OBV with MA & Bollinger Bands by Marius1032OBV with MA & Bollinger Bands by Marius1032
This script adds customizable moving averages and Bollinger Bands to the classic OBV (On Balance Volume) indicator. It helps identify volume-driven momentum and trend strength.
Features:
OBV-based trend tracking
Optional smoothing: SMA, EMA, RMA, WMA, VWMA
Optional Bollinger Bands with SMA
Potential Combinations and Trading Strategies:
Breakouts: Look for price breakouts from the Bollinger Bands, and confirm with a rising OBV for an uptrend or falling OBV for a downtrend.
Trend Reversals: When the price touches a Bollinger Band, examine the OBV for divergence. A bullish divergence (price lower low, OBV higher low) near the lower band could signal a reversal.
Volume Confirmation: Use OBV to confirm the strength of the trend indicated by Bollinger Bands. For example, if the BBs indicate an uptrend and OBV is also rising, it reinforces the bullish signal.
1. On-Balance Volume (OBV):
Purpose: OBV is a momentum indicator that uses volume flow to predict price movements.
Calculation: Volume is added on up days and subtracted on down days.
Interpretation: Rising OBV suggests potential upward price movement. Falling OBV suggests potential lower prices.
Divergence: Divergence between OBV and price can signal potential trend reversals.
2. Moving Average (MA):
Purpose: Moving Averages smooth price fluctuations and help identify trends.
Combination with OBV: Pairing OBV with MAs helps confirm trends and identify potential reversals. A crossover of the OBV line and its MA can signal a trend reversal or continuation.
3. Bollinger Bands (BB):
Purpose: BBs measure market volatility and help identify potential breakouts and trend reversals.
Structure: They consist of a moving average (typically 20-period) and two standard deviation bands.
Combination with OBV: Combining BBs with OBV allows for a multifaceted approach to market analysis. For example, a stock hitting the lower BB with a rising OBV could indicate accumulation and a potential upward reversal.
Created by: Marius1032
ค้นหาในสคริปต์สำหรับ "Divergence"
Risk-Adjusted Momentum Oscillator# Risk-Adjusted Momentum Oscillator (RAMO): Momentum Analysis with Integrated Risk Assessment
## 1. Introduction
Momentum indicators have been fundamental tools in technical analysis since the pioneering work of Wilder (1978) and continue to play crucial roles in systematic trading strategies (Jegadeesh & Titman, 1993). However, traditional momentum oscillators suffer from a critical limitation: they fail to account for the risk context in which momentum signals occur. This oversight can lead to significant drawdowns during periods of market stress, as documented extensively in the behavioral finance literature (Kahneman & Tversky, 1979; Shefrin & Statman, 1985).
The Risk-Adjusted Momentum Oscillator addresses this gap by incorporating real-time drawdown metrics into momentum calculations, creating a self-regulating system that automatically adjusts signal sensitivity based on current risk conditions. This approach aligns with modern portfolio theory's emphasis on risk-adjusted returns (Markowitz, 1952) and reflects the sophisticated risk management practices employed by institutional investors (Ang, 2014).
## 2. Theoretical Foundation
### 2.1 Momentum Theory and Market Anomalies
The momentum effect, first systematically documented by Jegadeesh & Titman (1993), represents one of the most robust anomalies in financial markets. Subsequent research has confirmed momentum's persistence across various asset classes, time horizons, and geographic markets (Fama & French, 1996; Asness, Moskowitz & Pedersen, 2013). However, momentum strategies are characterized by significant time-varying risk, with particularly severe drawdowns during market reversals (Barroso & Santa-Clara, 2015).
### 2.2 Drawdown Analysis and Risk Management
Maximum drawdown, defined as the peak-to-trough decline in portfolio value, serves as a critical risk metric in professional portfolio management (Calmar, 1991). Research by Chekhlov, Uryasev & Zabarankin (2005) demonstrates that drawdown-based risk measures provide superior downside protection compared to traditional volatility metrics. The integration of drawdown analysis into momentum calculations represents a natural evolution toward more sophisticated risk-aware indicators.
### 2.3 Adaptive Smoothing and Market Regimes
The concept of adaptive smoothing in technical analysis draws from the broader literature on regime-switching models in finance (Hamilton, 1989). Perry Kaufman's Adaptive Moving Average (1995) pioneered the application of efficiency ratios to adjust indicator responsiveness based on market conditions. RAMO extends this concept by incorporating volatility-based adaptive smoothing, allowing the indicator to respond more quickly during high-volatility periods while maintaining stability during quiet markets.
## 3. Methodology
### 3.1 Core Algorithm Design
The RAMO algorithm consists of several interconnected components:
#### 3.1.1 Risk-Adjusted Momentum Calculation
The fundamental innovation of RAMO lies in its risk adjustment mechanism:
Risk_Factor = 1 - (Current_Drawdown / Maximum_Drawdown × Scaling_Factor)
Risk_Adjusted_Momentum = Raw_Momentum × max(Risk_Factor, 0.05)
This formulation ensures that momentum signals are dampened during periods of high drawdown relative to historical maximums, implementing an automatic risk management overlay as advocated by modern portfolio theory (Markowitz, 1952).
#### 3.1.2 Multi-Algorithm Momentum Framework
RAMO supports three distinct momentum calculation methods:
1. Rate of Change: Traditional percentage-based momentum (Pring, 2002)
2. Price Momentum: Absolute price differences
3. Log Returns: Logarithmic returns preferred for volatile assets (Campbell, Lo & MacKinlay, 1997)
This multi-algorithm approach accommodates different asset characteristics and volatility profiles, addressing the heterogeneity documented in cross-sectional momentum studies (Asness et al., 2013).
### 3.2 Leading Indicator Components
#### 3.2.1 Momentum Acceleration Analysis
The momentum acceleration component calculates the second derivative of momentum, providing early signals of trend changes:
Momentum_Acceleration = EMA(Momentum_t - Momentum_{t-n}, n)
This approach draws from the physics concept of acceleration and has been applied successfully in financial time series analysis (Treadway, 1969).
#### 3.2.2 Linear Regression Prediction
RAMO incorporates linear regression-based prediction to project momentum values forward:
Predicted_Momentum = LinReg_Value + (LinReg_Slope × Forward_Offset)
This predictive component aligns with the literature on technical analysis forecasting (Lo, Mamaysky & Wang, 2000) and provides leading signals for trend changes.
#### 3.2.3 Volume-Based Exhaustion Detection
The exhaustion detection algorithm identifies potential reversal points by analyzing the relationship between momentum extremes and volume patterns:
Exhaustion = |Momentum| > Threshold AND Volume < SMA(Volume, 20)
This approach reflects the established principle that sustainable price movements require volume confirmation (Granville, 1963; Arms, 1989).
### 3.3 Statistical Normalization and Robustness
RAMO employs Z-score normalization with outlier protection to ensure statistical robustness:
Z_Score = (Value - Mean) / Standard_Deviation
Normalized_Value = max(-3.5, min(3.5, Z_Score))
This normalization approach follows best practices in quantitative finance for handling extreme observations (Taleb, 2007) and ensures consistent signal interpretation across different market conditions.
### 3.4 Adaptive Threshold Calculation
Dynamic thresholds are calculated using Bollinger Band methodology (Bollinger, 1992):
Upper_Threshold = Mean + (Multiplier × Standard_Deviation)
Lower_Threshold = Mean - (Multiplier × Standard_Deviation)
This adaptive approach ensures that signal thresholds adjust to changing market volatility, addressing the critique of fixed thresholds in technical analysis (Taylor & Allen, 1992).
## 4. Implementation Details
### 4.1 Adaptive Smoothing Algorithm
The adaptive smoothing mechanism adjusts the exponential moving average alpha parameter based on market volatility:
Volatility_Percentile = Percentrank(Volatility, 100)
Adaptive_Alpha = Min_Alpha + ((Max_Alpha - Min_Alpha) × Volatility_Percentile / 100)
This approach ensures faster response during volatile periods while maintaining smoothness during stable conditions, implementing the adaptive efficiency concept pioneered by Kaufman (1995).
### 4.2 Risk Environment Classification
RAMO classifies market conditions into three risk environments:
- Low Risk: Current_DD < 30% × Max_DD
- Medium Risk: 30% × Max_DD ≤ Current_DD < 70% × Max_DD
- High Risk: Current_DD ≥ 70% × Max_DD
This classification system enables conditional signal generation, with long signals filtered during high-risk periods—a approach consistent with institutional risk management practices (Ang, 2014).
## 5. Signal Generation and Interpretation
### 5.1 Entry Signal Logic
RAMO generates enhanced entry signals through multiple confirmation layers:
1. Primary Signal: Crossover between indicator and signal line
2. Risk Filter: Confirmation of favorable risk environment for long positions
3. Leading Component: Early warning signals via acceleration analysis
4. Exhaustion Filter: Volume-based reversal detection
This multi-layered approach addresses the false signal problem common in traditional technical indicators (Brock, Lakonishok & LeBaron, 1992).
### 5.2 Divergence Analysis
RAMO incorporates both traditional and leading divergence detection:
- Traditional Divergence: Price and indicator divergence over 3-5 periods
- Slope Divergence: Momentum slope versus price direction
- Acceleration Divergence: Changes in momentum acceleration
This comprehensive divergence analysis framework draws from Elliott Wave theory (Prechter & Frost, 1978) and momentum divergence literature (Murphy, 1999).
## 6. Empirical Advantages and Applications
### 6.1 Risk-Adjusted Performance
The risk adjustment mechanism addresses the fundamental criticism of momentum strategies: their tendency to experience severe drawdowns during market reversals (Daniel & Moskowitz, 2016). By automatically reducing position sizing during high-drawdown periods, RAMO implements a form of dynamic hedging consistent with portfolio insurance concepts (Leland, 1980).
### 6.2 Regime Awareness
RAMO's adaptive components enable regime-aware signal generation, addressing the regime-switching behavior documented in financial markets (Hamilton, 1989; Guidolin, 2011). The indicator automatically adjusts its parameters based on market volatility and risk conditions, providing more reliable signals across different market environments.
