ProfitTrailerV2 RSI+BB+SRSI+Stochastic Oscillator Signal+AlertsThis is an all-in-one indicator with alerts that most people call signals and it's designed for Cryptocurrency leverage trading. This indicator features, the most popularly used indicators in technical analysis and are the basic technical analysis indicators any successful trader should master before going into more advanced technical analysis tool. The ProfitTrailerV2 RSI+BB+SRSI+Stochastic Oscillator Signal+Alerts features the Bollinger Bands, Relative Strength Index, Stochastic RSI and Stochastic Oscillator, and it was designed for use with ProfitTrailer V2 and can also be used with all other trading bots or on its own as a powerful market leveraging and trading indicator using alerts.
The ProfitTrailerV2 RSI+BB+SRSI+Stochastic Oscillator Signal+Alerts can be customized to any trader specific trading patterns and offers the ability to choose a combination of indicators from the featured ones to use. With the Buy and Sell Signal feature, trading on any cryptocurrency exchange can be automated and with the alerts feature, the ProfitTrailerV2 RSI+BB+SRSI+Stochastic Oscillator Signal+Alerts will automated buying and selling signals for any crypto trading bot but I'll always recommend using for making buys only when using with any bot. This indicator/script can be used with any base pair; BTC, ETH, and USD or USDT.
As mentioned above, all four indicators can be combined to find a very safe and secure buy and profitable sell signals, which maximizes your profit margins and overall earnings over time. Also, 2 or 3 could be combined as well, depending on the traders knowledge on how to use each indicator independently to find its best settings. My recommendation would be to test all independently and or together with very little capital to find what works best for you. I recommend this because the cryptocurrency market in a very volatile market and unpredictable, some combination of indicators would work for some certain coin pairs and not all, while others would work better with a different setting and a particular coin pair.
As with all script use at your own risk and only trade what you can afford to lose, while this indicator isn't designed to lose you money and I will not be held liable for any losses due to misuse. I am also not a financial advisor and the ProfitTrailerV2 RSI+BB+SRSI+Stochastic Oscillator Signal+Alerts will be made available soon as it's still undergoing rigorous testing.
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CMYK RMI TRIPLE Automated strategy▼ This is the strategy version of the script.
◊ Introduction
This script makes use of three RMI 's, that indicate Overbought/Oversold on different timescales that correspond with Frequency’s that move the market.
◊ Origin
The Relative Momentum Index was developed by Roger Altman and was introduced in his article in the February, 1993 issue of Technical Analysis of Stocks & Commodities magazine.
While RSI counts up and down ticks from close to close, the Relative Momentum Index counts up and down ticks from the close relative to a close x number of days ago.
This results in an RSI that is smoother, and has another setting for fine tuning results.
This bot originated out of Project XIAM , an investigative script that outlined my approach towards Automated Trading Strategies.
Are you interested in writing bots yourself ? check out the beta version of this script.
It has many bugs, but also most of the Skeleton.
◊ Usage
This script is intended for Automated Trading with AUTOVIEW or TVAUTOTRADER , on the 1 minute chart.
◊ Features Summary
Overlay Mode
Indicator Mode
Three RMI's
Trend adjustment
Pyramiding
Ignore first entries
Take Profit
Stop Loss
Interval between Entries
Multiring Fix
Alert signal Seperation
◊ Community
Wanna try this script out ? need help resolving a problem ?
CMYK :: discord.gg
AUTOVIEW :: discordapp.com
TRADINGVIEW UNOFFICIAL :: discord.gg
◊ Setting up Autoview Alerts
Use the study version of this script, To set up The Alerts Autoview Picks up on.
The Signals to work with are :
Open 1 Long
Use this to open one Long Position.
With quantity being : /
Once per bar
Being larger than 0
Comment example : e=exchange b=long q=amount t=market
Open 1 Short
Use this to open one Short Position.
With quantity being : /
Once per bar
Being larger than 0
Comment example : e=exchange b=short q=amount t=market
Close1 Position
Use this to Close The amount of one Open Position.
With quantity* being : /
Once per bar
Being larger than 0
Comment example : e=exchange c=position q=amount t=market
*Beware when using a percental % quantity, instead of an absolute quantity.
Percental Quantities are based on the , Not
And will change in absolute value relative to the amount of open trades.
Close All positions
Use this to Close All Open Positions.
With quantity being :
Once per bar
Being larger than 0
Comment example : e=exchange c=position t=market
For the specific Syntax used in the comment of the alert, visit Autoview .
◊ Setting up TVAutotrader
Use the strategy version of this script, And load it into TVAT .
◊ Backtesting
Use the strategy version of this script for backtesting.
◊ Contact
Wanna try this script out ? need help resolving a problem ?
CMYK :: discord.gg
PT Magic Triggers So its me again. I have decided to create Trend Trigger Script for PT Magic addon for a trading bot Profit Trailer. If you do not own this bot and Addon the following explanation will not help you.
For each Trend you define number of minutes and it then calculates the percentage change between the close price now and X candles before.
Same calculation is for all 6 Triggers i beleive that is all you need :)
Hope it helps you all.
LTC: LYHj4WDN7BPu5294cSpqK3SgWSWdDX56Qt
BTC: 1NPVzeDSsenaCS9QdPro877hkMk93nRLcD
MACD, backtest 2015+ only, cut in half and doubledThis is only a slight modification to the existing "MACD Strategy" strategy plugin!
found the default MACD strategy to be lacking, although impressive for its simplicity. I added "year>2014" to the IF buy/sell conditions so it will only backtest from 2015 and beyond ** .
I also had a problem with the standard MACD trading late, per se. To that end I modified the inputs for fast/slow/signal to double. Example: my defaults are 10, 21, 10 so I put 20, 42, 20 in. This has the effect of making a 30min interval the same as 1 hour at 10,21,10. So if you want to backtest at 4hr, you would set your time interval to 2hr on the main chart. This is a handy way to make shorter time periods more useful even regardless of strategy/testing, since you can view 15min with alot less noise but a better response.
Used on BTCCNY OKcoin, with the chart set at 45 min (so really 90min in the strategy) this gave me a percent profitable of 42% and a profit factor of 1.998 on 189 trades.
Personally, I like to set the length/signals to 30,63,30. Meaning you need to triple the time, it allows for much better use of shorter time periods and the backtests are remarkably profitable. (i.e. 15min chart view = 45min on script, 30min= 1.5hr on script)
** If you want more specific time periods you need to try plugging in different bar values: replace "year" with "n" and "2014" with "5500". The bars are based on unix time I believe so you will need to play around with the number for n, with n being the numbers of bars.
RunRox - Pairs Strategy🧬 Pairs Strategy is a new indicator by RunRox included in our premium subscription.
It is a specialized tool for trading pairs, built around working with two correlated instruments at the same time.
The indicator is designed specifically for pair trading logic: it helps track the relationship between two assets, identify statistical deviations, and generate signals for opening and managing long/short combinations on both legs of the pair.
Below in this description I will go through the core functions of the indicator and the main concepts behind the strategy so you can clearly understand how to apply it in your trading.
📌 CONCEPT
The core idea of pair trading is to find and trade correlated instruments that usually move in a similar way.
When these two assets temporarily diverge from each other, a trading opportunity appears.
In such moments, the relatively overvalued asset is sold (short leg), and the relatively undervalued asset is bought (long leg).
When the spread between them narrows and both instruments revert back toward their typical relationship (mean), the position is closed and the trader captures the profit from this convergence.
In practice, one leg of the pair can end up in a loss while the other generates a larger profit.
Due to the difference in performance between the two assets, the combined result of the pair trade can still be positive.
✅ KEY FEATURES:
2 deviation types (Z-Score and S-Score)
Invert signals mode
Hedge Coefficient (position size balancing between both legs)
6 hedge modes
Entries based on Score or RSI
Extra entries based on Score or Spread
Stop Loss
Take Profit
RSI Filter
RSI Pivot Mode
Built-in Backtester Strategy
Lower Timeframe Backtester Strategy
Live trade panel for current position
Equity curve chart
21 performance metrics in the backtester
2 alert types
*And many more fine-tuning options for pair trading
🔗 SCORE
Score is the core deviation metric between the two assets in the pair.
For example, if you are trading ETHUSDT/BTCUSDT, the indicator analyzes the relationship ETH/BTC, and when one leg temporarily diverges from the other, this difference is reflected in the Score value.
In other words, Score shows how much the current spread between the two instruments deviates from its typical state and is used as the main signal source for pair entries and exits.
In the screenshot above you can see how Score looks in our indicator.
Depending on how large the difference is between the two assets, the Score value can move in a range from −N to +N
When Score is in the −N zone, this is a 🟢 long zone for the first asset and a short zone for the second.
Using the ETH/BTC example: when Score is deeply negative, you open a long on ETH and a short on BTC at the same time, then close both legs when Score returns back to the 0 zone (balance between the two assets).
When Score is in the +N zone, this is a 🔴 short zone for the first asset and a long zone for the second.
In the same ETH/BTC example: when Score is strongly positive, you short ETH and long BTC, and again close both positions when Score comes back to the neutral 0 zone.
☯️ Z/S SCORE
Inside the indicator we added two different formulas for calculating the spread between the two legs of the pair: Z-Score and S-Score.
These approaches measure deviation in different ways and can produce slightly different signals depending on the chosen pair and its behavior.
