BayesCore Golden Bars BOVESPA Index-MiniIt is recommended to use this indicator for the Bovespa Index-Mini Futures.
This indicator uses golden candles and dots that appear directly on the chart to draw the trader’s attention to potential entry opportunities (buy/sell).
Usage:
When the lines are in an uptrend, if the second golden candle is above the lines and moving upward, there is a buying opportunity.
When the lines are in a downtrend, if the second golden candle is below the lines and moving downward, there is a selling opportunity.
In a sideways market, do not execute trades.
If you wish to trade in a sideways market, you can use the blue line as a guide: when the price is below the line, you buy; when it is above, you sell — this way, you can perform scalping.
These golden signals are designed to highlight candles that align more closely with the moving averages (blue and green lines), increasing the likelihood of capturing trades in line with the prevailing trend. By concentrating on these highlighted points, traders can more easily identify high-probability setups while avoiding unnecessary distractions.
The main purpose is to support longer trades on the Bovespa Index-Mini Futures, without adding new positions along the way. This approach helps traders maintain a safer and more consistent trading style.
Always confirm whether the golden signals converge with the overall market trend.
Forecasting
BayesCore AI Golden BarsThis indicator analyzes the market candle by candle, using the overall trend as a reference to highlight entry opportunities (buy or sell) by coloring candles in gold. These golden bars signal probabilistic opportunities for entries and re-entries throughout the trade.
We’ve added three classic moving averages so traders can have a visual reference of zones and trends to decide whether to act on the opportunities suggested by the indicator.
Tip: The best entries usually occur near the regions of the moving averages (blue and green lines). That’s why we included these classic moving averages, to give traders a clear trend reference.
Additionally, the indicator provides alerts such as “Only Buy,” “Only Sell,” or “No Action” to help traders maintain psychological discipline during the trading process and seek the best entries aligned with the market trend.
Giant candles, which can signal the ignition force of a market trend, are also colored gold and marked with an elephant icon, symbolizing the “leader of the herd,” suggesting that the movement may be worth following.
On the chart, the indicator plots two lines above and two lines below the candles near the active candle. These lines suggest possible stop-loss placements based on previous swing highs and lows, ensuring they are not overly costly stops. They serve only as indicative stop-loss positions, leaving it up to the trader to assess—based on their risk management—whether the suggested placement is appropriate.
Always consider whether the golden candle coloring aligns with the overall market trend.
Past results do not guarantee future returns.
WASDE DatesOverview
WASDE Dates — a small, focused event indicator that displays confirmed USDA WASDE release dates for 2025 on the chart and marks each release day. The indicator is designed to be a lightweight timing tool for traders who want clean visual reminders and optional alerts around USDA WASDE publications.
Features
• Shows official WASDE release dates for 2025 in a compact chart table.
• Draws on-chart markers and a dotted vertical line on WASDE release days.
• Two alert conditions you can enable in TradingView: "WASDE Day Alert" and "WASDE 24h Reminder".
• Simple table position control (Top/Bottom, Left/Right) in the indicator settings.
• Minimal, self-contained code — no external data feeds or permissions required.
How to use
1. Apply the indicator to any chart and timeframe.
2. Use the indicator settings to choose table position.
3. Enable Alerts (if desired) via TradingView Alerts → choose “WASDE Day Alert” or “WASDE 24h Reminder”.
4. This version contains 2025 confirmed dates only — verify dates for live trading and enable alerts as needed.
Design & rationale
This indicator is intentionally not a technical trading signal. It is an event scheduler focused on clarity and low overhead: combine it with your existing setup to avoid being surprised by WASDE publications and to quickly inspect price action around these event dates.
Limitations & disclaimer
• This script shows **confirmed 2025** WASDE dates only. It does not provide trading advice or entry/exit signals. Use at your own risk.
• Double-check official USDA publishing times before executing trades.
• No external links or contact information are included in this description to comply with TradingView publishing rules.
Feature outlook (V2)
Planned V2 (future release): enhanced countdown (days → hours/minutes), optional inclusion of estimated 2026 dates marked as (TBC), and an invite-only/protected advanced version with reaction overlays (T+1/T+3) and extended alert options. V2 will be announced on this script page when ready.
Changelog
v1 — public release: 2025 confirmed dates, release markers, alerts, table position control.
Smart Money Support/Resistance — LiteSmart Money Support/Resistance — Lite
Overview & Methodology
This indicator identifies support and resistance as zones derived from concentrated buying and selling pressure, rather than relying solely on traditional swing highs/lows. Its design focuses on transparency: how data is sourced, how zones are computed, and how the on‑chart display should be interpreted.
Lower‑Timeframe (LTF) Data
The script requests Up Volume, Down Volume, and Volume Delta from a lower timeframe to expose intrabar order‑flow structure that the chart’s native timeframe cannot show. In practical terms, this lets you see where buyers or sellers briefly dominated inside the body of a higher‑timeframe bar.
bool use_custom_tf_input = input.bool(true, title="Use custom lower timeframe", tooltip="Override the automatically chosen lower timeframe for volume calculations.", group=grpVolume)
string custom_tf_input = input. Timeframe("1", title="Lower timeframe", tooltip="Lower timeframe used for up/down volume calculations (default 5 seconds).", group=grpVolume)
import TradingView/ta/10 as tvta
resolve_lower_tf(useCustom, customTF) =>
useCustom ? customTF :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
get_up_down_volume(lowerTf) =>
= tvta.requestUpAndDownVolume(lowerTf)
var float upVolume = na
var float downVolume = na
var float deltaVolume = na
string lower_tf = resolve_lower_tf(use_custom_tf_input, custom_tf_input)
= get_up_down_volume(lower_tf)
upVolume := u_tmp
downVolume := d_tmp
deltaVolume := dl_tmp
• Data source: TradingView’s ta.requestUpAndDownVolume(lowerTf) via the official TA library.
• Plan capabilities: higher‑tier subscriptions unlock seconds‑based charts and allow more historical bars per chart. This expands both the temporal depth of LTF data and the precision of short‑horizon analysis, while base tiers provide minute‑level data suitable for day/short‑swing studies.
