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Volume Flow Indicator [LazyBear]VFI,introduced by Markos Katsanos, is based on the popular On Balance Volume (OBV) but with three very important modifications: * Unlike the OBV, indicator values are no longer meaningless. Positive readings are bullish and negative bearish. * The calculation is based on the day's median (typical price) instead of the closing price. * A volatility threshold takes into account minimal price changes and another threshold eliminates excessive volume. A simplified interpretation of the VFI is: * Values above zero indicate a bullish state and the crossing of the zero line is the trigger or buy signal. * The strongest signal with all money flow indicators is of course divergence. I have exposed options to plot a signal EMA. All parameters are configurable. Markos suggests using 0.2 coeff for day trading and 0.1 for intra-day. More info: www.precisiontradingsystems.com
Pine Script®指标
由LazyBear提供
100
Indicator: Relative Volume Indicator & Freedom Of MovementRelative Volume Indicator ------------------------------ RVI is a support-resistance technical indicator developed by Melvin E. Dickover. Unlike many conventional support and resistance indicators, the Relative Volume Indicator takes into account price-volume behavior in order to detect the supply and demand pools. These pools are marked by "Defended Price Lines" (DPLs), also introduced by the author. RVI is usually plotted as a histogram; its bars are highlighted (black, by default) when the volume is unusually large. According to the author, this happens if the indicator value exceeds 2.0, thus signifying that a possible DPL is present. DPLs are horizontal lines that run across the chart at levels defined by following conditions: * Overlapping bars: If the indicator spike (i.e., indicator is above 2.0 or a custom value) corresponds to a price bar overlapping the previous one, the previous close can be used as the DPL value. * Very large bars: If the indicator spike corresponds to a price bar of a large size, use its close price as the DPL value. * Gapping bars: If the indicator spike corresponds to a price bar gapping from the previous bar, the DPL value will depend on the gap size. Small gaps can be ignored: the author suggests using the previous close as the DPL value. When the gap is big, the close of the latter bar is used instead. * Clustering spikes: If the indicator spikes come in clusters, use the extreme close or open price of the bar corresponding to the last or next to last spike in cluster. DPLs can be used as support and resistance levels. In order confirm and refine them, RVI is used along with the FreedomOfMovement indicator discussed next. Freedom of Movement Indicator ------------------------------ FOM is a support-resistance technical indicator, also by Melvin E. Dickover. FOM is the ratio of relative effect (relative price change) to the relative effort (normalized volume), expressed in standard deviations. This value is plotted as a histogram; its bars are highlighted (black, by default( when this ratio is unusually high. These highlighted bars, or "spikes", define the positioning of the DPLs. Suggestions for placing DPLs are the same as for the Relative Volume Indicator discussed above. Note that clustering spikes provide the strongest DPLs while isolated spikes can be used to confirm and refine those provided by the Relative Volume Indicator. Coincidence of spikes of the two indicator can be considered a sign of greater strength of the DPL. More info: S&C magazine, April 2014. I am still trying these on various instruments to understand the workings more. Don't forget to share what you learn -- any use cases / ideal scenarios / gotchas, would love to hear them all.
Pine Script®指标
由LazyBear提供
25
3 new Indicators - PGO / RAVI / TIIMy "to-publish" list is getting too big, so decided to push out 3 indicators in the same chart Feel free to "make mine" and use :) Leave a comment on what you think. Pretty Good Oscillator ---------------------------------------- This indicator, by Mark Johnson, measures the distance of the current close from its N-day simple moving average, expressed in terms of an average true range (see Average True Range) over a similar period. So for instance a PGO value of +2.5 would mean the current close is 2.5 average days' range above the SMA. Johnson's approach was to use it as a breakout system for longer term trades. If the PGO rises above 3.0 then go long, or below -3.0 then go short, and in both cases exit on returning to zero (which is a close back at the SMA). Indicator marks all these areas (3/-3/0) Rapid Adaptive Variance Indicator --------------------------------------------------------- RAVI is a simple indicator, by Tushar Chande, to show whether a stock is trending or not. Unlike ADX, RAVI measures only the trend intensity, it doesn't distinguish which way the trend is going. Rising RAVI shows the beginning of a trend or an increase in trend intensity, a decreasing slope signifies decreasing intensity. Also, RAVI often reacts more quickly and exhibits a more pronounced curve than ADX. The standard values for daily charts are 7 and 65. For hourly charts, the most common averaging periods are 12 and 72 or 24 and 120. The signal lines suggested are from +/- 0.3% to +/-1%. I haven't added any markings as these signals are instrument-specific. I suggest doing some back testing and adding these accordingly. Trend Intensity Index -------------------------------------- TII, by M. H. Pee, measures the strength of a trend, by looking at what proportion of the past "n" days prices have been above or below the level of today's "x"-day simple moving average. You can configure "n" via options page. "x" is calculated as "2 times n". TII moves between 0 and 100. A strong uptrend is indicated when TII is above 80. A strong downtrend is indicated when TII is below 20. Pee recommended entering trades when levels of 80 on the upside or 20 on the downside are reached. Indicator marks these lines for easy reference.