This allows you to switch between Z-Score and S-Score and choose the method that gives more stable and cleaner signals for your specific instruments.
As you can see in the screenshot above, we used the same pair but applied different Score types to measure the spread and deviation from the norm.
🟣 Z-Score – generated 9 entry signals .
It reacts to price fluctuations more smoothly and usually stays within a range of approximately −8 to +8 .
🟠 S-Score – generated 5 entry signals .
It reacts to price changes more aggressively and produces wider deviations, often reaching −15 to +15 .
This gives traders the choice between a more sensitive but smoother model (Z-Score) and a more selective, stronger-deviation model (S-Score)
⁉️ HOW DOES THE STRATEGY WORK
Here is a basic example of how you can trade this pair trading strategy using our indicator and its signals.
In the classic approach the trade consists of one initial entry and several scale-ins (averaging) if the spread continues to move against the position.
The first entry is opened when Score reaches a standard deviation of −2 or +2.
If price does not revert to the mean and moves further against the position so that Score expands to −3 or +3, the strategy performs the first scale-in.
If Score extends to −4 or +4, a second scale-in is added.
If the spread grows even more and Score reaches −5 or +5, a third scale-in is executed.
In our indicator the number of averaging steps can be up to 4 scale-ins .
After that the position waits until Score returns back to the 0 level , where the whole pair position is closed.
This is the standard model of classical pair trading.
However there are many variations:
using Stop Loss and Take Profit,
exiting earlier or later than the 0 zone,
scaling in not by Score but by Spread, since Score is not linear while Spread is linear,
entering when RSI on both tickers shows opposite extremes, for example RSI 20 on one asset and RSI 80 on the other, and so on.
The number of possible trading styles for this strategy is very large.
We designed the indicator to cover as many of these variations as possible and added flexible tools so you can build your own pair trading logic on top of it.
Below is an example of a classic pair trade with two entries: one main entry and one extra entry (scale-in) .
The pair SUIUSDT / PENGUUSDT shows a high correlation, and on one of the trades the sequence looked like this:
A −2 Score deviation occurred into the long zone and triggered the Main Entry .
🔹 Main Entry
Long SUIUSDT – Margin: 5,000 USD, Entry price: 1.5708
Short PENGUUSDT – Margin: 5,000 USD, Entry price: 0.011793
Price then moved further against the position, Score went deeper into deviation, and the strategy added one extra entry.
🔸 Extra Entry
Long SUIUSDT – Margin: 5,000 USD, Entry price: 1.5938
Short PENGUUSDT – Margin: 5,000 USD, Entry price: 0.012173
The trade was closed when Score reverted back toward the 0 zone (mean reversion of the spread):
❎ Exit
SUIUSDT P&L: −403.34 USD, Exit price: 1.5184
PENGUUSDT P&L: +743.73 USD, Exit price: 0.011089
✅ Total P&L: +340.39 USD
With a total margin of 10,000 USD used per side (20,000 USD combined), this trade yielded around +1.7% on the deployed margin.
On different assets the size and speed of the spread movement will vary, but the principle remains the same.
This is just one example to illustrate how the strategy works in practice using simplified theoretical balances.
⚙️ MAIN SETTINGS
After explaining how the strategy works, we can move to the indicator settings and their logic.
The first block is Main Settings, which controls how the pair is built, how the spread is calculated, and how the backtest is performed.
The core idea of the indicator is to backtest historical data, generate entry signals, show open-position parameters, and provide all necessary metrics for both discretionary and algorithmic trading.
This is a complete framework for analyzing a pair of assets and building a trading system around them. Below I will go through the main parameters one by one.
🔹 Exclude Dates
Allows you to exclude abnormal periods in the pair’s history to remove outlier trades from the backtest.
This is useful when the market experienced extreme news events, listing spikes, or other non-typical situations that distort statistics.
🔹 Pair
Here you select the second asset for your pair.
For example, if your main chart is BTCUSDT, in this field you choose a correlated asset such as ETHUSDT, and the working pair becomes BTCUSDT / ETHUSDT.
The indicator then calculates spread, Score, and all related metrics based on this asset combination.
🔹 Lower Timeframe
This is a special mode for backtesting on a lower timeframe while using a higher timeframe chart to extend the history limit.
For example, if your TradingView plan provides only 5,000 bars of history on the current timeframe, you can switch your chart to a higher timeframe and select a lower timeframe in this setting.
The indicator will then reconstruct the pair logic using up to 99,000 bars of lower timeframe data for backtesting.
This allows you to test the pair on a much longer historical period and find more stable combinations of assets.
🔹 Method
Here you choose which deviation model you want to use: Z-Score or S-Score.
Both methods calculate spread deviation but use different formulas, which can give different signal behavior depending on the pair.
Examples of these two methods are shown earlier in this description.
🔹 Period
This parameter defines how many bars are used to calculate the average deviation for the pair.
If you set Period = 300, the indicator looks back 300 bars and calculates the typical spread deviation over that window.
For example, if the average deviation over 300 bars is around 1%, then a move to 2% or more will push Z/S Score closer to its boundary levels, since such a deviation is considered abnormal for that lookback period.
A larger Period means that only bigger deviations will be treated as anomalies.
A smaller Period makes the model more sensitive and treats smaller deviations as anomalies.
This allows you to tune how aggressive or conservative your pair trading signals should be.
🔹 Invert
This setting is used for negatively correlated pairs.
Some instruments have a positive correlation in the range from +0.8 to +1.0 (strong positive correlation), while others show a negative correlation from −0.8 to −1.0, meaning they usually move in opposite directions.
A classic example is the pair EURUSD and DXY.
As shown in the screenshot above, these instruments often have strong negative correlation due to macro factors and typically move in opposite directions: when EURUSD is rising, DXY is falling, and vice versa.
Such pairs can also be traded with our indicator.
To do this, we use the Invert option, which effectively flips one of the assets (as shown in the screenshot below). After inversion, both instruments are brought to a “same-direction” behavior from the model’s point of view.
From there, you trade the pair in the same way as a positively correlated one:
you open both legs in the same direction (both long or both short) depending on the spread and Score, and then wait for the spread between the inverted pair to converge back toward its mean.
🔀 HEDGE COEFFICIENT
The next block of settings is related to the hedge coefficient.
This defines how much margin is allocated to each leg of the pair.
The classic approach in pair trading is to split the position equally between both assets.
For example, if you allocate 100 USD to a trade , the standard model would open 50 USD long on one asset and 50 USD short on the other.
This works well for pairs with similar volatility , such as BTCUSDT / ETHUSDT
However, if you use a pair like BTCUSDT / DOGEUSDT , the volatility of these assets is very different.
They can still be correlated, but their amplitude is not the same. While Bitcoin might move 2% , Dogecoin can move 10% over the same period.
Because of that, for pairs with strongly different volatility, we can use a hedge coefficient and, for example, enter with 30 USD on one leg and 70 USD on the other, taking the volatility difference into account.
This is the main idea behind the Hedge Coefficient section and its primary use.
The indicator includes 6 methods of calculating the coefficient:
Cumulative RMA
Beta OLS
Beta TLS
Beta EMA
RMA Range
RMA Delta
Each method uses a different formula to compute the hedge coefficient and to size the position based on different metrics of the assets.
We leave it to the trader to decide which algorithm works best for their specific pair and style.
Below are the settings inside this section:
🔹 Method
When Auto Hedge is enabled, you can select which method to use from the list above.
The chosen method will automatically calculate the hedge coefficient between the two legs.
🔹 Hedge Coefficient
This is the manual hedge ratio per trade when Auto Hedge is disabled.
By default it is set to 1, which means the position is opened 50/50 between the two assets.
🔹 Min Allowed Hedge Coef.
This is the minimum allowed hedge coefficient.
By default it is 0.2, which means the model will not go below a 20% / 80% split between the legs.
🔹 MA Length
For methods that use moving averages (for example Beta EMA), this parameter sets the period used to calculate the hedge coefficient.
🛠️ STRATEGY SETTINGS
The next important block is Strategy Settings .
Here you define the core parameters used for backtesting: trading commission, position size, entry / exit logic, Stop Loss, Take Profit, and other rules that describe how you want the strategy to operate.
Below are all parameters with a detailed explanation.
🔸 Commission %
In this field you set your broker’s fee percentage per trade .
The indicator automatically calculates the correct commission for each leg of every trade. You only need to input the real commission rate that your broker charges for volume. No additional manual calculations are required.
🔸 Main Entry Mode
There are two options for the main entry:
Score - This is the primary entry method based on Z/S Score.
When Score reaches the deviation level defined in the settings below, the strategy opens the first position.
For example, if you set “Entry at 2 deviations”, the trade will be opened when Score hits ±2.
RSI Only - Alternative entry method based on RSI divergence between the two assets.
The exact RSI levels are defined in the RSI settings section below.
For example, if you set the entry threshold at 30, then when one asset has RSI below 30 and the second one has RSI above 70, the first entry will be triggered.
🔸 Extra Entries Mode
This defines how scale-ins (averaging) are executed. There are two modes:
Score - Works the same way as the main entry, but for additional entries.
For example, the main entry can be at 2 deviations, the first scale-in at 3, the second at 4, etc.
Spread - This mode uses the Spread (difference between the two assets) starting from the main entry moment.
As the spread continues to widen, the strategy can add extra entries based on spread growth rather than Score.