### 6.3 Institutional Applications
The sophisticated risk management overlay makes RAMO particularly suitable for institutional applications where drawdown control is paramount. The indicator's design philosophy aligns with the risk budgeting approaches used by hedge funds and institutional investors (Roncalli, 2013).
## 7. Limitations and Future Research
### 7.1 Parameter Sensitivity
Like all technical indicators, RAMO's performance depends on parameter selection. While default parameters are optimized for broad market applications, asset-specific calibration may enhance performance. Future research should examine optimal parameter selection across different asset classes and market conditions.
### 7.2 Market Microstructure Considerations
RAMO's effectiveness may vary across different market microstructure environments. High-frequency trading and algorithmic market making have fundamentally altered market dynamics (Aldridge, 2013), potentially affecting momentum indicator performance.
### 7.3 Transaction Cost Integration
Future enhancements could incorporate transaction cost analysis to provide net-return-based signals, addressing the implementation shortfall documented in practical momentum strategy applications (Korajczyk & Sadka, 2004).
## References
Aldridge, I. (2013). *High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems*. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Ang, A. (2014). *Asset Management: A Systematic Approach to Factor Investing*. New York: Oxford University Press.
Arms, R. W. (1989). *The Arms Index (TRIN): An Introduction to the Volume Analysis of Stock and Bond Markets*. Homewood, IL: Dow Jones-Irwin.
Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. *Journal of Finance*, 68(3), 929-985.
Barroso, P., & Santa-Clara, P. (2015). Momentum has its moments. *Journal of Financial Economics*, 116(1), 111-120.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. New York: McGraw-Hill.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. *Journal of Finance*, 47(5), 1731-1764.
Calmar, T. (1991). The Calmar ratio: A smoother tool. *Futures*, 20(1), 40.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). *The Econometrics of Financial Markets*. Princeton, NJ: Princeton University Press.
Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. *International Journal of Theoretical and Applied Finance*, 8(1), 13-58.
Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. *Journal of Financial Economics*, 122(2), 221-247.
Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. *Journal of Finance*, 51(1), 55-84.
Granville, J. E. (1963). *Granville's New Key to Stock Market Profits*. Englewood Cliffs, NJ: Prentice-Hall.
Guidolin, M. (2011). Markov switching models in empirical finance. In D. N. Drukker (Ed.), *Missing Data Methods: Time-Series Methods and Applications* (pp. 1-86). Bingley: Emerald Group Publishing.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. *Econometrica*, 57(2), 357-384.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. *Journal of Finance*, 48(1), 65-91.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. *Econometrica*, 47(2), 263-291.
Kaufman, P. J. (1995). *Smarter Trading: Improving Performance in Changing Markets*. New York: McGraw-Hill.
Korajczyk, R. A., & Sadka, R. (2004). Are momentum profits robust to trading costs? *Journal of Finance*, 59(3), 1039-1082.
Leland, H. E. (1980). Who should buy portfolio insurance? *Journal of Finance*, 35(2), 581-594.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. *Journal of Finance*, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. *Journal of Finance*, 7(1), 77-91.
Murphy, J. J. (1999). *Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications*. New York: New York Institute of Finance.
Prechter, R. R., & Frost, A. J. (1978). *Elliott Wave Principle: Key to Market Behavior*. Gainesville, GA: New Classics Library.
Pring, M. J. (2002). *Technical Analysis Explained: The Successful Investor's Guide to Spotting Investment Trends and Turning Points*. 4th ed. New York: McGraw-Hill.
Roncalli, T. (2013). *Introduction to Risk Parity and Budgeting*. Boca Raton, FL: CRC Press.
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. *Journal of Finance*, 40(3), 777-790.
Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable*. New York: Random House.
Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. *Journal of International Money and Finance*, 11(3), 304-314.
Treadway, A. B. (1969). On rational entrepreneurial behavior and the demand for investment. *Review of Economic Studies*, 36(2), 227-239.
Wilder, J. W. (1978). *New Concepts in Technical Trading Systems*. Greensboro, NC: Trend Research.
Demand Index (Hybrid Sibbet) by TradeQUODemand Index (Hybrid Sibbet) by TradeQUO \
\Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\Calculation\
\
\ \Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\Interpretation\
\
\ \Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\Usage Notes & Warnings\
\
\ \Never Use DI in Isolation\
It is a \filter\ and \confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \Parameter Selection\
• \Vol EMA length (n₁)\: Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \Buy/Sell EMA length (n₂)\: Typically 2 bars for fast smoothing.
• \DI smoothing (n₃)\: Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
Aggregated Spot vs Perp Volume (% Change)Aggregated Spot vs Perp Volume (% Change)
Description
The "Aggregated Spot vs Perp Volume (% Change)" indicator helps crypto traders compare the momentum of spot and perpetual futures (perp) trading volumes across 12 major exchanges. It calculates the percentage change in volume from one bar to the next, highlighting divergences and showing which market—spot or perp—is leading a move. By focusing on relative changes, it eliminates the issue of absolute volume differences, making trends clear.
The indicator aggregates data from Binance, Bybit, OKX, Coinbase, Bitget, MEXC, Phemex, BingX, WhiteBIT, BitMEX, Kraken, and HTX. Users can toggle exchanges and choose to measure volume in coin units (e.g., BTC) or USD.
How It Works
Volume Aggregation:
Fetches spot and perp volume data for the selected crypto (e.g., BTC) from up to 12 exchanges.
Spot volume is included only if perp volume is available for the same pair, ensuring consistency.
Volume can be measured in coin units or USD (volume × spot price).
Percentage Change:
Calculates the percentage change in spot and perp volumes from the previous bar:
Percentage Change = ((Current Volume − Previous Volume) / Previous Volume) ×100
This focuses on relative momentum, making spot and perp volumes directly comparable.
Visualization:
Spot volume % change is plotted as a blue line, and perp volume % change as a red line, both with a linewidth of 1.
Who Should Use It
Crypto Traders: To understand spot vs. perp market dynamics across exchanges.
Momentum Traders: To spot which market is driving price moves via volume divergences.
Scalpers/Day Traders: For identifying short-term shifts in market activity.
Analysts: To study liquidity and sentiment in crypto markets.
How to Use It
Blue line: Spot volume % change.
Red line: Perp volume % change.
Look for divergences (e.g., a sharp rise in the red line but not the blue line suggests perp markets are leading).
Combine with Price:
Use alongside price charts to confirm trends or spot potential reversals.
Context
Spot markets reflect actual asset trading, while perp markets, with leverage, attract speculative activity and often show higher volumes. This indicator uses percentage change to compare their momentum, helping traders identify market leadership and divergences. For example, a 50% increase in both spot and perp volumes plots at the same level, making it easy to see relative shifts across exchanges.
[blackcat] L2 Enhanced MACD Trend█ OVERVIEW
The Enhanced MACD Trend script combines traditional Moving Average Convergence Divergence (MACD) analysis with On-Balance Volume (OBV) insights to provide traders with a comprehensive understanding of market trends. By examining both price momentum and volume fluctuations, this tool aids in identifying potential upward or downward market transitions.
█ LOGICAL FRAMEWORK
Initially, the script prompts users to configure fundamental parameters such as the speed of moving averages. It subsequently utilizes a specialized auxiliary function named calculate_macd_obv_signals to perform intricate computations. This function calculates the discrepancy between two distinct types of moving averages (captured via MACD analysis), evaluates the direction of capital inflows and outflows within securities (using OBV), and applies smoothing techniques to mitigate undue influence from minor fluctuations. Ultimately, visual representations of these calculations are rendered on an additional chart pane for enhanced interpretability.
█ CUSTOM FUNCTIONS
Function: calculate_macd_obv_signals
• Purpose: Determines critical aspects associated with MACD and OBV.
• Parameters:
• fastLength (int): Dictates the responsiveness of the shorter Exponential Moving Average (EMA) to price variations.
• slowLength (int): Specifies the reactivity of the longer EMA.
• signalSmoothing (int): Defines the degree of smoothness applied to the divergence between EMAs.
• Functionality:
• macd_diff: Illustrates whether price increases have accelerated relative to previous levels or decelerated, providing insight into existing momentum.
• macd_signal_line: Smoothens macd_diff values, serving akin to a trailing indicator for macd_diff.
• macd_histogram: Visually accentuates disparities between macd_diff and macd_signal_line employing color-coded bars, facilitating identification of significant divergences.
• obv_signal: Represents a refined variant of short-term OBV concentrating solely on periods characterized by elevated buying interest, aiding in reduction of extraneous signals.
• moving_average_short: Analyzes recent closing prices across several sessions to corroborate burgeoning bullish or bearish tendencies.
• Returns: An array encompassing .
█ KEY POINTS AND TECHNIQUES
Advanced Features: Employs sophisticated functions including ta.ema() and ta.sma(), enabling accurate calculation of EMAs and SMAs respectively, thus enhancing precision in trend detection.
Optimization Techniques: Incorporates customizable inputs (input.int) permitting strategic adjustments alongside scrutiny of escalating or declining volumes to accurately gauge genuine sentiment shifts while discounting insignificant anomalies.
Best Practices: Maintains separation between algorithmic processes and graphical outputs, preserving organizational clarity; hence simplifying debugging efforts and future enhancements.
Unique Approaches: Integrates multifaceted assessments simultaneously – amalgamating candlestick formations and volumetric activities – offering a holistic perspective instead of reliance on singular indicators. Consequently, delivers astute recommendations grounded in diverse analytical underpinnings rather than speculative forecasts.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential Modifications:
1 — Implement automated alert mechanisms signaling crossover events pinpointing optimal buy/sell junctures to fine-tune timing preemptively minimizing losses proactively.
2 — Enable user customization of sensitivity criteria governing trigger intensity thereby eliminating trivial aberrations and emphasizing substantial patterns exclusively.
Application Scenarios:
Beneficial for high-frequency trading aiming to capitalize on fleeting price movements swiftly. Suitable for dynamic environments necessitating rapid responses due to frequent market volatility demanding prompt reactions. Perfect for individuals engaging in regular transactions seeking unparalleled accuracy navigating fluctuating circumstances ensuring consistent profitability amidst disturbances maintaining steady yields irrespective of upheavals.
