Signals PridictorSignals Predictor is a powerful, next-generation technical indicator built upon advanced algorithms Designed for traders who seek clarity, reliability, and dynamic insights, this indicator predicts price movement directions with high accuracy, enhancing decision-making and trading efficiency.
Key Features
Dynamic Signal Entries & Exits:
Utilizes customizable ATR-based dynamic exits and time-based strict exits, allowing traders to adapt strategies to changing market conditions.
Candle Coloring:
Candles dynamically color green for bullish conditions and red for bearish conditions, offering instant visual feedback on the prevailing market sentiment.
Trade Performance Table:
Includes a built-in real-time performance statistics table, tracking total trades, win rate, profit ratio, and early signal flips, which helps traders quickly assess strategy effectiveness.
How to Use
Entry Signals:
Green Label (▲+): Indicates a strong bullish (buy) signal.
Red Label (▼+): Indicates a strong bearish (sell) signal.
Exit Signals:
Small cross (×) represents recommended trade exits.
Visual Confirmation:
Kernel Regression Estimate Line visually confirms the underlying trend strength.
Candle colors reinforce the trend direction—green for bullish, red for bearish.
Who Should Use Signals Predictor?
Day Traders
Swing Traders
Trend-Following Traders
Technical Analysts
Recommended Usage
Combine with price action, support & resistance levels, and trend analysis for maximum reliability.
Optimal results when used on major forex pairs, indices, commodities, and cryptocurrencies.
Disclaimer
Signals Predictor is intended as an analysis tool to complement your trading strategy. Always apply proper risk management and never rely solely on one indicator.
#indicator
#tradingindicator
#technicalanalysis
#algotrading
#tradingtools
#forexindicator
#stockmarket
#cryptotrading
Kitaran
Order Flow Hawkes Process [ScorsoneEnterprises]This indicator is an implementation of the Hawkes Process. This tool is designed to show the excitability of the different sides of volume, it is an estimation of bid and ask size per bar. The code for the volume delta is from www.tradingview.com
Here’s a link to a more sophisticated research article about Hawkes Process than this post arxiv.org
This tool is designed to show how excitable the different sides are. Excitability refers to how likely that side is to get more activity. Alan Hawkes made Hawkes Process for seismology. A big earthquake happens, lots of little ones follow until it returns to normal. Same for financial markets, big orders come in, causing a lot of little orders to come. Alpha, Beta, and Lambda parameters are estimated by minimizing a negative log likelihood function.
How it works
There are a few components to this script, so we’ll go into the equation and then the other functions used in this script.
hawkes_process(params, events, lkb) =>
alpha = clamp(array.get(params, 0), 0.01, 1.0)
beta = clamp(array.get(params, 1), 0.1, 10.0)
lambda_0 = clamp(array.get(params, 2), 0.01, 0.3)
intensity = array.new_float(lkb, 0.0)
events_array = array.new_float(lkb, 0.0)
for i = 0 to lkb - 1
array.set(events_array, i, array.get(events, i))
for i = 0 to lkb - 1
sum_decay = 0.0
current_event = array.get(events_array, i)
for j = 0 to i - 1
time_diff = i - j
past_event = array.get(events_array, j)
decay = math.exp(-beta * time_diff)
past_event_val = na(past_event) ? 0 : past_event
sum_decay := sum_decay + (past_event_val * decay)
array.set(intensity, i, lambda_0 + alpha * sum_decay)
intensity
The parameters alpha, beta, and lambda all represent a different real thing.
Alpha (α):
Definition: Alpha represents the excitation factor or the magnitude of the influence that past events have on the future intensity of the process. In simpler terms, it measures how much each event "excites" or triggers additional events. It is constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)). A higher alpha means past events have a stronger influence on increasing the intensity (likelihood) of future events. Initial value is set to 0.1 in init_params. In the hawkes_process function, alpha scales the contribution of past events to the current intensity via the term alpha * sum_decay.
Beta (β):
Definition: Beta controls the rate of exponential decay of the influence of past events over time. It determines how quickly the effect of a past event fades away. It is constrained between 0.1 and 10.0 (e.g., clamp(array.get(params, 1), 0.1, 10.0)). A higher beta means the influence of past events decays faster, while a lower beta means the influence lingers longer. Initial value is set to 0.1 in init_params. In the hawkes_process function, beta appears in the decay term math.exp(-beta * time_diff), which reduces the impact of past events as the time difference (time_diff) increases.
Lambda_0 (λ₀):
Definition: Lambda_0 is the baseline intensity of the process, representing the rate at which events occur in the absence of any excitation from past events. It’s the "background" rate of the process. It is constrained between 0.01 and 0.3 .A higher lambda_0 means a higher natural frequency of events, even without the influence of past events. Initial value is set to 0.1 in init_params. In the hawkes_process function, lambda_0 sets the minimum intensity level, to which the excitation term (alpha * sum_decay) is added: lambda_0 + alpha * sum_decay
Alpha (α): Strength of event excitation (how much past events boost future events).
Beta (β): Rate of decay of past event influence (how fast the effect fades).
