7. عدم إصدار أسهم جديدة: هل قامت الشركة بتخفيف ملكية المساهمين الحاليين عن طريق إصدار أسهم جديدة خلال العام؟ (تحصل على نقطة إذا لم تصدر أسهماً جديدة).
ج) الكفاءة التشغيلية (Operating Efficiency) - (2 نقطة محتملة)
8. تحسن هامش الربح الإجمالي: هل زاد هامش الربح الإجمالي هذا العام مقارنة بالعام الماضي؟ (نقطة واحدة)
9. تحسن معدل دوران الأصول: هل زادت كفاءة الشركة في استخدام أصولها لتوليد المبيعات هذا العام؟ (نقطة واحدة)
تفسير النتائج:
نتيجة قوية (8-9 نقاط): تشير إلى أن الشركة في وضع مالي قوي جداً وأساسياتها تتحسن بشكل ملحوظ.
نتيجة محايدة (3-7 نقاط): وضع الشركة مستقر ولكن لا توجد إشارات قوية على تحسن أو تدهور كبير.
نتيجة ضعيفة (0-2 نقاط): تشير إلى أن أساسيات الشركة المالية ضعيفة وقد تكون في مسار تدهور.
2. كيفية استخدام المؤشر على TradingView
الكود الذي قدمته يجعل من السهل تطبيق هذا التحليل المعقد بنقرة زر.
التطبيق على الرسم البياني:
أضف المؤشر إلى الرسم البياني. سيظهر في نافذة منفصلة أسفله، ويعرض خطاً يمثل قيمة F-Score عبر الزمن.
فهم المدخلات (الإعدادات):
Symbol (الرمز): كما في المؤشر السابق، اتركه فارغاً لتحليل السهم الحالي، أو أدخل رمز سهم آخر للمقارنة.
Period (الفترة): يتيح لك اختيار الفترة المالية التي يتم على أساسها حساب المعايير التسعة. FY (سنوي) هو الخيار الأكثر شيوعاً لأنه يقارن أداء الشركة على أساس سنوي، وهو ما يتوافق مع تصميم النموذج الأصلي.
قراءة المخرجات البصرية:
خط F-Score: يوضح قيمة المؤشر تاريخياً. هل كانت الشركة قوية مالياً في الماضي؟ هل تحسنت مؤخراً؟
الخطوط المتقطعة: الخط الأخضر عند 8 والخط الأحمر عند 2 يمثلان حدود المناطق القوية والضعيفة.
الخلفية الملونة: تقدم ملخصاً بصرياً سريعاً:
أخضر: الشركة قوية جداً (F-Score ≥ 8).
أحمر: الشركة ضعيفة (F-Score ≤ 2).
بدون لون: الشركة في المنطقة المحايدة.
الاستخدام العملي في التحليل:
فلترة الأسهم القيمة: الاستخدام الأساسي للنموذج هو فلترة الأسهم التي تبدو "رخيصة" (مثلاً، لديها نسبة سعر إلى ربح منخفضة). سهم رخيص مع F-Score مرتفع (8 أو 9) هو مرشح استثماري واعد. سهم رخيص مع F-Score منخفض (0-2) هو على الأرجح "فخ قيمة" (value trap) يجب تجنبه.
تتبع التحولات: راقب الشركات التي ينتقل مؤشرها من المنطقة الضعيفة إلى المنطقة المحايدة أو القوية. هذا قد يكون مؤشراً مبكراً على تحول إيجابي في أداء الشركة.
تجنب المخاطر: الشركات التي لديها F-Score منخفض باستمرار هي شركات يجب التعامل معها بحذر شديد، حتى لو بدت أسعارها مغرية.
أداة تكميلية: F-Score هو أداة كمية ممتازة، لكن يجب دمجها دائماً مع تحليل نوعي (فهم نموذج عمل الشركة، إدارتها، وميزتها التنافسية).
In English
1. The Scientific Method: What is the Piotroski F-Score?
The F-Score is a numerical scoring system developed in 2000 by Joseph Piotroski, an accounting professor at Stanford University. The model's purpose is to measure the financial strength of value stocks, specifically those with a high book-to-market ratio.
The core idea is to sift through seemingly "cheap" companies and distinguish between those whose financial fundamentals are improving (the "winners") and those whose fundamentals are deteriorating (the "losers").
The model is based on nine simple criteria, divided into three main categories. A company earns one point for each criterion it meets and zero if it doesn't. The final score is the sum of these points, ranging from 0 (worst) to 9 (best).
The Nine Criteria (How Points are Scored):
A) Profitability (4 possible points)
Positive Net Income (ROA > 0): Did the company make a profit in the last year? (1 point)
Positive Operating Cash Flow: Did the company generate cash from its core operations? (1 point)
Quality of Earnings (Cash Flow > Net Income): Is operating cash flow higher than net income? This suggests earnings are not just accounting-driven. (1 point)
Improving Return on Assets (ROA): Is this year's ROA better than last year's? (1 point)
B) Leverage & Liquidity (3 possible points)
5. Lower Leverage: Did the long-term debt-to-assets ratio decrease this year compared to last year? (1 point)
6. Improving Current Ratio: Has the company's short-term liquidity improved this year? (1 point)
7. No New Share Issuance: Did the company dilute existing shareholders by issuing new shares during the year? (1 point is awarded if it did not issue new shares).
C) Operating Efficiency (2 possible points)
8. Improving Gross Margin: Did the gross profit margin increase this year compared to last year? (1 point)
9. Improving Asset Turnover: Did the company's efficiency in using its assets to generate sales improve this year? (1 point)
Interpreting the Score:
Strong Score (8-9 points): Indicates the company is in a very strong financial position and its fundamentals are improving significantly.
Neutral Score (3-7 points): The company's situation is stable, but there are no strong signals of major improvement or deterioration.
Weak Score (0-2 points): Indicates the company's financial fundamentals are weak and may be on a deteriorating path.
2. How to Use the Indicator on TradingView
The code you provided makes applying this complex analysis as simple as a click.
Applying to the Chart:
Add the indicator to a chart. It will appear in a separate pane below, displaying a line representing the F-Score's value over time.
Understanding the Inputs (Settings):
Symbol: As with the previous indicator, leave it blank to analyze the current stock, or enter another ticker for comparison.
Period: This allows you to select the fiscal period on which the nine criteria are based. FY (Fiscal Year) is the most common choice as it compares the company's performance on a year-over-year basis, which aligns with the model's original design.
Reading the Visual Outputs:
F-Score Line: Shows the historical value of the score. Was the company financially strong in the past? Has it improved recently?
Dashed Lines: The green line at 8 and the red line at 2 mark the thresholds for the strong and weak zones.
Colored Background: Provides a quick visual summary:
Green: The company is very strong (F-Score ≥ 8).
Red: The company is weak (F-Score ≤ 2).
No Color: The company is in the neutral zone.
Practical Use in Analysis:
Filtering Value Stocks: The model's primary use is to filter stocks that appear "cheap" (e.g., have a low P/E ratio). A cheap stock with a high F-Score (8 or 9) is a promising investment candidate. A cheap stock with a low F-Score (0-2) is likely a "value trap" and should be avoided.
