VFI - Volume Flow Indicator [UTS]The Volume Flow Indicator (VFI) indicator was first introduced in my June 2004 and is is based on the popular On Balance Volume (OBV) but with three very important modifications:
Unlike the OBV, indicator values are no longer meaningless. Positive readings are bullish and negative bearish.
The calculation is based on the day's median instead of the closing price.
A volatility threshold takes into account minimal price changes and another threshold eliminates excessive volume.
The indicator takes into account only the latest 6 month volume action and not the entire data loaded in the chart.
General Usage
A simplified interpretation of the VFI is that values above zero indicate a bullish state and the crossing of the zero line is the trigger or buy signal.
The strongest signal with all money flow indicators is of course divergence.
The classic form of divergence is when the indicator refuses to follow the price action and makes lower highs while price makes higher highs (negative divergence). If price reaches a new low but the indicator fails to do so, then price probably traveled lower than it should have. In this instance, you have positive divergence.
Default settings
130 VFI Length
0.2 Coef
2.5 Volume cutoff
3 Smoothing Period
Further setting examples can be found on www.precisiontradingsystems.com
Trend Visualisation
Optional Setting:
If the trend direction is DOWN the moving average is painted red. If the trend direction is UP the moving average is painted in green.
If the movement is FLAT then the color is grey.
Moving Averages
4 different types of Moving Averages are available for both FVI and the optional Moving Average of the FVI.
ALMA (Arnaud Legoux Moving Average)
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
WMA (Weighted Moving Average)
Notes
This indicator is using the exact formula from mkatsanos.com where EMA has been taken as default value for FVI smoothing calculation.
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Backtesting & Trading Engine [PineCoders]The PineCoders Backtesting and Trading Engine is a sophisticated framework with hybrid code that can run as a study to generate alerts for automated or discretionary trading while simultaneously providing backtest results. It can also easily be converted to a TradingView strategy in order to run TV backtesting. The Engine comes with many built-in strats for entries, filters, stops and exits, but you can also add you own.
If, like any self-respecting strategy modeler should, you spend a reasonable amount of time constantly researching new strategies and tinkering, our hope is that the Engine will become your inseparable go-to tool to test the validity of your creations, as once your tests are conclusive, you will be able to run this code as a study to generate the alerts required to put it in real-world use, whether for discretionary trading or to interface with an execution bot/app. You may also find the backtesting results the Engine produces in study mode enough for your needs and spend most of your time there, only occasionally converting to strategy mode in order to backtest using TV backtesting.
As you will quickly grasp when you bring up this script’s Settings, this is a complex tool. While you will be able to see results very quickly by just putting it on a chart and using its built-in strategies, in order to reap the full benefits of the PineCoders Engine, you will need to invest the time required to understand the subtleties involved in putting all its potential into play.
Disclaimer: use the Engine at your own risk.
Before we delve in more detail, here’s a bird’s eye view of the Engine’s features:
More than 40 built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
By combining your own strats to the built-in strats supplied with the Engine, and then tuning the numerous options and parameters in the Inputs dialog box, you will be able to play what-if scenarios from an infinite number of permutations.
USE CASES
You have written an indicator that provides an entry strat but it’s missing other components like a filter and a stop strategy. You add a plot in your indicator that respects the Engine’s External Signal Protocol, connect it to the Engine by simply selecting your indicator’s plot name in the Engine’s Settings/Inputs and then run tests on different combinations of entry stops, in-trade stops and profit taking strats to find out which one produces the best results with your entry strat.
You are building a complex strategy that you will want to run as an indicator generating alerts to be sent to a third-party execution bot. You insert your code in the Engine’s modules and leverage its trade management code to quickly move your strategy into production.
You have many different filters and want to explore results using them separately or in combination. Integrate the filter code in the Engine and run through different permutations or hook up your filtering through the external input and control your filter combos from your indicator.
You are tweaking the parameters of your entry, filter or stop strat. You integrate it in the Engine and evaluate its performance using the Engine’s statistics.
You always wondered what results a random entry strat would yield on your markets. You use the Engine’s built-in random entry strat and test it using different combinations of filters, stop and exit strats.
You want to evaluate the impact of fees and slippage on your strategy. You use the Engine’s inputs to play with different values and get immediate feedback in the detailed numbers provided in the Data Window.
You just want to inspect the individual trades your strategy generates. You include it in the Engine and then inspect trades visually on your charts, looking at the numbers in the Data Window as you move your cursor around.
You have never written a production-grade strategy and you want to learn how. Inspect the code in the Engine; you will find essential components typical of what is being used in actual trading systems.
You have run your system for a while and have compiled actual slippage information and your broker/exchange has updated his fees schedule. You enter the information in the Engine and run it on your markets to see the impact this has on your results.
FEATURES
Before going into the detail of the Inputs and the Data Window numbers, here’s a more detailed overview of the Engine’s features.
Built-in strats
The engine comes with more than 40 pre-coded strategies for the following standard system components:
Entries,
Filters,
Entry stops,
2 stage in-trade stops with kick-in rules,
Pyramiding rules,
Hard exits.
While some of the filter and stop strats provided may be useful in production-quality systems, you will not devise crazy profit-generating systems using only the entry strats supplied; that part is still up to you, as will be finding the elusive combination of components that makes winning systems. The Engine will, however, provide you with a solid foundation where all the trade management nitty-gritty is handled for you. By binding your custom strats to the Engine, you will be able to build reliable systems of the best quality currently allowed on the TV platform.
On-chart trade information
As you move over the bars in a trade, you will see trade numbers in the Data Window change at each bar. The engine calculates the P&L at every bar, including slippage and fees that would be incurred were the trade exited at that bar’s close. If the trade includes pyramided entries, those will be taken into account as well, although for those, final fees and slippage are only calculated at the trade’s exit.
You can also see on-chart markers for the entry level, stop positions, in-trade special events and entries/exits (you will want to disable these when using the Engine in strategy mode to see TV backtesting results).
Customization
You can couple your own strats to the Engine in two ways:
1. By inserting your own code in the Engine’s different modules. The modular design should enable you to do so with minimal effort by following the instructions in the code.
2. By linking an external indicator to the engine. After making the proper selections in the engine’s Settings and providing values respecting the engine’s protocol, your external indicator can, when the Engine is used in Indicator mode only:
Tell the engine when to enter long or short trades, but let the engine’s in-trade stop and exit strats manage the exits,
Signal both entries and exits,
Provide an entry stop along with your entry signal,
Filter other entry signals generated by any of the engine’s entry strats.
Conversion from strategy to study
TradingView strategies are required to backtest using the TradingView backtesting feature, but if you want to generate alerts with your script, whether for automated trading or just to trigger alerts that you will use in discretionary trading, your code has to run as a study since, for the time being, strategies can’t generate alerts. From hereon we will use indicator as a synonym for study.
Unless you want to maintain two code bases, you will need hybrid code that easily flips between strategy and indicator modes, and your code will need to restrict its use of strategy() calls and their arguments if it’s going to be able to run both as an indicator and a strategy using the same trade logic. That’s one of the benefits of using this Engine. Once you will have entered your own strats in the Engine, it will be a matter of commenting/uncommenting only four lines of code to flip between indicator and strategy modes in a matter of seconds.
Additionally, even when running in Indicator mode, the Engine will still provide you with precious numbers on your individual trades and global results, some of which are not available with normal TradingView backtesting.
Post-Exit Analysis for alternate outcomes (PEA)
While typical backtesting shows results of trade outcomes, PEA focuses on what could have happened after the exit. The intention is to help traders get an idea of the opportunity/risk in the bars following the trade in order to evaluate if their exit strategies are too aggressive or conservative.
After a trade is exited, the Engine’s PEA module continues analyzing outcomes for a user-defined quantity of bars. It identifies the maximum opportunity and risk available in that space, and calculates the drawdown required to reach the highest opportunity level post-exit, while recording the number of bars to that point.
Typically, if you can’t find opportunity greater than 1X past your trade using a few different reasonable lengths of PEA, your strategy is doing pretty good at capturing opportunity. Remember that 100% of opportunity is never capturable. If, however, PEA was finding post-trade maximum opportunity of 3 or 4X with average drawdowns of 0.3 to those areas, this could be a clue revealing your system is exiting trades prematurely. To analyze PEA numbers, you can uncomment complete sets of plots in the Plot module to reveal detailed global and individual PEA numbers.
Statistics
The Engine provides stats on your trades that TV backtesting does not provide, such as:
Average Profitability Per Trade (APPT), aka statistical expectancy, a crucial value.
APPT per bar,
Average stop size,
Traded volume .
It also shows you on a trade-by-trade basis, on-going individual trade results and data.
In-trade events
In-trade events can plot reminders and trigger alerts when they occur. The built-in events are:
Price approaching stop,
Possible tops/bottoms,
Large stop movement (for discretionary trading where stop is moved manually),
Large price movements.
Slippage and Fees
Even when running in indicator mode, the Engine allows for slippage and fees to be included in the logic and test results.
Alerts
The alert creation mechanism allows you to configure alerts on any combination of the normal or pyramided entries, exits and in-trade events.
Backtesting results
A few words on the numbers calculated in the Engine. Priority is given to numbers not shown in TV backtesting, as you can readily convert the script to a strategy if you need them.
We have chosen to focus on numbers expressing results relative to X (the trade’s risk) rather than in absolute currency numbers or in other more conventional but less useful ways. For example, most of the individual trade results are not shown in percentages, as this unit of measure is often less meaningful than those expressed in units of risk (X). A trade that closes with a +25% result, for example, is a poor outcome if it was entered with a -50% stop. Expressed in X, this trade’s P&L becomes 0.5, which provides much better insight into the trade’s outcome. A trade that closes with a P&L of +2X has earned twice the risk incurred upon entry, which would represent a pre-trade risk:reward ratio of 2.
The way to go about it when you think in X’s and that you adopt the sound risk management policy to risk a fixed percentage of your account on each trade is to equate a currency value to a unit of X. E.g. your account is 10K USD and you decide you will risk a maximum of 1% of it on each trade. That means your unit of X for each trade is worth 100 USD. If your APPT is 2X, this means every time you risk 100 USD in a trade, you can expect to make, on average, 200 USD.
By presenting results this way, we hope that the Engine’s statistics will appeal to those cognisant of sound risk management strategies, while gently leading traders who aren’t, towards them.
We trade to turn in tangible profits of course, so at some point currency must come into play. Accordingly, some values such as equity, P&L, slippage and fees are expressed in currency.
Many of the usual numbers shown in TV backtests are nonetheless available, but they have been commented out in the Engine’s Plot module.
Position sizing and risk management
All good system designers understand that optimal risk management is at the very heart of all winning strategies. The risk in a trade is defined by the fraction of current equity represented by the amplitude of the stop, so in order to manage risk optimally on each trade, position size should adjust to the stop’s amplitude. Systems that enter trades with a fixed stop amplitude can get away with calculating position size as a fixed percentage of current equity. In the context of a test run where equity varies, what represents a fixed amount of risk translates into different currency values.
Dynamically adjusting position size throughout a system’s life is optimal in many ways. First, as position sizing will vary with current equity, it reproduces a behavioral pattern common to experienced traders, who will dial down risk when confronted to poor performance and increase it when performance improves. Second, limiting risk confers more predictability to statistical test results. Third, position sizing isn’t just about managing risk, it’s also about maximizing opportunity. By using the maximum leverage (no reference to trading on margin here) into the trade that your risk management strategy allows, a dynamic position size allows you to capture maximal opportunity.
To calculate position sizes using the fixed risk method, we use the following formula: Position = Account * MaxRisk% / Stop% [, which calculates a position size taking into account the trade’s entry stop so that if the trade is stopped out, 100 USD will be lost. For someone who manages risk this way, common instructions to invest a certain percentage of your account in a position are simply worthless, as they do not take into account the risk incurred in the trade.
The Engine lets you select either the fixed risk or fixed percentage of equity position sizing methods. The closest thing to dynamic position sizing that can currently be done with alerts is to use a bot that allows syntax to specify position size as a percentage of equity which, while being dynamic in the sense that it will adapt to current equity when the trade is entered, does not allow us to modulate position size using the stop’s amplitude. Changes to alerts are on the way which should solve this problem.
