TradFi Fundamentals: Enhanced Macroeconomic Momentum Trading Introduction
The "Enhanced Momentum with Advanced Normalization and Smoothing" indicator is a tool that combines traditional price momentum with a broad range of macroeconomic factors. I introduced the basic version from a research paper in my last script. This one leverages not only the price action of a security but also incorporates key economic data—such as GDP, inflation, unemployment, interest rates, consumer confidence, industrial production, and market volatility (VIX)—to create a comprehensive, normalized momentum score.
Previous indicator
Explanation
In plain terms, the indicator calculates a raw momentum value based on the change in price over a defined lookback period. It then normalizes this momentum, along with several economic indicators, using a method chosen by the user (options include simple, exponential, or weighted moving averages, as well as a median absolute deviation (MAD) approach). Each normalized component is assigned a weight reflecting its relative importance, and these weighted values are summed to produce an overall momentum score.
To reduce noise, the combined momentum score can be further smoothed using a user-selected method.
Signals
For generating trade signals, the indicator offers two modes:
Zero Cross Mode: Signals occur when the smoothed momentum line crosses the zero threshold.
Zone Mode: Overbought and oversold boundaries (which are user defined) provide signals when the momentum line crosses these preset limits.
Definition of the Settings
Price Momentum Settings:
Price Momentum Lookback: The number of days used to compute the percentage change in price (default 50 days).
Normalization Period (Price Momentum): The period over which the price momentum is normalized (default 200 days).
Economic Data Settings:
Normalization Period (Economic Data): The period used to normalize all economic indicators (default 200 days).
Normalization Method: Choose among SMA, EMA, WMA, or MAD to standardize both price and economic data. If MAD is chosen, a multiplier factor is applied (default is 1.4826).
Smoothing Options:
Apply Smoothing: A toggle to enable further smoothing of the combined momentum score.
Smoothing Period & Method: Define the period and type (SMA, EMA, or WMA) used to smooth the final momentum score.
Signal Generation Settings:
Signal Mode: Select whether signals are based on a zero-line crossover or by crossing user-defined overbought/oversold (OB/OS) zones.
OB/OS Zones: Define the upper and lower boundaries (default upper zones at 1.0 and 2.0, lower zones at -1.0 and -2.0) for zone-based signals.
Weights:
Each component (price momentum, GDP, inflation, unemployment, interest rates, consumer confidence, industrial production, and VIX) has an associated weight that determines its contribution to the overall score. These can be adjusted to reflect different market views or risk preferences.
Visual Aspects
The indicator plots the smoothed combined momentum score as a continuous blue line against a dotted zero-line reference. If the Zone signal mode is selected, the indicator also displays the upper and lower OB/OS boundaries as horizontal lines (red for overbought and green for oversold). Buy and sell signals are marked by small labels ("B" for buy and "S" for sell) that appear at the bottom or top of the chart when the score crosses the defined thresholds, allowing traders to quickly identify potential entry or exit points.
Conclusion
This enhanced indicator provides traders with a robust approach to momentum trading by integrating traditional price-based signals with a suite of macroeconomic indicators. Its normalization and smoothing techniques help reduce noise and mitigate the effects of outliers, while the flexible signal generation modes offer multiple ways to interpret market conditions. Overall, this tool is designed to deliver a more nuanced perspective on market momentum.
Fundamental Analysis
ICT Asian Range and Killzones (Power of 3) ANAKIN UTC+3 AMDworking amd indicator for p03 using p03 this is used by looking for sweeps and making use of stuff like
mmxm
smt
csd
and mss to find structural liquidity entries
RSI - Vortex Cross Signals long/shortSync of the 2 indicators , Vortex / RSI on crossover to signal long or short possible events, need to be combine with another indicator like SMA (200) to filter noise and SMA (8) to exit position
fairas Gold ScalpingStrategi price action adalah strategi perdagangan yang didasarkan pada analisis pergerakan harga aset keuangan.
Penjelasan
Price action adalah analisis teknis yang berfokus pada hubungan harga pasar saat ini dengan harga masa lalu.
