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NormInvTargetSeekerNormInvTargetSeeker The NormInvTargetSeeker is a trading tool designed to aid traders in identifying and capitalizing on Distribution and Accumulation zones, highlighting specific price levels that could serve as targets for future price movements. Although the indicator itself is not multi-timeframe, an effective trading strategy might involve signal validation across multiple timeframes. 🔶 USAGE The indicator identifies Distribution and Accumulation zones, providing potential targets for future price moves. Traders are encouraged to use these zones as profit targets or potential reversal points. Confluence Zones These zones are identified as regions where various factors or levels converge, signaling an increased probability of price reaction. They can be used to reinforce signals or identify levels where price might encounter significant resistance or support. 🔹 Trading Strategy First, identify a signal on your primary trading timeframe. Manually check higher timeframes to ensure the signal aligns with them. Use the identified zones, whether Distribution or Accumulation, as target zones for your trades. 🔶 Order Blocks The NormInvTargetSeeker identifies "Order Blocks" by examining a specified number of consecutive candles with a specific condition: the current candle must completely engulf the previous candle. This means that both the high and low of the current candle are higher and lower, respectively, than the high and low of the previous candle, signifying a dominant move in the direction of the current candle. 🔹 Trading Strategy Target Confirmation: Order Blocks can serve to confirm target points, providing additional validation for identified levels. Market Insight: They offer crucial insights into whether "big hands" or institutional players are positioned as buyers or sellers in the market. Traders can use Order Blocks as a means to validate targets or key price levels, observing if the price reacts significantly upon reaching these blocks. They can also provide insights into the general market direction or underlying market strength by identifying where the major market players are placing their orders. 🔶 SETTINGS The indicator allows users to adjust various parameters to customize the display and logic of the tool to fit their needs. 🔹 Display Settings Users can customize the colors and displays of various zones and labels to match their preferences. 🔶 LICENSE AND CREDITS This work is licensed under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). More information here: creativecommons.org This indicator utilizes a TypeScript implementation of the Normal Inverse function as a reference, which can be found here : github.com Special thanks to the authors of the referenced code for providing a foundation upon which this indicator was built. 🔶 UPDATES Current Version: 1.0.0 For future updates, please check the comment section. 🔶 CONTACT For any questions or suggestions, please feel free to contact @RickSimpson on TradingView.
Pine Script™ indicator
by RickSimpson
7
The Master Pattern Indicator***READ THIS FIRST**** THE MASTER PATTERN Indicator USER AGREEMENT *** The personal/private use of this indicator is allowed, commercial use is FORBIDDEN. ***Commercial use will be interpreted as taking advantage of the free indicator in order to profit from it, for example: as part of any courses or mentorships offering training of the indicator or the concept its based. You don't need to pay for any training for this, the strategy is a simple trend following approach, even a caveman would understand. ********************************************************************************************************************** Now please enjoy the BEST Master Pattern indicator you will ever find for Tradingvew, and for the best price: FREE. Please do not give money to people trying to charge you for any inferior version of this indicator. DESCRIPTION The Master Pattern indicator or The Forex Master Pattern is an alternative form of technical analysis that provides a framework which will help you to find and follow the hidden price pattern that reveals the true intentions of financial markets. This algorithm I came up with does a very good job detecting the Phase 1 of the Forex Master Pattern cycle, which is the contraction point (or Value), and then proceeds to differentiate between major or minor lines and prints the liquidity lines the correct manner in relation to the swings expanding from the contraction. On Phase 2 we get higher timeframe activation (also called Expansion), which is where price oscillates above and below the average price defined on Phase 1. On Phase 3 is where we get a sustained deviation from value (the Trend). In a very short time you will start noticing this pattern, even on naked charts. It is all a matter of training your eyes - the more time you invest studying the charts with this indicator (both historically and replaying the market on strategy tester), the faster you will become familiar with this method. This indicator DOES NOT REPAINT. You can safely study the chart historically because what is printed historically is what prints real time. Why do traditional based indicator systems fail over time? Because the markets move in cycles that constantly change structure. Those traditional indicator systems must be constantly optimized and settings tinkered with because of the changing market environment. There are an infinite number of variables that affect price so no exact technical system can work the same forever, which is also the reason why most bots/EA fail. If you learn to spot the Forex Master Pattern and understand the sequence of the real cycles that drive the markets, you can more accurately forecast market behavior. By using traditional indicators you end up masking this pattern. Use the insights provided by the Forex Master Pattern indicator to elevate your trading to the next level. This method of analysis works in any liquid market and timeframe. VERY IMPORTANT: The default setting of historical bars is set to 500. This is more than enough for day trading and ensures fast drawings loading time and stable performance. Bear in mind that, the more bars you choose to load historically, the longer it will take to draw everything. The max setting of this input for now is 800. If it is possible to increase it, I will update the code. So if you want to make historical analysis far in the past, just use the chart replay feature. Indicator Parameters: They are all self-explanatory, except Type. You can choose between 1 and 2. 1 is better suited for LTF (M1 to M30) 2 is better suited for HTF (H1 and upwards) However, this is my personal preference. You can of course experiment and choose what looks best for you. Instructions to use the alert function: 1st step - Choose symbol and timeframe for the alert 2nd step - Go to indicator settings and tick/untick the boxes for the alerts you want 3rd step - Click on the ... (three dots) next to the indicator name (chart upper left corner) and click to add indicator alert Then it's gonna add the alert with the conditions that you've ticked/unticked inside indicator settings. Then repeat the process for different symbols, timeframes and different alert conditions.