• Coverage clarity: a small on‑chart Coverage Panel reports the active lower timeframe, the number of bars covered, and the latest computed support/resistance ranges so you always know the bounds of valid LTF input.
Core Method
1) Data acquisition (LTF)
The script retrieves three series from the chosen lower timeframe:
– Up Volume (buyers)
– Down Volume (sellers)
– Delta (Up – Down)
2) Rolling window & extrema
Over a user‑defined lookback (Global Volume Period), the algorithm builds rolling arrays of completed bars and scans for extrema:
– Buyers_max / Buyers_min from Up Volume
– Sellers_max / Sellers_min from Down Volume
Only completed bars are considered; the current bar is excluded for stability.
3) Price mapping
The extrema are mapped back to their source candles to obtain price bounds:
– For “maximum” roles the algorithm uses the relevant candle highs.
– For “minimum” roles it uses the relevant candle lows.
These pairs define candidate resistance (max‑based) and support (min‑based) zones or vice versa.
4) Zone construction & minimum width
To ensure practicality on all symbols, zones enforce a minimum vertical thickness of two ticks. This prevents visually invisible or overly thin ranges on instruments with tight ticks.
5) Vertical role resolution
When both max‑ and min‑based zones exist, the script compares their midpoints. If, due to local price structure, the min‑based zone sits above the max‑based zone, display roles are swapped so the higher zone is labeled Resistance and the lower zone Support. Colors/widths are updated accordingly to keep the visual legend consistent.
6) Rendering & panel
Two horizontal lines and a filled box represent each active zone. The Coverage Panel (bottom‑right by default) prints:
– Lower‑timeframe in use
– Number of bars covered by LTF data
– Current Support and Resistance ranges
If the two zones overlap, an additional “Range Market” note is shown.
Key Inputs
• Global Volume Period: shared lookback window for the extrema search.
• Lower timeframe: user‑selectable override of the automatically resolved lower timeframe.
• Visualization toggles: independent show/hide controls and colors for maximum (resistance) and minimum (support) zones.
• Coverage Panel: enable/disable the single‑cell table and its readout.
Operational Notes
• The algorithm aligns all lookups to completed bars (no peeking). Price references are shifted appropriately to avoid using the still‑forming bar in calculations.
• Second‑based lower timeframes improve granularity for scalping and very short‑term entries. Minute‑based lower timeframes provide broader coverage for intraday and short‑swing contexts.
• Use the Coverage Panel to confirm the true extent of available LTF history on your symbol/plan before drawing conclusions from very deep lookbacks.
Visual Walkthrough
A step‑by‑step image sequence accompanies this description. Each figure demonstrates how the indicator reads LTF volume, locates extrema, builds price‑mapped zones, and updates labels/colors when vertical order requires it.
Chart Interpretation
This chart illustrates two distinct perspectives of the Smart Money Support/Resistance — Lite indicator, each derived from different lookback horizons and lower-timeframe (LTF) resolutions.
1- Short-term view (43 bars, 10-second LTF)
Using the most recent 43 completed bars with 10-second intrabar data, the algorithm detects that both maximum and minimum volume extrema fall within a narrow range. The result is a clearly identified range market: resistance between 178.15–184.55 and support between 175.02–179.38.
The Coverage Panel (bottom-right) confirms the scope of valid input: the lower timeframe used, number of bars covered, and the resulting zones. This short-term scan highlights how the indicator adapts to limited data depth, flagging sideways structure where neither side dominates.
2 - Long-term view (120 bars, 30-second LTF)
Over a wider 120-bar lookback with higher-granularity 30-second data, broader supply and demand zones emerge.
– The long-term resistance zone captures the concentration of buyers and sellers at the upper boundary of recent price history.
– The long-term support zone anchors to the opposite side of the distribution, derived from maxima and minima of both buying and selling pressure.
These zones reflect deeper structural levels where market participants previously committed significant volume.
Combined Perspective
By aligning the short-term and long-term outputs, the chart shows how the indicator distinguishes immediate consolidation (range market) from more durable support and resistance levels derived from extended history. This dual resolution approach makes clear that support and resistance are not static lines but dynamic zones, dependent on both timeframe depth and the resolution of intrabar volume data.
Momentum Volume Analyzer [CHE] Momentum Volume Analyzer — Adaptive momentum with volume-gated signals and expressive visual cues
Summary
This indicator combines a normalized momentum oscillator with a volume Z-score gate and adaptive gradient visuals. The oscillator centers around a midline and scales between a lower and an upper bound. Intensity is derived from the distance to the midline and is normalized inside a rolling window, which helps keep contrast consistent across regimes. Volume pressure is compressed to a discrete level between one and ten and is used to qualify momentum flips and extremes. Layered “burst” markers and optional background gradients provide immediate visual emphasis without adding new data sources. Pine version is v6. The script runs in a separate pane.
Motivation: Why this design?
Common oscillators flip rapidly during noisy conditions or flatten during calm periods, which obscures actionable shifts. A rolling normalization keeps the visual intensity stable across different regimes, and a volume gate reduces reactions when participation is weak. The goal is clearer momentum shifts that are supported by measurable activity rather than cosmetic smoothing alone.
What’s different vs. standard approaches?
Baseline reference: Classical RSI-style oscillators or simple filtered momentum without volume gating.
Architecture differences:
Local window normalization with gamma control for contrast.
Volume converted to a Z-score and compressed into a discrete level between one and ten with a configurable cap.
Directional color gradients that intensify with distance from the midline.
Layered glow markers with optional trail and an internal label budget to avoid UI overload.
Practical effect: Signals are visually stronger only when both momentum and volume align; background and line colors convey regime strength at a glance.
How it works (technical)
Momentum core: A high-pass path with automatic gain control produces a bounded oscillator centered around a midline. A simple moving average smooths the result over a short window.
Normalization and contrast: The absolute distance from the midline is scaled inside a rolling window and limited between zero and one. Two gamma parameters separately shape contrast for the line and for labels.