Price action berbeda dengan sebagian besar analisis teknis lainnya karena tidak bergantung pada nilai "bekas" dari riwayat harga.
Price action lebih memahami inti perdagangan daripada menggunakan pengenalan pola grafik atau menerapkan indikator teknis.
Studi tentang price action membantu memahami pergerakan harga dan memiliki jeda alami.
Price action membantu memahami hubungan harga pasar saat ini dengan harga masa lalu atau terkini.
DİNAMİK BEAR VS BULL POWER 2025Bu indikatör şu özelliklere sahiptir:
Dinamik Hesaplama:
Belirtilen periyot içindeki fiyat hareketlerini analiz eder
Yüzdesel değişimleri kullanarak boğa ve ayı güçlerini hesaplar
RSI bazlı momentum faktörü ile değerleri düzeltir
Düzleştirme:
Ani değişimleri yumuşatmak için hareketli ortalama kullanır
Daha stabil sinyaller üretir
Görselleştirme:
Yeşil çizgi: Boğa gücü
Kırmızı çizgi: Ayı gücü
Sağ üst köşede güncel değerleri gösteren tablo
Özellikler:
Değerler 0-100 arasında değişir
Ani geçişler yerine kademeli değişim gösterir
Momentum faktörü ile trend yönünü dikkate alır. YATIRIM TAVSİYESİ NİTELİĞİNDE DEĞİLDİR.TÜM SORUMLULUK SİZE AİTTİR.TEST EDEBİLİRSİNİZ.
Cryptolabs Global Liquidity Cycle Momentum IndicatorCryptolabs Global Liquidity Cycle Momentum Indicator (LMI-BTC)
This open-source indicator combines global central bank liquidity data with Bitcoin price movements to identify medium- to long-term market cycles and momentum phases. It is designed for traders who want to incorporate macroeconomic factors into their Bitcoin analysis.
How It Works
The script calculates a Liquidity Index using balance sheet data from four central banks (USA: ECONOMICS:USCBBS, Japan: FRED:JPNASSETS, China: ECONOMICS:CNCBBS, EU: FRED:ECBASSETSW), augmented by the Dollar Index (TVC:DXY) and Chinese 10-year bond yields (TVC:CN10Y). This index is:
- Logarithmically scaled (math.log) to better represent large values like central bank balances and Bitcoin prices.
- Normalized over a 50-period range to balance fluctuations between minimum and maximum values.
- Compared to prior-year values, with the number of bars dynamically adjusted based on the timeframe (e.g., 252 for 1D, 52 for 1W), to compute percentage changes.
The liquidity change is analyzed using a Chande Momentum Oscillator (CMO) (period: 24) to measure momentum trends. A Weighted Moving Average (WMA) (period: 10) acts as a signal line. The Bitcoin price is also plotted logarithmically to highlight parallels with liquidity cycles.
Usage
Traders can use the indicator to:
- Identify global liquidity cycles influencing Bitcoin price trends, such as expansive or restrictive monetary policies.
- Detect momentum phases: Values above 50 suggest overbought conditions, below -50 indicate oversold conditions.
- Anticipate trend reversals by observing CMO crossovers with the signal line.
It performs best on higher timeframes like daily (1D) or weekly (1W) charts. The visualization includes:
- CMO line (green > 50, red < -50, blue neutral), signal line (white), Bitcoin price (gray).
- Horizontal lines at 50, 0, and -50 for improved readability.
Originality
This indicator stands out from other momentum tools like RSI or basic price analysis due to:
- Unique Data Integration: Combines four central bank datasets, DXY, and CN10Y as macroeconomic proxies for Bitcoin.
- Dynamic Prior-Year Analysis: Calculates liquidity changes relative to historical values, adjustable by timeframe.
- Logarithmic Normalization: Enhances visibility of extreme values, critical for cryptocurrencies and macro data.
This combination offers a rare perspective on the interplay between global liquidity and Bitcoin, unavailable in other open-source scripts.
