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Reversal finderThis script is used to visually highlight candles which may signal a reversal following a false break of a support or resistance level. Inputs are: Lookback period: look for the highest high and the lowest low of the prior x bars. SMA length: used for a simple moving average of the range (high minus low) of the prior x bars. Range multiple: used to filter out signals for any bars with a range smaller than the average range of the preceding bars (determined by SMA length above) e.g. a range multiple of 2 will only show signals for bars with a range twice of that of the average range of the preceding bars. Range threshold: used to filter signals for bars both the open and close of the bar are at the extreme end of the bar e.g. a threshold setting of 33% will only show buy signals for bars which open and close within the upper 1/3rd of the bar’s high/low range (vice versa for sell signals). This helps highlight, for example, bars with a high which exceeds resistance in a current range but which close back inside the range. Highlight signal bars?: This will highlight bars with a buy signal in green, sell signal bars in red, and all other bars in grey. The script was designed for use with a dark background, so you will need to play around with the bar colours in the style settings to suit your preferences. Settings used in the example chart are not the default – they are lookback: 5, SMA length: 20, range multiple: 1.2, range threshold: 33%. Enjoy!
Indicatore Pine Script®
di NS91
23
Pivots MTF [LucF]Pivots detected at higher timeframes are more significant because more market activity—or work—is required to produce them. This indicator displays pivots calculated on the higher timeframe of your choice. Features ► Timeframe selection — The higher timeframe (HTF) can be selected in 3 different ways:  • By steps (15 min., 60 min., 4H, 1D, 3D, 1W, 1M, 1Y). This setting is the default.  • As a multiple of the current chart's resolution, which can be fractional, so 3.5 will work.  • Fixed. — The HTF used can be displayed near the last bar (default). — Note that using the HTF is not mandatory. If it is disabled, the indicator will calculate on the chart's resolution. — Non-repainting or repainting mode can be selected. This has no impact on the display of historical bars, but when no repainting is selected, pivot detection in the realtime bar will be delayed by one chart bar (not one bar at the HTF). ► Pivots — Three color schemes are provided: green/red, aqua/pink and coral/violet (the default). — Both the thickness and brightness of lines can be controlled separately for the hi and lo pivots. — The visibility of the last hi/lo pivots can be enhanced. — Prices can be displayed on pivot lines and the text's size and color can be adjusted. — The number of bars required for the left/right pivot legs can be controlled (the default is 4). — The source can be selected individually for hi and lo pivots (the default is hlc3 and low . — The mean of the hi/lo pivot values of the last few thousand chart bars can be displayed. Pivots having lasted longer during the mean's period will weigh more in the calculation. The mean can be displayed in running mode and/or only showing its last level as a long horizontal line. I don't find it very useful; maybe others will. ► Markers and Alerts — Markers can be configured on breaches of either the last hi/lo pivot levels, or the hi/lo mean. Crossovers and crossunders are controlled separately. — Alerts can be configured using any of the marker combinations. As is usual for my indicators, only one alert is used. It will trigger on the markers that are active when you create your alert. Once your markers are set up the way you want, create your alert from the chart/timeframe you want the alert to run on, and be sure to use the “Once Per Bar Close” triggering condition. Use an alert message that will remind you of the combination of markers used when creating the alert. If you use multiple markers to trigger one alert, then having the indicator show those markers will be important to help you figure out which marker triggered the alert when it fired. A quick look at the pattern of these markers will hopefully convince you that using them as entry/exit signals would be perilous, as they are prone to whipsaw. I have included them because some traders may use the markers as reminders. Using Pivots These pivots can be used in a few different ways: — When using the high / low sources they will show extreme levels, breaches of which should be more significant. — Another way to use them is with hlc3 (the average of the high , low and close ) for hi pivots and low for the lo pivots. This accounts for my personal mythology to the effect that drops typically reach previous lows more easily than rallies make newer highs. — Using low for hi pivots and high for lo pivots (so backward) can be a useful way to set stops or to detect weakness in movements. You will usually be better served by pivots if you consider them as denoting regions rather than precise levels. The flexibility in the display options of this indicator will help you adapt it to the way you use your pivots. To indicate areas rather than levels, for example, try using a brightness of 1 with a line thickness of 30. The cloud effect generated this way will show areas better than fine lines. Realize that these pivot lines are positioned in the past, and so they are drawn after the fact because a given number of bars need to elapse before calculations determine a pivot has occurred. You will thus never see a pivot top, for example, identified on the realtime bar. To detect a pivot, it takes a number of bars corresponding to the dilation of the higher timeframe in the current one, multiplied by the number of bars you use for your pivots' right leg. Also note that the Pine native function used to detect pivots in this indicator considers a summit to be a top when the number of bars in each leg are lower or equal to that top. Bars in legs do not need to be progressively lower on each side of the pivot for a pivot to be detected. If you program in Pine — See the Pinecoders MTF Selection Framework for an explanation of the functions used in this script to provide the selection mechanism for the higher timeframe. — This code uses the Pine Script Coding Conventions . Thanks — To the Pine coders asking questions in the Pine Script chat on TV ; your questions got me to write this indicator.
Indicatore Pine Script®
di LucF
53
Leledc Exhaustion V4This is one of my fav script (Leledec Exhaustion). The original script was written in V2 by Glaz here All I did is to convert this to Version 4 of Pine Scripting language. An Exhaustion Bar is a bar which signals the exhaustion of the trend in the current direction. In other words, an exhaustion bar is “A bar of the last seller” in case of a downtrend and “A bar of last buyer” in case of an uptrend. Having said that when a party cannot take the price further in their direction, naturally the other party comes in, takes charge and reverses the direction of the trend. The Psychology Let's assume that we have a group of people, say 100 people who decide to go for a casual running. After running for a few KM's few of them will say “I am exhausted. I cannot run further”. They will quit running. After running further, another bunch of runners will say “I am exhausted. I can’t run further” and they also will quit running. This goes on and on and then there will be a stage where only a few will be left in the running. Now a stage will come where the last person left in the running will say “ am exhausted” and he stops running. That means no one is left now in the running. This means all are exhausted in the running. The same way an exhaustion bar works. The reason is an exhaustion bar sometimes formed at almost tops and bottoms. Timeframe The exhaustion bars are found on all Time frames as a trend also exists on all Timeframes. However, as a thumb rule “Higher the Time frame, higher will be the accuracy as well as the profitability”. Trading the Leledec Exhaustion Bars I may trade as soon as it is shown on the chart. I may trade when price breaks the high/low of the bar depending on whether I am getting bullish or bearish signal I may trade when price breaks the high/low of the bar depending on whether I am getting bullish or bearish signal. I may also be looking to ensure the current volume is higher than the previous few (? how many?) bar volumes.
Indicatore Pine Script®
di Joy_Bangla
21
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.
Indicatore Pine Script®
di PineCoders
130
MFI v1.0 Normal and Dinamic (Totals)The normal MFI script use an RSI in the formula so the quantity of movments are not visible, this script allows you to see how much volume is being trade at the moment, so you can detect unusual levels, but you will no be allowed to see the RSI (0-100)* so I suggest to use this script with a normal MFI Features: + Normal MFI length (14) + Green bars show the total of money trade of the bars that are going up + Red bars show the total of money trade when of the bars that are going down + Dinamic calculation (Optional)(Bellow) Normal MFI use hlc3 ((high+low+close)/3) * (volume) to calculate each bar The dinamic MFI: (This is an optional feature, if you dont active it you will use the normal MFI calculation) (The information bellow is experimental and theorical only, you can use it or not in the script with the Dinamic option) Dinamic MFI divides the bar and volume in three parts. Volume is corresponding on each part ex. If the bar has not a top or lower wick the 100% of volume is in the middle... ex 2 If the 50% of the bar is a top wick, the 50% of volume is in the top wick Top wick: Is calculated this way If the bar is red (high-open)*volume of top wick or If the bar is green (high-close)*volume of top wick Middle: Is calculated this way If the bar is green (close-open)*volumemiddle or If the bar is red (open-close)*volumemiddle Lower wick If the bar is red (close-low)*volume of lower wick or If the bar is green (open- low)*volume of lower wick
Indicatore Pine Script®
di Oscar118
MIDAS VWAP Jayy his is just a bash together of two MIDAS VWAP scripts particularly AkifTokuz and drshoe. I added the ability to show more MIDAS curves from the same script. The algorithm primarily uses the "n" number but the date can be used for the 8th VWAP I have not converted the script to version 3. To find bar number go into "Chart Properties" select " "background" then select Indicator Titles and "Indicator values". When you place your cursor over a bar the first number you see adjacent to the script title is the bar number. Put that in the dialogue box midline is MIDAS VWAP . The resistance is a MIDAS VWAP using bar highs. The resistance is MIDAS VWAP using bar lows. In most case using N will suffice. However, if you are flipping around charts inputting a specific date can be handy. In this way, you can compare the same point in time across multiple instruments eg first trading day of the year or an election date. Adding dates into the dialogue box is a bit cumbersome so in this version, it is enabled for only one curve. I have called it VWAP and it follows the typical VWAP algorithm. (Does that make a difference? Read below re my opinion on the Difference between MIDAS VWAP and VWAP ). I have added the ability to start from the bottom or top of the initiating bar. In theory in a probable uptrend pick a low of a bar for a low pivot and start the MIDAS VWAP there using the support. For a downtrend use the high pivot bar and select resistance. The way to see is to play with these values. Difference between MIDAS VWAP and the regular VWAP MIDAS itself as described by Levine uses a time anchored On-Balance Volume (OBV) plotted on a graph where the horizontal (abscissa) arm of the graph is cumulative volume not time. He called his VWAP curves Support/Resistance VWAP or S/R curves. These S/R curves are often referred to as "MIDAS curves". These are the main components of the MIDAS chart. A third algorithm called the Top-Bottom Finder was also described. (Separate script). Additional tools have been described in "MIDAS_Technical_Analysis" Midas Technical Analysis: A VWAP Approach to Trading and Investing in Today’s Markets by Andrew Coles, David G. Hawkins Copyright © 2011 by Andrew Coles and David G. Hawkins. Denoting the different way in which Levine approached the calculation. The difference between "MIDAS" VWAP and VWAP is, in my opinion, much ado about nothing. The algorithms generate identical curves albeit the MIDAS algorithm launches the curve one bar later than the VWAP algorithm which can be a pain in the neck. All of the algorithms that I looked at on Tradingview step back one bar in time to initiate the MIDAS curve. As such the plotted curves are identical to traditional VWAP assuming the initiation is from the candle/bar midpoint. How did Levine intend the curves to be drawn? On a reversal, he suggested the initiation of the Support and Resistance VVWAP (S/R curve) to be started after a reversal. It is clear in his examples this happens occasionally but in many cases he initiates the so-called MIDAS S/R VWAP right at the reversal point. In any case, the algorithm is problematic if you wish to start a curve on the first bar of an IPO . You will get nothing. That is a pain. Also in Levine's writings, he describes simply clicking on the point where a S/R VWAP is to be drawn from. As such, the generally accepted method of initiating the curve at N-1 is a practical and sensible method. The only issue is that you cannot draw the curve from the first bar on any security, as mentioned without resorting to the typical VWAP algorithm. There is another difference. VWAP is launched from the middle of the bar (as per AlphaTrends), You can also launch from the top of the bar or the bottom (or anywhere for that matter). The calculation proceeds using the top or bottom for each new bar. The potential applications are discussed in the MIDAS Technical Analysis book.
