BAERMThe Bitcoin Auto-correlation Exchange Rate Model: A Novel Two Step Approach
THIS IS NOT FINANCIAL ADVICE. THIS ARTICLE IS FOR EDUCATIONAL AND ENTERTAINMENT PURPOSES ONLY.
If you enjoy this software and information, please consider contributing to my lightning address
Prelude
It has been previously established that the Bitcoin daily USD exchange rate series is extremely auto-correlated
In this article, we will utilise this fact to build a model for Bitcoin/USD exchange rate. But not a model for predicting the exchange rate, but rather a model to understand the fundamental reasons for the Bitcoin to have this exchange rate to begin with.
This is a model of sound money, scarcity and subjective value.
Introduction
Bitcoin, a decentralised peer to peer digital value exchange network, has experienced significant exchange rate fluctuations since its inception in 2009. In this article, we explore a two-step model that reasonably accurately captures both the fundamental drivers of Bitcoin’s value and the cyclical patterns of bull and bear markets. This model, whilst it can produce forecasts, is meant more of a way of understanding past exchange rate changes and understanding the fundamental values driving the ever increasing exchange rate. The forecasts from the model are to be considered inconclusive and speculative only.
Data preparation
To develop the BAERM, we used historical Bitcoin data from Coin Metrics, a leading provider of Bitcoin market data. The dataset includes daily USD exchange rates, block counts, and other relevant information. We pre-processed the data by performing the following steps:
Fixing date formats and setting the dataset’s time index
Generating cumulative sums for blocks and halving periods
Calculating daily rewards and total supply
Computing the log-transformed price
Step 1: Building the Base Model
To build the base model, we analysed data from the first two epochs (time periods between Bitcoin mining reward halvings) and regressed the logarithm of Bitcoin’s exchange rate on the mining reward and epoch. This base model captures the fundamental relationship between Bitcoin’s exchange rate, mining reward, and halving epoch.
where Yt represents the exchange rate at day t, Epochk is the kth epoch (for that t), and epsilont is the error term. The coefficients beta0, beta1, and beta2 are estimated using ordinary least squares regression.
Base Model Regression
We use ordinary least squares regression to estimate the coefficients for the betas in figure 2. In order to reduce the possibility of over-fitting and ensure there is sufficient out of sample for testing accuracy, the base model is only trained on the first two epochs. You will notice in the code we calculate the beta2 variable prior and call it “phaseplus”.
The code below shows the regression for the base model coefficients:
\# Run the regression
mask = df\ < 2 # we only want to use Epoch's 0 and 1 to estimate the coefficients for the base model
reg\_X = df.loc\ [mask, \ \].shift(1).iloc\
reg\_y = df.loc\ .iloc\
reg\_X = sm.add\_constant(reg\_X)
ols = sm.OLS(reg\_y, reg\_X).fit()
coefs = ols.params.values
print(coefs)
The result of this regression gives us the coefficients for the betas of the base model:
\
or in more human readable form: 0.029, 0.996869586, -0.00043. NB that for the auto-correlation/momentum beta, we did NOT round the significant figures at all. Since the momentum is so important in this model, we must use all available significant figures.
Fundamental Insights from the Base Model
Momentum effect: The term 0.997 Y suggests that the exchange rate of Bitcoin on a given day (Yi) is heavily influenced by the exchange rate on the previous day. This indicates a momentum effect, where the price of Bitcoin tends to follow its recent trend.
Momentum effect is a phenomenon observed in various financial markets, including stocks and other commodities. It implies that an asset’s price is more likely to continue moving in its current direction, either upwards or downwards, over the short term.
The momentum effect can be driven by several factors:
Behavioural biases: Investors may exhibit herding behaviour or be subject to cognitive biases such as confirmation bias, which could lead them to buy or sell assets based on recent trends, reinforcing the momentum.
Positive feedback loops: As more investors notice a trend and act on it, the trend may gain even more traction, leading to a self-reinforcing positive feedback loop. This can cause prices to continue moving in the same direction, further amplifying the momentum effect.
Technical analysis: Many traders use technical analysis to make investment decisions, which often involves studying historical exchange rate trends and chart patterns to predict future exchange rate movements. When a large number of traders follow similar strategies, their collective actions can create and reinforce exchange rate momentum.
Impact of halving events: In the Bitcoin network, new bitcoins are created as a reward to miners for validating transactions and adding new blocks to the blockchain. This reward is called the block reward, and it is halved approximately every four years, or every 210,000 blocks. This event is known as a halving.
The primary purpose of halving events is to control the supply of new bitcoins entering the market, ultimately leading to a capped supply of 21 million bitcoins. As the block reward decreases, the rate at which new bitcoins are created slows down, and this can have significant implications for the price of Bitcoin.
The term -0.0004*(50/(2^epochk) — (epochk+1)²) accounts for the impact of the halving events on the Bitcoin exchange rate. The model seems to suggest that the exchange rate of Bitcoin is influenced by a function of the number of halving events that have occurred.
Exponential decay and the decreasing impact of the halvings: The first part of this term, 50/(2^epochk), indicates that the impact of each subsequent halving event decays exponentially, implying that the influence of halving events on the Bitcoin exchange rate diminishes over time. This might be due to the decreasing marginal effect of each halving event on the overall Bitcoin supply as the block reward gets smaller and smaller.
This is antithetical to the wrong and popular stock to flow model, which suggests the opposite. Given the accuracy of the BAERM, this is yet another reason to question the S2F model, from a fundamental perspective.
The second part of the term, (epochk+1)², introduces a non-linear relationship between the halving events and the exchange rate. This non-linear aspect could reflect that the impact of halving events is not constant over time and may be influenced by various factors such as market dynamics, speculation, and changing market conditions.
The combination of these two terms is expressed by the graph of the model line (see figure 3), where it can be seen the step from each halving is decaying, and the step up from each halving event is given by a parabolic curve.
NB - The base model has been trained on the first two halving epochs and then seeded (i.e. the first lag point) with the oldest data available.
Constant term: The constant term 0.03 in the equation represents an inherent baseline level of growth in the Bitcoin exchange rate.
In any linear or linear-like model, the constant term, also known as the intercept or bias, represents the value of the dependent variable (in this case, the log-scaled Bitcoin USD exchange rate) when all the independent variables are set to zero.
The constant term indicates that even without considering the effects of the previous day’s exchange rate or halving events, there is a baseline growth in the exchange rate of Bitcoin. This baseline growth could be due to factors such as the network’s overall growth or increasing adoption, or changes in the market structure (more exchanges, changes to the regulatory environment, improved liquidity, more fiat on-ramps etc).
Base Model Regression Diagnostics
Below is a summary of the model generated by the OLS function
OLS Regression Results
\==============================================================================
Dep. Variable: logprice R-squared: 0.999
Model: OLS Adj. R-squared: 0.999
Method: Least Squares F-statistic: 2.041e+06
Date: Fri, 28 Apr 2023 Prob (F-statistic): 0.00
Time: 11:06:58 Log-Likelihood: 3001.6
No. Observations: 2182 AIC: -5997.
Df Residuals: 2179 BIC: -5980.
Df Model: 2
Covariance Type: nonrobust
\==============================================================================
coef std err t P>|t| \
\------------------------------------------------------------------------------
const 0.0292 0.009 3.081 0.002 0.011 0.048
logprice 0.9969 0.001 1012.724 0.000 0.995 0.999
phaseplus -0.0004 0.000 -2.239 0.025 -0.001 -5.3e-05
\==============================================================================
Omnibus: 674.771 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 24937.353
Skew: -0.765 Prob(JB): 0.00
Kurtosis: 19.491 Cond. No. 255.
\==============================================================================
Below we see some regression diagnostics along with the regression itself.