Coloring: When the oscillator is above the midline, a green gradient is used; below the midline, a red gradient is used. Intensity increases with normalized distance. Optional area fill to the midline and a background gradient reinforce strength.
Volume levels: Volume is standardized over a lookback window, clipped by a user cap, and mapped to a level between one and ten. Only positive excursions are considered; non-positive values map to zero.
Event markers: When the oscillator reaches extreme zones and the volume level is positive, the script spawns layered circular labels at fixed y-positions. A small trail can extend behind the event. An internal queue discards the oldest labels when a user-defined maximum is exceeded.
Alerts: Alerts fire on overbought and oversold spikes, midline shifts with minimum intensity and volume, and continuation patterns inside strong zones.
Parameter Guide
TFRSI length (default six): Core momentum lookback. Shorter values react faster but are less stable.
Signal SMA (default two): Light smoothing of the oscillator. Larger values reduce jitter.
Gradient window (default one hundred): Normalization window for intensity. Longer values produce steadier contrast but slower adaptation.
Line/marker transparency (default zero): Visual prominence of drawings. Higher values reduce dominance.
Background on and BG transparency (defaults true and eighty-five): Enables and tunes the pane background gradient.
Area fill to fifty and Fill transparency (defaults true and eighty): Fills between the oscillator and the midline.
Gamma bars/labels and Gamma plot (defaults zero point seven and zero point eight): Contrast shapers for markers and line. Higher values compress low intensities.
Bottom marker and Show last N (defaults true and three hundred thirty-three): Optional compact heat markers with a display cap.
Up/Down colors: Dark and neon pairs for positive and negative regimes.
Lookback (default two hundred) and Z cap (default five): Volume standardization window and clipping level before scaling to one through ten.
Enable bursts, Layers, Trail, Trail transparency, Max live labels, Size scale: Control the layered glow effect, trail length, opacity, label budget, and size multiplier. Reducing the size scale lowers visual dominance.
Spike min level, Shift min level, Min intensity, Rise/Fall length: Gates for alerts; adjust to balance sensitivity and false positives.
Reading & Interpretation
Line color and intensity: Green shades above the midline indicate bullish pressure; red shades below indicate bearish pressure. Stronger color corresponds to stronger normalized distance.
Background and fill: Reinforce regime strength; consider reducing transparency when the pane feels too busy.
Bursts and trails: Emphasize volume-backed extremes. Larger bursts reflect stronger volume levels or scaling choices.
Volume level: Internal level between one and ten. Levels near the upper bound signal exceptional activity.
Practical Workflows & Combinations
Trend following: Use midline cross upward with minimum shift level and intensity as a trigger. Confirm with structure such as higher highs and higher lows. For shorts, reverse the conditions.
Exits and risk: Fade exposure when intensity weakens toward the midline or when volume level drops below the shift threshold. Consider disabling bursts when monitoring many symbols.
Multi-asset and multi-timeframe: Defaults are designed to travel across liquid futures, large-cap equities, and major crypto pairs. For higher timeframes, increase the lookback window and consider reducing the Z cap.
Behavior, Constraints & Performance
Repaint and confirmation: Signals are evaluated on the live bar. They can appear and withdraw before bar close. For confirmed signals, require closed-bar alerts or manual confirmation.
Higher-timeframe sources: Not used. No `security` calls.
Resources: `max_bars_back` is two thousand. The script uses arrays and label objects, including loops for trails. The label budget mitigates clutter.
Known limits: Very illiquid symbols with unstable volume can reduce the usefulness of the Z-score. Sharp regime changes can still produce brief flips.
Sensible Defaults & Quick Tuning
Starting point: TFRSI length six, Signal two, Gradient window one hundred, Z cap five, Spike level six, Shift level four, Min intensity zero point four, Rise length three, Size scale zero point five.
Too many flips: Increase Signal, increase Gradient window, or raise Shift level.
Too sluggish: Decrease TFRSI length or reduce Gradient window.
Bursts too dominant: Lower Size scale or reduce Layers; increase Trail transparency or set Trail length to zero.
What this indicator is—and isn’t
This is a visualization and signal layer that couples momentum with a volume gate and adaptive visuals. It is not a complete trading system, optimizer, or predictor. Use it together with market structure, risk controls, and position management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
ML-Enhanced Multi-Indicator Composite Signal🤖 ML-Enhanced Multi-Indicator Composite Signal
Revolutionary AI-Powered Trading Indicator with Adaptive Learning
Transform your trading with cutting-edge machine learning technology that automatically optimizes indicator weights based on real market performance!
🎯 What Makes This Indicator Special?
This isn't just another composite indicator. It's an intelligent trading system that learns from market data and continuously adapts to improve signal accuracy. Unlike static indicators with fixed weights, this AI-powered tool dynamically adjusts the importance of each technical indicator based on their actual prediction success rates.
⚡ Key Features
🤖 Adaptive Machine Learning Engine
Automatically tracks prediction accuracy for each indicator
Dynamically adjusts weights based on performance
Continuous learning and adaptation to market conditions
Configurable learning parameters for fine-tuning
📊 Multi-Indicator Fusion
SuperTrend: Trend direction and momentum
Moving Averages: Price trend confirmation (SMA/EMA/WMA/RMA)
VWAP: Volume-weighted price levels
Linear Regression: Mathematical trend analysis
🎯 Intelligent Signal Generation
Strong Buy/Buy/Sell/Strong Sell signals
Configurable threshold levels
Signal smoothing to reduce noise
Smart signal timing to avoid repetitive alerts
📈 Performance Analytics Dashboard
Real-time accuracy tracking for each indicator
Weight distribution visualization
ML vs. Equal weights comparison
Learning progress monitoring
🚀 How It Works
1. Data Collection Phase
The indicator continuously monitors the performance of each technical component, storing predictions and actual market outcomes.
2. Learning Phase
Using configurable learning periods (20-500 bars), the ML engine calculates accuracy rates for each indicator's predictions.