Indicatore Pine Script®
di jayy
21
PumpC Price Action Candles & MAsPumpC – PAC & MAs (Open Source) A complete Price Action Candles (PAC) toolkit with Fair Value Gaps, Inside Bars, Hammers, and Inverted Hammers—combined with a flexible Moving Averages (MAs) module. Draws forward-extending boxes, optionally recolors levels once price trades back through them, qualifies signals with a global High-Volume filter, and ships with ready-made alerts. Works on intraday through swing across any market (e.g., NASDAQ:QQQ , $CME:ES1!, FX:EURUSD , CRYPTO:BTCUSD ). This is an open-source script. The description explains purpose, behavior, and configuration so traders can evaluate fit. It makes no performance claims and does not provide trade advice. Acknowledgment & credits This script builds upon structural and box-handling code patterns originally derived from the Super OrderBlock / FVG / BoS Tools by makuchaku & eFe . Their work established the foundation for array handling, forward-extending boxes, and mitigation recoloring. I have adapted, reorganized, and expanded this framework to integrate PAC-specific logic, Al Brooks-inspired price action interpretations, high-volume filters, and a custom multi-timeframe MA module. What it does Fair Value Gaps (FVG): Highlights three-bar displacement gaps with forward-extending boxes, labeled FVG+ (bullish) and FVG- (bearish). Optional mitigation recolor when price later trades back into the gap. Inside Bars (IB): Boxes inside ranges when a bar is fully contained in the prior bar. Can require high volume to emphasize participation. Hammers (H) & Inverted Hammers (IH): Detects candles using configurable body/upper/lower-wick thresholds. Can require high volume. Mitigation recolor: Per-pattern option to flip a box to a mitigated color after price trades back through its vertical range. Moving Averages (MAs): Up to four configurable lines with a global type (EMA or SMA), custom lengths, per-MA timeframe selection, per-MA color, and a clean plotting rule to avoid clutter when downshifting timeframes. Alerts included: New FVG+, FVG-, IB, H, and IH events can trigger TradingView alerts and webhooks. How it works FVG: Identifies a gap between the current bar and the bar two periods back. A box spans the gap and extends forward. If mitigation recolor is enabled, the box changes to the mitigated color once price trades back inside it. IB: A bar is “inside” when its high is at or below the previous high and its low is at or above the previous low. The box extends forward; high-volume qualification is optional. Hammer / Inverted Hammer: Classifies candles by body size relative to total range and wick proportions. Each event becomes a forward-extending box; high-volume qualification is optional. MAs: Choose EMA or SMA globally, set each MA’s length and (optionally) a higher timeframe source. When a higher timeframe is chosen, the line only plots when that timeframe is above the chart’s timeframe, keeping visuals honest and uncluttered. Connection to Al Brooks’ PAC teachings This script reflects Al Brooks’ Price Action Candles (PAC) methodology: micro-patterns like Inside Bars, Hammers, and Inverted Hammers gain meaning not in isolation, but in context of the surrounding trend, supply/demand zones, and failed breakouts. Brooks emphasizes reading effort vs. result —what participants are trying to do, and whether they succeed. By highlighting these PACs and layering in volume confirmation, the script helps traders see which small patterns are worth paying attention to. Why the High-Volume filter matters Volume is a practical proxy for conviction. A pattern formed on light volume can be misleading noise; one formed on above-average volume has greater weight and aligns with Brooks’ view of price action strength. The global high-volume filter in this script lets you: Elevate Inside Bars that show absorption or compression with significant activity. Distinguish Hammers that reject lower prices aggressively from those that simply drift. Highlight Inverted Hammers where sellers dominate with conviction. This makes PAC readings cleaner and more actionable, especially in thin sessions or small timeframes. Inputs & customization Inputs are grouped for fast configuration: visibility first, then colors and styling, then labels, with a shared High-Volume baseline. High-Volume Filter (global) High-Vol Lookback: Length for the average volume baseline. High-Vol Multiple: A pattern only qualifies (when its toggle is on) if its volume exceeds the baseline multiplied by this factor. Fair Value Gaps Plot / Recolor Mitigated: Show gaps and optionally flip boxes when price trades back inside. Colors: Separate colors for FVG+ and FVG- , plus mitigated color. Box style & capacity: Border style, transparency, and maximum number of boxes. Labels: Toggle label, choose label color and size. Inside Bar (IB) Plot / Require High Volume / Recolor Mitigated: Main controls. Colors: IB color and mitigated color. Box style & capacity: Border style, transparency, max boxes. Labels: Toggle label, color, size. Hammer (H) Plot / Require High Volume / Recolor Mitigated: Main controls. Colors & style: Primary and mitigated colors, border style, transparency, max boxes. Labels: Toggle label, color, size. Thresholds: Body-to-range maximum %, minimum lower-wick-to-range %, and maximum upper-wick-to-range %. Inverted Hammer (IH) Plot / Require High Volume / Recolor Mitigated: Main controls. Colors & style: Primary and mitigated colors, border style, transparency, max boxes. Labels: Toggle label, color, size. Thresholds: Body-to-range maximum %, minimum upper-wick-to-range %, and maximum lower-wick-to-range %. Moving Averages (MAs) MA Type: EMA or SMA (global selection). Source: Choose price source (default: close). Per-MA settings (x4): Toggle on/off, length, optional higher-timeframe source, color. Clean plotting rule: If a higher timeframe is selected, the line displays only when that timeframe is above the chart timeframe, preventing clutter and keeping visuals accurate. Alerts Five alert conditions fire when a new pattern is created on the detecting bar—ideal for notifications or webhook automation. New Bullish FVG (+) New Bearish FVG (-) New Inside Bar (IB) New Hammer (H) New Inverted Hammer (IH) Suggested workflow Pick market & timeframe: Script works across equities, futures, forex, and crypto from scalping to swing. Toggle what you trade: Enable only the patterns you act on. Assign distinct colors for clarity. Use MAs for bias: Track trend, slope, and pullbacks. Consider sourcing one or more MAs from a higher timeframe for structural context. Enable High-Volume gating when needed: Filter out weak PACs during low participation. Tune the lookback/multiple per market. Monitor mitigation state: Recolored boxes immediately reveal which levels have been interacted with. Set alerts with purpose: Only enable alerts for setups aligned with your plan, then combine with structure, timing, and risk rules. Originality Unified PAC engine: FVG, IB, H, and IH presented consistently as forward-extending boxes with optional mitigation. Brooks-inspired design: Patterns are contextualized with volume and MAs, reflecting Al Brooks’ PAC methodology. Flexible high-volume gating: Shared baseline with per-pattern toggles supports cleaner signals across markets. MTF-aware MAs: Higher-timeframe averaging with clutter-free plotting rules. Open-source transparency: Code is fully available for learning, modifying, or extending. Disclaimer For educational and informational purposes only. Not financial advice. Trading carries risk; always manage exposure and test before live use.
Indicatore Pine Script®
di PumpCTrader
[Top] Simple ATR TP/SLSimple TP/SL from ATR (Locked per Bar) - Advanced Position Management Tool What This Indicator Does: Automatically calculates and displays Take Profit (TP) and Stop Loss (SL) levels based on Average True Range (ATR) Locks ATR values and direction signals at the start of each bar to prevent repainting and provide consistent levels Offers multiple direction detection modes including real-time candle-based positioning for dynamic trading approaches Displays entry, TP, and SL levels as clean horizontal lines that extend from the current bar Original Features That Make This Script Unique: Bar-Locked ATR System: ATR values are captured and frozen at bar open, ensuring levels remain stable throughout the bar's progression Multi-Modal Direction Detection: Four distinct modes for determining TP/SL positioning - Trend Following (EMA-based), Bullish Only, Bearish Only, and real-time Candle Based Real-Time Candle Flipping: In Candle Based mode, TP/SL levels flip immediately when the current candle changes from bullish to bearish or vice versa Persistent Line Management: Uses efficient line object management to prevent ghost lines and maintain clean visual presentation Flexible Base Price Selection: Choose between Open (static), Close (dynamic), or midpoint (H+L)/2 for entry level calculation How The Algorithm Works: ATR Calculation: Captures ATR value at each bar open using specified length parameter, maintaining consistency throughout the bar Direction Determination: Uses different methods based on selected mode - EMA crossover for trend following, or real-time candle color for dynamic positioning Level Calculation: TP level = Base Price + (Direction × TP Multiplier × ATR), SL level = Base Price - (Direction × SL Multiplier × ATR) Visual Management: Creates persistent line objects once, then updates their positions every bar for optimal performance Direction Modes Explained: Trend Following: Uses 5-period and 12-period EMA relationship to determine trend direction (locked at bar open) Bullish Only: Always places TP above and SL below entry (traditional long setup) Bearish Only: Always places TP below and SL above entry (traditional short setup) Candle Based: Dynamically adjusts based on current candle direction - flips in real-time as candle develops Key Input Parameters: ATR Length: Period for ATR calculation (default 14) - longer periods provide smoother volatility measurement TP Multiplier: Take profit distance as multiple of ATR (default 1.0) - higher values target larger profits SL Multiplier: Stop loss distance as multiple of ATR (default 1.0) - higher values allow more room for price movement Base Price: Reference point for level calculations - Open for static entry, Close for dynamic tracking Direction Mode: Method for determining whether TP goes above or below entry level How To Use This Indicator: For Position Sizing: Use the displayed SL distance to calculate appropriate position size based on your risk tolerance For Entry Timing: Wait for price to approach the entry level before taking positions For Risk Management: Set your actual stop loss orders at or near the displayed SL level For Profit Taking: Use the TP level as initial profit target, consider scaling out at this level Mode Selection: Choose Candle Based for scalping and quick reversals, Trend Following for swing trading Visual Style Customization: Line Colors: Customize TP line color (default teal) and SL line color (default orange) for easy identification Line Widths: Adjust TP/SL line thickness (1-5) and entry line thickness (1-3) for visibility preferences Clean Display: Lines extend 3 bars forward from current bar and update position dynamically Best Practices: Use on clean charts without multiple overlapping indicators for clearest visual interpretation Combine with volume analysis and key support/resistance levels for enhanced decision making Adjust ATR length based on your trading timeframe - shorter for scalping, longer for position trading Test different TP/SL multipliers based on the volatility characteristics of your chosen instruments Consider using Trend Following mode during strong trending periods and Candle Based during ranging markets
Indicatore Pine Script®
di TopTradesUA
Prime NumbersPrime Numbers highlights prime numbers (no surprise there 😅), tokens and the recent "active" feature in "input". 🔸 CONCEPTS 🔹 What are Prime Numbers? A prime number (or a prime) is a natural number greater than 1 that is not a product of two smaller natural numbers. Wikipedia: Prime number 🔹 Prime Factorization The fundamental theorem of arithmetic states that every integer larger than 1 can be written as a product of one or more primes. More strongly, this product is unique in the sense that any two prime factorizations of the same number will have the same number of copies of the same primes, although their ordering may differ. So, although there are many different ways of finding a factorization using an integer factorization algorithm, they all must produce the same result. Primes can thus be considered the "basic building blocks" of the natural numbers. Wikipedia: Fundamental theorem of arithmetic Math Is Fun: Prime Factorization We divide a given number by Prime Numbers until only Primes remain. Example: 24 / 2 = 12 | 24 / 3 = 8 12 / 3 = 4 | 8 / 2 = 4 4 / 2 = 2 | 4 / 2 = 2 | 24 = 2 x 3 x 2 | 24 = 3 x 2 x 2 or | or 24 = 2² x 3 | 24 = 2² x 3 In other words, every natural/integer number above 1 has a unique representation as a product of prime numbers, no matter how the number is divided. Only the order can change, but the factors (the basic elements) are always the same. 🔸 USAGE The Prime Numbers publication contains two use cases: Prime Factorization: performed on "close" prices, or a manual chosen number. List Prime Numbers: shows a list of Prime Numbers. The other two options are discussed in the DETAILS chapter: Prime Factorization Without Arrays Find Prime Numbers 🔹 Prime Factorization Users can choose to perform Prime Factorization on close prices or a manually given number. ❗️ Note that this option only applies to close prices above 1, which are also rounded since Prime Factorization can only be performed on natural (integer) numbers above 1. In the image below, the left example shows Prime Factorization performed on each close price for the latest 50 bars (which is set with "Run script only on 'Last x Bars'" -> 50). The right example shows Prime Factorization performed on a manually given number, in this case "1,340,011". This is done only on the last bar. When the "Source" option "close price" is chosen, one can toggle "Also current price", where both the historical and the latest current price are factored. If disabled, only historical prices are factored. Note that, depending on the chosen options, only applicable settings are available, due to a recent feature, namely the parameter "active" in settings. Setting the "Source" option to "Manual - Limited" will factorize any given number between 1 and 1,340,011, the latter being the highest value in the available arrays with primes. Setting to "Manual - Not Limited" enables the user to enter a higher number. If all factors of the manual entered number are in the 1 - 1,340,011 range, these factors will be shown; however, if a factor is higher than 1,340,011, the calculation will stop, after which a warning is shown: The calculated factors are displayed as a label where identical factors are simplified with an exponent notation in superscript. For example 2 x 2 x 2 x 5 x 7 x 7 will be noted as 2³ x 5 x 7² 🔹 List Prime Numbers The "List Prime Numbers" option enables users to enter a number, where the first found Prime Number is shown, together with the next x Prime Numbers ("Amount", max. 200) The highest shown Prime Number is 1,340,011. One can set the number of shown columns to customize the displayed numbers ("Max. columns", max. 20). 