Tracking Turnarounds: Keep an eye on companies whose score moves from the weak zone into the neutral or strong zone. This could be an early indicator of a positive turnaround in the company's performance.
Risk Avoidance: Companies with a persistently low F-Score are ones to be very cautious about, even if their prices look tempting.
A Complementary Tool: The F-Score is an excellent quantitative tool, but it should always be combined with qualitative analysis (understanding the business model, management, and competitive landscape)
Altman Z-Score Indicator
1. المنهج العلمي: ما هو نموذج ألتمان Z-Score؟
نموذج Z-Score هو صيغة إحصائية متعددة المتغيرات تم تطويرها في عام 1968 من قبل البروفيسور إدوارد ألتمان (Edward Altman)، أستاذ التمويل في جامعة نيويورك. الهدف الأساسي للنموذج هو التنبؤ باحتمالية إفلاس شركة مساهمة عامة خلال العامين التاليين.
يعتمد النموذج على دمج خمس نسب مالية أساسية، يتم استخلاصها من القوائم المالية للشركة (قائمة الدخل والميزانية العمومية). يتم ضرب كل نسبة في معامل (وزن) محدد، ثم يتم جمع النتائج للحصول على قيمة واحدة هي "Z-Score".
المعادلة الأساسية للشركات الصناعية العامة (وهي التي يطبقها الكود):
`Z = 1.2 X₁ + 1.4 X₂ + 3.3 X₃ + 0.6 X₄ + 1.0 X₅`
حيث أن:
X₁ = (رأس المال العامل / إجمالي الأصول): يقيس سيولة الشركة على المدى القصير. رأس المال العامل المرتفع يعني أن الشركة لديها أصول متداولة كافية لتغطية التزاماتها قصيرة الأجل.
X₂ = (الأرباح المحتجزة / إجمالي الأصول): يقيس الربحية التراكمية للشركة وقدرتها على تمويل أصولها من أرباحها الخاصة بدلاً من الديون.
X₃ = (الأرباح قبل الفوائد والضرائب (EBIT) / إجمالي الأصول): يقيس كفاءة الشركة في تحقيق أرباح من أصولها قبل احتساب تكاليف التمويل والضرائب. إنها مؤشر قوي على الربحية التشغيلية.
X₄ = (القيمة السوقية لحقوق الملكية / إجمالي الالتزامات): يقيس الرافعة المالية للشركة. كلما انخفضت قيمة الشركة السوقية مقارنة بديونها، زاد خطر الإفلاس.
X₅ = (إجمالي الإيرادات (المبيعات) / إجمالي الأصول): يعرف بـ "معدل دوران الأصول". يقيس مدى كفاءة الشركة في استخدام أصولها لتوليد المبيعات.
تفسير النتائج (مناطق التصنيف):
قام ألتمان بتحديد ثلاث مناطق لتصنيف الشركات بناءً على قيمة Z-Score:
1. منطقة الخطر (Distress Zone) | Z < 1.81: الشركات التي تقع في هذه المنطقة لديها احتمالية عالية جداً لمواجهة صعوبات مالية قد تؤدي إلى الإفلاس.
2. المنطقة الرمادية (Grey Zone) | 1.81 ≤ Z ≤ 2.99: الشركات في هذه المنطقة تقع في وضع غير مؤكد. لا يمكن تصنيفها بأنها آمنة أو في خطر وشيك، وتتطلب تحليلاً أعمق.
3. المنطقة الآمنة (Safe Zone) | Z > 2.99: الشركات التي تحقق نتيجة في هذه المنطقة تعتبر في وضع مالي سليم ومستقر، واحتمالية إفلاسها منخفضة جداً.
2. كيفية استخدام المؤشر على TradingView
الكود الذي قمت بتطويره يجعل استخدام هذا النموذج سهلاً للغاية. إليك كيفية استخدامه بفعالية:
1. التطبيق على الرسم البياني:
أضف المؤشر إلى الرسم البياني لأي سهم ترغب في تحليله. سيظهر المؤشر في نافذة منفصلة أسفل الرسم البياني للسعر.
2. فهم المدخلات (الإعدادات):
Symbol (الرمز): يمكنك ترك هذا الحقل فارغاً ليقوم المؤشر بتحليل السهم الحالي على الرسم البياني تلقائياً. أو يمكنك إدخال رمز سهم آخر (مثلاً `AAPL` أو `MSFT`) لتحليل تلك الشركة ومقارنتها بالشركة الحالية.
Fiscal Period (الفترة المالية): هذا هو أهم إعداد. يتيح لك اختيار البيانات التي سيعتمد عليها التحليل:
`FY` (سنوي): يستخدم بيانات آخر سنة مالية كاملة. هذا هو الخيار الأكثر شيوعاً واستقراراً.
`FQ` (ربع سنوي): يستخدم بيانات آخر ربع مالي. هذا الخيار أكثر حساسية للتغيرات قصيرة المدى.
`TTM` (آخر 12 شهراً): يستخدم البيانات المجمعة لآخر 12 شهراً. يوفر نظرة حديثة ومستمرة.
3. قراءة المخرجات البصرية:
خط Z-Score: هو الخط الرئيسي للمؤشر. حركته عبر الزمن توضح كيف يتغير الوضع المالي للشركة. هل يتحسن (الخط يرتفع) أم يتدهور (الخط ينخفض)؟
الخطوط المتقطعة: الخط الأخضر عند `2.99` والخط الأحمر عند `1.81` يمثلان حدود المناطق (الآمنة والخطر). عبور خط Z-Score لهذه الحدود يعتبر إشارة هامة.
الخلفية الملونة: هي أسرع طريقة لمعرفة وضع الشركة الحالي:
أخضر: الشركة في المنطقة الآمنة.
أصفر (رمادي): الشركة في المنطقة الرمادية.
أحمر: الشركة في منطقة الخطر.
4. الاستخدام العملي في التحليل:
التحليل الاتجاهي: لا تنظر فقط إلى القيمة الحالية. راقب اتجاه خط Z-Score على مدى عدة سنوات. شركة يرتفع مؤشرها باستمرار من 1.5 إلى 2.5 هي في مسار تحسن، بينما شركة ينخفض مؤشرها من 4.0 إلى 3.1 قد تكون في بداية مسار تدهور.
إشارات الإنذار المبكر: إذا انخفض Z-Score لشركة ما تحت 2.99 ودخل المنطقة الرمادية، فهذه دعوة للبدء في تحليل أعمق لأسباب هذا الانخفاض. إذا انخفض تحت 1.81، فهذه إشارة خطر واضحة يجب أخذها على محمل الجد.
المقارنة بين الشركات: استخدم حقل `Symbol` لمقارنة الصحة المالية لشركتين في نفس القطاع. أي منهما لديها Z-Score أعلى وأكثر استقراراً؟
تأكيد التحليل الأساسي: استخدم هذا المؤشر كأداة مساعدة بجانب تحليلاتك الأخرى، وليس كأداة وحيدة لاتخاذ القرار. فهو لا يأخذ في الاعتبار عوامل مثل الإدارة، الميزة التنافسية، أو ظروف السوق الكلية.