Diagnostics: We can see that the residuals are looking a little skewed and there is some heteroskedasticity within the residuals. The coefficient of determination, or r2 is very high, but that is to be expected given the momentum term. A better r2 is manually calculated by the sum square of the difference of the model to the untrained data. This can be achieved by the following code:
\# Calculate the out-of-sample R-squared
oos\_mask = df\ >= 2
oos\_actual = df.loc\
oos\_predicted = df.loc\
residuals\_oos = oos\_actual - oos\_predicted
SSR = np.sum(residuals\_oos \*\* 2)
SST = np.sum((oos\_actual - oos\_actual.mean()) \*\* 2)
R2\_oos = 1 - SSR/SST
print("Out-of-sample R-squared:", R2\_oos)
The result is: 0.84, which indicates a very close fit to the out of sample data for the base model, which goes some way to proving our fundamental assumption around subjective value and sound money to be accurate.
Step 2: Adding the Damping Function
Next, we incorporated a damping function to capture the cyclical nature of bull and bear markets. The optimal parameters for the damping function were determined by regressing on the residuals from the base model. The damping function enhances the model’s ability to identify and predict bull and bear cycles in the Bitcoin market. The addition of the damping function to the base model is expressed as the full model equation.
This brings me to the question — why? Why add the damping function to the base model, which is arguably already performing extremely well out of sample and providing valuable insights into the exchange rate movements of Bitcoin.
Fundamental reasoning behind the addition of a damping function:
Subjective Theory of Value: The cyclical component of the damping function, represented by the cosine function, can be thought of as capturing the periodic fluctuations in market sentiment. These fluctuations may arise from various factors, such as changes in investor risk appetite, macroeconomic conditions, or technological advancements. Mathematically, the cyclical component represents the frequency of these fluctuations, while the phase shift (α and β) allows for adjustments in the alignment of these cycles with historical data. This flexibility enables the damping function to account for the heterogeneity in market participants’ preferences and expectations, which is a key aspect of the subjective theory of value.
Time Preference and Market Cycles: The exponential decay component of the damping function, represented by the term e^(-0.0004t), can be linked to the concept of time preference and its impact on market dynamics. In financial markets, the discounting of future cash flows is a common practice, reflecting the time value of money and the inherent uncertainty of future events. The exponential decay in the damping function serves a similar purpose, diminishing the influence of past market cycles as time progresses. This decay term introduces a time-dependent weight to the cyclical component, capturing the dynamic nature of the Bitcoin market and the changing relevance of past events.
Interactions between Cyclical and Exponential Decay Components: The interplay between the cyclical and exponential decay components in the damping function captures the complex dynamics of the Bitcoin market. The damping function effectively models the attenuation of past cycles while also accounting for their periodic nature. This allows the model to adapt to changing market conditions and to provide accurate predictions even in the face of significant volatility or structural shifts.
Now we have the fundamental reasoning for the addition of the function, we can explore the actual implementation and look to other analogies for guidance —
Financial and physical analogies to the damping function:
Mathematical Aspects: The exponential decay component, e^(-0.0004t), attenuates the amplitude of the cyclical component over time. This attenuation factor is crucial in modelling the diminishing influence of past market cycles. The cyclical component, represented by the cosine function, accounts for the periodic nature of market cycles, with α determining the frequency of these cycles and β representing the phase shift. The constant term (+3) ensures that the function remains positive, which is important for practical applications, as the damping function is added to the rest of the model to obtain the final predictions.
Analogies to Existing Damping Functions: The damping function in the BAERM is similar to damped harmonic oscillators found in physics. In a damped harmonic oscillator, an object in motion experiences a restoring force proportional to its displacement from equilibrium and a damping force proportional to its velocity. The equation of motion for a damped harmonic oscillator is:
x’’(t) + 2γx’(t) + ω₀²x(t) = 0
where x(t) is the displacement, ω₀ is the natural frequency, and γ is the damping coefficient. The damping function in the BAERM shares similarities with the solution to this equation, which is typically a product of an exponential decay term and a sinusoidal term. The exponential decay term in the BAERM captures the attenuation of past market cycles, while the cosine term represents the periodic nature of these cycles.
Comparisons with Financial Models: In finance, damped oscillatory models have been applied to model interest rates, stock prices, and exchange rates. The famous Black-Scholes option pricing model, for instance, assumes that stock prices follow a geometric Brownian motion, which can exhibit oscillatory behavior under certain conditions. In fixed income markets, the Cox-Ingersoll-Ross (CIR) model for interest rates also incorporates mean reversion and stochastic volatility, leading to damped oscillatory dynamics.
By drawing on these analogies, we can better understand the technical aspects of the damping function in the BAERM and appreciate its effectiveness in modelling the complex dynamics of the Bitcoin market. The damping function captures both the periodic nature of market cycles and the attenuation of past events’ influence.
Conclusion
In this article, we explored the Bitcoin Auto-correlation Exchange Rate Model (BAERM), a novel 2-step linear regression model for understanding the Bitcoin USD exchange rate. We discussed the model’s components, their interpretations, and the fundamental insights they provide about Bitcoin exchange rate dynamics.
The BAERM’s ability to capture the fundamental properties of Bitcoin is particularly interesting. The framework underlying the model emphasises the importance of individuals’ subjective valuations and preferences in determining prices. The momentum term, which accounts for auto-correlation, is a testament to this idea, as it shows that historical price trends influence market participants’ expectations and valuations. This observation is consistent with the notion that the price of Bitcoin is determined by individuals’ preferences based on past information.
Furthermore, the BAERM incorporates the impact of Bitcoin’s supply dynamics on its price through the halving epoch terms. By acknowledging the significance of supply-side factors, the model reflects the principles of sound money. A limited supply of money, such as that of Bitcoin, maintains its value and purchasing power over time. The halving events, which reduce the block reward, play a crucial role in making Bitcoin increasingly scarce, thus reinforcing its attractiveness as a store of value and a medium of exchange.
The constant term in the model serves as the baseline for the model’s predictions and can be interpreted as an inherent value attributed to Bitcoin. This value emphasizes the significance of the underlying technology, network effects, and Bitcoin’s role as a medium of exchange, store of value, and unit of account. These aspects are all essential for a sound form of money, and the model’s ability to account for them further showcases its strength in capturing the fundamental properties of Bitcoin.
The BAERM offers a potential robust and well-founded methodology for understanding the Bitcoin USD exchange rate, taking into account the key factors that drive it from both supply and demand perspectives.
In conclusion, the Bitcoin Auto-correlation Exchange Rate Model provides a comprehensive fundamentally grounded and hopefully useful framework for understanding the Bitcoin USD exchange rate.
Komut dosyalarını "market structure" için ara
Multi VWAP from Gaps [MW]Multi VWAP from Gaps
Introduction
The Multi VWAP from Gaps tool extends the concept of using the Anchored Volume Weighted Average Price, popularized by its founder, Brian Shannon, founder of AlphaTrends. It creates automatic AVWAPS for anchor points originating at the biggest gaps of the week, month, quarter and year. Currently, most standard VWAP tools allow users to place custom anchored VWAPs, but the routine of doing this for every equity being watched can become cumbersome. This tool makes that process multi-times easier. Considering that large gaps can represent a shift in market structure, this tool provides unique and immediate insight into how past daily price gaps can and have affected price action.
Settings
LABEL SETTINGS
Show Biggest Gap of Week | Month | Quarter : Toggle labels that identify the location of the biggest gaps for the selected time period.
Show Big Labels : Toggle labels from showing the date and gap size to just showing a single letter (W/M/Q/Y) designating the time period that the gap is from.
Hide All Labels : Turn labels off and on.