Settings
- CMO Period: Default 24, adjustable for faster/slower signals.
- Signal WMA: Default 10, for smoothing the CMO line.
- Normalization Window: Default 50 periods, customizable.
Users can modify these parameters in the Pine Editor to tailor the indicator to their strategy.
Note
This script is designed for medium- to long-term analysis, not scalping. For optimal results, combine it with additional analyses (e.g., on-chain data, support/resistance levels). It does not guarantee profits but supports informed decisions based on macroeconomic trends.
Data Sources
- Bitcoin: INDEX:BTCUSD
- Liquidity: ECONOMICS:USCBBS, FRED:JPNASSETS, ECONOMICS:CNCBBS, FRED:ECBASSETSW
- Additional: TVC:DXY, TVC:CN10Y
DeadMoney || OrderBlocksСкрипт от DeadMoney автоматически определяет и визуализирует бычьи (Bullish) и медвежьи (Bearish) ордер-блоки на графике.
Он основан на поиске свингов (Swing High/Low) и выделяет прямоугольные зоны, где может быть повышенная активность покупателей или продавцов.
Когда цена пробивает ордер-блок, зона отображается другим цветом и перестаёт считаться актуальной.
Основные параметры
Swing Lookback: определяет, насколько далеко назад идёт поиск свинг-точек.
Bullish OB и Bearish OB: сколько последних бычьих и медвежьих блоков отображать на графике.
Use Candle Body: если включено, логика учитывает тело свечи (open/close) вместо её экстремумов (high/low).
Использование
Добавьте скрипт на график — он автоматически построит ордер-блоки.
Параметры в меню Settings позволяют менять количество отображаемых блоков, глубину поиска свингов и учитывать/игнорировать тела свечей.
Цвета бычьих и медвежьих блоков, а также их «пробитых» состояний можно изменить в разделе Style.
Скрипт предназначен для помощи в техническом анализе, но не даёт гарантий успеха.
Перед использованием обязательно изучите принципы технического анализа и убедитесь что вы понимаете логику работы индикатора а также ордер-блоков.
Автор: DeadMoney
Контакт: @DeadMoneyKrypto (Telegram)
Higher Time Frame Fair Value Gap [ZeroHeroTrading]A fair value gap (FVG) highlights an imbalance area between market participants, and has become popular for technical analysis among price action traders.
A bullish (respectively bearish) fair value gap appears in a triple-candle pattern when there is a large candle whose previous candle’s high (respectively low) and subsequent candle’s low (respectively high) do not fully overlap the large candle. The space between these wicks is known as the fair value gap.
The following script aims at identifying higher timeframe FVG's within a lower timeframe chart. As such, it offers a unique perspective on the formation of FVG's by combining the multiple timeframe data points in the same context.
You can change the indicator settings as you see fit to achieve the best results for your use case.
Features
It draws higher timeframe bullish and bearish FVG's on the chart.
For bullish (respectively bearish) higher timeframe FVG's, it adds the buying (respectively selling) pressure as a percentage ratio of the up (respectively down) volume of the second higher timeframe bar out of the total up (respectively down) volume of the first two higher timeframe bars.
It adds a right extended trendline from the most recent lowest low (respectively highest high) to the top (respectively bottom) of the higher timeframe bullish (respectively bearish) FVG.
It detects and displays higher timeframe FVG's as early as one starts forming.
It detects and displays lower timeframe (i.e. chart's timeframe) FVG's upon confirmation.
It allows for skipping inside first bars when evaluating FVG's.
It allows for dismissing higher timeframe FVG's if there is no update for any period of the chart's timeframe. For instance, this can occur at lower timeframes during low trading activity periods such as extended hours.
Settings
Higher Time Frame FVG dropdown: Selects the higher timeframe to run the FVG detection on. Default is 15 minutes. It must be higher than, and a multiple of, the chart's timeframe.
Higher Time Frame FVG color select: Selects the color of the text to display for higher timeframe FVG's. Default is black.