🔸 DETAILS The Prime Numbers publication consists out of 4 parts: Prime Factorization Without Arrays Prime Factorization List Prime Numbers Find Prime Numbers The usage of "Prime Factorization" and "List Prime Numbers" is explained above. 🔹 Prime Factorization Without Arrays This option is only there to highlight a hurdle while performing Prime Factorization. The basic method of Prime Factorization is to divide the base number by 2, 3, ... until the result is an integer number. Continue until the remaining number and its factors are all primes. The division should be done by primes, but then you need to know which one is a prime. In practice, one performs a loop from 2 to the base number. Example: Base_number = input.int(24) arr = array.new() n = Base_number go = true while go for i = 2 to n if n % i == 0 if n / i == 1 go := false arr.push(i) label.new(bar_index, high, str.tostring(arr)) else arr.push(i) n /= i break Small numbers won't cause issues, but when performing the calculations on, for example, 124,001 and a timeframe of, for example, 1 hour, the script will struggle and finally give a runtime error. How to solve this? If we use an array with only primes, we need fewer calculations since if we divide by a non-prime number, we have to divide further until all factors are primes. I've filled arrays with prime numbers and made libraries of them. (see chapter "Find Prime Numbers" to know how these primes were found). 🔹 Tokens A hurdle was to fill the libraries with as many prime numbers as possible. Initially, the maximum token limit of a library was 80K. Very recently, that limit was lifted to 100K. Kudos to the TradingView developers! What are tokens? Tokens are the smallest elements of a program that are meaningful to the compiler. They are also known as the fundamental building blocks of the program. I have included a code block below the publication code (// - - - Educational (2) - - - ) which, if copied and made to a library, will contain exactly 100K tokens. Adding more exported functions will throw a "too many tokens" error when saving the library. Subtracting 100K from the shown amount of tokens gives you the amount of used tokens for that particular function. In that way, one can experiment with the impact of each code addition in terms of tokens. For example adding the following code in the library: export a() => a = array.from(1) will result in a 100,041 tokens error, in other words (100,041 - 100,000) that functions contains 41 tokens. Some more examples, some are straightforward, others are not ) // adding these lines in one of the arrays results in x tokens , 1 // 2 tokens , 111, 111, 111 // 12 tokens , 1111 // 5 tokens , 111111111 // 10 tokens , 1111111111111111111 // 20 tokens , 1234567890123456789 // 20 tokens , 1111111111111111111 + 1 // 20 tokens , 1111111111111111111 + 8 // 20 tokens , 1111111111111111111 + 9 // 20 tokens , 1111111111111111111 * 1 // 20 tokens , 1111111111111111111 * 9 // 21 tokens , 9999999999999999999 // 21 tokens , 1111111111111111111 * 10 // 21 tokens , 11111111111111111110 // 21 tokens //adding these functions to the library results in x tokens export f() => 1 // 4 tokens export f() => v = 1 // 4 tokens export f() => var v = 1 // 4 tokens export f() => var v = 1, v // 4 tokens //adding these functions to the library results in x tokens export a() => const arraya = array.from(1) // 42 tokens export a() => arraya = array.from(1) // 42 tokens export a() => a = array.from(1) // 41 tokens export a() => array.from(1) // 32 tokens export a() => a = array.new() // 44 tokens export a() => a = array.new(), a.push(1) // 56 tokens What if we could lower the amount of tokens, so we can export more Prime Numbers? Look at this example: 829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193 Eight numbers contain the same number 8291. If we make a function that removes recurrent values, we get fewer tokens! 829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193 //is transformed to: 829111, 21, 23, 51, 59, 77, 87, 93 The code block below the publication code (// - - - Educational (1) - - - ) shows how these values were reduced. With each step of 100, only the first Prime Number is shown fully. This function could be enhanced even more to reduce recurrent thousands, tens of thousands, etc. Using this technique enables us to export more Prime Numbers. The number of necessary libraries was reduced to half or less. The reduced Prime Numbers are restored using the restoreValues() function, found in the library fikira/Primes_4. 🔹 Find Prime Numbers This function is merely added to show how I filled arrays with Prime Numbers, which were, in turn, added to libraries (after reduction of recurrent values). To know whether a number is a Prime Number, we divide the given number by values of the Primes array (Primes 2 -> max. 1,340,011). Once the division results in an integer, where the divisor is smaller than the dividend, the calculation stops since the given number is not a Prime. When we perform these calculations in a loop, we can check whether a series of numbers is a Prime or not. Each time a number is proven not to be a Prime, the loop starts again with a higher number. Once all Primes of the array are used without the result being an integer, we have found a new Prime Number, which is added to the array. Doing such calculations on one bar will result in a runtime error. To solve this, the findPrimeNumbers() function remembers the index of the array. Once a limit has been reached on 1 bar (for example, the number of iterations), calculations will stop on that bar and restart on the next bar. This spreads the workload over several bars, making it possible to continue these calculations without a runtime error. The result is placed in log.info() , which can be copied and pasted into a hardcoded array of Prime Number values. These settings adjust the amount of workload per bar: Max Size: maximum size of Primes array. Max Bars Runtime: maximum amount of bars where the function is called. Max Numbers To Process Per Bar: maximum numbers to check on each bar, whether they are Prime Numbers. Max Iterations Per Bar: maximum loop calculations per bar. 🔹 The End ❗️ The code and description is written without the help of an LLM, I've only used Grammarly to improve my description (without AI :) )
Indicatore Pine Script®
di fikira
11
Return Volatility (σ) — auto-annualized [v6]Overview This indicator calculates and visualizes the return-based volatility (standard deviation) of any asset, automatically adjusting for your chart's timeframe to provide both absolute and annualized volatility values. It’s designed for traders who want to filter trades, adjust position sizing, and detect volatility events based on statistically significant changes in market activity. Key Features Absolute Volatility (abs σ%) – Standard deviation of returns for the current timeframe (e.g., 1H, 4H, 1D). Annualized Volatility (ann σ%) – Converts abs σ% into an annualized figure for easier cross-timeframe and cross-asset comparison. Relative Volatility (rel σ) – Ratio of current volatility to the long-term average (default: 120 periods). Z-Score – Number of standard deviations the current volatility is above or below its historical average. Auto-Timeframe Adjustment – Detects your chart’s bar size (seconds per bar) and calculates bars/year automatically for crypto’s 24/7 market. Highlight Mode – Optional yellow background when volatility exceeds set thresholds (rel σ ≥ threshold OR z-score ≥ threshold). Alert Conditions – Alerts trigger when relative volatility or z-score exceed defined limits. How It Works Return Calculation Log returns: ln(Pt / Pt-1) (default) or Simple returns: (Pt / Pt-1) – 1 Volatility Measurement Standard deviation of returns over the lookback period N (default: 20 bars). Absolute volatility = σ × 100 (% per bar). Annualization Uses: σₐₙₙ = σ × √(bars/year) × 100 (%) Bars/year auto-calculated based on timeframe: 1H = 8,760 bars/year 4H ≈ 2,190 bars/year 1D = 365 bars/year Relative and Statistical Context Relative σ = Current σ / Historical average σ (baseLen, default: 120) Z-score = (Current σ – Historical average σ) / Std. dev. of σ over baseLen Trading Applications Volatility Filter – Only allow trade entries when volatility exceeds historical norms (trend traders often benefit from this). Risk Management – Reduce position size during high volatility spikes to manage risk; increase size in low-volatility trending environments. Market Scanning – Identify assets with the highest relative volatility for momentum or breakout strategies. Event Detection – Highlight significant volatility surges that may precede large moves. Suggested Settings Lookback (N): 20 bars for short/medium-term trading. Base Length (M): 120 bars to establish long-term volatility baseline. Relative Threshold: 1.5× baseline σ. Z-score Threshold: ≥ 2.0 for statistically significant volatility shifts. Use Log Returns: Recommended for more consistent scaling across prices. Notes & Limitations Volatility measures movement magnitude, not direction. Combine with trend or momentum filters for directional bias. Very low volatility may still produce false breakouts; combine with volume and market structure analysis. Crypto markets trade 24/7 — annualization assumes no market closures; adjust for other asset classes if needed. 💡 Best Practice: Use this indicator as a pre-trade filter for breakout or trend-following strategies, or as a risk control overlay in mean-reversion systems.
Indicatore Pine Script®
di owwmyG0d
Aggregated VolumeHow to Read the “Aggregated Volume” Signal This indicator combines normalized volume, short-term volume bursts, pivot levels, VWAP, and a 200-period EMA to give you a multi-dimensional view of trading activity. Here’s how to interpret each component and synthesize them into actionable insights. 1. Custom Volume Signal (vSignal) • Calculation • vSignal = Sum of over bars, divided by the current price. • A rising vSignal means more volume is being traded per unit of price, signaling growing interest relative to price level. • Plot styling • Bars are lime when (bullish volume days) • Bars are orange when (bearish volume days) How to read it • Trend confirmation: Increasing lime bars alongside rising price suggests buyers in control. • Warning sign: Rising orange bars on a down move indicate accelerating selling pressure. • Divergence: • Price making new highs while vSignal stalls or drops → potential top. • Price making new lows while vSignal holds → potential bottom. 2. Short-Term Volume Bursts Three semi-transparent histograms show how much the last 2, 5, and 10-bar raw volumes exceed (or fall below) the current vSignal: • Blue = vol(2) – vSignal • Green = vol(5) – vSignal • Red = vol(10) – vSignal If a colored bar sits above zero, that lookback’s volume is surging relative to the longer-term average (vSignal). How to read it • Clustered bursts: • Blue + Green + Red above zero → strong, broad-based volume surge. • Great for confirming breakouts and shakeouts. • Isolated burst: • Only Blue (> 0) on a small range bar → might be a false breakout or intrabar squeeze. • Only Red (> 0) on a wide range → institutional involvement; act with caution. 3. Pivot Volume Levels (v & t) • Every 21 bars, the script finds the highest and lowest vSignal values and plots them as shaded price levels: • Magenta area = recent vSignal high (resistance) • Cyan area = recent vSignal low (support) How to read it • Rejection/Break: • Price approaches magenta zone and stalls → sellers defending that volume high. • Break above magenta with high vSignal → likely sustained rally. • Support flip: • Cyan zone hold → buyers stepping in at heavy-volume lows. • Break below cyan with rising vSignal → bearish conviction. 4. Midline Cross (Volume Equilibrium) • A 10-bar SMA of • Drawn as a faint white cross on price How to read it • Above midline → overall volume bias is skewed bullish. • Below midline → bearish volume bias. Crossovers of vSignal through this midline can signal shifts in underlying conviction. 5. VWAP & 200-Period EMA Overlays • VWAP (transparent red if above price, green if below) • EMA(200) plotted as aqua circles How to read them • VWAP tells you the intraday “value area.” • Price above VWAP + rising vSignal = intraday buyers in charge. • Price below VWAP + rising vSignal = aggressive sellers. • EMA(200) gives you the longer-term trend. • Above EMA200 = bullish regime • Below EMA200 = bearish regime 6. Putting It All Together: Example Scenarios 1. Bullish Entry • Price > EMA200 & VWAP is green • vSignal rising in lime • All three short-term bursts above zero • Price near or breaking the magenta pivot with volume confirmation 2. Bearish Entry • Price < EMA200 & VWAP is red • vSignal rising in orange • Two-bar burst (blue) spikes on a down bar • Price failing at magenta pivot or breaking cyan support 3. Divergence Play • Price makes new high, but vSignal peaks lower than last high → look for a reversal. • Price drops to new low, but vSignal stays above its last low → prepare for a bounce. By combining these layers—normalized volume, burst indicators, pivot levels, VWAP, and EMA—you get a clear map of where volume is clustering, which lets you anticipate support/resistance, gauge real interest, and spot potential reversals or breakouts with greater confidence.