3. Weight Optimization
Based on performance data, the system automatically adjusts weights using a configurable learning rate, ensuring better-performing indicators have more influence.
4. Signal Generation
The optimized composite signal triggers buy/sell alerts when crossing predefined thresholds, with visual signals and background coloring.
⚙️ Customization Options
Machine Learning Parameters
Learning Period: 20-500 bars (default: 100)
Prediction Horizon: 1-20 bars (default: 5)
Learning Rate: 0.01-1.0 (default: 0.1)
Minimum Weight: Prevents any indicator from becoming irrelevant
Performance Smoothing: Reduces noise in accuracy calculations
Traditional Settings
SuperTrend: Period and multiplier adjustment
Moving Average: Type selection and length
VWAP: Source customization
Linear Regression: Length and source options
Signal Configuration
Threshold Levels: Customizable buy/sell trigger points
Signal Smoothing: Reduces false signals
Manual Override: Option to use fixed weights instead of ML
📱 Visual Features
Signal Line Display
Dynamic color coding based on signal strength
Threshold level lines for clear entry/exit points
Background coloring for quick market sentiment assessment
Performance Table
Real-time accuracy metrics for each indicator
Current weight distribution showing ML optimization
Performance comparison between ML and equal weights
Learning progress indicator
Signal Shapes
🚀 Strong Buy: Large green triangle with text
📈 Buy: Standard green triangle
📉 Sell: Standard red triangle
💥 Strong Sell: Large red triangle with text
🎓 Best Practices & Usage Tips
For Beginners
Start with default ML settings
Allow 100+ bars for proper learning
Focus on Strong Buy/Sell signals initially
Monitor the performance table to understand ML adaptation
For Advanced Traders
Adjust learning rate based on market volatility
Customize prediction horizon for your trading timeframe
Fine-tune threshold levels for your risk tolerance
Combine with additional confirmation indicators
Recommended Settings by Timeframe
Scalping (1m-5m): Learning Period: 50, Prediction Horizon: 3
Day Trading (15m-1h): Learning Period: 100, Prediction Horizon: 5
Swing Trading (4h-1D): Learning Period: 200, Prediction Horizon: 10
🔔 Alert System
Set up comprehensive alerts for:
Strong Buy/Sell signals with maximum consensus
Regular Buy/Sell signals for standard entries
Custom message templates with price and signal strength
Email, SMS, and webhook compatibility
⚠️ Important Notes
Learning Period: Allow sufficient data for ML optimization (minimum 50 bars recommended)
Market Conditions: Performance may vary during high volatility or trending vs. ranging markets
Backtesting: Test thoroughly on historical data before live trading
Risk Management: Always use proper position sizing and stop losses
🏆 Why Choose This Indicator?
✅ Adaptive Intelligence: Unlike static indicators, this tool evolves with market conditions
✅ Transparent Performance: See exactly how well each component is performing
✅ Comprehensive Analytics: Make informed decisions with detailed performance metrics
✅ Professional Grade: Developed by experienced traders for serious market participants
✅ Continuous Innovation: Regular updates and improvements based on user feedback
📊 Performance Tracking
The indicator provides unprecedented transparency into its decision-making process:
Individual indicator accuracy rates
Weight evolution over time
Improvement metrics vs. baseline
Learning curve visualization
Transform your trading with the power of adaptive machine learning. Let the market data guide your strategy optimization automatically!
Tags: Machine Learning, AI Trading, Composite Signal, Multi-Indicator, Adaptive Algorithm, Signal Generation, Trading Automation, Technical Analysis
Category: Trend Following, Oscillators, Signal Generators
Baseline Buy/Sell Alerts (v6) - FixedGood for indexes,metals and cryptos
Thanks Universe Thanks Angels
NY 14:30 High/Low - 1mThis indicator automatically draws horizontal lines for the High (green) and Low (red) of the 14:30 (Lisbon) candle on the 1-minute chart.
It is designed for traders who want to quickly identify the New York open levels (NY Open), allowing you to:
Visualize the NY market opening zone.
Use these levels as intraday support or resistance.
Plan entries and exits based on breakouts or pullbacks.
Features:
Works on any 1-minute chart.
Lines are drawn immediately after the 14:30 candle closes.
Lines extend automatically to the right.
Simple and lightweight, no complex variables or external dependencies.
Daily reset, always showing the current day’s levels.
Recommended Use:
Combine with support/resistance zones, order blocks, or fair value gaps.
Monitor price behavior during the NY open to identify breakout or rejection patterns.
ORB 15m + MAs (v4.1)Session ORB Live Pro — Pre-Market Boxes & MA Suite (v4.1)
What it is
A precision Opening Range Breakout (ORB) tool that anchors every session to one specific 15-minute candle—then projects that same high/low onto lower timeframes so your 1m/5m levels always match the source 15m bar. Perfect for scalpers who want session structure without drift.
What it draws
Asia, Pre-London, London, Pre-New York, New York session boxes.
On 15m: only the high/low of the first 15-minute bar of each window (optionally persists for extra bars).
On 5m: mirrors the same 15m range, visible up to 10 bars.
On 1m: mirrors the same 15m range, visible up to 15 bars.
Levels update live while the 15m candle is forming, then lock.
Fully editable windows (easy UX)
Change session times with TradingView’s native input.session fields using the familiar format HHMM-HHMM:1234567. You can tweak each window independently:
Asia
Pre-London
London
Pre-New York
New York
Multi-TF logic (no guesswork)
Designed to show only on 1m, 5m, 15m (by default).
15m = ground truth. Lower timeframes never “recalculate a different range”—they mirror the 15m bar for that session, exactly.
Alerts
Optional breakout alerts when price closes above/below the session range.
Clean visuals
Per-session color controls (box + lines). Boxes extend only for the configured number of bars per timeframe, keeping charts uncluttered.
Built-in MA suite
SMA 50 and RMA 200.
Three extra MAs (SMA/EMA/RMA/WMA/HMA) with selectable color, width, and style (line, stepline, circles).
Why traders like it
Consistency: Lower-TF ranges always match the 15m source bar.