Show Trend Line checkbox: Turns on/off trendline display. Default is on.
Show Lower Time Frame FVG checkbox: Turns on/off lower timeframe (i.e. chart's timeframe) FVG detection. Default is on.
Show Lower Time Frame FVG color select: Selects the color of the border for lower timeframe (i.e. chart's timeframe) FVG's. Default is white.
Include Inside Bars checkbox: Turns on/off the inclusion of inside first bars when evaluating FVG's. Default is on.
With Consistent Updates checkbox: Turns on/off consistent updates requirement. Default is on.
NUBA 20 Nes2tilson t3 rsı ema50 - 200 Bu algoritma da her türlü çeşit var. tablodan özellikleri açıp kapatabilirsiniz.
Bollinger Bands + RSI Strategy//@version=5
strategy("Bollinger Bands + RSI Strategy", overlay=true,
description="This is a trading strategy based on Bollinger Bands and RSI. The strategy generates buy and sell signals based on price action and market momentum. It buys when the price crosses above the lower Bollinger Band while the RSI is below 30 (indicating oversold conditions). It sells when the price crosses below the upper Bollinger Band while the RSI is above 70 (indicating overbought conditions). Positions are closed when the price crosses the middle Bollinger Band (the moving average).")
// Bollinger Bands parameters
length = input.int(20, title="Bollinger Bands Length")
src = input(close, title="Source")
mult = input.float(2.0, title="Bollinger Bands Multiplier")
basis = ta.sma(src, length)
dev = mult * ta.stdev(src, length)
upper_band = basis + dev
lower_band = basis - dev
// RSI parameters
rsi_length = input.int(14, title="RSI Length")
rsi = ta.rsi(src, rsi_length)
// Plot Bollinger Bands
plot(upper_band, color=color.red, linewidth=2, title="Upper Bollinger Band")
plot(lower_band, color=color.green, linewidth=2, title="Lower Bollinger Band")
plot(basis, color=color.blue, linewidth=1, title="Middle Band")
// Buy Condition
buy_condition = ta.crossover(close, lower_band) and rsi < 30
if buy_condition
strategy.entry("Buy", strategy.long)
// Sell Condition
sell_condition = ta.crossunder(close, upper_band) and rsi > 70
if sell_condition
strategy.entry("Sell", strategy.short)
// Exit Conditions (optional: use the middle Bollinger Band for exits)
exit_condition = ta.cross(close, basis)
if exit_condition
strategy.close("Buy")
strategy.close("Sell")
// Optional: Plot RSI for additional insight
hline(70, "Overbought", color=color.red)
hline(30, "Oversold", color=color.green)
plot(rsi, color=color.purple, title="RSI", linewidth=1, offset=-5)
DeadMoney || LiquidityИндикатор автоматически определяет зоны ликвидности на графике на основе локальных экстремумов (high и low) и отслеживает накопленный объём торгов на этих уровнях.
1. Поиск ликвидности
- При формировании локального максимума (high) создаётся «sell»-уровень (красная линия по умолчанию).
- При формировании локального минимума (low) создаётся «buy»-уровень (зелёная линия по умолчанию).
2. Накопление объёма
- Пока цена не пробивает уровень, индикатор суммирует объём (volume) каждой новой свечи и обновляет подпись на линии.
- Когда цена пересекает уровень (пробивает его), линия становится штриховой и перестаёт обновляться (ликвидность снимается).
3. Настройки
- Sell и Buy цвета линий можно менять в параметрах: Sell, Buy.
- Pivot Length позволяет управлять чувствительностью к локальным экстремумам: чем больше значение, тем реже формируются новые уровни (14 по умолчанию).
Используйте DeadMoney || Liquidity в своей торговле, чтобы автоматически определять зоны ликвидности и видеть накопленный объём на важных уровнях!