Pine Script™ indicator
by Beto_Gauer
141
Price based concepts / quantifytools- Overview Price based concepts incorporates a collection of multiple price action based concepts. Main component of the script is market structure, on top of which liquidity sweeps and deviations are built on, leaving imbalances the only standalone concept included. Each concept can be enabled/disabled separately for creating a selection of indications that one deems relevant for their purposes. Price based concepts are quantified using metrics that measure their expected behavior, such as historical likelihood of supportive price action for given market structure state and volume traded at liquidity sweeps. The concepts principally work on any chart, whether that is equities, currencies, cryptocurrencies or commodities, charts with volume data or no volume data. Essentially any asset that can be considered an ordinary speculative asset. The concepts also work on any timeframe, from second charts to monthly charts. None of the indications are repainted. Market structure Market structure is an analysis of support/resistance levels (pivots) and their position relative to each other. Market structure is considered to be bullish on a series of higher highs/higher lows and bearish on a series of lower highs/lower lows. Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side. Supportive market structure typically provides lengthier and sustained trending environment, making it an ideal point of confluence for establishing directional bias for trades. Liquidity sweeps Liquidity sweeps are formed when price exceeds a pivot level that served as a provable level of demand once and is expected to display demand again when revisited. A simple way to look at liquidity sweeps is re-tests of untapped support/resistance levels. Deviations Deviations are formed when price exceeds a reference level (market structure shift level/liquidity sweep level) and shortly closes back in, leaving participating breakout traders in an awkward position. On further adverse movement, stuck breakout traders are forced to cover their underwater positions, creating ideal conditions for a lengthier reversal. Imbalances Imbalances, also known as fair value gaps or single prints, depict areas of inefficient and one sided transacting. Given inclination for markets to trade efficiently, price is naturally attracted to areas that lack proper participation, making imbalances ideal targets for entries or exits. Key takeaways - Price based concepts consists of market structure, liquidity sweeps, deviations and imbalances. - Market structure shifts from bullish to bearish and vice versa on a break of the most recent pivot high/low, indicating weak ability to defend a key level from the dominating side. - Supportive market structure tends to provide lengthier and sustained movement for the dominating side, making it an ideal foundation for establishing directional bias for trades. - Liquidity sweeps are formed when price exceeds an untapped support/resistance level that served as a provable level of demand in the past, likely to show demand again when revisited. - Deviations are formed when price exceeds a key level and shortly closes back in, leaving breakout traders in an awkward position. Further adverse movement compels trapped participants to cover their positions, creating ideal conditions for a reversal. - Imbalances depict areas of inefficient and one sided transacting where price is naturally attracted to, making them ideal targets for entries or exits. - Price based concepts are quantified using metrics that measure expected behavior, such as historical likelihood of supportive structure and volume traded at liquidity sweeps. - For practical guide with practical examples, see last section. Accessing script 🔑 See "Author's instructions" section, found at bottom of the script page. Disclaimer Price based concepts are not buy/sell signals, a standalone trading strategy or financial advice. They also do not substitute knowing how to trade. Example charts and ideas shown for use cases are textbook examples under ideal conditions, not guaranteed to repeat as they are presented. Price based concepts notify when a set of conditions are in place from a purely technical standpoint. Price based concepts should be viewed as one tool providing one kind of evidence, to be used in conjunction with other means of analysis. Price based concepts are backtested using metrics that reasonably depict their expected behaviour, such as historical likelihood of supportive price movement on each market structure state. The metrics are not intended to be elaborate and perfect, but to serve as a general barometer for feedback created by the indications. Backtesting is done first and foremost to exclude scenarios where the concepts clearly don't work or work suboptimally, in which case they can't be considered as valid evidence. Even when the metrics indicate historical reactions of good quality, price impact can and inevitably does deviate from the expected. Past results do not guarantee future performance. - Example charts Chart #1 : BTCUSDT Chart #2 : EURUSD Chart #3 : ES futures Chart #4 : NG futures Chart #5 : Custom timeframes - Concepts Market structure Knowing when price has truly pivoted is much harder than it might seem at first. In this script, pivots are determined using a custom formula based on volatility adjusted average price, a fundamentally different approach to the widely used highest/lowest price within X amount of bars. The script calculates average price within set period and adjusts it to volatility. Using this formula, the script determines when price has turned significantly enough and aggressively enough to constitute a relevant pivot, resulting in high accuracy while ruling out subjective decision making completely. Users can adjust length of market structure basis and