[itradesize] ICT Opening range
This indicator automatically annotates the opening ranges of the AM and PM sessions. It should be used on the 1-minute timeframe , although you can check and build a further models when using a 2-3-4 or even 5-minute timeframe. You can customize this under the settings tab.
Additionally, it includes features such as standard deviations and the initial fair value gap presented. Everything is based on what ICT said in his algorithmic timing video.
The algorithm will continue to adjust prices higher or lower until it reaches a predetermined target price. This process will occur within specific time frames: the last 10 minutes before the hour and the first 10 minutes after a new hour begins.
For the AM session opening range, this is from 9:30 to 10:00 , and for the PM session, it's from 13:30 to 14:00 . Defining these ranges allows us to identify the first presented fair value gaps there, as the algorithm is designed to leave these signatures for smart money. This process of time-based delivery precision repeats every day. You can build a whole New York model on this.
It's important to journal and backtest your results results. If the market breaks the opening range on either side and there is evident liquidity, it is highly likely that it will pursue that liquidity.
However, before doing so, the market should retrace back to the first fair value gap if it hasn’t already occurred or back to the 0.75 or 0.5 level of the range at maximum.
When does this happen? Typically, when a macro event occurs— for example, during the lunch macro from 11:30 to 12:00 . In most cases, you can expect a retracement during lunch macro. If the market retraces beyond these levels, there is a higher probability that the expected scenario will not play out.
The algorithm primarily refers to the 30-minute opening range each time. The standard deviation levels can be used to establish algorithmic delivery targets and anticipate another run after the PM session opening range has occurred. The AM session often helps determine the likely direction of movement after the PM session range concludes.
The PM macro runs from 15:15 to 15:45 . At this time, the market will typically operate within the narrative that is currently underway.
Cari dalam skrip untuk "liquidity"
RSI + SMA Strategy (Second Touch Confirmation + Volume Filter)RSI + SMA Strategy (Second Touch Confirmation + Volume Filter)
👉 Optimized for the 3-minute timeframe
This indicator combines the power of the RSI (Relative Strength Index) and its SMA (Simple Moving Average) to generate highly reliable BUY and SELL signals. The strategy is designed to confirm signals only on the second consecutive touch of the overbought (70) and oversold (30) thresholds, reducing false signals caused by sudden market movements. Additionally, it includes a dynamic volume filter, ensuring that signals are generated only during periods of high liquidity.
Key Features
Second Touch RSI:
BUY and SELL signals are generated only after the RSI reaches the overbought/oversold threshold for the second consecutive time, improving accuracy.
Volume Filter:
Signals are confirmed only if the current volume exceeds the 20-period moving average multiplied by a configurable value (volume_multiplier), filtering out low-liquidity moments.
Optimized for Short Timeframes:
Perfect for the 3-minute timeframe, ideal for scalping and intraday trading strategies.
Customizable Parameters:
Adjustable settings for RSI, SMA, overbought/oversold thresholds, and volume filter, making it adaptable to various markets and conditions.
How to Use It
BUY Signal: When RSI touches the oversold threshold (30) for the second consecutive time and crosses above its SMA, with volume higher than average.
SELL Signal: When RSI touches the overbought threshold (70) for the second consecutive time and crosses below its SMA, with volume higher than average.
Upcoming Developments
📢 We will soon release our private strategy!
This strategy will be based on advanced logic and optimized to achieve even more consistent results in volatile markets like cryptocurrencies. Stay tuned for more details!
Disclaimer
This indicator is designed to support decision-making in trading. We recommend testing it on a demo account before using it in live trading. Remember that trading involves risks and does not guarantee profits.
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.
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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.
Fair Value Gap Finder [Find Better Trades]Fair Value Gap Finder (FVG) – Spot Institutional Imbalances
📈 Identify Key Market Imbalances
The Fair Value Gap Finder automatically detects price inefficiencies where aggressive buying or selling has created an imbalance in liquidity. These gaps, often left by institutional traders, can serve as key areas for price to revisit before continuing its trend.
🔍 How It Works:
Highlights bullish Fair Value Gaps (FVGs) in green, signaling potential support zones.
Highlights bearish Fair Value Gaps (FVGs) in red, signaling potential resistance zones.
Uses ATR-based filtering to eliminate small, insignificant gaps, focusing only on high-probability setups.
Alerts included! Get notified when a valid Fair Value Gap is detected.
📊 How to Trade Using FVGs:
✅ For Buy Trades: Wait for price to return to a bullish FVG and confirm support before entering long.
✅ For Sell Trades: Wait for price to revisit a bearish FVG and confirm resistance before entering short.
✅ Use with candlestick patterns, trend analysis, or volume for additional confirmation.
⚙️ Customizable Settings:
Adjust the ATR Multiplier to control how large a gap must be before triggering a signal.
Enable alerts to stay informed in real time when new FVGs appear.
💡 Why Use This Indicator?
Fair Value Gaps are widely used by professional traders to spot areas of liquidity, making them valuable for scalping, swing trading, and institutional-style trading.
🚀 Add it to your TradingView chart and start trading with precision!
Quantitative Easing and Tightening PeriodsQuantitative Easing (QE) and Quantitative Tightening (QT) periods based on historical events from the Federal Reserve:
Quantitative Easing (QE) Periods:
QE1:
Start: November 25, 2008
End: March 31, 2010
Description: The Federal Reserve initiated QE1 in response to the financial crisis, purchasing mortgage-backed securities and Treasuries.
QE2:
Start: November 3, 2010
End: June 29, 2011
Description: QE2 involved the purchase of $600 billion in U.S. Treasury bonds to further stimulate the economy.
QE3:
Start: September 13, 2012
End: October 29, 2014
Description: QE3 was an open-ended bond-buying program with monthly purchases of $85 billion in Treasuries and mortgage-backed securities.
QE4 (COVID-19 Pandemic Response):
Start: March 15, 2020
End: March 10, 2022
Description: The Federal Reserve engaged in QE4 in response to the economic impact of the COVID-19 pandemic, purchasing Treasuries and MBS in an effort to provide liquidity.