Related Concepts:
Contemplate interactions among oscillators (such as MACD) and volume metrics detecting instances wherein they oppose each other (indicative of divergences) or concur (signaling crossovers). Profound comprehension of these interrelationships substantially refines trading strategies integrating broader economic factors, seasonal influences guiding overarching plans resulting in heightened predictive capabilities elevating trading effectiveness leveraging cumulative information transforming unprocessed statistics into actionable intelligence empowering informed decisions advancing confidently toward objectives effortlessly scaling achievements seamlessly realizing aspirations effortlessly.
faiz MACDMACD: Moving Average Convergence Divergence
The Moving Average Convergence Divergence (MACD) is a popular momentum indicator used in technical analysis to gauge the strength, direction, and potential reversal points of a trend in a financial asset's price movement. Developed by Gerald Appel in the late 1970s, MACD is particularly favored by traders for its ability to capture both trend-following and momentum aspects of price behavior.
Components of the MACD
The MACD is derived from two exponential moving averages (EMAs) of a security's price:
MACD Line: This is the difference between the 12-day and 26-day EMAs. The shorter 12-day EMA reacts more quickly to price changes, while the 26-day EMA smooths out price fluctuations, offering a longer-term perspective.
Formula: MACD Line = 12-day EMA - 26-day EMA
Signal Line: This is the 1-day EMA of the MACD Line itself. The signal line is used to generate buy and sell signals when it crosses the MACD line.
Formula: Signal Line = 1-day EMA of the MACD Line
MACD Histogram: The histogram represents the difference between the MACD Line and the Signal Line. It is displayed as bars that oscillate above and below a zero line, helping to visualize the convergence or divergence between the two lines.
Formula: Histogram = MACD Line - Signal Line
Interpretation of MACD
The MACD indicator is used to identify potential buy and sell signals based on the following observations:
MACD Line and Signal Line Crossovers:
Bullish Crossover: A buy signal occurs when the MACD Line crosses above the Signal Line. This suggests that the momentum is shifting in favor of the bulls, indicating a potential upward price movement.
Bearish Crossover: A sell signal occurs when the MACD Line crosses below the Signal Line. This suggests a bearish trend may be emerging, signaling a potential downward movement.
Divergence:
Bullish Divergence: Occurs when the price of the asset is making new lows, but the MACD is forming higher lows. This suggests that the downward momentum is weakening and a potential reversal to the upside may be imminent.
Bearish Divergence: Occurs when the price is making new highs, but the MACD is forming lower highs. This suggests that the upward momentum is weakening and a reversal to the downside may occur.
Only use it in timeframe m1, and solely use for XAUUSD pair.
Advisable to use it as a confirmation with other indicator such as
BBMA, SMC, SUPPORT RESISTANCE, SUPPLY AND DEMAND.
how to use :
MA 5 Crossing above MA9, will generate BUY signals
MA 5 Crossing below MA9, will generate SELL signals
Trade at your own SKILLS.
I dont mind people using this script for free.
All I want is just prayer for me and my family success.
Thank You and Have a nice and pleasant day :-)
Atareum Volume Ichimuku CandleAVIC (Atareum Volume Ichimoku Candles) is clearly an awesome indicator that is based on Ichimoku concepts by combination with volume. This is a new approach of volume candles that is combined with Ichimoku concepts and creates such a powerful tool to trace the market and assists traders to make better decisions, truly.
Concept:
Using Ichimoku leading periods and calculations on redesigning new candles in combination with volume, that makes unique reform candles on Tenkansen movement, but these new candles clearly omit noises in combination with volume, and then the new redesigned system of cloud calculations builds, new series of data for Senko Span A and Senko Span B which is so odd in first view, because they will barely ever cross each other, but they show very more informative and useful.
Parameters:
Section 1 : Candle colour setting for flourishing just as you desire !
Section 2 : Defining Periods of standard Ichimoku and source of candle data in combination with determining the smoothing type of moving averages and signal period.
Section 3 : Select using Heikin Ashi based candles alongside with redesigned cloud calculation type and three additional moving averages which can plot on each newly generated candles and standard candles on a chart with the type mode defined in the previous section.
Note: if you want to omit any or all of these moving averages, you can use 0 in period, instead of selecting "None" in the plot moving option!
Usage :
Overall:
Regardless of the additional moving averages which will lead to so many situations of market according to their types and designs, that is four different period for new redesign AVIC and three period for standard chart. You can easily select periods and type for these moving averages. Also, do not forget that signal moving averages is shown only on AVIC chart and have two different colour for upward and downward trends. Other moving averages are plot by just one single colour.
Cloud levels are so important because AVIC candles show respect to them and when they break the clouds upward or downward it's surly beginning of a trend that is may last long. Also when cloud levels flatten, it is determining a support or resistance according to up cloud or down cloud nature and as long as they will continue or repeated periodically on same level of AVIC chart, it will implement their weakness or strength.
Support and Resistance:
Any flattens of cloud up or down level means the support or resistance level due to its nature, but important thing is how long the cloud lasts flatten or how many times repeated in the same level in AVIC chart.
For plotting the support or resistance you should trace first candle of start of flattens in standard chart just like following picture.
Divergence:
All Higher high or Lower low of standard chart has its reflect in AVIC chart but there is secret in it, It is named divergence. When standard chart price candles generating lower low but the AVIC chart candles do not cross the bottom, it means we will spike high as soon as AVIC candle chart complete its divergence. You can see perfect example in following picture.
Cloud level Ends
When cloud down level become flattens and cloud up level start a bull run it means we will face a great up trend movement but as soon as cloud down level starts to move up it mean we are going to finish the bull run and maybe it goes with consolidation phase or reversal phase. This reaction is exactly happen in vice versa for bear run trend. You can see both examples in following pictures.
Note: if we face end of bull run and cloud down level make a U turn shape upside down it means we will have reversal phase even not too long but it is sharp and fast reversal. If cloud down level just turn right slightly, it means we should have consolidation phase, mostly or we can continue the last trend slightly. All these situations can happen in vice versa bear run. You can see example in following picture.
Signals:
Long but risky:
You can go long when AVIC candles are green and be in position as long as they are not change in colour.
Long and safe :
You can go long when AVIC candles cross up cloud down level and be in position as long as AVIC candles cross down cloud up level.
Long and sure:
You can go long when AVIC candles cross up cloud up level and be in position as long as AVIC candles cross down cloud down level.
Short but risky:
You can go short when AVIC candles are red and be in position as long as they are not change in colour.
Short and safe :
You can go short when AVIC candles cross down cloud up level and be in position as long as AVIC candles cross up cloud down level.
Short and sure:
You can go short when AVIC candles cross down cloud down level and be in position as long as AVIC candles cross up cloud up level.
Notice : Candles with large body are so strong but if a body candle is weak or flatten it may a signal of changing colour and direction, especially when using Heikin Ashi type.
It is the result of many years of experience in markets and there are so many details about this AVIC chart which I am in the experiment phase to publish in the future, so please help me with your ideas and do not hesitate to comment and inform me any suggestions or criticism.
Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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Market Sentiment Technicals [LuxAlgo]The Market Sentiment Technicals indicator synthesizes insights from diverse technical analysis techniques, including price action market structures, trend indicators, volatility indicators, momentum oscillators, and more.
The indicator consolidates the evaluated outputs from these techniques into a singular value and presents the combined data through an oscillator format, technical rating, and a histogram panel featuring the sentiment of each component alongside the overall sentiment.
🔶 USAGE
The Market Sentiment Technicals indicator is a tool able to swiftly and easily gauge market sentiment by consolidating the individual sentiment from multiple technical analysis techniques applied to market data into a single value, allowing users to asses if the market is uptrending, consolidating, or downtrending.
The tool includes various components and presentation formats, each described in the sub-sections below.
🔹Indicators Sentiment Panel
The indicators sentiment panel provides normalized sentiment scores for each supported indicator, along with a synthesized representation derived from the average of all individual normalized sentiments.
🔹Market Sentiment Meter
The market sentiment meter is obtained from the synthesized representation derived from the average of all individual normalized sentiments. It allows users to quickly and easily gauge the overall market sentiment.
🔹Market Sentiment Oscillator
The market sentiment oscillator provides a visual means to monitor the current and historical strength of the market. It assists in identifying the trend direction, trend momentum, and overbought and oversold conditions, aiding in the anticipation of potential trend reversals.
Divergence occurs when there is a difference between what the price action is indicating and what the market sentiment oscillator is indicating, helping traders assess changes in the price trend.
🔶 DETAILS
The indicator employs a range of technical analysis techniques to interpret market data. Each group of indicators provides valuable insights into different aspects of market behavior.
🔹Momentum Indicators
Momentum indicators assess the speed and change of price movements, often indicating whether a trend is strengthening or weakening.
Relative Strength Index (RSI): Measures the magnitude of recent price changes to evaluate overbought or oversold conditions.
Stochastic %K: Compares the closing price to the range over a specified period to identify potential reversal points.
Stochastic RSI Fast: Combines features of Stochastic oscillators and RSI to gauge both momentum and overbought/oversold levels efficiently.
Commodity Channel Index (CCI): Measures the deviation of an asset's price from its statistical average to determine trend strength and overbought and oversold conditions.
Bull Bear Power: Evaluates the strength of buying and selling pressure in the market.
🔹Trend Indicators
Trend indicators help traders identify the direction of a market trend.
Moving Averages: Provides a smoothed representation of the underlying price data, aiding in trend identification and analysis.
Bollinger Bands: Consists of a middle band (typically a simple moving average) and upper and lower bands, which represent volatility levels of the market.
Supertrend: A trailing stop able to identify the current direction of the trend.
Linear Regression: Fits a straight line to past data points to predict future price movements and identify trend direction.
🔹Market Structures
Market Structures: Analyzes the overall pattern of price movements, including Break of Structure (BOS), Market Structure Shifts (MSS), also referred to as Change of Character (CHoCH), aiding in identifying potential market turning and continuation points.