Enhanced Interval Candle with Breakout Detection and Detailed InThis indicator visualizes the last candle of a user-defined time interval (e.g., 1 hour, 4 hours, 1 day) on the current chart, providing enhanced details and breakout detection. It fetches the open, high, low, and close prices of the interval candle and draws a stylized representation of it, offset to the right of the current bar. The candle body and wicks are colored according to whether the interval candle closed bullishly (green) or bearishly (red). In addition to the candle itself, the indicator displays horizontal dotted lines representing the high, low, and midpoint of the interval candle, along with labels showing their exact values. These labels are dynamically updated as the interval candle changes. Furthermore, the script detects and visualizes breakouts of the interval candle's high or low. When the current price closes above the interval high, a green dashed line and a "Bullish Breakout" label are displayed. Conversely, when the current price closes below the interval low, a red dashed line and a "Bearish Breakout" label are shown. The breakout lines and labels are also dynamically updated. This indicator helps traders easily track the price action of a higher timeframe candle and spot potential breakouts based on that candle's range. The user can configure the time interval to suit their trading needs.
Dynamic Fibonacci Levels with Value and Percentage LabelsThis indicator plots the most common Fibonacci retracement levels (23.6%, 38.2%, 50%, 61.8%, and 78.6%) on the price chart, using a configurable period to calculate recent high and low points. Unlike standard Fibonacci indicators, this script enhances visualization by including dynamic labels that display both the numerical value of the Fibonacci level and its corresponding percentage. The levels are calculated using a configurable "support/resistance" period and smoothed using a simple moving average to reduce noise. The user can customize the calculation period length, smoothing period, label visibility, and line thickness. Labels are dynamically updated on each new bar, showing the current values and percentages of the calculated Fibonacci levels. This indicator makes it easier to identify potential support and resistance areas based on Fibonacci retracements, providing clear and concise visual information directly on the chart.
TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals.
Revenue & Profit GrowthA simple yet powerful financial tracker that helps you identify fundamental growth trends by visualizing quarterly and TTM (Trailing Twelve Months) revenue and profit data. The script combines bar and line visualizations with a dynamic growth table to provide comprehensive insights into a company's financial performance at a glance.
A business has many metrics, but revenue and profit growths - I would argue - are the primordial ones.
Why is this unique? It overlays profit and revenues in one graph and provides QoQ and YoY growth rates.
Features
Quarterly performance bars overlaid with TTM trend lines for both revenue and profit metrics
Automatic calculation of Year-over-Year (YoY) and Quarter-over-Quarter (QoQ) growth rates
Color-coded visualization: blue for revenue, green/red for profits based on positive/negative values
Alerts for revenue and profit changes
Blockchain Fundamentals: Liquidity Cycle MomentumLiquidity Cycle Momentum Indicator
Overview:
This indicator analyzes global liquidity trends by calculating a unique Liquidity Index and measuring its year-over-year (YoY) percentage change. It then applies a momentum oscillator to the YoY change, providing insights into the cyclical momentum of liquidity. The indicator incorporates a limited historical data workaround to ensure accurate calculations even when the chart’s history is short.
Features Breakdown:
1. Limited Historical Data Workaround
Function: The limit(length) function adjusts the lookback period when there isn’t enough historical data (i.e., near the beginning of the chart), ensuring that calculations do not break due to insufficient data.
2. Global Liquidity Calculation
Data Sources:
TVC:CN10Y (10-year yield from China)
TVC:DXY (US Dollar Index)
ECONOMICS:USCBBS (US Central Bank Balance Sheet)
FRED:JPNASSETS (Japanese assets)
ECONOMICS:CNCBBS (Chinese Central Bank Balance Sheet)
FRED:ECBASSETSW (ECB assets)
Calculation Methodology:
A ratio is computed (cn10y / dxy) to adjust for currency influences.
The Liquidity Index is then derived by multiplying this ratio with the sum of the other liquidity components.
3. Year-over-Year (YoY) Percent Change
Computation:
The indicator determines the number of bars that approximately represent one year.
It then compares the current Liquidity Index to its value one year ago, calculating the YoY percentage change.