In order for you to simulate performance with the constraint of fixed position sizing, the Engine also offers a third, less preferable option, where position size is defined as a fixed percentage of initial capital so that it is constant throughout the test and will thus represent a varying proportion of current equity.
Let’s recap. The three position sizing methods the Engine offers are:
1. By specifying the maximum percentage of risk to incur on your remaining equity, so the Engine will dynamically adjust position size for each trade so that, combining the stop’s amplitude with position size will yield a fixed percentage of risk incurred on current equity,
2. By specifying a fixed percentage of remaining equity. Note that unless your system has a fixed stop at entry, this method will not provide maximal risk control, as risk will vary with the amplitude of the stop for every trade. This method, as the first, does however have the advantage of automatically adjusting position size to equity. It is the Engine’s default method because it has an equivalent in TV backtesting, so when flipping between indicator and strategy mode, test results will more or less correspond.
3. By specifying a fixed percentage of the Initial Capital. While this is the least preferable method, it nonetheless reflects the reality confronted by most system designers on TradingView today. In this case, risk varies both because the fixed position size in initial capital currency represents a varying percentage of remaining equity, and because the trade’s stop amplitude may vary, adding another variability vector to risk.
Note that the Engine cannot display equity results for strategies entering trades for a fixed amount of shares/contracts at a variable price.
SETTINGS/INPUTS
Because the initial text first published with a script cannot be edited later and because there are just too many options, the Engine’s Inputs will not be covered in minute detail, as they will most certainly evolve. We will go over them with broad strokes; you should be able to figure the rest out. If you have questions, just ask them here or in the PineCoders Telegram group.
Display
The display header’s checkbox does nothing.
For the moment, only one exit strategy uses a take profit level, so only that one will show information when checking “Show Take Profit Level”.
Entries
You can activate two simultaneous entry strats, each selected from the same set of strats contained in the Engine. If you select two and they fire simultaneously, the main strat’s signal will be used.
The random strat in each list uses a different seed, so you will get different results from each.
The “Filter transitions” and “Filter states” strats delegate signal generation to the selected filter(s). “Filter transitions” signals will only fire when the filter transitions into bull/bear state, so after a trade is stopped out, the next entry may take some time to trigger if the filter’s state does not change quickly. When you choose “Filter states”, then a new trade will be entered immediately after an exit in the direction the filter allows.
If you select “External Indicator”, your indicator will need to generate a +2/-2 (or a positive/negative stop value) to enter a long/short position, providing the selected filters allow for it. If you wish to use the Engine’s capacity to also derive the entry stop level from your indicator’s signal, then you must explicitly choose this option in the Entry Stops section.
Filters
You can activate as many filters as you wish; they are additive. The “Maximum stop allowed on entry” is an important component of proper risk management. If your system has an average 3% stop size and you need to trade using fixed position sizes because of alert/execution bot limitations, you must use this filter because if your system was to enter a trade with a 15% stop, that trade would incur 5 times the normal risk, and its result would account for an abnormally high proportion in your system’s performance.
Remember that any filter can also be used as an entry signal, either when it changes states, or whenever no trade is active and the filter is in a bull or bear mode.
Entry Stops
An entry stop must be selected in the Engine, as it requires a stop level before the in-trade stop is calculated. Until the selected in-trade stop strat generates a stop that comes closer to price than the entry stop (or respects another one of the in-trade stops kick in strats), the entry stop level is used.
It is here that you must select “External Indicator” if your indicator supplies a +price/-price value to be used as the entry stop. A +price is expected for a long entry and a -price value will enter a short with a stop at price. Note that the price is the absolute price, not an offset to the current price level.
In-Trade Stops
The Engine comes with many built-in in-trade stop strats. Note that some of them share the “Length” and “Multiple” field, so when you swap between them, be sure that the length and multiple in use correspond to what you want for that stop strat. Suggested defaults appear with the name of each strat in the dropdown.
In addition to the strat you wish to use, you must also determine when it kicks in to replace the initial entry’s stop, which is determined using different strats. For strats where you can define a positive or negative multiple of X, percentage or fixed value for a kick-in strat, a positive value is above the trade’s entry fill and a negative one below. A value of zero represents breakeven.
Pyramiding
What you specify in this section are the rules that allow pyramiding to happen. By themselves, these rules will not generate pyramiding entries. For those to happen, entry signals must be issued by one of the active entry strats, and conform to the pyramiding rules which act as a filter for them. The “Filter must allow entry” selection must be chosen if you want the usual system’s filters to act as additional filtering criteria for your pyramided entries.
Hard Exits
You can choose from a variety of hard exit strats. Hard exits are exit strategies which signal trade exits on specific events, as opposed to price breaching a stop level in In-Trade Stops strategies. They are self-explanatory. The last one labelled When Take Profit Level (multiple of X) is reached is the only one that uses a level, but contrary to stops, it is above price and while it is relative because it is expressed as a multiple of X, it does not move during the trade. This is the level called Take Profit that is show when the “Show Take Profit Level” checkbox is checked in the Display section.
While stops focus on managing risk, hard exit strategies try to put the emphasis on capturing opportunity.
Slippage
You can define it as a percentage or a fixed value, with different settings for entries and exits. The entry and exit markers on the chart show the impact of slippage on the entry price (the fill).
Fees
Fees, whether expressed as a percentage of position size in and out of the trade or as a fixed value per in and out, are in the same units of currency as the capital defined in the Position Sizing section. Fees being deducted from your Capital, they do not have an impact on the chart marker positions.
In-Trade Events
These events will only trigger during trades. They can be helpful to act as reminders for traders using the Engine as assistance to discretionary trading.
Post-Exit Analysis
It is normally on. Some of its results will show in the Global Numbers section of the Data Window. Only a few of the statistics generated are shown; many more are available, but commented out in the Plot module.
Date Range Filtering
Note that you don’t have to change the dates to enable/diable filtering. When you are done with a specific date range, just uncheck “Date Range Filtering” to disable date filtering.
Alert Triggers
Each selection corresponds to one condition. Conditions can be combined into a single alert as you please. Just be sure you have selected the ones you want to trigger the alert before you create the alert. For example, if you trade in both directions and you want a single alert to trigger on both types of exits, you must select both “Long Exit” and “Short Exit” before creating your alert.
Once the alert is triggered, these settings no longer have relevance as they have been saved with the alert.
When viewing charts where an alert has just triggered, if your alert triggers on more than one condition, you will need the appropriate markers active on your chart to figure out which condition triggered the alert, since plotting of markers is independent of alert management.
Position sizing
You have 3 options to determine position size:
1. Proportional to Stop -> Variable, with a cap on size.
2. Percentage of equity -> Variable.
3. Percentage of Initial Capital -> Fixed.
External Indicator
This is where you connect your indicator’s plot that will generate the signals the Engine will act upon. Remember this only works in Indicator mode.
DATA WINDOW INFORMATION
The top part of the window contains global numbers while the individual trade information appears in the bottom part. The different types of units used to express values are:
curr: denotes the currency used in the Position Sizing section of Inputs for the Initial Capital value.
quote: denotes quote currency, i.e. the value the instrument is expressed in, or the right side of the market pair (USD in EURUSD ).
X: the stop’s amplitude, itself expressed in quote currency, which we use to express a trade’s P&L, so that a trade with P&L=2X has made twice the stop’s amplitude in profit. This is sometimes referred to as R, since it represents one unit of risk. It is also the unit of measure used in the APPT, which denotes expected reward per unit of risk.
X%: is also the stop’s amplitude, but expressed as a percentage of the Entry Fill.
The numbers appearing in the Data Window are all prefixed:
“ALL:” the number is the average for all first entries and pyramided entries.
”1ST:” the number is for first entries only.
”PYR:” the number is for pyramided entries only.
”PEA:” the number is for Post-Exit Analyses
Global Numbers
Numbers in this section represent the results of all trades up to the cursor on the chart.
Average Profitability Per Trade (X): This value is the most important gauge of your strat’s worthiness. It represents the returns that can be expected from your strat for each unit of risk incurred. E.g.: your APPT is 2.0, thus for every unit of currency you invest in a trade, you can on average expect to obtain 2 after the trade. APPT is also referred to as “statistical expectancy”. If it is negative, your strategy is losing, even if your win rate is very good (it means your winning trades aren’t winning enough, or your losing trades lose too much, or both). Its counterpart in currency is also shown, as is the APPT/bar, which can be a useful gauge in deciding between rivalling systems.
Profit Factor: Gross of winning trades/Gross of losing trades. Strategy is profitable when >1. Not as useful as the APPT because it doesn’t take into account the win rate and the average win/loss per trade. It is calculated from the total winning/losing results of this particular backtest and has less predictive value than the APPT. A good profit factor together with a poor APPT means you just found a chart where your system outperformed. Relying too much on the profit factor is a bit like a poker player who would think going all in with two’s against aces is optimal because he just won a hand that way.
Win Rate: Percentage of winning trades out of all trades. Taken alone, it doesn’t have much to do with strategy profitability. You can have a win rate of 99% but if that one trade in 100 ruins you because of poor risk management, 99% doesn’t look so good anymore. This number speaks more of the system’s profile than its worthiness. Still, it can be useful to gauge if the system fits your personality. It can also be useful to traders intending to sell their systems, as low win rate systems are more difficult to sell and require more handholding of worried customers.
Equity (curr): This the sum of initial capital and the P&L of your system’s trades, including fees and slippage.
Return on Capital is the equivalent of TV’s Net Profit figure, i.e. the variation on your initial capital.
Maximum drawdown is the maximal drawdown from the highest equity point until the drop . There is also a close to close (meaning it doesn’t take into account in-trade variations) maximum drawdown value commented out in the code.
The next values are self-explanatory, until:
PYR: Avg Profitability Per Entry (X): this is the APPT for all pyramided entries.
PEA: Avg Max Opp . Available (X): the average maximal opportunity found in the Post-Exit Analyses.
PEA: Avg Drawdown to Max Opp . (X): this represents the maximum drawdown (incurred from the close at the beginning of the PEA analysis) required to reach the maximal opportunity point.
Trade Information
Numbers in this section concern only the current trade under the cursor. Most of them are self-explanatory. Use the description’s prefix to determine what the values applies to.
PYR: Avg Profitability Per Entry (X): While this value includes the impact of all current pyramided entries (and only those) and updates when you move your cursor around, P&L only reflects fees at the trade’s last bar.
PEA: Max Opp . Available (X): It’s the most profitable close reached post-trade, measured from the trade’s Exit Fill, expressed in the X value of the trade the PEA follows.
PEA: Drawdown to Max Opp . (X): This is the maximum drawdown from the trade’s Exit Fill that needs to be sustained in order to reach the maximum opportunity point, also expressed in X. Note that PEA numbers do not include slippage and fees.
EXTERNAL SIGNAL PROTOCOL
Only one external indicator can be connected to a script; in order to leverage its use to the fullest, the engine provides options to use it as either an entry signal, an entry/exit signal or a filter. When used as an entry signal, you can also use the signal to provide the entry’s stop. Here’s how this works:
For filter state: supply +1 for bull (long entries allowed), -1 for bear (short entries allowed).
For entry signals: supply +2 for long, -2 for short.
For exit signals: supply +3 for exit from long, -3 for exit from short.
To send an entry stop level with an entry signal: Send positive stop level for long entry (e.g. 103.33 to enter a long with a stop at 103.33), negative stop level for short entry (e.g. -103.33 to enter a short with a stop at 103.33). If you use this feature, your indicator will have to check for exact stop levels of 1.0, 2.0 or 3.0 and their negative counterparts, and fudge them with a tick in order to avoid confusion with other signals in the protocol.
Remember that mere generation of the values by your indicator will have no effect until you explicitly allow their use in the appropriate sections of the Engine’s Settings/Inputs.
An example of a script issuing a signal for the Engine is published by PineCoders.
RECOMMENDATIONS TO ASPIRING SYSTEM DESIGNERS
Stick to higher timeframes. On progressively lower timeframes, margins decrease and fees and slippage take a proportionally larger portion of profits, to the point where they can very easily turn a profitable strategy into a losing one. Additionally, your margin for error shrinks as the equilibrium of your system’s profitability becomes more fragile with the tight numbers involved in the shorter time frames. Avoid <1H time frames.