🔹The Normalization Technique
The normalization technique employed for trend indicators relies on buy-sell signals. The script tracks price movements and normalizes them based on these signals.
normalize(buy, sell, smooth)=>
var os = 0
var float max = na
var float min = na
os := buy ? 1 : sell ? -1 : os
max := os > os ? close : os < os ? max : math.max(close, max)
min := os < os ? close : os > os ? min : math.min(close, min)
ta.sma((close - min)/(max - min), smooth) * 100
In this Pine Script snippet:
The variable os tracks market sentiment, taking a value of 1 for buy signals and -1 for sell signals, indicating bullish and bearish sentiments, respectively.
max and min are used to identify extremes in sentiment and are updated based on changes in os . When market sentiment shifts from buying to selling (or vice versa), max and min adjust accordingly.
Normalization is achieved by comparing current price levels to historical extremes in sentiment. The result is smoothed by default using a 3-period simple moving average. Users have the option to customize the smoothing period via the script settings input menu.
🔶 SETTINGS
🔹Generic Settings
Timeframe: This option selects the timeframe for calculating sentiment. If a timeframe lower than the chart's is chosen, calculations will be based on the chart's timeframe.
Horizontal Offset: Determines the distance at which the visual components of the indicator will be displayed from the primary chart.
Gradient Colors: Allows customization of gradient colors.
🔹Indicators Sentiment Panel
Indicators Sentiment Panel: Toggle the visibility of the indicators sentiment panel.
Panel Height: Determines the height of the panel.
🔹Market Sentiment Meter
Market Sentiment Meter: Toggle the visibility of the market sentiment meter (technical ratings in the shape of a speedometer).
🔹Market Sentiment Oscillator
Market Sentiment Oscillator: Toggle the visibility of the market sentiment oscillator.
Show Divergence: Enables detection of divergences based on the selected option.
Oscillator Line Width: Customization option for the line width.
Oscillator Height: Determines the height of the oscillator.
🔹Settings for Individual Components
In general,
Source: Determines the data source for calculations.
Length: The period to be used in calculations.
Smoothing: Degree of smoothness of the evaluated values.
🔹Normalization Settings - Trend Indicators
Smoothing: The period used in smoothing normalized values, where normalization is applied to moving averages, Bollinger Bands, Supertrend, VWAP bands, and market structures.
🔶 LIMITATIONS
Like any technical analysis tool, the Market Sentiment Technicals indicator has limitations. It's based on historical data and patterns, which may not always accurately predict future market movements. Additionally, market sentiment can be influenced by various factors, including economic news, geopolitical events, and market psychology, which may not be fully captured by technical analysis alone.
Delta Volume Channels [LucF]█ OVERVIEW
This indicator displays on-chart visuals aimed at making the most of delta volume information. It can color bars and display two channels: one for delta volume, another calculated from the price levels of bars where delta volume divergences occur. Markers and alerts can also be configured using key conditions, and filtered in many different ways. The indicator caters to traders who prefer chart visuals over raw values. It will work on historical bars and in real time, using intrabar analysis to calculate delta volume in both conditions.
█ CONCEPTS
Delta Volume
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest techniques use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which usually limits the historical depth of charts and the number of symbols for which tick data is available.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. In the context where historical tick data is not yet available on TradingView, intrabar analysis is the most precise technique to calculate volume delta on historical bars on our charts. TradingView's Volume Profile built-in indicators use it, as do the CVD - Cumulative Volume Delta Candles and CVD - Cumulative Volume Delta (Chart) indicators published from the TradingView account . My Volume Delta Columns Pro indicator also uses intrabar analysis. Other volume delta indicators such as my Realtime 5D Profile use realtime chart updates to achieve more precise volume delta calculations. Indicators of that type cannot be used on historical bars however; they only work in real time.
This is the logic I use to assign intrabar volume to up or down slots:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added and the down volumes subtracted. The resulting value is volume delta for that chart bar, which can be used as an estimate of the buying/selling pressure on an instrument.
Delta Volume Percent (DV%)
This value is the proportion that delta volume represents of the total intrabar volume in the chart bar. Note that on some symbols/timeframes, the total intrabar volume may differ from the chart's volume for a bar, but that will not affect our calculations since we use the total intrabar volume.
Delta Volume Channel
The DV channel is the space between two moving averages: the reference line and a DV%-weighted version of that reference. The reference line is a moving average of a type, source and length which you select. The DV%-weighted line uses the same settings, but it averages the DV%-weighted price source.
The weight applied to the source of the reference line is calculated from two values, which are multiplied: DV% and the relative size of the bar's volume in relation to previous bars. The effect of this is that DV% values on bars with higher total volume will carry greater weight than those with lesser volume.
The DV channel can be in one of four states, each having its corresponding color:
• Bull (teal): The DV%-weighted line is above the reference line.
• Strong bull (lime): The bull condition is fulfilled and the bar's close is above the reference line and both the reference and the DV%-weighted lines are rising.
• Bear (maroon): The DV%-weighted line is below the reference line.
• Strong bear (pink): The bear condition is fulfilled and the bar's close is below the reference line and both the reference and the DV%-weighted lines are falling.
Divergences
In the context of this indicator, a divergence is any bar where the slope of the reference line does not match that of the DV%-weighted line. No directional bias is assigned to divergences when they occur.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's low and high ) saved when divergences occur. When price has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Prices breaches of the divergence channel will change its state. Divergence channels can be in one of five different states:
• Bull (teal): Price has breached the channel to the upside.
• Strong bull (lime): The bull condition is fulfilled and the DV channel is in the strong bull state.
• Bear (maroon): Price has breached the channel to the downside.
• Strong bear (pink): The bear condition is fulfilled and the DV channel is in the strong bear state.
• Neutral (gray): The channel has not been breached.
█ HOW TO USE THE INDICATOR
Load the indicator on an active chart (see here if you don't know how).
The default configuration displays:
• The DV channel, without the reference or DV%-weighted lines.
• The Divergence channel, without its level lines.
• Bar colors using the state of the DV channel.
The default settings use an Arnaud-Legoux moving average on the close and a length of 20 bars. The DV%-weighted version of it uses a combination of DV% and relative volume to calculate the ultimate weight applied to the reference. The DV%-weighted line is capped to 5 standard deviations of the reference. The lower timeframe used to access intrabars automatically adjusts to the chart's timeframe and achieves optimal balance between the number of intrabars inspected in each chart bar, and the number of chart bars covered by the script's calculations.
The Divergence channel's levels are determined using the high and low of the bars where divergences occur. Breaches of the channel require a bar's low to move above the top of the channel, and the bar's high to move below the channel's bottom.
No markers appear on the chart; if you want to create alerts from this script, you will need first to define the conditions that will trigger the markers, then create the alert, which will trigger on those same conditions.
To learn more about how to use this indicator, you must understand the concepts it uses and the information it displays, which requires reading this description. There are no videos to explain it.
█ FEATURES
The script's inputs are divided in four sections: "DV channel", "Divergence channel", "Other Visuals" and "Marker/Alert Conditions". The first setting is the selection method used to determine the intrabar precision, i.e., how many lower timeframe bars (intrabars) are examined in each chart bar. The more intrabars you analyze, the more precise the calculation of DV% results will be, but the less chart coverage can be covered by the script's calculations.
DV Channel
Here, you control the visibility and colors of the reference line, its weighted version, and the DV channel between them.
You also specify what type of moving average you want to use as a reference line, its source and length. This acts as the DV channel's baseline. The DV%-weighted line is also a moving average of the same type and length as the reference line, except that it will be calculated from the DV%-weighted source used in the reference line. By default, the DV%-weighted line is capped to five standard deviations of the reference line. You can change that value here. This section is also where you can disable the relative volume component of the weight.
Divergence Channel
This is where you control the appearance of the divergence channel and the key price values used in determining the channel's levels and breaching conditions. These choices have an impact on the behavior of the channel. More generous level prices like the default low and high selection will produce more conservative channels, as will the default choice for breach prices.
In this section, you can also enable a mode where an attempt is made to estimate the channel's bias before price breaches the channel. When it is enabled, successive increases/decreases of the channel's top and bottom levels are counted as new divergences occur. When one count is greater than the other, a bull/bear bias is inferred from it.
Other Visuals
You specify here:
• The method used to color chart bars, if you choose to do so.
• The display of a mark appearing above or below bars when a divergence occurs.
• If you want raw values to appear in tooltips when you hover above chart bars. The default setting does not display them, which makes the script faster.
• If you want to display an information box which by default appears in the lower left of the chart.
It shows which lower timeframe is used for intrabars, and the average number of intrabars per chart bar.
Marker/Alert Conditions
Here, you specify the conditions that will trigger up or down markers. The trigger conditions can include a combination of state transitions of the DV and the divergence channels. The triggering conditions can be filtered using a variety of conditions.
Configuring the marker conditions is necessary before creating an alert from this script, as the alert will use the marker conditions to trigger.
Markers only appear on bar closes, so they will not repaint. Keep in mind, when looking at markers on historical bars, that they are positioned on the bar when it closes — NOT when it opens.
Raw values
The raw values calculated by this script can be inspected using a tooltip and the Data Window. The tooltip is visible when you hover over the top of chart bars. It will display on the last 500 bars of the chart, and shows the values of DV, DV%, the combined weight, and the intermediary values used to calculate them.
█ INTERPRETATION
The aim of the DV channel is to provide a visual representation of the buying/selling pressure calculated using delta volume. The simplest characteristic of the channel is its bull/bear state. One can then distinguish between its bull and strong bull states, as transitions from strong bull to bull states will generally happen when buyers are losing steam. While one should not infer a reversal from such transitions, they can be a good place to tighten stops. Only time will tell if a reversal will occur. One or more divergences will often occur before reversals.
The nature of the divergence channel's design makes it particularly adept at identifying consolidation areas if its settings are kept on the conservative side. A gray divergence channel should usually be considered a no-trade zone. More adventurous traders can use the DV channel to orient their trade entries if they accept the risk of trading in a neutral divergence channel, which by definition will not have been breached by price.
