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CamarillaStrategy -V1 - H4 and L4 breakout - exits addedExits added using trailing stops. 2.6 Profit Factor and 76% Profitable on SPY , 5M - I think it's a pretty good number for an automated strategy that uses Pivots. I don't think it's possible to add volume and day open price in relation to pivot levels -- that's what I do manually .. Still trying to add EMA for exits.. it will increase profitability. You can play in pinescript with trailing stops entries..
Pine Script®策略
由cristian.d提供
15
Leading Indicator by Parag RautBreakdown of the Leading Indicator: Linear Regression (LRC): A linear regression line is used to estimate the current trend direction. When the price is above or below the regression line, it indicates whether the price is deviating from its mean, signaling potential reversals. Rate of Change (ROC): ROC measures the momentum of the price over a set period. By using thresholds (positive or negative), we predict that the price will continue in the same direction if momentum is strong enough. Leading Indicator Calculation: We calculate the difference between the price and the linear regression line. This is normalized using the standard deviation of price over the same period, giving us a leading signal based on price divergence from the mean trend. The leading indicator is used to forecast changes in price behavior by identifying when the price is either stretched too far from the mean (indicating a potential reversal) or showing strong momentum in a particular direction (predicting trend continuation). Buy and Sell Signals: Buy Signal: Generated when ROC is above a threshold and the leading indicator shows the price is above the regression line. Sell Signal: Generated when ROC is below a negative threshold and the leading indicator shows the price is below the regression line. Visual Representation: The indicator oscillates around zero. Values above zero signal potential upward price movements, while values below zero signal potential downward movements. Background colors highlight potential buy (green) and sell (red) areas based on our conditions. How It Works as a Leading Indicator: This indicator attempts to predict price movements before they happen by combining the trend (via linear regression) and momentum (via ROC). When the price significantly diverges from the trendline and momentum supports a continuation, it signals a potential entry point (either buy or sell). It is leading in that it anticipates price movement before it becomes fully apparent in the market. Next Steps: You can adjust the length of the linear regression and ROC to fine-tune the indicator’s sensitivity to your trading style. This can be combined with other indicators or used as part of a larger strategy
Pine Script®指标
由paragrraut提供
1
Saty Volume StackBreaks volume into buy and sell volume and stacks them based on which side has higher volume. Dynamic Buy / Sell Stack Unlike other buy/sell volume indicators, which statically display this information (typically green over red), this indicator dynamically stacks the higher volume side on top. For example, green over red indicates more buy-side volume, red over green indicators more sell-side volume. Current Candle Volume Buy/Sell % A label shows the % buy vs sell volume for the current candle in real-time. This label is also dynamic with the left position being higher volume. How the Buy/Sell Volume is Calculated Buy/Sell % is calculated based on price. Buy % is calculated using the distance between the low of the candle to the closing value of the candle and dividing that by the total range of the candle high to low. Sell % is calculated using the distance between the high of the candle to the closing value of the candle and dividing that by the total range of the candle high to low. Please note this is a proxy metric and while it is incredibly useful, it is not going to match up exactly with actual buy/sell volume that can be found on tape.
Pine Script®指标
由satymahajan提供
30
Breakout Candles + RSIHello! This is my firt script :) This indicator looks for candles that are significantly larger than the previous X candle. It is possible to set the following: Multiplier: deviation from the size of the previous X candle (if set to 3 the size of the actual candle's body /abs(open - close)/ must be larger than the size of the bigger candle from the prevous X candles) Previous candles: the number of previous candles to size check Upper RSI limit: if the RSI14 close higher than the specified number, the candle will ignore Lower RSI limit: if the RSI14 close lower than the specified number, the candle will ignore Without dojis: if checked, watches candles only that do not have a bottom spike (bullish) or top spike (bearish). Useful for Heikin-Ashi candles Feel free to left any suggestion! Thank You!
Pine Script®指标
由mildZebra14333提供
2
Volume PressureBreaks down volume into buyers (green part) vs sellers (red part). It is recommended to set the volume's scale, especially if you switch tickers on the same chart. Follow these steps: Select the Volume Pressure indicator's 3 dots (...) Select Pin To Scale Select a separate scale from the main chart, such as Pin To New Left Scale (Z) Left click and hold the scale on the side of the chart and drag it up/down to bring the volume bars into the desired area To update to the latest version, just close the indicator and add it again.