Know and calculate fees and slippage. To avoid market shock, backtest using conservative fees and slippage parameters. Systems rarely show unexpectedly good returns when they are confronted to the markets, so put all chances on your side by being outrageously conservative—or a the very least, realistic. Test results that do not include fees and slippage are worthless. Slippage is there for a reason, and that’s because our interventions in the market change the market. It is easier to find alpha in illiquid markets such as cryptos because not many large players participate in them. If your backtesting results are based on moving large positions and you don’t also add the inevitable slippage that will occur when you enter/exit thin markets, your backtesting will produce unrealistic results. Even if you do include large slippage in your settings, the Engine can only do so much as it will not let slippage push fills past the high or low of the entry bar, but the gap may be much larger in illiquid markets.
Never test and optimize your system on the same dataset , as that is the perfect recipe for overfitting or data dredging, which is trying to find one precise set of rules/parameters that works only on one dataset. These setups are the most fragile and often get destroyed when they meet the real world.
Try to find datasets yielding more than 100 trades. Less than that and results are not as reliable.
Consider all backtesting results with suspicion. If you never entertained sceptic tendencies, now is the time to begin. If your backtest results look really good, assume they are flawed, either because of your methodology, the data you’re using or the software doing the testing. Always assume the worse and learn proper backtesting techniques such as monte carlo simulations and walk forward analysis to avoid the traps and biases that unchecked greed will set for you. If you are not familiar with concepts such as survivor bias, lookahead bias and confirmation bias, learn about them.
Stick to simple bars or candles when designing systems. Other types of bars often do not yield reliable results, whether by design (Heikin Ashi) or because of the way they are implemented on TV (Renko bars).
Know that you don’t know and use that knowledge to learn more about systems and how to properly test them, about your biases, and about yourself.
Manage risk first , then capture opportunity.
Respect the inherent uncertainty of the future. Cleanse yourself of the sad arrogance and unchecked greed common to newcomers to trading. Strive for rationality. Respect the fact that while backtest results may look promising, there is no guarantee they will repeat in the future (there is actually a high probability they won’t!), because the future is fundamentally unknowable. If you develop a system that looks promising, don’t oversell it to others whose greed may lead them to entertain unreasonable expectations.
Have a plan. Understand what king of trading system you are trying to build. Have a clear picture or where entries, exits and other important levels will be in the sort of trade you are trying to create with your system. This stated direction will help you discard more efficiently many of the inevitably useless ideas that will pop up during system design.
Be wary of complexity. Experienced systems engineers understand how rapidly complexity builds when you assemble components together—however simple each one may be. The more complex your system, the more difficult it will be to manage.
Play! . Allow yourself time to play around when you design your systems. While much comes about from working with a purpose, great ideas sometimes come out of just trying things with no set goal, when you are stuck and don’t know how to move ahead. Have fun!
@LucF
NOTES
While the engine’s code can supply multiple consecutive entries of longs or shorts in order to scale positions (pyramid), all exits currently assume the execution bot will exit the totality of the position. No partial exits are currently possible with the Engine.
Because the Engine is literally crippled by the limitations on the number of plots a script can output on TV; it can only show a fraction of all the information it calculates in the Data Window. You will find in the Plot Module vast amounts of commented out lines that you can activate if you also disable an equivalent number of other plots. This may be useful to explore certain characteristics of your system in more detail.
When backtesting using the TV backtesting feature, you will need to provide the strategy parameters you wish to use through either Settings/Properties or by changing the default values in the code’s header. These values are defined in variables and used not only in the strategy() statement, but also as defaults in the Engine’s relevant Inputs.
If you want to test using pyramiding, then both the strategy’s Setting/Properties and the Engine’s Settings/Inputs need to allow pyramiding.
If you find any bugs in the Engine, please let us know.
THANKS
To @glaz for allowing the use of his unpublished MA Squize in the filters.
To @everget for his Chandelier stop code, which is also used as a filter in the Engine.
To @RicardoSantos for his pseudo-random generator, and because it’s from him that I first read in the Pine chat about the idea of using an external indicator as input into another. In the PineCoders group, @theheirophant then mentioned the idea of using it as a buy/sell signal and @simpelyfe showed a piece of code implementing the idea. That’s the tortuous story behind the use of the external indicator in the Engine.
To @admin for the Volatility stop’s original code and for the donchian function lifted from Ichimoku .
To @BobHoward21 for the v3 version of Volatility Stop .
To @scarf and @midtownsk8rguy for the color tuning.
To many other scripters who provided encouragement and suggestions for improvement during the long process of writing and testing this piece of code.
To J. Welles Wilder Jr. for ATR, used extensively throughout the Engine.
To TradingView for graciously making an account available to PineCoders.
And finally, to all fellow PineCoders for the constant intellectual stimulation; it is a privilege to share ideas with you all. The Engine is for all TradingView PineCoders, of course—but especially for you.
Look first. Then leap.
ATR Percentile BiznesFilosofThis script was created based on statistics and market research. Here you can see the increase in the activity of large players. Those. when they begin to take out "extra passengers", gaining a position for a strong trend movement in the aftermath. Also they can be found with stops and takeprofit (their value for the most likely operation).
By default, the red line stands at around 190. But then you can edit it for the current situation. Ideally, it should be at the lowest level of volatility (ATR).
The gray zone is favorable for setting stops and calculating the take-profit.
If you reduce the scale of the chart, you can see the red zone of market activity. This helps to understand when there is a lull in the big players (whales) and when they are again activated for the new pampas.
In more detail, I'm talking about this indicator on my channel in Youtube.
===
Этот скрипт создан, исходя из статистики и исследований рынка. Здесь можно увидеть повышение активности крупных игроков. Т.е. когда начинают выносить "лишних пассажиров", набирают позицию для сильного трендового движения в последствии. Также на основании данного индикатора можно определиться со стопами и тейкпрофитом (их величиной для наиболее вероятного срабатывания).
По умолчанию красная линия стоит на отметке 190. Но потом её можно отредактировать под текущую ситуацию. В идеале она должна быть на самом нижнем уровне волатильности (ATR).
Серая зона благоприятная для установки стопов и расчета тейкпрофита.
Если уменьшить масштаб графика, то можно увидеть красные зоны активности рынка. Это помогает понять, когда происходит затишье крупных игроков (китов) и когда опять они активируются для нового пампа.
Более подробно я рассказываю про этот индикатор на своём канале в Ютуб.
JNSARJust Nifty SAR strategy has been developed by our Master Ilangovan.
Trading based on JNSAR:
JNSAR is a number based on market’s strength and weakness as well as the balance of demand and supply. Whatever the number may be, a choppy market could whipsaw the number occasionally to shake off your confidence in them. However, staying with one method brings you consistent winnings.
Step:1: As the JNSAR for yesterday was xxxx and the previous trade taken was a sell @ yyyy on “previous” day, the moment Nifty breached xxxx yesterday, you close out your earlier short and take a long position in minimum 2 lots – Stop and reverse (SAR).
Step:2: If after triggering a reversal long trade @ xxxx and markets fall again, you keep a filter of 20 to 30 points to JNSAR and manage them. Knowing key support numbers closer to JNSAR help in filtering out the whipsaws during long trades and Knowing key resistance numbers closer to JNSAR help in filtering out the whipsaws during short trades.
Step:3:Once a new trade is taken in with a minimum of 2 lots, you book on one lot with a profit of 50, 100+ points and keep the 2nd lot till a reverse trade is triggered based on each subsequent day’s JNSAR.
Step:4: After booking out on the 1st lot, if Nifty climbs back(retraces) substantially and start to fall again, take a new trade(rebuying) again. Rebuying the part booked trade is done at 50% to 61.8% of last segment of rise ( Reselling the part booked trade is done at 50% to 61.8% of last segment of fall) OR at critical 21 or 34 HrSmas. This step is optional and suited for the experienced.
Step:5: You may use the filter of 25 to 30 points on JNSAR for 2 days once JNSAR new trade is taken to give the new trade a fighting chance & survive. For eg: For the new long trade taken @ xxxx yesterday, the JNSAR of today @ zzzz may be altered to zzzz-30.
Step:6: Do not count your winnings. Stay focussed on each trade.
Get Rich Slowly & Quietly.
(Mr. Ilangovan)
JC_MacD_RSI_Candle_Strat_public//
// Author : Jacques CRETINON
// Last Version : V1.0 11-22-2016
//
// Risk disclaimer : Do not use this script in production environment. We assume no liability or responsibility for any damage to you, your computer, or your other property, due to the use of this script.
//
// Purpose of this script :
// 1- use same pine code for strategy or study script (with simple modifications)
// 2- be able to send alerts : enterlong, entershort, exitlong, exitshort, stoplosslong, stoplossshort, takeprofitlong, takeprofitshort in a study script like a strategy script should do
// 3- do not repaint (I HOPE)
//
// RoadMap :
// 1- manage : Trailing Stop Loss and Trailing Stop Loss offset
//
// I use this script :
// 1- with default value for XAUUSD, current chart resolution : 1mn, large timeframe : 15mn.
// 2- That's why I hard code MACD5 (5mn average), MACD15 (15mn average), MACD60 (1h average) ...
// 3- MACD, RSI (1mn and 15mn) and Candles info are my inputs to take any decisions
//
// I do not publish my enterLong, enterShort, exitLong and exitShort conditions (lines 204 to 207 are sample !) as they are not as perfect as I'd like. Fell free to use your own conditions :)
//
// Please, report me any bug, fell free to discuss and share. English is not my natural language, so be clement ;) Happy safe trading :)
BTCCNY premiums over BTCUSD - yuan devaluationBitcoin as an alternative to capital outflows, with a market cap of just 2 billion can easily be up by multiples from the outflow of yuan from mainland China alone.
People simply do not want yuan if their purchasing power is going down over time.
Current methods of taking capital off mainland China via overseas cash withdrawals are quickly being closed out by the communist government.
------------------------------------------------------------
www.zerohedge.com
China has capped the amount of money Chinese holders of bank and credit cards can withdraw outside the country, in its latest effort to discourage people from moving badly needed capital offshore.
China’s foreign-exchange regulator put a new annual cap on overseas cash withdrawals using China UnionPay Co. bank cards, a UnionPay official said on Tuesday. Under the new rules, UnionPay cardholders can withdraw up to 50,000 yuan ($7,854) overseas during the last three months of this year, and the amount will be capped at 100,000 yuan for all of next year, the official said.
State-run UnionPay has a virtual monopoly on processing card transactions in China, meaning the limits extend to nearly all Chinese bank- and credit-card holders. It wasn’t clear when the new cap was issued.
The new cap is in addition to an existing 10,000 yuan daily withdrawal limit, part of China’s curbs on how much money can flow across its borders.
The move by China’s State Administration of Foreign Exchange is the latest by Beijing to scrutinize capital outflows.
The People’s Bank of China, the country’s central bank, said earlier this month that its foreign-exchange reserves fell by $93.9 billion, the biggest monthly drop ever, after it surprised the market on Aug. 11 with its decision to devalue the yuan by around 2%.
Key takeaway from the yuan devaluation and capital control:
The collapse of 2 bubbles: housing and stock market.
Weakness in commodities such as steel, copper and oil are seen which signals a weakening economy of which China are the core driver of that expansion since 2008. I suspect that China's GDP is never 8% as it is reported, but rather near 2~4% right now.
China have spent over 100 billion USD in US treasury proceeds to stabilize the yuan collapsing faster due to speculators. The amount of reserves spent at the current rate is unsustainable, it will take just 2 years for them to be used up completely.
Over time yuan will still be heading downwards.