4. Momentum Oscillator on YoY Change
Oscillator Components:
1. Calculated using the Chande Momentum Oscillator (CMO) applied to the YoY percent change with a user-defined momentum length.
2. A weighted moving average (WMA) that smooths the momentum signal.
3. Overbought and Oversold zones
Signal Generation:
Buy Signal: Triggered when the momentum crosses upward from an oversold condition, suggesting a potential upward shift in liquidity momentum.
Sell Signal: Triggered when crosses below an overbought condition, indicating potential downward momentum.
State Management:
The indicator maintains a state variable to avoid repeated signals, ensuring that a new buy or sell signal is only generated when there’s a clear change in momentum.
5. Visual Presentation and Alerts
Plots:
The oscillator value and signalline are plotted for visual analysis.
Overbought and oversold levels are marked with dashed horizontal lines.
Signal Markers:
Buy and sell signals are marked with green and maroon circles, respectively.
Background Coloration:
Optionally, the chart’s background bars are colored (yellow for buy signals and fuchsia for sell signals) to enhance visual cues when signals are triggered.
Conclusion
In summary, the Liquidity Cycle Momentum Indicator provides a robust framework to analyze liquidity trends by combining global liquidity data, YoY changes, and momentum oscillation. This makes it an effective tool for traders and analysts looking to identify cyclical shifts in liquidity conditions and potential turning points in the market.
Forward Curve Visualization ToolProvide the spot symbol and the futures product root, and the script automatically scans all relevant contracts for you—no more tedious manual searches. The result is a clean, intuitive chart showing the live forward curve in real time.
It also detects contango or backwardation conditions (based on spot < F1 < F2 < F3).
Future Features:
Plot historical snapshots of the curve (1 day, 1 week, or 1 month ago) to understand market trends over time.
Display additional metrics such as annualized basis, cost of carry (CoC), and even volume or open interest for deeper insights.
If you trade futures and watch the forward curve, this script will give you the actionable data you need and get more ideas or features you’d like to see. Let’s build them together!
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Blockchain Fundamentals: Liquidity & BTC YoYLiquidity & BTC YoY Indicator
Overview:
This indicator calculates the Year-over-Year (YoY) percentage change for two critical metrics: a custom Liquidity Index and Bitcoin's price. The Liquidity Index is derived from a blend of economic and forex data representing the M2 money supply, while the BTC price is obtained from a reliable market source. A dedicated limit(length) function is implemented to handle limited historical data, ensuring that the YoY calculations are available immediately—even when the chart's history is short.
Features Breakdown:
1. Limited Historical Data Workaround
- Functionality: limit(length) The function dynamically adjusts the lookback period when there isn’t enough historical data. This prevents delays in displaying YoY metrics at the beginning of the chart.
2. Liquidity Calculation
- Data Sources: Combines multiple data streams:
USM2, ECONOMICS:CNM2, USDCNY, ECONOMICS:JPM2, USDJPY, ECONOMICS:EUM2, USDEUR
- Formula:
Liquidity Index = USM2 + (CNM2 / USDCNY) + (JPM2 / USDJPY) + (EUM2 / USDEUR)
[b3. Bitcoin Price Calculation
- Data Source: Retrieves Bitcoin's price from BITSTAMP:BTCUSD on the user-selected timeframe for its historical length.
4. Year-over-Year (YoY) Percent Change Calculation
- Methodology:
- The indicator uses a custom function, to autodetect the proper number of bars, based on the selected timeframe.
- It then compares the current value to that from one year ago for both the Liquidity Index and BTC price, calculating the YoY percentage change.
5. Visual Presentation
- Plotting:
- The YoY percentage changes for Liquidity (plotted in blue) and BTC price (plotted in orange) are clearly displayed.
- A horizontal zero line is added for visual alignment, making it easier to compare the two copies of the metric. You add one copy and only display the BTC YoY. Then you add another copy and only display the M2 YoY.
-The zero lines are then used to align the scripts to each other by interposing them. You scale each chart the way you like, then move each copy individually to align both zero lines on top of each other.