Pine Script®指标
由LazyBear提供
22
[2022]Volume Flow v3 with alertsIndicators are an essential part of technical analysis of cryptocurrency. Their main function is to predict market direction based on historic price, cryptocurrency volume and other information. There are several types of crypto indicators illustrating various parameters (trend, volatility, volume, momentum, etc.) but in this article we will look at volume indicators. Volume indicators demonstrate changing of trading volume over time. This information is very useful as crypto trading volume displays how strong the current trend is. For example, if the price goes up and the volume is high then the trend is strong and will more likely last longer. There are various volume indicators, but we’ll talk about the most popular ones, such as: On Balance Volume Accumulation/Distribution Line Money Flow Index Chaikin Oscillator Chaikin Money Flow Ease of Movement
Pine Script®指标
由Peggoy提供
Gold Option Signals with EMA and RSIIndicators: Exponential Moving Averages (EMAs): Faster to respond to recent price changes compared to simple moving averages. RSI: Measures the magnitude of recent price changes to evaluate overbought or oversold conditions. Signal Generation: Buy Call Signal: Generated when the short EMA crosses above the long EMA and the RSI is not overbought (below 70). Buy Put Signal: Generated when the short EMA crosses below the long EMA and the RSI is not oversold (above 30). Plotting: EMAs: Plotted on the chart to visualize trend directions. Signals: Plotted as shapes on the chart where conditions are met. RSI Background Color: Changes to red for overbought and green for oversold conditions. Steps to Use: Add the Script to TradingView: Open TradingView, go to the Pine Script editor, paste the script, save it, and add it to your chart. Interpret the Signals: Buy Call Signal: Look for green labels below the price bars. Buy Put Signal: Look for red labels above the price bars. Customize Parameters: Adjust the input parameters (e.g., lengths of EMAs, RSI levels) to better fit your trading strategy and market conditions. Testing and Validation To ensure that the script works as expected, you can test it on historical data and validate the signals against known price movements. Adjust the parameters if necessary to improve the accuracy of the signals.
Pine Script®指标
由LunaDogeSaving提供
1
CCI-RSI MR Indicators: Bollinger Bands (20 period, 2σ) RSI (14 period) and Simple moving average of RSI (5 period) CCI (20 period) SMA (5 period) Entry Conditions: Buy when: Swing low (5) should be lower than the highest of lower BB (3 periods) Both RSI crossover RSI_5 and CCI crossover -100 should have happened within last 3 candles (including the current candle) Once all the above conditions are met, the close should be higher than SMA (5) within the next 3 candles After condition 3 is satisfied, we enter the trade at next candle’s open Stop loss will be at 1 tick lower than previous swing low Sell when: Swing high (5) should be higher than the lowest of upper BB (3 periods) Both RSI crossunder RSI_5 and CCI crossunder 100 should have happened within last 3 candles (including the current candle) Once all the above conditions are met, the close should be lower than SMA (5) within the next 3 candles After condition 3 is satisfied, we enter the trade at next candle’s open Stop loss will be at 1 tick higher than previous swing high Exit Conditions: Since it’s mean reversion strategy we’ll be having only 2 target exits with a trailing stop loss after target price 1 is achieved. Target exit price 1 & 2 are decided based on the risk ‘R’ for each trade Depending on the instrument and time frame a trailing stop loss of 0.5R or 1R has opted. A stop limit is placed @Entry_price +- 2*ATR(20) to offset the risk of losing significantly more than 1xR in a trade
Pine Script®策略
由monikabhay提供
1
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling. A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools. The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured. Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns. The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration. How does it work? This indicator calculates acceleration based the highs and lows of each dataset Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration It then plots multiple lines with customizable variance from the primary selected length Practical Tips: The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles. The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
Pine Script®指标
由NantzOS提供