sensitivity of volatility adjustment to achieve desired magnitude of pivots, reflected on the average swing metrics. Note that structure pivots are backpainted. Typical confirmation time for a pivot is within 2-3 bars after peak in price. Market structure shifts Generally speaking, traders consider market structure to have shifted when most recent structure high/low gets taken out, flipping underlying bias from one side over to the other (e.g. from bullish structure favoring upside to bearish structure favoring downside). However, there are many ways to approach the concept and the most popular method might not always be the best one. Users can determine their own market structure shift rules by choosing source (close, high, low, ohlc4 etc.) for determining structure shift. Users can also choose additional rules for structure shift, such as two consecutive closes above/below pivot to qualify as a valid shift. Liquidity sweeps Users can set maximum amount of bars liquidity levels are considered relevant from the moment of confirmed pivot. By default liquidity levels are monitored for 250 bars and then discarded. Level of tolerance can be set to anything between 100 and 1000 bars. For each liquidity sweep, relative volume (volume relative to volume moving average) is stored and added to average calculations for keeping track of typical depth of liquidity found at sweeps. Deviations Users can set a maximum amount of bars price has to spend above/below reference level to consider a deviation to be in place. By default set to 6 bars. Imbalances Users can set a desired fill point for imbalances using the following options: 100%, 75%, 50%, 25%. Users can also opt for excluding insignificant imbalances to attain better relevance in indications. - Backtesting Built-in backtesting is based on metrics that are considered to reasonably quantify expected behaviour of the main concept, market structure. Structure feedback is monitored using two metrics, supportive structure and structure period gain. Rest of the metrics provided are informational in nature, such as average swing and average relative volume traded at liquidity sweeps. Main purpose of the metrics is to form a general barometer for monitoring whether or not the concepts can be viewed as valid evidence. When the concepts are clearly not working optimally, one should adjust expectations accordingly or take action to improve performance. To make any valid conclusions of performance, sample size should also be significant enough to eliminate randomness effectively. If sample size on any individual chart is insufficient, one should view feedback scores on multiple correlating and comparable charts to make up for the loss. For more elaborate backtesting, price based concepts can be used in any other script that has a source input, including fully mechanic strategies utilizing Tradingview's native backtester. Each concept and their indications (e.g. higher low on a bearish structure, lower high on a bullish structure, market structure shift up, imbalance filled etc.) can be utilized separately and used as a component in a backtesting script of your choice. Structure feedback Structure feedback is monitored using two metrics, likelihood of supportive price movement following a market structure shift and average structure period gain. If either of the two employed tests indicate failed reactions beyond a tolerable level, one should take action to improve feedback by adjusting the settings. If feedback metrics after adjusting the settings are still insufficient, the concepts are working suboptimally for the given chart and cannot be regarded as valid technical evidence as they are. Metric #1 : Supportive structure Each structure pivot is benchmarked against its respective structure shift level. Feedback is considered successful if structure pivot takes place above market structure shift level (in the case of bullish structure) or below market structure shift level (in the case of bearish structure). Structure feedback constitutes as one test indicating how often a market structure state results in price movement that can be considered supportive. Metric #2 : Structure period gain Each structure period is expected to present favorable appreciation, measured from one market structure shift level to another. E.g. bullish structure period gain is measured from market structure shift up level to market structure shift down level that ends the bullish structure period. Bearish structure is measured in a vice versa manner, from market structure shift down level to market structure shift up level that ends the bearish structure period. Feedback is considered successful if average structure period gain is supportive for a given structure (positive for bullish structure, negative for bearish structure). Additional metrics On top of structure feedback metrics, percentage gain for each swing (distance between a pivot to previous pivot) is recorded and stored to average calculations. Average swing calculations shed light on typical pivot magnitude for better understanding changes made in market structure settings. Average relative volume traded at liquidity sweep on the other hand gives a clue of depth of liquidity typically found on a sweeps. Feedback scores When market structure (basis for most concepts) is working optimally, quality threshold for both feedback metrics are met. By default, threshold for supportive structure is set to 66%, indicating valid feedback on 2/3 of backtesting periods on average. On top, average structure period gain needs to be positive (for bullish structures) and negative (for bearish structure) to qualify as valid feedback. When both tests are passed, a tick indicating valid feedback will appear next to feedback scores, otherwise an exclamation mark indicating suboptimal performance on either or both. If both or either test fail, market structure parameters