Pine Script®指标
由David-Hamilton提供
2
Breakout Volume Can Help Confirm Other SignalsVolume can help confirm signals we might discover using other methods of technical analysis. This indicator tracks volume intelligently. Its logic spots above-average turnover and then tests against the price change. BrkVol highlights sessions with heavy volume and directional moves. This can help take out the noise and help confirm the trend. Tesla is a classic example of this, with the stock rallying after showing heavy-volume gains on October 24- 25, December 16 and January 8.
Pine Script®指标
由TradeStation提供
6
Price Action Smart Money Concepts [BigBeluga]THE SMART MONEY CONCEPTS Toolkit The Smart Money Concepts [ BigBeluga ] is a comprehensive toolkit built around the principles of "smart money" behavior, which refers to the actions and strategies of institutional investors. The Smart Money Concepts Toolkit brings together a suite of advanced indicators that are all interconnected and built around a unified concept: understanding and trading like institutional investors, or "smart money." These indicators are not just randomly chosen tools; they are features of a single overarching framework, which is why having them all in one place creates such a powerful system. This all-in-one toolkit provides the user with a unique experience by automating most of the basic and advanced concepts on the chart, saving them time and improving their trading ideas. Real-time market structure analysis simplifies complex trends by pinpointing key support, resistance, and breakout levels. Advanced order block analysis leverages detailed volume data to pinpoint high-demand zones, revealing internal market sentiment and predicting potential reversals. This analysis utilizes bid/ask zones to provide supply/demand insights, empowering informed trading decisions. Imbalance Concepts (FVG and Breakers) allows traders to identify potential market weaknesses and areas where price might be attracted to fill the gap, creating opportunities for entry and exit. Swing failure patterns help traders identify potential entry points and rejection zones based on price swings. Liquidity Concepts, our advanced liquidity algorithm, pinpoints high-impact events, allowing you to predict market shifts, strong price reactions, and potential stop-loss hunting zones. This gives traders an edge to make informed trading decisions based on liquidity dynamics. 🔵 FEATURES The indicator has quite a lot of features that are provided below: Swing market structure Internal market structure Mapping structure Adjustable market structure Strong/Weak H&L Sweep Volumetric Order block / Breakers Fair Value Gaps / Breakers (multi-timeframe) Swing Failure Patterns (multi-timeframe) Deviation area Equal H&L Liquidity Prints Buyside & Sellside Sweep Area Highs and Lows (multi-timeframe) 🔵 BASIC DEMONSTRATION OF ALL FEATURES 1. MARKET STRUCTURE The preceding image illustrates the market structure functionality within the Smart Money Concepts indicator. ➤ Solid lines: These represent the core indicator's internal structure, forming the foundation for most other components. They visually depict the overall market direction and identify major reversal points marked by significant price movements (denoted as 'x'). ➤ Internal Structure: These represent an alternative internal structure with the potential to drive more rapid market shifts. This is particularly relevant when a significant gap exists in the established swing structure, specifically between the Break of Structure (BOS) and the most recent Change of High/Low (CHoCH). Identifying these formations can offer opportunities for quicker entries and potential short-term reversals. ➤ Sweeps (x): These signify potential turning points in the market where liquidity is removed from the structure. This suggests a possible trend reversal and presents crucial entry opportunities. Sweeps are identified within both swing and internal structures, providing valuable insights for informed trading decisions. ➤ Mapping structure: A tool that automatically identifies and connects significant price highs and lows, creating a zig-zag pattern. It visualizes market structure, highlights trends, support/resistance levels, and potential breakouts. Helps traders quickly grasp price action patterns and make informed decisions. ➤ Color-coded candles based on market structure: These colors visually represent the underlying market structure, making it easier for traders to quickly identify trends. ➤ Extreme H&L: It visualizes market structure with extreme high and lows, which gives perspective for macro Market Structure. 