Indicatore Pine Script®
di ximi-imibitty
Range Breakout [sgbpulse]Range Breakout 1. Overview The "Range Breakout " indicator is a powerful tool designed to identify and visually display price ranges on your chart using pivot points. It dynamically draws two distinct boxes – an External Range and an Internal Range – helping traders pinpoint potential support and resistance zones. Beyond its visual representation, the indicator offers a comprehensive set of 12 unique breakout alerts, providing real-time notifications for significant price movements outside these defined ranges. Additionally, it integrates RSI and MFI metrics for momentum confirmation. 2. How It Works The indicator operates by identifying pivot points based on user-defined "left" and "right" bar lengths. A high pivot is a bar with a specified number of lower highs both to its left and right, and similarly for a low pivot. External Range: Calculated using longer pivot lengths (default: 15 bars left, 6 bars right). This range represents broader, more significant price consolidation areas. Internal Range: Calculated using shorter pivot lengths (default: 4 bars left, 3 bars right). This range captures tighter, more immediate price consolidations within the broader trend. The External Range will always be greater than or equal to the Internal Range, as it's based on a wider historical context. Both ranges are displayed as transparent boxes on your chart, dynamically adjusting as new pivots are formed. 3. Key Features and Settings Customizable Pivot Lengths: External Range (Left/Right Bars): Adjust sensitivity for identifying the broader price range. Longer lengths lead to more stable, but less frequent, range updates. Internal Range (Left/Right Bars): Adjust sensitivity for the tighter, more immediate price range. Tool Tips: Minimum 6 bars for the External Range, and minimum 2 bars for the Internal Range. Customizable Range Colors: Easily change the background colors of the External and Internal Range boxes to match your chart's aesthetic. Dynamic Range Display: The indicator automatically updates the range boxes as new pivot highs and lows are formed, always presenting the most current valid ranges. RSI / MFI Settings: Timeframe Source: Select the timeframe for RSI and MFI calculation. - Chart: Calculation based on the current chart timeframe. - Daily: Always calculated based on the daily ("D") timeframe, even if the chart is on a lower timeframe. RSI Length: Period length for RSI calculation (default: 14). RSI Overbought Level: Overbought level for RSI (default: 70.0). RSI Oversold Level: Oversold level for RSI (default: 30.0). MFI Length: Period length for MFI calculation (default: 14). MFI Overbought Level: Overbought level for MFI (default: 80.0). MFI Oversold Level: Oversold level for MFI (default: 20.0). 4. Synergy of Ranges & Breakout Strength The interaction between the External and Internal Ranges provides deep insights into price movement and breakout strength: Immediate Direction: The movement of the Internal Range (up or down) indicates the short-term directional bias within the broader framework of the External Range. Strength Confirmation: A breakout of the External Range, followed by a breakout of the Internal Range, confirms the strength of the move and increases confidence in the breakout. Strong Momentum ("Leaving" Ranges Behind): When price breaks out with exceptionally strong momentum, it continues to move aggressively and does not immediately form new pivots. In such situations, the existing ranges (External and Internal) remain in place while the candles "leave them behind." A "Full Candle" breakout, where the entire candle moves past both ranges, indicates a particularly powerful and decisive move. Momentum (RSI / MFI) as Confirmation: - RSI (Relative Strength Index): Measures the speed and change of price movements. Extreme values (above 70 or below 30) indicate overbought/oversold conditions respectively, confirming strong momentum in a breakout. - MFI (Money Flow Index): Similar to RSI but incorporates volume. Extreme values (above 80 or below 20) indicate strong money flow in/out, reinforcing breakout confirmation. - Importance of Confirmation: If a breakout occurs but momentum indicators do not confirm it (for example, an upside breakout while RSI is declining), this could signal weakness in the move and the risk of a false breakout (Fakeout). 5. Visuals The indicator provides clear visual representations on the chart: Range Boxes: Two dynamic boxes are drawn on the chart: one for the External Range and one for the Internal Range. These boxes update continuously, displaying the current range boundaries based on the latest pivots. They provide an immediate visual indication of support and resistance levels. RSI/MFI Status Labels: Small text labels appear to the right of the current bar, vertically centered. They display the status of RSI and MFI: RSI OB (Overbought), RSI OS (Oversold), MFI OB, MFI OS, along with the exact value. Important: The labels remain on the chart as long as the condition holds (indicator is above/below the level), unlike alerts which mark a singular crossover event. Plotting of Key Values: The indicator plots six invisible series on the chart, primarily to allow the user to view the exact numerical values of: - The upper and lower bounds of the External Range (External High, External Low). - The upper and lower bounds of the Internal Range (Internal High, Internal Low). - The calculated RSI and MFI values (RSI, MFI). These values are accessible for viewing through TradingView's Data Window and also via the Status Line when hovering over the relevant candle. This enables more precise quantitative analysis of range levels and momentum. 6. Comprehensive Breakout Alerts The "Range Breakout " indicator provides 12 distinct alert conditions for breakouts, allowing you to select the required level of confirmation for each alert. All alerts are triggered only upon a fully confirmed bar close (barstate.isconfirmed) to minimize false signals and ensure reliability. All breakout alerts are configured to detect a Crossover/Crossunder of the levels, meaning a specific event where the price moves from one side of the range to the other. External Range Breakout UP - Close: Price closes above the External Range. - Real Body: The entire "real body" of the candle (min of open/close prices) closes above the External Range. - Full Candle: The entire candle (the lowest point of the candle) closes above the External Range. External Range Breakout DOWN - Close: Price closes below the External Range. - Real Body: The entire "real body" of the candle (max of open/close prices) closes below the External Range. - Full Candle: The entire candle (the highest point of the candle) closes below the External Range. Internal Range Breakout UP - Close: Price closes above the Internal Range. - Real Body: The "real body" of the candle closes above the Internal Range. - Full Candle: The entire candle closes above the Internal Range. Internal Range Breakout DOWN - Close: Price closes below the Internal Range. - Real Body: The "real body" of the candle closes below the Internal Range. - Full Candle: The entire candle closes below the Internal Range. 7. Ideal Use Cases This indicator is ideal for traders who: Want to clearly identify and monitor price consolidation zones. Seek confirmation for breakout strategies across various timeframes. Require reliable and automated alerts for potential entry or exit points based on range expansion. 8. Complementary Indicator For even more comprehensive market analysis, we highly recommend using this indicator in conjunction with Market Structure Support & Resistance External/Internal & BoS . This powerful complementary indicator automatically and accurately identifies significant support and resistance levels by locating high and low pivot points, as well as key Pre-Market High/Low levels. Its strength lies in its dynamic adaptability to any timeframe and asset, providing precise and relevant real-time levels while maintaining a clean chart. It also identifies Break of Structure (BoS) to signal potential trend changes or continuations. Using both indicators together provides a robust framework for identifying defined ranges and potential trend shifts, enabling more informed trading decisions. View Market Structure Support & Resistance External/Internal & BoS Indicator 9. Important Note: Trading Risk This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever. Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Indicatore Pine Script®
di sgbpulse
The Sequences of FibonacciThe Sequences of Fibonacci - Advanced Multi-Timeframe Confluence Analysis System THEORETICAL FOUNDATION & MATHEMATICAL INNOVATION The Sequences of Fibonacci represents a revolutionary approach to market analysis that synthesizes classical Fibonacci mathematics with modern adaptive signal processing. This indicator transcends traditional Fibonacci retracement tools by implementing a sophisticated multi-dimensional confluence detection system that reveals hidden market structure through mathematical precision. Core Mathematical Framework Dynamic Fibonacci Grid System: Unlike static Fibonacci tools, this system calculates highest highs and lowest lows across true Fibonacci sequence periods (8, 13, 21, 34, 55 bars) creating a dynamic grid of mathematical support and resistance levels that adapt to market structure in real-time. Multi-Dimensional Confluence Detection: The engine employs advanced mathematical clustering algorithms to identify areas where multiple derived Fibonacci retracement levels (0.382, 0.500, 0.618) from different timeframe perspectives converge. These "Confluence Zones" are mathematically classified by strength: - CRITICAL Zones: 8+ converging Fibonacci levels - HIGH Zones: 6-7 converging levels - MEDIUM Zones: 4-5 converging levels - LOW Zones: 3+ converging levels Adaptive Signal Processing Architecture: The system implements adaptive Stochastic RSI calculations with dynamic overbought/oversold levels that adjust to recent market volatility rather than using fixed thresholds. This prevents false signals during changing market conditions. COMPREHENSIVE FEATURE ARCHITECTURE Quantum Field Visualization System Dynamic Price Field Mathematics: The Quantum Field creates adaptive price channels based on EMA center points and ATR-based amplitude calculations, influenced by the Unified Field metric. This visualization system helps traders understand: - Expected price volatility ranges - Potential overextension zones - Mathematical pressure points in market structure - Dynamic support/resistance boundaries Field Amplitude Calculation: Field Amplitude = ATR × (1 + |Unified Field| / 10) The system generates three quantum levels: - Q⁰ Level: 0.618 × Field Amplitude (Primary channel) - Q¹ Level: 1.0 × Field Amplitude (Secondary boundary) - Q² Level: 1.618 × Field Amplitude (Extreme extension) Advanced Market Analysis Dashboard Unified Field Analysis: A composite metric combining: - Price momentum (40% weighting) - Volume momentum (30% weighting) - Trend strength (30% weighting) Market Resonance Calculation: Measures price-volume correlation over 14 periods to identify harmony between price action and volume participation. Signal Quality Assessment: Synthesizes Unified Field, Market Resonance, and RSI positioning to provide real-time evaluation of setup potential. Tiered Signal Generation Logic Tier 1 Signals (Highest Conviction): Require ALL conditions: - Adaptive StochRSI setup (exiting dynamic OB/OS levels) - Classic StochRSI divergence confirmation - Strong reversal bar pattern (adaptive ATR-based sizing) - Level rejection from Confluence Zone or Fibonacci level - Supportive Unified Field context Tier 2 Signals (Enhanced Opportunity Detection): Generated when Tier 1 conditions aren't met but exceptional circumstances exist: - Divergence candidate patterns (relaxed divergence requirements) - Exceptionally strong reversal bars at critical levels - Enhanced level rejection criteria - Maintained context filtering Intelligent Visualization Features Fractal Matrix Grid: Multi-layer visualization system displaying: - Shadow Layer: Foundational support (width 5) - Glow Layer: Core identification (width 3, white) - Quantum Layer: Mathematical overlay (width 1, dotted) Smart Labeling System: Prevents overlap using ATR-based minimum spacing while providing: - Fibonacci period identification - Topological complexity classification (0, I, II, III) - Exact price levels - Strength indicators (○ ◐ ● ⚡) Wick Pressure Analysis: Dynamic visualization showing momentum direction through: - Multi-beam projection lines - Particle density effects - Progressive transparency for natural flow - Strength-based sizing adaptation PRACTICAL TRADING IMPLEMENTATION Signal Interpretation Framework Entry Protocol: 1. Confluence Zone Approach: Monitor price approaching High/Critical confluence zones 2. Adaptive Setup Confirmation: Wait for StochRSI to exit adaptive OB/OS levels 3. Divergence Verification: Confirm classic or candidate divergence patterns 4. Reversal Bar Assessment: Validate strong rejection using adaptive ATR criteria 5. Context Evaluation: Ensure Unified Field provides supportive environment Risk Management Integration: - Stop Placement: Beyond rejected confluence zone or Fibonacci level - Position Sizing: Based on signal tier and confluence strength - Profit Targets: Next significant confluence zone or quantum field boundary Adaptive Parameter System Dynamic StochRSI Levels: Unlike fixed 80/20 levels, the system calculates adaptive OB/OS based on recent StochRSI range: - Adaptive OB: Recent minimum + (range × OB percentile) - Adaptive OS: Recent minimum + (range × OS percentile) - Lookback Period: Configurable 20-100 bars for range calculation Intelligent ATR Adaptation: Bar size requirements adjust to market volatility: - High Volatility: Reduced multiplier (bars naturally larger) - Low Volatility: Increased multiplier (ensuring significance) - Base Multiplier: 0.6× ATR with adaptive scaling Optimization Guidelines Timeframe-Specific Settings: Scalping (1-5 minutes): - Fibonacci Rejection Sensitivity: 0.3-0.8 - Confluence Threshold: 2-3 levels - StochRSI Lookback: 20-30 bars Day Trading (15min-1H): - Fibonacci Rejection Sensitivity: 0.5-1.2 - Confluence Threshold: 3-4 levels - StochRSI Lookback: 40-60 bars Swing Trading (4H-1D): - Fibonacci Rejection Sensitivity: 1.0-2.0 - Confluence Threshold: 4-5 levels - StochRSI Lookback: 60-80 bars Asset-Specific Optimization: Cryptocurrency: - Higher rejection sensitivity (1.0-2.5) for volatile conditions - Enable Tier 2 signals for increased opportunity detection - Shorter adaptive lookbacks for rapid market changes Forex Major Pairs: - Moderate sensitivity (0.8-1.5) for stable trending - Focus on Higher/Critical confluence zones - Longer lookbacks for institutional flow detection Stock Indices: - Conservative sensitivity (0.5-1.0) for institutional participation - Standard confluence thresholds - Balanced adaptive parameters IMPORTANT USAGE CONSIDERATIONS Realistic Performance Expectations This indicator provides probabilistic advantages based on mathematical confluence analysis, not guaranteed outcomes. Signal quality varies with market conditions, and proper risk management remains essential regardless of signal tier. Understanding Adaptive Features: - Adaptive parameters react to historical data, not future market conditions - Dynamic levels adjust to past volatility patterns - Signal quality reflects mathematical alignment probability, not certainty Market Context Awareness: - Strong trending markets may produce fewer reversal signals - Range-bound conditions typically generate more confluence opportunities - News events and fundamental factors can override technical analysis Educational Value Mathematical Concepts Introduced: - Multi-dimensional confluence analysis - Adaptive signal processing techniques - Dynamic parameter optimization - Mathematical field theory applications in trading - Advanced Fibonacci sequence applications Skill Development Benefits: - Understanding market structure through mathematical lens - Recognition of multi-timeframe confluence principles - Appreciation for adaptive vs. static analysis methods - Integration of classical Fibonacci with modern signal processing UNIQUE INNOVATIONS First-Ever Implementations 1. True Fibonacci Sequence Periods: First indicator using authentic Fibonacci numbers (8,13,21,34,55) for timeframe analysis 2. Mathematical Confluence Clustering: Advanced algorithm identifying true Fibonacci level convergence 3. Adaptive StochRSI Boundaries: Dynamic OB/OS levels replacing fixed thresholds 4. Tiered Signal Architecture: Democratic signal weighting with quality classification 5. Quantum Field Price Visualization: Mathematical field representation of price dynamics Visualization Breakthroughs - Multi-Layer Fibonacci Grid: Three-layer rendering with intelligent spacing - Dynamic Confluence Zones: Strength-based color coding and sizing - Adaptive Parameter Display: Real-time visualization of dynamic calculations - Mathematical Field Effects: Quantum-inspired price channel visualization - Progressive Transparency Systems: Natural visual flow without chart clutter COMPREHENSIVE DASHBOARD SYSTEM Multi-Size Display Options Small Dashboard: Core metrics for mobile/limited screen space Normal Dashboard: Balanced information density for standard desktop use Large Dashboard: Complete analysis suite including adaptive parameter values Real-Time Metrics Tracking Market Analysis Section: - Unified Field strength with visual meter - Market Resonance percentage - Signal Quality assessment with emoji indicators - Market Bias classification (Bullish/Bearish/Neutral) Confluence Intelligence: - Total active zones count - High/Critical zone identification - Nearest zone distance and strength - Price-to-zone ATR measurement Adaptive Parameters (Large Dashboard): - Current StochRSI OB/OS levels - Active ATR multiplier for bar sizing - Volatility ratio for adaptive scaling - Real-time StochRSI positioning TECHNICAL SPECIFICATIONS Pine Script Version: v5 (Latest) Calculation Method: Real-time with confirmed bar processing Maximum Objects: 500 boxes, 500 lines, 500 labels Dashboard Positions: 4 corner options with size selection Visual Themes: Quantum, Holographic, Crystalline, Plasma Alert Integration: Complete alert system for all signal types Performance Optimizations: - Efficient confluence zone calculation using advanced clustering - Smart label spacing prevents overlap - Progressive transparency for visual clarity - Memory-optimized array management EDUCATIONAL FRAMEWORK Learning Progression Beginner Level: - Understanding Fibonacci sequence applications - Recognition of confluence zone concepts - Basic signal interpretation - Dashboard metric comprehension Intermediate Level: - Adaptive parameter optimization - Multi-timeframe confluence analysis - Signal quality assessment techniques - Risk management integration Advanced Level: - Mathematical field theory applications - Custom parameter optimization strategies - Market regime adaptation techniques - Professional trading system integration DEVELOPMENT ACKNOWLEDGMENT Special acknowledgment to @AlgoTrader90 - the foundational concepts of this system came from him and we developed it through a collaborative discussions about multi-timeframe Fibonacci analysis. While the original framework came from AlgoTrader90's innovative approach, this implementation represents a complete evolution of the logic with enhanced mathematical precision, adaptive parameters, and sophisticated signal filtering to deliver meaningful, actionable trading signals. CONCLUSION The Sequences of Fibonacci represents a quantum leap in technical analysis, successfully merging classical Fibonacci mathematics with cutting-edge adaptive signal processing. Through sophisticated confluence detection, intelligent parameter adaptation, and comprehensive market analysis, this system provides traders with unprecedented insight into market structure and potential reversal points. The mathematical foundation ensures lasting relevance while the adaptive features maintain effectiveness across changing market conditions. From the dynamic Fibonacci grid to the quantum field visualization, every component reflects a commitment to mathematical precision, visual elegance, and practical utility. Whether you're a beginner seeking to understand market confluence or an advanced trader requiring sophisticated analytical tools, this system provides the mathematical framework for informed decision-making based on time-tested Fibonacci principles enhanced with modern computational techniques. Trade with mathematical precision. Trade with the power of confluence. Trade with The Sequences of Fibonacci. "Mathematics is the language with which God has written the universe. In markets, Fibonacci sequences reveal the hidden harmonies that govern price movement, and those who understand these mathematical relationships hold the key to anticipating market behavior." * Galileo Galilei (adapted for modern markets) — Dskyz, Trade with insight. Trade with anticipation.