Bassi MACD Pro + ADX Filter + Smart Histogram TP + RSIA professional-grade MACD indicator that dramatically reduces false signals by combining four powerful filters:
Key Features
Classic MACD (12,26,9) with clean, high-visibility histogram coloring
ADX + DI filter – only takes trades when ADX > user-defined threshold (default 25) ensuring you trade only in strong trending markets
Smart Histogram Take-Profit logic – automatically detects the exact moment bullish/bearish momentum starts to weaken after a strong move and marks a precise TP level (one TP per trade – no repainting, no multiple signals)
Zero-line crossover confirmation + histogram direction filter – eliminates many whipsaw signals common in regular MACD
Separate RSI pane with overbought/oversold levels and visual markers (for additional confluence – does not interfere with main logic)
Visual Signals
Green “MACD BUY” label + lime triangle = confirmed long entry in strong trend
Red “MACD SELL” label + red triangle = confirmed short entry in strong trend
Small lime/red “TP” triangles = Smart Histogram Take-Profit triggered (perfect exit timing based on momentum fade)
Alert Conditions Included
MACD BUY
MACD SELL
TP Long Hit
TP Short Hit
Combined “Any Signal” alert
Why this version outperforms standard MACD
Most MACD crossovers fail in ranging markets. This script solves that by:
Requiring strong trend (ADX filter)
Confirming histogram is actually growing in the new direction
Waiting for the true zero-line cross with momentum
Giving you an intelligent, non-fixed % take-profit based on real histogram exhaustion
Excellent for swing trading, day trading, crypto, forex, and stocks on any timeframe (works especially well on 1H–4H–Daily).
Clean, fast, no repainting, fully alert-ready.
Add to chart → set your alerts → trade only the highest-probability MACD signals.
10% and 23.6% support bandsWhen a share is in momentum and showing lot of strength that relative strength it takes breather at 10% band from new 52 week high and and tends to consolidate at 23.6% from new 52 week high. This forms a higher low and gives opportunity to get in the rally. The volume bars should be taken into consideration as low volume and dry up at the bottom indicate reversal is coming. The stoploss for all entry is 1% below recent base low and entry pont is crossing of weekly high with greater than 20 days volume average.
Volume essential parameters overlayVolume EPO – Essential Volume Parameters Overlay
1. Motivation and design philosophy
Volume EPO is designed as a conceptual overlay rather than a self contained trading system. The main idea behind this script is to take complex, foundational market concepts out of heavy, menu driven strategies and express them as lightweight, independent layers that sit on top of any chart or indicator.
In many TradingView scripts, a single strategy tries to handle everything at once: signal logic, risk settings, visual cues, multi timeframe controls, and conceptual explanations. This usually leads to long input menus, performance issues, and difficult maintenance. The architectural approach behind Volume EPO is the opposite: keep the core strategy lean, and move the explanation and measurement of key concepts into dedicated overlays.
In this framework, Volume EPO is the base layer for the concept of volume. It does not decide anything about entries or exits. Instead, it exposes and clarifies how different definitions of volume behave candle by candle. Other layers or strategies can then build on top of this understanding.
2. What Volume EPO does
Volume EPO focuses on four essential volume parameters for each bar:
- Buy volume - Sell volume - Total volume - Delta volume (the difference between buy and sell volume)
The script presents these parameters in a compact heads up display (HUD) table that can be positioned anywhere on the chart. It is designed to be visually minimal, language aware, and usable on top of any other indicator or price action without cluttering the view.
The indicator does not output signals, alerts, arrows, or strategy entries. It is a descriptive and educational tool that shows how volume is distributed, not a prescriptive tool that tells the trader what to do.
3. Two definitions of volume
A central theme of this script is that there is more than one way to define and interpret “volume” inside a single candle. Volume EPO implements and clearly separates two different approaches:
- A geometric, candle based approximation that uses only OHLC and volume of the current bar. - An intrabar, data driven definition that uses lower timeframe up and down volume when it is available.
The user can switch between these modes via the calculation method input. The mode is prominently shown inside the on chart table so that the context is always explicit.
3.1 Geometry mode (Source File, approximate)
In Geometry mode, Volume EPO works only with the current bar’s OHLC values and total volume. No lower timeframe data is required.
The candle’s range is defined as high minus low. If the range is positive, the position of the close inside that range is used as a simple model for how volume might have been distributed between buyers and sellers:
- The closer the close is to the high, the more of the total volume is attributed to the buying side. - The closer the close is to the low, the more of the total volume is attributed to the selling side. - In a rare case where the bar has no price range (for example a flat or doji bar), total volume is split evenly between buy and sell volume.
From this model, the script derives:
- Buy volume (approximated) - Sell volume (approximated) - Total volume (as reported by the bar) - Delta volume as the difference between buy and sell volume
This approach is intentionally labeled as “Geometry (Approx)” in the HUD. It is a theoretical reconstruction based solely on the candle’s geometry and total volume, and it is always available on any market or timeframe that provides OHLCV data.
3.2 Intrabar mode (Precise)
In Intrabar mode, Volume EPO uses the TradingView built in library for up and down volume on a user selected lower timeframe. Instead of inferring volume from the shape of the candle, it reads the underlying lower timeframe data when that data is accessible.
The script requests up and down volume from a lower timeframe such as 15 seconds, using the official TA library functions. The results are then interpreted as follows:
- Buy volume is taken as the absolute value of the up volume. - Sell volume is taken as the absolute value of the down volume. - Total volume is the sum of buy and sell volume. - Delta volume is provided directly by the library as the difference between up and down volume.
If valid lower timeframe data exists for a bar, the bar is counted as covered by Intrabar data. If not, that bar is marked as invalid for this precise calculation and is excluded from the covered count.
This mode is labeled “Precise” in the HUD, together with the selected lower timeframe, because it is anchored in actual intrabar data rather than in a geometric model. It provides a closer view of how buying and selling pressure unfolded inside the bar, at the cost of requiring more data and being dependent on the availability of that data.
4. Coverage, lookback, and what the numbers mean
The top part of the HUD reports not only which volume definition is active, but also an additional line that describes the effective coverage of the data.
In Intrabar (Precise) mode, the script displays:
- “Scanned: N Bars”
Here, N counts how many bars since the indicator was loaded have successfully received valid lower timeframe delta data. It is a measure of how much of the visible history has been truly covered by intrabar information, not a lookback window in the sense of a rolling calculation.
In Geometry mode, the script displays:
- “Lookback: L Bars”
In this extracted layer, the lookback value L is purely descriptive. It does not change how the current bar’s volume is computed, and it is not used in any iterative or statistical calculation inside this script. It is meant as a conceptual label, for example to keep the volume layer consistent with a broader framework where lookback length is a structural parameter.
Summarizing these two fields:
- Scanned tells you how many bars have been processed using real intrabar data. - Lookback is a descriptive parameter in Geometry mode in this specific overlay, not a direct driver of the computations.
5. The HUD layout on the chart
The on chart table is intentionally compact and structured to be read quickly:
- Header: a title identifying the overlay as Volume EPO. - Mode line: explicitly states whether the script is in Precise or Geometry mode, and for Precise mode also shows the lower timeframe used. - Coverage line: - In Precise mode, it shows “Scanned: N Bars”. - In Geometry mode, it shows “Lookback: L Bars”. - Volume block: - A line for buy and sell volume, marked with clear directional symbols. - A line for total volume and the absolute delta, accompanied by the sign of the delta. - Numeric formatting uses human friendly suffixes (for example K, M, B) to keep the display readable. - Footer: the current symbol and a time stamp, adjusted by a user selectable timezone offset so that the HUD can be aligned with the trader’s local time reference.
The table can be positioned anywhere on the chart and resized via inputs, and it supports multiple color themes and languages in order to integrate cleanly into different chart layouts.
6. How to use Volume EPO in practice
Volume EPO is meant to be read together with price action and other tools, not in isolation. Typical uses include:
- Studying how often a strong directional candle is actually supported by dominant buy or sell volume. - Comparing the behavior of delta volume between Geometry and Intrabar definitions. - Building a personal intuition for how intrabar data refines or contradicts the simple candle based approximation. - Feeding these insights into separate, lean strategy scripts that do not need to carry the full explanatory logic of volume inside them.
Because it is an overlay layer, Volume EPO can be stacked with other custom indicators without adding new signals or complexity to their logic. It simply adds a clear and consistent view of volume behavior on top of whatever the trader is already watching.
7. Educational and non signalling nature
Finally, it is important to stress that Volume EPO is not a trading system, not a signal generator, and not financial advice. The script does not tell the user when to enter or exit. It only reports how different definitions of volume describe the current bar.
Deciding whether to trade, how to trade, and which risk parameters to use remains entirely with the user and with their own strategy. Volume EPO provides context and clarity around the concept of volume so that those decisions can be informed by a better understanding of how buying and selling pressure is structured inside each candle.
Note: Even on lower timeframes, every reconstruction of volume remains an approximation, except at the true single tick level. However, the closer the chosen lower timeframe is to a one tick stream, the more accurately it can reflect the underlying order flow and balance between buying and selling pressure.
Weighted KDE Mode🙏🏻 The ‘ultimate’ typical value estimator, for the highest computational cost @ time complexity O(n^2). I am not afraid to say: this is the last resort BFG9000 you can ‘ever’ get to make dem market demons kneel before y’all
Quickguide
pls read it, you won’t find it anywhere else in open access
When to use:
If current market activity is so crazy || things on your charts are really so bad (contaminated data && (data has very heavy tails || very pronounced peak)), the only option left is to use the peak (mode) of Kernel Density Estimate , instead of median not even mentioning mean. So when WMA won’t help, when WPNR won’t help, you need this thing.
Setting it up:
Interval: choose what u need, you can use usual moving windows, but I also added yearly and session anchors alike in old VWAP (always prefer 24h instead of Session if your plan allows). Other options like cumulative window are also there.
Parameters: this script ain't no joke, it needs time to make calculations, so I added a setting to calculate only for the last N bars (when “starting at bar N” is put on 0). If it’s not zero it acts as a starting point after which the calculations happen (useful for backtesting). Other parameters keep em as they are, keep student5 kernel , turn off appropriate weights if u apply it to other than chart data, on other studies etc.
But instead of listening to me just experiment with parameters and see what they change, would take 5 mins max
Been always saying that VWAP is ish, not time-aware etc, volume info is incorporated in a lil bit wrong way… So I decided not just to fix VWAP (you can do it yourself in 5 mins), but instead to drop there the Ultimate xD typical value estimator that is ever possible to do. Time aware, volume / inferred volume aware, resistant to all kinds of BS. This is your shieldwall.
How it works:
You can easily do a weighted kernel density estimation, in our case including temporal and intensity information while accumulating densities. Here are some details worth mentioning about the thing:
Kernels are raw (not unit variance), that’s easier to work with later.
h_constants for each kernel were calculated ^^ given that ^^ with python mpmath module with high decimal precision.
In bandwidth calculation instead of using empirical standard deviation as a scaler, I use... ta.range(src, len) / math.sqrt(12)
...that takes data range and converts it to standard deviation, assuming data is uniformly distributed. That’s exactly what we need: a scaler that is coherent with the KDE, that has nothing to do with stdevs, as the kernels except for gaussian ones (that we don’t even need to use). More importantly, if u take multiple windows and see over time which distro they approach on the long term, that would be the uniform one (not the normal one as many think). Sometimes windows are multimodal, sometimes Laplace like etc, so in general all together they are uniform ish.
The one and only kernel you really need is Student t with v = 5 , for the use case I highlighted in the first part of the post for TV users. It’s as far as u can get until ish becomes crazy like undefined variance etc. It has the highest kurtosis = 9 of all distros, perfect for the real use case I mentioned. Otherwise, you don’t even need KDE 4 real, but still I included other senseful kernels for comparison or in case I am trippin there.
Btw, don’t believe in all that hype about Epanechnikov kernel which in essence is made from beta distribution with alpha = beta = 2, idk why folk call it with that weird name, it’s beta2 kernel. Yes on papers it really minimises AMISE (that’s how I calculated h constants for all dem kernels in the script), but for really crazy data (proper use case for us), it ain't provides even ‘closely’ compared with student5 kernel. Not much else to add.
Shout out to @RicardoSantos for inspiration, I saw your KDE script a long time ago brotha, finna got my hands on it.
∞
[CT] ATR Ratio MTFThis indicator is an enhanced, multi-timeframe version of the original “ATR ratio” by RafaelZioni. Huge thanks to RafaelZioni for the core concept and base logic. The script still combines an ATR-based ratio (Z-score style reading of where price sits within its recent ATR envelope) with an ATR Supertrend, but expands it into a more flexible trade-decision and visual context tool.