Parabolic Scalp Take Profit[ChartPrime]Indicators can be a great way to signal when the optimal time is for taking profits. However, many indicators are lagging in nature and will get market participants out of their trades at less than optimal price points. This take profit indicator uses the concept of slope and exponential gain to calculate when the optimal time is to take profits on your trades, thus making this a leading indicator. Usage: In essence the indicator will draw a parabolic line that starts from the market participants entry point and exponentially grows the slope of the line eventually intersecting with the price action. When price intersects with the parabolic line a take profit signal will appear in the form of an x. We have found that this take profit indicator is especially useful for scalp trades on lower timeframes. How To Use: Add the indicator to the chart. Click on the candle which the trade is on. Click on either the price which the trade will be at, or at the bottom of the candle in a long, or the top of a candle in a short. Select long or short. Open the settings of the indicator and adjust the aggressiveness to the desired value. Settings: - Start Time -- This is the bar in which your entry will be at, or occured at and the script will ask you to click on the bar with your mouse upon first adding the script. - Start Price -- This is the price in which the entry will be at, or was at and the script will ask you to click on the price with your mouse upon first adding the script. - Long/Short -- This is a setting which lets the script know if it is a long or a short trade, and the script will ask you to confirm this upon first adding it to the chart. - Aggressiveness -- This directly affects how aggressive the exponential curve is. A value of 101 is the lowest possible setting, indicating a very non-aggressive exponential buildup. A value of 200 is the highest and most aggressive setting, indicating a doubling effect per bar on the slope.
Pine Script®指标
由ChartPrime提供
5
Alson Chew PAM EXE and Mother BarIndicators for strategies taught by Alson Chew's Price Action Manipulation (PAM) course Two functions. First it identifies EXE bars (Pin, Mark, Icecream bars). Second it identifies Mother bars and draws an extension line for 6 bars. Applicable to all time frames and can customise how many signals to show. To be used in conjunction with trading strategies like - 20 SMA, 50 SMA, 200 SMA FS formation - Force Bottom, Force Top FS formation - UR1 and DR1 using EXE Bar
Pine Script®指标
由LimYX提供
1
Neeson Crypto Cycle - Super Enhanced EditionThe "Neeson Crypto Cycle - Super Enhanced Edition": A Philosophical and Practical Framework for Market Analysis Originality & Core Philosophy Most trading indicators focus on a single domain: pure price action, a specific economic theory, or a handful of technical oscillators. The "Neeson Crypto Cycle" breaks this paradigm. Its fundamental originality lies not in inventing one new mathematical formula, but in architecting a multi-dimensional, multi-timeframe convergence framework. It operates on a core philosophical premise: financial markets are Complex Adaptive Systems (CAS) influenced by a symphony of concurrent cycles. These cycles range from mathematical and technical ones visible on the chart, to fundamental economic rhythms, down to collective human psychology and even speculative meta-patterns. The script is built as a "dashboard of dashboards," attempting to quantify and visualize these disparate layers on a single pane. It does not claim predictive certainty but aims to provide a holistic situational awareness, allowing the trader to identify when multiple, unrelated cycles from different domains align (convergence) or conflict (divergence). What It Does & How It Achieves It The indicator functions as a comprehensive market-phase and sentiment analysis engine implemented directly on the TradingView chart. It is an overlay indicator that provides visual plots, background coloring, signal labels, and, most notably, extensive multi-table data panels. Its implementation can be broken down into several operational layers: 1. The Core Technical Cycle Layer: This is the foundational price-based engine. It simultaneously tracks multiple proprietary cyclical models derived from moving average crossovers with non-standard periods believed to capture crypto-specific rhythms. CCT Pi Cycle: Uses the interaction between a 150-period EMA / 471-period SMA pair (for "bottom" identification) and a 111-period SMA / (350-period SMA * 2) pair (for "top" identification). It identifies golden/death crosses within these specific pairs. Atlantean Signals: A variant using similar periods (471, 150, 350, 111) but with different multipliers (e.g., 0.745) and crossover logic to define "Market Bottom," "Bull Market Start," and "Market Top" events. Bitcoin Cycle: Based on the interaction between a 116-period SMA and a doubled 365-period SMA. Golden Pi Cycle: Another variant using SMAs of 111, 350, 150, and 471 periods. These are not just four random moving average systems; they are distinct models targeting different aspects of the purported "Pi-based" and long-term cyclicality in Bitcoin's price history. The script visually plots these lines and labels their crossover events. 