2. VOLUMETRIC ORDER BLOCKS Order blocks are specific areas on a financial chart where significant buying or selling activity has occurred. These are not just simple zones; they contain valuable information about market dynamics. Within each of these order blocks, volume bars represent the actual buying and selling activity that took place. These volume bars offer deeper insights into the strength of the order block by showing how much buying or selling power is concentrated in that specific zone. Additionally, these order blocks can be transformed into Breaker Blocks. When an order block fails—meaning the price breaks through this zone without reversing—it becomes a breaker block. Breaker blocks are particularly useful for trading breakouts, as they signal that the market has shifted beyond a previously established zone, offering opportunities for traders to enter in the direction of the breakout. Here's a breakdown: ➤ Bear Order Blocks (Red): These are zones where a lot of selling happened. Traders see these areas as places where sellers were strong, pushing the price down. When the price returns to these zones, it might face resistance and drop again. ➤ Bull Order Blocks (Green): These are zones where a lot of buying happened. Traders see these areas as places where buyers were strong, pushing the price up. When the price returns to these zones, it might find support and rise again. These Order Blocks help traders identify potential areas for entering or exiting trades based on past market activity. The volume bars inside blocks show the amount of trading activity that occurred in these blocks, giving an idea of the strength of buying or selling pressure. ➤ Breaker Block: When an order block fails, meaning the price breaks through this zone without reversing, it becomes a breaker block. This indicates a significant shift in market liquidity and structure. ➤ A bearish breaker block occurs after a bullish order block fails. This typically happens when there's an upward trend, and a certain level that was expected to support the market's rise instead gives way, leading to a sharp decline. This decline indicates that sellers have overcome the buyers, absorbing liquidity and shifting the sentiment from bullish to bearish. Conversely, a bullish breaker block is formed from the failure of a bearish order block. In a downtrend, when a level that was expected to act as resistance is breached, and the price shoots up, it signifies that buyers have taken control, overpowering the sellers. 3. FAIR VALUE GAPS: A fair value gap (FVG), also referred to as an imbalance, is an essential concept in Smart Money trading. It highlights the supply and demand dynamics. This gap arises when there's a notable difference between the volume of buy and sell orders. FVGs can be found across various asset classes, including forex, commodities, stocks, and cryptocurrencies. FVGs in this toolkit have the ability to detect raids of FVG which helps to identify potential price reversals. Mitigation option helps to change from what source FVGs will be identified: Close, Wicks or AVG. 4. SWING FAILURE PATTERN (SFP): The Swing Failure Pattern is a liquidity engineering pattern, generally used to fill large orders. This means, the SFP generally occurs when larger players push the price into liquidity pockets with the sole objective of filling their own positions. SFP is a technical analysis tool designed to identify potential market reversals. It works by detecting instances where the price briefly breaks a previous high or low but fails to maintain that breakout, quickly reversing direction. How it works: Pattern Detection: The indicator scans for price movements that breach recent highs or lows. Reversal Confirmation: If the price quickly reverses after breaching these levels, it's identified as an SFP. ➤ SFP Display: Bullish SFP: Marked with a green symbol when price drops below a recent low before reversing upwards. Bearish SFP: Marked with a red symbol when price rises above a recent high before reversing downwards. ➤ Deviation Levels: After detecting an SFP, the indicator projects white lines showing potential price deviation: For bullish SFPs, the deviation line appears above the current price. For bearish SFPs, the deviation line appears below the current price. These deviation levels can serve as a potential trading opportunity or areas where the reversal might lose momentum. With Volume Threshold and Filtering of SFP traders can adjust their trading style: Volume Threshold: This setting allows traders to filter SFPs based on the volume of the reversal candle. By setting a higher volume threshold, traders can focus on potentially more significant reversals that are backed by higher trading activity. SFP Filtering: This feature enables traders to filter SFP detection. It includes parameters such as: 5. LIQUIDITY CONCEPTS: ➤ Equal Lows (EQL) and Equal Highs (EQH) are important concepts in liquidity-based trading. EQL: A series of two or more swing lows that occur at approximately the same price level. EQH: A series of two or more swing highs that occur at approximately the same price level. EQLs and EQHs are seen as potential liquidity pools where a large number of stop loss orders or limit orders may be clustered. They can be used as potential reverse points for trades. This multi-period feature allows traders to select less and more significant EQL and EQH: ➤ Liquidity wicks: Liquidity wicks are a minor representation of a stop-loss hunt during the retracement of a pivot point: ➤ Buy and Sell side liquidity: The buy side liquidity represents a concentration of potential buy orders below the current price level. When price moves into this area, it can lead to increased buying pressure due to the execution of these orders. The sell side liquidity indicates a pool of potential sell orders below the current price level. Price movement into this area can result in increased selling pressure as these orders are executed. ➤ Sweep Liquidation Zones: Sweep Liquidation Zones are crucial for understanding market structure and potential future price movements. They provide insights into areas where significant market participants have been forced out of their positions, potentially setting up new trading opportunities. 