Quantitative Tightening (QT) Periods:
QT1:
Start: October 1, 2017
End: August 1, 2019
Description: The Federal Reserve began shrinking its balance sheet in 2017, gradually reducing its holdings of U.S. Treasuries and mortgage-backed securities. This period ended in August 2019 when the Fed decided to stop reducing its balance sheet.
QT2:
Start: June 1, 2022
End: Ongoing (as of March 2025)
Description: The Federal Reserve started QT again in June 2022, reducing its holdings of U.S. Treasuries and MBS in response to rising inflation. The Fed has continued this tightening cycle.
These periods are key moments in U.S. monetary policy, where the Fed either injected liquidity into the economy (QE) or reduced its balance sheet by not reinvesting maturing securities (QT). The exact dates and nature of these policies may vary based on interpretation and adjustments to the Fed's actions during those times.
ATR 3x Multiplier StrategyBeta version
Volatility and Candle Spikes in Trading
Volatility
Volatility refers to the degree of variation in the price of a financial asset over time. It measures how much the price fluctuates and is often associated with risk and uncertainty in the market. High volatility means larger price swings, while low volatility indicates more stable price movements.
Key aspects of volatility:
Measured using indicators like Average True Range (ATR), Bollinger Bands, and Implied Volatility (IV).
Influenced by factors such as market news, economic events, and liquidity.
Higher volatility increases both risk and potential profit opportunities.
Candle Spikes
A candle spike (or wick) refers to a sudden price movement that forms a long shadow or wick on a candlestick chart. These spikes can indicate strong buying or selling pressure, liquidity hunts, or stop-loss triggers.
Types of candle spikes:
Bullish Spike (Long Lower Wick): Indicates buyers rejected lower prices, pushing the price higher.
Bearish Spike (Long Upper Wick): Suggests sellers rejected higher prices, pushing the price lower.
Stop-Loss Hunt: Market makers may trigger stop-losses by creating artificial spikes before reversing the price.
News-Induced Spikes: Economic data releases or unexpected events can cause sudden price jumps.
Understanding volatility and candle spikes can help traders manage risk, spot entry/exit points, and avoid false breakouts. 🚀📈
Electronic Trading Hours Session/CandlesThis indicator visually distinguishes the electronic trading session, spanning from the prior day's close (e.g., 5:00 PM EST) through the overnight period until the next day's opening bell (e.g., 9:30 AM EST).
It can be customized to highlight this period with a shaded zone or colored candles depending on the trader’s preference.
The overnight levels that create the opening range gap often act as critical zones of liquidity.
The indicator provides a clear visual cue of potential price magnets that smart money (institutional traders) may target during the opening bell session to trigger liquidity sweeps.
BPR [TakingProphets]The BPR (Balanced Price Range) Indicator by Taking Prophets is built for traders who follow ICT (Inner Circle Trader) concepts and smart money strategies. In ICT methodology, a Balanced Price Range (BPR) occurs when price rapidly moves in one direction, creating an imbalance that often gets revisited before price continues its trend. These areas represent inefficiencies in the market where liquidity was not properly distributed, making them key zones for potential retracements and trade setups.
How the Indicator Works:
🔹 Automatically Detects BPRs – No need to manually mark imbalances; the indicator highlights them for you.
🔹 Helps Identify Smart Money Footprints – Spot areas where price is likely to retrace and rebalance liquidity.
🔹 Customizable Sensitivity – Adjust detection parameters based on your preferred trading style.
🔹 Works Across All Markets – Apply it to Forex, Futures, Crypto, and Stocks on TradingView.
🔹 Clean and Intuitive Interface – Designed to be simple yet powerful for both new and experienced traders.
Financials Score All Description of the "Financials Score All" Script
This Pine Script calculates a financial score for a specific stock, based on various financial metrics. The purpose is to provide a comprehensive numerical score that reflects the financial health of the stock. The score is calculated using multiple financial indicators, including profitability, valuation, debt management, and liquidity. Here’s a breakdown of what each part of the script does:
period = input.string('FQ', 'Period', options= )
FQ refers to Quarterly financial data.
FY refers to Fiscal Year financial data.
Financial Metrics:
The script uses various financial metrics to calculate the score. These are obtained via request.financial, which retrieves financial data for the stock from TradingView's database. Below are the metrics used:
opmar (Operating Margin): Measures the company's profitability as a percentage of revenue.
eps (Earnings Per Share): Represents the portion of a company's profit allocated to each outstanding share.
eps_ttm (Earnings Per Share – Trailing Twelve Months): EPS over the most recent 12 months.
pe_ratio (Price-to-Earnings Ratio): A measure of the price investors are willing to pay for a stock relative to its earnings.
pb_ratio (Price-to-Book Ratio): A valuation ratio comparing a company’s market value to its book value.
de_ratio (Debt-to-Equity Ratio): A measure of the company’s financial leverage, showing how much debt it has compared to shareholders' equity.
roe_pb (Return on Equity Adjusted to Book): Measures the company's profitability relative to its book value.
fcf_per_share (Free Cash Flow per Share): Represents the free cash flow available for dividends, debt reduction, or reinvestment, per share.
pfcf_ratio (Price-to-Free-Cash-Flow Ratio): A measure comparing a company’s market value to its free cash flow.
current_ratio (Current Ratio): A liquidity ratio that measures a company's ability to pay short-term obligations with its current assets.
RSI Calculation:
The script calculates the Relative Strength Index (RSI) for the stock using an 8-period lookback:
rsi = ta.rsi(close, 8)
Score Calculation:
The script calculates a total score by adding points based on the values of the financial metrics. Each metric is checked against a condition, and if the condition is met, the score is incremented:
If the Operating Margin (opmar) is greater than 20, the score is incremented by 20 points.
If Earnings Per Share (EPS) is positive, 10 points are added.
If the P/E ratio is between 0 and 20, 10 points are added.
If the P/B ratio is less than 3, 10 points are added.