2. The Market Phase & Structural Context Layer: Background Coloring: It dynamically colors the chart background (blue for "Bottom to Top" phase, orange for "Top to Bottom" phase) based on the sequential logic of Atlantean signals, providing immediate visual context for the perceived market regime. Halving Event Annotations: It marks key historical and projected Bitcoin halving dates with vertical lines and labels, anchoring price action to this fundamental supply schedule. 3. The Quantitative Dashboard Layer (Technical & On-Chain): This is where the script transitions from chart plotting to an information system. It renders multiple fixed tables on the chart (bottom-left, bottom-center, bottom-right) only on the last bar. Technical Sentiment Dashboard (Right): A massive table aggregating over a dozen classic and advanced technical indicators (RSI, MACD, Bollinger Bands, Stochastic, ADX, Ichimoku, Parabolic SAR, Fibonacci levels, etc.). For each, it shows a calculated Status (e.g., "Overbought"), a numeric Value, and a concise Advice (e.g., "Sell"). It then groups these into "Cycle Indicators" (status of the core models above) and "Risk Management" metrics (Max Drawdown, Sharpe Ratio simulation, volatility). Synthetic On-Chain Metrics Dashboard (Center): Since TradingView cannot pull real on-chain data, the script ingeniously simulates 80 different on-chain metrics (NVT, MVRV, Hash Rate, Exchange Flows, HODL Waves, S2F, etc.) by deriving them from price and volume data. Each metric displays a name, a simulated value, a signal ("Overvalued"), and a color code. This provides a proxy for the fundamental/network health narrative. Multi-Cycle Systems Dashboard (Left): This table transcends traditional finance, cataloging the status of various long-wave cycles: Economic Cycles: Kondratieff (50-60yr), Kuznets (15-25yr), Juglar (7-11yr), Kitchin (3-5yr), etc., each with a hardcoded current phase (e.g., "Recession (2020-2030)"), impact, and advice. Speculative & Novel Cycles: Lunar, Seasonal, Commodity Super, Debt, and Innovation cycles. Esoteric Systems: A full celestial (astrological) positioning of planets and a Four Pillars of Destiny (Bazi) reading, each with assigned market "impact" and "advice." 4. The Synthesis & Alert Layer: Comprehensive Statistics: The right dashboard concludes with a tally of "Bullish vs. Bearish Signals" from across all technical and cycle indicators, generating an "Overall Sentiment" score. Alert System: It creates TradingView alert conditions for every major crossover event from the core cycle models (CCT, Atlantean, Bitcoin, Golden Pi), allowing for automated notifications. Underlying Calculation Logic & Rationale The logic is built on convergence and weighted evidence. The creator's hypothesis appears to be that significant market turning points are rarely signaled by one indicator in isolation. Instead, they occur when: Multiple Price-Based Cycle Models Align: When the CCT, Atlantean, and Bitcoin cycles all approach a "bottom" or "top" signal near the same time, the probability of a true phase change is considered higher. Technical Conditions Match the Cycle Phase: A "Bull Market Start" signal is more credible if accompanied by oversold RSI/Stochastic, bullish MACD, and money flowing in (rising OBV). The Macro Backdrop Supports the Narrative: The script hardcodes a specific macroeconomic worldview (e.g., "Tightening Credit Cycle," "AI Revolution Tech Cycle") to remind the user of the broader environment the price cycles are operating within. Awareness of "Non-Rational" Drivers: By including astrological and Bazi elements, the script acknowledges that market narratives and crowd psychology can sometimes be influenced by or framed within these non-traditional systems. It doesn't necessarily predict with them but tracks them as potential sentiment catalysts. The calculations for technical indicators are standard. The novelty is in their collective presentation and the synthetic creation of supporting data realms (on-chain, economic, esoteric) to form a complete, albeit highly speculative, "universe" of market-influencing factors. How