Kondratieff Wave & Benner Business CyclesKondratieff Wave Theory
Description: The Kondratieff Wave, also known as K-Waves or Long Waves, is an economic theory that posits long-term cycles of approximately 40-60 years in capitalist economies. These cycles consist of four phases: Spring (expansion and recovery), Summer (prosperity and peak), Autumn (stagnation and recession), and Winter (depression and restructuring). The theory suggests that technological innovations and major economic shifts drive these waves, influencing periods of growth and decline over decades.
Creator Bio: Nikolai Dmitriyevich Kondratieff (1892–1938) was a Russian economist born in the Kostroma Governorate. He studied at the University of St. Petersburg and became a prominent figure in Soviet economics. Kondratieff developed his long-wave theory in the 1920s while analyzing historical economic data, publishing works like The Major Economic Cycles (1925). His ideas clashed with Soviet ideology, leading to his arrest in 1930 during Stalin’s purges. He was executed in 1938, but his work gained recognition posthumously, influencing modern economic cycle analysis.
Benner Cycle Theory
Description: The Benner Cycle, proposed by Samuel Benner, is a predictive model for business and commodity price cycles, focusing on shorter-term economic fluctuations. Benner identified recurring patterns in market peaks (highs), panics (crashes), and buying opportunities (lows), with cycles averaging 8-10 years for highs, 7-8 years for panics, and 8-9 years for buys. His theory, based on historical observations of U.S. markets, aimed to guide farmers and investors by forecasting periods of prosperity and distress.
Creator Bio: Samuel T. Benner (1830s–unknown) was an American farmer and businessman from Ohio, not a formally trained economist. After losing his fortune in the Panic of 1873, Benner turned to studying economic patterns. In 1875, he self-published Benner’s Prophecies of Future Ups and Downs in Prices, a book that charted cycles in pig iron prices and other commodities. His work gained a cult following among traders and remains studied for its empirical approach, despite Benner’s lack of academic credentials and limited biographical records.
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.
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.
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.
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
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.
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.
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.
HinduTime Choghadiya(Dynamic Day & Night)🕉️ HinduTime Choghadiya (Dynamic Day & Night) — Visualize real-time Choghadiya Muhurat across global timezones with dynamic sunrise/sunset-based day & night cycles. Perfect for astrology-based or Vedic timing strategies.
How to Use:
Add to Chart: Click "Add to chart" from the TradingView script panel.
Select Your Timezone: Use the dropdown to choose your local timezone (e.g., Asia/Kolkata).
Customize Sunrise/Sunset:
Set "Day Start Hour" (typically 6 AM).
Set "Night Start Hour" (typically 6 PM).
Visual Choghadiya Overlay:
Background color represents the current Choghadiya (e.g., Amrit, Shubh, Rog).
Adjusts dynamically by weekday and day/night period.
Use for Timing Entries:
Favorable: Amrit, Shubh, Labh
Neutral: Chal
Avoid: Rog, Kal, Udveg
High and Low DayHigh and Low Day
This indicator automatically tracks and displays the daily high and low of the current trading session directly on your chart.
Each new day, it resets the levels and plots horizontal lines:
Green Line for the daily high
Red Line for the daily low
It also adds labels (“High Day” and “Low Day”) for easy visual reference.
The levels update in real time as new highs or lows are formed throughout the day.
You can toggle the visibility of these lines and labels using the "Mostrar Linhas do Dia Atual" (Show Current Day Lines) setting.
Perfect for intraday traders looking to keep track of key support and resistance levels during the trading day.
DB - CME Gap [Multi Asset Auto Detection: BTC,SOL, etc]DB - CME Gap is a pro-grade, zero-maintenance CME gap tracker designed for serious traders.
This script automatically detects unfilled CME futures gaps across a wide range of assets—crypto, equities, bonds, commodities, FX, and agriculture—by pulling the official Friday close from CME’s daily futures data. It visually highlights unfilled weekend gaps and keeps them active on the chart until the price fully crosses through the gap level, offering a reliable view of market inefficiencies that often attract future liquidity.
Whether you're trading BTC, ES, CL, ZN, 6E, or ZC... this tool auto-detects and adjusts to the asset you're charting, so you don’t need to change any settings.