Lambda_0 (λ₀): Baseline event rate (background intensity without excitation).
Other parts of the script.
Clamp
The clamping function is a simple way to make sure parameters don’t grow or shrink too much.
ObjectiveFunction
This function defines the objective function (negative log-likelihood) to minimize during parameter optimization.It returns a float representing the negative log-likelihood (to be minimized).
How It Works:
Calls hawkes_process to compute the intensity array based on current parameters.Iterates over the lookback period:lambda_t: Intensity at time i.event: Event magnitude at time i.Handles na values by replacing them with 0.Computes log-likelihood: event_clean * math.log(math.max(lambda_t_clean, 0.001)) - lambda_t_clean.Ensures lambda_t_clean is at least 0.001 to avoid log(0).Accumulates into log_likelihood.Returns -log_likelihood (negative because the goal is to minimize, not maximize).
It is used in the optimization process to evaluate how well the parameters fit the observed event data.
Finite Difference Gradient:
This function calculates the gradient of the objective function we spoke about. The gradient is like a directional derivative. Which is like the direction of the rate of change. Which is like the direction of the slope of a hill, we can go up or down a hill. It nudges around the parameter, and calculates the derivative of the parameter. The array of these nudged around parameters is what is returned after they are optimized.
Minimize:
This is the function that actually has the loop and calls the Finite Difference Gradient each time. Here is where the minimizing happens, how we go down the hill. If we are below a tolerance, we are at the bottom of the hill.
Applied
After an initial guess the parameters are optimized with a mix of bid and ask levels to prevent some over-fitting for each side while keeping some efficiency. We initialize two different arrays to store the bid and ask sizes. After we optimize the parameters we clamp them for the calculations. We then get the array of intensities from the Hawkes Process of bid and ask and plot them both. When the bids are greater than the ask it represents a bullish scenario where there are likely to be more buy than sell orders, pushing up price.
Tool examples:
The idea is that when the bid side is more excitable it is more likely to see a bullish reaction, when the ask is we see a bearish reaction.
We see that there are a lot of crossovers, and I picked two specific spots. The idea of this isn’t to spot crossovers but avoid chop. The values are either close together or far apart. When they are far, it is a classification for us to look for our own opportunities in, when they are close, it signals the market can’t pick a direction just yet.
The value works just as well on a higher timeframe as on a lower one. Hawkes Process is an estimate, so there is a leading value aspect of it.
The value works on equities as well, here is NASDAQ:TSLA on a lower time frame with a lookback of 5.
Inputs
Users can enter the lookback value and timeframe.
No tool is perfect, the Hawkes Process value is also not perfect and should not be followed blindly. It is good to use any tool along with discretion and price action.
REW - CNTThis indicator combines RSI(14), EMA(9), and WMA(45) to generate crossover signals. A green arrow appears when RSI crosses above EMA and EMA is below WMA, indicating a potential upward trend. A red arrow signals a possible downtrend when RSI crosses below EMA and EMA is above WMA.
EMA Crossover StrategyAdjust your partial TP and stop loss percentages.
Disable trades on chart to avoid clutter.
Strategy should work fine for identifying entries.
Transient Impact Model [ScorsoneEnterprises]This indicator is an implementation of the Transient Impact Model. This tool is designed to show the strength the current trades have on where price goes before they decay.
Here are links to more sophisticated research articles about Transient Impact Models than this post arxiv.org and arxiv.org
The way this tool is supposed to work in a simple way, is when impact is high price is sensitive to past volume, past trades being placed. When impact is low, it moves in a way that is more independent from past volume. In a more sophisticated system, perhaps transient impact should be calculated for each trade that is placed, not just the total volume of a past bar. I didn't do it to ensure parameters exist and aren’t na, as well as to have more iterations for optimization. Note that the value will change as volume does, as soon as a new candle occurs with no volume, the values could be dramatically different.
How it works
There are a few components to this script, so we’ll go into the equation and then the other functions used in this script.
// Transient Impact Model
transient_impact(params, price_change, lkb) =>
alpha = array.get(params, 0)
beta = array.get(params, 1)
lambda_ = array.get(params, 2)
instantaneous = alpha * volume
transient = 0.0
for t = 1 to lkb - 1
if na(volume )
break
transient := transient + beta * volume * math.exp(-lambda_ * t)
predicted_change = instantaneous + transient
math.pow(price_change - predicted_change, 2)
The parameters alpha, beta, and lambda all represent a different real thing.
Alpha (α):
Represents the instantaneous impact coefficient. It quantifies the immediate effect of the current volume on the price change. In the equation, instantaneous = alpha * volume , alpha scales the current bar's volume (volume ) to determine how much of the price change is due to immediate market impact. A larger alpha suggests that current volume has a stronger instantaneous influence on price.
Beta (β):
Represents the transient impact coefficient.It measures the lingering effect of past volumes on the current price change. In the loop calculating transient, beta * volume * math.exp(-lambda_ * t) shows that beta scales the volume from previous bars (volume ), contributing to a decaying effect over time. A higher beta indicates a stronger influence from past volumes, though this effect diminishes with time due to the exponential decay factor.