MAX VWAP LINES
Max Weekly | Monthly | Quarterly | Yearly Lines : How many VWAP lines, starting from today, should be shown for the specified time period. Max: 5
SHOW VWAP LINES
Show Weekly | Monthly | Quarterly | Yearly Lines : This feature allows you to remove lines for the specified time period.
Calculations
This indicator does not provide buy or sell signals. It is simply the VWAP calculated starting from an “anchor point”, or start time. It is calculated by the summation of Price x Volume / Volume for the period starting at the anchor point.
How to Interpret
According to Brian Shannon, VWAP is an objective measure of what the average trader has paid for a particular equity over a given period, and is the value that large institutional investors frequently use as a trade signal. Therefore, by definition, when the price is above an AVWAP, buyers are in control for that period of time. Likewise, if the price is below the AVWAP, sellers are in control for that period of time.
VWAPs that coincide with important events, such as FOMC meetings, CPI reports, earnings reports, have added significance. In many cases, these events can cause gaps to happen in day-to-day price movement, and can affect market structure going forward.
Practically speaking, price action can tend to change direction when a significant VWAP is hit, voiding buy and sell signals. Like moving averages, this indicator can show, in real-time, how a buy or sell signal should be interpreted. A significant AVWAP line is a point of interest, and can serve as strong support or resistance, because large institutions may be using those values for entries or exits. For a great analysis of how to use AVWAP, visit the AlphaTrends channel on Youtube here or you can buy Brian Shannon’s “Anchored VWAP” book on Amazon.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Additionally, in order to build the VWAP calculations, past data is needed that may not be available on shorter timeframes. The workaround is that for some longer-term VWAP lines on shorter timeframes, you may see less than the total of lines that you selected in settings. This is particularly the case with quarterly VWAP lines on the 5 minute timeframe for some equities.
Acknowledgements
This script uses the MarketHolidays library by @Protervus. Also, for debugging, the JavaScript-style Debug Console by @algotraderdev was invaluable. Special thanks to @antsmuzic for helping review and debug the script. And, of course, without Brian Shannon's books, videos, and interviews, this indicator would would not have happened.
Order Blocks Finder [TradingFinder] Major OB | Supply and Demand🔵 Introduction
Drawing all order blocks on the path, especially in range-bound or channeling markets, fills the chart with lines, making it confusing rather than providing the trader with the best entry and exit points.
🔵 Reason for Indicator Creation
For traders familiar with market structure and only need to know the main accumulation points (best entry or exit points), and primary order blocks that act as strong sources of power.
🟣 Important Note
All order blocks, both ascending and descending, are identified and displayed on the chart when the structure of "BOS" or "CHOCH" is broken, which can also be identified with "MSS."
🔵 How to Use
When the indicator is installed, it plots all order blocks (active order blocks) and continues until the price reaches them. This continuation happens in boxes to have a better view in the TradingView chart.
Green Range : Ascending order blocks where we expect a price increase in these areas.
Red Range : Descending order blocks where we expect a price decrease in these areas.
🔵 Settings
Order block refine setting : When Order block refine is off, the supply and demand zones are the entire length of the order block (Low to High) in their standard state and cannot be improved. If you turn on Order block refine, supply and demand zones will improve using the error correction algorithm.
Refine type setting : Improving order blocks using the error correction algorithm can be done in two ways: Defensive and Aggressive. In the Aggressive method, the largest possible range is considered for order blocks.
🟣 Important
The main advantage of the Aggressive method is minimizing the loss of stops, but due to the widening of the supply or demand zone, the reward-to-risk ratio decreases significantly. The Aggressive method is suitable for individuals who take high-risk trades.
In the Defensive method, the range of order blocks is minimized to their standard state. In this case, fewer stops are triggered, and the reward-to-risk ratio is maximized in its optimal state. It is recommended for individuals who trade with low risk.
Show high level setting : If you want to display major high levels, set show high level to Yes.
Show low level setting : If you want to display major low levels, set show low level to Yes.
🔵 How to Use
The general view of this indicator is as follows.
When the price approaches the range, wait for the price reaction to confirm it, such as a pin bar or divergence.
If the price passes with a strong candle (spike), especially after a long-range or at the beginning of sessions, a powerful event is happening, and it is outside the credibility level.
An Example of a Valid Zone
An Example of Breakout and Invalid Zone. (My suggestion is not to use pending orders, especially when the market is highly volatile or before and after news.)
After reaching this zone, expect the price to move by at least the minimum candle that confirmed it or a price ceiling or floor.
🟣 Important : These factors can be more accurately measured with other trend finder indicators provided.
🔵 Auxiliary Tools
There is much talk about not using trend lines, candlesticks, Fibonacci, etc., in the web space. However, our suggestion is to create and use tools that can help you profit from this market.
• Fibonacci Retracement
• Trading Sessions
• Candlesticks
🔵 Advantages
• Plotting main OBs without additional lines;
• Suitable for timeframes M1, M5, M15, H1, and H4;
• Effective in Tokyo, Sydney, and London sessions;
• Plotting the main ceiling and floor to help identify the trend.
Candlestick Patterns [NAS Algo]Candlestick Patterns plots most commonly used chart patterns to help and understand the market structure.
Bullish Reversal Patterns:
Hammer:
Appearance: Small body near the high, long lower shadow.
Interpretation: Indicates potential bullish reversal after a downtrend.
Inverted Hammer:
Appearance: Small body near the low, long upper shadow.
Interpretation: Signals potential bullish reversal, especially when the preceding trend is bearish.
Three White Soldiers:
Appearance: Three consecutive long bullish candles with higher closes.
Interpretation: Suggests a strong reversal of a downtrend.
Bullish Harami:
Appearance: Small candle (body) within the range of the previous large bearish candle.
Interpretation: Implies potential bullish reversal.
Bearish Reversal Patterns:
Hanging Man:
Appearance: Small body near the high, long lower shadow.
Interpretation: Suggests potential bearish reversal after an uptrend.
Shooting Star:
Appearance: Small body near the low, long upper shadow.
Interpretation: Indicates potential bearish reversal, especially after an uptrend.
Three Black Crows:
Appearance: Three consecutive long bearish candles with lower closes.
Interpretation: Signals a strong reversal of an uptrend.
Bearish Harami:
Appearance: Small candle (body) within the range of the previous large bullish candle.
Interpretation: Implies potential bearish reversal.
Dark Cloud Cover:
Appearance: Bearish reversal pattern where a bullish candle is followed by a bearish candle that opens above the high of the previous candle and closes below its midpoint.
Continuation Patterns:
Rising Three Methods:
Appearance: Consists of a long bullish candle followed by three small bearish candles and another bullish candle.
Interpretation: Indicates the continuation of an uptrend.
Falling Three Methods:
Appearance: Consists of a long bearish candle followed by three small bullish candles and another bearish candle.
Interpretation: Suggests the continuation of a downtrend.
Gravestone Doji:
Appearance: Doji candle with a long upper shadow, little or no lower shadow, and an opening/closing price near the low.
Interpretation: Signals potential reversal, particularly in an uptrend.
Long-Legged Doji:
Appearance: Doji with long upper and lower shadows and a small real body.
Interpretation: Indicates indecision in the market and potential reversal.
Dragonfly Doji:
Appearance: Doji with a long lower shadow and little or no upper shadow.
Interpretation: Suggests potential reversal, especially in a downtrend.
Candle volume analysis The indicator is designed for traders who are more interested in market structures and price action using volumes. Volume analysis can help traders build a clearer understanding of zones of buyer and seller interest, as well as places to capture liquidity (traders' stop levels).
Key Features:
The indicator highlights candle volumes in selected colors, where the volume is greater individually than the volumes of the trader's chosen number of preceding candles. Or the volume that is greater than the sum of volumes of the trader's chosen number of preceding candles.