🧠 Key Benefits
Fully Automated – No symbol selection required; works instantly across asset classes
Professional Grade – Clean, minimal visuals with dynamic gap tracking
Always Accurate – Uses CME official daily closes to identify true weekend gaps
Cross-Market Versatility – Supports a broad range of assets without editing code
✅ Features
🔍 Auto Symbol Detection
Automatically identifies whether you're viewing BTC, ETH, SOL, ES, NQ, CL, ZN, 6E, GC, ZC, and more—no input required.
📅 CME Friday Close Logic
Pulls the actual Friday close from CME's daily data to detect accurate gap reference points.
🚨 Weekend Gap Detection
Monitors Friday after-hours, Saturday, and Sunday to detect gaps between CME close and weekend price action.
🧠 Persistent Gap Tracking
Gaps remain active until price fully crosses the gap level—no false closures.
📈 Dynamic Line Drawing
Draws a horizontal line at the gap price and extends it to the point of fill.
🌈 Custom Gradient Shading
Fills the area between the current price and the CME gap with directional color gradients based on price movement.
🎨 User-Configurable Colors
Adjust bull and bear fill color themes to suit your personal style.
🧩 Compatible with All Major Asset Classes
Works with:
Crypto: BTC, ETH, SOL
Equities: ES, NQ, YM, MES, MNQ
Bonds & Rates: ZN, ZB, ZF, ZT, GE
Commodities: CL, GC, NG, BZ, SI
FX: 6E, 6J, 6B
Ags: ZC (Corn), ZS (Soybeans)
J Weighted Average Price📘 How to Use the OBV VWAP Reentry Signal Effectively
This indicator plots a VWAP based on OBV (On-Balance Volume), along with dynamic bands to identify overbought and oversold conditions in volume flow.
🔺 Red Triangle Up: Appears when OBV crosses back below the upper band → Potential reversal from overbought → Watch for short opportunities.
🔻 Blue Triangle Down: Appears when OBV crosses back above the lower band → Potential reversal from oversold → Watch for long opportunities.
📌 Tip: Use these signals in confluence with price action or trend confirmation to filter false signals. For example:
Enter short after a reentry from upper band and a lower high in price.
Enter long after a reentry from lower band and a bullish candle structure.
This setup helps you catch mean reversion moves based on volume flow, not just price.
HALC SYHALC SY @CK
Heikin Ashi Last Candle shows color of the last closed 30m heikin ashi candle for every new candle on your graph indicating local trend for scalp & short term trading in rder to help u choose right direction in your 1-5m tf trading. Non-repainting & designed for use on any graph type incl HA, Renko and other problematic syntetic as well as any of your own.
Dont recommend as entry signal but strong support to confirm/deny your trade system entry signal. Enjoy!
Daily Open Levels (Custom Pips)Daily Open Levels Indicator
Overview: The Daily Open Levels indicator is a simple but powerful tool designed for intraday traders who focus on the daily open price and pip-based levels for decision-making. This indicator helps you visualize key price levels based on the daily opening price, with configurable upper and lower levels calculated in pips. It is especially useful for tracking price movements relative to the previous day’s open and can help traders identify breakout zones, potential support/resistance, and key entry/exit points.
eatures:
Daily Open Price: The indicator automatically calculates and plots the daily open of the current trading day.
Upper and Lower Levels: Configurable upper and lower levels based on a user-defined pip interval. These levels can act as potential resistance or support zones.
Adjustable Pip Interval: You can customize the pip distance for the upper and lower levels to suit different trading styles and volatility.
Works for All Pairs: Option to automatically detect JPY pairs with a different pip value (0.1), or you can manually select your pair setting.
Color Customization: You can choose different colors for the daily open line, upper levels, and lower levels for easy visualization.
Immediate Visual Feedback: The indicator immediately draws the lines on the chart when added, without waiting for any market data.
How It Works:
The daily open price is retrieved from the current trading day, and horizontal lines are drawn at this price level, as well as at pip-based distances above and below it.
The pip distance is calculated using the Pip Interval setting and can be adjusted for any pair. For example, a 225-pip interval would create lines at 225 pips above and below the daily open.