If your charts are already busy with other stuff you want to hold on to, you could consider using only the chart bar coloring component of this indicator:
At its simplest, one way to use this indicator would be to look for overlaps of the strong bull/bear colors in both the DV channel and a divergence channel, as these identify points where price is breaching the divergence channel when buy/sell pressure is consistent with the direction of the breach. I have highlighted all those points in the chart below. Not all of them would have produced profitable trades, but nothing is perfect in the markets. Also, keep in mind that the circles identify the visual you would be looking for — not the trade's entry level.
█ LIMITATIONS
• The script will not work on symbols where no volume is available. An error will appear when that is the case.
• Because a maximum of 100K intrabars can be analyzed by a script, a compromise is necessary between the number of intrabars analyzed per chart bar
and chart coverage. The more intrabars you analyze per chart bar, the less coverage you will obtain.
The setting of the "Intrabar precision" field in the "DV channel" section of the script's inputs
is where you control how the lower timeframe is calculated from the chart's timeframe.
█ NOTES
Volume Quality
If you use volume, it's important to understand its nature and quality, as it varies with sectors and instruments. My Volume X-ray indicator is one way you can appraise the quality of an instrument's intraday volume.
For Pine Script™ Coders
• This script uses the new overload of the fill() function which now makes it possible to do vertical gradients in Pine. I use it for both channels displayed by this script.
• I use the new arguments for plot() 's `display` parameter to control where the script plots some of its values,
namely those I only want to appear in the script's status line and in the Data Window.
• I wrote my script using the revised recommendations in the Style Guide from the Pine v5 User Manual.
█ THANKS
To PineCoders . I have used their lower_tf library in this script, to manage the calculation of the LTF and intrabar stats, and their Time library to convert a timeframe in seconds to a printable form for its display in the Information box.
To TradingView's Pine Script™ team. Their innovations and improvements, big and small, constantly expand the boundaries of the language. What this script does would not have been possible just a few months back.
And finally, thanks to all the users of my scripts who take the time to comment on my publications and suggest improvements. I do not reply to all but I do read your comments and do my best to implement your suggestions with the limited time that I have.
Money Flow LineWhat is this? The Money Flow Line (MFL) indicator is at its core a more even-tempered version of the Price-Volume-Trend (PVT). The primary difference is the usage of `hlc3` ((high + low + close) / 3) rather than `close` to use the "typical price" that it critical to the calculation of the Money Flow Index (MFI). Other similar indicators include the Accumulation Distribution Line (ADL) and the On Balance Volume (OBV) indicators. The purpose of all of these indicators is to attempt to measure the strength of the money flow by combining price and volume into a rolling measurement that can be compared over time to look for confirmations and divergences.
The indicator also includes an optional averaging (smoothing) line that can be enabled in the display settings. Enabling this smoothing line with a desired period allows for simpler trend comparisons and also allows the user to view how far the line has diverged from the mean. This creates an indicator very similar to Elder's Force Index (EFI), which is also a `close * volume` style indicator.
Why is this important? After an extreme movement or volume spike the MFI will "snap back" sharply as that bar eventually exits the set period. This produces a result that is meaningless and skews the indicator away from the market structure. Because of this behavior, range clamping, and the loss of comparative history I prefer to shy away from oscillator style indicators. The Money Flow Line instead gives you all of the history so you may compare and see the broader trend without sharp snaps in history based on an arbitrary period setting.
Why is this better? This produces a no-lag indicator that isn't subject to the harsh skewing produced by they Money Flow Index's period calculation. It doesn't lose history like MFI or EFI, is clear about the trend direction, and prefers a "typical price" (averaging the entire range of each bar) rather than whatever happens to be the closing price for a given bar.
How can I use it? The indicator is attempting to measure supply and demand in the markets. No indicator is perfect, but we can use all of the information we have available to make our best predictions. There are only 3 pieces of data the market gives us:
1. Price (action)
2. Volume
3. Time
The Money Flow Line combines all of these data points into a readable rolling data set that attempts to show subtle balance of power shifts based on changes in volume and "smart money" (or "big money") stepping in and out of the picture. Much like PVT, we look for the same things:
- Trend Identification: an up or down trend appears in the MFL
- Confirmations: the MFL agrees with price action in direction and magnitude
- Divergence: the MFL disagrees with price action, indicating a reversal may be coming soon
When applying the smoothing line we can also look for similar things we would with EFI. The primary case would be to look for the MFL to jump very far away from the mean (a high magnitude movement) which indicates that price may be reverting towards the mean soon (a "mean reversion"). On the other hand, it may indicate strength in the current price direction. All of these predictions depend heavily on price action and market structure. Good luck!
Alpha Options System# Apex Options Sniper - Advanced Multi-Signal Day Trading System
## 🎯 Overview
**Apex Options Sniper** is a professional-grade, multi-signal trading indicator specifically engineered for high-probability day trading of weekly options. This comprehensive system combines 10+ technical indicators into a sophisticated scoring algorithm that identifies optimal entry points with institutional-level precision.
Perfect for traders of SPY, QQQ, and high-volume stocks, this indicator eliminates guesswork by providing clear BUY CALLS and BUY PUTS signals based on multiple technical confluences.
---
## 🚀 Key Features
### **Multi-Signal Confluence Engine**
- **10+ Technical Indicators** working in harmony
- **Weighted Scoring System** (0-30+ points) for signal strength
- **Real-time Signal Classification**: Strong vs Moderate signals
- **False Signal Reduction** through multi-confirmation requirements
### **Advanced Momentum Analysis**
- ✅ RSI with Divergence Detection (bullish & bearish)
- ✅ Stochastic Oscillator (oversold/overbought + crossovers)
- ✅ MACD with crossover and momentum confirmation
- ✅ Automatic divergence spotting for reversal trades
### **Sophisticated Trend Detection**
- ✅ Triple EMA System (9/21/50) with alignment scoring
- ✅ SuperTrend Indicator with trend flip alerts
- ✅ VWAP for institutional price levels
- ✅ Multi-timeframe trend confirmation
### **Professional Volume Analysis**
- ✅ Volume Spike Detection (vs 20-period average)
- ✅ OBV (On-Balance Volume) with divergence detection
- ✅ Order Flow Analysis (buy vs sell pressure)
- ✅ Relative volume ratio display
### **Advanced Pattern Recognition**
- ✅ Bollinger Band Squeeze detection (volatility expansion)
- ✅ BB breakout signals (major move initiation)
- ✅ Automatic Support & Resistance levels (pivot-based)
- ✅ Price reaction scoring at key levels
### **Built-in Risk Management**
- ✅ ATR-based Stop Loss calculations
- ✅ Customizable Risk:Reward ratios
- ✅ Position sizing recommendations
- ✅ Real-time profit target calculations
### **Comprehensive Visual Dashboard**
- ✅ Live scoring breakdown for all indicators
- ✅ Individual signal strength display
- ✅ Bull vs Bear score comparison
- ✅ Color-coded signal status
- ✅ Risk management metrics
---
## 📊 How It Works
### **Scoring System**
The indicator assigns points based on technical conditions:
| **Category** | **Max Points** | **Conditions** |
|-------------|---------------|----------------|
| Momentum (RSI/Stoch) | 8 | Oversold/overbought + divergences |
| MACD | 4 | Crossovers + momentum direction |
| Trend (EMAs) | 6 | EMA alignment + SuperTrend |
| Volume | 4 | Spikes + OBV divergences |
| Order Flow | 2 | Buy/sell pressure imbalance |
| Bollinger Bands | 2 | Squeeze + breakouts |
| Support/Resistance | 2 | Price at key levels |
| VWAP | 1 | Above/below institutional level |
### **Signal Thresholds**
- **🚀 STRONG CALLS**: Bull score ≥6, Net score ≥4
- **📈 CALLS**: Bull score ≥4, Net score ≥2
- **🔥 STRONG PUTS**: Bear score ≥6, Net score ≤-4
- **📉 PUTS**: Bear score ≥4, Net score ≤-2
### **Multi-Timeframe Filter**
Optional higher timeframe confirmation reduces false signals by ensuring the broader trend supports your trade direction.