If the Debt-to-Equity ratio is less than 0.8, 10 points are added.
If the Return on Equity Adjusted to Book is greater than 10, 10 points are added.
If the P/FCF ratio is between 0 and 15, 10 points are added.
If the Current Ratio is greater than 1.61, 10 points are added.
If the RSI is less than 35, 10 points are added.
The score is accumulated based on these conditions and stored in the total_score variable.
Displaying the Total Score:
Finally, the total score is plotted on the chart:
Summary of How It Works:
This script calculates a financial score for a stock using a variety of financial indicators. Each metric has a threshold, and when the stock meets certain criteria (for example, a good operating margin, a healthy debt-to-equity ratio, or a low P/E ratio), points are added to the overall score. The result is a single numerical value that reflects the financial health of the stock.
This score can help traders or investors identify companies with strong financials, or serve as a comparison tool between different stocks based on their financial health.
Generally >60 is the best stocks for med and long term trades
Mean Price
^^ Plotting switched to Line.
This method of financial time series (aka bars) downsampling is literally, naturally, and thankfully the best you can do in terms of maximizing info gain. You can finally chill and feed it to your studies & eyes, and probably use nothing else anymore.
(HL2 and occ3 also have use cases, but other aggregation methods? Not really, even if they do, the use cases are ‘very’ specific). Tho in order to understand why, you gotta read the following wall, or just believe me telling you, ‘I put it on my momma’.
The true story about trading volumes and why this is all a big misdirection
Actually, you don’t need to be a quant to get there. All you gotta do is stop blindly following other people’s contextual (at best) solutions, eg OC2 aggregation xD, and start using your own brain to figure things out.
Every individual trade (basically an imprint on 1D price space that emerges when market orders hit the order book) has several features like: price, time, volume, AND direction (Up if a market buy order hits the asks, Down if a market sell order hits the bids). Now, the last two features—volume and direction—can be effectively combined into one (by multiplying volume by 1 or -1), and this is probably how every order matching engine should output data. If we’re not considering size/direction, we’re leaving data behind. Moreover, trades aren’t just one-price dots all the time. One trade can consume liquidity on several levels of the order book, so a single trade can be several ticks big on the price axis.
You may think now that there are no zero-volume ticks. Well, yes and no. It depends on how you design an exchange and whether you allow intra-spread trades/mid-spread trades (now try to Google it). Intra-spread trades could happen if implemented when a matching engine receives both buy and sell orders at the same microsecond period. This way, you can match the orders with each other at a better price for both parties without even hitting the book and consuming liquidity. Also, if orders have different sizes, the remaining part of the bigger order can be sent to the order book. Basically, this type of trade can be treated as an OTC trade, having zero volume because we never actually hit the book—there’s no imprint. Another reason why it makes sense is when we think about volume as an impact or imbalance act, and how the medium (order book in our case) responds to it, providing information. OTC and mid-spread trades are not aggressive sells or buys; they’re neutral ticks, so to say. However huge they are, sometimes many blocks on NYSE, they don’t move the price because there’s no impact on the medium (again, which is the order book)—they’re not providing information.
... Now, we need to aggregate these trades into, let’s say, 1-hour bars (remember that a trade can have either positive or negative volume). We either don’t want to do it, or we don’t have this kind of information. What we can do is take already aggregated OHLC bars and extract all the info from them. Given the market is fractal, bars & trades gotta have the same set of features:
- Highest & lowest ticks (high & low) <- by price;
- First & last ticks (open & close) <- by time;
- Biggest and smallest ticks <- by volume.*
*e.g., in the array ,
2323: biggest trade,
-1212: smallest trade.
Now, in our world, somehow nobody started to care about the biggest and smallest trades and their inclusion in OHLC data, while this is actually natural. It’s the same way as it’s done with high & low and open & close: we choose the minimum and maximum value of a given feature/axis within the aggregation period.
So, we don’t have these 2 values: biggest and smallest ticks. The best we can do is infer them, and given the fact the biggest and smallest ticks can be located with the same probability everywhere, all we can do is predict them in the middle of the bar, both in time and price axes. That’s why you can see two HL2’s in each of the 3 formulas in the code.
So, summed up absolute volumes that you see in almost every trading platform are actually just a derivative metric, something that I call Type 2 time series in my own (proprietary ‘for now’) methods. It doesn’t have much to do with market orders hitting the non-uniform medium (aka order book); it’s more like a statistic. Still wanna use VWAP? Ok, but you gotta understand you’re weighting Type 1 (natural) time series by Type 2 (synthetic) ones.
How to combine all the data in the right way (khmm khhm ‘order’)
Now, since we have 6 values for each bar, let’s see what information we have about them, what we don’t have, and what we can do about it:
- Open and close: we got both when and where (time (order) and price);
- High and low: we got where, but we don’t know when;
- Biggest & smallest trades: we know shit, we infer it the way it was described before.'
By using the location of the close & open prices relative to the high & low prices, we can make educated guesses about whether high or low was made first in a given bar. It’s not perfect, but it’s ultimately all we can do—this is the very last bit of info we can extract from the data we have.
There are 2 methods for inferring volume delta (which I call simply volume) that are presented everywhere, even here on TradingView. Funny thing is, this is actually 2 parts of the 1 method. I wonder how many folks see through it xD. The same method can be used for both inferring volume delta AND making educated guesses whether high or low was made first.
Imagine and/or find the cases on your charts to understand faster:
* Close > open means we have an up bar and probably the volume is positive, and probably high was made later than low.
* Close < open means we have a down bar and probably the volume is negative, and probably low was made later than high.
Now that’s the point when you see that these 2 mentioned methods are actually parts of the 1 method:
If close = open, we still have another clue: distance from open/close pair to high (HC), and distance from open/close pair to low (LC):
* HC < LC, probably high was made later.
* HC > LC, probably low was made later.
And only if close = open and HC = LC, only in this case we have no clue whether high or low was made earlier within a bar. We simply don’t have any more information to even guess. This bar is called a neutral bar.