The ATR ratio is normalized so you can quickly see when price is pressing into extended bullish or bearish territory, while the Supertrend defines directional bias and a dynamic support-resistance trail. You can choose any higher timeframe in the settings, allowing you to run the ATR ratio and Supertrend from a larger anchor timeframe while trading on a lower chart.
Upgrades include a full Pine Script v6 rewrite, multi-timeframe support for both the ATR ratio and Supertrend, user-controlled colors for the Supertrend in bull and bear modes, and optional bar coloring so price bars automatically reflect Supertrend direction. Entry, pyramiding and take-profit logic from the original script are preserved, giving you a familiar framework with more control over timeframe, visuals and trend bias.
This indicator is designed to give you a clean directional framework that blends volatility, trend, and timing into one view. The ATR ratio side of the script shows you where price sits inside a recent ATR-based envelope. When the ATR ratio pushes up and sustains above the bullish threshold, it signals that price is trading in an extended, momentum-driven zone relative to recent volatility. When it drops and holds below the bearish threshold, it shows the opposite: sellers have pushed price down into an extended bearish zone. The optional background coloring simply makes these bullish and bearish environments easier to see at a glance.
On top of that, the Supertrend and bar colors tell you what side of the market to favor. The Supertrend is calculated from ATR on whatever timeframe you choose in the settings. If you set the MTF input to a higher timeframe, the Supertrend and ATR ratio become your higher time frame bias while you trade on a lower chart. When price is above the MTF Supertrend, the line uses your bullish color and, if bar coloring is enabled, candles adopt your bullish bar color. That is your “long only” environment: you generally look for buys when price is above the Supertrend and the ATR ratio is either turning up from neutral or already in a bullish zone. When price is below the MTF Supertrend, the line uses your bearish color and candles can shift to your bearish bar color; that is where you focus on shorts, especially when the ATR ratio is rolling over or holding in the bearish zone.
The built-in long and short conditions are meant as signal prompts, not rigid rules. Long signals fire when the ATR ratio crosses up through a positive level while the Supertrend is bullish. Short signals fire when the ATR ratio crosses down through a negative level while the Supertrend is bearish. The script tracks how many longs or shorts have been taken in sequence (pyramiding) and will only allow a new signal up to the limit you set, so you can control how aggressively you stack positions in a trend. The take-profit logic then watches the percentage move from your last entry and flags “TP” when that move has reached your take-profit percent, helping you standardize exits instead of eyeballing them bar by bar.
In practice you typically start by choosing your anchor timeframe for the MTF setting, for example a 1-hour or 4-hour Supertrend and ATR ratio while watching a 5-minute or 15-minute chart. You then use the Supertrend direction and bar colors as your bias filter, only taking signals in the direction of the trend, and you use the ATR ratio behavior to judge whether you are entering into strength, fading an extreme, or trading inside a neutral consolidation. Over time this gives you a consistent way to answer three questions on every chart: which side am I allowed to trade, how extended is price within its recent volatility, and where are my structured entries and exits based on that framework.
The Oracle: Dip & Top Adaptive Sniper [Hakan Yorganci]█ OVERVIEW
The Oracle: Dip & Top Adaptive Sniper is a precision-focused trend trading strategy designed to solve the biggest problem in swing trading: Timing.
Most trend-following strategies chase price ("FOMO"), buying when the asset is already overextended. The Oracle takes a different approach. It adopts a "Sniper" mentality: it identifies a strong macro trend but patiently waits for a Mean Reversion (pullback) to execute an entry at a discounted price.
By combining the structural strength of Moving Averages (SMA 50/200) with the momentum precision of RSI and the volatility filtering of ADX, this script filters out noise and targets high-probability setups.
█ HOW IT WORKS
This strategy operates on a strictly algorithmic protocol known as "The Yorganci Protocol," which involves three distinct phases: Filter, Target, and Execute.
1. The Macro Filter (Trend Identification)
* SMA 200 Rule: By default, the strategy only scans for buy signals when the price is trading above the 200-period Simple Moving Average. This ensures we are always trading in the direction of the long-term bull market.
* Adaptive Switch: A new feature allows users to toggle the Only Buy Above SMA 200? filter OFF. This enables the strategy to hunt for oversold bounces (dead cat bounces) even during bearish or neutral market structures.
2. The Volatility Filter (ADX Integration)
* Sideways Protection: One of the main weaknesses of moving average strategies is "whipsaw" losses during choppy, ranging markets.
* Solution: The Oracle utilizes the ADX (Average Directional Index). It will BLOCK any trade entry if the ADX is below the threshold (Default: 20). This ensures capital is only deployed when a genuine trend is present.
3. The Sniper Entry (Buying the Dip)
* Instead of buying on breakout strength (e.g., RSI > 60), The Oracle waits for the RSI Moving Average to dip into the "Value Zone" (Default: 45) and cross back up. This technique allows for tighter stops and higher Risk/Reward ratios compared to traditional breakout systems.
█ EXIT STRATEGY
The Oracle employs a dynamic dual-exit mechanism to maximize gains and protect capital:
* Take Profit (The Peak): The strategy monitors RSI heat. When the RSI Moving Average breaches the Overbought Threshold (Default: 75), it signals a "Take Profit", securing gains near the local top before a potential reversal.
* Stop Loss (Trend Invalidated): If the market structure fails and the price closes below the 50-period SMA, the position is immediately closed to prevent deep drawdowns.
█ SETTINGS & CONFIGURATION
* Moving Averages: Fully customizable lengths for Support (SMA 50) and Trend (SMA 200).
* Trend Filter: Checkbox to enable/disable the "Bull Market Only" rule.
* RSI Thresholds:
* Sniper Buy Level: Adjustable (Default: 45). Lower values = Deeper dips, fewer trades.
* Peak Sell Level: Adjustable (Default: 75). Higher values = Longer holds, potentially higher profit.
* ADX Filter: Checkbox to enable/disable volatility filtering.
█ BEST PRACTICES
* Timeframe: Designed primarily for 4H (4-Hour) charts for swing trading. It can also be used on 1H for more frequent signals.
* Assets: Highly effective on trending assets such as Bitcoin (BTC), Ethereum (ETH), and high-volume Altcoins.
* Risk Warning: This strategy is designed for "Long Only" spot or leverage trading. Always use proper risk management.
█ CREDITS
* Original Concept: Inspired by the foundational work of Murat Besiroglu (@muratkbesiroglu).
* Algorithm Development & Enhancements: Developed by Hakan Yorganci (@hknyrgnc).
* Modifications include: Integration of ADX filters, Mean Reversion entry logic (RSI Dip), and Dynamic Peak Profit taking.
Super-AO Engine - Sentiment Ribbon - 11-29-25Super-AO Sentiment Ribbon by Signal Lynx
Overview:
The Super-AO Sentiment Ribbon is the visual companion to the Super-AO Strategy Suite.
While the main strategy handles the complex mathematics of entries and risk management, this tool provides a simple "Traffic Light" visual at the top of your chart to gauge the overall health of the market.
How It Works:
This indicator takes the core components of the Super-AO strategy (The SuperTrend and the Awesome Oscillator), calculates the spread between them and the current price, and generates a normalized "Sentiment Score."
Reading the Colors:
🟢 Lime / Green: Strong Upward Momentum. Ideally, you only want to take Longs here.
🟤 Olive / Yellow: Trend is weakening. Be careful with new entries, or consider taking profit.
⚪ Gray: The "Kill Zone." The market is chopping sideways. Automated strategies usually suffer here.
🟠 Orange / Red: Strong Downward Momentum. Ideally, you only want to take Shorts here.
Integration:
This script uses the same default inputs as our Super-AO Strategy Template and Alerts Template. Use them together to confirm your automated entries visually.
About Signal Lynx:
Free Scripts supporting Automation for the Night-Shift Nation 🌙
(www.signallynx.com)
Grok/Claude Turtle Trend Pro Strategy Turtle Trend Pro Strategy: A Modern Implementation of the Legendary Turtle Trading System
Historical Background: The Original Turtle Experiment
In 1983, legendary commodities trader Richard Dennis made a bet with his partner William Eckhardt: could successful trading be taught, or was it an innate skill? To settle the debate, Dennis recruited and trained a group of novices—whom he called "Turtles" (inspired by turtle farms he'd visited in Singapore)—teaching them a complete mechanical trading system. The results were remarkable: over the next four years, the Turtles reportedly earned over $175 million, proving that systematic, rule-based trading could be taught and replicated.
The strategy you've shared is a faithful modern adaptation of those original Turtle rules, enhanced with contemporary technical filters.
Core Turtle Principles Preserved in This Strategy
1. Donchian Channel Breakouts (The Heart of Turtle Trading)
The original Turtles used Donchian Channels—a simple concept where you track the highest high and lowest low over a specific lookback period. This strategy implements both original Turtle systems:
System 1 (Default): 20-period entry breakout, 15-period exit
System 2 (Optional): 55-period entry breakout, 20-period exit
The logic is elegantly simple:
Go long when price breaks above the highest high of the last 20 (or 55) periods
Go short when price breaks below the lowest low of the last 20 (or 55) periods
This captures the Turtle philosophy of trend-following through momentum breakouts—the idea that markets trending strongly in one direction tend to continue.
2. ATR-Based Position Sizing and Stops
The Turtles were pioneers in using Average True Range (ATR) for risk management. This strategy preserves that approach:
Stop Loss: Set at 2× ATR from entry (the original Turtle rule)
ATR Period : 20 days (matching the original)
The ATR stop adapts to market volatility—wider stops in volatile markets, tighter stops in calm ones—preventing premature exits while still protecting capital.
3. Opposite Channel Exit
Rather than using arbitrary profit targets, the Turtles exited positions when price broke the opposite channel:
Exit longs when price breaks below the 15-period (or 20-period) low
Exit shorts when price breaks above the 15-period (or 20-period) high
This allows winning trades to run while providing a systematic exit that doesn't rely on prediction.
Modern Enhancements Beyond the Original System
While the core mechanics remain true to 1983, this strategy adds sophisticated filters the original Turtles didn't have access to:
Trend Filter (200 EMA)
Only takes long trades when price is above the 200-period moving average (and the MA is sloping up), and vice versa for shorts. This aligns trades with the major trend, reducing whipsaws in choppy markets. Set of off by default and fully adjustable in settings.
ADX Filter (Trend Strength)
The Average Directional Index ensures trades are only taken when the market is actually trending (ADX > 20 threshold). The original Turtles suffered significant drawdowns in ranging markets—this filter addresses that weakness.
Optional RSI Filter
Adds overbought/oversold confirmation to entries, though this is disabled by default to stay closer to the original system.
Volume Confirmation
Optional requirement for volume surges on breakouts, adding conviction to signals.
The Strategy's Risk Management Framework
Parameter Setting Turtle Origin Position Size 10% of equity. Turtles used volatility-adjusted sizing.
Stop Loss2× ATR.
Original Turtle rule Commission 0.075%. Modern crypto exchange rate.
Pyramiding Disabled.
Turtles did pyramid, but simplified here.
Visual Elements and Regime Detection
The strategy includes a "Neural Fusion Pro" styled display that would make the original Turtles jealous:
Color-coded Donchian Channels: Green (bullish), Red (bearish), Yellow (neutral)
Trend Strength Meter: Combines ADX, price vs. MA distance, channel position, and DI spread
Regime Classification : Automatically identifies Bull, Bear, or Neutral market conditions
Information Panel: Real-time display of all key metrics
Why Turtle Trading Still Works
The genius of the Turtle system lies in its mechanical discipline. It removes emotion from trading by providing explicit rules for:
What to trade (anything with sufficient liquidity and volatility)
When to enter (channel breakouts)
How much to trade (volatility-adjusted position sizing)
When to exit (opposite breakout or ATR stop)
This strategy faithfully preserves that mechanical approach while adding modern filters to improve the win rate in today's markets.
Student Wyckoff Target Shooter
**Target Shooter — Equal Move Target Tool (Larry Williams idea)**
**1. What this indicator does**
Target Shooter is a tool that measures the last meaningful price swing and projects an **equal move target** in the direction of the breakout.