Speed: You see structure immediately—no waiting for N bars.
Control: Edit session times directly; tune how long boxes stay on chart per TF.
Clarity: Minimal, purposeful plotting with alerts when it matters.
Quick start
Set your session times via the five input.session fields.
Choose how long boxes persist on 1m/5m/15m.
Enable alerts if you want instant breakout notifications.
(Optional) Configure the MA suite for trend/bias context.
Best for
Intraday traders and scalpers who rely on repeatable session behavior and demand exact cross-TF alignment of ORB levels.
Cost Basis of DCA Strategy (Enhanced)“Cost Basis of DCA Strategy (Enhanced): An Analytical Tool for Smarter DCA Investing”
The indicator designed here serves as a comprehensive analytical tool for evaluating a Dollar-Cost Averaging (DCA) strategy. Instead of merely recording scattered buy transactions, it integrates all purchases into a clear framework that reveals the real cost basis, portfolio performance, and capital allocation. Its primary function is to transform the concept of DCA from a mechanical process into a measurable and strategic decision-making system.
At the foundation of its operation, the user provides essential inputs such as the initial capital, the price and size of each buy transaction, and an optional sell price for hypothetical exit scenarios. With these inputs, the indicator calculates how many units were acquired in total, how much money was spent, and what the average cost per unit—the cost basis—truly is. This cost basis acts as the anchor for evaluating whether the market price has moved in favor or against the investor’s average entry point.
Beyond this, the indicator goes further by calculating both realized and unrealized dimensions of performance. It presents the current market value of holdings based on live price data and contrasts it with the total cost to derive unrealized profit or loss in both absolute terms and percentages. If the user sets a sell price, the tool simulates a full liquidation scenario, displaying the expected profit or loss should all holdings be sold at that level. This dual perspective enables the user to examine their strategy both from a present-value standpoint and a forward-looking one.
In addition, the indicator keeps track of remaining capital—the portion of initial funds not yet deployed into purchases—thus bridging the gap between portfolio construction and financial planning. It also reports the number of buy transactions, reinforcing awareness of execution discipline in DCA.
For visualization, the system is not confined to numbers alone. It marks each buy price directly on the price chart with distinct horizontal lines, labeled for clarity. This allows the trader to see not just statistics in a table but also the spatial relationship between historical entry points and ongoing market dynamics.
In essence, this indicator reframes the practice of DCA into a structured analytical exercise. It empowers investors to understand the true average entry cost, evaluate ongoing performance, and simulate future outcomes under different price scenarios. By doing so, it elevates DCA from a passive habit into an active, data-driven investment methodology, allowing users to make more informed, confident, and strategically grounded decisions.
Lakshmi - Vajra Energy Signal (VES)Vajra Energy Signal (VES) is an advanced volume analysis indicator that detects energy accumulated inside the market.
When assessing the strength of trading activity, conventional practice looks at the magnitude of volume; VES is designed with the understanding that the same volume can have different meanings depending on the price range.
VES analyzes the complex relationship between price movement and volume with a proprietary algorithm and can detect internal market activities that are invisible from surface‑level price action, visualizing the characteristic whereby the value rises before a breakout.
In other words, VES views the market as an “energy system.” In the energy accumulation phase, relatively high volume occurs relative to the price range, and in the energy release phase, the stored energy is emitted as high volatility in price, that is, a breakout—this is the core concept on which VES is established.
⚡️ Basic Demonstration
i.imgur.com
As you can see in the image above, VES simply displays the highs and lows of energy stored in the market as a thin line in a separate panel.
It is easy for traders to understand its intuitive patterns: it rises when hidden buying accumulation or selling activity continue and sink when a price breakout occurs. It can be applied across symbols and markets (stocks, commodities, cryptocurrencies, spot, and futures). While reducing clutter in price scale labels, it also supports dynamic autoscaling.
⚡️ Practical Usage
VES is expected to be used for the following purposes.
- Entry signal
When the VES value continues to rise—i.e., during energy accumulation—it can be considered on standby for a breakout. After a breakout, a trader can confirm the trend direction and enter.
- Exit signal
If the VES value rises during a trend, consider the possibility of a reversal and consider taking profits.
- Risk management
If the VES value remains elevated for a long period, regard it as increased market uncertainty and an approaching breakout; adopt a cautious trading strategy to prepare for higher volatility and adjust position size.
For example, in the BINANCE:SOLUSDT daily chart below, VES clearly shows how it functions in short‑term trading.
i.imgur.com
In September 2023, when the price was moving around 20 USDT, VES formed frequent small spikes. These early spikes suggest that market participants were still in a wait‑and‑see mode and that small‑scale accumulation was being conducted intermittently.
A decisive change came in early October 2023. While the price still stagnated in the 20–25 USDT range, VES suddenly formed a huge spike. The scale of this spike was far larger than those in September 2023, clearly suggesting that hidden substantial trading activities by large investors had begun.
In mid‑October 2023, the price began to rise. It climbed stepwise from 25 USDT to 40 USDT, then to 60 USDT and 75 USDT, and then surged to above 120 USDT within just a few weeks. This suggests that the energy built in the buy accumulation phase in early October 2023 was converted into price appreciation.
Therefore, after such a large VES signal is observed and the price breaks upward, entering a long position could have been profitable.
A large VES reaction is not only a quiet “buy signal” as in the example above; it can also be a “sell signal.” Such a case is explained below using an example on the BTC chart.
i.imgur.com
This BITSTAMP:BTCUSD 4‑hour chart is a valuable example showing how VES detects top formation on a short timeframe. In the first half of February 2024, the price moved in a relatively narrow 96,000–99,000 USD range. During this period, VES remained stable at low levels, and the market continued a calm uptrend.
The first sign appeared on February 16, 2024. While the price still held around 97,000 USD, VES formed a clearly identifiable small spike. This implied that some large investors had begun to take profits, or that new sellers had started to build short positions. However, at that point, the impact on price was limited, and many traders may have overlooked the signal.