to Use It: A Practical Guide This is not a "set and forget" system that generates simple buy/sell arrows. It is a decision-support and research tool. Market Phase Identification: First, look at the background color and the status of the core cycle models in the right dashboard. Are you in a blue "Bottom to Top" phase? Check if the Atlantean "Bull Market Start" is active. This sets your primary bias. Seeking Convergent Signals: Before acting on a cycle signal, cross-reference it with the Technical Sentiment dashboard. For example, an Atlantean "Market Top" signal is stronger if the RSI and Stochastic also show "Overbought," the MACD is "Bearish," and the Fear & Greed Index is in "Extreme Greed." Look for clusters of agreement. Context from Other Dimensions: Check the On-Chain dashboard. Does the synthetic data suggest the network is "Overheated" or "Undervalued"? Check the Economic Cycle table. Does the perceived long-wave phase (e.g., "Kondratieff Recession") support a risk-on or risk-off stance? This provides narrative context for your trade thesis. Risk Management Integration: Before sizing a position, check the Risk Management section. What is the current "Max Drawdown" and "Volatility Risk"? The dashboard suggests position sizing ("Light," "Medium," "Heavy") based on this. Utilizing Alerts: Set alerts for the key cycle crossovers (CCT, Atlantean, etc.). When an alert triggers, it's your cue to open the chart and perform the full multi-dimensional convergence analysis described above, rather than acting on the alert alone. In essence, the "Neeson Crypto Cycle" is a conceptual trading terminal. It posits that the modern trader, especially in crypto, must synthesize information from technicals, fundamentals, macroeconomics, and market psychology. By attempting to model all these facets in one place—even through estimation and simulation—it aims to give the user a structured framework for asking the right questions about the current state of the market, rather than providing simplistic, one-dimensional answers. Its value is in the breadth of its perspective and the discipline of multi-factor confirmation it encourages.
Pine Script®指标
由neeson1987提供
Multi-Signal the FlasherTitle: Multi-Signal Flasher - External Signal Alert System Short Description: Visual screen flash alerts triggered by external indicator signals. Supports 4 signal sources with separate Long/Short flash colors. Description: This indicator provides a powerful visual alert system that flashes your entire chart when external indicator signals fire. Perfect for traders who need unmissable alerts when their custom signals trigger. Features 4 External Signal Sources - Connect up to 4 different indicators Long/Short Classification - Assign each signal as Long or Short for different colored flashes OR Logic - Any enabled signal firing triggers the flash Customizable Flash Colors - Separate color schemes for Long and Short signals Adjustable Cycles - Control how many times the colors alternate On-Screen Message - Displays "LONG SIGNAL!" or "SHORT SIGNAL!" during flash How It Works The indicator monitors your selected external signal sources. The trigger fires when a signal transitions from no value to a value >= 1, the chart flashes with alternating colors to grab your attention. Signals set to Long → Flash with Long colors (default: green/purple) Signals set to Short → Flash with Short colors (default: red/yellow) Setup Add your signal indicators to the chart first Add this indicator In settings, enable Signal 1-4 as needed Select each signal's plot from the dropdown Set each signal as Long or Short Check "Enable the Flasher" to arm the system Customize colors and messages to your preference Important Notes ⚠️ Seizure Warning - This indicator flashes colors rapidly. User discretion is advised for those with photosensitive epilepsy. Flashes only occur in real-time - historical bars will not trigger flashes The trigger fires when a signal transitions from no value to a value >= 1. not while signal persists Color cycling depends on feed updates Use Cases Multi-indicator confluence alerts Separate long/short signal systems High-visibility scalping alerts Any system where missing a signal is costly Credits: Original "the Flasher" code by @allanster Core flash function and table-based color cycling system Modified by @m4ybee Multi-signal source support (4 inputs) External indicator integration via input.source() Long/Short signal classification OR logic signal combining Separate color schemes for Long/Short
Pine Script®指标
由mm44yybbee提供