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In English
1. The Scientific Method: What is the Altman Z-Score Model?
The Z-Score model is a multivariate statistical formula developed in 1968 by Dr. Edward Altman, a Professor of Finance at New York University. The primary objective of the model is to predict the probability of a publicly traded company going bankrupt within the next two years.
The model works by combining five key financial ratios derived from a company's financial statements (the income statement and balance sheet). Each ratio is multiplied by a specific coefficient (weight), and the results are summed up to produce a single value: the "Z-Score."
The Original Formula for Public Manufacturing Companies (which your code implements):
`Z = 1.2 X₁ + 1.4 X₂ + 3.3 X₃ + 0.6 X₄ + 1.0 X₅`
Where:
X₁ = (Working Capital / Total Assets): Measures the company's short-term liquidity. High working capital indicates the company has sufficient current assets to cover its short-term liabilities.
X₂ = (Retained Earnings / Total Assets): Measures the company's cumulative profitability and its ability to finance its assets with its own profits instead of debt.
X₃ = (Earnings Before Interest and Taxes (EBIT) / Total Assets): Measures the company's efficiency in generating profits from its assets before accounting for financing costs and taxes. It's a strong indicator of operational profitability.
X₄ = (Market Value of Equity / Total Liabilities): Measures the company's financial leverage. The more a company's market value declines relative to its debt, the higher the bankruptcy risk.
X₅ = (Total Revenue (Sales) / Total Assets): Known as "Asset Turnover." It measures how efficiently the company is using its assets to generate sales.
Interpreting the Score (The Zones of Discrimination):
Altman identified three zones to classify companies based on their Z-Score:
1. Distress Zone | Z < 1.81: Companies in this zone have a very high probability of facing financial distress that could lead to bankruptcy.
2. Grey Zone | 1.81 ≤ Z ≤ 2.99: Companies here are in an uncertain position. They cannot be classified as either safe or in imminent danger and require deeper analysis.
3. Safe Zone | Z > 2.99: Companies with a score in this zone are considered to be in a sound and stable financial position, with a very low probability of bankruptcy.
2. How to Use the Indicator on TradingView
The code you've developed makes using this model incredibly easy. Here is how to use it effectively:
1. Applying to the Chart:
Add the indicator to the chart of any stock you wish to analyze. The indicator will appear in a separate pane below the price chart.
2. Understanding the Inputs (Settings):
Symbol: You can leave this blank for the indicator to automatically analyze the current stock on the chart. Alternatively, you can enter another stock ticker (e.g., `AAPL` or `MSFT`) to analyze that company and compare it to the current one.
Fiscal Period: This is the most important setting. It lets you choose the data on which the analysis is based:
`FY` (Fiscal Year): Uses data from the last full fiscal year. This is the most common and stable option.
`FQ` (Fiscal Quarter): Uses data from the last fiscal quarter. This option is more sensitive to short-term changes.
`TTM` (Trailing Twelve Months): Uses aggregated data from the last 12 months, providing a recent and rolling view.
3. Reading the Visual Outputs:
Z-Score Line: This is the main plot of the indicator. Its movement over time shows how the company's financial health is evolving. Is it improving (line goes up) or deteriorating (line goes down)?
Dashed Lines: The green line at `2.99` and the red line at `1.81` represent the thresholds for the Safe and Distress zones. The Z-Score line crossing these thresholds is a significant signal.
Colored Background: This is the quickest way to see the company's current status:
Green: The company is in the Safe Zone.
Yellow (Grey): The company is in the Grey Zone.
Red: The company is in the Distress Zone.
4. Practical Use in Analysis:
Trend Analysis: Don't just look at the current value. Observe the trend of the Z-Score line over several years. A company whose score is consistently rising from 1.5 to 2.5 is on an improving path, whereas a company whose score is falling from 4.0 to 3.1 may be at the beginning of a deteriorating path.
Early Warning Signals: If a company's Z-Score drops below 2.99 into the Grey Zone, it's a call to start a deeper analysis into the reasons for this decline. If it drops below 1.81, it is a clear danger signal that must be taken seriously.
Peer Comparison: Use the `Symbol` input field to compare the financial health of two companies in the same sector. Which one has a higher and more stable Z-Score?
Fundamental Analysis Confirmation: Use this indicator as a supplementary tool alongside your other analyses, not as a sole decision-making tool. It does not account for factors like management quality, competitive advantage, or macroeconomic conditions.
KKF RangeIts a very unique range indicator that uses stochastics and volume bookmap and radp to view current trend to identify potential entries.
Date Marker📅 Date Marker
Date Marker is a simple, lightweight indicator that draws a single vertical line on a chosen date — ideal for quickly comparing how different charts looked at the same point in time.
Switch between symbols or timeframes, and the line automatically stays fixed at your selected date.
Perfect for studying market reactions to key events, earnings, announcements, or macro shifts.
Multi Brownian Forecast📊 Multi Brownian Forecast (Time-Adaptive, Probabilistic)
This indicator uses a sophisticated Geometric Brownian Motion (GBM) Monte Carlo simulation to project future price paths. It adapts to any chart timeframe and provides quantitative, multi-period probability signals.
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🧠 Core Mathematical Methodology
The model relies on GBM, which is a continuous-time stochastic process that models asset prices.
1. Historical Analysis (Drift & Volatility):
* The script first calculates Logarithmic Returns over a user-defined Historical Lookback (Hours) .
* Drift ($\mu$): Computed as the average of the log returns.
* Volatility ($\sigma$): Computed as the standard deviation of the log returns.
* These values are then time-adapted to an hourly step, compensating for the chart's current timeframe (e.g., 5-minute, 1-hour).
2. Monte Carlo Simulation:
* It runs a specified Number of Simulations (e.g., 1000).
* For each simulation, the price is stepped forward hourly using the GBM formula, which incorporates the calculated drift and a random shock drawn from a normal distribution (generated via the Box-Muller transform ).
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✨ Key Features
Probabilistic Quartile Forecast: Plots a dynamic "cone" of probability on the chart. It shows key price percentiles (Q1, Q2/Median, Q3, and Q4/Outer Bound) at the forecast's expiration, visualizing the expected range of price outcomes based on the simulations.
Multi-Period Probability Signals: This is the core signal feature. Users can define multiple, independent forecast periods (e.g., 4h, 16h, 48h) in a comma-separated list.
* For each period, a Probability Up and Probability Down is calculated based on hitting a custom Target Price Change (%) (e.g., 2%) at a certain confidence level given a simulation over the historical backlook.
* The probabilities are displayed in a chart table. The cell text turns white if the calculated probability exceeds the user-defined Signal Confidence (%) .
Conditional Fibonacci Retracement: Optionally displays a Fibonacci Retracement on the chart. This feature is only activated when one of the multi-period signals reaches its minimum confidence threshold, providing a contextual technical level when a probabilistic edge is found.
Force of Strategy (FoS, Multi TF/TA, Backtest, Alerts)Introducing the FoS Trading System
A comprehensive and innovative solution designed for both novice and experienced traders to enhance their intraday trading.