The indicator dynamically updates every minute to reflect new daily opens and adjustments for each trading day.
Lines are drawn using the HLine (horizontal line) objects in MetaTrader 5, making them easy to spot and follow.
Parameters:
Pip Interval: Defines the pip distance for upper and lower levels (e.g., 225 pips). This affects how far above and below the daily open the levels are drawn.
Number of Levels: Sets how many upper and lower levels are drawn.
JPY Pairs: An option to adjust the pip value for JPY pairs (0.1 pip for JPY pairs vs. 0.01 pip for others).
Line Colors: Customize the colors for the daily open, upper levels, and lower levels.
Style & Width: Adjust the style (solid/dashed) and width of the lines to match your preferences.
Sahid Strategy v2This script identifies potential buy/sell signals using:
Pivot Points - Detects swing highs/lows (price reversals)
Confirmation Filters - Reduces false signals using:
RSI (momentum)
Moving Average (trend direction)
Optional MACD (trend confirmation)
Key Features
Signal Type Trigger Conditions
BUY - Price makes a swing low (pivot)
Copy
- RSI ≤ 30 (oversold)
- Price above trend MA
- MACD bullish (optional) |
| SELL | - Price makes a swing high (pivot)
- RSI ≥ 70 (overbought)
- Price below trend MA
- MACD bearish (optional) |
Visual Signals
Green "BUY" labels below price bars
Red "SELL" labels above price bars
Purple trend line (20-period EMA/SMA)
Orange/blue circles showing raw pivot points
Optional Tools
Debug Table (top-right): Shows real-time:
RSI value
Price vs MA position
MACD status
Alerts - Triggers audible/visual notifications
Customization
Adjust in settings:
Pivot sensitivity (left/right bars)
RSI levels (30/70 by default)
MA type/length (20-period EMA/SMA)
Toggle MACD filter on/off
Best For: Swing trading in trending markets (1H-4H timeframes). Signals appear faster than classic pivot strategies but still require confirmation from other analysis tools.
50-Line Oscillator // (\_/)
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25-Line Oscillator
Description:
The 25-Line Oscillator is a sophisticated technical analysis tool designed to visualize market trends through the use of multiple Simple Moving Averages (SMAs). This indicator computes a series of 26 SMAs, incrementally increasing the base length, providing traders with a comprehensive view of price dynamics.
Features:
Customizable Base Length: Adjust the base length of the SMAs according to trading preferences, enhancing versatility for different market conditions.
Rainbow Effect: The indicator employs a visually appealing rainbow color scheme to differentiate between the various trend lines, making it easy to identify crossovers and momentum shifts.
Crossovers Detection: The script includes logic to detect crossover events between consecutive trend lines, which can serve as signals for potential entry or exit points in trading.
Clear Visualization: Suitable for both novice and seasoned traders, the plots enable quick interpretation of trends and market behavior.
How to Use:
Add the indicator to your chart and customize the base length as desired.
Observe the rainbow-colored lines for trend direction.
Look for crossover events between the SMAs as potential trading signals.
Application: This indicator is particularly useful for swing traders and trend followers who aim to capitalize on market momentum and identify reversals. By monitoring the behavior of multiple SMAs, traders can gain insights into the strength and direction of price movements over various time frames.
Closing Range BreakoutIndicator Description:
This tool tracks the closing price range of a trading session (like New York or London market hours) and highlights potential breakout opportunities. It shows:
Extended Range Lines: Drawn after the session closes, marking the high/low of the session's final hour.
Breakout Arrows: Appear when prices close above/below the range for a user-defined number of consecutive bars.
Session Background: Gray highlight during the selected market's closing hour.
It helps traders spot momentum shifts by focusing on price behavior relative to the closing range, with customizable alerts for confirmed breakouts.
How to Use:
Select Session: Choose your market's closing hour (e.g., New York/London).
Set Confirmation: Adjust how many closes are needed to confirm a breakout.
Watch Visuals:
Gray background = Active closing session
Blue range = Extended high/low from last session
Arrows = First breakout signal
Trade Signals: Price closing outside the range triggers alerts (labels update automatically).
Focus on breakouts with momentum, using the range as support/resistance.