Lambda (λ):
Represents the decay rate of the transient impact.It controls how quickly the influence of past volumes fades over time in the transient component. In the term math.exp(-lambda_ * t), lambda determines the rate of exponential decay, where t is the time lag (in bars). A larger lambda means the impact of past volumes decays faster, while a smaller lambda implies a longer-lasting effect.
So in full.
The instantaneous term, alpha * volume , captures the immediate price impact from the current volume.
The transient term, sum of beta * volume * math.exp(-lambda_ * t) over the lookback period, models the cumulative, decaying effect of past volumes.
The total predicted_change combines these two components and is compared to the actual price change to compute an error term, math.pow(price_change - predicted_change, 2), which the script minimizes to optimize alpha, beta, and lambda.
Other parts of the script.
Objective function:
This is a wrapper function with a function to minimize so we get the best alpha, beta, and lambda values. In this case it is the Transient Impact Function, not something like a log-likelihood function, helps with efficiency for a high iteration count.
Finite Difference Gradient:
This function calculates the gradient of the objective function we spoke about. The gradient is like a directional derivative. Which is like the direction of the rate of change. Which is like the direction of the slope of a hill, we can go up or down a hill. It nudges around the parameter, and calculates the derivative of the parameter. The array of these nudged around parameters is what is returned after they are optimized.
Minimize:
This is the function that actually has the loop and calls the Finite Difference Gradient each time. Here is where the minimizing happens, how we go down the hill. If we are below a tolerance, we are at the bottom of the hill.
Applied
After an initial guess, we optimize the parameters and get the transient impact value. This number is huge, so we apply a log to it to make it more readable. From here we need some way to tell if the value is low or high. We shouldn’t use standard deviation because returns are not normally distributed, an IQR is similar and better for non normal data. We store past transient impact values in an array, so that way we can see the 25th and 90th percentiles of the data as a rolling value. If the current transient impact is above the 90th percentile, it is notably high. If below the 25th percentile, notably low. All of these values are plotted so we can use it as a tool.
Tool examples:
The idea around it is that when impact is low, there is room for big money to get size quickly and move prices around.
Here we see the price reacting in the IQR Bands. We see multiple examples where the value above the 90th percentile, the red line, corresponds to continuations in the trend, and below the 25th percentile, the purple line, corresponds to reversals. There is no guarantee these tools will be perfect, that is outlined in these situations, however there is clearly a correlation in this tool and trend.
This tool works on any timeframe, daily as we saw before, or lower like a two minute. The bands don’t represent a direction, like bullish or bearish, we need to determine that by interpreting price action. We see at open and at close there are the highest values for the transient impact. This is to be expected as these are the times with the highest volume of the trading day.
This works on futures as well as equities with the same context. Volume can be attributed to volatility as well. In volatile situations, more volatility comes in, and we can perceive it through the transient impact value.
Inputs
Users can enter the lookback value.
No tool is perfect, the transient impact value is also not perfect and should not be followed blindly. It is good to use any tool along with discretion and price action.
Crypto Scenario Alert SystemThe "Crypto Scenario Alert System" is a indicator that monitors key crypto assets like Bitcoin (BTC), Bitcoin Dominance (BTC.D), Ethereum (ETH), and total market caps (TOTAL, TOTAL2), providing alerts when important price levels are crossed.
Key Alerts:
BTC Price: Alerts for breakdowns below $72K or breakouts above $85K.
BTC Dominance: Alerts for spikes above 65% or drops below 60%.
Total Market Cap: Alerts for market cap changes above $2.85T or below $2.4T.
Total2 Market Cap: Alerts for altcoin market cap movements above $1.25T or below $1.05T.
ETH Price: Alerts for movements below $3K or above $3.6K.
Instructions:
Add the Indicator to your chart.
Manually Create Alerts:
Right-click on the chart, select "Add Alert".
Choose your desired alert condition (e.g., BTC Breakdown ).
Set your notification preferences.
Donchian Channel Trend Meter [Custom TF]DC TREND METER WITH CUSTOM TF
Check trend patterns in combi with other confleunces w/m formation above 50 ma 1 hr
BUY trend breaks and pay attention to 50 line
1 minute works good already
[4LC] Period Highs, Lows and OpensPeriod Highs, Lows, and Opens (HLO)
This script plots highs, lows, and opens from different time periods—yearly, monthly, weekly, Monday, and daily—on your chart. It includes a grouping feature that combines levels close to each other, based on a percentage distance, to keep the display organized.
What It Does:
It shows key price levels from various timeframes, marking where the market has hit highs, lows, or started a period. These levels can indicate potential support or resistance zones and help track price behavior over time.
How to Use It:
Add it to your chart and choose which levels to display (e.g., "Yearly High," "Daily Open").
Check where price is relative to these levels—above might suggest upward momentum, below could point to downward pressure.
Use the highs and lows to identify ranges for trading or watch for breakouts past these points.
Adjust settings like colors, spacing, or grouping distance as needed, and toggle price labels to see exact values.