The decisive turning point came on February 23, 2024. With the price moving around 98,000 USD, VES suddenly formed a huge spike. The scale of this spike was far larger than previous moves, clearly indicating that significant energy was accumulating.
Importantly, even at this moment the price still remained at the highs. On the surface, price barely moved and the bull trend appeared intact, but VES detected a major internal change underway.
On February 24, 2024, the price collapsed and began to fall. It dropped about 15% from 97,000 USD to 82,000 USD in a few days. The speed and magnitude of this decline corroborated the quiet “sell signal” indicated by the VES spikes.
The key lesson from this chart is that a VES spike does not necessarily mean buy accumulation. A large VES spike formed at high prices may instead indicate a distribution phase—that is, large investors exiting or building short positions. When the price is at elevated levels, a VES spike should be considered not only as a precursor to further upside but also as a warning of potential downside.
From a trading‑strategy perspective, the huge VES spike on February 23, 2024 was a clear signal to exit or to consider entering short positions. At that point, traders should have either closed long positions or to consider building a short position. The moment when price started to decline from its peak was exactly the entry timing for a short.
On the 4‑hour timeframe, changes in VES appear faster and more dramatically. While this allows more agile responses, the risk of false signals is also higher; therefore, confirmation on other timeframes and comprehensive judgment with price action are essential.
VES is a powerful tool for reading internal market activities, and this chart clearly shows that its interpretation requires flexibility that takes into account market conditions and price location.
⚡️ Parameter Settings
Strength 1: The lower the number, the more it emphasizes responses closer to the present timeframe; the higher the number, the more it emphasizes responses farther from the present timeframe. 5 is recommended.
Strength 2: The lower the number, the greater the volatility of the value; the higher the number, the smaller the volatility. 5 is recommended.
Scale: Adjusts the display scale. −30 is recommended.
⚡️ Conclusion
Vajra Energy Signal (VES) visualizes the cycle of energy accumulation in the market from the relative relationship between price range and volume, detecting hidden activities by market participants that conventional volume analysis cannot capture. VES serves as a powerful auxiliary tool for early detection of turning points, enabling deeper market understanding and more accurate timing decisions. As the examples show, there is a possibility of sensing major price movements in advance. When using VES, flexible interpretation according to market environment and price location is required, and it demonstrates its true value when combined with price action and other analysis methods such as support/resistance.
⚡️ Important Notes
- VES is a tool that infers internal market energy; it does not guarantee trades or suggest future results.
- We strongly recommend using it together with price action analysis and support/resistance.
- Confirmation across different timeframes improves reliability.
- Effectiveness may vary depending on market conditions and liquidity.
- Very illiquid instruments or newly listed assets may produce more noise.
⚡️ How to Get Access
This indicator is Public Invite‑Only. If you would like access, please apply by following the Author’s Instructions.
Session ORB 15m Synced + Pre-Sessions + MAs (final v3)Session ORB Live Pro — Pre-Market Boxes & MA Suite
Description (EN):
Session ORB Live Pro is a Pine v6 indicator built for intraday traders who rely on Opening Range Breakouts. It draws session boxes for London, New York, and Asia—plus configurable Pre-London and Pre-New York windows—live from the very first candle (no waiting for 10 bars). The high/low levels update in real time, and optional breakout alerts fire the moment price closes beyond the range. To keep charts clean and relevant for scalping, the boxes auto-hide on chart timeframes above 20 minutes.
Beyond ranges, the tool adds a compact moving-average suite: SMA-50 and RMA-200 out of the box, plus three fully customizable MAs (SMA/EMA/RMA/WMA/HMA) with selectable color, thickness, and style (line, stepline, circles). Each session and pre-session can be toggled on/off and tinted with its own color, so you can tailor the visual map of liquidity grabs and range breaks to your strategy.
Key features
Live ORB boxes for London, New York, Asia (no 10-bar delay).
Pre-sessions: Pre-London & Pre-New York with independent time windows and colors.
Auto visibility filter: boxes show only on ≤ 20m chart TF; hidden on higher TFs.
Breakout alerts when price closes above/below the session range (ready for alert() rules).
MA toolkit: SMA-50, RMA-200 + 3 user MAs (SMA/EMA/RMA/WMA/HMA) with color, style, and width.
Clean inputs using input.session; robust, low-friction UX.
How to use
Set your ORB calculation timeframe (e.g., 15m) and choose which sessions/pre-sessions to display.
Pick colors for each box and enable alerts if you want instant breakout notifications.
Configure the MA suite for trend bias and dynamic S/R (e.g., SMA-50 for momentum, RMA-200 for bias).
Trade the first clean break or the retest of the ORB extremes—your choice. The visual map updates tick by tick.
ORB Storico + Box Multipli + Notifiche (final clean v2)Session ORB Live Pro — Pre-Market Boxes & MA Suite
Description (EN):
Session ORB Live Pro is a Pine v6 indicator built for intraday traders who rely on Opening Range Breakouts. It draws session boxes for London, New York, and Asia—plus configurable Pre-London and Pre-New York windows—live from the very first candle (no waiting for 10 bars). The high/low levels update in real time, and optional breakout alerts fire the moment price closes beyond the range. To keep charts clean and relevant for scalping, the boxes auto-hide on chart timeframes above 20 minutes.
Beyond ranges, the tool adds a compact moving-average suite: SMA-50 and RMA-200 out of the box, plus three fully customizable MAs (SMA/EMA/RMA/WMA/HMA) with selectable color, thickness, and style (line, stepline, circles). Each session and pre-session can be toggled on/off and tinted with its own color, so you can tailor the visual map of liquidity grabs and range breaks to your strategy.
Key features
Live ORB boxes for London, New York, Asia (no 10-bar delay).
Pre-sessions: Pre-London & Pre-New York with independent time windows and colors.
Auto visibility filter: boxes show only on ≤ 20m chart TF; hidden on higher TFs.
Breakout alerts when price closes above/below the session range (ready for alert() rules).
MA toolkit: SMA-50, RMA-200 + 3 user MAs (SMA/EMA/RMA/WMA/HMA) with color, style, and width.