🔵 USAGE & EXAMPLES The core principle behind the success of this toolkit lies in identifying "confluence." This refers to the convergence of multiple trading indicators all signaling the same information at a specific point or area. By seeking such alignment, traders can significantly enhance the likelihood of successful trades. MS + OBs The chart illustrates a highly bullish setup where the price is rejecting from a bullish order block (POC), while simultaneously forming a bullish Swing Failure Pattern (SFP). This occurs after an internal structure change, marked by a bullish Change of Character (CHoCH). The price broke through a bearish order block, transforming it into a breaker block, further confirming the bullish momentum. The combination of these elements—bullish order blocks, SFP, and CHoCH—creates a powerful bullish signal, reinforcing the potential for upward movement in the market. SFP + Bear OB This chart above displays a bearish setup with a high probability of a price move lower. The price is currently rejecting from a bear order block, which represents a key resistance area where significant selling pressure has previously occurred. A Swing Failure Pattern (SFP) has also formed near this bear order block, indicating that the price briefly attempted to break above a recent high but failed to sustain that upward movement. This failure suggests that buyers are losing momentum, and the market could be preparing for a move to the downside. Additionally, we can toggle on the Deviation Area in the SFP section to highlight potential levels where price deviation might occur. These deviation areas represent zones where the price is likely to react after the Swing Failure Pattern: BUY – SELL sides + EQL The chart showcases a bullish setup with a high probability of price breaking out of the current sell-side resistance level. The market structure indicates a formation of Equal Lows (EQL), which often suggests a build-up of liquidity that could drive the price higher. The presence of strong buy-side pressure (69%), indicated by the green zone at the bottom, reinforces this bullish outlook. This area represents a key support zone where buyers are outpacing sellers, providing the foundation for a potential upward breakout. EQL + Bull ChoCh This chart illustrates a potential bullish setup, driven by the formation of Equal Lows (EQL) followed by a bullish Change of Character (CHoCH). The presence of Equal Lows often signals a liquidity build-up, which can lead to a reversal when combined with additional bullish signals. Liquidity grab + Bull ChoCh + FVGs This chart demonstrates a strong bullish scenario, where several important market dynamics are at play. The price begins its upward momentum from Liquidity grab following a bullish Change of Character (CHoCH), signaling the transition from a bearish phase to a bullish one. As the price progresses, it performs liquidity grabs, which serve to gather the necessary fuel for further movement. These liquidity grabs often occur before significant price surges, as large market participants exploit these areas to accumulate positions before pushing the price higher. The chart also highlights a market imbalance area, showing strong momentum as the price moves swiftly through this zone. In this examples, we see how the combination of multiple “smart money” tools helps identify a potential trade opportunities. This is just one of the many scenarios that traders can spot using this toolkit. Other combinations—such as order blocks, liquidity grabs, fair value gaps, and Swing Failure Patterns (SFPs)—can also be layered on top of these concepts to further refine your trading strategy. 🔵 SETTINGS Window: limit calculation period Swing: limit drawing function Mapping structure: show structural points Algorithmic Logic: (Extreme-Adjusted) Use max high/low or pivot point calculation Algorithmic loopback: pivot point look back Show Last: Amount of Order block to display Hide Overlap: hide overlapping order blocks Construction: Size of the order blocks Fair value gaps: Choose between normal FVG or Breaker FVG Mitigation: (close - wick - avg) point to mitigate the order block/imbalance SFP lookback: find a higher / lower point to improve accuracy Threshold: remove less relevant SFP Equal H&L: (short-mid-long term) display longer term Liquidity Prints: Shows wicks of candles where liquidity was grabbed Sweep Area: Identify Sweep Liquidation areas By combining these indicators in one toolkit, traders are equipped with a comprehensive suite of tools that address every angle of the Smart Money Concept. Instead of relying on disparate tools spread across various platforms, having them integrated into a single, cohesive system allows traders to easily see confluence and make more informed trading decisions.