The logic is simple:
* The market makes a move from point A to point B (a swing high to a swing low, or vice versa).
* Then price breaks out above or below this swing range.
* Target Shooter takes the size of that swing and **adds it in the direction of the breakout**, showing a logical **price target zone** where the move may:
* slow down,
* react,
* or potentially reverse.
This is a practical implementation of the “Equal Moves” idea often referenced by Larry Williams.
---
**2. Core idea (example)**
Example from the classic explanation:
* Price drops from **80 down to 20** → the move is **60 points**.
* The swing range is now: **High = 80, Low = 20**.
* Later, price **breaks above 80**.
Target Shooter assumes:
> “If the market could move 60 points in one direction, after a breakout it may travel another 60 points in the opposite direction.”
So the upside target becomes:
* Move size: 80 − 20 = 60
* Breakout above 80
* **Target = 80 + 60 = 140**
The indicator finds such swings automatically and draws:
* **UT (Upper Target)** on upside breakouts
* **DT (Down Target)** on downside breakouts
---
**3. What you see on the chart**
1. **Target lines**
* When price breaks **above** a previous swing range, the indicator plots a horizontal **UT (Upper Target)** line — the projected equal move target.
* When price breaks **below** the previous swing range, it plots a **DT (Down Target)** line — the downside target.
* Each line is drawn from the breakout bar and extended to the right for a user-defined number of bars.
2. **Price labels**
* A small label “UT” or “DT” is shown at the end of the line with the exact target price.
* This makes it easy to see where the projected target is without checking the scale.
3. **Optional swing range (debug view)**
* There is an option to display the **swing range** that the target is based on (similar to a Donchian channel on previous bars).
* This shows the upper (swing high) and lower (swing low) boundaries the indicator used to define the last move.
---
**4. Key inputs (plain language)**
* **Swing window length (bars)**
How many bars back the indicator looks to find the last meaningful swing (highest high and lowest low).
This is like the length of a Donchian channel used to define the previous range.
Smaller values → more frequent, shorter targets.
Larger values → bigger swings and more distant targets.
* **Minimum move size (in ticks)**
This is a noise filter.
If the distance between the swing high and swing low is smaller than this threshold, no targets are drawn.
The indicator will only react to moves that are big enough to matter for your trading.
* **Breakout type: Close vs High/Low**
* **Breakout by Close**:
The target appears only when the **bar closes** above/below the swing range.
More conservative and fewer false signals.
* **Breakout by High/Low**:
The target appears as soon as the **high** or **low** of the bar breaks the swing range.
Faster and more aggressive, but more sensitive to noise.
* **Target line length (bars)**
How far to the right the UT/DT lines should be extended.
Shorter length → local target zones.
Longer length → important levels visible far into the future.
* **Appearance settings**
* Separate color, width and style for **UT** and **DT** lines.
* Option to show or hide labels with price and “UT/DT” text.
---
**5. How to use Target Shooter in trading**
> Important: this is **not** an entry signal indicator.
> Target Shooter is a **targeting and context tool**, not a standalone system.
Typical uses:
1. **Planning take-profit zones**
* You already have an entry signal from your own strategy (Wyckoff, Larry Williams patterns, levels, volume, whatever you use).
* Target Shooter shows a **logical equal move target** where the current wave can reasonably “shoot”.
* You can:
* place your main take-profit around the target,
* scale out part of the position,
* tighten stops when price approaches the target.
2. **Finding potential reaction / reversal areas**
* Equal move targets often act as **zones of interest**.
* If price reaches a UT/DT level and then shows weakness/absorption/volume spikes or reversal candles, this might be a good place to take profits or look for counter-trend opportunities (for experienced traders).
3. **Assessing trend strength**
* If price **easily exceeds** the equal move target and keeps going without any reaction, it suggests a very strong trend.
* If price **fails to reach** the target and reverses early, the move is weaker than expected.
---
**6. Timeframes**
Target Shooter can be used on:
* **Intraday** (M5, M15, M30, H1) — for shorter-term targets within the day,
* **Higher timeframes** (H4, D1 and above) — for swing and position trades.
General rule:
The **higher the timeframe and the larger the swing**, the **more important** the target level tends to be.
---
**7. Notes and limitations**
* The indicator does **not** predict the future.
It simply projects a geometric equal move from the last swing.
* It should be combined with your own trading framework:
* support/resistance,
* Wyckoff / VSA,
* trend tools,
* volume/flow, etc.
* Always keep proper risk management.
A target is a **scenario**, not a guarantee.
.
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy
## 📊 Overview
**Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols.
The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions.
## 🎯 Core Algorithm
### Triple EMA System
The strategy employs a three-layer EMA system to identify trend direction and strength:
- **Fast EMA (12)**: Quick response to price changes
- **Slow EMA (26)**: Confirmation of trend direction
- **Trend EMA (100)**: Overall market bias filter
Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend.
### Multi-Signal Confirmation (8 Signal Types)
The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position:
1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal)
2. **MACD Cross** - MACD line crossing signal line (momentum confirmation)
3. **RSI Reversal** - RSI bouncing from oversold/overbought zones
4. **Price Action** - Strong bullish/bearish candles (>60% of range)
5. **Volume Spike** - Above-average volume confirmation
6. **Breakout** - Price breaking 20-period high/low with volume
7. **Pullback to EMA** - Trend continuation after healthy retracement
8. **Bollinger Bounce** - Price bouncing from BB bands
This multi-signal approach significantly reduces false signals and improves win rate.
## 💰 Risk Management
### Position Sizing
- Default: 20-25% of equity per trade
- Adjustable based on risk tolerance
- Smaller positions recommended for leveraged trading
### Stop Loss & Take Profit
- **Stop Loss**: 2.0% (tight control of risk)
- **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio)
- Both levels are fixed at entry to avoid emotional decisions
### Trailing Stop System
- Activates after 1.8% profit
- Trails at 1.3% below current price
- Locks in profits during extended trends
- Automatically adjusts as price moves in your favor
### Maximum Hold Time
- 36-48 hours maximum (configurable)
- Designed to minimize funding rate costs on futures
- Forces position closure to avoid excessive exposure
- Helps maintain capital velocity
## 📈 Key Features
### Trend Filters
- **ADX Filter**: Ensures sufficient trend strength (threshold: 20)
- **EMA Alignment**: All three EMAs must confirm trend direction
- **RSI Boundaries**: Avoids extreme overbought/oversold entries
### Volume Analysis
- Volume must exceed 20-period moving average
- Configurable multiplier (default: 1.0x)
- Helps identify institutional participation
### Automatic Exit Conditions
1. Take Profit target reached
2. Stop Loss triggered
3. Trailing stop activated
4. Trend reversal (EMA cross in opposite direction)
5. Maximum hold time exceeded
## 🎮 Recommended Settings
### For Spot Trading (Conservative)
```
Position Size: 15-20%
Stop Loss: 2.5%
Take Profit: 6.0%
Max Hold: 72 hours
Leverage: 1x
```
### For Futures 3-5x Leverage (Balanced)
```
Position Size: 12-15%
Stop Loss: 2.0%
Take Profit: 5.5%
Max Hold: 36 hours
Trailing: Active
```
### For Aggressive Trading 5-10x (High Risk)
```
Position Size: 8-12%
Stop Loss: 1.5%
Take Profit: 4.5%
Max Hold: 24 hours
ADX Filter: Disabled
```
## 📊 Performance Metrics
### Backtested Results (BTC/USDT 1H, 2 years)
- **Total Return**: ~19% (spot) / ~75% (5x leverage)*
- **Total Trades**: 240-300
- **Win Rate**: 49-52%
- **Profit Factor**: 1.25-1.50
- **Max Drawdown**: ~18-22%
- **Average Trade**: 0.5-3 days
*Leverage results exclude funding rates and real-world slippage
### Optimal Timeframes
- **1 Hour**: Best for active trading (recommended)
- **4 Hour**: More stable, fewer signals
- **15 Min**: High frequency (requires monitoring)
### Best Performing Assets
- BTC/USDT (most tested)
- ETH/USDT
- Major altcoins with good liquidity
- Not recommended for low-cap or illiquid pairs
## ⚙️ How to Use
1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart
2. **Adjust Settings**: Configure risk parameters based on your preference
3. **Review Signals**: Green = Long, Red = Short, labels show signal count
4. **Monitor Performance**: Check strategy tester for detailed statistics
5. **Optimize**: Use strategy optimization to find best parameters for your market
## 🎨 Visual Indicators
The strategy provides clear visual feedback:
- **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend)
- **BUY/SELL Labels**: Show entry points with signal count
- **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades
- **Background Color**: Light green (long), light red (short) when in position
- **Info Panel**: Shows current trend, RSI, ADX, and volume status
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational purposes only
- Past performance does not guarantee future results
- Cryptocurrency trading involves substantial risk
- Only trade with capital you can afford to lose
- Always use proper position sizing and risk management
### Limitations
- Performs poorly in sideways/choppy markets
- Requires sufficient liquidity for best execution
- Backtests do not include:
- Real-world slippage (especially during volatility)
- Funding rates (for perpetual futures)
- Exchange downtime or connection issues
- Emotional trading decisions
### For Futures Trading
If using this strategy on futures with leverage:
- Reduce position size proportionally to leverage
- Account for funding rates (~0.01% per 8h)
- Set max hold time to minimize funding costs
- Use lower leverage (3-5x max recommended)
- Monitor liquidation price carefully
## 🔧 Customization
All parameters are fully customizable:
- EMA periods (fast/slow/trend)
- MACD settings (12/26/9)
- RSI levels (30/70)
- Stop Loss / Take Profit percentages
- Trailing stop activation and offset
- Volume multiplier
- ADX threshold
- Maximum hold time
## 📚 Strategy Logic
The strategy follows this decision tree:
```
1. Check Trend Direction (EMA alignment)
↓
2. Scan for Entry Signals (8 types)
↓
3. Confirm with Filters (ADX, Volume, RSI)
↓
4. Enter Position with Fixed SL/TP
↓
5. Monitor for Exit Conditions:
- TP Hit → Close with profit
- SL Hit → Close with loss
- Trailing Active → Follow price
- Trend Reversal → Close position
- Max Time → Force close
```
## 🎓 Best Practices
1. **Start Conservative**: Use smaller position sizes initially
2. **Track Performance**: Monitor actual vs backtested results
3. **Optimize Regularly**: Market conditions change, adapt parameters
4. **Combine with Analysis**: Don't rely solely on automated signals
5. **Manage Emotions**: Stick to the system, avoid manual overrides
6. **Paper Trade First**: Test on demo before risking real capital
## 📞 Support & Updates
This strategy is actively maintained and updated based on:
- Market condition changes
- User feedback and suggestions
- Performance optimization
- Bug fixes and improvements
## 🏆 Conclusion
Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends.
The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach.
**Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions.
---
*Version: 1.0*
*Last Updated: November 2025*
*Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)*
*Recommended Capital: $5,000+ for optimal position sizing*
ATR Trailing Stop (Long or Short Selectable)The ATR Trailing Stop (Long or Short Selectable) will start calculating on a set date that you specify. This is great because you want to trail the price from the breakout day or even after exceeding specific price level (can be your breakeven level or even to capture more of the upside after the price target is met).
Entry price: If you act at the close of the day, you can leave this value as 0 and it will take the close of the day for the initial protective stop-loss calculation. You can choose to add a value such as the pattern boundary and in that case it will subtract the initial protective stop-loss from the pattern boundary and not the close of the day. If you use a scaling in tactic during the day (buying in tranches intraday as the breakout takes place) and your average purchase price is different than the close of the day, you can also plug that number in to calculate the initial protective stop-loss.
This is a modified version as many followers asked for ATR trailing for short setups. Now you can select the Long/Short trade setup from the drop down menu.
ATR period: You can select the ATR period. It can be 10 day, 14 day or 30 day or any ATR period of your choice.
ATR Multiplier for Stop-loss: This is the multiplier that you want to trail the price with. From the highest level price reached it will trail the price with a 3 x ATR () distance. The higher the number, the wider the trailing stop-loss. A multiplier of 1 will trail the price so close that and adverse movement can result in triggering the stop-loss.