Clean inputs using input.session; robust, low-friction UX.
How to use
Set your ORB calculation timeframe (e.g., 15m) and choose which sessions/pre-sessions to display.
Pick colors for each box and enable alerts if you want instant breakout notifications.
Configure the MA suite for trend bias and dynamic S/R (e.g., SMA-50 for momentum, RMA-200 for bias).
Trade the first clean break or the retest of the ORB extremes—your choice. The visual map updates tick by tick.
DHYT Moon Cycles IndicatorThis indicator tracks the moon cycles which seem to correlate with bullish and bearish periods for Cryptocurrency trading. This indicator allows you to calibrate these windows using recent moon phase dates and times. You can also add customizable highlighted bands before and after these events to highlight these bullish and bearish periods.
Created by: Dan Heilman
OPEN = LOW + VWAP + Volume SurgeTradingView Pine Script that scans for OPEN = LOW, confirms VWAP support, and checks for volume surge — tailored for your intraday breakout strategy
X Trend dashboard (Lite)X Trend Dashboard
The X Trend Dashboard provides an instant snapshot of market sentiment by analyzing the aggregate "pressure" from 11 classic technical indicators. This version features a flexible EMA Fan (Fast, Medium, and Slow EMAs) instead of fixed timeframes, allowing for greater adaptability to any chart.
This tool is ideal for quickly assessing current market strength and identifying moments when bulls or bears are in control. The panel also displays the asset's correlation with BTC and ETH for additional market context.
Settings
Dashboard Settings: Change the panel's appearance and position.
Correlation Settings: Configure the BTC and ETH correlation.
Indicator Components: Enable or disable any of the indicators, including the three customizable EMAs, to tailor the pressure calculation to your trading style.
G. Santostasi Bitcoin Power Law Monte Carlo IndicatorOverview:
The "G. Santostasi Bitcoin Power Law Monte Carlo" is a sophisticated TradingView indicator inspired by the Bitcoin Power Law Theory developed by physicist Giovanni Santostasi.
This theory posits that Bitcoin's price follows a power-law relationship with time, measured in days since the Bitcoin Genesis Block (January 3, 2009). The indicator leverages this framework to analyze Bitcoin's price dynamics through a normalized metric called "Daily Slopes," which captures local deviations from the long-term power-law trend. By fitting these Daily Slopes to a t-location scale distribution on a moving window, the indicator computes key parameters (mu, sigma, and nu) and plots them along with deviation bands. This allows traders to identify local minima and maxima in price action relative to the global power-law slope of approximately 5.9.Additionally, the indicator incorporates Monte Carlo simulations to project potential future price paths up to 100 days ahead, generating up to 500 randomized trajectories based on the statistical properties of the Daily Slopes. This tool is particularly useful for understanding Bitcoin's inherent diminishing returns, assessing market stability, and forecasting short-term scenarios while emphasizing the asset's long-term predictability as a self-organizing network akin to natural systems.
The indicator does not predict exponential growth but instead highlights Bitcoin's scale-invariant behavior, where returns diminish predictably over time—a feature, not a bug, of its design. It has been observed that the core metric (mu) remains stable across Bitcoin's entire history, reinforcing the power law as Bitcoin's "DNA."
Core Concept: Daily Slopes:
At the heart of the indicator is the "Daily Slopes" metric, which normalizes daily logarithmic returns to account for the diminishing nature predicted by the power-law model. This normalization reveals a stable "local slope" (n) that oscillates around a fixed global value, providing insight into Bitcoin's consistent behavior over time.
Definition and Calculation:
Daily logarithmic returns are calculated as log(P2/P1)\log(P_2 / P_1)\log(P_2 / P_1), where P2P_2P_2 is the current day's closing price and P1P_1P_1 is the previous day's closing price.
According to the power-law model, if Bitcoin's price ( P(t) ) follows P(t)=c⋅tnP(t) = c \cdot t^nP(t) = c \cdot t^n
(where ( t ) is days since the Genesis Block, ( c ) is a constant, and n≈5.9n \approx 5.9n \approx 5.9
is the global slope from log-log regression), then the expected daily log return is n⋅log((t+1)/t)n \cdot \log((t+1)/t)n \cdot \log((t+1)/t)
.
The Daily Slope is thus the normalized value:
Daily Slope=log(P2/P1)log((t+1)/t)\text{Daily Slope} = \frac{\log(P_2 / P_1)}{\log((t+1)/t)}\text{Daily Slope} = \frac{\log(P_2 / P_1)}{\log((t+1)/t)}
This normalization "stabilizes" the returns by dividing out the theoretical decay factor log((t+1)/t)\log((t+1)/t)\log((t+1)/t)
, which diminishes as ( t ) increases (reflecting slower growth in mature systems).
Result: The Daily Slope represents a "local n" that should remain stable, oscillating around the global slope of ~5.9 without long-term drift. Empirical data shows this stability holds over Bitcoin's 16-year history, with oscillations but no systematic change—indicating Bitcoin has statistically "done the same thing" since inception.
Interpretation:
Positive deviations (Daily Slope > 5.9) signal bullish momentum or potential local maxima.
Negative deviations (Daily Slope < 5.9) indicate bearish pressure or local minima.
The metric adjusts for absolute volatility, which appears to decrease over time due to diminishing returns. However, when normalized via Daily Slopes, relative volatility has been constant for the last 8 years, underscoring Bitcoin's resilience to macroeconomic factors.
Distribution Fitting and Parameter Estimation:
To quantify the behavior of Daily Slopes, the indicator fits them to a t-location scale distribution (Student's t-distribution with location and scale parameters) over a user-configurable moving window (e.g., 365 days for annual analysis).
This distribution is chosen as the best empirical fit for the heavy-tailed, outlier-prone nature of Bitcoin's normalized returns, outperforming alternatives like Gaussian or Laplacian.t-Location Scale Distribution:
The distribution is parameterized by:μ (mu): Location parameter, representing the mean or "average slope." This is the most critical metric, stable around 5.9 across Bitcoin's history. It tracks the central tendency of Daily Slopes and signals overall market regime (e.g., rising mu indicates strengthening momentum).