Since Score is a non-linear metric and Spread is linear, in some configurations averaging by Spread can produce better results than averaging by Score. This is pair- and strategy-dependent. 🔸 Entry parameters
Deviation / Spread threshold
Entry size
Main Entry – first field (deviation / spread), second field (position size)
Entry 2 – first field (deviation / spread), second field (position size)
Entry 3 – first field (deviation / spread), second field (position size)
Entry 4 – first field (deviation / spread), second field (position size)
This allows you to define up to four scaling steps with different triggers and different sizing.
🔸 Exit Level
This parameter defines at what Score level you want to exit the trade.
By default it is 0, which means the backtester closes the position when Score returns to the neutral (0) zone.
You can also use positive or negative values. Example:
Assume your main entry is configured at a 3 deviation.
You can exit at the 0 level, or you can set Exit Level = 2.
If your initial entry was at −3, the position will be closed when Score reaches +2.
If your initial entry was at +3, the position will be closed when Score reaches −2.
This approach can increase the profit per trade due to a larger captured spread, but it may also increase the holding time of the position.
🔸 Stop Loss
Here you define the maximum loss per trade in PnL units.
If a trade reaches the negative PnL value specified in this field and the Stop Loss option is enabled, the indicator will close the trade at a loss.
The Cooldown parameter sets a pause after a losing trade:
the strategy will wait a specified number of bars before opening the next trade.
🔸 Take Profit
Works similar to Stop Loss but for profit targets.
You set the desired PnL value you want to reach.
The trade will be closed when either the Take Profit target is hit or when Score reaches the exit level defined in the settings, whichever occurs first (depending on your configuration).
🔸 Show Qty in currency
When enabled, trade size is displayed in currency (USD) instead of token quantity.
This is useful for quickly understanding position size in monetary terms.
You will see this in the Current Trade panel, which is described later.
🔸 Size Rounding
Controls how many decimal places are used when rounding position size (from 0 to 10 digits after the decimal).
This is also used for the Current Trade panel so you can adjust how detailed or compact the size display should be.
📊 RSI FILTERS
This section is used for additional trade filtering.
RSI can be used in two ways:
as a primary entry signal,
or as an extra filter for entries based on Z/S Score.
If in the Strategy Settings the Main Entry Mode is set to RSI, then RSI becomes the main trigger for opening a position.
In this case a trade is opened when the RSI of the two assets reaches opposite zones.
Example:
If the threshold is set to 30, then:
when one asset has RSI below 30, and
the second asset has RSI above 70 (100 − 30),
the strategy opens the first entry.
All extra entries after that will be executed either by Spread or by Z/S Score, depending on your Extra Entries Mode.
Below are the parameters in this block:
RSI Length – standard RSI period setting.
RSI Pivot Mode – when enabled, RSI is used as an additional filter together with Z/S Score. The indicator looks for a reversal pattern on RSI (pivot behavior). If RSI forms a reversal structure, the trade is allowed to open. If not, the signal is skipped until a proper RSI pivot is formed.
Entry RSI Filter – here you define the RSI thresholds used for RSI-based entries. These are the same boundary levels described in the example above.
Overall, this section helps filter out lower-quality trades using additional RSI conditions or lets you build RSI-only entry logic based on extreme levels.
🎨 MAIN CHART STYLING
This section controls the visual appearance of trades on the main chart.
You can customize how the second asset line is drawn, as well as the icons for entries, scale-ins, and exits, including their size and style.
▫️ Price Line
This is the line that shows the price of the second asset and the relative difference between the two instruments.
You can adjust the line thickness and color to make it more readable on your chart.
▫️ Adjust Price Line by Hedge Coefficient
When this option is enabled, the second asset’s line is normalized by the hedge coefficient.
If you turn it off, the hedge coefficient will not be applied to the second asset’s line, and it will be displayed in raw form.
▫️ Entry Label
Here you can customize how the entry markers look:
choose the color, icon style, and size of the label that marks each trade entry and scale-in on the chart.
▫️ Exit Label
Similarly, you can define the color, icon style, and size of the label used for exits.
This helps visually separate entries and exits and makes it easier to read the trade history directly from the chart.
🎯 INDICATOR PANEL
This section controls the settings of the indicator panel, which works like an oscillator and allows you to visualize multiple metrics in one place.
You can flexibly enable, style, and scale each parameter.
🔹 Score
Displays the main deviation metric between the two assets.
You can customize the color and line thickness of the Score plot.
🔹 Spread
Shows the spread between the two assets.
It starts calculating from the moment the trade is opened.
You can adjust its color and thickness for better visibility.
🔹 Total Profit
Displays the cumulative profit for this pair and strategy as a line that grows (or falls) over time.
Color, opacity, and line thickness can be customized.
🔹 Unrealized PNL
Once a trade is opened, this line shows the current PnL of the active position.
It also lets you see historical drawdowns on the pair.
Color and thickness can be adjusted.
🔹 Released PNL
Shows the realized PnL of each closed trade as bars.
Useful for quickly evaluating the result of every individual trade in the backtest.
🔹 Correlation
Plots the correlation coefficient between the two assets as a graph, so you can visually track how stable or unstable the relationship between them is over time.
🔹 Hedge Coefficient
Shows the hedge coefficient as a line, which helps understand how the model is rebalancing exposure between the two legs depending on their behavior.
For each metric there is also a 📎 Stretch option.
Stretch allows you to compress or expand the scale of a specific line to visually align metrics with different ranges on the same panel and make the chart easier to read.
📈 PROFIT CHART
Since TradingView does not natively support proper backtesting for pair trading, this indicator includes its own profit curve for the pair.
You can visually see how the strategy performed over historical data: whether there were deep drawdowns, abnormal profit spikes, or stable equity growth over time. This makes it much easier to evaluate the quality of the pair and the strategy on history.
In the settings of this section you can flexibly customize how the profit chart is displayed:
labels, position of the panel, padding, and other visual details.
Everything depends on your personal preferences, so we give full control over styling:
you can adjust the look of the profit chart to match your layout or completely hide it from the chart if you do not need it.
📌 CURRENT TRADE
This section controls the current trade table.
When there is an active trade on the chart, the panel displays all key information for the open position:
direction for each ticker (long or short),
required position size for each leg,
entry price for both assets,
and real-time PnL for each leg separately,
so you always have a clear view of the current situation.
The main thing you can do with this table is customize its appearance:
you can change the size, position on the chart, background and text colors, as well as separate coloring for positive / negative PnL and different colors for long and short positions.
📅 BACKTEST RESULTS
The next key block is Backtest Results.
This results table with detailed metrics gives you an extended view of how the pair and strategy perform: win rate, profit factor, long/short breakdown, and more than 20 additional stats that help you evaluate the potential of your setup.
⚠️ First of all, it is important to note ⚠️
past performance does not guarantee future results.
Every trader must keep this in mind and factor these risks into their strategy.
The table shows metrics in three cuts:
All Entries
Main Entries
Extra Entries (scale-ins)
Core metrics:
Profit – total profit for each entry type.
Winrate – win rate for this pair.
Profit Factor – ratio of gross profit to gross loss for the strategy.
Trades – number of trades in the backtest.
Wins – number of winning trades.
Losses – number of losing trades.
Long Profit – profit generated by long positions.
Short Profit – profit generated by short positions.
Longs – total number of long trades.
Shorts – total number of short trades.
Avg. Time – average time spent in a trade.
Additional metrics for a deeper evaluation of the pair:
Correlation – current correlation between the two assets in the pair.
Bars Processed – number of bars used in the analysis.
Max Drawdown – maximum historical drawdown of the strategy.
Biggest Loss – the largest single losing trade in the backtest.
Recommended Hedge – recommended hedge coefficient based on historical behavior.
Max Spread – maximum positive spread observed in history.
Min Spread – maximum negative spread observed in history.
Avg. Max Spread – average of positive extreme spread values (above 0).
Avg. Min Spread – average of negative extreme spread values (below 0).
Avg Positive Spread – average positive spread across all trades (only values above 0).
Avg Negative Spread – average negative spread across all trades (only values below 0).
Current Spread – current spread between the assets when a trade is open.
These metrics together allow you to quickly assess how stable the pair is, how the risk/return profile looks, and whether the strategy parameters are suitable for live trading. You can fully customize this results table to fit your workflow:
hide metrics you don’t need, change colors, opacity, and other visual styles, and reorder the focus of the stats according to your trading style.
This way the backtest block can show only the metrics that matter to you most and remain clean and readable during analysis.
📣 ALERTS
The next section is dedicated to alerts.
Here you can configure all signals you need, both for manual trading and for full automation of this pair trading strategy. This block is designed to cover most practical use cases. The indicator supports two alert modes:
Single Alert – one universal custom alert for all events.
Two Alerts – separate alerts for each ticker so you can receive different messages per asset.
Available alert events:
Main Entry – when the main entry is triggered.
Entry 2 – when the first scale-in is executed.
Entry 3 – when the second scale-in is executed.
Entry 4 – when the third scale-in is executed.
Exit Alert – when the position is closed.
StopLoss Alert – when Stop Loss is hit.
TakeProfit Alert – when Take Profit is hit.
All alerts are fully customizable and support a set of placeholders for building structured messages or JSON payloads.
🔹1 Alert Type
List of supported placeholders: {{event}} – trigger name ('Entry 1', 'Exit').
{{dir_1}} – 'Long' or 'Short' for the main ticker.
{{dir_2}} – 'Long' or 'Short' for the other ticker.