The basic idea of creating this script is to stay profitable in any market
Key Features:
There are over 25 no-repaint strategies for generating buy and sell signals to choose from
10 symbols for simultaneous trading
Webhook alerts in TTA format (tradingview to anywhere) pre-configured to send messages for trading cross-margin futures on major Crypto Exchanges: Binance, Bitget, BingX, Bybit, GateIO and OKX
A unique automated "Strategy switcher" feature for backtesting and live trading—not just a specific strategy, but the logic behind choosing a trading one or another strategy based on backtesting data obtained in real time
Advanced risk management options and backtest result metrics
Higher Timeframe filters (Technical Rating, ADX, Volatility) and ability for check backtest results with 9 main higher timeframes
Buy and sell signals are generated using TradingView Technical Ratings, indicators with adaptive length algorithms and various classic indicators with standard settings to avoid overfitting
Next, I will describe in detail what this script does and what settings it operates with:
"All Strategies" off
- In the global settings block, as shown in the main chart screenshot, you select how long the script will perform backtests in days, with a limitation on the number of bars for calculations. This limitation is necessary to maintain an acceptable calculation speed. You also choose which two higher timeframes we will use for signal and filters when confirming the opening of trades
- With "All Strategies" off - as in the example on the main chart screenshot, trading is carried out by strategy #1 on 10 selected tickers simultaneously. By default, I selected the 9 top-capitalized cryptocurrencies on the Bitget exchange and the chart symbol. You can change that choice of 9 non chart opened instruments and # strategy for each them
- The first row in the table 1 shows some of the main choosen script settings, in attached example: initial capital 20$, leverage 50L, 20 backtest days, 3$ is invest in one deal, 60m - is chart timeframe, next 60m is higher timeframe 1 and last 90m is higher timeframe 2. In first column you see shortened to 5 characters ticker names
- The exchange name in the second row determines the alert messages format
I've attached another example of trading with setting "All strategies" off in the image below. In this example, trading 10 standard symbols on an hourly timeframe, 2 coins from 10: 1000SATS and DOGE have generated a profit of over $65 over the past 20 days using strategy #4
Can you browse a wide range of trading instruments and select the 10 best strategies and settings for future trading? Of course, trading is what this script is do!
The parameters in the table 1 mean the following:
TR - count of closed trading deals
WR - Winning Rate, PF - Profit Factor
MDD - Max Draw Down for all calculated time from initial capital
R$ - trading profit result in usd
The parameters in the table 2 is just more metrics for chart symbol:
PT - result in usd Per one Trade
PW - result Per Win, PL - result Per Lose
ROI - Rate of Investments
SR - Sharpe Ratio, MR - CalMAR ration
Tx - Commision Fee in Usd
R$ - trading profit result in usd again
Table 2 separate trade results of backtesting for longs and shorts. In first column you see how many USD were invested in one trade, taking into account possible position splitting (will be discussed in more detail in the risk management section)
Settings:
"All Strategies" on, "Check Last" off
When "All Strategies" is active, trading changed from 10 symbols and one strategy to all strategies and one chart symbol. If option "Check Last" is inactive you will see backtest results for each of strategy in backtest setting days. This is useful, for example, if you want to see backtest results under different settings over a long period of time for calibrating risk management or entry rules
"All Strategies" on, "Check Last" on
- If "All Strategies" and "Check Last" is active trading will occur on the chart symbol only for those strategies that meet the criteria of the settings block for the enabled "All Strategies" option. For example your criteria is: for last 5 trades for all strategies, open next trade only on strategy which reached ROI 25% and WinRate 50%. When strategy with this setting criteria receive Buy or Sell Signal this trade will be opened, and when trade will be close "check last" will repeat. This feature i called "Strategy switcher"
-In Table 1 if strategy meet criteria you will see "Ok" label, if strategy meet criteria and have maximum from other reached ROI they labeled "Best". Chart strategy labeled "Chart", Chart and Ok labels in one time is "Chart+", "Chart" and "Best" is labeled "Best+"
- The color in the first column of table 1 indicates that the strategy is currently in an open position: green means an open long position, red means an open short position.
In picture bellow you will see good example for trading with check results for last 10 trades, and make desicion for trading when criteries 0.25 ROI and WinRate 50% reached for Top 2 by ROI strategies from all list of them. This example of trading logic in last 20 days (include periods when strategy don't arise 10 trades) give a profit $30+. At the bottom of the screen, you can see Labels with the numbers of the strategies that opened the trades. In this example, trades were primarily opened using strategy number 2, and the second most effective strategy after the 20-day backtest was strategy number 9
Who can promise you'll make a profit of $30 in the next 20 days with a drawdown of no more than $8 from the initial $20 with invest in one trade just 2.7$? No one. But this script guarantees that in the future it will repeat the same logic of switching trading strategies that brought profit over the last 20 days
Risk management options
- When a buy or sell trade is opened, you'll see three lines on the chart: a red stop-loss line (SL), a green take-profit line (TP), and a blue line representing the entry price. The trade will be closed if the high price or low price reaches the line TP or SL (no wait for bar close) and alert will be triggered once per bar when script recalculates
- Several options are available to control the behavior of SL/TP lines, such as stop-loss by percentage, ATR, or Highest High (HH) and Lowest Low (LL). Take Profit can be in percent, ATR or in Risk Reward ratio. There some Trailing Stop with start trail trigger options, like ATR, percent or HH / LL
- Additionally, in risk managment settings a function has been implemented for adding a position when the breakeven level expressed in the current ROI is reached for opened trade (splitting position). The position is added within the bar.
- Webhook alerts in TTA format with message contained next info : Buy / Sell or adding Quantity, Leverage, SL price, TP price and close trade
Keep in mind if the stop-loss changed when adding a position, the stop-loss will not be able to be higher than the current bar's low price, regardless of your settings, as backtest trades do not use intra-bar data, in this situation SL will be correct at next bar (but alert message don't be sended twice). And please note that this script does not have an option to simultaneously open trades in different directions. Only 1 trade can be opened for 1 trading instrument at a time
Backtest Engine
Backtest is a very important part of this script. Here describe how its calculate:
- Profit or Loss is USD: close trade price * open trade quantity - open trade price * open trade quantity - open trade quantity * (open trade price + close trade price)/2 * commision fee
Possible slippage or alert sending delay needed to be include in commission % which you will set in risk managment settings block, default settings is 0.15% (0,06% for open, 0,06% for close and 0,03% for possible slippage or additional fees)
- Maximum Draw Down: Drawdown = (peak - current equity) / peak * 100 ;
Drawdown > maxDrawdown ? maxDrawdown = Drawdown
- ROI: profit result in USD / sum of all positions margin
- CalMAR Ratio: ROI / (-MaxDrawDown)
- Sharpe Ratio: ROI / standard deviation for (Sum of all Profits and Loses) / (Sum of all Position Margins)
This description was added because in metrics i don't use parameters like "The risk-free rate of return". Keep in mind how exactly this script calculate profit and perfomance when adjusting key criteria in the strategy switching parameters block of script settings
Strategies itself
For trading, you can enable or disable various Higher Timeframes Filters (ADX, volatility, technical rating).