At this point, we have both time (order) and price info for each of our 6 values. Now, we have to solve another weighted average problem, and that’s it. We’ll weight prices according to the order we’ve guessed. In the neutral bar case, open has a weight of 1, close has a weight of 3, and both high and low have weights of 2 since we can’t infer which one was made first. In all cases, biggest and smallest ticks are modeled with HL2 and weighted like they’re located in the middle of the bar in a time sense.
P.S.: I’ve also included a "robust" method where all the bars are treated like neutral ones. I’ve used it before; obviously, it has lesser info gain -> works a bit worse.
Price and OI ChangePrice and OI Change
Description:
The "Price and OI Change" indicator provides insights into market dynamics by analyzing the price and open interest (OI) changes over a 7-day period. This indicator is designed for use with both spot and futures markets, including cryptocurrencies.
Key Features:
Price and OI Change Calculation: Computes the 7-day change in price and open interest to help identify market trends and shifts.
Market Conditions Visualization: Differentiates market conditions by changing the background color based on:
Leverage-Driven Market: Blue background indicates increasing prices and OI, suggesting a bullish trend driven by leverage.
Spot-Driven Market: Green background shows increasing prices but decreasing OI, indicating a bullish trend driven by spot market activity.
Leverage Sell-Off: Orange background reveals decreasing prices with increasing OI, signaling a potential liquidation phase.
Deleveraging Sell-Off: Red background reflects decreasing prices and OI, indicating a bearish market with reduced leverage.
Top 3 BTC Futures Average OI: Displays the average open interest for the top 3 BTC futures contracts from major exchanges (Binance, OKX, Bybit). This helps gauge overall market sentiment and liquidity.
Visualization Tools: Includes optional plotting of open interest data and average OI for better visualization of market conditions.
Usage:
Traders and Analysts: Use the background color changes and average OI to make informed decisions about market entry and exit points.
Futures Traders: Track OI changes in major BTC futures to assess market strength and potential liquidity issues.
Relative Equal Highs/LowsThis Pine script indicator is designed to create a visual representation of the relative equal highs & lows formed and automatically removed mitigated ones. Unlike indicators designed to show exact equal high/lows this indicator allows a small, configurable degree of variance between price to identify areas where price stops.
Relevance:
Relative Equal highs and lows can serve as valuable tools in identifying potential shifts in trend direction. They come into play when the price hits a support or resistance level and can’t advance further, signaling a possible reversal or pivot point. When the price sufficiently retreats from these levels, relative equal highs and lows can also indicate liquidity draws where buy/sell stops might be positioned, in accordance with SMC/ICT concepts.
How It Works:
The indicator tracks all unmitigated highs & lows within the chart’s present timeframe, limited to the user-defined max bars lookback for optimal performance. If the prices are within the configured variance they are marked as relatively equal and at that point are visually identified by a horizontal line, which connects the two (or more) points of price. Depending on configuration of the indicator, a line is rendered from the 1st, last or both values within the relatively equal range of price. A unique feature of this indicator is its ability to remove the line once the price mitigates the relative equal high/low by falling below the lows or rising above highs. This ensures the chart remains uncluttered and highlights only the currently relevant levels, setting it apart from other indicators providing similar functionality.
Configurability:
The indicator offers five style settings for complete customization of the lines that represent equal highs/lows. These settings include line style, color, and width, along with an option to extend the lines to the right of the chart for enhanced visibility of equal high/low levels. To optimize performance, the indicator allows users to configure the lookback length, determining how far back the price history should be examined. In most instances, the default setting of 500 bars proves more than adequate. Additionally, you can set thresholds via separate configs for stocks & indices that will determine if the price is relatively equal and lastly allow you to configure where the indicator line should be drawn, the first, last or all the values.
Additional notes:
This uses a different approach then my “equal highs/lows” indicator to identify price levels and because it focuses specifically on relative as opposed to exact values it is entirely different and may show “weaker”, but still important levels of liquidity. This indicator is more suited for analysis of stocks and indices or higher-timeframes where price-action rarely forms exact equal values instead more frequently forming almost equal values. My other indicator is more suited for smaller (15m or less) timeframe on indices where exact equal prices are often identical. Depending on situation different indicators should be used.
Open Intrest / Volume / Liquidations (Suite) [BigBeluga]This indicator is a suite of tools that aims to provide traders with efficient metrics to analyze the market in a different way, such as various types of Open Interest, Intraday Volume, and Liquidations.
This indicator can both save time and also provide a different approach to the usual price action trading style.
🔶 FEATURES
The indicator contains the following features:
Open Interest Suite
- Delta OI
- Net longs and shorts
- OI Relative Strength Index
Intraday Volume Suite
- Bullish and Bearish LTF Volume
- CVD
- Delta Volume
Liquidations Suite
- Long and Short Liquidations
- Cumulative Liquidations
🔶 EXAMPLE OF SUITE
In the example above, we can see how we can plot long and short positions, both opening and closing out.
This can give a unique way to view which side is the strongest but also which side has the most resting liquidity.
For example, if more longs are entering the market, it also means more liquidity for longs and vice versa.
Or, for example, plotting the delta OI will allow the user to see big percentages in change and spot big areas of position closing out.
This presents a fascinating method for observing numerous positions closing out in conjunction with a surge of liquidations, which could indicate a potential reversal in price.
Here, we can see a basic example of using intraday volume on a 1m LTF.
With this, we are able to see both bullish and bearish volume of the same candle, very useful to see both volumes traded in the same candle.
Using the CVD to see the overall direction based purely on the volume and spot divergence, for example, the price in an uptrend but CVD going down, indicating weak shorts in the market or trapped shorts.
Or simply view liquidations happening in the market in a very different way, both long and short liquidation at the same time + the option to use multi-timeframe liquidations.
🔶 CONCLUSION
The idea of this script is to provide a set of tools in a unique script to optimize time and analyze the market in both a quick way and in a different way than usual.
Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
Advanced Optimized VSA - 15 MinThis script is written in Pine Script and is designed to be run on the TradingView trading platform. It is an advanced technical analysis indicator that utilizes various methods and indicators to generate trading signals based on a Volume Spread Analysis (VSA) approach.
Here's a detailed breakdown of its functionalities:
### Customizable Parameters:
1. `scoreLabel` and `TDLabel`: Customizable labels for score and trend direction.
2. `labelColorScore` and `labelColorTD`: Colors for the score and trend direction labels.
### Base Indicators and Variables:
1. `spread`: Calculates the difference between the high and low of a candle.
2. `emaVolume`: Exponential moving average of volume over a 21-period range.
3. `rsi14`: Relative Strength Index (RSI) over a 14-period range.
4. `sma200` and `ema50`: Simple moving average over a 200-period range and exponential moving average over a 50-period range, respectively.
5. `volatility`: Calculates the 14-period Average True Range (ATR) to determine volatility.
6. `trendDirection`: Establishes the trend direction based on the SMA200.
### Risk Management:
1. `atrValue`: Calculates the value of the ATR.
2. `stopLoss` and `takeProfit`: Calculates the stop-loss and take-profit levels based on the ATR.
### MACD:
Computes the MACD line, signal line, and histogram.
### Volume Analysis:
1. `weightedVol`: Weighted volume.
2. `forceFactor`: Measures the strength of price movement in relation to volume.
### Support and Resistance:
1. `support` and `resistance`: Calculates support and resistance levels based on the most recent 50 periods.
### Liquidity Check:
1. `isLiquid`: Checks if an asset is sufficiently liquid.
### Score Calculation:
Evaluates various factors such as price position relative to support/resistance levels, RSI, MACD, strength of movement, and volatility to generate a score.
### Criteria for Final Signals:
1. `isBullSpread` and `isBearSpread`: Generates a bullish or bearish signal based on various factors, including the score, trend direction, and liquidity.
### Notifications:
Generates alert conditions for bullish and bearish signals.
### Graphical Elements:
Displays various indicators and signals on the chart, including stop-loss, take-profit, SMA200, EMA50, and support and resistance lines.
### Debugging Labels:
Shows labels on the chart for score and trend direction.
The goal is to provide a comprehensive picture of the current asset, taking into consideration various factors and generating potentially profitable trading signals.
################################################################### ITALIANO ########################################################################################
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Questo script è scritto in Pine Script e progettato per essere eseguito sulla piattaforma di trading TradingView. È un indicatore di analisi tecnica avanzata che utilizza diversi metodi e indicatori per generare segnali di trading basati su un approccio Volume Spread Analysis (VSA).
Ecco un riepilogo dettagliato delle funzionalità:
### Parametri personalizzabili:
1. `scoreLabel` e `TDLabel`: Etichette personalizzabili per i punteggi e la direzione del trend.
2. `labelColorScore` e `labelColorTD`: Colori delle etichette per punteggio e direzione del trend.
### Indicatori e variabili base:
1. `spread`: Calcola la differenza tra il massimo e il minimo di una candela.
2. `emaVolume`: Media mobile esponenziale del volume con un periodo di 21.
3. `rsi14`: RSI (Relative Strength Index) con un periodo di 14.
4. `sma200` e `ema50`: Media mobile semplice con un periodo di 200 e media mobile esponenziale con un periodo di 50, rispettivamente.
5. `volatility`: Calcola l'Average True Range (ATR) con un periodo di 14 per determinare la volatilità.
6. `trendDirection`: Stabilisce la direzione del trend basata sulla SMA200.
### Gestione del rischio:
1. `atrValue`: Calcola il valore dell'ATR.
2. `stopLoss` e `takeProfit`: Calcola i livelli di stop-loss e take-profit basati sull'ATR.
### MACD:
Calcola le linee MACD, segnale e l'istogramma.
### Analisi del volume:
1. `weightedVol`: Volume ponderato.
2. `forceFactor`: Misura la forza del movimento del prezzo in relazione al volume.
### Supporto e resistenza:
1. `support` e `resistance`: Calcola i livelli di supporto e resistenza basati sui 50 periodi più recenti.
### Verifica della liquidità:
1. `isLiquid`: Verifica se un asset è sufficientemente liquido.
### Calcolo del punteggio:
Valuta diversi fattori come la posizione del prezzo rispetto ai livelli di supporto/resistenza, RSI, MACD, forza del movimento e volatilità per generare un punteggio.
### Criteri per i segnali finali:
1. `isBullSpread` e `isBearSpread`: Genera un segnale rialzista o ribassista basato su vari fattori, incluso il punteggio, la direzione del trend e la liquidità.
### Notifiche:
Genera condizioni di allarme per segnali rialzisti e ribassisti.
### Elementi grafici:
Visualizza diversi indicatori e segnali sul grafico, inclusi stop-loss, take-profit, SMA200, EMA50, e linee di supporto e resistenza.
### Etichette di debug:
Mostra etichette sul grafico per il punteggio e la direzione del trend.
L'obiettivo è fornire un quadro completo dell'asset corrente, prendendo in considerazione diversi fattori e generando segnali di trading potenzialmente profittevoli.
Scalping level 1.3.0The indicator shows the horizontal levels behind which the liquidity accumulates. The indicator is based on the price extremums according to the specified settings. Each extremum is marked with a faint blue line and the price. If two or more extrema are located at the same price or close enough to each other, they are highlighted in bright blue, and it indicates a strong resistance or support level. When prices approach strong resistance levels, we can consider the situation on a long breakout or a bounce from the level in the short. As price approaches strong support levels, we could consider a breakout in the short or a bounce from the level in the long. Each level has a time (indicated at each price extremum), when it was formed in hours, the more hours ago the level was formed, the stronger it is and the more likely is the price reaction at this level.
The marks next to the price show the distance in percent to the nearest strong levels, it gives a reference point for how soon the price will approach these levels.
Additional indicators, located at the top right of the chart help to make decisions in trading.
Daily dollar volume - shows how interesting the instrument to the market participants, if the traded volume for 24 hours is low, then it is not worth to pay attention to this tool.