Indicatore Pine Script®
di DskyzInvestments
4
Multifractal Forecast [ScorsoneEnterprises]Multifractal Forecast Indicator The Multifractal Forecast is an indicator designed to model and forecast asset price movements using a multifractal framework. It uses concepts from fractal geometry and stochastic processes, specifically the Multifractal Model of Asset Returns (MMAR) and fractional Brownian motion (fBm), to generate price forecasts based on historical price data. The indicator visualizes potential future price paths as colored lines, providing traders with a probabilistic view of price trends over a specified trading time scale. Below is a detailed breakdown of the indicator’s functionality, inputs, calculations, and visualization. Overview Purpose: The indicator forecasts future price movements by simulating multiple price paths based on a multifractal model, which accounts for the complex, non-linear behavior of financial markets. Key Concepts: Multifractal Model of Asset Returns (MMAR): Models price movements as a multifractal process, capturing varying degrees of volatility and self-similarity across different time scales. Fractional Brownian Motion (fBm): A generalization of Brownian motion that incorporates long-range dependence and self-similarity, controlled by the Hurst exponent. Binomial Cascade: Used to model trading time, introducing heterogeneity in time scales to reflect market activity bursts. Hurst Exponent: Measures the degree of long-term memory in the price series (persistence, randomness, or mean-reversion). Rescaled Range (R/S) Analysis: Estimates the Hurst exponent to quantify the fractal nature of the price series. Inputs The indicator allows users to customize its behavior through several input parameters, each influencing the multifractal model and forecast generation: Maximum Lag (max_lag): Type: Integer Default: 50 Minimum: 5 Purpose: Determines the maximum lag used in the rescaled range (R/S) analysis to calculate the Hurst exponent. A higher lag increases the sample size for Hurst estimation but may smooth out short-term dynamics. 2 to the n values in the Multifractal Model (n): Type: Integer Default: 4 Purpose: Defines the resolution of the multifractal model by setting the size of arrays used in calculations (N = 2^n). For example, n=4 results in N=16 data points. Larger n increases computational complexity and detail but may exceed Pine Script’s array size limits (capped at 100,000). Multiplier for Binomial Cascade (m): Type: Float Default: 0.8 Purpose: Controls the asymmetry in the binomial cascade, which models trading time. The multiplier m (and its complement 2.0 - m) determines how mass is distributed across time scales. Values closer to 1 create more balanced cascades, while values further from 1 introduce more variability. Length Scale for fBm (L): Type: Float Default: 100,000.0 Purpose: Scales the fractional Brownian motion output, affecting the amplitude of simulated price paths. Larger values increase the magnitude of forecasted price movements. Cumulative Sum (cum): Type: Integer (0 or 1) Default: 1 Purpose: Toggles whether the fBm output is cumulatively summed (1=On, 0=Off). When enabled, the fBm series is accumulated to simulate a price path with memory, resembling a random walk with long-range dependence. Trading Time Scale (T): Type: Integer Default: 5 Purpose: Defines the forecast horizon in bars (20 bars into the future). It also scales the binomial cascade’s output to align with the desired trading time frame. Number of Simulations (num_simulations): Type: Integer Default: 5 Minimum: 1 Purpose: Specifies how many forecast paths are simulated and plotted. More simulations provide a broader range of possible price outcomes but increase computational load. Core Calculations The indicator combines several mathematical and statistical techniques to generate price forecasts. Below is a step-by-step explanation of its calculations: Log Returns (lgr): The indicator calculates log returns as math.log(close / close ) when both the current and previous close prices are positive. This measures the relative price change in a logarithmic scale, which is standard for financial time series analysis to stabilize variance. Hurst Exponent Estimation (get_hurst_exponent): Purpose: Estimates the Hurst exponent (H) to quantify the degree of long-term memory in the price series. Method: Uses rescaled range (R/S) analysis: For each lag from 2 to max_lag, the function calc_rescaled_range computes the rescaled range: Calculate the mean of the log returns over the lag period. Compute the cumulative deviation from the mean. Find the range (max - min) of the cumulative deviation. Divide the range by the standard deviation of the log returns to get the rescaled range. The log of the rescaled range (log(R/S)) is regressed against the log of the lag (log(lag)) using the polyfit_slope function. The slope of this regression is the Hurst exponent (H). Interpretation: H = 0.5: Random walk (no memory, like standard Brownian motion). H > 0.5: Persistent behavior (trends tend to continue). H < 0.5: Mean-reverting behavior (price tends to revert to the mean). Fractional Brownian Motion (get_fbm): Purpose: Generates a fractional Brownian motion series to model price movements with long-range dependence. Inputs: n (array size 2^n), H (Hurst exponent), L (length scale), cum (cumulative sum toggle). Method: Computes covariance for fBm using the formula: 0.5 * (|i+1|^(2H) - 2 * |i|^(2H) + |i-1|^(2H)). Uses Hosking’s method (referenced from Columbia University’s implementation) to generate fBm: Initializes arrays for covariance (cov), intermediate calculations (phi, psi), and output. Iteratively computes the fBm series by incorporating a random term scaled by the variance (v) and covariance structure. Applies scaling based on L / N^H to adjust the amplitude. Optionally applies cumulative summation if cum = 1 to produce a path with memory. Output: An array of 2^n values representing the fBm series. Binomial Cascade (get_binomial_cascade): Purpose: Models trading time (theta) to account for non-uniform market activity (e.g., bursts of volatility). Inputs: n (array size 2^n), m (multiplier), T (trading time scale). Method: Initializes an array of size 2^n with values of 1.0. Iteratively applies a binomial cascade: For each block (from 0 to n-1), splits the array into segments. Randomly assigns a multiplier (m or 2.0 - m) to each segment, redistributing mass. Normalizes the array by dividing by its sum and scales by T. Checks for array size limits to prevent Pine Script errors. Output: An array (theta) representing the trading time, which warps the fBm to reflect market activity. Interpolation (interpolate_fbm): Purpose: Maps the fBm series to the trading time scale to produce a forecast. Method: Computes the cumulative sum of theta and normalizes it to . Interpolates the fBm series linearly based on the normalized trading time. Ensures the output aligns with the trading time scale (T). Output: An array of interpolated fBm values representing log returns over the forecast horizon. Price Path Generation: For each simulation (up to num_simulations): Generates an fBm series using get_fbm. Interpolates it with the trading time (theta) using interpolate_fbm. Converts log returns to price levels: Starts with the current close price. For each step i in the forecast horizon (T), computes the price as prev_price * exp(log_return). Output: An array of price levels for each simulation. Visualization: Trigger: Updates every T bars when the bar state is confirmed (barstate.isconfirmed). Process: Clears previous lines from line_array. For each simulation, plots a line from the current bar’s close price to the forecasted price at bar_index + T. Colors the line using a gradient (color.from_gradient) based on the final forecasted price relative to the minimum and maximum forecasted prices across all simulations (red for lower prices, teal for higher prices). Output: Multiple colored lines on the chart, each representing a possible price path over the next T bars. How It Works on the Chart Initialization: On each bar, the indicator calculates the Hurst exponent (H) using historical log returns and prepares the trading time (theta) using the binomial cascade. Forecast Generation: Every T bars, it generates num_simulations price paths: Each path starts at the current close price. Uses fBm to model log returns, warped by the trading time. Converts log returns to price levels. Plotting: Draws lines from the current bar to the forecasted price T bars ahead, with colors indicating relative price levels. Dynamic Updates: The forecast updates every T bars, replacing old lines with new ones based on the latest price data and calculations. Key Features Multifractal Modeling: Captures complex market dynamics by combining fBm (long-range dependence) with a binomial cascade (non-uniform time). Customizable Parameters: Allows users to adjust the forecast horizon, model resolution, scaling, and number of simulations. Probabilistic Forecast: Multiple simulations provide a range of possible price outcomes, helping traders assess uncertainty. Visual Clarity: Gradient-colored lines make it easy to distinguish bullish (teal) and bearish (red) forecasts. Potential Use Cases Trend Analysis: Identify potential price trends or reversals based on the direction and spread of forecast lines. Risk Assessment: Evaluate the range of possible price outcomes to gauge market uncertainty. Volatility Analysis: The Hurst exponent and binomial cascade provide insights into market persistence and volatility clustering. Limitations Computational Intensity: Large values of n or num_simulations may slow down execution or hit Pine Script’s array size limits. Randomness: The binomial cascade and fBm rely on random terms (math.random), which may lead to variability between runs. Assumptions: The model assumes log-normal price movements and fractal behavior, which may not always hold in extreme market conditions. Adjusting Inputs: Set max_lag based on the desired depth of historical analysis. Adjust n for model resolution (start with 4–6 to avoid performance issues). Tune m to control trading time variability (0.5–1.5 is typical). Set L to scale the forecast amplitude (experiment with values like 10,000–1,000,000). Choose T based on your trading horizon (20 for short-term, 50 for longer-term for example). Select num_simulations for the number of forecast paths (5–10 is reasonable for visualization). Interpret Output: Teal lines suggest bullish scenarios, red lines suggest bearish scenarios. A wide spread of lines indicates high uncertainty; convergence suggests a stronger trend. Monitor Updates: Forecasts update every T bars, so check the chart periodically for new projections. Chart Examples This is a daily AMEX:SPY chart with default settings. We see the simulations being done every T bars and they provide a range for us to analyze with a few simulations still in the range. On this intraday PEPPERSTONE:COCOA chart I modified the Length Scale for fBm, L, parameter to be 1000 from 100000. Adjusting the parameter as you switch between timeframes can give you more contextual simulations. On BITSTAMP:ETHUSD I modified the L to be 1000000 to have a more contextual set of simulations with crypto's volatile nature. With L at 100000 we see the range for NASDAQ:TLT is correctly simulated. The recent pop stays within the bounds of the highest simulation. Note this is a cherry picked example to show the power and potential of these simulations. Technical Notes Error Handling: The script includes checks for array size limits and division by zero (math.abs(denominator) > 1e-10, v := math.max(v, 1e-10)). External Reference: The fBm implementation is based on Hosking’s method (www.columbia.edu), ensuring a robust algorithm. Conclusion The Multifractal Forecast is a powerful tool for traders seeking to model complex market dynamics using a multifractal framework. By combining fBm, binomial cascades, and Hurst exponent analysis, it generates probabilistic price forecasts that account for long-range dependence and non-uniform market activity. Its customizable inputs and clear visualizations make it suitable for both technical analysis and strategy development, though users should be mindful of its computational demands and parameter sensitivity. For optimal use, experiment with input settings and validate forecasts against other technical indicators or market conditions.