With filters enabled, trades will only open when the setting parameters are reached
- Strategy number 1, 2 and 3: is Higher Timeframe TradingView Technical Ratings itself, 1 is summary total rating, 2 is oscillators and 3 is moving averages. When TR filter cross filter levels trade will be open at chart bar close. By Default on chart you see Summary Technical Rating oscillator, but here the options for change it to Oscillator TR or Moving Average TR
- Strategy number 4, 5 and 6: is Chart TimeFrame TR. Trades will open when its values (Summary, Oscillators and Moving Averages) reached setting buy sell level
- Strategy number 7, 8 and 9: is Alternative buy sell logic for Chart TimeFrame TR, trades will open when counting rising or falling values will be reached
- Strategies with number from 10 to 18: is chosen by user adaptive moving averages and oscillators indicators. There in settings you will see many different adaptive length algorithms for trading and different types of moving averages and oscillators. In tooltips in settings you will find very more information, and in settings you will see list of all indicators and algorithms (more than 30 variations). All adaptive strategies have their options in settings for calibrating and plotting
- Strategies with number from 19: its can't be chosen or calibarted, this is needed for avoid overfitting, i try to found mostly time worked strategies and use its with standard settings. In future it's possible to changing current or adding additional strategies. At the time of publication this script uses: Dynamic Swing HH LL (19), Composite indicator (20), %R Exhausting with different signals (21,22,23), Pivot Point SuperTrend (24), Ichimoku Cloud (25), TSI (26), Fib Level RSI (27). I don't plot classic strategies in this script
Let me explain, the value of this script is not in the strategies it includes, but in how exactly it collects the results of their work, how it filters the opening of trades, what risk management it applies and what strategy switching logic it performs. The system itself that you are now reading about represents the main value of this script
Finally if you get access for this script
- You will see many other not described options and possibilities like Kelly position or list of settings for adaptive strategies, also i added many usefull tooltips in script settings
Happy trading, and stay tuned for updates!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorized for this script, and the information published with them. This script is strictly for individual use. No one know future and Investments are always made at your own risk. I am not responsible for any losses you may incur. Please before investment make sure that chosen logic is enaugh profitable on virtual demo account.
Advanced HMM - 3 States CompleteHidden Markov Model
Aconsistent challenge for quantitative traders is the frequent behaviour modification of financial
markets, often abruptly, due to changing periods of government policy, regulatory environment
and other macroeconomic effects. Such periods are known as market regimes. Detecting such
changes is a common, albeit difficult, process undertaken by quantitative market participants.
These various regimes lead to adjustments of asset returns via shifts in their means, variances,
autocorrelation and covariances. This impacts the effectiveness of time series methods that rely
on stationarity. In particular it can lead to dynamically-varying correlation, excess kurtosis ("fat
tails"), heteroskedasticity (volatility clustering) and skewed returns.
There is a clear need to effectively detect these regimes. This aids optimal deployment of
quantitative trading strategies and tuning the parameters within them. The modeling task then
becomes an attempt to identify when a new regime has occurred adjusting strategy deployment,
risk management and position sizing criteria accordingly.
A principal method for carrying out regime detection is to use a statistical time series tech
nique known as a Hidden Markov Model . These models are well-suited to the task since they
involve inference on "hidden" generative processes via "noisy" indirect observations correlated
to these processes. In this instance the hidden, or latent, process is the underlying regime state,
while the asset returns are the indirect noisy observations that are influenced by these states.
Smart Money Volume Activity [AlgoAlpha]🟠 OVERVIEW
This tool visualizes how Smart Money and Retail participants behave through lower-timeframe volume analysis. It detects volume spikes far beyond normal activity, classifies them as institutional or retail, and projects those zones as reactive levels. The script updates dynamically with each bar, showing when large players enter while tracking whether those events remain profitable. Each event is drawn as a horizontal line with bubble markers and summarized in a live P/L table comparing Smart Money versus Retail.
🟠 CONCEPTS
The core logic uses Z-score normalization on lower-timeframe volumes (like 5m inside a 1h chart). This lets the script detect statistically extreme bursts of buying or selling activity. It classifies each detected event as:
Smart Money — volume inside the candle body (suggesting hidden accumulation or distribution)
Retail — volume closing at bar extremes (suggesting chase entries or panic exits)
When new events appear, the script plots them as horizontal levels that persist until price interacts again. Each level acts as a potential reaction zone or liquidity footprint. The integrated P/L table then measures which class (Retail or Smart Money) is currently “winning” — comparing cumulative profitable versus losing volume.
🟠 FEATURES
Classifies flows into Smart Money or Retail based on candle-body context.
Displays live P/L comparison table for Smart vs Retail performance.
Alerts for each detected Smart or Retail buy/sell event.
🟠 USAGE
Setup : Add the script to any chart. Set Lower Timeframe Value (e.g., “5” for 5m) smaller than your main chart timeframe. The Period input controls how many bars are analyzed for the Z-score baseline. The Threshold (|Z|) decides how extreme a volume must be to plot a level.
Read the chart : Horizontal lines mark where heavy Smart or Retail volume occurred. Bright bubbles show the strongest events — their size reflects Z-score intensity. The on-chart table updates live: green cells show profitable flows, red cells show losing flows. A dominant green Smart Money row suggests institutions are currently controlling price.
See what others are doing :
Settings that matter : Raising Threshold (|Z|) filters noise, showing only large players. Increasing Period smooths results but reacts slower to new bursts. Use Show = “Both” for full comparison or isolate “Smart Money” / “Retail” to focus on one class.
Blocks🔍 On-Chain Analytics Overview
This indicator compares key on-chain metrics against their 55-day and 111-day moving averages to evaluate the network’s overall health.
It helps visualize trends in user activity, transaction dynamics, and market valuation to identify potential shifts in market sentiment.
📊 Core Metrics
Active Addresses: The number of unique addresses actively interacting with the network. An increase suggests higher user engagement and network utilization.
New Address Count: The number of newly created wallets. A decline may indicate slowing user adoption or lower retail participation.
Non-zero Balance Addresses: Addresses holding a non-zero balance — a metric of long-term adoption and retention.
Active Supply (1Y): The percentage of supply that has moved within the last year. Lower values imply stronger “HODL” behavior and long-term confidence.
Realized Market Value: Represents the total value of coins based on their last on-chain movement, reflecting the cost basis of holders.
Market Value: The current market capitalization derived from price × circulating supply.
Large Transaction Count / Volume: Measures institutional or whale-level activity. Spikes may indicate accumulation or distribution phases.
90-day NVT (Network Value to Transaction Volume): A valuation metric comparing network value to transaction activity.
High NVT → Overvalued or speculative phase
Low NVT → Undervalued or high on-chain utility
Daily Transaction Count: Indicates on-chain activity levels; rising values often precede bullish momentum.
Transaction Fees (USD): Network demand indicator — rising fees can reflect congestion or growing user activity.
Top Holder Addresses: Tracks concentration among top wallets (e.g., top 0.1%, 0.001%), offering insights into wealth distribution and whale dominance.
⚙️ Delta & Score System
Δ (Delta): Shows deviation from the long-term average (MA-55 / MA-111).