Notes:
The script pulls data from multiple periods to give a broader view of price action. The grouping reduces overlap by averaging nearby levels into a single line with a combined label (e.g., "Yearly High, Monthly High"). It’s meant for traders interested in tracking significant levels across timeframes, whether for range trading or spotting market direction.
Fibonacci Levels with SMA SignalsThis strategy leverages Fibonacci retracement levels along with the 100-period and 200-period Simple Moving Averages (SMAs) to generate robust entry and exit signals for long-term swing trades, particularly on the daily timeframe. The combination of Fibonacci levels and SMAs provides a powerful way to capitalize on major trend reversals and market retracements, especially in stocks and major crypto assets.
The core of this strategy involves calculating key Fibonacci retracement levels (23.6%, 38.2%, 61.8%, and 78.6%) based on the highest high and lowest low over a 365-day lookback period. These Fibonacci levels act as potential support and resistance zones, indicating areas where price may retrace before continuing its trend. The 100-period SMA and 200-period SMA are used to define the broader market trend, with the strategy favoring uptrend conditions for buying and downtrend conditions for selling.
This indicator highlights high-probability zones for long or short swing setups based on Fibonacci retracements and the broader trend, using the 100 and 200 SMAs.
In addition, this strategy integrates alert conditions to notify the trader when these key conditions are met, providing real-time notifications for optimal entry and exit points. These alerts ensure that the trader does not miss significant trade opportunities.
Key Features:
Fibonacci Retracement Levels: The Fibonacci levels provide natural price zones that traders often watch for potential reversals, making them highly relevant in the context of swing trading.
100 and 200 SMAs: These moving averages help define the overall market trend, ensuring that the strategy operates in line with broader price action.
Buy and Sell Signals: The strategy generates buy signals when the price is above the 200 SMA and retraces to the 61.8% Fibonacci level. Sell signals are triggered when the price is below the 200 SMA and retraces to the 38.2% Fibonacci level.
Alert Conditions: The alert conditions notify traders when the price is at the key Fibonacci levels in the context of an uptrend or downtrend, allowing for efficient monitoring of trade opportunities.
Application:
This strategy is ideal for long-term swing trades in both stocks and major cryptocurrencies (such as BTC and ETH), particularly on the daily timeframe. The daily timeframe allows for capturing broader, more sustained trends, making it suitable for identifying high-quality entries and exits. By using the 100 and 200 SMAs, the strategy filters out noise and focuses on larger, more meaningful trends, which is especially useful for longer-term positions.
This script is optimized for swing traders looking to capitalize on retracements and trends in markets like stocks and crypto. By combining Fibonacci levels with SMAs, the strategy ensures that traders are not only entering at optimal levels but also trading in the direction of the prevailing trend.
US Recessions with SPX reversals v3 [FornaxTV]In addition to highlighting periods of official US recessions (as defined by the NBER) this script also displays vertical lines for the SPX market top and bottom associated with each recession .
This facilitates more detailed analysis of potential leading and coincident indicators for market tops and bottoms. This is particularly relevant for market tops, which typically precede the start of a recession by several months.
In addition to recessions with SPX market tops and market bottoms:
- A horizontal line can optionally be displayed for the last market top . (NOTE: this line will only be displayed for SPX tickers.)
- Labels can optionally be displayed for market tops & bottoms, plus the start and end of recessions. If the statistics are enabled (see below) these labels will also indicate the number of weeks between key market events, e.g. a market top and the start of a recession.
- A statistics table can optionally be displayed, contained statistics such as the number of weeks wince the last recession & market bottom, as well as averages for all recessions included in the analysis set.
For the recession statistics:
- "Outlier" recessions such as 1945 (WWII, where the market top occurred well after the recession itself) and 2020 (COVID pandemic, which was arguably not a "true" economic recession) can optionally be excluded.
- You can choose to exclude recessions occurring before a specific year.
SH1 Strategy -- STG ConvexShipHullStrategy ConvexShipHull v0_014_b0050
Featuring Hull Moving averages and IPMAN (Inflexion Point
Moving Average Nuance) via Convexity estimates. Excels
on lower time frames.
RSI Support & Resistance Breakouts with OrderblocksThis tool is an overly simplified method of finding market squeeze and breakout completely based on a dynamic RSI calculation. It is designed to draw out areas of price levels where the market is pushing back against price action leaving behind instances of short term support and resistance levels you otherwise wouldn't see with the common RSI.
It uses the changes in market momentum to determine support and resistance levels in real time while offering price zone where order blocks exist in the short term.
In ranging markets we need to know a couple things.
1. External Zone - It's important to know where the highs and lows were left behind as they hold liquidity. Here you will have later price swings and more false breakouts.
2. Internal Zone - It's important to know where the highest and lowest closing values were so we can see the limitations of that squeeze. Here you will find the stronger cluster of orders often seen as orderblocks.
In this tool I've added a 200 period Smoothed Moving Average as a trend filter which causes the RSI calculation to change dynamically.
Regular Zones - without extending
The Zones draw out automatically but are often too small to work with.
To solve this problem, you can extend the zones into the future up to 40 bars.
This allows for more visibility against future price action.