Bitcoin correlation - (used for the cryptocurrency market), if the coin price follows the bitcoin (the indicator value is close to 1), then you should exclude this coin, because the price is controlled by robot correlators, not market participants.
Natr - the average volatility of a 5-minute candle in %. The low value of volatility can indicate that the instrument is not active at the moment. Also it is possible to use this value as a stoploss in scalper deals.
Price change - price change for the current session in %, if the value is more than 10% (for cryptocurrencies), then the breakdown of resistance levels have a higher probability than a bounce, if the value is less than -10%, then the probability of breaking support levels have a higher than a bounce.
Percentage of average daily ATR - shows how much the price passed in % for the current session from the average daily ATR. If price passed about 100%, it is possible to consider the price reversal from resistance or support levels.
Important! When trading on levels it is necessary to consider the situation in the Depth of Market. Pay attention to large densities located near support and resistance levels.
=== Basic settings: ===
LOCAL LEVEL, MIDDLE LEVEL, GLOBAL LEVEL . Three ranges of levels (local, middle, global). For each range, you can configure the period and lifetime of the level. For example, global levels are the strongest, they have the longest period and the longest time of existence (note: 0 for Lifetime means infinite time of existence), while local levels have the shortest period and the shortest time of existence. Period - the period in which the level is built. Lifetime - time after which the level is removed from the chart. Color and width - color and width of the line.
BREAK LEVELS . Levels broken by the price. These levels are displayed for convenient tracking of previous breakouts. Parameters are set similarly to other levels.
IMPORTANT LEVELS . Important levels show behind which price range the greatest accumulation of liquidity. Important levels can be adjusted by setting the minimum number of adjacent levels, for example 2 or more, as well as the maximum distance between adjacent levels. Thus, important levels show the accumulation of price extremums, behind which there are Stop Losses of the participants.
Near level coefficient - the distance coefficient between adjacent levels, the higher the coefficient is, the greater is the acceptable price range between the levels. The coefficient is multiplied by the average ATR, as a result we get the price range. For example, if we specify 0, then strong levels will be detected only if 2 or more extrema have the same price.
Minimum near levels - the minimum number of adjacent (close to each other) levels. For example, if 2 is specified, then if 2 or more levels are situated near each other at a distance not exceeding the distance, specified in the Near level coefficient, then those levels will be displayed in bright blue color.
Week level transparent - transparency of "weak" levels located at the price extremums.
COMMON.
Max distance to level - the maximum distance of levels is set by a coefficient, it is necessary to display only the closest levels to hide the levels that are formed very far from the current price. It is calculated on the basis of ATR.
Show level time - shows level existence time.
PRICE. Visual settings of price levels on the chart
Size - print size of price on the chart
Color - color of price on the chart
Round price color - color of the round price number. The round number is the price with the last two digits 0. Example 28124.00 or 0.2500
INDICATORS. Auxiliary numeric indicators (located in the upper right corner of the chart):
Daily dollar volume , the traded volume for the last 24 hours in dollars. You can specify a volume threshold in millions of dollars, above which the value will be highlighted in green. The default value is 100 million dollars. A high value of traded volume indicates a large number of participants and increases the probability of volatility of the instrument.
Bitcoin correlation , an indicator of price correlation with bitcoin, the lower the indicator, the instrument is more independent, the closer to 1, the stronger the instrument repeats bitcoin price movements. It has a threshold value of 0.5 by default. If the indicator reading is below the threshold, it is highlighted in color.
Natr , shows the average range at which the price passes in 5 min. The higher the indicator, the higher the volatility of the instrument.
Price change , price change in % for the current session.
Percentage of average daily ATR , shows how much the price passed in % for the current session from the average daily ATR.
Price & Volume Profile (Expo)█ Overview
The Price & Volume Profile provides a holistic perspective on market dynamics by simultaneously tracking price action and trading volume across a range of price levels. So it is not only a volume-based indicator but also a price-based one. In addition to illustrating volume distribution, it quantifies how frequently the price has fallen within a particular range, thus offering a holistic perspective on market dynamics.
This unique and comprehensive approach to market analysis by considering both price action and trading volume, two crucial dimensions of market activity. Its distinctive methodology offers several advantages:
Holistic Market View: By simultaneously tracking the frequency of specific price ranges (Price Profile) and the volume traded at those ranges (Volume Profile), this indicator provides a more complete picture of market behavior. It shows not only where the market is trading but also how much it's trading, reflecting both price acceptance levels and market participation intensity.
Point of Control (POC): The POC, as highlighted by this indicator, serves as a significant reference point for traders. It identifies the price level with the highest trading activity, thus indicating a strong consensus among market participants about the asset's fair value. Observing how price interacts with the POC can offer valuable insights into market sentiment and potential trend reversals.
Support and Resistance Levels: Price levels with high trading activity often act as support or resistance in future price movements. The indicator visually represents these levels, enabling traders to anticipate potential price reactions.
Price Profile
Price and Volume Profile
█ Calculations
The algorithm analyzes both trade frequency and volume across different price levels. It identifies these levels within the visible chart range, then examines each bar to determine if the selected price falls within these levels. If so, it increases a counter and adds the trading volume. This process repeats across the visible range and is visualized as a horizontal histogram, each bar representing a price level and the bar length reflecting trade frequency and volume. Additionally, it calculates the Point of Control (POC), signifying the price level with the highest activity.
In summary: The histogram presents a dual perspective - not only the traded volume at each price level but also the frequency of the price hitting each range. The longer the bar, the more times the price has frequented that specific range, revealing key insights into price behavior and acceptance levels. These frequently visited areas often emerge as strong support or resistance zones, helping traders navigate market movements.
Please note that the indicator adjusts to the visible price range, making it adaptable to changing market conditions. This dynamic analysis can provide more relevant and timely information than static indicators.
█ How to use
This indicator is beneficial for traders as it offers insights into the distribution of trading activity across different price levels. It helps identify key areas of support and resistance and gives a visual representation of market sentiment and liquidity.