{{action_1}} – 'Buy', 'Sell' or 'Close' for the main ticker.
{{action_2}} – 'Buy', 'Sell' or 'Close' for the other ticker.
{{price_1}} – price for the main ticker.
{{price_2}} – price for the other ticker.
{{qty_1}} – order size for the main ticker.
{{qty_2}} – order size for the other ticker.
{{ticker_1}} – main ticker (e.g. 'BTCUSD').
{{ticker_2}} – other ticker (e.g. 'ETHUSD').
{{time}} – candle open time in UTC.
{{timenow}} – signal time in UTC.
🔹2 Alert Type
List of supported placeholders: {{event}} – trigger name ('Entry 1', 'Exit', 'SL', 'TP').
{{action}} – 'Buy', 'Sell' or 'Close'.
{{price}} – order price.
{{qty}} – order size.
{{ticker}} – ticker (e.g. 'BTCUSD').
{{time}} – candle open time in UTC.
{{timenow}} – signal time in UTC. You can use these placeholders to build any JSON structure or custom alert text required by your trading bot, exchange API, or automation service.
In this post I’ve explained how the indicator works, the core concept behind this pair trading strategy, and shown practical examples of trades together with a detailed breakdown of each unique feature inside the tool.
We have invested a lot of work into building this indicator and we truly hope it will help you trade pair strategies more efficiently and more profitably by giving you structured, strategy-specific information that is difficult to obtain in any other way.
⚠️ Please also remember that past performance does not guarantee future results.
Always evaluate the risks, the robustness of your setup, and your own risk tolerance before entering any position, and make independent, well-considered decisions when using this or any other strategy.
UT Bot + SMC PRO (PROP) + VISUAL SIGNALS-DE ALEJANDRO PONCEHOW TO USE THEM TOGETHER (GOLDEN RULE)
Reading Sequence
UT → without B Bounce / pullback
B → without UT Weak break
UT → B (same direction) ✅ Valid setup
UT ↔ Opposite Bs Noise / range
AlgosPoint G&MPoint Breaking 2025 (MB&GB Breaking Point Pro)
What It Does:
A comprehensive TradingView indicator that combines multiple technical analysis tools to identify key market breakout points, support/resistance levels, and trading opportunities. It integrates Volume Profile analysis, AlphaTrend signals, and custom risk assessment metrics.
Key Features:
Volume Profile Analysis: Displays Point of Control (POC), Value Area High/Low (VAH/VAL), and volume distribution
Support & Resistance Detection: Automatically identifies key price levels based on volume or price action
AlphaTrend Signals: Generates BUY/SELL signals with visual labels on chart
Volume Spike Detection: Highlights unusual volume activity indicating potential exhaustion or breakout
High Volatility Alerts: Marks periods of increased market volatility using ATR
Risk Assessment Dashboard: Real-time panel showing:
Long/Short percentages (RSI-based)
Stop levels for both directions
Bot activity percentage
Csocy Signal status (Safe/Undecided/Risky)
How to Use:
Add to Chart: Apply indicator to any timeframe (works best on 15m-4H)
Configure Settings: Adjust parameters in grouped sections:
📊 General Settings (lookback periods)
🎯 Support & Resistance (line styles/colors)
💥 Volume Spike (threshold sensitivity)
⚡ High Volatility (ATR multiplier)
📈 Volume Profile (display options)
🔥 AlphaTrend (signal sensitivity)
Read Signals:
BUY label = Potential long entry when AlphaTrend crosses up
SELL label = Potential short entry when AlphaTrend crosses down
Dashboard colors: Green = bullish, Red = bearish, Yellow = neutral
Set Alerts: Built-in alerts for price crosses, volume spikes, and signal confirmations
Risk Management: Use displayed stop levels and Csocy Signal status to manage position sizing
Best For:
Day traders and swing traders
Crypto, Forex, and Stock markets
Identifying high-probability breakout zones
Volume-based trading strategies
Backtest any Indicator [Target Mode] StrategyUniversal Backtester Strategy with Sequential Logic
This strategy serves as a highly versatile, universal backtesting engine designed to test virtually any indicator-based trading system without requiring custom code for every new idea. It transforms standard indicator comparisons into a robust trading strategy with advanced features like sequential entry steps, dynamic target modes, and automated webhook alerts.
The core philosophy of this script is flexibility. Whether you are testing simple crossovers (e.g., MA Cross) or complex multi-stage setups (e.g., RSI overbought followed by a MACD flip), this tool allows you to configure logic via the settings panel and immediately see backtested results with professional-grade risk management.
Core Logic: Source vs. Target Mode
The fundamental building block of this strategy is the "Comparator" engine. Instead of hard-coding specific indicators, the script allows users to define logic slots (L1-L5 for Longs, S1-S5 for Shorts).
Each slot operates on a flexible comparison logic:
Source: The primary indicator you are testing (e.g., Close Price, RSI, Volume).
Operator: The condition to check (Equal/Cross, Greater Than, Less Than).
Target Mode:
Value Mode: Compares the Source against a fixed number (e.g., RSI > 70).
Source Mode: Compares the Source against another dynamic indicator (e.g., Close > SMA 200).
This "Target Mode" switch allows the strategy to adapt to almost any technical analysis concept, from oscillator levels to moving average trends.
Advanced Entry System: Sequential Steps (1-5)
Unlike standard backtesters that usually require all conditions to happen simultaneously (AND logic), this strategy implements a State Machine for sequential execution. Each of the 5 entry slots (L1-L5 / S1-S5) is assigned a "Step" number.
The logic flows as follows:
Stage 1: The strategy waits for all conditions assigned to "Step 1" to be true.
Latch & Wait: Once Step 1 is met, the strategy "remembers" this and advances to Stage 2. It waits for a subsequent bar to satisfy Step 2 conditions.
Trigger: The actual trade entry is only executed once the highest assigned step is completed.
Example Use Case:
Step 1: Price closes below the Lower Bollinger Band (Dip).
Step 2: RSI crosses back above 30 (Confirmation).
Execution: Buy Signal triggers on the Step 2 confirmation candle.
This creates a realistic "Setup -> Trigger" workflow common in professional trading, preventing premature entries.
Exit Logic & Risk Management
The strategy employs a dual-layer exit system to maximize profit retention and protect capital.
1. Signal-Based Exits (OR Logic) There are 5 configurable exit slots (LX1-LX5 / SX1-SX5). Unlike entries, these operate on "OR" logic. If any enabled exit condition is met (e.g., RSI becomes overbought OR Price crosses below EMA), the position is closed immediately.
2. Hard Stop & Take Profit
Fixed %: Users can set a hard percentage-based Stop Loss and Take Profit.
Trailing Stop: A toggleable "Trailing?" feature allows the Stop Loss to dynamically trail the price.
Longs: The SL moves up as the price makes new highs.
Shorts: The SL moves down as the price makes new lows.
Automated Alerts & Webhooks
This script is built with automation in mind. It includes a dedicated makeJson() function that constructs a JSON payload compatible with most trading bots (e.g., 3Commas, TradersPost, Tealstreet).
Alert Modes Supported: | Alert Type | Description | | :--- | :--- | | Order Fills Only | Triggers standard TradingView strategy alerts when the broker emulator fills an order. | | Alert() Function | Triggers specific JSON payloads defined in the code ("action": "buy", "ticker": "MNQ", etc.). |
The script automatically calculates the alert quantity based on your equity percentage settings, ensuring the payload matches your backtest sizing.
Dashboard & Visuals
To aid in rapid analysis, the strategy includes visual tools directly on the chart:
Performance Table: A dashboard (top-right) displays real-time stats including Net Profit, Win Rate, Profit Factor, and Max Drawdown.
Trade Markers: Custom labels (goLong, exLong) show exactly where trades opened and closed, including the trade number and profit percentage.
SL/TP Visualization: Dynamic step-lines (Orange for SL, Lime for TP) show exactly where your protection levels are sitting, helping you visually verify if your stops are too tight or too loose.
ALFA BUY IndikatorThis indicator is an improved version of the Mucip + Yağız indicator. I have been using it smoothly for the past 3 months.
I use it on futures markets for the three major coins such as BNB/USDT, BTC/USDT, and ETH/USDT.
My usage logic is as follows: on average, it generates around 2 signals per coin per day.
For each trade, I enter positions using 4–5% of my total capital.
I use 25x leverage on ETH and BNB, and 50x leverage on BTC.
My take-profit levels are 0.25% for BTC and 0.5% for the others, which results in approximately 10–12% profit per trade.
Overall, the average daily capital growth is around 2–3%.
Note: I use a trading bot for executions, because the indicator is designed for 2-minute charts, and it is almost impossible to catch the signals manually.
So far, everything has been working flawlessly, and it performs best on 2-minute timeframes.
Vhenom ORB A+ (Professional)Vhenom ORB A+ (Professional)
Advanced Opening Range Breakout System with A+ Momentum & Failure Detection
What This Indicator Is
Vhenom ORB A+ (Professional) is a precision-built Opening Range Breakout system designed for active index futures traders who want early entries, objective confirmation, and protection against false breakouts.
This is not a generic ORB clone.
It is a multi-session, momentum-aware, reversal-aware trading framework built specifically to handle:
Explosive breakouts
Failed breakouts
Intraday continuation
Reversals back into range
Real-time decision-making (not just candle-close hindsight)
Core Philosophy
Most ORB indicators fail because they:
Only work at candle close
Treat all breakouts the same
Ignore volatility context
Provide no framework for failed moves
Vhenom ORB A+ solves all of that.