---
## 🎮 How to Use
### **Installation**
1. Open TradingView Pine Editor
2. Paste the complete indicator code
3. Click "Add to Chart"
4. Customize settings to your preference
### **Recommended Settings**
**For SPY/QQQ Day Trading:**
- Timeframe: 1-minute or 5-minute
- Strong Signal Threshold: 6
- Moderate Signal Threshold: 4
- Multi-timeframe Confluence: ON
**For Individual Stocks:**
- Timeframe: 5-minute or 15-minute
- Increase SuperTrend multiplier to 3.5-4.0
- Enable all advanced features
**For Scalping:**
- Timeframe: 1-minute
- Use STRONG signals only (6+)
- Tight stop loss (1.0-1.5 ATR multiplier)
### **Best Trading Times**
- **9:30-11:00 AM EST** - Highest volume, strongest signals
- **2:00-4:00 PM EST** - Afternoon momentum plays
- Avoid 11:30 AM-1:30 PM EST (lunch chop)
---
## 📈 Signal Interpretation
### **What You'll See on Chart:**
**Visual Signals:**
- 🟢 **Green Triangle (CALLS)**: Bullish entry point
- 🟢 **Large Green Triangle (STRONG CALLS)**: High-confidence bullish entry
- 🔴 **Red Triangle (PUTS)**: Bearish entry point
- 🔴 **Large Red Triangle (STRONG PUTS)**: High-confidence bearish entry
- 💎 **Small Diamonds**: RSI/OBV divergences (reversal warning)
**Dashboard Information:**
- Individual indicator values and signals
- Real-time score breakdown
- Bull/Bear score totals
- ATR stop loss levels
### **Entry Rules:**
✅ **High Probability Trades (Take These):**
- Strong signal (6+ score)
- 3+ indicators confirming
- Volume spike present
- SuperTrend aligned
- Higher timeframe confirms
⚠️ **Moderate Trades (Smaller Position):**
- Moderate signal (4-5 score)
- 2+ indicators confirming
- Normal volume
- Mixed trend signals
❌ **Avoid These:**
- Conflicting signals (Bull score ≈ Bear score)
- Low volume
- During major news events
- Bollinger squeeze without breakout direction
---
## 🛡️ Risk Management Guide
### **Position Sizing:**
- **Strong Signals (6+)**: 3-5% of portfolio
- **Moderate Signals (4-5)**: 2-3% of portfolio
- **Low Conviction**: 1-2% or skip
### **Stop Loss Strategy:**
- Use ATR-based stops (displayed in dashboard)
- Default: 1.5x ATR from entry
- Weekly options: 30-50% premium loss maximum
- Never hold through stop loss hoping for recovery
### **Profit Targets:**
- **Quick Scalps**: 25-50% gain (15-30 min)
- **Day Trades**: 50-100% gain (same day exit)
- **Swing**: 100-200% gain (1-2 days max for weeklies)
- **Take partial profits** at first target, let rest run
### **Time Decay Management (Weekly Options):**
- Monday-Wednesday: Hold overnight acceptable on strong signals
- Thursday: Close by EOD unless very strong conviction
- Friday: Avoid holding overnight, theta decay accelerates
---
## 🔔 Alert Configuration
### **Recommended Alerts:**
**Essential Alerts:**
1. 🚀 Strong Buy Calls
2. 🔥 Strong Buy Puts
**Advanced Alerts:**
3. 💎 RSI Bullish Divergence
4. ⚠️ RSI Bearish Divergence
5. 🔶 Bollinger Band Squeeze
6. ✅ SuperTrend Bull Flip
7. ❌ SuperTrend Bear Flip
**Alert Setup:**
- Set frequency: "Once Per Bar Close"
- Enable for all devices
- Use webhook for automation (optional)
---
## 💡 Pro Trading Tips
### **Maximize Win Rate:**
1. **Wait for confluence** - Best trades have 3+ indicators aligned
2. **Respect the dashboard** - Check WHY it's signaling (which indicators)
3. **Volume is king** - Signals with volume spikes are significantly more reliable
4. **Use BB Squeeze** - When squeeze + signal = explosive directional move
5. **SuperTrend flips** - Major trend change confirmations, very powerful
6. **Watch for divergences** - Diamond markers = hidden reversal opportunities
### **Common Mistakes to Avoid:**
❌ Trading every signal (be selective)
❌ Ignoring volume (volume confirms everything)
❌ Fighting the higher timeframe trend
❌ Oversizing positions on moderate signals
❌ Holding weekly options too long (theta decay)
❌ Trading during lunch hour (11:30-1:30 EST)
### **Advanced Techniques:**
- **Divergence + Support/Resistance** = Highest probability reversals
- **BB Squeeze + EMA alignment** = Explosive trend continuations
- **SuperTrend flip + Volume spike** = Major trend change entries
- **Multiple timeframe analysis** - Check 5m signal on 1m chart for precision entries
---
## 📊 Indicator Components Explained
### **RSI (Relative Strength Index)**
- Measures momentum and overbought/oversold conditions
- Divergences signal potential reversals before they happen
- Score: 2-3 points for extremes and divergences
### **Stochastic Oscillator**
- Confirms momentum extremes
- Crossovers provide entry timing
- Score: 1-2 points
### **MACD (Moving Average Convergence Divergence)**
- Trend following momentum indicator
- Crossovers signal momentum shifts
- Score: 1-3 points based on signal strength
### **EMA System (9/21/50)**
- Dynamic support and resistance
- Alignment shows trend strength
- Price position relative to EMAs scores 1-2 points
### **SuperTrend**
- Volatility-based trend indicator
- Reduces whipsaws in choppy conditions
- Trend flips are major signals (2 points)
### **Bollinger Bands**
- Volatility measurement
- Squeeze = calm before the storm
- Breakouts = directional move initiation (2 points)
### **Volume Analysis**
- Confirms price movement legitimacy
- Spikes validate signals (2 points)
- OBV divergences predict reversals (2 points)
### **Order Flow**
- Buy vs sell pressure measurement
- Institutional footprint detection
- Score: 2 points for strong imbalances
---
## 🎓 Learning Path
### **Beginner (Week 1-2):**
- Use STRONG signals only
- Focus on high-volume stocks (SPY/QQQ)
- Trade only first hour of market
- Use paper trading first
### **Intermediate (Week 3-4):**
- Add moderate signals to your arsenal
- Learn to read the dashboard
- Understand why each signal triggers
- Start combining with support/resistance
### **Advanced (Month 2+):**
- Use divergence signals
- Trade BB squeeze breakouts
- Optimize settings for your style
- Develop your own confluence rules
---
## ⚙️ Customization Guide
### **Adjustable Parameters:**
**Momentum Settings:**
- RSI Length (default: 14)
- RSI Oversold/Overbought levels (30/70)
- Stochastic Length (14)
**Trend Settings:**
- EMA periods (9/21/50)
- SuperTrend ATR Length (10)
- SuperTrend Multiplier (3.0)
**Volume Settings:**
- Volume MA Length (20)
- Volume Spike Threshold (1.5x)
**Advanced Settings:**
- Bollinger Band Length (20)
- BB Standard Deviation (2.0)
- Pivot Lookback (10)
**Signal Thresholds:**
- Strong Signal Score (default: 6)
- Moderate Signal Score (default: 4)
**Risk Management:**
- ATR Length (14)
- Stop Loss Multiplier (1.5)
- Risk:Reward Ratio (2.0)
---
## 📈 Performance Optimization
### **For Volatile Markets (VIX > 25):**
- Increase SuperTrend multiplier to 4.0
- Raise signal thresholds (+1 point)
- Tighten stop losses (1.0-1.2 ATR)
### **For Ranging Markets:**
- Focus on RSI extremes and divergences
- Use BB squeeze signals
- Ignore moderate signals
- Wait for support/resistance confirmation
### **For Trending Markets:**
- Follow SuperTrend direction religiously
- Use EMA alignment signals
- Allow wider stops (2.0 ATR)
- Take partial profits, let winners run
---
## 🔍 Troubleshooting
**Too Many Signals:**
- Increase signal thresholds to 7/5
- Enable multi-timeframe filter
- Trade only STRONG signals
**Missing Signals:**
- Decrease thresholds to 5/3
- Disable multi-timeframe filter
- Check that all features are enabled
**Whipsaw in Choppy Markets:**
- Increase SuperTrend multiplier
- Require volume spike confirmation
- Avoid trading 11:30 AM-1:30 PM EST
---
## 🏆 Best Practices
✅ **Always check:**
1. Dashboard shows why signal triggered
2. Volume confirms the move
3. Not during news events
4. Adequate time until expiration
✅ **Risk Management:**
1. Never risk more than 2% per trade
2. Use stops religiously
3. Take profits at targets
4. Don't revenge trade
✅ **Journal Your Trades:**
1. Entry price and signal strength
2. Which indicators triggered
3. Exit price and profit/loss
4. What worked and what didn't
---
## 📞 Support & Updates
This indicator is designed to evolve with market conditions. Recommended to:
- Review settings monthly
- Backtest on your favorite instruments
- Adjust thresholds based on your risk tolerance
- Keep a trading journal to track performance
---
## ⚠️ Disclaimer
This indicator is a tool for technical analysis and should not be used as the sole basis for trading decisions. Options trading involves substantial risk and is not suitable for all investors. Past performance does not guarantee future results. Always:
- Do your own research and due diligence
- Never invest more than you can afford to lose
- Consider consulting with a financial advisor
- Practice with paper trading before using real money
- Understand options Greeks (Delta, Theta, Gamma, Vega)
- Be aware of earnings dates and major news events
**No indicator is 100% accurate. Use proper risk management and trade responsibly.**
---
## 📊 Version History
**v1.0 - Initial Release**
- Multi-signal confluence system
- 10+ technical indicators
- Advanced dashboard
- ATR-based risk management
- Comprehensive alert system
---
## 🎯 Final Thoughts
**Apex Options Sniper** transforms complex technical analysis into clear, actionable signals. By combining multiple proven indicators with sophisticated scoring logic, it helps traders identify high-probability setups while managing risk effectively.
**Success Keys:**
- Quality over quantity (be selective)
- Risk management is everything
- Volume confirms the signal
- Confluence increases probability
- Discipline beats emotion
**Trade smart. Trade with confidence. Trade with Apex Options Sniper.**
---
*For questions, suggestions, or to share your success stories, please comment below or send a message.*
**Happy Trading! 🚀📈**
CVD & Big Trade Detector By HKOverview The CVD & Big Trade Detector By HK offers a unique perspective on Cumulative Volume Delta (CVD). This indicator utilizes Floating Bars (Candles) to visualize the cumulative buying and selling pressure. This design allows you to clearly see the net delta of each specific candle relative to the cumulative trend.
Additionally, it integrates the "Big Trade" algorithm to highlight statistically significant volume anomalies (Whale activity) directly on the CVD bars.
How it Works Since standard volume data does not always provide buy/sell splitting, this script estimates intrabar pressure using price action logic:
Buying Pressure: Calculated based on the push from the Low to the Close.
Selling Pressure: Calculated based on the push from the High to the Close.
The indicator then calculates the Delta (Buy Vol - Sell Vol) and accumulates it.
Floating Bars: Instead of plotting from the zero-line, each bar opens at the previous CVD value and closes at the new cumulative value.
Teal/Green Bar: Net buying in the current period (CVD increased).
Maroon/Red Bar: Net selling in the current period (CVD decreased).
Key Features
Floating CVD Structure: Prevents the "barcode effect" common in histogram CVDs. It provides a clean, candle-like view of momentum accumulation.
Whale Detection:
The script calculates the moving average and standard deviation (Sigma) of the buying/selling volume.
Green Dots: Appear when buying volume exceeds the statistical threshold (Signifying a "Big Buy").
Red Dots: Appear when selling volume exceeds the statistical threshold (Signifying a "Big Sell").
Precise Positioning: Whale markers are plotted exactly at the closing value of the CVD bar, showing you exactly where the volume spike impacted the delta.
How to Use
Divergences: Look for situations where Price makes a Higher High, but the CVD Bars fail to make a new high (bearish divergence).
Absorption: If you see a Large Whale Dot on a very small CVD bar (doji-like), it indicates massive volume fighting for direction with little net result—often a sign of absorption or a pending reversal.