need to be optimized for better performance or one needs to adjust expectations accordingly. Verifying backtest calculations Backtest metrics can be toggled on via input menu, separately for bullish and bearish structure. When toggled on, both cumulative and average counters used in backtesting will appear on "Data Window" tab. Calculation states are shown at a point in time where cursor is hovered. E.g. when hovering cursor on 4th of January 2021, backtest calculations as they were during this date will be shown. - Alerts Available alerts are the following. - HH/HL/LH/LL/EQL/EQH on a bullish/bearish structure - Bullish/bearish market structure shift - Bullish/bearish imbalance created - Bullish/bearish imbalance filled - Bullish/bearish liquidity sweep - Bullish/bearish deviation - Visuals Each concept can be enabled/disabled separately for creating a selection indications that one deems relevant for their purposes. On top, each concept has a stealth visual option for more discreet visuals. Unfilled imbalances and untapped liquidity levels can be extended forward to better gauge key areas of interest. Liquidity sweeps have an intensity option, using color and width to visualize volume traded at sweep. Market structure states and market structure shifts can be visualized as chart color. Metric table can be offsetted horizontally or vertically from any four corners of the chart, allowing space for tables from other scripts. Table sizes, label sizes and colors are fully customizable via input menu. - Practical guide The basic idea behind market structure is that a side (bulls or bears) have shown significant weakness on a failed attempt to defend a key level (most recent pivot high/low). In the same way, a side has shown significant strength on a successful attempt to break through a key level. This successful break through a key level often leads to sustained lengthier movement for the side that provably has the upper hand, making it an ideal tool for establishing directional bias. Multi-timeframe view of market structure provides crucial guidance for analyzing market structure states on any individual timeframe. If higher timeframe market structure is bullish, it doesn't make sense to expect contradicting lower timeframe market structure to provide significant adverse movement, but rather a normal correction within a long term trend. In the same way, if lower timeframe market structure is in agreement with higher timeframe market structure, one can expect a reliable trending environment to ensue as multiple points of confluence are in place. Bullish structure can be considered constructive on a series of higher highs and higher lows, indicating strong interest from bulls to sustain an uptrend. Vice versa is true for bearish structure, a series of lower highs and lower lows can be considered constructive. When structure does not indicate strong interest to maintain a supportive trend (lower highs on bullish structure, higher lows on bearish structure), a structure shift and a turn in trend might be nearing. Market structure shifts are of great interest for breakout traders who position for continuation. Structure shifts can indeed be fertile ground for executing a breakout trade, but breakouts can easily turn into fakeouts that leave participants in an awkward position. When price moves further away from the underwater participants, potential for snowball effect of covering positions and driving price further away is elevated. Liquidity sweeps as a concept is based on the premise that pivoting price is evidence of meaningful depth of liquidity found at/around pivot. If liquidity existed at a pivot once, it is likely to exist there in the future as well. When price grinds against liquidity, it is on a path of resistance rather than path of least resistance. Pivots are also attractive placements for traders to set stop-losses, which act as fuel for price to move to the opposite direction when swept and triggered. Behind tightly formed pivots are potentially many stop-loss orders lulled in the comfort of having many layers of levels protecting their position. Compression that leaves such clusters of unswept liquidity rarely goes unvisited. As markets strive for efficient and proper transacting most of the time, imbalances serve as points in price where price is naturally attracted to. However, imbalances too are contextual and sometimes one sided trading is rewarded with follow through, rather than with a fill. Identifying market regimes give further clue into what to expect from imbalances. In a ranging environment, one can expect imbalances to fill relatively quick, making them ideal targets for entries and exits. On a strongly trending environment on the other hand imbalances tend to stick for a much longer time. In such environments continuation can be expected with no fills or only partial fills. Signs of demand preventing fill attempts serve as additional clues for imminent continuation.
Pine Script™ indicator
by quantifytools
5
ADR/AWR/AMR Average Daily+Weekly+Monthly Range[Traders Reality]Advanced ADR/AWR/AMR indicator created for Traders Reality community, as well as the greater trading community. Thanks to the TR community discord guys: infernix, peshocore and xtech5192 Everything is modular and can be turned on/off, including a customisable table showing daily/weekly/monthly average pips/dollars. If you just want the average daily range lines for example, you can just disable everything else. You can choose how many days to look back; as well as for weeks or months. Check out Traders Reality on YouTube if you want to see this implemented as part of Tino's strategy that utilizes market manipulation, imbalances, times of day etc. Price regularly reverses from ADR, making it one of the few highly valuable indicators in price action/smart money trading.
Pine Script™ indicator
by SmartMoneyConceptsOnYouTube
9