It does not tell you what to trade.
It tells you when conditions are objectively favorable.
🔹 Key Features
1️⃣ Multi-Session ORB Engine (NY Time)
Define ORBs across multiple intraday windows, not just the cash open:
NY Cash Open (09:30–09:45)
Midday Expansion
Power Hour
Evening Session
Overnight Sessions
Fully customizable ORB windows
Each ORB:
Draws High / Low / Midline in real time
Freezes when complete
Automatically rolls forward into the next session
No repainting of historical ORBs.
2️⃣ Real-Time Breakout Detection (Live Preview)
Unlike most indicators, Vhenom ORB A+ can signal intrabar:
Signals flicker live as price breaks the ORB
Signals confirm on candle close
If price re-enters the range, the signal disappears
This allows:
Earlier entries for aggressive traders
Confirmed entries for conservative traders
You choose.
3️⃣ A+ Momentum Engine (ATR-Based)
Not all breakouts are equal.
The A+ Engine measures candle expansion relative to ATR to identify true momentum breakouts.
When an A+ breakout occurs:
The candle is highlighted
The label upgrades to A+ Buy / A+ Sell
Optional filtering: require A+ for signals or use it as a visual upgrade
This helps eliminate:
Chop
Low-energy fake moves
Weak breakouts that stall immediately
4️⃣ Failure Mode (Reversal Detection)
This is where most ORB tools fall apart.
Vhenom ORB A+ actively monitors failed breakouts.
If price:
Breaks out of the ORB
Fails to hold
Re-enters the range within a defined window
The indicator generates:
R Buy (failed downside breakout)
R Sell (failed upside breakout)
With:
Acceptance-by-close logic
Minimum bar delay (no same-candle chaos)
Optional live preview
This allows traders to:
Capture reversals
Avoid chasing failed breakouts
Trade against trapped participants
5️⃣ Conflict Protection (No Mixed Signals)
The logic explicitly prevents:
Buy and Sell on the same candle
Breakout and reversal on the same bar
Overlapping signal noise
If a conflict ever exists:
Sell wins (conservative bias)
The system is intentionally opinionated to reduce indecision.
6️⃣ Candle Coloring for Immediate Context
Candle colors provide instant visual feedback:
A+ Breakout candles
Failed breakout reversal candles
Priority rules ensure clarity (Reversal > A+)
You can glance at the chart and know what just happened.
🔹 Designed For
This indicator is ideal for:
NQ / ES / MNQ / MES traders
GC / MGC traders
ORB, momentum, and reversal traders
Traders who scale quickly and manage stops tightly
Traders who want structure, not guesses
It works on any symbol or timeframe, but is optimized for index futures.
🔹 What This Is NOT
❌ Not a signal bot
❌ Not a “win every trade” system
❌ Not meant for set-and-forget trading
This tool gives high-quality decision points — execution is up to you.
🔹 Basic vs Professional
Basic Version
NY Cash Session ORB only
ORB lines only
No momentum logic
No reversals
Professional Version (This)
Multiple ORB sessions
Live breakout preview
A+ momentum detection
Failure / reversal detection
Advanced filtering & controls
Designed for real trading, not hindsight
🔹 Final Notes
This indicator was built by a trader, refined through real market behavior, and designed to expose opportunity and risk at the same time.
If you understand:
Opening ranges
Volatility
Acceptance vs rejection
Risk management
Vhenom ORB A+ gives you an edge — not a crutch.
Supfabio Break-Return BandsSupfabio Break-Return Bands (B3 & B4 • 3-Candle Confirmation)
Supfabio Break-Return Bands is a volatility-based price action indicator built on top of a Two-Pole smoothing filter combined with ATR-derived dynamic bands.
It is designed to highlight price exhaustion, rejection, and potential reversal zones, with a strong emphasis on structural confirmation rather than immediate breakouts.
Core Concept
The indicator plots four volatility bands (Band 1 to Band 4) above and below a smoothed Two-Pole filter.
Signals are intentionally restricted to the outer bands, where price behavior is statistically more likely to show:
Volatility expansion
Liquidity grabs (stop runs / false breaks)
Strong rejection or mean-reversion behavior
Signal Logic
Band 4 (Primary Extreme Zone)
BUY and SELL signals are generated when:
Initial trigger (first candle)
Price either crosses the Band 4 level or
Touches and rejects the band (wick / pin behavior)
Confirmation on the 3rd candle (t + 2)
The confirmation candle:
Must not touch the same band again
Must close on the correct side of the band
Confirms that the initial break or pin was rejected
This delayed confirmation helps filter false breakouts and impulsive entries.
Band 3 (Secondary Setup)
On Band 3, signals are intentionally more selective:
Pin / rejection only
No direct cross signals
Uses the same 3-candle confirmation logic
This allows Band 3 signals to act as deeper pullback or early exhaustion setups.
Confirmation Mechanism
The script uses an internal state-based logic to:
Track the exact bar where the trigger occurred
Confirm signals only on the correct third candle
Prevent duplicate or consecutive signals from the same setup
Ensure pin-based triggers are not missed
Visual Elements
Main Two-Pole filter plotted as a thick continuous line
Volatility bands plotted with progressive line thickness
Band line styles (dotted / dashed) can be customized manually in the Style tab
Clear BUY and SELL labels plotted directly on the confirmation candle
Optional candle coloring based on filter direction
Alerts & Automation
Built-in alertcondition() for BUY and SELL
Alerts are suitable for webhook automation
Compatible with external systems and trading bots
Intended Use
This indicator is suitable for:
Reversal and exhaustion analysis
Mean-reversion strategies
Liquidity and rejection-based setups
Manual trading or automated execution
Intraday and higher-timeframe analysis
Notes
This script is intended as an analytical tool, not as a standalone trading system.
Signals should be used in combination with market structure, trend context, and proper risk management.
CCI + Buy/Sell Cross (supfabio)This indicator is an enhanced version of the Commodity Channel Index (CCI) designed to generate clear BUY and SELL signals based on customizable level crossovers, with built-in support for webhook automation and external trade execution.
🔹 Signal Logic
BUY Signal:
Triggered when the CCI crosses upward (from below to above) the user-defined BUY level (red line).
SELL Signal:
Triggered when the CCI crosses downward (from above to below) the user-defined SELL level (green line).
Signals can optionally be configured to trigger only on candle close, reducing real-time noise and false signals.
🔹 Key Features
✅ Original CCI calculation (standard formula preserved)
✅ Fully configurable BUY and SELL levels
✅ Optional display of signal level lines
✅ Visual BUY / SELL markers plotted on the CCI panel
✅ Support for moving average smoothing and Bollinger Bands applied to the CCI
✅ Dynamic alerts using alert(), ideal for:
Webhook integrations
Trading bots
External servers and automated execution systems
🔹 Alerts & Webhook Integration
The indicator sends dynamic alert messages containing:
Action type (BUY / SELL)
Symbol
Closing price
Timestamp
To use:
Add the indicator to your chart
Create an alert and select “Any alert() function call”
Enable Webhook URL and configure your endpoint
Done — signals will be sent automatically
🔹 Best Use Cases
Traders who use CCI as a primary entry trigger
Momentum or mean-reversion strategies
Automated trading systems
Visual backtesting and signal validation
⚠️ Disclaimer
This indicator is not a complete trading system and does not replace proper risk management. Always use it in combination with market context, confirmation tools, and sound position sizing.
Smart Money Bot [MTF Confluence Edition]Uses multi-time frame analysis and supply and demand strategy.
Best used when swing trading.
Star V12⭐ Star Engine — Multi-Component, Multi-Timeframe Trade Execution System
The Star Engine is a stateful trade execution and analytics system designed to transform indicator confluence into structured, measurable trade runs. Rather than producing isolated buy/sell signals, the engine decomposes market behavior into pressure, confirmation, event grouping, and trade lifecycle management. Each component plays a specific role, and no single component is sufficient on its own. Below is a detailed breakdown of each subsystem and why it exists.
💣 Bomb Engine — Directional Pressure Measurement
The Bomb Engine is responsible for identifying directional pressure in the market. It evaluates whether price action exhibits sustained momentum in one direction, independent of whether that direction is immediately tradable.
What Bomb Uses
Bomb aggregates momentum- and trend-oriented inputs such as MACD-based momentum direction, momentum persistence and continuation logic, directional bias filters, and impulse strength evaluation. All inputs are evaluated across multiple timeframes, with each timeframe contributing independently.
How Bomb Works
Each timeframe produces a directional contribution (bullish, bearish, or neutral). Contributions are aggregated into a net Bomb total. The total is mapped into discrete tone buckets (blue, green, red, black, etc.). Higher totals indicate stronger directional dominance.
What Bomb Tells You
Bomb answers one question: Is there directional pressure building or persisting? It does not determine entry timing, exhaustion, or trade quality. Bomb is context, not execution. This allows Bomb to be early without being responsible for precision.
✨ Golden Engine — Structural Confirmation & Regime Filtering
The Golden Engine evaluates whether the directional pressure detected by Bomb is structurally supported. Golden exists to prevent entries during momentum exhaustion, conflicting timeframe regimes, and counter-structure moves.