Pine Script®指标
由BigBeluga提供
127
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action 1. Introduction 1.1 Overview ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active. The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured: import TradingView/ta/10 as tvta // Determine lower timeframe string based on user choice and chart resolution string lower_tf_breakout = use_custom_tf_input ? custom_tf_input : timeframe.isseconds ? "1S" : timeframe.isintraday ? "1" : timeframe.isdaily ? "5" : "60" // Request up/down volume (both positive) = tvta.requestUpAndDownVolume(lower_tf_breakout) Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity. Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate. Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history. Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”) 2. Price‑Structure Backbone Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations. 2.1 What it draws • Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded. • Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly. • Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels. • Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick. 2.2 Key settings • length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels. • pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings. • point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded. • label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price. • Styling inputs for trend lines, horizontal lines and labels (color, width and line style). Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots. These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle. The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable. 3. Breakout Module 3.1 Concept This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled. 3.2 Inputs • lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly. • vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout. • rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution. • ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases). • use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe. • Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width. 3.3 Detection logic 1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume. 2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window. 3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive. 4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history. 5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1). 6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector. Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move. Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold. 4. Market Phase Module (Volume Only) 4.1 Concept Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table. 4.2 Inputs • phase_period_len: Number of bars over which to compute sums and ratios for phase detection. • phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume. • strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation). • Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles. • show_phase_module: Toggles the entire phase detection subsystem. • show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected. 4.3 Detection logic The module computes three families of statistics over the volume window defined by phase_period_len: 1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends. 2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction. 3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues. The algorithm then combines these signals: • For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case. • For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category. If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” . 4.4 Outputs • Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral). • On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences. Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began. Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window. 5. OB/OS Spike Module 5.1 What overbought/oversold means here In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate. 5.2 Inputs • minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print. • syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals. • Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike. • Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable. • Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width. 5.3 Detection logic 1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos. 2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS. 3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold). 4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought. 5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line. Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels. Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow. 6. Buyer/Seller Trap Module 6.1 Concept A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps. 6.2 Inputs • trap_lookback_len: Window length used to rank extremes and detect sweeps. • trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep. • trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.) • trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed. • Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps. • Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart. 6.3 Scoring logic The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped): 1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick. 2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick. 3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand. 4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa. 5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average. The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars. Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label. Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range. 7. Sharp Move Module 7.1 Concept Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation. 