Opening Range Gap + Std Dev [starclique]The ICT Opening Range Gap is a concept taught by Inner Circle Trader and is discussed in the videos: 'One Trading Setup For Life' and 2023 ICT Mentorship - Opening Range Gap Repricing Macro
ORGs, or Opening Range Gaps, are gaps that form only on the Regular Trading Hours chart.
The Regular Trading Hours gap occurs between 16:15 PM - 9:29 AM EST (UTC-4)
These times are considered overnight trading, so it is useful to filter the PA (price action) formed there.
The RTH option is only available for futures contracts and continuous futures from CME Group.
To change your chart to RTH, first things first, make sure you’re looking at a futures contract for an asset class, then on the bottom right of your chart, you’ll see ETH (by default) - Click on that, and change it to RTH.
Now your charts are filtering the price action that happened overnight.
To draw out your gap, use the Close of the 4:14 PM candle and the open of the 9:30 AM candle.
How is this concept useful?
Well, It can be used in many ways.
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How To Use The ORG
One of the ways you can use the opening range gap is simply as support and resistance
If we extend out the ORG from the example above, we can see that there is a clean retest of the opening range gap high after breaking structure to the upside and showing acceptance outside of the gap after consolidating within it.
The ORG High (4:14 Candle Close in this case) was used as support.
We then see an expansion to the upside.
Another way to implement the ORG is by using it as a draw on liquidity (magnet for price)
In this example, if we looked to the left, there was a huge ORG to the downside, leaving a massive gap.
The market will want to rebalance that gap during the regular trading hours.
The market rallies higher, rejects, comes down to clear the current days ORG low, then closes.
That is one example of how you can combine liquidity & ICT market structure concepts with Opening Range Gaps to create a story in the charts.
Now let’s discuss standard deviations.
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Standard Deviations
Standard Deviations are essentially projection levels for ranges / POIs (Point of Interests)
By this I mean, if you have a range, and you would like to see where it could potentially expand to, you’d place your fibonacci retracement tool on and high and low of the range, then use extension levels to find specific price points where price might reject from.
Since 0 and 1 are your Range High and Low respectively, your projection levels would be something like 1.5, 2, 2.5, and 3, for the extension from your 1 Fib Level, and -0.5, -1, -1.5, and -2 for your 0 Fib level.
The -1 and 2 level produce a 1:1 projection of your range low and high, meaning, if you expect price to expand as much as it did from the range low to range high, then you can project a -1 and 2 on your Fib, and it would show you what ICT calls “symmetrical price”
Now, how are standard deviations relevant here?
Well, if you’ve been paying attention to ICT’s recent videos, you would’ve caught that he’s recently started using Standard Deviation levels on breakers.
So my brain got going while watching his video on ORGs, and I decided to place the fib on the ORG high and low and see what it’d produce.
The results were very interesting.
Using this same example, if we place our fib on the ORG High and Low, and add some projection levels, we can see that we rejected right at the -2 Standard Deviation Level.
---
You can see that I also marked out the EQ (Equilibrium, 50%, 0.5 of Fib) of the ORG. This is because we can use this level as a take profit level if we’re using an old ORG as our draw.
In days like these, where the gap formed was within a consolidation, and it continued to consolidate within the ORG zone that we extended, we can use the EQ in the same way we’d use an EQ for a range.
If it’s showing acceptance above the EQ, we are bullish, and expect the high of the ORG to be tapped, and vice versa.
---
Using The Indicator
Here’s where our indicator comes in play.
To avoid having to do all this work of zooming in and marking out the close and open of the respective ORG candles, we created the Opening Range Gap + Standard Deviations Indicator, with the help of our dedicated Star Clique coder, a1tmaniac.
With the ORG + STD DEV indicator, you will be able to view ORG’s and their projections on the ETH (Electronic Trading Hours) chart.
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Features
Range Box
- Change the color of your Opening Range Gap to your liking
- Enable or disable the box from appearing using the checkbox
Range Midline
- Change the color of your Opening Range Gap Equilibrium
- Enable or disable the midline from appearing using the checkbox
Std. Dev
- Add whichever standard deviation levels you’d like.
- By default, the indicator comes with 0.5, 1, 1.5, and 2 standard deviation levels.
- Ensure that you add a comma ( , ) in between each standard deviation level
- Enable or disable the standard deviations from appearing using the opacity of the color (change to 0%)
Labels / Offset
- Adjust the offset of the label for the Standard Deviations
- Enable or disable the Labels from appearing using the checkbox
Time
- Adjust the time used for the indicators range
- If you’d like to use this for a Session or ICT Killzone instead, adjust the time
- Adjust the timezone used for the time referenced
- Options are UTC, US (UTC-4, New York Local Time) or UK (UTC+1, London Time)
- By default, the indicator is set to US
Faytterro Market Structerethis indicator creates the market structure with a little delay but perfectly. each zigzag is always drawn from highest to lowest. It also signals when the market structure is broken. signals fade over time.
The table above shows the percentage distance of the price from the last high and the last low.
zigzags are painted green when making higher peaks, while lower peaks are considered downtrends and are painted red. In fact, the indicator is quite simple to understand and use.
"length" is used to change the frequency of the signal.
"go to past" is used to see historical data.
Please review the examples:
CANDLE FILTER Todays scripts is based on my Pullback And Rally Candles with other meaningful candles such as Hammers and Dojis.
You can choose which Candles to show on the cart and if you want to candles to appear above or below a moving average.
If you follow my work, you may recognise some of these candles which I'm about to show you however these candles are 1) more refined and 2) has moving average filters.
Ive included a D,6H,1H Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low / swing high so the DPB and RD will only work on the Daily
//Pullback candle
This candle is very powerful when used with simple Price Action such as Market Structure//Demand zones and support zones. (((((WORKS BEST IN UPTRENDS AND BOTTOM OF RANGES)))))
Ive included a D,6H,1H Pullback Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low so the DPB will only work on the Daily
//DAILY PULLBACK (Swing Traders)
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//4H PULLBACK (Swing Traders)
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- this signal will produce more signals due to the swing low filter on the 4H
//1H PULLBACK
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- this signal has been refined due to too many candle displaying in weak areas
!!!IF YOU DONT WANT TO USE PULLBACKS DURING DOWNTRENDS THEN USE THE EMA FILTER TO TURN OFF THE PULLBACKS WHEN PRICE IS BELOW THE MOVING AVERAGE!!!
//Rally candle (My personal Favourite) (((((WORKS BEST IN DOWNTRENDS AND TOP OF RANGES)))))
This candle is very powerful when used with simple Price Action such as Market Structure//Supply zones and Resistance zones.
//DAILY RALLY(Swing Traders)
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//4H RALLY(Swing Traders)
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- this signal will produce more signals due to the swing high filter on the 4H
!!!IF YOU DONT WANT TO USE RALLIES DURING UPTRENDSTHEN USE THE EMA FILTER TO TURN OFF THE RALLIES WHEN PRICE IS ABOVE THE MOVING AVERAGE!!!
//POWERFUL DOJIS (INDECISION)
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We look for indecision in key areas to see if momentum is shifting. When combined with Pullbacks or Rallys - this will enhance the odds of a probably area.
//HAMMERS
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//MOVING AVERAGES
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Short EMA = 50
Long EMA = 200
This filter can be used when the market is trending - look out for rejections off the moving averages
Also you can chance the Short And Long EMA to choose which MA cross you want to use
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ALSO ALL THE CANDLES HAVE A ALERT CONDITIONS WHICH YOU CAN ACCESS - THIS WILL ALERT ANY CANDLE YOU CHOOSE
Please leave a like/comment on this post as this is much appreciated....