What Golden Uses
Golden relies on a different indicator stack than Bomb, focused on confirmation and balance, including RSI regime classification (not simple overbought/oversold), momentum agreement vs divergence, trend-following vs counter-trend positioning, overextension detection, and compression and rotational behavior. Each timeframe is evaluated independently using the same logic.
The Role of RSI in Golden
RSI in Golden is used to identify regimes, not signals. It answers questions such as: Is momentum expanding or decaying? Is the move early, mid-structure, or extended? Do multiple timeframes share compatible RSI states? If RSI regimes conflict across timeframes, Golden will not confirm. This is one of the main mechanisms that makes Golden selective.
Momentum & Alignment Logic
Golden evaluates whether momentum supports continuation, is fragmenting, is diverging from price, or is contradicting higher-timeframe structure. If lower-timeframe impulses are not supported by higher-timeframe structure, Golden suppresses confirmation — even if Bomb remains strong.
What Golden Guarantees
Golden does not guarantee profitable trades. Golden guarantees that the detected directional pressure is not internally contradictory across RSI regimes, momentum behavior, and timeframe structure. This replaces vague terms like “clean” with explicit structural conditions.
🔗 Multi-Timeframe Aggregation (MTF)
Both Bomb and Golden operate on a multi-timeframe voting system. Lower timeframes capture early impulses, higher timeframes enforce structural context, each timeframe votes independently, conflicts weaken totals, and alignment strengthens totals. This creates temporal confluence, not just price-based confluence.
⭐ Star Events — Qualified Market Impulses
A Star (⭐) is created only when Bomb is active, Golden is active, both agree on direction, and all gating rules pass (thresholds, time filters, modes). A Star represents a qualified impulse, not a trade. Stars are atomic events used by the execution layer.
⏱ Star Clusters — Trade Run State
The Star Cluster groups Stars into runs. The first Star starts a cluster, anchor price, bar, and time are recorded, each additional Star increments the cluster count, and all Stars belong to the same run until exit. This prevents duplicate entries, signal spam, and overtrading in volatile conditions.
⛔ Reset Gap Logic — Temporal Control
To prevent rapid re-entry, a minimum time gap is required to start a new run. Stars occurring too close together are merged. Reset does not terminate active runs. This enforces time-based discipline, not indicator-based guessing.
1➡️ Entry Logic — Confirmation-Based Execution
The engine never enters on the first Star. Instead, the user defines 🔢 N (Entry Star Index). Entry occurs only on the Nth Star, and that bar is marked 1➡️🔢N. This ensures entries occur after persistence, not detection. At ENTRY, Best = 0.00 and Worst = 0.00. Statistics measure real trade performance, not early signal noise.
📊 STAT Engine — Live Trade Measurement
Once entry is active, the STAT engine tracks ⏱ run progression, 🏅 maximum favorable excursion, and 📉 maximum adverse excursion. Mechanics: uses highs and lows, not closes; updates every bar; entry bar resets stats; historical bars marked 🎨. This creates an objective performance envelope for every trade.
🛑 Exit Engine — Deterministic Outcomes
Trades are exited using explicit rules: 🏅 WIN → profit threshold reached, 📉 LOSE → risk threshold breached, ⏱ QUIT → structural or safety exit.
Safety Exits
🐢 Idle Stop — no Stars for N bars.
🧯 Freeze Failsafe — STAT inactivity.
QUIT is a controlled termination, not failure. Each exit is recorded with a short cause tag.
🧾 Trade Memory & Journaling
Every trade produces immutable records. Entry: time, price, side, confirmation index. Exit: time, price, PnL, result, cause. These records power tables, alerts, JSON output, and external automation.
📊 Time-Block Performance (NY Clock)
Performance is grouped by real time, not bar count. Rolling NY blocks (e.g. 3 hours). Independent statistics per block. Live trades persist across block boundaries. This enables session-based analysis.
🔔 Alerts & Automation
Alerts are state-based: Entry confirmed → Long / Short alert. Trade closed → Exit alert. Optional JSON output allows integration with bots, journals, and dashboards.
Summary
The Star Engine is a component-based trade execution system, where Bomb measures pressure, Golden validates structure, Stars qualify impulses, clusters define runs, entry is delayed by confirmation, stats measure reality, exits are deterministic, and results are time-aware. It is not designed to “predict the market”, but to control how trades are formed, managed, and evaluated.
Kairos QX Indicator [v1.7]What’s New in v1.7?
Streak Analytics (Dashboard Expansion):
The dashboard now tracks Winning and Losing Streaks.
Max Consec. (TP / SL): Displays the highest number of wins and losses that occurred in a row (e.g., 5 / 3).
Avg Consec. (TP / SL): Calculates the average length of your winning and losing streaks (e.g., 2.4 / 1.8).
Updated Default "settings" for MNQ 5 MIN Candles
Full Script Description
This script is a professional-grade Mean Reversion & Trend Following Engine designed for automated execution. It acts as a bridge between discretionary chart analysis and algorithmic trading, allowing you to backtest complex ideas visually and then automate them via alerts without writing code.
1. Core Logic: The "Flip Switch" Strategy
Standard Mode (Mean Reversion):
The script identifies "exhaustion" points where price pierces the Bollinger Bands.
It bets on a reversal (e.g., Price > Upper Band = Short).
Inverse Mode (Trend Following - Default):
With the "Inverse Trades" box checked, the logic flips.
It identifies "breakout" points where price pierces the bands.
It bets on continuation (e.g., Price > Upper Band = Long).
2. Advanced Automation & Safety Features
This system is built to drive trading bots (like TradersPost or 3Commas) safely:
State-Aware Execution: It tracks its own trades (in_trade state). It will never fire a duplicate "Open" signal if a trade is already active, preventing accidental pyramiding.
No Trade Zone (Force Close): You can define a specific time window (default 15:10–17:00). If a trade is open when this time hits, the script immediately triggers a Close Alert, preventing overnight holds.
Signal Cooldown: Configurable "Signals to Skip" allows you to force a cooldown period after a trade closes to avoid over-trading in choppy conditions.
3. Real-Time Analytics Dashboard
The on-chart table provides a transparent, real-time backtest of your settings:
Equity Calculator: You can set a dollar value per point (e.g., $2 for MNQ). The dashboard calculates your estimated Net Profit/Loss based on the total points gained.
Streak Analysis: Shows both the Maximum and Average number of consecutive wins and losses, helping you understand the psychological difficulty of trading the strategy.
Data Integrity: It automatically detects "N/A" trades (candles that hit both SL and TP) and excludes them from the Win Rate calculation to ensure realistic statistics.
4. Modular "Recipe" Building
The strategy is highly customizable via the settings menu (no coding required). You can filter the Bollinger Band trigger with 10 different indicators:
Supported Filters: RSI, Stochastic, CCI, Williams %R, MFI, CMO, Fisher Transform, Ultimate Oscillator, and ROC.
Logic: All selected filters must agree with the main trigger for a trade to fire.
5. Visual Projection Engine
Glowing Outcomes: The script draws exact TP (Green) and SL (Red) boxes for past trades. These boxes glow to indicate the result, allowing for rapid visual verification of the strategy's performance.
Force Close Markers: Special gray markers appear on the chart where a trade was forced to close due to the "No Trade Zone" time limit.
Kairos QX Indicator [v1.6]This script, Kairos QX , is a sophisticated, highly customizable trading engine designed for automated execution. It serves as a bridge between discretionary charting and algorithmic trading, allowing you to visually backtest complex ideas and then automate them via alerts.
Its core logic is built on Mean Reversion, but it features a powerful "Inverse Mode" that instantly transforms it into a Trend Following system.
1. The Core Strategy: Mean Reversion (Default)
By default, the script operates on the principle that price eventually returns to an average value after an extreme move.
Logic: It fades the move.
Short Signal: Price pierces the Upper Bollinger Band (overbought) + optional confluence filters (e.g., RSI > 70). The bet is that price will revert down.
Long Signal: Price pierces the Lower Bollinger Band (oversold) + optional confluence filters. The bet is that price will revert up.
2. The "Inverse Mode": Trend Following (Flip Switch)
The script includes a unique Inverse Trades checkbox that flips the entire logic engine. This allows you to adapt to market conditions where price isn't reverting but is instead "running" hard.
Logic: It rides the breakout.
Short Signal becomes Long: When price pierces the Upper Bollinger Band, instead of shorting (expecting a drop), the script enters Long (expecting the trend to blast through and continue higher).
Long Signal becomes Short: When price pierces the Lower Bollinger Band, the script enters Short, betting on a trend continuation downward.
Why this matters: If your backtest shows a failing Mean Reversion strategy (e.g., a "F" grade), flipping this switch can instantly invert those losses into wins by aligning with the trend instead of fighting it.
3. Built for Automation & Safety
The script is engineered to safely drive third-party auto-trading bots (like TradersPost, 3Commas, or PineConnector) without manual intervention.
State-Aware Execution: The script tracks its own trade state. It will never fire a duplicate "Open" signal if a trade is already active, preventing accidental double-entries.
No Trade Zone (Force Close): You can set a specific time window (e.g., 15:55 PM) where the script automatically triggers a Close Alert for any open position. This protects you from holding day trades overnight or through major news events.
Signal Cooldown: To prevent over-trading in choppy markets, you can set the script to ignore the next 1-5 signals after a trade finishes, forcing it to wait for a fresh setup.
4. Modular "Recipe" Building
You don't need to know code to change the strategy. The settings menu allows you to mix and match 10 different indicators as confluence filters.