σ (sigma): Scale parameter, akin to standard deviation, measuring the spread or volatility of slopes. It has shown slight increases in certain contexts (e.g., hash rate applications) but remains stable for price data.
ν (nu): Degrees of freedom, controlling the "tailedness" (lower ν means heavier tails, capturing extreme events like bubbles or crashes).
Fitting is performed on a rolling basis, updating μ, σ, and ν dynamically.
Plotting:
Local μ: Plotted as a central line, showing the moving average slope.
Deviation Bands: μ + σ (upper band) and μ - σ (lower band), highlighting 1-standard-deviation ranges.
These bands help identify overbought/oversold conditions by measuring deviations from the global mean of 5.9.
For example:
Crossing above μ + σ may signal a local maximum (potential sell opportunity).
Dipping below μ - σ could indicate a local minimum (buy signal).
Additional visualizations include raw Daily Slopes (oscillating series) and smoothed averages for clarity.
Stability and Insights:μ has remained remarkably stable over 16 years, oscillating without drift, validating the power law's predictive power.
Parameters may show minor trends in rolling windows (e.g., slight σ increases), but no monotonic drift is observed in price data. This stability extends to related metrics like addresses and hash rate, where Daily Slopes can be derived similarly (e.g., via log(A2/A1) / log((t+1)/t) for addresses, yielding equivalent slopes around 5.9).
Monte Carlo Simulations for Future Projections
The indicator enables short-term forecasting (up to 100 days) by reversing the normalization process and simulating paths using the fitted distribution.
Projection Mechanism:
Recover expected daily returns: Multiply the sampled Daily Slope (drawn from the t-location scale distribution with current μ, σ, ν) by log((t+1)/t)\log((t+1)/t)\log((t+1)/t)
.
Generate randomized samples to create up to 500 Monte Carlo paths, incorporating the distribution's properties to model uncertainty (e.g., heavy tails for rare events).
Simulations can use the full historical dataset for broader spreads or recent windows (e.g., last 8 years) for tighter, regime-specific forecasts.
Output: Fan chart of projected prices, showing median path (based on μ), confidence intervals (e.g., ±σ bands), and extreme scenarios.
Applications and Limitations:
Useful for risk assessment, e.g., probability of reaching $200K in 2025 is low (1-2% per recent simulations).
Assumes parameters evolve minimally; if drift is detected, simulations can adjust dynamically.
Not for long-term predictions (beyond 100 days), as the power law excels in multi-year trends rather than short-term noise.
Empirical validation: Simulations align with historical backtests, where deviations (bubbles/crashes) revert to the power-law trend.
Usage Notes Inputs:
Customize moving window size, number of Monte Carlo paths (default: 500), projection horizon (up to 100 days), and global slope (default: 5.9).
Visuals: Overlay on BTCUSD log-log chart for context; bands and simulations appear in separate panels.
Caveats: This is not financial advice. The power law describes emergent behavior from network effects, not guarantees. Cycles and bubbles are secondary deviations, not core to the model.
Extensions: The concept applies beyond price (e.g., to addresses or hash rate), revealing interconnected power laws in Bitcoin's ecosystem.
This indicator transforms Santostasi's theoretical insights into a practical tool, empowering users to navigate Bitcoin's dynamics with statistical rigor.
Premarket Power MovePremarket Power Move is an intraday research tool that tracks what happens after strong premarket or opening gaps.
📊 Core Idea
• When a stock opens +X% above the prior close, it often attracts momentum traders.
• This script measures whether the stock continues to follow through higher or instead fades back down within the first trading hour.
• It calculates:
• The probability of a post-gap rally vs. a drawdown
• Average and maximum retracements after the surge
• Event-day hit rate (how many days actually triggered the condition)
🎯 Use Cases
• Identify “gap-and-go” opportunities where strong premarket strength leads to further gains.
• Spot potential fade setups where early enthusiasm quickly reverses.
• Backtest your intraday strategies with objective statistics instead of gut feeling.
⚙️ Features
• Customizable thresholds for premarket/open surge (%) and follow-through window (minutes).
• Marks the chart with reference lines:
• Prior close
• Surge threshold (e.g. +6%)
• Intraday high/low used for probability calculations.
• Outputs summary statistics (probabilities, averages, counts) directly on the chart.
🔔 Note
This is not a buy/sell signal generator. It is a probability and behavior analysis tool that helps traders understand how often strong premarket gaps continue vs. fade.
Golden/Death Cross with SMAGolden Cross: Triggered when the 50 SMA crosses above the 200 SMA.
Death Cross: Triggered when the 50 SMA crosses below the 200 SMA.
Weekly Volume ChangeWeekly Volume Change %
See weekly volume trends at a glance! This indicator shows current vs. previous week’s volume, calculates percent change, and highlights increases (green) or decreases (red). Features customizable look-back weeks and table color for easy visualization.
Trey London + NY Open Alerts + Session LinesThis is a indicator that alerts you when London & New York opens everyday of the week.
Instructions are included if any confusion:
- Adjust Timezones:
UTC Offset
Change this if your broker’s chart is in a different timezone.
Example: 2 for UTC+2 (default).
- Enable / Disable Alerts:
Visual Alerts (Labels) they only go 10 executions back
Toggle On/Off to show labels above/below candles.
Sound Alerts
Toggle On/Off to play an alert sound when a session starts
- Using Alerts:
Go to TradingView Alerts (⏰).
Create a new alert and select:
Condition: London Open or New York Open
Action: Show pop-up, play sound, or send notification.
Alerts will trigger exactly at the session start.
Expiration: set the date as far back as you can and the time to around 23:00. You will have renew the alert after Expiration or update it to a later time.
should me a little green clock beside the indicator
- AMD:
comes with zones in London and new York time everyday and the previous day gets deleted.
Adjust Timezones, UTC Offset
Change this if your broker’s chart is in a different timezone.
Example: 2 for UTC+2 (default).
(These things may be upgraded in the future if subscription is upgraded.)