Higher Order PivotsFirst order pivot points are defined as 3 or 5 bar "V" shaped patterns. For example a high with a lower high either side of the peak and in the case of the 5 bar variant with lower highs adjacent to a high below the peak.
Second order pivot points are defined by three first order pivots in the same manner. For example a peak pivot high with a lower pivot high to either side.
Third order pivots follow the same pattern, a peak second order pivot high with two adjacent second order pivot highs.
As it can take a significant and variable amount of time before higher order pivots are confirmed, it is generally inadvisable to use higher order pivots for live trading!
However they can be used for historical analysis. For example to delineate market structure of major market inflections.
For example :
Delineating market structure using 2nd order pivots derived from 3 bar, 1st order pivots
Major market inflections from 3rd order pivots derived from 5 bar, 1st order pivots
+ BB %B: MA selection, bar coloring, multi-timeframe, and alerts+ %B is, at its simplest, the classic Bollinger Bands %B indicator with a few added bells and whistles.
However, the right combination of bells and whistles will often improve and make a more adaptable indicator.
Classically, Bollinger Bands %B is an indicator that measures volatility, and the momentum and strength of a trend, and/or price movements.
It shows "overbought" and "oversold" spots on a chart, and is also useful for identifying divergences between price and trend (similar to RSI).
With + %B I've added the options to select one or two moving averages, candle coloring, and a host of others.
Let's start with the moving averages:
There are options for two: one faster and one slower. Or combine them how you will, or omit one or both of them entirely.
Here you will find options for SMA, EMA (as well as double and triple), Hull MA, Jurik MA, Least Squares MA, Triangular MA, Volatility Adjusted MA, and Weighted MA.
A moving average essentially helps to define trend by smoothing the noise of movements of the underlying asset, or, in this case, the output of the indicator.
All of these MAs available track this in a different way, and it's up to the trader to figure out which makes most sense to him/her.
MA's, in my opinion, improve the basic %B by providing a clearer picture of what the indicator is actually "seeing", and may be useful for providing entries and exits.
Next up is candle coloring:
I've added the option for this indicator to color candles on the chart based on where the %B is in relation to its upper and lower bounds, and median line.
If the %B is above the median but below the upper bound, candles will be green (showing bullish market structure). If %B is below the median but above the lower bound, candles will be red (denoting bearish market structure).
Overbought and oversold candles will also be colored on the chart, so that a quick glance will tell you whether price action is bullish/bearish or "oversold"/"overbought".
I've also added functionality that enables candles to be colored based on if the %B has crossed up or crossed down the primary moving average.
One example as a way to potentially use these features is if the candles are showing oversold coloration followed by the %B crossing up your moving average coloration. You might consider a long there (or exit a short position if you are short).
And the last couple of tweaks:
You may set the timeframe to whatever you wish, so maybe you're trading on the hourly, but you want to know where the %B is on the 4h chart. You can do that.
The background fill for the indicator is split into bullish and bearish halves. Obviously you may turn the background off, or make it all one color as well.
I've also added alerts, so you may set alerts for "overbought" and "oversold" conditions.
You may also set alerts for %B crossing over or under the primary moving average, or for crossing the median line.
All of these things may be turned on and off. You can pretty much customize this to your heart's delight. I see no reason why anyone would use the standard %B after playing with this.
I am no coder. I had this idea in my head, though, and I made it happen through referencing another indicator I was familiar with, and watching tutorials on YouTube.
Credits:
Firstly, thanks to www.tradingview.com for his brilliant, free tutorials on YouTube.
Secondly, thanks to www.tradingview.com for his beautiful SSL Hybrid indicator (and his clean code) from which I obtained the MAs.
Please enjoy this indicator, and I hope that it serves you well. :)
MA, MATR, ChEx | All in One - 4CR CUPIn trade position setup, we always need to determine the market structure and manage the position sizing in a short period of decision time. Indicators such as moving average, initial stop loss and trailing stop loss are always helpful.
This indicator put all these handy tools into a single toolkit, which includes the following price action and risk management indicators:
MA - Moving Average
MATR - Moving Average less Average True Range
ChEx - Chandelier Exit
This script further enhances the setting so that you can easily customize the indicators.
For both the Moving Averages and the Moving Average less Average True Range , you can pick a type of moving average which suits your analysis style from a list of commonly used moving average formulations: namely, EMA , HMA , RMA, SMA and WMA , where EMA is selected as default.
The Moving Average less Average True Range , MATR, is usually applied as a reference to set the initial stop loss whenever opening a new position.
The abbreviation, MATR, is picked, so that this can serve as a handy reminder of a very good trading framework as elaborates as below:
M – Market Structure
A – Area of Value
T – Trigger
R – Risk Management (aka. Exit Strategy)
Ichimoku Kinko Hyo and moreI am publishing my updated Ichimoku ++ study with a more suitable title. Future updates will take place with this version.
Description:
The intention of this script is to build/provide a kind of work station / work bench for analysing markets and especially Bitcoin . Another goal is to get maximum market information while maintaining a good chart overview. A chart overloaded with indicators is useless because the structure of the chart is more difficult to see. The chart should be clear and market structure should be easy to see. The script allows you to add indicators and signals in different visualizations to better assess the quality of signals and the sentiment of the market.
A general advise:
Use the included indicators and signals in a confluent way to get stoploss, buy and sell entry points. SR clusters can be identified for use in conjunction with Fractals and other indicators as entry and exit pints. My other scripts can also help. Prefer 4 hours, daily and a longer time frame. There is no "Holy Grail" :).
Ultimate Regression Channel v5.0 [WhiteStone_Ibrahim]Ultimate Regression Channel v5.0: Comprehensive User Guide
This indicator is designed to visualize the current trend, potential support/resistance levels, and market volatility through a statistical analysis of price action. At its core, it plots a regression line (a trend line) based on prices over a specific period and adds channels based on standard deviation around this line.
1. Core Features and Settings
Length Mode:
Numerical (Manual): You define the number of bars to be used for the regression channel calculation. You can use lower values (e.g., 50-100) for short-term analysis and higher values (e.g., 200-300) to identify long-term trends.
Automatic (Based on Market Structure): This mode automatically draws the channel starting from the highest high or lowest low that has formed within the Auto Scan Period. This allows the indicator to adapt itself to significant market turning points (swing points), which is highly useful.
Regression Model:
Linear: Calculates the trend as a straight line. It generally works well in stable, short-to-medium-term trends.
Logarithmic: Calculates the trend as a curved line. It more accurately reflects price action, especially on long-term charts or for assets that experience exponential growth/decline (like cryptocurrencies or growth stocks).
Channel Widths:
These settings determine how far from the central trend line (in terms of standard deviations) the channels will be drawn.
The 0 (Inner), 1 (Middle), and 2 (Outer) channels represent the "normal" range of price movement and the "extreme" zones. Statistically, about 95% of all price action occurs within the outer channels (2nd standard deviation).
2. Visual Extras and Their Interpretation
Breakout Style:
This feature alerts you when the price closes above the uppermost channel (Channel 2) with a green arrow/background or below the lowermost channel with a red arrow/background.
This is a very important signal. A breakout can signify that the current trend is strengthening and likely to continue (a breakout/trend-following strategy) or that the market has become overextended and may be due for a reversal (an exhaustion/top-bottom signal). It is critical to confirm this signal with other indicators (e.g., RSI, Volume).
Info Label:
This provides an at-a-glance summary of the channel on the right side of the chart:
Trend Status: Identifies the trend as "Uptrend," "Downtrend," or "Sideways" based on the slope of the centerline. The Horizontal Threshold setting allows you to filter out noise by treating very small slopes as "Sideways."
Regression Model and Length: Shows your current settings.
Trend Slope: A numerical value representing how steep or weak the trend is.