Positive Delta → Metric above historical norm (strength or overheating)
Negative Delta → Metric below historical norm (weakness or cooling)
Score Icons:
✅ = Healthy / Positive trend
⚠️ = Mixed or Neutral signal
🔻 = Caution / Negative trend
🧭 Interpretation
A cluster of green checkmarks (✅) signals robust network fundamentals — often supportive of long-term growth.
A dominance of warnings (⚠️) or red signals (🔻) indicates network slowdowns or profit-taking phases.
PnL PortfolioThis indicator provides a comprehensive, real-time overview of your open trading portfolio directly on the chart. It allows you to track up to 20 different trading pairs simultaneously.
For each asset, simply input the Pair Symbol, Average Entry Price, and Position Quantity. The script securely fetches the current market price and dynamically calculates and displays a customizable table showing:
Real-Time Profit/Loss ($)
Percentage PnL (%)
Entry Price and Position Quantity
The table uses color coding to clearly highlight profitable (green) or losing (red) positions, and its location on the chart (top/bottom, left/right) is fully adjustable.
PnL TrackerThis script allows you to manually input the details for up to 64 unique positions in the settings, each requiring a Symbol, Average Cost, and Quantity (Qty).
Key Features:
Average Cost Line: Plots a horizontal line on the chart corresponding to your recorded Average Cost for the security currently being viewed.
Real-Time PnL Label: A dynamic label attached to the Average Cost line provides an instant summary of your PnL in both percentage and currency for the last visible bar.
Detailed PnL Box: Displays a consolidated, easy-to-read table in the bottom-right corner of the chart, clearly showing:
The Symbol and Quantity of your position.
Your Average Cost.
The current PnL in percentage (%) and base currency (e.g., USD, EUR).
Visibility Controls: Toggles in the settings allow you to show or hide the Average Cost line and the PnL summary box independently.
This tool is perfect for actively managing and visualizing your multi-asset portfolio positions without leaving your main trading chart. Simply enter your positions in the indicator's settings, and the script will automatically track the PnL for the symbol matching the current chart.
RAXIS — PnL/TP/RR HUD + Precise Bollinger + Future Candles# RAXIS — PnL/TP/RR HUD + Precise Bollinger + Future Candles
A pro-grade trading dashboard with precise Bollinger Bands, future-candle projection, and risk–reward analytics.
**Developed by the hosh365 team**
## Why RAXIS?
RAXIS is an all-in-one package for professional traders who want real-time PnL, entries/exits, signal accuracy, and forward scenarios on the **same** chart—cleanly, with precise controls.
## Key Features
* **Animated HUD + Fixed Panel:** Real-time list of entries (ROI/PnL), total PnL, weighted ROI, and a signal-accuracy summary. A fixed bottom-right panel shows equity, entry/average, E1..E4, weighted targets, SL, R:R, and final net profit.
* **Risk Management & R:R:** Equity input, risk percentage, and ATR-based stop suggestions; set SL/TP and draw their lines on the chart; calculate and display risk–reward.
* **Precise Bollinger + Signals & Alerts:** Choose MA type (SMA/EMA/RMA/WMA), squeeze threshold, and icons/labels for band touches/reversions; alert conditions for Long/Short.
* **Analytical “Future Candles” Projection:** Generates “phantom candles” weighted by momentum (EMA), mid-band slope, and Ichimoku bias; ATR-clamped drift; draws body/wicks for each projected candle. Tunables include count, momentum length, mean-reversion strength, volatility, drift cap, and weights.
* **Multiple Entries + Dynamic Sizing:** Four independent entries (E1..E4) with leverage and $/coin sizing modes; dynamic position sizing based on location relative to Bollinger Bands.
* **On-Chart Lines:** Sticky lines for entry, targets, and stop with thickness control.
* **Symbol Memory & Change Notice:** Store/apply live PnL to per-symbol equity, reset equity, and auto-notify on ticker change.
## Who It’s For
**Scalpers** *(very short-term traders; seconds to minutes, aiming to capture small moves)*, **swing traders** *(medium-term traders; holding for days to weeks to ride price swings)*, and **futures/spot** traders who need a mix of real-time performance view, risk control, and forward scenario planning in one tool.
## Access (Invite-Only)
This script is published as **Invite-Only**. To receive access, please send your TradingView username. (Optional: add your access terms/plan here.)
## Important Notes
* This tool is for educational/analytical purposes and is **not** a buy/sell signal or a guarantee of profit; you are responsible for your own trading decisions.
* Stop-loss and exit suggestions are based on your inputs and technical parameters (ATR/risk %) and must align with your personal strategy and risk management.
PnL PortfolioThis script allows you to input the details for up to 20 active positions across various trading pairs or markets. Stop manually calculating your trades—get instant, real-time feedback on your performance.
Key Features:
Multi-Pair Tracking: Monitor up to 20 unique symbols simultaneously.
Required Inputs: Easily define the Symbol, Entry Price, and Position Quantity (size) for each trade in the indicator settings.
Real-Time PnL: Instantly calculates and displays two critical metrics based on the current market price:
% PnL (Percentage Profit/Loss)
Absolute Profit/Loss (in currency)
Color-Coded Feedback: The PnL columns are color-coded (green/teal for profit, red/maroon for loss) for immediate visual confirmation of your trade health.
Customizable Layout: Choose where the dashboard table appears on your chart (top-left, top-right, bottom-left, or bottom-right) to keep your trading view clean.
This is an essential overlay for any trader managing multiple active positions and needing a consolidated, easy-to-read overview.
RAXIS — PnL/TP/RR HUD + Precise Bollinger + Future Candles# RAXIS — PnL/TP/RR HUD + Precise Bollinger + Future Candles
A pro-grade trading dashboard with precise Bollinger Bands, future-candle projection, and risk–reward analytics.
**Developed by the hosh365 team**
## Why RAXIS?
RAXIS is an all-in-one package for professional traders who want real-time PnL, entries/exits, signal accuracy, and forward scenarios on the **same** chart—cleanly, with precise controls.
## Key Features
* **Animated HUD + Fixed Panel:** Real-time list of entries (ROI/PnL), total PnL, weighted ROI, and a signal-accuracy summary. A fixed bottom-right panel shows equity, entry/average, E1..E4, weighted targets, SL, R:R, and final net profit.
* **Risk Management & R:R:** Equity input, risk percentage, and ATR-based stop suggestions; set SL/TP and draw their lines on the chart; calculate and display risk–reward.
* **Precise Bollinger + Signals & Alerts:** Choose MA type (SMA/EMA/RMA/WMA), squeeze threshold, and icons/labels for band touches/reversions; alert conditions for Long/Short.
* **Analytical “Future Candles” Projection:** Generates “phantom candles” weighted by momentum (EMA), mid-band slope, and Ichimoku bias; ATR-clamped drift; draws body/wicks for each projected candle. Tunables include count, momentum length, mean-reversion strength, volatility, drift cap, and weights.
* **Multiple Entries + Dynamic Sizing:** Four independent entries (E1..E4) with leverage and $/coin sizing modes; dynamic position sizing based on location relative to Bollinger Bands.