Indicatore Pine Script®
di ScorsoneEnterprises
FvgTypes█ OVERVIEW This library serves as a foundational module for Pine Script™ projects focused on Fair Value Gaps (FVGs). Its primary purpose is to define and centralize custom data structures (User-Defined Types - UDTs) and enumerations that are utilized across various components of an FVG analysis system. By providing standardized types for FVG characteristics and drawing configurations, it promotes code consistency, readability, and easier maintenance within a larger FVG indicator or strategy. █ CONCEPTS The library introduces several key data structures (User-Defined Types - UDTs) and an enumeration to organize Fair Value Gap (FVG) related data logically. These types are central to the functioning of FVG analysis tools built upon this library. Timeframe Categorization (`tfType` Enum) To manage and differentiate FVGs based on their timeframe of origin, the `tfType` enumeration is defined. It includes: `LTF`: Low Timeframe (typically the current chart). `MTF`: Medium Timeframe. `HTF`: High Timeframe. This allows for distinct logic and visual settings to be applied depending on the FVG's source timeframe. FVG Data Encapsulation (`fvgObject` UDT) The `fvgObject` is a comprehensive UDT designed to encapsulate all pertinent information and state for an individual Fair Value Gap throughout its lifecycle. Instead of listing every field, its conceptual structure can be understood as holding: Core Definition: The FVG's fundamental price levels (top, bottom) and its formation time (`startTime`). Classification Attributes: Characteristics such as its direction (`isBullish`) and whether it qualifies as a Large Volume FVG (`isLV`), along with its originating timeframe category (`tfType`). Lifecycle State: Current status indicators including full mitigation (`isMitigated`, `mitigationTime`), partial fill levels (`currentTop`, `currentBottom`), midline interaction (`isMidlineTouched`), and overall visibility (`isVisible`). Drawing Identifiers: References (`boxId`, `midLineId`, `mitLineLabelId`, etc.) to the actual graphical objects drawn on the chart to represent the FVG and its components. Optimization Cache: Previous-bar state values (`prevIsMitigated`, `prevCurrentTop`, etc.) crucial for optimizing drawing updates by avoiding redundant operations. This comprehensive structure facilitates easy access to all FVG-related information through a single object, reducing code complexity and improving manageability. Drawing Configuration (`drawSettings` UDT) The `drawSettings` UDT centralizes all user-configurable parameters that dictate the visual appearance of FVGs across different timeframes. It's typically populated from script inputs and conceptually groups settings for: General Behavior: Global FVG classification toggles (e.g., `shouldClassifyLV`) and general display rules (e.g., `shouldHideMitigated`). FVG Type Specific Colors: Colors for standard and Large Volume FVGs, both active and mitigated (e.g., `lvBullColor`, `mitigatedBearBoxColor`). Timeframe-Specific Visuals (LTF, MTF, HTF): Detailed parameters for each timeframe category, covering FVG boxes (visibility, colors, extension, borders, labels), midlines (visibility, style, color), and mitigation lines (visibility, style, color, labels, persistence after mitigation). Contextual Information: The current bar's time (`currentTime`) for accurate positioning of time-dependent drawing elements and timeframe display strings (`tfString`, `mtfTfString`, `htfTfString`). This centralized approach allows for extensive customization of FVG visuals and simplifies the management of drawing parameters within the main script. Such centralization also enhances the maintainability of the visual aspects of the FVG system. █ NOTES User-Defined Types (UDTs): This library extensively uses UDTs (`fvgObject`, `drawSettings`) to group related data. This improves code organization and makes it easier to pass complex data between functions and libraries. Mutability and Reference Behavior of UDTs: When UDT instances are passed to functions or methods in other libraries (like `fvgObjectLib`), those functions might modify the fields of the passed object if they are not explicitly designed to return new instances. This is because UDTs are passed by reference and are mutable in Pine Script™. Users should be aware of this standard behavior to prevent unintended side effects. Optimization Fields: The `prev_*` fields in `fvgObject` are crucial for performance optimization in the drawing logic. They help avoid unnecessary redrawing of FVG elements if their state or relevant settings haven't changed. No Direct Drawing Logic: `FvgTypes` itself does not contain any drawing logic. It solely defines the data structures. The actual drawing and manipulation of these objects are handled by other libraries (e.g., `fvgObjectLib`). Centralized Definitions: By defining these types in a separate library, any changes to the structure of FVG data or settings can be made in one place, ensuring consistency across all dependent scripts and libraries. █ EXPORTED TYPES fvgObject   fvgObject Represents a Fair Value Gap (FVG) object. Fields:      top (series float) : The top price level of the FVG.      bottom (series float) : The bottom price level of the FVG.      startTime (series int) : The start time (timestamp) of the bar where the FVG formed.      isBullish (series bool) : Indicates if the FVG is bullish (true) or bearish (false).      isLV (series bool) : Indicates if the FVG is a Large Volume FVG.      tfType (series tfType) : The timeframe type (LTF, MTF, HTF) to which this FVG belongs.      isMitigated (series bool) : Indicates if the FVG has been fully mitigated.      mitigationTime (series int) : The time (timestamp) when the FVG was mitigated.      isVisible (series bool) : The current visibility status of the FVG, typically managed by drawing logic based on filters.      isMidlineTouched (series bool) : Indicates if the price has touched the FVG's midline (50% level).      currentTop (series float) : The current top level of the FVG after partial fills.      currentBottom (series float) : The current bottom level of the FVG after partial fills.      boxId (series box) : The drawing ID for the main FVG box.      mitigatedBoxId (series box) : The drawing ID for the box representing the partially filled (mitigated) area.      midLineId (series line) : The drawing ID for the FVG's midline.      mitLineId (series line) : The drawing ID for the FVG's mitigation line.      boxLabelId (series label) : The drawing ID for the FVG box label.      mitLineLabelId (series label) : The drawing ID for the mitigation line label.      testedBoxId (series box) : The drawing ID for the box of a fully mitigated (tested) FVG, if kept visible.      keptMitLineId (series line) : The drawing ID for a mitigation line that is kept after full mitigation.      prevIsMitigated (series bool) : Stores the isMitigated state from the previous bar for optimization.      prevCurrentTop (series float) : Stores the currentTop value from the previous bar for optimization.      prevCurrentBottom (series float) : Stores the currentBottom value from the previous bar for optimization.      prevIsVisible (series bool) : Stores the visibility status from the previous bar for optimization (derived from isVisibleNow passed to updateDrawings).      prevIsMidlineTouched (series bool) : Stores the isMidlineTouched status from the previous bar for optimization. drawSettings   drawSettings A structure containing settings for drawing FVGs. Fields:      shouldClassifyLV (series bool) : Whether to classify FVGs as Large Volume (LV) based on ATR.      shouldHideMitigated (series bool) : Whether to hide FVG boxes once they are fully mitigated.      currentTime (series int) : The current bar's time, used for extending drawings.      lvBullColor (series color) : Color for Large Volume Bullish FVGs.      mitigatedLvBullColor (series color) : Color for mitigated Large Volume Bullish FVGs.      lvBearColor (series color) : Color for Large Volume Bearish FVGs.      mitigatedLvBearColor (series color) : Color for mitigated Large Volume Bearish FVGs.      shouldShowBoxes (series bool) : Whether to show FVG boxes for the LTF.      bullBoxColor (series color) : Color for LTF Bullish FVG boxes.      mitigatedBullBoxColor (series color) : Color for mitigated LTF Bullish FVG boxes.      bearBoxColor (series color) : Color for LTF Bearish FVG boxes.      mitigatedBearBoxColor (series color) : Color for mitigated LTF Bearish FVG boxes.      boxLengthBars (series int) : Length of LTF FVG boxes in bars (if not extended).      shouldExtendBoxes (series bool) : Whether to extend LTF FVG boxes to the right.      shouldShowCurrentTfBoxLabels (series bool) : Whether to show labels on LTF FVG boxes.      shouldShowBoxBorder (series bool) : Whether to show a border for LTF FVG boxes.      boxBorderWidth (series int) : Border width for LTF FVG boxes.      boxBorderStyle (series string) : Border style for LTF FVG boxes (e.g., line.style_solid).      boxBorderColor (series color) : Border color for LTF FVG boxes.      shouldShowMidpoint (series bool) : Whether to show the midline (50% level) for LTF FVGs.      midLineWidthInput (series int) : Width of the LTF FVG midline.      midpointLineStyleInput (series string) : Style of the LTF FVG midline.      midpointColorInput (series color) : Color of the LTF FVG midline.      shouldShowMitigationLine (series bool) : Whether to show the mitigation line for LTF FVGs. (Line always extends if shown)      mitLineWidthInput (series int) : Width of the LTF FVG mitigation line.      mitigationLineStyleInput (series string) : Style of the LTF FVG mitigation line.      mitigationLineColorInput (series color) : Color of the LTF FVG mitigation line.      shouldShowCurrentTfMitLineLabels (series bool) : Whether to show labels on LTF FVG mitigation lines.      currentTfMitLineLabelOffsetX (series float) : The horizontal offset value for the LTF mitigation line's label.      shouldKeepMitigatedLines (series bool) : Whether to keep showing mitigation lines of fully mitigated LTF FVGs.      mitigatedMitLineColor (series color) : Color for kept mitigation lines of mitigated LTF FVGs.      tfString (series string) : Display string for the LTF (e.g., "Current TF").      shouldShowMtfBoxes (series bool) : Whether to show FVG boxes for the MTF.      mtfBullBoxColor (series color) : Color for MTF Bullish FVG boxes.      mtfMitigatedBullBoxColor (series color) : Color for mitigated MTF Bullish FVG boxes.      mtfBearBoxColor (series color) : Color for MTF Bearish FVG boxes.      mtfMitigatedBearBoxColor (series color) : Color for mitigated MTF Bearish FVG boxes.      mtfBoxLengthBars (series int) : Length of MTF FVG boxes in bars (if not extended).      shouldExtendMtfBoxes (series bool) : Whether to extend MTF FVG boxes to the right.      shouldShowMtfBoxLabels (series bool) : Whether to show labels on MTF FVG boxes.      shouldShowMtfBoxBorder (series bool) : Whether to show a border for MTF FVG boxes.      mtfBoxBorderWidth (series int) : Border width for MTF FVG boxes.      mtfBoxBorderStyle (series string) : Border style for MTF FVG boxes.      mtfBoxBorderColor (series color) : Border color for MTF FVG boxes.      shouldShowMtfMidpoint (series bool) : Whether to show the midline for MTF FVGs.      mtfMidLineWidthInput (series int) : Width of the MTF FVG midline.      mtfMidpointLineStyleInput (series string) : Style of the MTF FVG midline.      mtfMidpointColorInput (series color) : Color of the MTF FVG midline.      shouldShowMtfMitigationLine (series bool) : Whether to show the mitigation line for MTF FVGs. (Line always extends if shown)      mtfMitLineWidthInput (series int) : Width of the MTF FVG mitigation line.      mtfMitigationLineStyleInput (series string) : Style of the MTF FVG mitigation line.      mtfMitigationLineColorInput (series color) : Color of the MTF FVG mitigation line.      shouldShowMtfMitLineLabels (series bool) : Whether to show labels on MTF FVG mitigation lines.      mtfMitLineLabelOffsetX (series float) : The horizontal offset value for the MTF mitigation line's label.      shouldKeepMtfMitigatedLines (series bool) : Whether to keep showing mitigation lines of fully mitigated MTF FVGs.      mtfMitigatedMitLineColor (series color) : Color for kept mitigation lines of mitigated MTF FVGs.      mtfTfString (series string) : Display string for the MTF (e.g., "MTF").      shouldShowHtfBoxes (series bool) : Whether to show FVG boxes for the HTF.      htfBullBoxColor (series color) : Color for HTF Bullish FVG boxes.      htfMitigatedBullBoxColor (series color) : Color for mitigated HTF Bullish FVG boxes.      htfBearBoxColor (series color) : Color for HTF Bearish FVG boxes.      htfMitigatedBearBoxColor (series color) : Color for mitigated HTF Bearish FVG boxes.      htfBoxLengthBars (series int) : Length of HTF FVG boxes in bars (if not extended).      shouldExtendHtfBoxes (series bool) : Whether to extend HTF FVG boxes to the right.      shouldShowHtfBoxLabels (series bool) : Whether to show labels on HTF FVG boxes.      shouldShowHtfBoxBorder (series bool) : Whether to show a border for HTF FVG boxes.      htfBoxBorderWidth (series int) : Border width for HTF FVG boxes.      htfBoxBorderStyle (series string) : Border style for HTF FVG boxes.      htfBoxBorderColor (series color) : Border color for HTF FVG boxes.      shouldShowHtfMidpoint (series bool) : Whether to show the midline for HTF FVGs.      htfMidLineWidthInput (series int) : Width of the HTF FVG midline.      htfMidpointLineStyleInput (series string) : Style of the HTF FVG midline.      htfMidpointColorInput (series color) : Color of the HTF FVG midline.      shouldShowHtfMitigationLine (series bool) : Whether to show the mitigation line for HTF FVGs. (Line always extends if shown)      htfMitLineWidthInput (series int) : Width of the HTF FVG mitigation line.      htfMitigationLineStyleInput (series string) : Style of the HTF FVG mitigation line.      htfMitigationLineColorInput (series color) : Color of the HTF FVG mitigation line.      shouldShowHtfMitLineLabels (series bool) : Whether to show labels on HTF FVG mitigation lines.      htfMitLineLabelOffsetX (series float) : The horizontal offset value for the HTF mitigation line's label.      shouldKeepHtfMitigatedLines (series bool) : Whether to keep showing mitigation lines of fully mitigated HTF FVGs.      htfMitigatedMitLineColor (series color) : Color for kept mitigation lines of mitigated HTF FVGs.      htfTfString (series string) : Display string for the HTF (e.g., "HTF").