Smart Money Flow Signals [QuantAlgo]🟢 Overview The Smart Money Flow Signals indicator synthesizes significant volume-price dynamics through multi-component analysis to identify potential accumulation and distribution phases driven by substantial market participants. It combines Money Flow Index momentum, Chaikin Money Flow accumulation patterns, volume-weighted price momentum, and buying/selling pressure metrics into a unified composite oscillator that quantifies periods of concentrated capital movement, helping traders and investors identify conditions where significant volume participants may be actively positioning across multiple market conditions and timeframes. 🟢 How It Works The indicator's core methodology lies in its weighted composite approach, where multiple volume-price components are calculated sequentially and then integrated to create a comprehensive significant flow activity signal. First, the Money Flow Index (MFI) is calculated to measure buying and selling pressure by incorporating volume into price momentum analysis: raw_money_flow = source * volume positive_flow = source >= source ? raw_money_flow : 0 negative_flow = source < source ? raw_money_flow : 0 positive_money_flow = math.sum(positive_flow, mfi_period) negative_money_flow = math.sum(negative_flow, mfi_period) money_flow_index = 100 - 100 / (1 + positive_money_flow / negative_money_flow) This creates an RSI-style momentum indicator that tracks whether money (price × volume) is flowing into or out of the asset, with values ranging from 0 to 100 where readings above 50 suggest buying pressure dominance. Then, Chaikin Money Flow (CMF) is computed to evaluate accumulation and distribution by analyzing where prices close within each bar's range, weighted by volume: money_flow_multiplier = high != low ? (close - low - (high - close)) / (high - low) : 0 money_flow_volume = money_flow_multiplier * volume volume_sma = ta.sma(volume, trend_period) chaikin_money_flow = volume_sma != 0 ? ta.sma(money_flow_volume, trend_period) / volume_sma : 0 Positive CMF values indicate accumulation (closes near the high of the range), while negative values indicate distribution (closes near the low of the range), with volume weighting emphasizing periods of significant participation. Next, Volume Analysis is performed to quantify current volume intensity relative to historical averages: volume_average = ta.sma(volume, trend_period) volume_strength = volume_average != 0 ? volume / volume_average : 1 volume_weight = math.log(volume_strength + 1) The logarithmic transformation creates a volume weight that amplifies signals during high-volume periods while preventing extreme volume spikes from overwhelming the composite calculation. Following this, Buy/Sell Pressure is quantified by comparing cumulative volume during bullish versus bearish candles: buying_pressure = math.sum(volume * (close >= open ? 1 : 0), trend_period) selling_pressure = math.sum(volume * (close < open ? 1 : 0), trend_period) pressure_ratio = (buying_pressure - selling_pressure) / (buying_pressure + selling_pressure) * 100 This creates a directional pressure ratio that reveals whether significant participants are predominantly buying or selling, expressed as a percentage between -100 (all selling) and +100 (all buying). Then, Volume-Weighted Momentum is calculated through an exponential smoothing channel that adjusts price deviation based on volume intensity: exponential_smooth_average = ta.ema(source, momentum_channel_period) deviation = ta.ema(math.abs(source - exponential_smooth_average), momentum_channel_period) channel_index = deviation != 0 ? (source - exponential_smooth_average) / (0.015 * deviation) * (1 + volume_weight * 0.5) : 0 This channel index measures how far price has deviated from its exponential average relative to typical deviation, with the volume weight multiplier (1 + volume_weight * 0.5) amplifying the signal when significant volume accompanies the price movement. Finally, the Composite Wave is constructed by combining all components with specific weighting to create the final oscillator: momentum_wave = ta.ema(channel_index, trend_period) money_flow_wave = (money_flow_index - 50) * 1.2 chaikin_flow_wave = chaikin_money_flow * 100 composite_wave = momentum_wave * 0.5 + chaikin_flow_wave * 0.3 + money_flow_wave * 0.2 smoothed_wave = ta.sma(composite_wave, signal_smoothing) This creates a multi-dimensional volume flow oscillator that combines price-volume momentum, accumulation-distribution patterns, and buying-selling pressure into a single signal, providing traders with probabilistic insights into periods of concentrated market activity and directional bias based on weighted component convergence. 