* **On-Chart Lines:** Sticky lines for entry, targets, and stop with thickness control.
* **Symbol Memory & Change Notice:** Store/apply live PnL to per-symbol equity, reset equity, and auto-notify on ticker change.
## Who It’s For
**Scalpers** *(very short-term traders; seconds to minutes, aiming to capture small moves)*, **swing traders** *(medium-term traders; holding for days to weeks to ride price swings)*, and **futures/spot** traders who need a mix of real-time performance view, risk control, and forward scenario planning in one tool.
## Access (Invite-Only)
This script is published as **Invite-Only**. To receive access, please send your TradingView username. (Optional: add your access terms/plan here.)
## Important Notes
* This tool is for educational/analytical purposes and is **not** a buy/sell signal or a guarantee of profit; you are responsible for your own trading decisions.
* Stop-loss and exit suggestions are based on your inputs and technical parameters (ATR/risk %) and must align with your personal strategy and risk management.
Delta Volume Heatmap🔥 Delta Volume Heatmap
The Delta Volume Heatmap visualizes the real-time strength of per-bar delta volume — highlighting the imbalance between buying and selling pressure.
Each column’s color intensity reflects how strong the delta volume deviates from its moving average and standard deviation.
🟩 Green tones = Buy-dominant activity (bullish imbalance)
🟥 Red tones = Sell-dominant activity (bearish imbalance)
This tool helps traders quickly identify:
Abnormal volume spikes
Absorption or exhaustion zones
Potential reversal or continuation signals
First Passage Time - Distribution AnalysisThe First Passage Time (FPT) Distribution Analysis indicator is a sophisticated probabilistic tool that answers one of the most critical questions in trading: "How long will it take for price to reach my target, and what are the odds of getting there first?"
Unlike traditional technical indicators that focus on what might happen, this indicator tells you when it's likely to happen.
Mathematical Foundation: First Passage Time Theory
What is First Passage Time?
First Passage Time (FPT) is a concept in stochastic processes that measures the time it takes for a random process to reach a specific threshold for the first time. Originally developed in physics and mathematics, FPT has applications in:
Quantitative Finance: Option pricing, risk management, and algorithmic trading
Neuroscience: Modeling neural firing patterns
Biology: Population dynamics and disease spread
Engineering: Reliability analysis and failure prediction
The Mathematics Behind It
This indicator uses Geometric Brownian Motion (GBM), the same stochastic model used in the Black-Scholes option pricing formula:
dS = μS dt + σS dW
Where:
S = Asset price
μ = Drift (trend component)
σ = Volatility (uncertainty component)
dW = Wiener process (random walk)
Through Monte Carlo simulation, the indicator runs 1,000+ price path simulations to statistically determine:
When each threshold (+X% or -X%) is likely to be hit
Which threshold is hit first (directional bias)
How often each scenario occurs (probability distribution)
🎯 How This Indicator Works
Core Algorithm Workflow:
Calculate Historical Statistics
Measures recent price volatility (standard deviation of log returns)
Calculates drift (average directional movement)
Annualizes these metrics for meaningful comparison
Run Monte Carlo Simulations
Generates 1,000+ random price paths based on historical behavior
Tracks when each path hits the upside (+X%) or downside (-X%) threshold
Records which threshold was hit first in each simulation
Aggregate Statistical Results
Calculates percentile distributions (10th, 25th, 50th, 75th, 90th)
Computes "first hit" probabilities (upside vs downside)
Determines average and median time-to-target
Visual Representation
Displays thresholds as horizontal lines
Shows gradient risk zones (purple-to-blue)
Provides comprehensive statistics table
📈 Use Cases
1. Options Trading
Selling Options: Determine if your strike price is likely to be hit before expiration
Buying Options: Estimate probability of reaching profit targets within your time window
Time Decay Management: Compare expected time-to-target vs theta decay
Example: You're considering selling a 30-day call option 5% out of the money. The indicator shows there's a 72% chance price hits +5% within 12 days. This tells you the trade has high assignment risk.
2. Swing Trading
Entry Timing: Wait for higher probability setups when directional bias is strong
Target Setting: Use median time-to-target to set realistic profit expectations
Stop Loss Placement: Understand probability of hitting your stop before target
Example: The indicator shows 85% upside probability with median time of 3.2 days. You can confidently enter long positions with appropriate position sizing.
3. Risk Management
Position Sizing: Larger positions when probability heavily favors one direction
Portfolio Allocation: Reduce exposure when probabilities are near 50/50 (high uncertainty)
Hedge Timing: Know when to add protective positions based on downside probability
Example: Indicator shows 55% upside vs 45% downside—nearly neutral. This signals high uncertainty, suggesting reduced position size or wait for better setup.
4. Market Regime Detection
Trending Markets: High directional bias (70%+ one direction)
Range-bound Markets: Balanced probabilities (45-55% both directions)
Volatility Regimes: Compare actual vs theoretical minimum time
Example: Consistent 90%+ bullish bias across multiple timeframes confirms strong uptrend—stay long and avoid counter-trend trades.
First Hit Rate (Most Important!)
Shows which threshold is likely to be hit FIRST:
Upside %: Probability of hitting upside target before downside
Downside %: Probability of hitting downside target before upside
These always sum to 100%
⚠️ Warning: If you see "Low Hit Rate" warning, increase this parameter!
Advanced Parameters
Drift Mode
Allows you to explore different scenarios:
Historical: Uses actual recent trend (default—most realistic)
Zero (Neutral): Assumes no trend, only volatility (symmetric probabilities)
50% Reduced: Dampens trend effect (conservative scenario)
Use Case: Switch to "Zero (Neutral)" to see what happens in a pure volatility environment, useful for range-bound markets.
Distribution Type
Percentile: Shows 10%, 25%, 50%, 75%, 90% levels (recommended for most users)
Sigma: Shows standard deviation levels (1σ, 2σ)—useful for statistical analysis
⚠️ Important Limitations & Best Practices
Limitations
Assumes GBM: Real markets have fat tails, jumps, and regime changes not captured by GBM
Historical Parameters: Uses recent volatility/drift—may not predict regime shifts
No Fundamental Events: Cannot predict earnings, news, or macro shocks
Computational: Runs only on last bar—doesn't give historical signals
Remember: Probabilities are not certainties. Use this indicator as part of a comprehensive trading plan with proper risk management.
Created by: Henrique Centieiro. feedback is more than welcome!
Liquidity TriggersKey Points
Liquidity Triggers indicate:
Where liquidity-derived support levels are.
Where liquidity-derived resistance levels are.
When a large price increase is approaching via the Rip Currents .
- When a large price decrease is approaching via the Dip Currents .
Summary
Liquidity Triggers are produced by measuring liquidity and determining where supportive liquidity and resistance-liquidity are. These trigger-levels designate price-points where breakouts, breakthroughs, and bounces are anticipated.
Liquidity Triggers are dynamic, and they constantly re-evaluate liquidity conditions to determine where the next group of sellers or buyers are that can fuel rapid changes in price movement, such as initiating a trend change or stalling price-action completely.