--------------------------------------------
Two Types of Zones
External Zones - These zones give you positioning of the highest and lowest price traded within the ranging market. This is where liquidity will be swept and often is an ultimate breaking point for new price swings.
How to use them :
External Zones - External zones form at the top of a pullback. After this price should move back into its impulsive wave.
During the next corrective way, if price breaches the top of the previous External Zone, this is a sign of trend weakness. Expect a divergence and trend reversal.
Internal Zones - (OrderBlocks) Current price will move in relation to previous internal zones. The internal zone is where a majority of price action and trading took place. It's a stronger SQUEEZE area. Current price action will often have a hard time closing beyond the previous Internal Zones high or low. You can expect these zones to show you where the market will flip over. In these same internal zones you'll find large rejection candles.
**Important Note** Size Doesn't Matter
The size of the internal zone does not matter. It can be very small and still very powerful.
Once an internal zone has been hit a few times, its often not relevant any longer.
Order Block Zone Examples
In this image you can see the Internal Zone that was untouched had a STRONG price reaction later on.
Internal Zones that were touched multiple times had weak reactions later as price respected them less over time.
Zone Overlay Breakdown
The Zones form and update in real time until momentum has picked up and price begins to trend. However it leaves behind the elements of the inducement area and all the key levels you need to know about for future price action.
Resistance Fakeout : Later on after the zone has formed, price will return to this upper zone of price levels and cause fakeouts. A close above this zone implies the market moves long again.
Midline Equilibrium : This is simply the center of the strongest traded area. We can call this the Point of Control within the orderblock. If price expands through both extremes of this zone multiple times in the future, it eliminates the orderblock.
Support Fakeout : Just like its opposing brother, price will wick through this zone and rip back causing inducement to trap traders. You would need a clear close below this zone to be in a bearish trend.
BARCOLOR or Candle Color: (Optional)
Bars are colored under three conditions
Bullish Color = A confirmed bullish breakout of the range.
Bearish Color = A confirmed bearish breakout of the range.
Squeeze Color = Even if no box is formed a candle or candles can have a squeeze color. This means the ranging market happened within the high and low of that singular candle.
(US) Historical Trade WarsHistorical U.S. Trade Wars Indicator
Overview
This indicator visualizes major U.S. trade wars and disputes throughout modern economic history, from the McKinley Tariff of 1890 to recent U.S.-China tensions. This U.S.-focused timeline is perfect for macro traders, economic historians, and anyone looking to understand how America's trade conflicts correlate with market movements.
Features
Comprehensive U.S. Timeline: Covers 130+ years of U.S.-centered trade disputes with historically accurate dates.
Color-Coded Events:
🔴 Red: Marks the beginning of a U.S. trade war or major dispute.
🟡 Yellow: Highlights significant events within a trade conflict.
🟢 Green: Shows resolutions or ends of trade disputes.
Global Partners/Rivals: Tracks U.S. trade relations with China, Japan, EU, Canada, Mexico, Brazil, Argentina, and others.
Country Flags: Uses emoji flags for easy visual identification of nations in trade relations with the U.S.
Major Trade Wars Covered:
McKinley Tariff (1890-1894)
Smoot-Hawley Tariff Act (1930-1934)
U.S.-Europe Chicken War (1962-1974)
Multifiber Arrangement Quotas (1974-2005)
Japan-U.S. Trade Disputes (1981-1989)
NAFTA and Softwood Lumber Disputes
Clinton and Bush-Era Steel Tariffs
Obama-Era China Tire Tariffs
Rare Earth Minerals Dispute (2012-2014)
Solar Panel Dispute (2012-2015)
TPP and TTIP Negotiations
U.S.-China Trade War (2018-present)
Airbus-Boeing Dispute
Usage
Analyze how markets historically responded to trade war initiations and resolutions.
Identify patterns in market behavior during periods of trade tensions.
Use as an overlay with price action to examine correlations.
Perfect companion for macro analysis on daily, weekly, or monthly charts.
About
This indicator is designed as a historical reference tool for traders and economic analysts focusing on U.S. trade policy and its global impact. The dates and events have been thoroughly researched for accuracy. Each label includes emojis to indicate the U.S. and its trade partners/rivals, making it easy to track America's evolving trade relationships across time.
Note: This indicator works best on larger timeframes (daily, weekly, monthly) due to the historical span covered.
Pullback Long Screener - Bougie Verte 4h
This script is designed to be used within a Pullback Long Screener on TradingView.
It identifies cryptocurrencies currently displaying a green 4-hour candle (i.e., when the close is higher than the open).
The goal is to quickly detect assets in a potential bullish move, which is particularly useful for scalping.
This script is configured to work exclusively on cryptocurrencies listed on Binance as perpetual futures contracts.
The green circles displayed below the candles indicate a valid green 4-hour candle condition.
Bitcoin Valuation Model | OpusBitcoin Valuation Model | Opus
Technical Indicator Overview
The Bitcoin Valuation Model | Opus is a comprehensive tool that assesses Bitcoin’s market valuation using a blend of fundamental and technical Z-scores. Overlaying a dynamic Z-score plot on the price chart, it integrates metrics like MVRV, Bitcoin Thermocap, NUPL, and RSI, alongside a detailed table for real-time analysis. With vibrant visualizations and SDCA (Scaled Dollar-Cost Averaging) thresholds, this indicator helps traders identify overbought or oversold conditions with precision.