🟢 Signal Interpretation ▶ Positive Values (Above Zero, Green): Composite money flow above equilibrium indicating net accumulation pressure, positive buying volume dominance, and bullish volume-price alignment = Favorable conditions for long positions, significant capital flowing into the asset = Buy/hold opportunities ▶ Negative Values (Below Zero, Red): Composite money flow below equilibrium indicating net distribution pressure, negative selling volume dominance, and bearish volume-price alignment = Unfavorable conditions for long positions, significant capital flowing out of the asset = Sell/short opportunities ▶ Extreme Overbought Zone: Excessive bullish money flow indicating potential accumulation exhaustion, where buying pressure may have reached unsustainable levels with elevated reversal risk = Caution on new longs, potential distribution phase beginning, profit-taking zone for existing positions ▶ Extreme Oversold Zone: Excessive bearish money flow indicating potential distribution exhaustion, where selling pressure may have reached unsustainable levels with elevated reversal risk = Caution on new shorts, potential accumulation phase beginning, buying opportunity zone for contrarian entries ▶ Smoothed Trend Line (White) Alignment: When the smoothed trend line confirms the composite wave direction, it validates the underlying volume-price trend and filters false signals caused by short-term noise ▶ Volume Intensity Correlation: Gradient intensity (color saturation) reflects combined wave strength, volume participation, and directional alignment, where darker/more saturated colors indicate stronger concentrated activity and higher-probability directional moves 🟢 Features ▶ Preconfigured Presets: Three optimized parameter configurations accommodate different trading styles, timeframes, and market analysis approaches. 1. "Default" provides balanced volume flow measurement suitable for swing trading on 4-hour and daily charts, offering moderate responsiveness to money flow shifts with standard RSI-equivalent MFI period and moderate smoothing for most market conditions. 2. "Fast Response" delivers heightened sensitivity optimized for active intraday trading and scalping on 1-minute to 1-hour charts, using compressed calculation periods across all components and minimal smoothing to capture rapid volume flow changes and quick trend shifts as they develop, ideal for early entry/exit opportunities with acceptance of increased signal frequency during consolidation. 3. "Smooth Trend" offers conservative extreme identification ideal for position trading and long-term analysis on daily to weekly charts, employing extended periods across all money flow components with substantial smoothing to filter short-term noise and isolate only strong, sustained accumulation and distribution phases driven by significant volume participants. ▶ Built-in Alerts: Seven alert conditions enable comprehensive automated monitoring of significant money flow transitions and extreme market states. 1. "Bullish Flow" triggers when the composite wave crosses above zero, signaling the shift from distribution to accumulation and concentrated buying activity beginning. 2. "Bearish Flow" activates when the composite wave crosses below zero, signaling the shift from accumulation to distribution and concentrated selling activity starting. 3. "Any Flow Direction Change" provides a combined notification for either bullish or bearish crossover regardless of direction, useful for general money flow momentum shifts. 4. "Extreme Overbought" alerts when the composite wave reaches or exceeds the overbought threshold (default +60), indicating excessive buying pressure and potential exhaustion. 5. "Extreme Oversold" notifies when the composite wave reaches or falls below the oversold threshold (default -60), indicating excessive selling pressure and potential capitulation. 6. "Overbought Reversal" triggers specifically when the wave crosses back down through the overbought level after being extended, signaling the beginning of distribution from extreme levels. 7. "Oversold Reversal" activates when the wave crosses back up through the oversold level after being extended, signaling the beginning of accumulation from extreme levels. ▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast and immediate identification of bullish versus bearish volume flow conditions across various devices and screen sizes. Optional bar coloring provides instant visual context of current significant volume activity intensity and direction without switching between the price pane and indicator pane, enabling traders and investors to immediately assess volume-price positioning dynamics while analyzing price action.