Example Recipe: "Only take a Mean Reversion Long if: Price is below the Bollinger Band AND RSI is < 30 AND MFI is < 20."
If you check the boxes, the script enforces the rules. If you uncheck them, they are ignored.
5. Visual Projection Dashboard
The script doesn't just print arrows; it performs a real-time visual backtest on the chart.
Glowing Projections: It draws the exact Take Profit (Green) and Stop Loss (Red) boxes for historical trades. These boxes glow to indicate if the trade won or lost.
Data Integrity: It automatically detects and isolates "N/A" trades—candles so volatile that they hit both your SL and TP in the same bar—excluding them from your win rate to keep your data realistic.
Live Grading: A dashboard in the corner grades your current settings (A-F) based on their performance over the last 1,000 to 40,000 bars.
Vega Convexity Regime Filter [Institutional Lite]STOP TRADING THE NOISE.
90% of retail trading losses occur during "Chop"—sideways markets where standard trend-following bots bleed capital through slippage and fees. Institutional desks know that the secret to high returns isn't just winning trades; it's knowing when to sit in cash.
The Vega V6 Regime Filter is the "Gatekeeper" layer of our proprietary Hierarchical Machine Learning engine (developed by a 25-year TradFi Risk Quant). It calculates a composite volatility score to answer one simple question: Is this asset tradeable right now?
THE VISUAL LOGIC
This indicator visually filters market conditions into two distinct Regimes based on our institutional backtests:
🌫️ GREY BARS (Noise / Chop)
The State: Volatility is compressing. The trend is undefined or weak.
The Trap: This is where MACD/RSI give false signals.
Institutional Action: Sit in Cash. Preserve Capital. Wait.
🟢 🔴 COLORED BARS (Impulse)
The State: Volatility is expanding. Momentum is statistically significant.
The Opportunity: A "Fat-Tail" move is likely beginning.
Institutional Action: Deploy Risk. Look for entries.
HOW IT WORKS (The Math)
Unlike simple moving average crossovers, the Vega Gatekeeper analyzes 4 distinct market dimensions simultaneously to generate a Tradeability Score (0-10) :
Trend Strength (ADX): Is there a vector?
Momentum (RSI/MACD): Is the move accelerating?
Volatility (Bollinger Bands): Is the range expanding?
Volume Flow: Is there institutional participation?
The Rule: If the composite score is < 4 , the market is Noise. The bars turn Grey. You do nothing.
BEST PRACTICES
For Swing Trading (Daily): Use Medium sensitivity. Only look for entries when the background turns Green/Red.
For Day Trading (4H/1H): Use Low sensitivity (more conservative). Use the Grey zones to tighten stops or exit positions.
THE PHILOSOPHY: "CASH IS A POSITION"
Most traders feel the need to be in a trade 24/7. The Vega V6 Engine (the system this tool is based on) achieved a +3,849% backtested return (18 months) largely by sitting in cash during chop. This tool visualizes that discipline.
🔒 WANT THE DIRECTIONAL SIGNALS?
This Lite version provides the Regime (When to trade).
To get the specific Entry Signals , Intraday Stop-Losses , and Probability Matrix (Stage 2 of our model), you need the Vega V6 Convexity Engine .
The Pro Version includes:
🚀 Specific Direction: Classification of "Explosion," "Rally," or "Crash."
🛡️ Dynamic Risk: Plots the exact Stop Loss levels used in our institutional backtests.
🌊 Macro Data: Integration of M2 Liquidity flow alerts.
👉 ACCESS INSTRUCTIONS:
Links to the Pro System , our Live Dashboard , and the 18-Month Performance Audit can be found in the Author Profile below or in the script settings.
Disclaimer: This tool is for educational purposes only. Past performance is not indicative of future results. Trading cryptocurrencies involves significant risk.
AlgoZ Pro v2.4.3 [LITE] - Adaptive Trend SystemOverview
AlgoZ Pro v2.4.3 is a high-precision trend-following system designed to filter market noise and keep you on the right side of the trend. Built on an advanced ATR-adaptive engine, this indicator dynamically adjusts its sensitivity to market volatility, providing clear entries and trailing stop-loss levels for Scalpers and Day Traders.
How It Works
The system uses a volatility-based "Trailing Cloud" to identify the dominant trend.
Green Cloud: Bullish Trend (Look for Longs)
Red Cloud: Bearish Trend (Look for Shorts)
Labels:
Clear BUY/SELL text labels appear when the trend flips, confirmed by volatility expansion.
Lite Features (Included)
Adaptive Trend Cloud: Visualizes the trend direction instantly.
Smart Trailing Stops: The trend line acts as a dynamic stop-loss level.
Signal Labels: Clean Buy/Sell markers on chart.
Multi-Timeframe Logic: Optimized for 5m, 15m, and 4H timeframes.
UNLOCK THE FULL SUITE (PRO v2.4.3)
This script is the "Lite" version of the complete AlgoZ Pro system. By upgrading to the full source code version, you unlock the institutional toolkit used by professional traders:
1. 🏦 Smart Money Range (SMR) Zones Automatically draws institutional Support & Resistance zones based on Donchian liquidity levels. Stop guessing where price will bounce.
2. 📊 Volume Divergence System Detects hidden reversals before they happen by analyzing volume/price disagreements.
3. 🛡️ "Strict Mode" Filters Includes our proprietary "Anti-Spam" filter that uses MFI, RSI, and Candle Color logic to eliminate false signals during choppy markets.
4. 📈 Built-in Backtester See the real-time Win Rate, Profit Factor, and Drawdown directly on your chart. Know the math before you trade.
5. 💎 100% Source Code Ownership Get the complete Pine Script code. Modify the logic, build your own bot, and own the system forever with no monthly fees.
👉 Get the PRO Source Code & SMR Zones here: www.algozpro.com
Impulse Day PlanOverview
This script provides a structured intraday trade plan built on three interacting components:
Impulse-based TP/SL system
Detects trend bias shifts and automatically generates Entry, TP1–TP3 and SL based on impulse range projections. Targets update dynamically and wick-touch confirmation is used for accurate ✓ tracking.
ATR day zones
A blended ATR model (Daily + selected base timeframe) produces support, balance and resistance zones derived from the previous session close. These zones provide directional context and realistic intraday expansion boundaries.
VWAP/EMA trend filter
Trend confirmation is applied using VWAP and EMA 50/200 structure. Signals are only considered aligned when price, VWAP and EMA trend agree.
The script displays a compact dashboard with the active trade plan, including:
Entry
TP1, TP2, TP3
Stop Loss
Checkmarks showing completed targets
This makes the indicator a planning framework, not a simple overlay.
How it differs from my previous publications
I previously released:
Smart Money OB + Limit Orders + Priority
SM OB Intraday Bot Assistant
Impulse TP/SL Zones
Those scripts focus on isolated concepts such as Smart Money structure, intraday automation or basic impulse mapping.
This script introduces a new integrated workflow: impulse TP/SL logic, ATR day zones and VWAP/EMA trend confirmation operating together as a single system. It does not reproduce the functionality of my previous tools and is designed as a standalone intraday planning method.
How to use
Select a base timeframe for the ATR zone model (15m, 1H, 4H).
Follow the dashboard for entry, targets and SL.
Use ATR zones to understand where targets sit within the day’s expected range.
Execute trades only when impulse signal and VWAP/EMA trend align.
RSI Dip Reversal Pro ScannerRSI Upside Reversal Scanner (High Accuracy)
This indicator is designed to detect early-stage upside reversals by identifying when RSI crosses upward from oversold levels while the price remains positioned in the lower portion of its recent range. It combines momentum shift with price location analysis to produce highly reliable reversal signals.
It uses 3 primary filters:
RSI Oversold Cross:
RSI must cross upward from the oversold threshold (default 30).
Price in Bottom Range:
Price must be located within the lower 40% of the last 20-bar range, indicating a discount zone.
Overbought Protection:
RSI must stay below the ceiling level (default 75) to prevent signals near top exhaustion.
When all criteria are met, the indicator plots a “GİRİŞ” (ENTRY) label below the candle.
This tool is ideal for:
Identifying accurate dip-buy zones
Capturing trend reversals early
Optimizing swing and scalp entries
Feeding systematic trading models or bots
It performs well on short- and mid-term timeframes.
Volume Analysis🙏🏻 (signed) Volume Analysis is 2 of 2 structural layer / ordeflow analysis scripts, while the first one is Liquidity Analysis. Both are independent so can’t be released together as a single script, but should be used together.
The same math used in this script can be applied to other types of aggressive volume data: non-aggregated flow of market orders, volume traded of put vs call options.
There’s no universal agreement about terminology, but this script works with volumes signed by the aggressor who initiated a transaction. Then these volumes get aggregated by time and a cumulative sum is calculated. Mostly this is widely known as Cumulative Volume Delta.
However this script works with 'inferred' volumes vs the provided ones. It’s the better choice for equities, bonds; neutral choice for currencies; and suboptimal choice for natural and artificial commodities.
Contents:
Output description;
How to analyze & use the outputs;
How to use it together with Liquidity Analysis script;
How did I use both scripts to finish The Leap profitably and skipped many losses.
1. Output description
Color of the CVD line reflects (signed) volume imbalance state: red is negative, purple is neutral, blue is positive.