7.2 Inputs • sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels. • sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window. • sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax. • sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks. • sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range). • sharpScoreRisk: Minimum number of conditions that must be true to print a risk label. • sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation. • sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution). • Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves. • Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn. 7.3 Conditions (six per side) For each side, the indicator computes six boolean conditions and sums them to form a score: 1. Dominance (instant and cumulative): – Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume. – Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks). 2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish). 3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window. 4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range). 5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile. 6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed. Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores. 7.4 Scoring and labels • Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar. • Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1). • Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled. Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move. Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window. 8. Market‑Maker / Spread‑Capture Module 8.1 Concept Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets. 8.2 Inputs • scalpLookback: Window length used to compute volume averages. • scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple. • scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement. • scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%. • Label settings: ATR length, multiplier, size, colors, connector style and width. • Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels. 8.3 Signal When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled. Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window. 9. Money Flow Module 9.1 Concept To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow. 9.2 Inputs • mf_period_len_mf: Number of bars used for summing buy and sell dollars. • Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width. • Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed. 9.3 Calculations • Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $. • Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum(). • Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate. • Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences. Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context. In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period. 10. Info Table 10.1 Purpose When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active. 10.2 Symbols • ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money. • MA — Moving average. In the table it shows the average value of a series over the lookback period. • Σ (Sigma) — Cumulative sum over the chosen lookback period. • Δ (Delta) — Difference between buy and sell values. • B / S — Buyer and seller share of total volume, expressed as percentages. • Ref. Price — Reference price for breakout calculations, based on the latest pivot. • Status — Indicates whether a breakout condition is currently active (True) or has failed. 10.3 Row definitions 1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period. 2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity. 3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period. 4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume. 5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period. 6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume. 7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more. 8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed. 9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral. 10. Money Flow – The final rows display dollar amounts and status: – ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period. – ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum. – Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively. – Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral. – Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral. The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out). 11. Conclusion & Final Remarks This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart. A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window. Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
Pine Script®指标
由ata_sabanci提供
16
CYCLE BY RiotWolftradingDescription of the "CYCLE" Indicator The "CYCLE" indicator is a custom Pine Script v5 script for TradingView that visualizes cyclic patterns in price action, dividing the trading day into specific sessions and 90-minute quarters (Q1-Q4). It is designed to identify and display market phases (Accumulation, Manipulation, Distribution, and Continuation/Reversal) along with key support and resistance levels within those sessions. Additionally, it allows customization of boxes, lines, labels, and colors to suit user preferences. Main Features Cycle Phases: Accumulation (1900-0100): Represents the phase where large operators accumulate positions. Manipulation (0100-0700): Identifies potential manipulative moves to mislead retail traders. Distribution (0700-1300): The phase where large operators distribute their positions. Continuation/Reversal (1300-1900): Indicates whether the price continues the trend or reverses. 