To use, simply apply to your chart and monitor for Supportive Liquidity Triggers (LTs that are below price) for bounces, and Resistance Liquidity Triggers (LTs that are above price) for rejections.
You can also set Alerts designed specifically around the Liquidity Triggers.
Examples
Example 1: A quick look at LT Resistances and Supports. When a LT is above spot, then it is considered a resistance. When LT is below spot, it is considered a support.
Example 2: LTs can indicate to us when an upcoming Rip Current (large price appreciation) or a Dip Current (large price depreciation) is starting.
Here is an example of a Rip Current:
And here is a Dip Current:
Details
Liquidity Triggers come with a default load-out that utilizes several pre-configured settings for quick and easy start-up.
Triggers
The default triggers are labeled LT-1 through LT-7, these correspond ` orders ` that describe which type of liquidity is monitored. The two groups of traders that are monitored are the ` Eager ` and the ` Organic `.
The default triggers use the Fibonacci sequence to adjust their orders in a standardized way.
Triggers 1, 2, 3, and 4 monitor the ` Eager ` traders (with default settings) while triggers 5, 6, and 7 monitor the ` Organic `traders.
Eager Triggers represent profit-takers and dip-buyers .
When the Eager Triggers are above the price, they are ` selling the rip `, and when the Eager Triggers are below price, they are ` buying the dip `. These moments indicate growing pressure for a reversal. Eager triggers are any trigger with an order of 89 or less .
Organic Triggers represent value-seekers with long-term goals. When they are below price, they are areas of support and tend to fuel bounces, while when organic triggers that are above price are areas of resistance and often provoke rejections. Organic triggers are any trigger with an order of 90 or more .
Here's an example showing the faint eager liquidity triggers above spot, indicating profit-taking and below spot after a price-dip indicating dip-buying .
Customization
There are additional settings and configurations available to the Liquidity Triggers indicator that help customize your view of liquidity.
Smoothing
Smoothing can be applied to the triggers for a more peaceful showing. The smoothing options are:
None - Default.
Exponential-Moving Average (EMA) : Ideal for when you want the most recent activity to take higher priority.
Simple-Moving Average (SMA) : Ideal for when you want a smoother appearance but do not want to change the data too much.
Weighted-Moving Average (WMA): Ideal for when you want the smoothing to increase as the trigger order increases.
Modified-Moving Average (RMA): Produces the most smooth data.
Here is an example of how smoothing can change the appearance of LTs for easier analysis for when things get complicated:
Modifying the Default Load-out
The default loadout attempts to balance having a wide view of the data without bringing too many lines or values into the picture that might be too noisy, but these values can be added to customize and expand your view if desired.
The Fib load-out has the options with t he default load-out being .
Feel free to mix and match and explore which views you prefer when analyzing liquidity.
For example, for the extreme data-heads, you can add LDPM twice on the chart to get all of the orders displayed at once:
Liquidity Triggers - Granular Triggers
The granular trigger can be toggled on (default: off) for when candle-specific liquidity measurements desired. They can help identify which specific candles have eager and aggressive traders attempting to move spot: the further away the granular trigger is from the candle, the more force is being applied!
Manual LTs
If you’re not satisfied with the default options for triggers, you can set your own with the Manual Liquidity Triggers option.
Time-Based LTs
Time-based liquidity triggers give you a view of support and resistance triggers based off of the time chosen, rather than by an order. This allows you to construct “weekly Liquidity-Triggers” or “hourly Liquidity Triggers” to analyze and compare against.
Note: If the timeframes are too far apart, you might get an error. For instance, putting a 1-week reference LT onto a 30-second chart may not work.
Liquidity-Triggers Data-Table
With the `Display Liquidity Trigger Statuses and Values` option, you can place a data-table on the chart that will display the time-based triggers, their values, and if they are above (bearish) or below (bullish) spot.
Alerts
When you set alerts, you can determine which order is used for determining `Is bullish`, `Is Bearish`, `Has Become Bullish`, `Has Become Bearish` alerts in the LT Alert Order setting.
Several LT alerts are available to set:
Is Bullish / Bearish: these are designed to analyze conditions at the end of the candle and if spot is above the alert-trigger, then an alert is sent out that conditions are bullish, and if spot is below the alert-trigger, then an alert is sent out if conditions are bearish.
Has Become Bullish / Bearish: designed to analyze conditions at the start of a candle and determine if a change has occurred (a LT cross-over).
Suspected Rip Current: these are designed to alert you when a suspected upwards rip in price is underway, as characterized by all LT triggers moving rapidly down away from spot.
Suspected Dip Current: these are designed to alert you when a suspected downwards rip in price is underway, as characterized by all LT triggers moving rapidly up and above, away from spot.
These alerts can then be put into a webhook for external processing if desired.
Frequently Asked Questions
How can I gain access to LT?
Check out the Author's Instructions section below.
Where can I get more information?
Check out the Author's Instructions section below for how to obtain more information.
I tried to add LT to my chart but it produced an error.
Sometimes this happens but no worries. Just change the chart's interval to a different time and then back, the indicator should re-load. If that fails, try removing it completely and re-applying it.
Is it normal for LTs to have different values on different timeframes?
Yup! Think of each time-interval as a different "zoom" of the market. Imagine you are taking a picture of the ocean to figure out the direction of water movement. If you take the picture from space, you will see big general trends but if you take the photo from your boat in the harbor, you're going to get specific data about that area. That's how LT works!
The view of the liquidity depends on the "zoom-age" (the chart's interval) used when taking the photo.
I think there is an issue with the alerts - what should I do?
This is not ideal! If this happens, please reach out via the contact information in the Author's Instructions section below with the following details:
What symbol?
What timeframe?
Which alert?
When did the alert occur?
Can I attach the alerts to webhooks?
Yup! Be sure to check out TV's guide on webhooks ( T.V. Guide to Alerts ) for how to get started.
Does LT receive updates?
Yup! If a bug or issue is found, an update is pushed out. You will be notified when this occurs and it is highly recommended that you replace all charts with LT on them with the new version as the updates go out.
Seasonality📈 What “Seasonality” Means in Trading
Seasonality in trading refers to recurring market patterns that tend to happen around the same time each year, month, or even week. These patterns are based on historical tendencies, for example, certain stocks or indices often rise or fall during specific periods due to consistent economic, institutional, or behavioral factors.
A simple example:
The S&P 500 often performs stronger in the last quarter of the year (“Santa Rally”).
Crude oil prices tend to rise during summer months when demand for fuel increases.
Agricultural commodities follow planting and harvest cycles.
By analyzing these seasonal trends, traders can gain an additional layer of probability in their decision-making. It doesn’t replace technical or fundamental analysis, but it complements them by showing when a market historically tends to move in a certain direction.
That’s why a seasonality indicator can be extremely useful:
It visualizes past performance patterns directly on your chart.
It helps identify periods of high or low probability for bullish or bearish moves.
It allows traders to align trades with statistical tendencies, not just current price action.
You can also customize the lookback period, for example, view seasonal patterns from the last 5, 10, 15, or 20 years, depending on how much historical data you want to include.
In short, a good seasonality indicator doesn’t predict the future, it highlights what markets tend to do, helping traders act with more context and confidence.