Intraday Macro & Flow Indicator# IntraMacroFlow Indicator
## Introduction
IntraMacroFlow is a volume and delta-based indicator that identifies significant price movements within trading sessions. It generates signals when volume spikes coincide with quality price movement, filtered by RSI to avoid overbought/oversold conditions.
> **Note:** This indicator provides multiple signals and should be combined with additional analysis methods such as support/resistance, trend direction, and price action patterns.
## Inputs
### Volume Settings
* **Volume Lookback Period** (14) - Number of bars for volume moving average calculation
* **Volume Threshold Multiplier** (1.5) - Required volume increase over average to generate signals
* **Delta Threshold** (0.3) - Required close-to-open movement relative to bar range (higher = stronger movement)
### Session Configuration
* **Use Dynamic Session Detection** (true) - Automatically determine session times
* **Highlight Market Open Period** (true) - Highlight first third of trading session
* **Highlight Mid-Session Period** (true) - Highlight middle portion of trading session
* **Detect Signals Throughout Whole Session** (true) - Find signals in entire session
* **Session Time** ("0930-1600") - Trading hours in HHMM-HHMM format
* **Session Type** ("Regular") - Select Regular, Extended, or Custom session
### Manual Session Settings
Used when dynamic detection is disabled:
* **Manual Session Open Hour** (9)
* **Manual Session Open Minute** (30)
* **Manual Session Open Duration** (60)
* **Manual Mid-Session Start Hour** (12)
* **Manual Mid-Session End Hour** (14)
## How It Works
The indicator analyzes each bar using three primary conditions:
1. **Volume Condition**: Current volume > Average volume × Threshold
2. **Delta Condition**: |Close-Open|/Range > Delta threshold
3. **Time Condition**: Bar falls within configured session times
When all conditions are met:
* Bullish signals appear when close > open and RSI < 70
* Bearish signals appear when close < open and RSI > 30
## Display Elements
### Shapes and Colors
* Green triangles below bars - Bullish signals
* Red triangles above bars - Bearish signals
* Blue background - Market open period
* Purple background - Mid-session period
* Bar coloring - Green (bullish), Red (bearish), or unchanged
### Information Panel
A dynamic label shows:
* Current volume relative to average (Vol)
* Delta value for current bar (Delta)
* RSI value (RSI)
* Session status (Active/Closed)
## Calculation Method
```
// Volume Condition
volumeMA = ta.sma(volume, lookbackPeriod)
volumeCondition = volume > volumeMA * volumeThreshold
// Delta Calculation (price movement quality)
priceRange = high - low
delta = math.abs(close - open) / priceRange
deltaCondition = delta > deltaThreshold
// Direction and RSI Filter
bullishBias = close > open and entrySignal and not (rsi > 70)
bearishBias = close < open and entrySignal and not (rsi < 30)
```
## Usage Recommendations
### Suitable Markets
* Equities during regular trading hours
* Futures markets
* Forex during active sessions
* Cryptocurrencies with defined volume patterns
### Recommended Timeframes
* 1-minute to 1-hour (optimal: 5 or 15-minute)
### Parameter Adjustments
* For fewer but stronger signals: increase Volume Threshold (2.0+) and Delta Threshold (0.4-0.6)
* For more signals: decrease Volume Threshold (1.2-1.5) and Delta Threshold (0.2-0.3)
### Usage Tips
* Combine with trend analysis for higher-probability entries
* Focus on signals occurring at session boundaries and mid-session
* Use opposite signals as potential exit points
* Configure alerts to receive notifications when signals occur
## Additional Notes
* RSI parameters are fixed at 14 periods with 70/30 thresholds
* The indicator handles overnight sessions correctly
* Fully compatible with TradingView alerts
* Customizable visual elements
## Release Notes
Initial release: This is a template indicator that should be customized to suit your specific trading strategies and preferences.
London Breakout Tracker - Box Style📊 London Breakout Tracker (Pine Script v6)
This script is designed to track the Asian session range and identify breakout opportunities when the London session begins. It highlights high-probability trade setups and helps avoid fakeouts or overly wide ranges.