90-Minute Quarters (Q1-Q4): Divides each 6-hour cycle (360 minutes) into four 90-minute quarters (Q1: 00:00-01:30, Q2: 01:30-03:00, Q3: 03:00-04:30, Q4: 04:30-06:00 UTC). Each quarter is displayed with a colored box (Q1: light purple, Q2: light blue, Q3: light gray, Q4: light pink) and labels (defaulted to black). Support and Resistance Visualization: Draws boxes or lines (based on settings) showing the high and low levels of each session. Optionally displays accumulated volume at the highs and lows within the boxes. Daily Lines and Last 3 Boxes: How to Use the Indicator Step 1: Add the Indicator to TradingView Open TradingView and select the chart where you want to apply the indicator (e.g., UMG9OOR on a 5-minute timeframe, as shown in the screenshot). Go to the Pine Editor (at the bottom of the TradingView interface). Copy and paste the provided code. Click Compile and then Add to Chart. Step 2: Configure the Indicator Click on the indicator name on the chart ("CYCLE") and select Settings (or double-click the name). Adjust the options based on your needs: Cycle Phases: Enable/disable phases (Accumulation, Manipulation, Distribution, Continuation/Reversal) and adjust their time slots if needed. 90-Minute Quarters: Enable/disable quarters (Q1-Q4). Step 3: Interpret the Indicator Identify Cycle Phases: Observe the red boxes indicating the phases (Accumulation, Manipulation, etc.). The high and low levels within each phase are potential support/resistance zones. If volume is enabled, pay attention to the accumulated volume at highs and lows, as it may indicate the strength of those levels. Use the 90-Minute Quarters (Q1-Q4): The colored boxes (Q1-Q4) divide the day into 90-minute segments. Each quarter shows the price range (high and low) during that period. Use these boxes to identify price patterns within each quarter, such as breakouts or consolidations. The labels (Q1, Q2, etc.) help you track time and anticipate potential moves in the next quarter. Analyze Support and Resistance: The high and low levels of each phase/quarter act as support and resistance. Daily lines (if enabled) show key levels from the previous day, useful for planning entries/exits. The "last 3 boxes below price" (if enabled) highlight potential support levels the price might target. Avoid Manipulation: During the Manipulation phase (0100-0700), be cautious of sharp moves or false breakouts. Use the high/low levels of this phase to identify potential traps (as explained in your first question about manipulation candles). Step 4: Trading Strategy Entries and Exits: Support/Resistance: Use the high/low levels of phases and quarters to set entry or exit points. For example, if the price bounces off a Q1 support level, consider a buy. Breakouts: If the price breaks a high/low of a quarter (e.g., Q2), wait for confirmation to enter in the direction of the breakout. Volume: If accumulated volume is high near a key level, that level may be more significant. Risk Management: Place stop-loss orders below lows (for buys) or above highs (for sells) identified by the indicator. Avoid trading during the Manipulation phase unless you have a specific strategy to handle false breakouts. Time Context: Use the quarters (Q1-Q4) to plan your trades based on time. For example, if Q3 is typically volatile in your market, prepare for larger moves between 03:00-04:30 UTC. Step 5: Adjustments and Testing Test on Different Timeframes: The indicator is set for a 5-minute timeframe (as in the screenshot), but you can test it on other timeframes (e.g., 1-minute, 15-minute) by adjusting the time slots if needed. Adjust Colors and Styles: If the default colors are not visible on your chart, change them for better clarity. --- 📌 1. **Accumulation: Strong Institutional Activity** - During the **accumulation phase, we see **high volume: 82.773K, which suggests strong buying interest**, likely from institutional players. - This sets the base for the following upward move in price. --- 📌 2. **Manipulation: False Breakout with Lower Volume** - Later, there's a manipulation phase where price breaks above previous highs, but the volume (71.814K) is **lower than during accumulation**. - This implies that buyers are not as aggressive as before—no real demandbehind the breakout. - It’s likely a bull trap, where smart money is selling into the breakout to exit their positions. --- ### 📌 3. Distribution: Weakness and Lack of Demand - The market enters a distribution phase, and volume drops even further (only 7.914K). - Price struggles to go higher, and you start seeing rejections at the top. - This shows that demand is drying up, and smart money is offloading positions**—not accumulating anymore. --- ### 💡 Why Take the Short Here? - Volume is not increasing with new highs—showing weak demand**. - The manipulation volume is weaker than the accumulation volume, confirming the breakout was likely false. - Structure starts to break down (Q levels falling), which confirms weakness. - This creates a high-probability short setup: - **Entry:** after confirmation of distribution and structural breakdown. - **Stop loss:** above the manipulation high. - **Target:** down toward previous lows or value zones. --- ### ✅ Conclusion Since the manipulation volume failed to exceed the accumulation volume, the breakout lacked real strength. Combined with decreasing volume in the distribution phase, this indicates fading demand and supply taking control—which justifies entering a short position.
Pine Script®指标
由anarkiacapital提供
1