This indicator is ideal for analysts and investors looking to monitor macroeconomic liquidity trends alongside Bitcoin's performance, providing immediate insights.
On-chain Zscore | QuantumResearchQuantumResearch On-chain Zscore Indicator
The On-chain Zscore Indicator by QuantumResearch is a cutting-edge tool designed for traders and analysts who leverage on-chain metrics to assess Bitcoin’s market conditions. This indicator calculates a composite Z-score using three key on-chain metrics: NUPL (Net Unrealized Profit/Loss), SOPR (Spent Output Profit Ratio), and MVRV (Market Value to Realized Value). By normalizing these values through standard deviations, the indicator provides a dynamic, data-driven approach to identifying overbought and oversold conditions, improving market timing and decision-making.
1. Overview
This indicator integrates multiple on-chain metrics to:
Assess Market Cycles – Utilize Z-score normalization to detect potential tops and bottoms.
Smooth Volatility – Apply EMA and standard deviation filtering to refine signals.
Identify Buy & Sell Signals – Use adaptive thresholds to highlight market extremes.
Provide Visual Clarity – Color-coded bar signals and background fills for intuitive analysis.
2. How It Works
A. Z-score Calculation
What is a Z-score? – The Z-score measures how far a data point deviates from its historical mean in terms of standard deviations. This helps in identifying statistical extremes.
Zscore(source,mean,std)=>
zscore = (source-mean)/std
zscore
Standard Deviation Normalization – Each on-chain metric (NUPL, SOPR, MVRV) is individually standardized before being combined into a final score.
B. On-Chain Components
NUPL Z-score – Measures unrealized profits and losses relative to market cycles.
SOPR Z-score – Evaluates profit-taking behavior on spent outputs.
MVRV Z-score – Assesses whether Bitcoin is overvalued or undervalued based on market cap vs. realized cap.
C. Composite On-chain Score
The indicator computes an average Z-score of the three on-chain metrics to create a composite market assessment.
Adaptive thresholds (default: 0.73 for bullish signals, -0.44 for bearish signals) dynamically adjust based on market conditions.
3. Visual Representation
This indicator features color-coded elements and dynamic threshold visualization:
Bar Colors
Green Bars – Bullish conditions when Z-score exceeds the upper threshold.
Red Bars – Bearish conditions when Z-score drops below the lower threshold.
Gray Bars – Neutral market conditions.
Threshold Bands & Background Fill
Upper Band (Overbought) – Default threshold set at 0.73.
Middle Band – Neutral zone at 0.
Lower Band (Oversold) – Default threshold set at -0.44.
4. Customization & Parameters
This indicator is highly configurable, allowing traders to fine-tune settings based on their strategy:
On-Chain Z-score Settings
NUPL Z-score Length – Default: 126 periods
SOPR Z-score Length – Default: 111 periods
MVRV Z-score Length – Default: 111 periods
Signal Thresholds
Upper Threshold (Bullish Zone) – Default: 0.73
Lower Threshold (Bearish Zone) – Default: -0.44
Color & Visual Settings
Choose from eight customizable color modes to suit personal preferences.
5. Trading Applications
The On-chain Zscore Indicator is versatile and can be applied in various market scenarios:
Macro Trend Analysis – Identify long-term market tops and bottoms using normalized on-chain metrics.
Momentum Confirmation – Validate price action trends with SOPR & MVRV behavior.
Market Timing – Use deviation thresholds to enter at historically significant price zones.
Risk Management – Avoid overextended markets by watching for extreme Z-score readings.
6. Final Thoughts
The QuantumResearch On-chain Zscore Indicator provides a unique approach to market evaluation by combining three critical on-chain metrics into a single, normalized score.
By standardizing Bitcoin’s market behavior, this tool helps traders and investors make informed decisions based on historical statistical extremes.
Backtesting and validation are essential before using this indicator in live trading. While it enhances market analysis, it should be used alongside other tools and strategies.
Disclaimer: No indicator can guarantee future performance. Always use appropriate risk management and perform due diligence before trading.