Libreria Pine Script®
di no1x
Institutional Volume Profile# Institutional Volume Profile (IVP) - Advanced Volume Analysis Indicator ## Overview The Institutional Volume Profile (IVP) is a sophisticated technical analysis tool that combines traditional volume profile analysis with institutional volume detection algorithms. This indicator helps traders identify key price levels where significant institutional activity has occurred, providing insights into market structure and potential support/resistance zones. ## Key Features ### 🎯 Volume Profile Analysis - **Point of Control (POC)**: Identifies the price level with the highest volume activity - **Value Area**: Highlights the price range containing a specified percentage (default 70%) of total volume - **Multi-Row Distribution**: Displays volume distribution across 10-50 price levels for detailed analysis - **Customizable Period**: Analyze volume profiles over 10-500 bars ### 🏛️ Institutional Volume Detection - **Pocket Pivot Volume (PPV)**: Detects bullish institutional buying when up-volume exceeds recent down-volume peaks - **Pivot Negative Volume (PNV)**: Identifies bearish institutional selling when down-volume exceeds recent up-volume peaks - **Accumulation Detection**: Spots potential accumulation phases with high volume and narrow price ranges - **Distribution Analysis**: Identifies distribution patterns with high volume but minimal price movement ### 🎨 Visual Customization Options - **Multiple Color Schemes**: Heat Map, Institutional, Monochrome, and Rainbow themes - **Bar Styles**: Solid, Gradient, Outlined, and 3D Effect rendering - **Volume Intensity Display**: Visual intensity based on volume magnitude - **Flexible Positioning**: Left or right side profile placement - **Current Price Highlighting**: Real-time price level indication ### 📊 Advanced Visual Features - **Volume Labels**: Display volume amounts at key price levels - **Gradient Effects**: Multi-step gradient rendering for enhanced visibility - **3D Styling**: Shadow effects for professional appearance - **Opacity Control**: Adjustable transparency (10-100%) - **Border Customization**: Configurable border width and styling ## How It Works ### Volume Distribution Algorithm The indicator analyzes each bar within the specified period and distributes its volume proportionally across the price levels it touches. This creates an accurate representation of where trading activity has been concentrated. ### Institutional Detection Logic - **PPV Trigger**: Current up-bar volume > highest down-volume in lookback period + above volume MA - **PNV Trigger**: Current down-bar volume > highest up-volume in lookback period + above volume MA - **Accumulation**: High volume + narrow range + bullish close - **Distribution**: Very high volume + minimal price movement ### Value Area Calculation Starting from the POC, the algorithm expands both upward and downward, adding volume until reaching the specified percentage of total volume (default 70%). ## Configuration Parameters ### Profile Settings - **Profile Period**: 10-500 bars (default: 50) - **Number of Rows**: 10-50 levels (default: 24) - **Profile Width**: 10-100% of screen (default: 30%) - **Value Area %**: 50-90% (default: 70%) ### Institutional Analysis - **PPV Lookback Days**: 5-20 periods (default: 10) - **Volume MA Length**: 10-200 periods (default: 50) - **Institutional Threshold**: 1.0-2.0x multiplier (default: 1.2) ### Visual Controls - **Bar Style**: Solid, Gradient, Outlined, 3D Effect - **Color Scheme**: Heat Map, Institutional, Monochrome, Rainbow - **Profile Position**: Left or Right side - **Opacity**: 10-100% - **Show Labels**: Volume amount display toggle ## Interpretation Guide ### Volume Profile Elements - **Thick Horizontal Bars**: High volume nodes (strong support/resistance) - **Thin Horizontal Bars**: Low volume nodes (weak levels) - **White Line (POC)**: Strongest support/resistance level - **Blue Highlighted Area**: Value Area (fair value zone) ### Institutional Signals - **Blue Triangles (PPV)**: Bullish institutional buying detected - **Orange Triangles (PNV)**: Bearish institutional selling detected - **Color-Coded Bars**: Different colors indicate institutional activity types ### Color Scheme Meanings - **Heat Map**: Red (high volume) → Orange → Yellow → Gray (low volume) - **Institutional**: Blue (PPV), Orange (PNV), Aqua (Accumulation), Yellow (Distribution) - **Monochrome**: Grayscale intensity based on volume - **Rainbow**: Color-coded by price level position ## Trading Applications ### Support and Resistance - POC acts as dynamic support/resistance - High volume nodes indicate strong price levels - Low volume areas suggest potential breakout zones ### Institutional Activity - PPV above Value Area: Strong bullish signal - PNV below Value Area: Strong bearish signal - Accumulation patterns: Potential upward breakouts - Distribution patterns: Potential downward pressure ### Market Structure Analysis - Value Area defines fair value range - Profile shape indicates market sentiment - Volume gaps suggest potential price targets ## Alert Conditions - PPV Detection at current price level - PNV Detection at current price level - PPV above Value Area (strong bullish) - PNV below Value Area (strong bearish) ## Best Practices 1. Use multiple timeframes for confirmation 2. Combine with price action analysis 3. Pay attention to volume context (above/below average) 4. Monitor institutional signals near key levels 5. Consider overall market conditions ## Technical Notes - Maximum 500 boxes and 100 labels for optimal performance - Real-time calculations update on each bar close - Historical analysis uses complete bar data - Compatible with all TradingView chart types and timeframes --- *This indicator is designed for educational and informational purposes. Always combine with other analysis methods and risk management strategies.*
Indicatore Pine Script®
di padavans
5
Test OHLCV LibraryThis indicator, "Test OHLCV Library," serves as a practical example of how to use the OHLCVData library to fetch historical candle data from a specific timeframe (like 4H) in a way that is largely impervious to the chart's currently selected time frame. Here's a breakdown of its purpose and how it addresses request.security limitations: Indicator Purpose: The main goal of this indicator is to demonstrate and verify that the OHLCVData library can reliably provide confirmed historical OHLCV data for a user-specified timeframe (e.g., 4H), and that a collection of these data points (the last 10 completed candles) remains consistent even when the user switches the chart's time frame (e.g., from 5-second to Daily). It does this by: Importing the OHLCVData library. Using the library's getTimeframeData function on every bar of the chart. Checking the isTargetBarClosed flag returned by the library to identify the exact moment a candle in the target timeframe (e.g., 4H) has closed. When isTargetBarClosed is true, it captures the confirmed OHLCV data provided by the library for that moment and stores it in a persistent var array. It maintains a list of the last 10 captured historical 4H candle opens in this array. It displays these last 10 confirmed opens in a table. It uses the isAdjustedToChartTF flag from the library to show a warning if the chart's time frame is higher than the target timeframe, indicating that the data fetched by request.security is being aligned to that higher resolution. Circumventing request.security Limitations: The primary limitation of request.security that this setup addresses is the challenge of getting a consistent, non-repainting collection of historical data points from a different timeframe when the chart's time frame is changed. The Problem: Standard request.security calls, while capable of fetching data from other timeframes, align that data to the bars of the current chart. When you switch the chart's time frame, the set of chart bars changes, and the way the requested data aligns to these new bars changes. If you simply collected data on every chart bar where request.security returned a non-na value, the resulting collection would differ depending on the chart's resolution. Furthermore, using request.security without lookahead=barmerge.lookahead_off or an offset ( ) can lead to repainting on historical bars, where values change as the script recalculates. How the Library/Indicator Setup Helps: Confirmed Data: The OHLCVData library uses lookahead=barmerge.lookahead_off and, more importantly, provides the isTargetBarClosed flag. This flag is calculated using a reliable method (checking for a change in the target timeframe's time series) that accurately identifies the precise chart bar corresponding to the completion of a candle in the target timeframe (e.g., a 4H candle), regardless of the chart's time frame. Precise Capture: The indicator only captures and stores the OHLCV data into its var array when this isTargetBarClosed flag is true. This means it's capturing the confirmed, finalized data for the target timeframe candle at the exact moment it closes. Persistent Storage: The var array in the indicator persists its contents across the bars of the chart's history. As the script runs through the historical bars, it selectively adds confirmed 4H candle data points to this array only when the trigger is met. Impervious Collection: Because the array is populated based on the completion of the target timeframe candles (detected reliably by the library) rather than simply collecting data on every chart bar, the final contents of the array (the list of the last 10 confirmed 4H opens) will be the same regardless of the chart's time frame. The table then displays this static collection. In essence, this setup doesn't change how request.security fundamentally works or aligns data to the chart's bars. Instead, it uses the capabilities of request.security (fetching data from another timeframe) and Pine Script's execution model (bar-by-bar processing, var persistence) in a specific way, guided by the library's logic, to build a historical collection of data points that represent the target timeframe's candles and are independent of the chart's display resolution.
Indicatore Pine Script®
di viorel8
Casa_SessionsLibrary "Casa_Sessions" Advanced trading session management library that enhances TradingView's default functionality: Key Features: - Accurate session detection for futures markets - Custom session hour definitions - Drop-in replacements for standard TradingView session functions - Flexible session map customization - Full control over trading windows and market hours Perfect for traders who need precise session timing, especially when working with futures markets or custom trading schedules. SetSessionTimes(session_type_input, custom_session_times_input, syminfo_type, syminfo_root, syminfo_timezone)   Parameters:      session_type_input (simple string) : Input string for session selection: - 'Custom': User-defined session times - 'FX-Tokyo': Tokyo forex session - 'FX-London': London forex session - 'FX-New York': NY forex session - 'Overnight Session (ON)': After-hours trading - 'Day Session (RTH)': Regular trading hours      custom_session_times_input (simple string) : Session parameter for custom time windows Only used when session_type_input is 'Custom'      syminfo_type (simple string)      syminfo_root (simple string)      syminfo_timezone (simple string)   Returns: session_times: Trading hours for selected session session_timezone: Market timezone (relevant for forex) getSessionMap()   Get futures trading session hours map Keys are formatted as 'symbol:session', examples: - 'ES:market' - Regular trading hours (RTH) - 'ES:overnight' - Extended trading hours (ETH) - 'NQ:market' - NASDAQ futures RTH - 'CL:overnight' - Crude Oil futures ETH   Returns: Map Key: Symbol:session identifier Value: Session hours in format "HH:MM-HH:MM" getSessionString(session, symbol, sessionMap)   Returns a session string representing the session hours (and days) for the requested symbol (or the chart's symbol if the symbol value is not provided). If the session string is not found in the collection, it will return a blank string.   Parameters:      session (string) : A string representing the session hour being requested. One of: market (regular trading hours), overnight (extended/electronic trading hours), postmarket (after-hours), premarket      symbol (string) : The symbol to check. Optional. Defaults to chart symbol.      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided. inSession(session, sessionMap, barsBack)   Returns true if the current symbol is currently in the session parameters defined by sessionString.   Parameters:      session (string) : A string representing the session hour being requested. One of: market (regular trading hours), overnight (extended/electronic trading hours), postmarket (after-hours), premarket      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.      barsBack (int) : Private. Only used by futures to check islastbar. Optional. The default is 0. ismarket(sessionMap)   Returns true if the current bar is a part of the regular trading hours (i.e. market hours), false otherwise. Works for futures (TradingView's methods do not).   Parameters:      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: bool isfirstbar()   Returns true if the current bar is the first bar of the day's session, false otherwise. If extended session information is used, only returns true on the first bar of the pre-market bars. Works for futures (TradingView's methods do not).   Returns: bool islastbar()   Returns true if the current bar is the last bar of the day's session, false otherwise. If extended session information is used, only returns true on the last bar of the post-market bars. Works for futures (TradingView's methods do not).   Returns: bool ispremarket(sessionMap)   Returns true if the current bar is a part of the pre-market, false otherwise. On non-intraday charts always returns false. Works for futures (TradingView's methods do not).   Parameters:      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: bool ispostmarket(sessionMap)   Returns true if the current bar is a part of the post-market, false otherwise. On non-intraday charts always returns false. Works for futures (TradingView's methods do not).   Parameters:      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: bool isfirstbar_regular(sessionMap)   Returns true on the first regular session bar of the day, false otherwise. The result is the same whether extended session information is used or not. Works for futures (TradingView's methods do not).   Parameters:      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: bool islastbar_regular(sessionMap)   Returns true on the last regular session bar of the day, false otherwise. The result is the same whether extended session information is used or not. Works for futures (TradingView's methods do not).   Parameters:      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: bool isovernight(sessionMap)   Returns true if the current bar is a part of the pre-market or post-market, false otherwise. On non-intraday charts always returns false.   Parameters:      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: bool getSessionHighAndLow(session, sessionMap)   Returns a tuple containing the high and low print during the specified session.   Parameters:      session (string) : The session for which to get the high & low prints. Defaults to market.      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: A tuple containing getSessionHigh(session, sessionMap)   Convenience function to return the session high. Necessary if you want to call this function from within a request.security expression where you can't return a tuple.   Parameters:      session (string) : The session for which to get the high & low prints. Defaults to market.      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: The high of the session getSessionLow(session, sessionMap)   Convenience function to return the session low. Necessary if you want to call this function from within a request.security expression where you can't return a tuple.   Parameters:      session (string) : The session for which to get the high & low prints. Defaults to market.      sessionMap (map) : The map of futures session hours. Optional. Uses default if not provided.   Returns: The low of the session
Libreria Pine Script®
di Mupsje
Volume Flow Indicator Signals | iSolani Volume Flow Indicator Signals | iSolani: Decoding Trend Momentum with Volume Precision In markets where trends are fueled by institutional participation, discerning genuine momentum from false moves is critical. The Volume Flow Indicator Signals | iSolani cuts through this noise by synthesizing price action with volume dynamics, generating high-confidence signals when capital flows align with directional bias. This tool reimagines traditional volume analysis by incorporating volatility-adjusted thresholds and dual-layer smoothing, offering traders a laser-focused approach to trend identification. Core Methodology The indicator employs a multi-stage calculation to quantify volume-driven momentum: Volatility-Adjusted Filter: Measures price changes via log returns, scaling significance using a 30-bar standard deviation multiplied by user-defined sensitivity (default: 2x). Volume Normalization: Caps extreme volume spikes at 3x the 50-bar moving average, preventing distortion from anomalous trades. Directional Volume Flow: Assigns positive/negative values to volume based on whether price movement exceeds volatility-derived thresholds. Dual Smoothing: Applies consecutive SMA (3-bar) and EMA (14-bar) to create the Volume Flow Indicator (VFI) and its signal line, filtering out transient fluctuations. Breaking New Ground This implementation introduces three key innovations: Adaptive Noise Gates: Unlike static volume oscillators, the sensitivity coefficient dynamically adjusts to market volatility, reducing false signals during choppy conditions. Institutional Volume Capping: The vcoef parameter limits the influence of outlier volume spikes, focusing on sustained institutional activity rather than one-off trades. Non-Repainting Signals: Generates single-per-trend labels (buy below bars, sell above) to avoid chart clutter while maintaining visual clarity. Engine Under the Hood The script executes through five systematic stages: Data Preparation: Computes HLC3 typical price and its logarithmic rate of change. Threshold Calculation: Derives dynamic cutoff levels using 30-period volatility scaled by user sensitivity. Volume Processing: Filters raw volume through a 50-bar SMA, capping extremes at 3x average. VFI Construction: Sums directional volume flow over 50 bars, smoothed with a 3-bar SMA. Signal Generation: Triggers alerts when VFI crosses zero, confirmed by a 14-bar EMA crossover. Standard Configuration Optimized defaults balance responsiveness and reliability: Volume MA: 50-bar smoothing window Sensitivity: 2.0 (doubles volatility threshold) Signal Smoothing: 14-bar EMA Volume Cap: 3x average (hidden parameter) VFI Smoothing: Enabled (3-bar SMA) By fusing adaptive volume filtering with price confirmation logic, the Volume Flow Indicator Signals | iSolani transforms raw market data into institutional-grade trend signals. Its ability to mute choppy price action while amplifying high-conviction volume moves makes it particularly effective for spotting early trend reversals in equities, forex, and futures markets.