Pivot Points LIVE [CHE]Title: Pivot Points LIVE Indicator Subtitle: Advanced Pivot Point Analysis for Real-Time Trading Presented by: Chervolino Date: September 24, 2024 Introduction What are Pivot Points? Definition: Pivot Points are technical analysis indicators used to determine potential support and resistance levels in financial markets. Purpose: They help traders identify possible price reversal points and make informed trading decisions. Overview of Pivot Points LIVE : A comprehensive indicator designed for real-time pivot point analysis. Offers advanced features for enhanced trading strategies. Key Features Pivot Points LIVE Includes: Dynamic Pivot Highs and Lows: Automatically detects and plots pivot high (HH, LH) and pivot low (HL, LL) points. Customizable Visualization: Multiple options to display markers, price labels, and support/resistance levels. Fractal Breakouts: Identifies and marks breakout and breakdown events with symbols. Line Connection Modes: Choose between "All Separate" or "Sequential" modes for connecting pivot points. Pivot Extension Lines: Extends lines from the latest pivot point to the current bar for trend analysis. Alerts: Configurable alerts for breakout and breakdown events. Inputs and Configuration Grouping Inputs for Easy Customization: Source / Length Left / Length Right: Pivot High Source: High price by default. Pivot Low Source: Low price by default. Left and Right Lengths: Define the number of bars to the left and right for pivot detection. Colors: Customizable colors for pivot high and low markers. Options: Display Settings: Show HH, LL, LH, HL markers and price labels. Display support/resistance level extensions. Option to show levels as a fractal chaos channel. Enable fractal breakout/down symbols. Line Connection Mode: Choose between "All Separate" or "Sequential" for connecting lines. Line Management: Set maximum number of lines to display. Customize line colors, widths, and styles. Pivot Extension Line: Visibility: Toggle the display of the last pivot extension line. Customization: Colors, styles, and width for extension lines. How It Works - Calculating Pivot Points Pivot High and Pivot Low Detection: Pivot High (PH): Identified when a high price is higher than a specified number of bars to its left and right. Pivot Low (PL): Identified when a low price is lower than a specified number of bars to its left and right. Higher Highs, Lower Highs, Higher Lows, Lower Lows: Higher High (HH): Current PH is higher than the previous PH. Lower High (LH): Current PH is lower than the previous PH. Higher Low (HL): Current PL is higher than the previous PL. Lower Low (LL): Current PL is lower than the previous PL. Visual Elements Markers and Labels: Shapes: HH and LH: Downward triangles above the bar. HL and LL: Upward triangles below the bar. Labels: Optionally display the price levels of HH, LH, HL, and LL on the chart. Support and Resistance Levels: Extensions: Lines extending from pivot points to indicate potential support and resistance zones. Chaos Channels: Display levels as a fractal chaos channel for enhanced trend analysis. Fractal Breakout Symbols: Buy Signals: Upward triangles below the bar. Sell Signals: Downward triangles above the bar. Slide 7: Line Connection Modes All Separate Mode: Description: Connects pivot highs with pivot highs and pivot lows with pivot lows separately. Use Case: Ideal for traders who want to analyze highs and lows independently. Sequential Mode: Description: Connects all pivot points in the order they occur, regardless of being high or low. Use Case: Suitable for identifying overall trend direction and momentum. Pivot Extension Lines Purpose: Trend Continuation: Visualize the continuation of the latest pivot point's price level. Customization: Colors: Differentiate between bullish and bearish extensions. Styles: Solid, dashed, or dotted lines based on user preference. Width: Adjustable line thickness for better visibility. Dynamic Updates: The extension line updates in real-time as new bars form, providing ongoing trend insights. Alerts and Notifications Configurable Alerts: Fractal Break Arrow: Triggered when a breakout or breakdown occurs. Long and Short Signals: Specific alerts for bullish breakouts (Long) and bearish breakdowns (Short). Benefits: Timely Notifications: Stay informed of critical market movements without constant monitoring. Automated Trading Strategies: Integrate with trading bots or automated systems for executing trades based on alerts. Customization and Optimization User-Friendly Inputs: Adjustable Parameters: Tailor pivot detection sensitivity with left and right lengths. Color and Style Settings: Match the indicator aesthetics to personal or platform preferences. Line Management: Maximum Lines Displayed: Prevent chart clutter by limiting the number of lines. Dynamic Line Handling: Automatically manage and delete old lines to maintain chart clarity. Flexibility: Adapt to Different Markets: Suitable for various financial instruments including stocks, forex, and cryptocurrencies. Scalability: Efficiently handles up to 500 labels and 100 lines for comprehensive analysis. Practical Use Cases Identifying Key Support and Resistance: Entry and Exit Points: Use pivot levels to determine optimal trade entry and exit points. Trend Confirmation: Validate market trends through the connection of pivot points. Breakout and Breakdown Strategies: Trading Breakouts: Enter long positions when price breaks above pivot highs. Trading Breakdowns: Enter short positions when price breaks below pivot lows. Risk Management: Setting Stop-Loss and Take-Profit Levels: Utilize pivot levels to place strategic stop-loss and take-profit orders. Slide 12: Benefits for Traders Real-Time Analysis: Provides up-to-date pivot points for timely decision-making. Enhanced Visualization: Clear markers and lines improve chart readability and analysis efficiency. Customizable and Flexible: Adapt the indicator to fit various trading styles and strategies. Automated Alerts: Stay ahead with instant notifications on key market events. Comprehensive Toolset: Combines pivot points with fractal analysis for deeper market insights. Conclusion Pivot Points LIVE is a robust and versatile indicator designed to enhance your trading strategy through real-time pivot point analysis. With its advanced features, customizable settings, and automated alerts, it equips traders with the tools needed to identify key market levels, execute timely trades, and manage risks effectively. Ready to Elevate Your Trading? Explore Pivot Points LIVE and integrate it into your trading toolkit today! Q&A Questions? Feel free to ask any questions or request further demonstrations of the Pivot Points LIVE indicator.
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