Key Features 🌟
Multi-Metric Z-Score Analysis: Combines 12 fundamental and technical indicators into customizable Z-score plots for a holistic valuation view.
Dynamic Visualization: Displays Z-scores with gradient backgrounds, horizontal thresholds, and optional bar coloring for intuitive market insights.
Comprehensive Dashboard: Provides a compact table with Z-scores, market conditions, and ROC (Rate of Change) for each indicator.
SDCA Signals: Highlights buy (below -2) and sell (above 2) zones with dynamic background opacity to guide dollar-cost averaging strategies.
Retro Aesthetic: Features a Synthwave-inspired color scheme (cyan for oversold, magenta for overbought) with cloud effects and gradient fills.
Usage Guidelines 📋
Buy Signals: Enter or accumulate Bitcoin when the Z-score falls below -2 (cyan background), indicating an oversold market.
Sell Signals: Consider exiting or reducing exposure when the Z-score exceeds 2 (magenta background), signaling overbought conditions.
Market Condition Tracking: Use the table to monitor individual indicator Z-scores and ROC trends for confirmation of market states.
Trend Analysis: Assess the plotted Z-score against thresholds (-3 to 3) to gauge momentum and potential reversals.
Customizable Settings ⚙️
Table Position: Place the dashboard anywhere on the chart (e.g., Middle Right, Top Center).
Z-Score Plot: Select from 15 options (e.g., MVRV, RSI, Average Z-Score) to focus on specific metrics.
Indicator Parameters: Adjust lengths, means, and scales for each metric (e.g., RSI Length: 400, MVRV Scale: 2.1).
SDCA Thresholds: Set buy (-2) and sell (2) levels to tailor dollar-cost averaging signals.
Visual Options: Toggle bar coloring and customize ROC lookback (default: 7 days) for personalized analysis.
Applications 🌍
The Bitcoin Valuation Model | Opus is ideal for Bitcoin traders and hodlers seeking a data-driven approach to market timing. Its fusion of on-chain fundamentals, technical indicators, and visually rich feedback makes it perfect for identifying valuation extremes, optimizing SDCA strategies, and enhancing long-term investment decisions—all under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) © 2025 Opus Capital.
Fractal Dimension Index - FDIWhat is Fractal Dimension Index (FDI)?
The Fractal Dimension Index measures the complexity of price movements using fractal geometry concepts. It quantifies how "rough" or "smooth" the price series is:
Values close to 1 = Smooth, trending markets
Values approaching 2 = Chaotic, range-bound markets
Key Levels:
1.35 (Green Line): Below this suggests strong trending behavior
1.5 (Red Line): Above this indicates high market chaos/ranging
Trading Strategy:
Trend Identification:
FDI < 1.35: Strong trend (use trend-following strategies)
FDI > 1.5: Choppy market (use range strategies or stay out)
1.35-1.5: Transition zone
Divergence Trading:
Price makes new highs but FDI declines → Potential trend weakness
Price makes new lows but FDI rises → Potential reversal signal
Breakout Confirmation:
Valid breakouts often occur when FDI drops below 1.4 after being in high territory
Market State Filter:
Combine with other indicators:
In low FDI (trending): Use moving averages
In high FDI (choppy): Use oscillators like RSI
Science Behind the Indicator:
The FDI is based on the Hurst exponent and fractal geometry principles. It calculates the "roughness" of price movements by:
Normalizing prices between the period's high/low
Calculating the total path length using Pythagorean theorem
Using logarithmic scaling to compare path length to straight-line distance
Practical Usage Tips:
Timeframe Combinations:
Use daily FDI for overall market state
Combine with 4-hour FDI for entry timing
Asset-Specific Adjustments:
Volatile assets (crypto) often have higher baseline FDI
Adjust thresholds slightly for different instruments
Risk Management:
Wider stops in high FDI environments
Tighter trailing stops in low FDI trending markets
Confirmation Tools:
Pair with Volume Profile in high FDI zones
Use MACD in low FDI trending markets
DT_KEY_LEVELSDT_Key_Levels: Powerful Market Structure Analysis Indicator
DT_Key_Levels is an advanced indicator for fundamental market structure analysis, optimized for higher timeframes (D1, W, M). The indicator combines three powerful technical analysis tools — fractals, Fair Value Gaps (FVG), and psychological levels — in one comprehensive solution.