Custom Value for First day Trailing Stop: This is my favorite part. For aggressive risk management, your initial protective stop can be smaller than what the ATR Trailing Stop will use in its calculation after entry day. In this case you can take 1xATR () or even with FX and Futures you can apply 0.5xATR() as the first day to calculate initial protective stop. The protective stop turns into a trailing stop after the first day.
BTC -50% Crash to Recovery ZoneGeneral Overview This is a macro-analysis tool designed to visualize the true duration of Bitcoin’s "Suffering & Recovery Cycles." Unlike standard oscillators that only signal oversold conditions, this script highlights the entire timeline required for the market to flush out leverage and return to All-Time Highs (ATH).
Operational Logic The algorithm tracks Bitcoin’s historical All-Time High (ATH).
The Trigger: It activates automatically when the price drops 50% below the last recorded ATH.
The "Recovery Zone": Once triggered, the chart background turns red (indicating a "Drawdown" state). This zone remains active persistently, even during intermediate relief rallies.
The Reset: The zone deactivates only when the price breaks above the previous ATH, marking the official start of a new Price Discovery phase.
How to Read It
Red Background: We are officially in a Bear Market or Recovery Phase. The asset is technically "underwater." For the long-term investor with a low time preference, this visually defines the accumulation window.
Red Horizontal Line: Indicates the "Target." This is the exact price level of the old ATH that Bitcoin must reclaim to close the bearish cycle.
No Background Color: We are in Price Discovery. The market is healthy and pushing for new highs.
The Financial Lesson This indicator visually demonstrates a fundamental market truth: "Price takes the elevator down, but takes the stairs up." It shows that after a halving of value (-50%), Bitcoin may take months or years to recover previous levels, helping investors filter out the noise of short-term pumps that fail to break the macro-bearish structure.
Liquidity & inducementsHi all!
This indicator will show liquidity and inducements.
I will continue to try to add different types of liquidity and inducements, at this moment it contains 6 kinds of liquidity/inducement, they are:
• Grabs
• Big grabs
• Sweeps
• Turtle soups
• Equal highs/lows (liquidity and inducement)
• BSL & SSL
And 1 type of inducement:
• Retracement
This description will contain indicator examples of each individual liquidity and inducement. They will all be with the default settings.
Settings
First you will find settings for the market structure (BOS/CHoCH/CHoCH+). Select left and right pivot lengths and if the pivots should have a label or not.
This is the base foundation of this indicator and is possible with my library 'PriceAction' ().
You will see solid lines for break of structures (BOS), change of characters (CHoCH) and change of character plus (CHoCH+).
The pivots found will be the core of this indicator and will show you when the closing price breaks it. When that happens a break of structure (BOS) or a change of character (CHoCH or CHoCH+) will be created. The latest 5 pivots found within the current trend will be kept to take action on.
A break of structure is removed if an earlier pivot within the same trend is broken and the pivot's high price for a bullish trend or low price for a bearish trend is more extreme than the BOS pivot's price.
You are able to show the pivots that are used. "HH" (higher high), "HL" (higher low), "LH" (lower high), "LL" (lower low) and "H"/"L" (for pivots (high/low) when the trend has changed) are the labels used.
In the next section ('Liquidity ($$$)') you can select which types of liquidity you want to see. Note that 'Equal highs/lows' can also show inducement (more on that later).
In the section afterwards ('Inducement (IDM)') you can select if you want retracement inducements to be visible or not. More information on what they are later on.
The section for each individual liquidity and/or inducement can first contain a line named 'Pivot', where you can set the pivot lengths (first left, then right). Then you can set the 'Lookback', which means that the 'Lookback' number of past pivots is to take action on. After that you set the 'Timeframe' for the pivots used. That means that all available liquidity/inducements will be from your desired timeframe. Lastly you set the color of the liquidity/inducement (either a single color or bullish followed by bearish colors).
Lastly in the settings you can select the font sizes for the market structure and liquidity/inducements and what style liquidity/inducements lines will have. The sizes defaults to 7 and has a dotted line look.
Grabs
Liquidity grabs and liquidity sweeps are very similar. It all depends on if the current bar closed above/below the liquidity pivot and on if its a continuation or reversal. In a liquidity grab the bar that's above or below the liquidity pivot was not closed above or below it. Like this:
Or
The visual feedback will be a dotted line between the liquidity pivot and liquidity grab bar and a linefill between the high of the liquidity grab bar and the liquidity pivot.
Indicator example:
Big grabs
This is another 'grabs' option. You can show an additional grab if you want to. I suggest having this grab from a higher timeframe or with larger pivot lengths than the other grab.
The default is with the chart timeframe and 10/10 as pivot lengths.
Indicator example:
Sweeps
A liquidity sweep is like a liquidity grab but with the difference that price closes above/below and has a continuation instead of a reversal. If the liquidity pivot was at the same bar as a BOS/CHoCH/CHoCH+ it will not be a liquidity grab but a structural break instead.
They can look like this:
Indicator example;
Turtle soups
If only one candle is beyond the pivot it could be a liquidity grab. It's a grab if price didn't close beyond the liquidity pivot, if so it's invaliditet. Turtle soups are basically false breakouts that takes liquidity (is a false breakout from a pivot with the lengths and timeframe from the settings).
The turtle soup can have a confirmation in the terms of a change of character (CHoCH). You can enable this in the settings section for 'Turtle soups' through the 'Confirmation' checkbox (enabled by default). The turtle soup strategy usually comes with some sort of confirmation, in this case a CHoCH, but it can also be a market structure shift (MSS) or a change in state of delivery (CISD).
The addition of turtle soups is possible through my script 'Turtle soup' ().
The drawing will be a dotted line between the liquidity pivot and the last bar of the false breakout and a box from the start of the false breakout to the end of it.
Indicator example:
Equal highs/lows
Equal highs/lows will always show liquidity, but might also show inducement. Inducement will be shown on equal lows if the trend is bullish and on equal highs if it's bearish, like this:
Or
Equal highs can only be created if the second pivot is lower than the first one. Equal lows can only be created if the second pivot is higher than the first one. If that is not the case it could be a liquidity grab.
When equal highs or equal lows are find that produces inducement (equal lows in a bullish trend and equal highs in a bearish trend), the indicator will first display inducement and will show liquidity once traders are induced to enter the security. Stop loss placement, for liquidity, is 0.1 * the average true range (ATR, of length 14). They will look like this:
Only inducement:
Inducement and liquidity:
Indicator example:
Equal highs/lows inducements can not be triggered after a BOS/CHoCH/CHoCH+. They are cleared upon a structural break.
BSL & SSL
Buyside liquidity (BSL) and sellside liquidity (SSL) will be shown. A pivot that's been mitigated (touched by price) can never be BSL or SSL. The BSL/SSL available will be dynamic while price moves (work in Replay and lower timeframes that moves fast) and pick the latest pivot/s (with left and right lengths from the 'Market structure' section). You can define how many BSL/SSL you want to see with a default value of 1, meaning only 1 BSL and 1 SSL can be shown. If there is no unmitigated high (BSL) or low (SSL), no BSL/SSL will be available to show. If there are BSL/SSL available they're very useful to use as targets for entering a trade.
The will look like this when available;
And without BSL available:
Or
And without SSL available:
Note that the examples without BSL/SSL available could have liquidity available from previous price legs.
This can be an example of a BSL/SSL sequence:
First both buyside and sellside liquidity is available:
Then a new low appears and new sellside liquidity is available:
Then buyside liquidity is mitigated, so only sellside liquidity is available:
A new high pivot appears and buyside liquidity is available again:
Lastly a bearish CHoCH happens and sellside liquidity is mitigated, only buyside liquidity is available:
Retracement
The first retracement after a BOS/CHoCH/CHoCH+ is considered an inducement with the mission to get traders into a trade prematurely to get stopped out. This level is shown and look like this:
Or
A retracement inducement is removed when a new BOS/CHoCH/CHoCH+ appears and it's not triggered.
---------------------------
As of now there aren't any alerts available. You cannot use the Pine Screener from Tradingview either to see new liquidity/inducement events. I have this planned for future updates though.
I hope that this long description makes sense, let me know otherwise! Also let me know if you experience any bugs or have a feature request or just want to share good settings to use.
Best of trading luck!
Camarilla Pivot Plays (Lite) [BruzX]█ OVERVIEW
This indicator implements the Camarilla Pivot Points levels and a system for suggesting particular plays. It only 3rd, 4th, and 6th levels, as these are the only ones used by the system. It also optionally shows the Central Pivot Range, which is in fact between S2 and R2. In total, there are 12 possible plays, grouped into two groups of six. The algorithm evaluates in real-time which plays fulfil their precondition and shows the candidate plays. The user must then decide if and when to take the play.
█ CREDITS
The Camarilla pivot plays are defined in a strategy developed by Thor Young, and the whole system is explained in his book "A Complete Day Trading System". This description is self-sufficient for effective use.
█ FEATURES
Display the 3rd, 4th and 6th Camarilla pivot levels
Works for stocks, futures, indices, forex and crypto
Automatically switches between RTH and ETH data based on criteria defined by the system.
Option to force RTH/ETH data and force a close price to be used in the calculation.
Preconditions for the plays can be toggled on/off
Works correctly on both RTH and ETH charts
Well-documented options tooltips
Well-documented and high-quality open-source code for those who are interested
█ HOW TO USE
The defaults work well; at a minimum, just add the indicator and watch the plays being called. For US futures, you will probably want to chat the "Timezone for sessions" to New York and the regular session times to 09:30 - 16:00. The following diagram shows its key features.
By default, the indicator draws plays 1 days back; this can be changed up to 20 days. The labels can be shifted left/right using the "label offset" option to avoid overlapping with other labels in this indicator or those of another indicator.
An information box at the top-right of the chart shows:
The data currently in use for the main pivots. This can switch in the pre-market if the H/L range exceeds the previous day's H/L, and if it does, you will see that switch at the time that it happens
Whether the current day's pivots are in a higher or lower range compared to the previous day's.
The width of the pivots compared to the previous day
The current candidate plays fulfilling preconditions. You then need to watch the price action to decide whether to take the play.
The resistance pivots are all drawn in the same colour (red by default), as are the support pivots (green by default). You can change the resistance and support colours, but it is not possible to have different colours for different levels of the same kind.
█ CONCEPTS
The indicator is focused around daily Camarilla pivots and evaluates the preconditions for 12 possible plays: 6 when in a higher range, 6 when in a lower range. The plays are labelled by two letters—the first indicates the range, the second indicates the play—as shown in this diagram:
The pivots can be calculated using only RTH (Regular Trading Hours) data, or ETH (Extended Trading Hours) data, which includes the pre-market and post-market. The indicator implements logic to automatically choose the correct data, based on the rules defined by the strategy. This is user-overridable. With the default options, ETH will be used when the H/L range in the previous day's post-market or current day's pre-market exceeds that of the previous day's regular market. In auto mode, the chosen pivots are considered the main pivots for that day and are the ones used for play evaluation. The "other" pivots can also be shown—"other" here meaning using ETH data when the main pivots use RTH data, and vice versa.
The plays must fulfil a set of preconditions. There are preconditions for valid region and range, price sweeps into levels, correct pivot width, opening position, price action, and whether neutral range plays and premarket plays are enabled. When all the preconditions are fulfilled, the play will be shown as a candidate.
█ NOTE FOR FUTURES
Futures don't officially have a pre-market or post-market like equities. Let's take ES on CME as an example. It trades from 18:00 ET Sunday to 17:00 Friday (ET), with a daily pause between 17:00 and 18:00 ET. However, most of the trading activity is done between 09:30 and 16:00, which you can tell from the volume spikes at those times, and this coincides with NYSE/NASDAQ regular hours. So we define a pseudo-pre-market from 18:00 the previous day to 09:30 on the current day, then a pseudo-regular market from 08:30 to 16:00, then a pseudo-post-market from 16:00 to 17:00. The indicator then works exactly the same as with equities—all the options behave the same, just with different session times defined for the pre-, regular, and post-market, with "RTH" meaning just the regular market and "ETH" meaning all three.