🧱 1. Session Time Definitions (Adjusted for Kenyan Time)
The Asian session is defined as:
3:00 AM to 11:00 AM (Kenyan Time)
🔐 2. Asian Session High & Low
During the Asian session:
The script tracks the highest high and lowest low to define the range.
These are stored in variables: asianHigh and asianLow.
🧊 3. Box Drawing for the Asian Range
Once the Asian session ends:
A visual box is drawn around the session using box.new().
This box spans from the session start to end bars and from the high to low.
It helps visually see the range price must break out from.
🚨 4. Breakout Signals
After the Asian session:
A Long Breakout signal is generated if:
The candle closes above the Asian High.
A Short Breakout signal is generated if:
The candle closes below the Asian Low.
This corresponds to 00:00 to 08:00 UTC
These are shown with:
✅ Green up label for long breakouts
❌ Red down label for short breakouts
🧯 5. Fakeout Detection
If price breaks out but closes back inside the Asian range, it’s marked as a Fakeout:
Long Fakeout: Price breaks above high, then closes back below.
Short Fakeout: Price breaks below low, then closes back above.
These are marked with orange X-crosses above or below candles.
⚠️ 6. Wide Range Filter
If the Asian session range is too wide (e.g. > 40 pips), a gray background is drawn.
This warns you not to trade that day since breakouts from wide ranges are unreliable.
📣 7. Alert Conditions
The script can trigger alerts in TradingView when:
🔔 A Long or Short Breakout occurs
⚠️ A Fakeout is detected
You can set these up via the TradingView alert system.
🎯 Overall Purpose:
The script helps you:
Clearly see the Asian session range
Identify breakout opportunities at the London open
Avoid trading during fakeouts or wide-range sessions
Get alerted when breakout/fakeout conditions occur
Autofib Extensions | DTDHello trader comuunity!
I'm introducing another script that is part of my main day-trading strategy. We all know regardless of what strategy we use, we need to know what levels offer the least amount of risk to our trade entry and a great tool to anticipate how far a move might go or what level a move may retrace to are the Fibonacci Retracement and Extensions. This indicator combines both together, but with a twist.
The main elements of the script are:
1. Multiple Session High and Lows | Developing my first script led me to understand that measuring key times during each session provides understanding of the market's continuity. I have provided 3 "sessions' a user can define according to CST time where the script saves the high and low of that session window to produce the retracement and extensions from those plots. Currently, the levels are always plotted from low to high (with the 0 mark being the high) and negative values provided so the levels are consistent. You can toggle each session on or off.
2. Coloring Key Retracements / Extensions | I use a dark background for my charts so the default colors help me distinguish from other another indicator I use. Feel free to adjust the colors to your preference. I consider 3 different colors because of their significance. Retracements that you want to see continue fall back into the .50 to .618 level (this I consider the "Golden Zone"). While basic Elliott Wave Theory states a wave is completed near the 1.618 level (this I consider "Major Extensions"). Everything isn't noise, but minor levels in a larger sequence.
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Script Limitations
All of my scripts are made with the help of ChatGPT so there are going to be limitations. One current one that I have made progress on, but not fully is when you are viewing a timeframe where the candle doesn't start when a session window starts. On smaller timeframes like the 7-minute this is not an issue. However, on the hourly, if your session window starts at the half hour which the 3rd session default window does, the lines will not produce. I will hopefully have this rectified in the near future. I will open the script since none of this work is original in nature and I would love to see how others can create a better product. Also, this is mainly a futures trading tool. If you are using this on stocks you will find it not as useful if the session window is too wide since the script waits until the session window closes to calculate the extension values.
Cheers,
DTD
Weekly Levels Prep (Smart Weekly Candle)This script draws key weekly levels based on the most recent completed weekly candle (Monday–Friday). It automatically calculates and plots:
✅ Weekly High & Low
✅ Midpoint (50% level)
✅ Extension levels above and below
All levels are dynamically updated every new week and are visually marked with clean color-coded horizontal lines. Price values are shown near the price axis for clear visibility across all timeframes.
Great for:
Weekly preparation
Swing trading setups
Mean reversion and range breakouts
🔄 Works on all timeframes
🔍 Lightweight and non-intrusive
Built by a trader, for traders. 💼📈