Indicatore Pine Script®
di Quantura
CHAKRA RISS ENGULFING CANDLESTICK STRATEGYChakra RISS Engulfing Candlestick Strategy Type: Technical Indicator & Strategy Platform: TradingView Script Version: Pine Script v6 Overview: The Chakra RISS Engulfing Candlestick Strategy combines a momentum-based approach using the Relative Strength Index (RSI) with Engulfing Candlestick Patterns to generate buy and sell signals. The strategy filters trades based on price movement relative to a 50-period Simple Moving Average (SMA), making it a trend-following strategy. The indicator uses color-coded bars to visually represent market conditions, helping traders easily identify bullish and bearish trends. The strategy is designed to be dynamic, adapting to changing market conditions and filtering out noise using key technical indicators. How It Works: RSI-Based Color Conditions: Green Bars: When the RSI crosses above a specified UpLevel (default: 50), indicating a bullish momentum and signaling potential buy conditions. Red Bars: When the RSI crosses below a specified DownLevel (default: 50), indicating a bearish momentum and signaling potential sell conditions. Buy Signal: Triggered when the following conditions are met: RSI crosses from below the UpLevel (default: 50) to above it, signaling increasing bullish momentum. The close price is above the 50-period Simple Moving Average (SMA), confirming an uptrend. The Buy Signal is plotted below the bar with a green arrow and a "BUY" label. Sell Signal: Triggered when the following conditions are met: RSI crosses from above the DownLevel (default: 50) to below it, signaling increasing bearish momentum. The close price is below the 50-period Simple Moving Average (SMA), confirming a downtrend. The Sell Signal is plotted above the bar with a red arrow and a "SELL" label. Stop Loss and Take Profit: For long trades (buy signals), the stop loss is placed below the previous bar's low, and the take profit is set at 3% above the entry price. For short trades (sell signals), the stop loss is placed above the previous bar's high, and the take profit is set at 3% below the entry price. Dynamic Bar Coloring: The bar colors change dynamically based on RSI levels: Green Bars: Indicating a potential uptrend (bullish). Red Bars: Indicating a potential downtrend (bearish). These visual cues help traders quickly identify market trends and potential reversals. Trend Filtering: The 50-period Simple Moving Average (SMA) is used to filter trades based on the overall market trend: Buy signals are only considered when the price is above the moving average, indicating an uptrend. Sell signals are only considered when the price is below the moving average, indicating a downtrend. Alerting System: Alerts can be set for both buy and sell signals. These alerts notify traders in real-time when potential trades are generated, allowing them to act promptly. Alerts can be configured to send notifications through email, SMS, or a webhook for integration with other services like IFTTT or Zapier. Key Features: RSI and Moving Average-Based Signals: Combines RSI with a moving average for more accurate trade signals. Stop Loss and Take Profit: Dynamic risk management with custom stop loss and take profit levels based on previous high and low prices. Buy and Sell Alerts: Provides real-time alerts when a buy or sell signal is triggered. Trend Confirmation: Uses the 50-period Simple Moving Average to filter signals and confirm the direction of the trend. Visual Bar Color Changes: Makes it easy to identify bullish or bearish trends with color-coded bars. Usage: This strategy is suitable for traders who prefer a trend-following approach and want to combine momentum indicators (RSI) with price action (Engulfing Candlestick patterns). It is particularly useful in volatile markets where quick identification of trend changes can lead to profitable trades. Best Used For: Day trading, swing trading, and trend-following strategies. Timeframes: Works well on various timeframes, from 1-minute charts for scalping to daily charts for swing trading. Markets: Can be applied to any market with sufficient liquidity (stocks, forex, crypto, etc.). Settings: UpLevel: The RSI level above which the market is considered bullish (default: 50). DownLevel: The RSI level below which the market is considered bearish (default: 50). SMA Length: The period of the Simple Moving Average used to filter trades (default: 50). Risk Management: Customizable stop loss and take profit settings based on price action (default: 3% above/below the entry price).
Indicatore Pine Script®
di Tradewith_Riss
3
Wick Strategy AnalyzerOverview This indicator analyzes candle wick patterns and evaluates their outcomes over a user-definable range (default is 1 year). Labels are rendered on the chart to mark events that meet the specified wick condition. Features Customizable Bar Range - users can specify the range of bars to include in the analysis. Default is 365 bars back from the most recent bar (bar 0) Visual Indicators - labels are rendered to mark conditions & outcomes. Wick Condition Met - an Orange label below the wick candle displaying the wick’s percentage size. Outcome Labels - rendered above the candle after wick condition met candles P (Green): Pass F (Red): Fail N (Navy): Neutral I (Blue): Indicates the current candle has not yet closed, so the outcome is undetermined. Input Parameters Wick Threshold - minimum wick size required to qualify as a wick condition. Success Margin - Defines the margin for classifying outcomes as Pass, Fail, or Neutral. E.g., a success margin of 0.01 requires the next candle's close to exceed the wick candle's close by 1% in order to be a Pass. Bar Offset Start - starting offset from the last bar for analysis. A value of -1 will include all bars. Bar Offset End - ending offset from the last bar for analysis. Bars outside this range are excluded. Example Scenario Goal: Analyze how candles with a wick size of at least 3.5% perform within a success margin of 1% over the past 540 days. Setup: Set Wick Threshold to 0.035 Set Success Margin to 0.01 Set Bar Range Start to 0 Set Bar Range End to 540. Expected Output Candles with a wick of at least 3.5% are labeled. Outcome labels (P, F, or N) indicate performance.
Indicatore Pine Script®
di foosmoo
1
ToolsPosLibrary "ToolsPos" Library for general purpose position helpers new_pos(state, price, when, index)   Returns new PosInfo object   Parameters:      state (series PosState) : Position state      price (float) : float Entry price      when (int) : int Entry bar time UNIX. Default: time      index (int) : int Entry bar index. Default: bar_index   Returns: PosInfo new_tp(pos, price, when, index, info)   Returns PosInfo object with new take profit info object   Parameters:      pos (PosInfo) : PosInfo object      price (float) : float Entry price      when (int) : int Entry bar time UNIX. Default: time      index (int) : int Entry bar index. Default: bar_index      info (Info type from aybarsm/Tools/14) : Info holder object. Default: na   Returns: PosInfo new_re(pos, price, when, index, info)   Returns PosInfo object with new re-entry info object   Parameters:      pos (PosInfo) : PosInfo object      price (float) : float Entry price      when (int) : int Entry bar time UNIX. Default: time      index (int) : int Entry bar index. Default: bar_index      info (Info type from aybarsm/Tools/14) : Info holder object. Default: na   Returns: PosInfo PosTPInfo   PosTPInfo - Position Take Profit info object   Fields:      price (series float) : float Take profit price      when (series int) : int Take profit bar time UNIX. Default: time      index (series int) : int Take profit bar index. Default: bar_index      info (Info type from aybarsm/Tools/14) : Info holder object PosREInfo   PosREInfo - Position Re-Entry info object   Fields:      price (series float) : float Re-entry price      when (series int) : int Re-entry bar time UNIX. Default: time      index (series int) : int Take profit bar index. Default: bar_index      info (Info type from aybarsm/Tools/14) : Info holder object PosInfo   PosInfo - Position info object   Fields:      state (series PosState) : Position state      price (series float) : float Entry price      when (series int) : int Entry bar time UNIX. Default: time      index (series int) : int Entry bar index. Default: bar_index      tp (array) : PosTPInfo Take profit info. Default: na      re (array) : PosREInfo Re-entry info. Default: na      info (Info type from aybarsm/Tools/14) : Info holder object
Libreria Pine Script®
di aybarsm
Mean Price ^^ Plotting switched to Line. This method of financial time series (aka bars) downsampling is literally, naturally, and thankfully the best you can do in terms of maximizing info gain. You can finally chill and feed it to your studies & eyes, and probably use nothing else anymore. (HL2 and occ3 also have use cases, but other aggregation methods? Not really, even if they do, the use cases are ‘very’ specific). Tho in order to understand why, you gotta read the following wall, or just believe me telling you, ‘I put it on my momma’. The true story about trading volumes and why this is all a big misdirection Actually, you don’t need to be a quant to get there. All you gotta do is stop blindly following other people’s contextual (at best) solutions, eg OC2 aggregation xD, and start using your own brain to figure things out. Every individual trade (basically an imprint on 1D price space that emerges when market orders hit the order book) has several features like: price, time, volume, AND direction (Up if a market buy order hits the asks, Down if a market sell order hits the bids). Now, the last two features—volume and direction—can be effectively combined into one (by multiplying volume by 1 or -1), and this is probably how every order matching engine should output data. If we’re not considering size/direction, we’re leaving data behind. Moreover, trades aren’t just one-price dots all the time. One trade can consume liquidity on several levels of the order book, so a single trade can be several ticks big on the price axis. You may think now that there are no zero-volume ticks. Well, yes and no. It depends on how you design an exchange and whether you allow intra-spread trades/mid-spread trades (now try to Google it). Intra-spread trades could happen if implemented when a matching engine receives both buy and sell orders at the same microsecond period. This way, you can match the orders with each other at a better price for both parties without even hitting the book and consuming liquidity. Also, if orders have different sizes, the remaining part of the bigger order can be sent to the order book. Basically, this type of trade can be treated as an OTC trade, having zero volume because we never actually hit the book—there’s no imprint. Another reason why it makes sense is when we think about volume as an impact or imbalance act, and how the medium (order book in our case) responds to it, providing information. OTC and mid-spread trades are not aggressive sells or buys; they’re neutral ticks, so to say. However huge they are, sometimes many blocks on NYSE, they don’t move the price because there’s no impact on the medium (again, which is the order book)—they’re not providing information. ... Now, we need to aggregate these trades into, let’s say, 1-hour bars (remember that a trade can have either positive or negative volume). We either don’t want to do it, or we don’t have this kind of information. What we can do is take already aggregated OHLC bars and extract all the info from them. Given the market is fractal, bars & trades gotta have the same set of features: - Highest & lowest ticks (high & low) <- by price; - First & last ticks (open & close) <- by time; - Biggest and smallest ticks <- by volume.* *e.g., in the array , 2323: biggest trade, -1212: smallest trade. Now, in our world, somehow nobody started to care about the biggest and smallest trades and their inclusion in OHLC data, while this is actually natural. It’s the same way as it’s done with high & low and open & close: we choose the minimum and maximum value of a given feature/axis within the aggregation period. So, we don’t have these 2 values: biggest and smallest ticks. The best we can do is infer them, and given the fact the biggest and smallest ticks can be located with the same probability everywhere, all we can do is predict them in the middle of the bar, both in time and price axes. That’s why you can see two HL2’s in each of the 3 formulas in the code. So, summed up absolute volumes that you see in almost every trading platform are actually just a derivative metric, something that I call Type 2 time series in my own (proprietary ‘for now’) methods. It doesn’t have much to do with market orders hitting the non-uniform medium (aka order book); it’s more like a statistic. Still wanna use VWAP? Ok, but you gotta understand you’re weighting Type 1 (natural) time series by Type 2 (synthetic) ones. How to combine all the data in the right way (khmm khhm ‘order’) Now, since we have 6 values for each bar, let’s see what information we have about them, what we don’t have, and what we can do about it: - Open and close: we got both when and where (time (order) and price); - High and low: we got where, but we don’t know when; - Biggest & smallest trades: we know shit, we infer it the way it was described before.' By using the location of the close & open prices relative to the high & low prices, we can make educated guesses about whether high or low was made first in a given bar. It’s not perfect, but it’s ultimately all we can do—this is the very last bit of info we can extract from the data we have. There are 2 methods for inferring volume delta (which I call simply volume) that are presented everywhere, even here on TradingView. Funny thing is, this is actually 2 parts of the 1 method. I wonder how many folks see through it xD. The same method can be used for both inferring volume delta AND making educated guesses whether high or low was made first. Imagine and/or find the cases on your charts to understand faster: * Close > open means we have an up bar and probably the volume is positive, and probably high was made later than low. * Close < open means we have a down bar and probably the volume is negative, and probably low was made later than high. Now that’s the point when you see that these 2 mentioned methods are actually parts of the 1 method: If close = open, we still have another clue: distance from open/close pair to high (HC), and distance from open/close pair to low (LC): * HC < LC, probably high was made later. * HC > LC, probably low was made later. And only if close = open and HC = LC, only in this case we have no clue whether high or low was made earlier within a bar. We simply don’t have any more information to even guess. This bar is called a neutral bar. At this point, we have both time (order) and price info for each of our 6 values. Now, we have to solve another weighted average problem, and that’s it. We’ll weight prices according to the order we’ve guessed. In the neutral bar case, open has a weight of 1, close has a weight of 3, and both high and low have weights of 2 since we can’t infer which one was made first. In all cases, biggest and smallest ticks are modeled with HL2 and weighted like they’re located in the middle of the bar in a time sense. P.S.: I’ve also included a "robust" method where all the bars are treated like neutral ones. I’ve used it before; obviously, it has lesser info gain -> works a bit worse.
Indicatore Pine Script®
di gorx1
1