█ LIMITATIONS
The pivots are very close to those shown in DAS Trader Pro. They are not to-the-cent exact, but within a few cents. The reasons are:
TradingView provides free real-time data from CBOE One, not full exchange data (you can pay for this though, and it's not expensive), and
the close/high/low are taken from the intraday timeframe you are currently viewing, not daily data—which are very close, but often not exactly the same. For example, the high on the daily timeframe may differ slightly from the daily high you'll see on an intraday timeframe.
Despite these caveats, occasionally large spikes will be seem in one platform and not the other (even with paid data), or the spikes will reach significantly difference prices. Where these spikes create the daily high or low, this can cause significantly different pivots levels. The more traded the stock is, the less the difference tends to be. Highly traded stocks are usually within a few cents (but even they occasionally have large differences in spikes). There is nothing that can be done about this.
The 6th Camarilla level does not have a standard definition and may not match the level shown on other platforms. It does match the definition used by DAS Trader Pro.
Replay mode for stocks does not work correctly. This is due to some important Pine Script variables provided by the TradingView platform and used by the script not being assigned correct values in replay mode. Futures do not use these variables, so they should work in replay mode.
The indicator is an intraday indicator (despite also being able to show weekly and monthly pivots on an intraday chart). It deactivates on a daily timeframe and higher. Sub-minute timeframes are also not supported.
The indicator was developed and tested for US/European stocks, US futures and EURUSD forex and BTCUSD. It should work as intended for stocks and futures in different countries, and for all forex and crypto, but this is tested as much as the security it was developed for.
█ DISCLAIMER
This indicator is provided for information only and should not be used in isolation without a good understand of the system and without considering other factors. You should not take trades using real money based solely on what this indicator says. Any trades you take are entirely at your own risk.
Central Limit Theorem Reversion IndicatorDear TV community, let me introduce you to the first-ever Central Limit Theorem indicator on TradingView.
The Central Limit Theorem is used in statistics and it can be quite useful in quant trading and understanding market behaviors.
In short, the CLT states: "When you take repeated samples from any population and calculate their averages, those averages will form a normal (bell curve) distribution—no matter what the original data looks like."
In this CLT indicator, I use statistical theory to identify high-probability mean reversion opportunities in the markets. It calculates statistical confidence bands and z-scores to identify when price movements deviate significantly from their expected distribution, signaling potential reversion opportunities with quantifiable probability levels.
Mathematical Foundation
The Central Limit Theorem (CLT) says that when you average many data points together, those averages will form a predictable bell-curve pattern, even if the original data is completely random and unpredictable (which often is in the markets). This works no matter what you're measuring, and it gets more reliable as you use more data points.
Why using it for trading?
Individual price movements seem random and chaotic, but when we look at the average of many price movements, we can actually predict how they should behave statistically. This lets us spot when prices have moved "too far" from what's normal—and those extreme moves tend to snap back (mean reversion).
Key Formula:
Z = (X̄ - μ) / (σ / √n)
Where:
- X̄ = Sample mean (average return over n periods)
- μ = Population mean (long-term expected return)
- σ = Population standard deviation (volatility)
- n = Sample size
- σ/√n = Standard error of the mean
How I Apply CLT
Step 1: Calculate Returns
Measures how much price changed from one bar to the next (using logarithms for better statistical properties)
Step 2: Average Recent Returns
Takes the average of the last n returns (e.g., last 100 bars). This is your "sample mean."
Step 3: Find What's "Normal"
Looks at historical data to determine: a) What the typical average return should be (the long-term mean) and b) How volatile the market usually is (standard deviation)
Step 4: Calculate Standard Error
Determines how much sample averages naturally vary. Larger samples = smaller expected variation.
Step 5: Calculate Z-Score
Measures how unusual the current situation is.
Step 6: Draw Confidence Bands
Converts these statistical boundaries into actual price levels on your chart, showing where price is statistically expected to stay 95% and 99% of the time.
Interpretation & Usage
The Z-Score:
The z-score tells you how statistically unusual the current price deviation is:
|Z| < 1.0 → Normal behavior, no action
|Z| = 1.0 to 1.96 → Moderate deviation, watch closely
|Z| = 1.96 to 2.58 → Significant deviation (95%+), consider entry
|Z| > 2.58 → Extreme deviation (99%+), high probability setup
The Confidence Bands
- Upper Red Bands: 95% and 99% overbought zones → Expect mean reversion downward as the price is not likely to cross these lines.
- Center Gray Line: Statistical expectation (fair value)
- Lower Blue Bands: 95% and 99% oversold zones → Expect mean reversion upward
Trading Logic:
- When price exceeds the upper 95% band (z-score > +1.96), there's only a 5% probability this is random noise → Strong sell/short signal
- When price falls below the lower 95% band (z-score < -1.96), there's a 95% statistical expectation of upward reversion → Strong buy/long signal
Background Gradient
The background color provides real-time visual feedback:
- Blue shades: Oversold conditions, expect upward reversion
- Red shades: Overbought conditions, expect downward reversion
- Intensity: Darker colors indicate stronger statistical significance
Trading Strategy Examples
Hypothetically, this is how the indicator could be used:
- Long: Z-score < -1.96 (below 95% confidence band)
- Short: Z-score > +1.96 (above 95% confidence band)
- Take profit when price returns to center line (Z ≈ 0)
Input Parameters
Sample Size (n) - Default: 100
Lookback Period (m) - Default: 100
You can also create alerts based on the indicator.
Final notes:
- The indicator uses logarithmic returns for better statistical properties
- Converts statistical bands back to price space for practical use
- Adaptive volatility: Bands automatically widen in high volatility, narrow in low volatility
- No repainting: yay! All calculations use historical data only
Feedback is more than welcome!
Henri
Candle Breakout StrategyShort description (one-liner)
Candle Breakout Strategy — identifies a user-specified candle (UTC time), draws its high/low range, then enters on breakouts with configurable stop-loss, take-profit (via Risk:Reward) and optional alerts.
Full description (ready-to-paste)
Candle Breakout Strategy
Version 1.0 — Strategy script (Pine v5)
Overview
The Candle Breakout Strategy automatically captures a single "range candle" at a user-specified UTC time, draws its high/low as a visible box and dashed level lines, and waits for a breakout. When price closes above the range high it enters a Long; when price closes below the range low it enters a Short. Stop-loss is placed at the opposite range boundary and take-profit is calculated with a user-configurable Risk:Reward multiplier. Alerts for entries can be enabled.
This strategy is intended for breakout style trading where a clearly defined intraday range is established at a fixed time. It is simple, transparent and easy to adapt to multiple symbols and timeframes.
How it works (step-by-step)
On every bar the script checks the current UTC time.
When the first bar that matches the configured Target Hour:Target Minute (UTC) appears, the script records that candle’s high and low. This defines the breakout range.
A box and dashed lines are drawn on the chart to display the range and extended to the right while the range is active.
The script then waits for price to close outside the box:
Close > Range High → Long entry
Close < Range Low → Short entry
When an entry triggers:
Stop-loss = opposite range boundary (range low for longs, range high for shorts).
Take-profit = entry ± (risk × Risk:Reward). Risk is computed as the distance between entry price and stop-loss.
After entry the range becomes inactive (waitingForBreakout = false) until the next configured target time.
Inputs / Parameters
Target Hour (UTC) — the hour (0–23) in UTC when the range candle is detected.
Target Minute — minute (0–59) of the target candle.
Risk:Reward Ratio — multiplier for computing take profit from risk (0.5–10). Example: 2 means TP = entry + 2×risk.
Enable Alerts — turn on/off entry alerts (string message sent once per bar when an entry occurs).
Show Last Box Only (internal behavior) — when enabled the previous box is deleted at the next range creation so only the most recent range is visible (default behavior in the script).
Visuals & On-chart Info
A semi-transparent blue box shows the recorded range and extends to the right while active.
Dashed horizontal lines mark the range high and low.
On-chart shapes: green triangle below bar for Long signals, red triangle above bar for Short signals.
An information table (top-right) displays:
Target Time (UTC)
Active Range (Yes / No)
Range High
Range Low
Risk:Reward
Alerts
If Enable Alerts is on, the script sends an alert with the following formats when an entry occurs:
Long alert:
🟢 LONG SIGNAL
Entry Price:
Stop Loss:
Take Profit:
Short alert:
🔴 SHORT SIGNAL
Entry Price:
Stop Loss:
Take Profit:
Use TradingView's alert dialog to create alerts based on the script — select the script’s alert condition or use the alert() messages.
Recommended usage & tips
Timeframe: This strategy works on any timeframe but the definition of "candle at target time" depends on the chart timeframe. For intraday breakout styles, use 1m — 60m charts depending on the session you want to capture.
Target Time: Choose a time that is meaningful for the instrument (e.g., market open, economic release, session overlap). All times are handled in UTC.
Position Sizing: The script’s example uses strategy.percent_of_equity with 100% default — change default_qty_value or strategy settings to suit your risk management.
Filtering: Consider combining this breakout with trend filters (EMA, ADX, etc.) to reduce false breakouts.
Backtesting: Always backtest over a sufficiently large and recent sample. Pay attention to slippage and commission settings in TradingView’s strategy tester.
Known behavior & limitations
The script registers the breakout on close outside the recorded range. If you prefer intrabar breakout rules (e.g., high/low breach without close), you must adjust the condition accordingly.
The recorded range is taken from a single candle at the exact configured UTC time. If there are missing bars or the chart timeframe doesn't align, the intended candle may differ — choose the target time and chart timeframe consistently.
Only a single active position is allowed at a time (the script checks strategy.position_size == 0 before entries).
Example setups
EURUSD (Forex): Target Time 07:00 UTC — captures London open range.
Nifty / Index: Target Time 09:15 UTC — captures local session open range.
Crypto: Target Time 00:00 UTC — captures daily reset candle for breakout.
Risk disclaimer
This script is educational and provided as-is. Past performance is not indicative of future results. Use proper risk management, test on historical data, and consider slippage and commissions. Do not trade real capital without sufficient testing.
Change log
v1.0 — Initial release: range capture, box and level drawing, long/short entry by close breakout, SL at opposite boundary, TP via Risk:Reward, alerts, info table.
If you want, I can also:
Provide a short README version (2–3 lines) for the TradingView “Short description” field.
Add a couple of suggested alert templates for the TradingView alert dialog (if you want alerts that include variable placeholders).
Convert the disclaimer into multiple language versions.
Gold 15m: Trend + S/R + Liquidity Sweep (RR 1:2)This strategy is designed for short-term trading on XAUUSD (Gold) using the 15-minute timeframe. It combines trend direction, support/resistance pivots, liquidity sweep detection, and momentum confirmation to identify high-probability reversal setups in line with the dominant market trend.
⚙️ Core Logic:
Trend Filter (EMA 200):
The strategy only takes long positions when price is above the 200 EMA and short positions when price is below it.
Support/Resistance via Pivots:
Dynamic swing highs and lows are identified using pivot points. These act as local supply and demand levels where liquidity is likely to accumulate.
Liquidity Sweep Detection:
A bullish liquidity sweep occurs when price briefly breaks below the last pivot low (grabbing liquidity) and then closes back above it.
A bearish sweep occurs when price breaks above the last pivot high and then closes back below.
Momentum & Candle Strength:
The strategy filters signals based on candle range and body size to ensure entries occur during strong price reactions, not weak retracements.
Risk Management (1:2 RR):
Stop-loss is placed slightly beyond the last pivot level using ATR-based buffers, and take-profit is set at 2× the risk distance, maintaining a reward-to-risk ratio of 1:2.
💼 Trade Logic Summary:
Long Entry:
After a bullish liquidity sweep & reclaim, momentum confirmation, and trend alignment (above EMA 200).
Short Entry:
After a bearish sweep & reclaim, momentum confirmation, and trend alignment (below EMA 200).
Exit:
Automated via ATR-based Stop Loss and Take Profit targets.
📊 Customization Options:
Adjustable EMA length, pivot settings, ATR multipliers, and RR ratio.
Option to enable/disable trend filter.
Toggle display of S/R zones on chart.
🧠 Best Use:
Works best during London and New York sessions when Gold shows strong momentum.
Can be adapted for forex pairs and indices by tuning ATR and pivot parameters.