Channel Width: Shows the price difference between the outermost channels. This is a measure of current volatility. A widening channel indicates increasing volatility, while a narrowing one indicates decreasing volatility.
3. What Users Should Pay Attention To & Best Practices
Define Your Strategy: Mean Reversion or Breakout?
Mean Reversion: If the market is in a ranging or gently trending phase, the price will tend to revert to the centerline after hitting the outer channels (overbought/oversold zones). In this case, the outer channels can be considered opportunities to sell (upper channel) or buy (lower channel).
Breakout: If a strong trend is in place, a price close beyond an outer channel can be a sign that the trend is accelerating. In this scenario, one might consider taking a position in the direction of the breakout. Correctly analyzing the current market state (ranging vs. trending) is key to deciding which strategy to employ.
Don't Use It in Isolation: No indicator is a holy grail. Use the Regression Channel in conjunction with other tools. Confirm signals with RSI divergences for overbought/oversold conditions, Moving Averages for the overall trend direction, or Volume indicators to confirm the strength of a breakout.
Choose the Right Model: On shorter-term charts (e.g., 1-hour, 4-hour), the Linear model is often sufficient. However, on long-term charts like the daily, weekly, or monthly, the Logarithmic model will provide much more accurate results, especially for assets with parabolic movements.
The Power of Automatic Mode: The Automatic length mode is often the most practical choice because it finds the most logical starting point for you. It saves you the trouble of adjusting settings, especially when analyzing different assets or timeframes.
Use the Alerts: If you don't want to miss the moment the price touches a key channel line, set up an alert from the Alert Settings section for your desired line (e.g., only the "Outer Channels"). This helps you catch opportunities even when you are not in front of the screen.
VSA Simplified (Volume Spread Analysis)This indicator implements a simplified version of Volume Spread Analysis (VSA) to help traders identify key volume-based signals used by professional market participants.
It detects classic VSA patterns such as:
Climactic Volume: unusually high volume with wide price spread indicating potential buying/selling climax
No Demand / No Supply: low volume and small spreads signaling lack of interest or exhaustion
Stopping Volume: high volume with long wicks and neutral closes showing absorption or rejection
The indicator plots distinct shapes on the chart to highlight these conditions, assisting traders to read market intent and potential turning points.
Best used alongside market structure and support/resistance zones for confluence.
Money NoodleMoney Noodle Indicator - How It Works
The Money Noodle indicator is a trend-following and support/resistance tool that combines multiple exponential moving averages (EMAs) with dynamic volatility-based bands to create a comprehensive trading system.
Core Components
1. Triple EMA System ("The Noodles")
Fast EMA (12): Most responsive to price changes, shows short-term momentum
Medium EMA (21): Intermediate trend direction
Slow EMA (35): Main trend line that acts as the central reference point
The "noodle" effect comes from how these three EMAs weave around each other and the price action, creating curved, flowing lines that resemble noodles.
2. Dynamic Volatility Bands
Upper Band: Main EMA + (ATR × Band Multiplier)
Lower Band: Main EMA - (ATR × Band Multiplier)
Uses a 20-period ATR (Average True Range) to measure market volatility
Band width automatically adjusts - wider during volatile periods, tighter during consolidation
How It Functions
Trend Identification:
When all three EMAs are aligned (fast > medium > slow), it indicates a strong uptrend
When EMAs are inverted (fast < medium < slow), it signals a downtrend
EMA crossovers provide early trend change signals
Support & Resistance:
The bands act as dynamic support and resistance levels
Price tends to bounce off the bands during trending markets
Band breaks often signal strong momentum moves or trend changes
Volatility Assessment:
Band width indicates market volatility - wider bands = higher volatility
ATR-based calculation makes the bands adaptive to current market conditions
The 0.0125 multiplier provides optimal sensitivity for most timeframes
Trading Applications
Entry Signals:
Buy when price bounces off the lower band with EMA alignment
Sell when price bounces off the upper band against the trend
Breakout trades when price decisively breaks through bands
Trend Following:
Use the main EMA (35) as your trend filter
Trade in the direction of EMA alignment
The "noodles" help identify trend strength - tighter = stronger trend
Risk Management:
Bands provide natural stop-loss levels
Band width helps size positions (wider bands = smaller size due to higher volatility)
The indicator works best on daily timeframes and provides a visual, intuitive way to read market structure, trend direction, and volatility all in one tool.
Bias Table (VWAP + BOS/CHOCH)Quick Summary — “Bias Table (VWAP + BOS/CHOCH)”
This indicator displays a table on your chart showing:
VWAP Bias: Indicates if the price is above or below VWAP (Bullish or Bearish) for the 4H and 1H timeframes.
BOS/CHOCH: Detects Break of Structure (BOS) or Change of Character (CHOCH) up or down for both timeframes.
Time Left: Shows how much time remains until the current candle closes, formatted in hours, minutes, and seconds.
It provides a clear snapshot of trend direction, market structure shifts, and candle timing at a glance.
Session Range ProjectionsSession Range Projections
Purpose & Concept:
Session Range Projections is a comprehensive trading tool that identifies and analyzes price ranges during user-defined time periods. The indicator visualizes high-probability reversal zones and profit targets by projecting Fibonacci levels from custom session ranges, making it ideal for traders who focus on time-based market structure analysis.
Key Features & Calculations:
1. Custom Time Range Analysis
- Define any time period for range calculation - from traditional sessions (Asian, London, NY) to custom periods like opening ranges, hourly ranges, or 4-hour blocks
- Automatically captures the highest and lowest prices within your specified timeframe
- Supports multiple timezone selections for global market analysis
- Flexible enough for intraday scalping ranges or longer-term swing trading setups
2. Premium & Discount Zones
- Automatically divides the range into premium (above 50%) and discount (below 50%) zones
- Visual differentiation helps identify institutional buying and selling areas
- Color-coded boxes clearly mark these critical price zones
3. Optimal Trade Entry (OTE) Zones
- Highlights the 79-89% retracement zone in premium territory
- Highlights the 11-21% retracement zone in discount territory
- These zones represent high-probability reversal areas based on institutional order flow concepts
4. Fibonacci Projections
- Projects 11 customizable Fibonacci extension levels from the range extremes
- Levels extend both above and below the range for symmetrical analysis
- Each level can be individually toggled and color-customized
- Default levels include common retracement ratios: -0.5, -1.0, -2.0, -2.33, -2.5, -3.0, -4.0, -4.5, -6.0, -7.0, -8.0
How to Use:
Set Your Time Range: Input your desired session start and end times (24-hour format)
Select Timezone: Choose the appropriate timezone for your trading session
Customize Display: Toggle various visual elements based on your preferences
Monitor Price Action: Watch for reactions at projected levels and OTE zones
Set Alerts: Configure sweep alerts for when price breaks above/below range extremes
Input Parameters Explained:
Time Range Settings
Range Start/End Hour & Minute: Define your analysis period
Time Zone: Ensure accurate session timing across different markets
Visual Settings
Range Box: Toggle the premium/discount zone visualization
Horizontal Lines: Customize high/low line appearance
Internal Range Levels: Show/hide equilibrium and OTE zones
Labels: Configure text display for key levels
Fibonacci Projections: Enable/disable extension levels
Display Settings
Historical Ranges: Show up to 10 previous session ranges
Alert Type: Choose between high sweep, low sweep, or both
Trading Applications:
Session-Based Trading: Analyze specific market sessions (Asian, London, New York, opening ranges, hourly ranges)
Reversal Trading: Identify high-probability reversal zones at OTE levels
Breakout/Reversal Trading: Monitor range breaks/reversals with built-in sweep alerts
Risk Management: Use Fibonacci projections as profit targets or rejection areas
Multi-Timeframe Analysis: Apply to any timeframe for various trading styles
Important Notes:
This indicator is for educational purposes only and should not be considered financial advice
Past performance does not guarantee future results
Always use proper risk management when trading
The indicator automatically manages historical data to maintain chart performance
RACZ-SIGNAL-V2.1RACZ-SIGNAL-V2.1 – Reactive Analytical Confluence Zones
Developed by: RACZ Trading
Indicator Type: Multi-Factor Confluence System
Overlay: Off (separate pane)
Purpose: Detect powerful trade opportunities through confluence of technical signals.