Three Components of the Indicator
1. Enhanced Fractal System
The indicator uses an improved version of Bill Williams' classic fractals, allowing for deeper market structure analysis:
Dual Identification System:
Standard 5-bar fractals (displayed with thick lines) for analyzing reliable support/resistance levels
Light 3-bar fractals (displayed with thin lines) for early identification of potential reversal points
Intelligent Tracking System:
Automatic detection and filtering of completed fractals
Marking fractals with corresponding timeframe designation (HTF-1D, HTF-1W, HTF-1M)
Tracking and marking the All-Time High (ATH)
2. Fair Value Gaps (FVG) System
The indicator identifies and visualizes price gaps in market structure — zones that often act as magnets for future price movements:
Precise Identification of Inefficient Zones:
Bullish FVG: when the current candle's low is above the -2 candle's high
Bearish FVG: when the current candle's high is below the -2 candle's low
Detailed Visualization:
Clear display of upper and lower boundaries of each FVG
Midline (0.5 FVG) for determining key reaction levels within the gap
Marking each FVG with "FF" (Fair value Fill) label for quick identification
Dynamic Management:
Automatic removal of FVGs when they are filled by price movement
Customizable line extension for improved tracking of target zones
3. Intelligent Psychological Levels
The indicator automatically determines key psychological levels with adaptation to the type of instrument being traded:
Specialized Calibration for Various Assets:
Forex (EUR/USD, GBP/USD, USD/JPY): optimization for standard figures and round values
Precious metals (XAUUSD): adaptation to typical gold reaction zones with a $50 step
Cryptocurrencies (BTC, ETH): dynamic step adjustment depending on current price zone
Stock indices (NASDAQ, S&P500, DAX): accounting for the movement characteristics of each index
Smart Adaptation System:
Automatic determination of the optimal step for any instrument
Generation of up to 24 key levels, evenly distributed around the current price
Intelligent filtering to display only significant levels
Practical Application
Strategic Analysis
Identifying Key Structural Levels:
Use monthly and weekly fractals to determine strategic support/resistance zones
Look for coincidences of fractals with psychological levels to identify particularly strong zones of interest
Determine long-term barriers using type 5 fractals on higher timeframes
Analysis of Market Inefficiencies:
Track the formation of FVGs as potential targets for future movements
Use FVG midlines (0.5) as important internal reaction levels
Analyze the speed of FVG filling to understand trend strength
Tactical Trading Decisions
Entry Points and Risk Management:
Use bounces from fractals in the direction of the larger trend as a signal for entry
Place stop-losses behind fractal levels or key psychological levels
Monitor the formation of new fractals as a signal of potential reversal
Determining Target Levels:
Use unfilled FVGs as natural price targets
Apply nearby psychological levels for partial position closing
Project higher timeframe fractals to determine long-term goals
Indicator Advantages
Comprehensive Approach: combining three methodologies for a complete understanding of market structure
Intelligent Adaptation: automatic adjustment to the characteristics of different types of assets
Clean Visual Presentation: despite the abundance of information, the indicator maintains clarity of display
Effective Signal Filtering: automatic removal of completed levels to reduce visual noise
Higher Timeframe Optimization: specifically designed for daily, weekly and monthly charts
Usage Recommendations
Use the indicator only on D1, W, and M timeframes for the most reliable signals
Pay special attention to areas where different types of signals coincide (e.g., fractal + psychological level)
Use higher timeframe fractals as key zones for medium and long-term trading
Track FVGs as potential target zones and focus on their filling
OPR 14h30-14h45 amélioré avec options avancées + MA200OPR 14h30-14h45 amélioré avec options avancées + MA200
1min Specific Time Swing time concept
if you know PO3 of time in 5min candles
you should know manipulation times
this indicator shows manipulation times and swing high/lows!
Enjoy!
Enhanced Forex Trading SignalsEnhanced Forex Trading Strategy - Usage Instructions
Overview
This improved Pine Script strategy provides clear buy and sell signals for forex trading. The script has been enhanced to offer:
Signal Strength Calculation - A numerical value (0-100%) indicating the strength of buy/sell signals
Visual Dashboard - Real-time display of key trading indicators and current signal
Clear Visual Signals - Large triangles for buy/sell signals and background color changes
Multiple Technical Indicators - Combines moving averages, RSI, MACD, and price position analysis
Key Improvements
The original script has been enhanced with the following improvements:
Signal Strength System: Instead of binary yes/no signals, the strategy now calculates a strength percentage for both buy and sell signals
Signal Filtering: Only generates signals when strength exceeds your chosen threshold
Visual Dashboard: Shows all key information in one place for quick decision making
Clearer Visual Indicators: Background color changes and larger signal markers
Additional Technical Indicators: Added MACD and RSI divergence detection
Smoother Signals: Signal smoothing to reduce false signals and whipsaws
How to Use
Step 1: Load the Script in TradingView
Open TradingView and create a new Pine Script
Copy and paste the entire code from improved_forex_strategy.pine
Click "Save" and then "Add to Chart"
Step 2: Configure Settings
The script includes several customizable parameters:
Moving Average Periods: Adjust short and long MA periods based on your trading timeframe
Signal Threshold: Set the minimum signal strength (0-100) required to generate buy/sell signals
RSI Settings: Customize overbought/oversold levels
Stop Loss/Take Profit: Set your risk management parameters
Dashboard Settings: Enable/disable the dashboard and choose its location
Step 3: Interpreting Signals
Buy Signal (Green Triangle Up)
A buy signal is generated when:
Buy signal strength exceeds your threshold (default 70%)
Buy strength is greater than sell strength
A green triangle appears below the price bar
Background turns light green
Sell Signal (Red Triangle Down)
A sell signal is generated when:
Sell signal strength exceeds your threshold (default 70%)
Sell strength is greater than buy strength
A red triangle appears above the price bar
Background turns light red
Dashboard Information
The dashboard provides at-a-glance information:
Current buy and sell signal strengths (0-100%)
Overall market trend (Bullish/Bearish/Neutral)
RSI status (Overbought/Oversold/Neutral)
Price position relative to 52-week range
Current signal recommendation (Buy/Sell/No Signal)
Signal Strength Calculation
The signal strength is calculated based on multiple factors:
Buy Signal Strength Factors
Trend is up (short MA > long MA): +20%
Bullish MA crossover: +30%
RSI oversold condition: +15%
MACD bullish cross: +15%
MACD line positive: +10%
Price near 52-week low: +15%
Positive sentiment (volume surge with upward momentum): +10%
RSI bullish divergence: +15%
Sell Signal Strength Factors
Trend is down (short MA < long MA): +20%
Bearish MA crossover: +30%
RSI overbought condition: +15%
MACD bearish cross: +15%
MACD line negative: +10%
Price near 52-week high: +15%
Negative sentiment (volume surge with downward momentum): +10%
RSI bearish divergence: +15%
The final strength is smoothed over several periods to reduce noise and false signals.