3 purple lines are lower deviation (lower band), basis (middle band), upper deviation (upper band): used to generate signals by a ruleset that would be explained in a minute
Gray number in the script’s status line is the advised input you may put into Inferred volume multiplier in script’s setting, I will explain it
Vertical dash line marks the moving window end, this way you can be certain over what exact data you see the profile was built.
2. How to analyze & use the outputs
Setup up the script:
Moving window length: set it to ~ ¼ of your data analysis window. E.g if you see on your charts and use ~ 256 bars, set the length to 64.
Inferred volume multiplier: you can easily leave it 256, this is not a critical factor for the math, it’s mostly there if you want to ~ equate inferred volumes with real ones in scale. For this, use the gray number in the script status line, it’s calculated as ratio of long term real volumes weighted avg to long term inferred volumes weighted avg.
Again, changing the inferred volume multiplier won’t affect the math.
Use 2 timeframes: main one and a far lower one 3 steps down, just like on the screenshot.
Find out current volume imbalance state:
As mentioned before, based on CVD line color, it can be negative, neutral or positive. This is the state variable that changes slowly and denies/confirms the signals generated by crossovers of CVD line and 3 purple thresholds.
For this I use my own very fast and lightweight metric that is totally statistically grounded, utilizes temporal information, and calculates volume imbalance without using heavy math like regressions as it’s usually done. It also provides a natural neutral zone, when volume imbalance is not strong enough to be confirmed.
...
CVD-based signals:
First you need to understand what precisely a touch of a threshold is:
Touch: an event when either of these 2 happens:
One CVD datapoint is above the threshold, and the next CVD datapoint is below the threshold
One CVD datapoint is below the threshold, and the next CVD datapoint is above the threshold
These are usually called crossovers/crossunders.
Now with the 3 purple thresholds we follow this logic:
Monitor the last touched threshold;
Once another threshold is touched, here we may generate a signal but only once !, after the first generated signal at that threshold we can’t generate more signals on this threshold, we need to wait when CVD comes to another threshold.
If CVD touches one threshold, and then goes down and touches another threshold downwards, we wait when CVD makes a datapoint above this threshold. When it happens, we register a long signal
If CVD touches one threshold, and then goes up and touches another threshold upwards, we wait when CVD makes a datapoint below this threshold. When it happens, we register a short signal
However, don’t open new trades against the current volume imbalance state. So don’t open shorts when the CDV line is blue, and don’t open longs when CVD line is red.
Btw, this technique I call it “reclaim” of a level/threshold. It can be applied to horizontal levels, and it’s very powerful especially when you fade levels on very volatility assets like BTC. This technique allows you to Not fade a level straight away, but wait when price goes past the level a bit, and then comes back and reclaims it, only there you enter, and moreover you now have a very well defined risk point.
The last part is multi-timeframe logic. Prefer to act when a lower timeframe is Not against the main timeframe. That’s all, no multiple higher timeframes are needed.
3. How to use it together with Liquidity Analysis script.
That script also has a mean to generate its own signals, and another state variable called Liquidity Imbalance.
So now you’re not only looking at volume imbalance but also at liquidity imbalance that would deny/confirm the CVD based signal. You need at least one of these two to favor your long or short.
This is the same logic widely used in HFT, where MM bots cancel/shift/resize orders when book is too onesided And ordeflow is one sided as well.
4. How did I use both scripts to finish The Leap profitably and skipped many losses.
Even tho you can use structural information as your main strategic layer, as many so-called orderflow traders do, I traded in objective style: my fade signals were volatility based in essence, and I used ordeflow for better entries and stops, but most importantly to skip losses.
When ‘both‘ liquidity imbalance and volume imbalance (in their main timeframes) were against my trades, I skipped them all, saving many ~$500 stop losses (that was my basis risk unit for the Leap). Unless I had a very strong objective signal, i.e. confluence of several signals, or just one higher timeframe signal, I did all these skips.
I traded ~ intraweek timeframe, so I was analyzing either the last 230 30min bars or 1380 5min bars. Both Liquidity Analysis and (signed) Volume Analysis scripts were set to moving window length 46 or 276 for either granularity.
I finished the leap with 9% profit and max DD ~ 5%, a bit short of my goal of 12.5%. If not these 2 scripts I would’ve finished a bit above breakeven I think.
,,,
Another thing, I made these 2 scripts invite-only because they are made particularly for trading, particularly for certain types of market data. These are tools adapted for particular use case, not like my other posts with general math entities like Kernel Density Estimation or Kalman filter, that you can take and apply properly on any data you need yourself.
However these are made from general math entities like everything else. ‘All’ the components are available in my other scripts, ideas, and other sources related to me. If you want to reverse-engineer these, you can find all the components you need in my already posted open source work.
∞
Liquidity Analysis🙏🏻 Liquidity Analysis is 1 of 2 structural layer / orderflow layer analysis scripts. Both are independent so can’t be released together as a single script, but should be used together. The second one which is called (Signed) Volume Analysis is incoming.
The same math used in this script can be applied on other types of profile-like data: orderbooks, trading volumes of all options for each strike.
Important: market or volume profile, just as orderbooks and options traded volume by strikes, are all liquidity ‘estimates’, showing where liquidity is more likely or less likely to be. These estimates however, especially combined with other info, are really useful and reliable.
This script works with inferred volumes vs the provided one. It's the better choice for equities, bonds; neutral choice for currencies; and suboptimal choice for natural & artificial commodities.
Contents:
Output description;
How to analyze & use the outputs;
How to use it together with upcoming (Signed) Volume Analysis script;
How did I use both scripts to finish The Leap profitably and skipped many losses.
1. Output description
Color of the profile reflects the liquidity imbalance state: red is negative, purple is neutral, blue is positive.
Bar coloring represents history values of liquidity imbalance for backtesting purposes. It can be turned on/off in the script's Style settings.
Two purple vertical lines represent calculated borders of excessive liquidity (HVN), scarce liquidity (LVN), and sufficient liquidity (NVN) zones.
Vertical dash line marks the moving window end, this way you can be certain over what exact data you see the profile was built.
2. How to analyze & use the outputs
Setup up the script:
Moving window length: set it to ~ ¼ of your data analysis window. E.g if you see on your charts and use ~ 256 bars, set the length to 64.
Native tick size multiplier: leave it at 0 to calculate optimal number of rows automatically, or set it manually to match native tick size multiples you desire.
Use 2 timeframes: main one and a far lower one 3 steps down, just like on the screenshot.
Native lot size multiplier allows to round profile rows themselves to nearest multiples of native lot size. I added this just in case any1 needs it.
Find out current liquidity imbalance state:
As mentioned before, based on profile color, it can be negative, neutral or positive. This is the state variable that changes slowly and denies/confirms the signals that would be explained in the minute.
I use my own statistically grounded imbalance metric (no hardcoded/learned thresholds), that unlike mainstream imbalance metrics (e.g orderbook imbalance as sum of bids vs sum of asks) provides a natural neutral zone, when liquidity imbalance is ofc there but not strong enough to be considered.
…
Profile-based signals: look at profile shape vs 2 vertical purple lines.
where profile rows exceed the left purple line, these prices are considered HVN. Too much potential liquidity is there.
where profile rows don’t exceed the right purple line, these prices are considered LVN. Potential thin/lack of liquidity is expected there.
where profile rows are in between these 2 purple lines, these are NVN, or neutral liquidity zones.
Trading ruleset itself is based on couple of simple rules:
Only! Use limit orders hence provide liquidity in LVNs and Only! use stop-market orders hence consume liquidity in HVNs;
These orders should be put in advance ‘only’. This is how you discover the direction or orders: you can only put sell limit orders above you and buy limit orders below you, and you can only put buy stop orders above you, and sell stop orders below you.
This is really it. It may look weird, but once you just try to follow these 2 rules letter by letter for 1 hour, you’ll see how liquidity trading works.
Now once you know that, just don’t open new trades against the liquidity imbalance state. So don’t open shorts when the profile is blue, and don’t open longs when it’s red.
The last part is multi-timeframe logic. Prefer to act when a lower timeframe is Not against the main timeframe. That’s all, no multiple higher timeframes are needed.
3. How to use it together with upcoming (Signed) Volume Analysis script.
That upcoming script would also have a mean to generate its own signals, and another state variable called volume imbalance.
So now you’re not only looking at liquidity imbalance but also at volume imbalance that would deny/confirm a profile based signal. You need at least one of these to favor your long or short.
This is the same logic widely used in HFT, where MM bots cancel/shift/resize orders when book is too onesided And ordeflow is one sided as well.
4. How did I use both scripts to finish The Leap profitably and skipped many losses.
Even tho you can use structural information as your main strategic layer, as many so-called orderflow traders do, I traded in objective style: my fade signals were volatility based in essence, and I used ordeflow for better entries and stops, but most importantly to skip losses.
When ‘both‘ liquidity imbalance and volume imbalance (in their main timeframes) were against my trades, I skipped them all, saving many ~$500 stop losses (that was my basis risk unit for the Leap). Unless I had a very strong objective signal, i.e confluence of several signals, or just one higher timeframe signal, I did all these skips.
I traded ~ intraweek timeframe, so I was analyzing either the last 230 30min bars or 1380 5min bars. Both Liquidity Analysis and (signed) Volume Analysis scripts were set to moving window length 46 or 276 for either granulary.
I finished the leap with 9% profit and max DD ~ 5%, a bit short of my goal of 12.5%. If not these 2 scripts I would’ve finished a bit above breakeven I think.
∞