⸻
🔍 What is RACZ?
RACZ stands for Reactive Analytical Confluence Zones.
It’s a high-precision trading tool built for traders who rely on multi-signal confirmation, momentum alignment, and market structure awareness.
Rather than relying on a single technical metric, RACZ dynamically combines RSI, VWAP-RSI, Divergence, ADX, and Volume Analytics to produce a composite signal score from 0 to 12 — the higher the score, the stronger the signal.
⸻
🧠 How It Works – Core Components
1. RSI Analysis
• Detects momentum shifts.
• Compares RSI value to overbought (default: 67) and oversold (default: 33) thresholds.
• Adds points to Bullish or Bearish score.
2. VWAP-RSI
• Uses RSI based on VWAP (Volume Weighted Average Price).
• Adds weight to signals influenced by volume-adjusted price movement.
3. Divergence Detection
• Detects potential reversal zones.
• Bullish Divergence: RSI crosses up from low zone.
• Bearish Divergence: RSI crosses down from high zone.
• Strong confluence signal when present.
4. ADX Dynamic Strength Filter
• Custom-calculated ADX (trend strength indicator).
• Uses a dynamic threshold derived from SMA of ADX over a lookback period, scaled by a factor (default 0.9).
• Ensures signals are only validated in strong trend environments.
5. Volume Z-Score
• Detects anomalies in volume behavior.
• Z-score applied to 20-period volume average & deviation.
• Labels spikes, drops, high/low volume conditions.
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📊 Signal Scoring Logic
Each component (RSI, VWAP-RSI, Divergence, ADX) can score up to 3 points each.
• Bullish Score: Total from bullish alignment of each factor.
• Bearish Score: Total from bearish alignment of each factor.
• Signal Power = max(bullish, bearish)
📈 Signal Interpretation
• BUY: Bullish Score > Bearish Score
• SELL: Bearish Score > Bullish Score
• NEUTRAL: Scores are equal
• Signal power is plotted on a 0–12 histogram:
• 0–5 = Weak
• 6–8 = Medium
• 9–12 = Strong (High Confluence Zone)
🖥️ Live Status Panel (Top-Right Corner)
This real-time panel helps you break down the signal:Component
Value Explanation: RSI / VWAP / DIV / ADX
Shows points contributing to signal
SIGNAL: Current market bias (BUY, SELL, NEUTRAL)
VOLUME: Volume classification (Spike, Drop, High, Low, Normal)
Color-coded for quick interpretation.
✅ How to Use
1. Look at Histogram: Bars ≥6 suggest valid setups, especially ≥9.
2. Confirm Panel Agreement: Check which components are supporting the signal.
3. Validate Volume: Unusual spikes/drops often precede strong moves.
4. Follow Direction: Use BUY/SELL signals aligned with signal power and trend.
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⚙️ Customizable Inputs
• RSI period, overbought/oversold levels
• VWAP-RSI period
• ADX period and dynamic threshold settings
• Fully adjustable to fit any trading style
⸻
🚀 Why Choose RACZ?
• Clarity: Scores & signals derived from multiple tools, not just one.
• Confluence Logic: Designed for traders who look for confirmation across indicators.
• Speed: Real-time responsiveness to changing market dynamics.
• Volume Awareness: Integrated volume intelligence gives a deeper edge.
⸻
⚠️ Disclaimer
This indicator is intended strictly for educational and informational purposes only. It is not financial advice and should not be used to make actual investment decisions. Always conduct your own research or consult with a licensed financial advisor before trading or investing. Use of this script is at your own risk.
EMA Confluence Oscillator📌 EMA Confluence Oscillator + Signal
This oscillator helps detect ranging vs trending conditions by measuring EMA alignment, slope, and choppiness. It’s designed for traders who want to avoid chop and trade in clean directional moves.
⸻
🔍 How It Works:
• Uses 3 EMAs (Fast, Medium, Slow) to assess market structure
• Measures how flat the slow EMA is (low slope = range)
• Detects short-term momentum flips in fast/medium EMAs
• Calculates EMA spread to find tight, choppy zones
• Combines all signals into a Range Score (0–1 scale)
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🧠 How to Use:
• High Range Score (near 1): Market likely ranging
• Low Range Score (near 0): More directional/trending
• Watch for crosses below the range threshold to spot trend breakouts
• Optional Signal Line helps smooth decision points
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⚙️ Features:
• Custom lengths for 3 EMAs
• Adjustable slope and convergence thresholds
• Toggle smoothing and signal line
• Background highlight when market is likely in a range
• Clean layout designed for fast intraday analysis
⸻
🛠️ Input Settings Explained:
• Fast/Medium/Slow EMA: Controls trend detection windows
• Slope Lookback: Period used to assess flatness of slow EMA
• Convergence Threshold: How close EMAs must be to count as “tight”
• Smooth Output: Reduces noise in final Range Score
• Signal Line: Smoothed version of the score for easier reading
• Range Threshold: Level where choppiness is likely
• Show Background: Highlights range zones visually
Dinámicas de Mercado ProUser Manual: Indicator "Dinámicas de Mercado Pro" (DMP)
Author: @Profit_Quant
Created by: Gemini AI (2025)
1. General Concept
The "Dinámicas de Mercado Pro" indicator is an all-in-one technical analysis tool designed to be overlaid directly onto your price chart. Its goal is to provide a clear and concise view of the market structure by combining three crucial trading elements:
The Overall Trend: What is the main direction of the market?
Liquidity Zones: Where is the price likely to react (supports and resistances)?
Breakout Momentum: When is the price breaking out of a range with force and volume?
By integrating these components, the DMP helps you make more informed trading decisions by identifying high-probability zones for entering or exiting trades.
2. Essential Step! - Initial Chart Setup
For the indicator to work as designed, it is essential to hide the original candles of the TradingView chart.
The indicator already draws its own candles with the market sentiment colors. If you do not hide the original ones, you will see both sets of candles overlapping, which will make the chart confusing and unreadable.
How to hide the chart's candles?
There are two simple ways:
Method 1 (Recommended):
Once you have the "DMP" indicator on your chart, look for the symbol's name in the top-left corner of your screen (e.g., BTCUSD, EURUSD, etc.).
Right next to the name, you will see an eye icon (👁️).
Click that eye icon to hide the main symbol (the original candles, bars, or lines). The chart will become clean, showing only the candles drawn by the DMP indicator.
Method 2 (Alternative):
Click the gear icon (⚙️) for the chart settings.
Go to the "Symbol" tab.
Uncheck the boxes for "Body," "Borders," and "Wicks," or set their opacity to 0%.
3. Main Components and Their Interpretation
The indicator has 3 key visual components you need to understand.
a) Supply and Demand Zones (Order Blocks)
These are the colored rectangles drawn automatically on the chart.
What are they?: They represent zones where there was a strong imbalance between buyers and sellers, often caused by the activity of large institutions.
Demand Zone (Blue Rectangle): A potential support zone. When the price returns to this area, buying pressure is expected to increase, pushing the price up.
Supply Zone (Red Rectangle): A potential resistance zone. When the price reaches this area, selling pressure is expected to increase, pushing the price down.