The point of control (POC) , which is the price level with the highest traded volume or frequency count, becomes even more crucial in this context. It marks the price at which the most trading activity occurred, signaling a strong consensus among market participants about the asset's fair value. If the market price deviates significantly from the POC, it could suggest an overbought or oversold condition, potentially leading to a price reversion.
Fair Price Areas/gaps are specific price levels or zones where an asset has spent limited time in the past. These areas are considered interesting or significant because they may have an impact on future price action.
Similar to the concept of fair value gaps, which refers to discrepancies between an asset's market price and its estimated intrinsic value, Fair Price Areas/gaps focus on price levels that have been relatively underutilized in terms of trading activity. When an asset's price reaches a Fair Price Area/gap, traders and investors pay attention because they expect the price to react in some way. The rationale behind this concept is that price tends to gravitate towards areas where it has spent less time in the past, as the market perceives them as significant levels.
█ Settings
The indicator is customizable, allowing users to define the number of price levels (rows), the offset, the data source, and whether to display volume or frequency count. It also adjusts dynamically to the visible price range on the chart, ensuring that the analysis remains relevant and timely with changing market conditions.
Source: The price to use for the calculation. Typically, this is the closing price. By considering the user-selected Source (typically the closing price), the indicator determines the frequency with which the price lands within each designated price level (row) over the selected period. In essence, the indicator provides a count of bars where the Source price falls within each range, essentially creating a "Price Profile."
Row Size: The number of price levels (rows) to divide the visible price range into.
Display: Choose whether to display the number of bars ("Counter") or the total volume ("Volume") for each price level.
Offset: The distance of the histogram from the price chart.
Point of Control (POC): If enabled, the indicator will highlight the price level with the most activity.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
OverNightSession @joshuuuThis indicator highlights the Overnightsession (ONS), taught by TheCurrenyMerchant.
The Overnightsession is from 4-8 am UTC-5. This session can be used to form trades, e.g. after one side has been taken out.
It has the options to display Projection and the equilibrium level. Equilibrium level (50%) can be used to identify if price is currently in premium/discount of the range and the projections (standard deviations of the range) can be used to identify possible targets.
A classic setup he teaches is:
Price trades agressively out of the range taking liquidity. As soon as we trade above the high of the candle that took liquidity, that candle can be considered an orderblock, where the 50% level can be used for long setups.
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
Reversal Money Flow Indicator (RMFI)
This indicator is for tracking trend following of altcoins movement based on asset movement (RMFI, Reversal of Money Flow Indicator)
RMFI is specialized for the cryptocurrency market and can detect asset movement when altcoins, which previously showed similar price momentum as Bitcoin, begin to move independently
I have made many efforts to predict the independent volatility of altcoins that do not follow the price momentum of Bitcoin by modifying trading strategies and searching for patterns, but have faced many inefficiencies and disappointments. The time I spent constantly trying to simplify elements to consider between indicators according to the market conditions led me to create something truly innovative t I believe.
As the Market Cap of cryptocurrency has recently increased, liquidity has also increased, allowing for the classification of more patterns. Instead of considering many complex indicators, I focused on a single indicator to obtain clearer signals and were able to increase the reliability of patterns.
RMFI is not accurate in finding the reversal of independent momentum of all 8,000 altcoins (as of 2021), it is ideal for assets with slightly higher liquidity.
Education on all indicator functions will be provided through separate videos in my Telegram community space (refer to Instructions), and I would like to regularly research with users to provide better trading discoveries.
Introduction: It is very easy to read. The basic setting shows a divided view of positive and negative values, which is useful for finding independent trend reversals of altcoins. There are colors that need to be continuously watched, colors that indicate high possibility of trend reversal, and colors that indicate the start of trend reversal.
'Orange : indicates a monitoring signal
Sky blue : indicates an attempt of trend reversal after sufficient pressure
Green : Approaching independent trend reversal
Yellow : indicates a sudden trend reversal
Pink : overheating
Red : Weakness starts
I will explain the functions of RMFI indicator through below following chart.
'Orange candlesticks indicate a signal that assets are starting to move to the specific altcoin, while the blue candlesticks indicate that the asset movement has progressed enough to try for an independent trend reversal (It is not always the case that blue candles will be followed by 'orange candles in a specific order)
The green candles indicate that altcoin is nearing independent trend reversal, which is a BUY signal. The yellow candles indicate that, even though sufficient asset movement has not been confirmed, it is a signal for following the trend as the trend reversal has begun.
The green and yellow candles' signals must be evaluated by user. The first evaluation is to check that movement is sufficient by looking at the minus area's columns and blue columns. Additional details will be provided through a separate video in my Telegram community space (refer to Instructions)
*Buy signal evaluation (Sky blue) : Columns indicating trend reversal, which should be blue, is 'orange, indicating that assets are still in transit
*Buy signal evaluation (Green candle) : Blue column and green candle
*Buy signal evaluation (Yellow candle) : 'Orange column, indicating assets in transit and accumulation, is not visible, but minus area columns (blue) are confirmed and Columns cross into the plus area, indicating the start of a strong uptrend
Signals generated in the sequence of 'orange, blue, green, yellow are not always in order and can occur in the form of two signals or a single signal. I will explain further by looking at other example charts.
It is not the case that the candles' signals send a buy signal in all cases. However, by monitoring columns, user can identify when the trend is reversing and make good trades.
As previously explained, it is important for the user to pay attention to the changes in columns (ongoing : 'Orange columns / near completion of asset movement : Blue columns) when evaluating signals after a buy signal. Below is an example chart and detailed information on signal interpretation is provided in a separate video.
Pink candles indicate that assets that were previously inflow through altcoins are now being leaked. Signal of pink color implies that the upward trend may gradually decrease and price adjustments could occur. Red candles, on the other hand, indicate the start of a bearish momentum.
"Life dedicated to giving the best for the loved ones" Wishing luck to traders.
Expressing gratitude to all.