Recommended Settings for Different Timeframes
Short-term Trading (1h, 4h charts)
Short MA: 5-10
Long MA: 20-30
Signal Threshold: 60-70
RSI Period: 14
Signal Line Period: 3-5
Medium-term Trading (Daily chart)
Short MA: 10-20
Long MA: 30-50
Signal Threshold: 70-80
RSI Period: 14
Signal Line Period: 5-7
Long-term Trading (Weekly chart)
Short MA: 20-30
Long MA: 50-100
Signal Threshold: 80-90
RSI Period: 14
Signal Line Period: 7-10
Best Practices
Adjust the Signal Threshold: Start with 70% and adjust based on your risk tolerance. Lower values generate more signals but include more false positives.
Confirm with Multiple Timeframes: For stronger confirmation, check if signals align across different timeframes.
Use the Dashboard: Pay attention to all information in the dashboard, not just the final signal.
Monitor Signal Strength Trends: Watch how signal strength builds up or fades over time.
Customize for Your Pairs: Different forex pairs may require different settings. Test and adjust accordingly.
Troubleshooting
Too Many Signals: Increase the signal threshold or increase the signal smoothing period
Too Few Signals: Decrease the signal threshold or decrease the signal smoothing period
Delayed Signals: Decrease the moving average periods
False Signals: Increase the signal threshold and ensure you're using an appropriate timeframe for your trading style
Timed Reversion Markers (Custom Session Alerts)This script plots vertical histogram markers at specific intraday time points defined by the user. It is designed for traders who follow time-based reversion or breakout setups tied to predictable market behavior at key clock times, such as institutional opening moves, midday reversals, or end-of-day volatility.
Unlike traditional price-action indicators, this tool focuses purely on time-based triggers, a technique often used in time cycle analysis, market internals, and volume-timing strategies.
The indicator includes eight fully customizable time inputs, allowing users to mark any intraday minute with precision using a decimal hour format (for example, 9.55 for 9:55 AM). Each input is automatically converted into hour and minute format, and a visual histogram marker is plotted once per day at that exact time.
Example use cases:
Mark institutional session opens (e.g., 9:30, 10:00, 15:30)
Time-based mean reversion or volatility windows
Backtest recurring time-based reactions
Highlight algorithmic spike zones
The vertical plots serve as non-intrusive, high-contrast visual markers for scalping setups, session analysis, and decision-making checkpoints. All markers are displayed at the top of the chart without interfering with price candles.
ADR Actual en RecuadroADR data in a separate box. Shows a visualization of the average "market limit".
Buy and Sell Signal xNawaf (SMA)
"A new indicator, customizable for future adjustments. Thank you all!"
xNawaf
Nawaf aLOtaibi
thank you all
Custom Daily % Levels Table📘 Indicator Description
"Custom Daily % Levels – table" is a dynamic and customizable tool designed to help traders visualize daily percentage-based price ranges and key metrics in a compact, table-style format.
🧩 Key Features:
📐 Custom Percent Levels: Automatically calculates upper and lower price levels based on a user-defined base percentage and number of levels, relative to the previous daily close.
🟢🔴 Color Gradient Highlighting: Positive levels are shown with a green gradient, negative levels with red, and the level labels with a neutral tone for easy reference.
📊 Live Asset Info: Displays the current symbol, percentage change from the previous daily close, and 14-period RSI, all color-coded for quick interpretation.
⚙️ Header Control: Toggle the visibility of the main info headers and level headers independently.
📌 Position Customization: Choose where the table appears on your chart (top/bottom, left/right, center).
📈 Clean Layout: Makes it easy to visually track price movement relative to daily expected ranges.
This indicator is especially useful for intraday traders, scalpers, or anyone needing a clear visual of short-term price expansion and contraction based on predefined volatility zones.