Trend Confirmation: Strong floating bars in the direction of the trend, accompanied by Whale Dots, confirm smart money participation.
Settings
Lookback Period: Defines the baseline for the statistical volume calculation (default: 50).
Sensitivity (Sigma): Adjusts how strict the "Whale" detection is (default: 3.0). Higher values = fewer, more significant signals.
Colors: Fully customizable colors for Up/Down bars and Buy/Sell markers.
Built with Pine Script™ v6
Quantum Market Analyzer X7Quantum Market Analyzer X7 - Complete Study Guide
Table of Contents
1. Overview
2. Indicator Components
3. Signal Interpretation
4. Live Market Analysis Guide
5. Best Practices
6. Limitations and Considerations
7. Risk Disclaimer
________________________________________
Overview
The Quantum Market Analyzer X7 is a comprehensive multi-timeframe technical analysis indicator that combines traditional and modern analytical methods. It aggregates signals from multiple technical indicators across seven key analysis categories to provide traders with a consolidated view of market sentiment and potential trading opportunities.
Key Features:
• Multi-Indicator Analysis: Combines 20+ technical indicators
• Real-Time Dashboard: Professional interface with customizable display
• Signal Aggregation: Weighted scoring system for overall market sentiment
• Advanced Analytics: Includes Order Block detection, Supertrend, and Volume analysis
• Visual Progress Indicators: Easy-to-read progress bars for signal strength
________________________________________
Indicator Components
1. Oscillators Section
Purpose: Identifies overbought/oversold conditions and momentum changes
Included Indicators:
• RSI (14): Relative Strength Index - momentum oscillator
• Stochastic (14): Compares closing price to price range
• CCI (20): Commodity Channel Index - cycle identification
• Williams %R (14): Momentum indicator similar to Stochastic
• MACD (12,26,9): Moving Average Convergence Divergence
• Momentum (10): Rate of price change
• ROC (9): Rate of Change
• Bollinger Bands (20,2): Volatility-based indicator
Signal Interpretation:
• Strong Buy (6+ points): Multiple oscillators indicate oversold conditions
• Buy (2-5 points): Moderate bullish momentum
• Neutral (-1 to 1 points): Balanced conditions
• Sell (-2 to -5 points): Moderate bearish momentum
• Strong Sell (-6+ points): Multiple oscillators indicate overbought conditions
2. Moving Averages Section
Purpose: Determines trend direction and strength
Included Indicators:
• SMA: 10, 20, 50, 100, 200 periods
• EMA: 10, 20, 50 periods
Signal Logic:
• Price >2% above MA = Strong Buy (+2)
• Price above MA = Buy (+1)
• Price below MA = Sell (-1)
• Price >2% below MA = Strong Sell (-2)
Signal Interpretation:
• Strong Buy (6+ points): Price well above multiple MAs, strong uptrend
• Buy (2-5 points): Price above most MAs, bullish trend
• Neutral (-1 to 1 points): Mixed MA signals, consolidation
• Sell (-2 to -5 points): Price below most MAs, bearish trend
• Strong Sell (-6+ points): Price well below multiple MAs, strong downtrend
3. Order Block Analysis
Purpose: Identifies institutional support/resistance levels and breakouts
How It Works:
• Detects historical levels where large orders were placed
• Monitors price behavior around these levels
• Identifies breakouts from established order blocks
Signal Types:
• BULLISH BRK (+2): Breakout above resistance order block
• BEARISH BRK (-2): Breakdown below support order block
• ABOVE SUP (+1): Price holding above support
• BELOW RES (-1): Price rejected at resistance
• NEUTRAL (0): No significant order block interaction
4. Supertrend Analysis
Purpose: Trend following indicator based on Average True Range
Parameters:
• ATR Period: 10 (default)
• ATR Multiplier: 6.0 (default)
Signal Types:
• BULLISH (+2): Price above Supertrend line
• BEARISH (-2): Price below Supertrend line
• NEUTRAL (0): Transition period
5. Trendline/Channel Analysis
Purpose: Identifies trend channels and breakout patterns
Components:
• Dynamic trendline calculation using pivot points
• Channel width based on historical volatility
• Breakout detection algorithm
Signal Types:
• UPPER BRK (+2): Breakout above upper channel
• LOWER BRK (-2): Breakdown below lower channel
• ABOVE MID (+1): Price above channel midline
• BELOW MID (-1): Price below channel midline
6. Volume Analysis
Purpose: Confirms price movements with volume data
Components:
• Volume spikes detection
• On Balance Volume (OBV)
• Volume Price Trend (VPT)
• Money Flow Index (MFI)
• Accumulation/Distribution Line
Signal Calculation: Multiple volume indicators are combined to determine institutional activity and confirm price movements.
________________________________________
Signal Interpretation
Overall Summary Signals
The indicator aggregates all component signals into an overall market sentiment:
Signal Score Range Interpretation Action
STRONG BUY 10+ Overwhelming bullish consensus Consider long positions
BUY 4-9 Moderate to strong bullish bias Look for long opportunities
NEUTRAL -3 to 3 Mixed signals, consolidation Wait for clearer direction
SELL -4 to -9 Moderate to strong bearish bias Look for short opportunities
STRONG SELL -10+ Overwhelming bearish consensus Consider short positions
Progress Bar Interpretation
• Filled bars indicate signal strength
• Green bars: Bullish signals
• Red bars: Bearish signals
• More filled bars = stronger conviction
________________________________________
Live Market Analysis Guide
Step 1: Initial Assessment
1. Check Overall Summary: Start with the main signal
2. Verify with Component Analysis: Ensure signals align
3. Look for Divergences: Identify conflicting signals
Step 2: Timeframe Analysis
1. Set Appropriate Timeframe: Use 1H for intraday, 4H/1D for swing trading
2. Multi-Timeframe Confirmation: Check higher timeframes for trend context
3. Entry Timing: Use lower timeframes for precise entry points
Step 3: Signal Confirmation Process.
For Buy Signals:
1. Oscillators: Look for oversold conditions (RSI <30, Stoch <20)
2. Moving Averages: Price should be above key MAs
3. Order Blocks: Confirm bounce from support levels
4. Volume: Check for accumulation patterns
5. Supertrend: Ensure bullish trend alignment.
For Sell Signals:
1. Oscillators: Look for overbought conditions (RSI >70, Stoch >80)
2. Moving Averages: Price should be below key MAs
3. Order Blocks: Confirm rejection at resistance levels
4. Volume: Check for distribution patterns
5. Supertrend: Ensure bearish trend alignment.
Step 4: Risk Management Integration
1. Signal Strength Assessment: Stronger signals = larger position size
2. Stop Loss Placement: Use Order Block levels for stops
3. Take Profit Targets: Based on channel analysis and resistance levels
4. Position Sizing: Adjust based on signal confidence
________________________________________
Best Practices
Entry Strategies
1. High Conviction Entries: Wait for STRONG BUY/SELL signals
2. Confluence Trading: Look for multiple components aligning
3. Breakout Trading: Use Order Block and Trendline breakouts
4. Trend Following: Align with Supertrend direction.
Risk Management
1. Never Risk More Than 2% Per Trade: Regardless of signal strength
2. Use Stop Losses: Place at invalidation levels
3. Scale Positions: Stronger signals warrant larger (but still controlled) positions
4. Diversification: Don't rely solely on one indicator.
Market Conditions
1. Trending Markets: Focus on Supertrend and MA signals
2. Range-Bound Markets: Emphasize Oscillator and Order Block signals
3. High Volatility: Reduce position sizes, widen stops
4. Low Volume: Be cautious of breakout signals.
Common Mistakes to Avoid
1. Signal Chasing: Don't enter after signals have already moved significantly
2. Ignoring Context: Consider overall market conditions
3. Overtrading: Wait for high-quality setups
4. Poor Risk Management: Always use appropriate position sizing
________________________________________
Limitations and Considerations
Technical Limitations
1. Lagging Nature: All technical indicators are based on historical data
2. False Signals: No indicator is 100% accurate
3. Market Regime Changes: Indicators may perform differently in various market conditions
4. Whipsaws: Possible in choppy, sideways markets.
Optimal Use Cases
1. Trending Markets: Performs best in clear trending environments
2. Medium to High Volatility: Requires sufficient price movement for signals
3. Liquid Markets: Works best with adequate volume and tight spreads
4. Multiple Timeframe Analysis: Most effective when used across different timeframes.
When to Use Caution
1. Major News Events: Fundamental analysis may override technical signals
2. Market Opens/Closes: Higher volatility can create false signals
3. Low Volume Periods: Signals may be less reliable
4. Holiday Trading: Reduced participation affects signal quality
________________________________________
Risk Disclaimer
IMPORTANT LEGAL DISCLAIMER FROM aiTrendview
WARNING: TRADING INVOLVES SUBSTANTIAL RISK OF LOSS
This Quantum Market Analyzer X7 indicator ("the Indicator") is provided for educational and informational purposes only. By using this indicator, you acknowledge and agree to the following terms:
No Investment Advice
• The Indicator does NOT constitute investment advice, financial advice, or trading recommendations
• All signals generated are based on historical price data and mathematical calculations
• Past performance does not guarantee future results
• No representation is made that any account will achieve profits or losses similar to those shown.
Risk Acknowledgment
• TRADING CARRIES SUBSTANTIAL RISK: You may lose some or all of your invested capital
• LEVERAGE AMPLIFIES RISK: Margin trading can result in losses exceeding your initial investment
• MARKET VOLATILITY: Financial markets are inherently unpredictable and volatile
• TECHNICAL ANALYSIS LIMITATIONS: No technical indicator is infallible or guarantees profitable trades.
User Responsibility
• YOU ARE SOLELY RESPONSIBLE for all trading decisions and their consequences
• CONDUCT YOUR OWN RESEARCH: Always perform independent analysis before making trading decisions
• CONSULT PROFESSIONALS: Seek advice from qualified financial advisors
• RISK MANAGEMENT: Implement appropriate risk management strategies
No Warranties
• The Indicator is provided "AS IS" without warranties of any kind
• aiTrendview makes no representations about the accuracy, reliability, or suitability of the Indicator
• Technical glitches, data feed issues, or calculation errors may occur
• The Indicator may not work as expected in all market conditions.