Mitigated Zone (Gray Rectangle): When the price touches a supply or demand zone, it becomes "mitigated," meaning the liquidity in that zone has already been used. The zone turns gray to indicate that it is less reliable and the price is more likely to break through it in the future.
b) Candle Coloring (Market Sentiment)
The chart candles will change color based on a priority system to give you an instant read of market sentiment.
Green Candles (Uptrend): Indicate that the price is above the long-term Exponential Moving Average (EMA) (200 by default). This suggests the overall trend is bullish, and you should look for buying opportunities.
Red Candles (Downtrend): Indicate that the price is below the 200 EMA. This suggests the overall trend is bearish, and you should look for selling opportunities.
White Candles (Bullish Breakout): Alert! This occurs when the price breaks a recent range high AND is accompanied by above-average volume. It's a strong sign of bullish momentum.
Purple Candles (Bearish Breakout): Alert! This occurs when the price breaks a recent range low with high volume. It's a strong sign of bearish momentum.
Gray Candles (Neutral): Appear when the price is very close to the 200 EMA, indicating indecision or consolidation in the market. This is a time for caution.
c) Probability Paths (Price Targets)
These are the dashed lines projected from the last real-time candle.
Demand Path (Blue Dashed Line): Points from the current price to the center of the nearest unmitigated demand zone. It acts as a potential support target.
Supply Path (Red Dashed Line): Points from the current price to the center of the nearest unmitigated supply zone. It acts as a potential resistance target.
4. Basic Trading Strategies
Confluence Strategy: Look for buying opportunities when the price pulls back to a blue demand zone while the candles are green (uptrend). Look for selling opportunities when the price rallies to a red supply zone with red candles (downtrend).
Breakout Strategy: Use the white or purple candles as an aggressive entry signal in the direction of the breakout. The stop-loss could be placed on the other side of the breakout candle.
Range Strategy: When the price is trapped between a clear supply and demand zone (with no breakout candles), you can trade the bounces between them until one zone is broken with a white or purple candle, signaling the end of the range.
5. Indicator Settings (Parameters)
You can customize every aspect of the indicator in its settings panel (the options are self-explanatory in the indicator's menu).
Quantum RSI (TechnoBlooms)The Next Evolution of Momentum Analysis
📘 Overview
Quantum RSI is an advanced momentum oscillator based on Quantum Price Theory, designed as a superior alternative to the traditional RSI. It incorporates a Gaussian decay function to weigh price changes, creating a more responsive and intuitive measure of trend strength.
This indicator excels in identifying micro-trends and subtle momentum shifts — especially in narrow or low-volatility environments where standard RSI typically lags or gives false signals. With its enhanced smoothing, intuitive color gradients, and customizable moving average, Quantum RSI offers a powerful tool for traders seeking clarity and precision.
🔍 Key Features
• ⚛️ Quantum Momentum Engine: Measures net momentum using quantum-inspired Gaussian decay weighting.
• 🎨 Color-Reversed Gradient Zones:
o Green (Overbought): Shows momentum strength, not weakness.
o Red (Oversold): Highlights momentum exhaustion and potential bounce.
• 🧠 Smoothing with MA: Option to apply moving average (SMA/EMA/WMA/SMMA/VWMA) to the Quantum RSI line.
• 📊 Levels at 30 / 50 / 70: Standard RSI levels for decision-making guidance.
• 📈 Intuitive Visuals: Gradient fills for cleaner interpretation of zones and transitions.
👤 Who Is It For?
• Technical traders seeking a modern alternative to RSI.
• Quantitative analysts who value precision and smooth signal flow.
• Visual traders looking for intuitive, color-coded trend zones.
• Traders focused on market microstructure and early trend detection.
💡 Pro Tips
• Pair with order blocks, market structure tools, or Fibonacci confluences for high-probability entries.
• Use on assets with frequent compression or consolidation, where traditional RSI often misleads.
• Combine with volume-based indicators or smart money concepts for added confirmation.
• Ideal for sideways markets, false breakouts, or low-volatility zones where typical RSI lags.
EMA Pullback System 1:5 RRR [SL]EMA Trend Pullback System (1:5 RRR)
Summary:
This indicator is designed to identify high-probability pullback opportunities along the main trend, providing trade signals that target a high 1:5 Risk/Reward Ratio. It is a trend-following strategy built for patient traders who wait for optimal setups.
Strategy Logic:
The system is based on three Exponential Moving Averages (EMAs): 21, 50, and 200.
BUY Signal:
Trend (Uptrend): The price must be above the 200 EMA.
Pullback: The price must pull back into the "Dynamic Support Zone" between the 21 EMA and 50 EMA.
Confirmation: A strong Bullish Confirmation Candle (e.g., Bullish Engulfing) must form within this zone.
SELL Signal:
Trend (Downtrend): The price must be below the 200 EMA.
Pullback: The price must rally back into the "Dynamic Resistance Zone" between the 21 EMA and 50 EMA.
Confirmation: A strong Bearish Confirmation Candle (e.g., Bearish Engulfing) must form within this zone.
Key Features:
Clearly plots the 21, 50, and 200 EMAs on the chart.
Displays BUY and SELL labels when the rules are met.
Automatically calculates and plots Stop Loss (SL) and Take Profit (TP) levels for each signal.
The Risk/Reward Ratio for the Take Profit level is customizable in the settings (Default: 1:5).
How to Use:
Best suited for higher timeframes like H1 and H4.
It is crucial to wait for the signal candle to close before considering an entry.
While this is an automated tool, for best results, combine its signals with your own analysis of Price Action and Market Structure.
Disclaimer:
This is an educational tool and not financial advice. Trading involves substantial risk. Always use proper risk management. It is essential to backtest any strategy before deploying it with real capital.
3 Bar Reversal3 Bar Reversal
This pattern is described in John Carter's "Mastering the Trade"
The 3 Bar Reversal indicator is a simple but effective price action tool designed to highlight potential short-term reversals in market direction. It monitors consecutive bar behavior and identifies turning points based on a three-bar pattern. This tool can assist traders in spotting trend exhaustion or early signs of a reversal, particularly in scalping or short-term trading strategies.
How It Works
This indicator analyzes the relationship between consecutive bar closes:
It counts how many bars have passed since the price closed higher than the previous close (barssince(close >= close )) — referred to as an "up streak".
It also counts how many bars have passed since the price closed lower than the previous close (barssince(close <= close )) — known as a "down streak".
A reversal condition is met when:
There have been exactly 3 bars in a row moving in one direction (up or down), and
The 4th bar closes in the opposite direction.
When this condition is detected, the script performs two actions:
Plots a triangle on the chart to signal the potential reversal:
A green triangle below the bar for a possible long (buy) opportunity.
A red triangle above the bar for a possible short (sell) opportunity.
Triggers an alert condition so users can set notifications for when a reversal is detected.
Interpretation
Long Signal: The market has printed 3 consecutive lower closes, followed by a higher close — suggesting bullish momentum may be emerging.
Short Signal: The market has printed 3 consecutive higher closes, followed by a lower close — indicating possible bearish momentum.
These patterns are common in market retracements and can act as confirmation signals when used with other indicators such as RSI, MACD, support/resistance, or volume analysis.
Usage Examples
Scalping: Use the reversal signal to quickly enter short-term trades after a short-term exhaustion move.
Swing Trading: Combine this with trend indicators (e.g., moving averages) to time pullbacks within larger trends.
Confirmation Tool: Use this indicator alongside candlestick patterns or support/resistance zones to validate entry or exit points.
Alert Setup: Enable alerts based on the built-in alertcondition to receive instant notifications for potential trade setups.
Limitations
The 3-bar reversal logic does not guarantee a trend change; it signals potential reversals, which may need confirmation.
Best used in conjunction with broader context such as trend direction, market structure, or other technical indicators.