Volume composition / quantifytools— Overview
While net volume is useful information, it can be a blunt data point. Volume composition breaks down the content of volume, allowing a more detailed look inside each volume node. Volume composition consists of the following information:
Total volume (buy and sell). By default gray node.
Dominating volume (buy or sell). By default dark green/dark red node.
Dominating active volume (buy or sell). By default light green/light red node.
Dominating volume as percentage of total volume.
Dominating active volume as percentage of total active volume.
Buy and sell volume is defined by volume associated with lower timeframe up/down moves. This classification is further broken down to passive/active, standing for decreasing/increasing volume, e.g. a move up with volume higher than previous bar volume = active buy volume, a move up with volume lower than previous bar volume = passive buy volume.
Volume data is fetched from a lower timeframe that is automatically adjusted to fit the timeframe you're using. By default, the following settings are applied:
Charts <= 30 min: 1 minute timeframe
Charts > 30 min & <= 3 hours : 5 minute timeframe
Charts > 3 hours & <= 8 hours : 15 minute timeframe
Charts > 8 hours & <= 1D: 1 hour timeframe
Charts > 1D & <= 3D : 2 hour timeframe
Charts > 3D: 4 hour timeframe
Timeframe settings can be changed via input menu. The lower the timeframe, the more precision you get but with the cost of less historical data and slower loading time. Users can also choose which source to use for determining buy/sell volume, e.g. using close as source, a close that is higher than previous close would be considered as buy volume. This could be replaced with OHLC4 for example, resulting in a volume direction based on OHLC average.
Volume composition of current chart can also be replaced with any other chart volume composition:
— Visuals
Breakdown of visual elements:
1. Symbol and timeframe used for volume composition calculations. By default the chart that is viewed and automatically selected lower timeframe.
2. Dominating volume threshold exceeded. Can be defined via input menu, 70% of total volume by default.
3. Dominating volume as percentage of total volume. Plotted below volume nodes, without % symbol.
4. Dominating active volume, + or - symbol, standing for buy and sell. Plotted below dominating volume percentage. When dominating volume and dominating active volume sides are in a disagreement (e.g. dominating volume is on buy side while dominating active volume is on sell side) this symbol will appear inside brackets, (+) or (-).
5. Dominating active volume as percentage of total active volume. Plotted below +/- symbol.
6. Dominating active volume threshold exceeded. Can be defined via input menu, 70% by default.
Dominating volume & active volume percentages can be rounded to single numbers to avoid clutter caused by overlapping values. The percentage values will be rounded to closest single number value, e.g. dominating volume percentage at 54% = 5, dominating volume percentage at 55% = 6.
Volume anomalies can be highlighted on the chart with a color for studying the events and their past implications in greater detail. Available anomalies for highlights are the following:
Buy volume threshold exceeded
Sell volume threshold exceeded
Active buy volume threshold exceeded
Active sell volume threshold exceeded
Volume & active volume divergence
— Practical guide
Volume is arguably one of the most important data points as it directly relates to liquidity. High volume can be an indication of strength (price likely to continue moving) or absorption (price likely to halt/turn). Same applies to active volume, but with an element of aggression. High active volume serves as an indication of exuberance or otherwise forceful transacting, like stop losses triggering. With these principles in mind, the composition of volume allows distinguishing potentially important events.
Example #1 : Identifying areas of trapped market participants
Often when volume spikes distinctively, we can make the case that price has found sufficient liquidity to halt/turn. Since we know which side was absorbed, in what quantity and type (passive/active), we can identify areas of trapped market participants. In such scenarios, the higher the dominant active volume and volume spike itself, the better.
Example #2 : Identifying a healthy trend
A healthy trend is one that has an active and consistent bid driving it. When this is the case, it can be seen in consistently supportive active volume.
Example #3 : Identifying inflection points
When dominant side of volume and dominant side of active volume diverge, something is up. A divergence often marks an area of indecision, hinting an imminent move one way or the other.
Vol in FiatThis indicator is modified from veryevilone's BTC Volume in Fiat. Modified color and style, and bumped Pine language Version.
It shows volume in fiat, AKA dollar volume . If a trade pair is not traded in fiat, e.g. AAA-BBB , then it shows how much volume the BBB is involved.
Good for comparing liquidity between different pairs. Also good for pairs with big price fluctuation to determine actual liquidity.
IC Sniper
Hello fellow traders,
This is a script which tries to visualise SMC /Institutional Candles.
Few of the features which are used in the script are explained below,
CAUTION, Do not enable IC Candles option (BETA). It has a lot of flaws which require solving the problem from a different angle, and I am trying my level best to figure out a solution.
Left Bars and Right Bars, used to find pivot high and lows to help us make Market Structure.
Now first thing to understand when trying to figure out SMC or institutional moves is the figure out the trend you are in. Trend is always your friend, so use higher time frame to just see the trend ( Trend lines are handy ).
I suggest using manual trend detection option, you have other two options available. Either of them have some flaws which can be worked upon if required.
Find the trend, be it manually or EMA ensures are trend support order blocks and engulfing candles are shown.
IC = Institutional Candle
How to find an IC ???
Simple things are ensured.
Below is defined for a bear market
1) Clears liquidity ( I simply see the last green candle before a minor dump ( vice-versa ) and see if the last green candle or the following red candle have huge wicks which clear recent previous highs (3 candles)
2) Next I see if the red candle after the last green candles is engulfing in nature ( yellow for bearing environment and white for bullish )
3) Then I create an order block.
4) Sometimes if imbalance after an order block is tooo big, the re test only fills the imbalance rather than reaching the IC . Imbalances are shown with grey boxes, the ones filled are automatically removed.
For successful entries please ensure that the candles succeeding engulfing candles break a market structure (BOS, ChoCh).
Any suggestion are welcome.
Please change max moves to detect to 5 from 3
Caution not all order blocks made are perfect !! Further adjustments are required but are too complicated for me to code, have to find some way around and I am sure with update I will refine the options.
Basic things to look,
IC should be followed buy a pump or a dump ( with some candles being out of the trend (I have given some scope in the code)) plus it should have a high wick which clears liquidity.