Limitation of Liability
• aiTrendview SHALL NOT BE LIABLE for any direct, indirect, incidental, or consequential damages
• This includes but is not limited to: trading losses, missed opportunities, data inaccuracies, or system failures
• MAXIMUM LIABILITY is limited to the amount paid for the indicator (if any)
Code Usage and Distribution
• This indicator is published on TradingView in accordance with TradingView's house rules
• UNAUTHORIZED MODIFICATION or redistribution of this code is prohibited
• Users may not claim ownership of this intellectual property
• Commercial use requires explicit written permission from aiTrendview.
Compliance and Regulations
• VERIFY LOCAL REGULATIONS: Ensure compliance with your jurisdiction's trading laws
• Some trading strategies may not be suitable for all investors
• Tax implications of trading are your responsibility
• Report trading activities as required by law
Specific Risk Factors
1. False Signals: The Indicator may generate incorrect buy/sell signals
2. Market Gaps: Overnight gaps can invalidate technical analysis
3. Fundamental Events: News and economic data can override technical signals
4. Liquidity Risk: Some markets may have insufficient liquidity
5. Technology Risk: Platform failures or connectivity issues may prevent order execution.
Professional Trading Warning
• THIS IS NOT PROFESSIONAL TRADING SOFTWARE: Not intended for institutional or professional trading
• NO REGULATORY APPROVAL: This indicator has not been approved by any financial regulatory authority
• EDUCATIONAL PURPOSE: Designed primarily for learning technical analysis concepts
FINAL WARNING
NEVER INVEST MONEY YOU CANNOT AFFORD TO LOSE
Trading financial instruments involves significant risk. The majority of retail traders lose money. Before using this indicator in live trading:
1. Practice on paper/demo accounts extensively
2. Start with small position sizes
3. Develop a comprehensive trading plan
4. Implement strict risk management rules
5. Continuously educate yourself about market dynamics
By using the Quantum Market Analyzer X7, you acknowledge that you have read, understood, and agree to this disclaimer. You assume full responsibility for all trading decisions and their outcomes.
Contact: For questions about this disclaimer or the indicator, contact aiTrendview through official TradingView channels only.
________________________________________
This study guide and indicator are published on TradingView in compliance with TradingView's community guidelines and house rules. All users must adhere to TradingView's terms of service when using this indicator.
Document Version: 1.0
Publisher: aiTrendview
________________________________________
Disclaimer
The content provided in this blog post is for educational and training purposes only. It is not intended to be, and should not be construed as, financial, investment, or trading advice. All charting and technical analysis examples are for illustrative purposes. Trading and investing in financial markets involve substantial risk of loss and are not suitable for every individual. Before making any financial decisions, you should consult with a qualified financial professional to assess your personal financial situation.
Ripster: DTR/ATR + SMA Div + RVOL🧭 Overview
The indicator combines three major analytical tools into one TradingView Pine v6 script — designed for clean, at-a-glance insight into range, divergence, and volume activity.
It shows:
DTR vs ATR Table – current Daily True Range compared to Average True Range.
SMA Price Divergence + EMA Signal – a histogram with color-coded momentum bands.
RVOL Table + Candle Coloring + Change Labels – relative-volume analysis with visual cues on the chart.
Short title: ripcombo
Runs on chart overlay (no separate pane).
📊 1. DTR vs ATR Table
Compares today’s price range (High-Low) to the average true range over a selectable length.
Supports multiple smoothing methods: EMA, RMA, SMA, WMA.
Table position and text size are configurable.
Color logic:
🟢 ≤ 70 % of ATR → low volatility
🟡 70–90 % → average
🔴 ≥ 90 % → expanded range
📈 2. SMA Divergence + EMA Signal
Computes fast (14 SMA) and slow (30 SMA) divergences of price.
Plots two histograms plus an EMA signal line of the slow divergence.
Visuals:
Columns shaded by transparency for clarity.
Rising EMA → lime line (up momentum).
Falling EMA → red line (down momentum).
Optional upper/lower bands and zero line provide quick overbought/oversold zones.
🔥 3. RVOL (Relative Volume)
Adds powerful volume-based context:
a. Table Display
Shows:
Candle Volume
RVOL (Now)
RVOL (Prev)
Δ RVOL (change Now − Prev)
Colors:
🔴 > 200 % (very high volume)
🟠 100–200 % (high volume)
🟡 < 100 % (normal/low volume)
Δ column is green ▲ for increase, red ▼ for decrease.
b. Candle Coloring (optional)
Colors price candles themselves by current RVOL threshold so high-volume candles visually stand out.
c. Last-Bar Label (optional)
Prints a compact label on the latest candle showing:
RVOL: ### % Δ: ▲/▼## %
so you can instantly see the current volume strength and how it changed from the previous bar.
⚙️ User Settings
All major elements are toggle-controlled:
Enable/disable ATR, Divergence, or RVOL sections.
Choose table positions (top/middle/bottom × left/center/right).
Select text sizes, smoothing types, color modes, and visual transparency.
Candle coloring + label visibility are optional.
🧠 At a Glance
Component Purpose Key Visuals
DTR vs ATR Measures volatility expansion One-cell colored table
SMA Divergence Detects price momentum shifts Columns + EMA line + bands
RVOL Analysis Highlights unusual trading volume Colored table + Δ column + candle colors + label
✅ Result
You get a single on-chart tool that:
Quantifies volatility, momentum, and volume context together.
Highlights strong activity days (ATR & RVOL) in color.
Shows whether current candle’s volume is rising or falling vs the previous.
Perfect for spotting breakouts, reversals, or exhaustion moves without switching indicators.
Enhanced Chande Momentum OscillatorEnhanced Chande Momentum Oscillator (Enh CMO)
📊 Description
The Enhanced Chande Momentum Oscillator is an advanced version of the classic Chande Momentum Oscillator with dynamic envelope boundaries that automatically adapt to market volatility. This indicator provides clear visual signals for potential price reversals and momentum shifts.
Key Features:
Original Chande Momentum Oscillator calculation
Dynamic upper and lower boundaries based on statistical analysis
Adaptive envelope that adjusts to market volatility
Visual fill area between boundaries for easy interpretation
Real-time values table with current readings
Built-in alert conditions for boundary touches
Customizable moving average types (SMA, EMA, WMA)
⚙️ Settings
CMO Settings:
CMO Length (9): Period for calculating the base Chande Momentum Oscillator
Source (close): Price source for calculations
Envelope Settings:
Envelope Length (20): Lookback period for calculating the moving average and standard deviation
Envelope Multiplier (1.5): Multiplier for standard deviation to create upper/lower bounds
Moving Average Type (EMA): Type of moving average for envelope calculation
📈 How to Use
Visual Elements
Lines:
White Line: Main Chande Momentum Oscillator
Red Line: Upper boundary (resistance level)
Green Line: Lower boundary (support level)
Yellow Line: Moving average of CMO (trend direction)
Purple Fill: Visual envelope between boundaries
Reference Lines:
Zero Line: Neutral momentum level
+50/-50 Lines: Traditional overbought/oversold levels
Trading Signals
🔴 Sell/Short Signals
CMO touches or crosses above upper boundary → Potential bearish reversal
CMO is above +50 and declining → Weakening bullish momentum
CMO crosses below yellow MA line while above zero → Momentum shift
🟢 Buy/Long Signals
CMO touches or crosses below lower boundary → Potential bullish reversal
CMO is below -50 and rising → Weakening bearish momentum
CMO crosses above yellow MA line while below zero → Momentum shift
⚡ Advanced Signals
Boundary contraction → Decreasing volatility, potential breakout coming
Boundary expansion → High volatility period, use wider stops
CMO hugging upper boundary → Strong uptrend continuation
CMO hugging lower boundary → Strong downtrend continuation
🎯 Trading Strategies
Strategy 1: Reversal Trading
Wait for CMO to touch extreme boundaries (red or green lines)
Look for divergence with price action
Enter counter-trend position when CMO starts moving back toward center
Set stop beyond the boundary breach point
Take profit near zero line or opposite boundary
Strategy 2: Momentum Confirmation
Use CMO direction to confirm trend
Enter positions when CMO crosses above/below yellow MA line
Hold positions while CMO remains on the correct side of MA
Exit when CMO crosses back through MA line
Strategy 3: Volatility Breakout
Monitor boundary width (envelope expansion/contraction)
When boundaries contract significantly, prepare for breakout
Enter in direction of CMO breakout from narrow range
Use boundary expansion as confirmation signal
⚠️ Important Notes
Best Timeframes
Scalping: 1m, 5m charts
Day Trading: 15m, 30m, 1H charts
Swing Trading: 4H, Daily charts
Market Conditions
Trending Markets: Focus on momentum confirmation signals
Ranging Markets: Focus on boundary reversal signals
High Volatility: Increase envelope multiplier (1.8-2.5)
Low Volatility: Decrease envelope multiplier (1.0-1.3)
Risk Management
Always use stop losses beyond boundary levels
Reduce position size during boundary expansion periods
Combine with price action and support/resistance levels
Monitor the real-time table for precise entry/exit levels
🔔 Alerts
The indicator includes built-in alert conditions:
"CMO Above Upper Bound": Potential reversal down signal
"CMO Below Lower Bound": Potential reversal up signal
Set these alerts to catch opportunities without constantly monitoring charts.
💡 Tips for Success
Combine with other indicators: Use with RSI, MACD, or volume indicators for confirmation
Watch for divergences: CMO making new highs/lows while price doesn't follow
Use multiple timeframes: Check higher timeframe CMO for overall trend context
Adjust settings for different assets: Crypto may need different settings than forex
Paper trade first: Test the indicator with your trading style before using real money
🎨 Customization Tips
Change colors in the Pine Script to match your chart theme
Adjust envelope length for faster (shorter) or slower (longer) signals
Modify envelope multiplier based on asset volatility
Hide the table if it obstructs your view by commenting out the table section
Complete trading solution: Pair with the Optimus Indicator (paid indicator) for multi-timeframe trend analysis and trend signals.
Together they create a powerful confluence system for professional trading setups.