Pine Script®指标
由QuantAlgo提供
Smart Signal Assistant (Kewme)Smart Signal Assistant (Kewme) – Professional Trading Suite Overview The Smart Signal Assistant (Kewme) is a comprehensive, all-in-one trading toolkit designed to bring institutional-grade discipline and visual clarity to your trading. Unlike clutter-heavy indicators, this system focuses on precision and risk management. It combines a powerful trend-following engine with an automated trade manager that visualizes your risk and reward in real-time. Key Features 1. 🛡️ Disciplined Trade Management (One Trade at a Time) Stop over-trading with the built-in "Focus Mode." No Signal Spam: The system will never generate a new signal while a trade is currently running. Active Management: A new signal is only generated after the current trade has either hit the Take Profit (TP) or the Stop Loss (SL). This enforces strict trading discipline. 2. 📦 Dynamic Risk/Reward Boxes Visualizing your trade has never been easier. Instant Zones: Upon a signal, the script automatically draws a Green Profit Zone and a Red Loss Zone directly on the chart. ATR-Based Precision: Stop Loss levels are calculated dynamically using Average True Range (ATR), ensuring your stops breathe with market volatility. Auto-Cutoff: The boxes automatically stop drawing the moment price hits your TP or SL, keeping your chart clean and historical performance visible. 3. 🎯 Clear Exit Labels No more guessing. The script clearly marks the exact candle where your trade closed: TP Hit 🎯: Appears when your target is reached. SL Hit ❌: Appears if the market goes against you. 4. 🚀 Smart Trend Engine & Filters Hybrid Modes: Choose between "Swing" (for reliable, long-term trends) or "Scalping" (for quick, short-term moves). Trend-Range Classifier (TRC): An intelligent filter system that monitors ADX and market volatility. It automatically blocks signals during choppy, sideways markets to protect your capital. 5. 📊 Live Status Dashboard A sleek, on-chart dashboard provides real-time data at a glance: Trade Status: Shows if a trade is "RUNNING" or "SEARCHING." Market Bias: Bullish or Bearish. Trend Strength: Indicates if the market is Strong or Sideways. How to Use Select Mode: Choose 'Swing' for higher timeframes or 'Scalping' for lower timeframes in settings. Adjust Risk: Set your preferred Risk/Reward Ratio (e.g., 1:2) and SL Multiplier. Follow the Boxes: Enter when the box appears, and exit exactly when the "TP Hit" or "SL Hit" label pops up. Disclaimer: This tool is for educational and assistance purposes only. Always use proper risk management.
Pine Script®指标
由arup19901提供
1
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment ## 1. Introduction The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016). The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms. ## 2. Theoretical Framework ### 2.1 Market Efficiency and Information Integration The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009). ### 2.2 Multi-Factor Asset Pricing Theory Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986). ## 3. Methodology ### 3.1 Data Sources and Quality Framework The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds: Supply Indicators: - US Oil Production (ECONOMICS:USCOP) - US Oil Rigs Count (ECONOMICS:USCOR) - API Crude Runs (ECONOMICS:USACR) Inventory Indicators: - US Crude Stock Changes (ECONOMICS:USCOSC) - Cushing Stocks (ECONOMICS:USCCOS) - API Crude Stocks (ECONOMICS:USCSC) - API Gasoline Stocks (ECONOMICS:USGS) - API Distillate Stocks (ECONOMICS:USDS) Demand Indicators: - Refinery Crude Runs (ECONOMICS:USRCR) - Gasoline Production (ECONOMICS:USGPRO) - Distillate Production (ECONOMICS:USDFP) - Industrial Production Index (FRED:INDPRO) Trade Indicators: - US Crude Imports (ECONOMICS:USCOI) - US Oil Exports (ECONOMICS:USOE) - API Crude Imports (ECONOMICS:USCI) - Dollar Index (TVC:DXY) Sentiment Indicators: - Oil Volatility Index (CBOE:OVX) ### 3.2 Data Quality Monitoring System Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring: Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators Where validity is determined by: - Non-null data availability - Positive value validation - Temporal consistency checks ### 3.3 Statistical Normalization Framework #### 3.3.1 Z-Score Normalization The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability: Z_i,t = (X_i,t - μ_i) / σ_i Where: - X_i,t = Raw value of indicator i at time t - μ_i = Sample mean of indicator i - σ_i = Sample standard deviation of indicator i Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977). #### 3.3.2 Percentile Rank Transformation For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999): Percentile_Rank = (Number of values < current_value) / Total_observations × 100 ### 3.4 Exponential Smoothing Framework Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter: S_t = α × X_t + (1-α) × S_{t-1} Where α = 2/(N+1) and N represents the smoothing period. ### 3.5 Dynamic Threshold Optimization The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992): Dynamic_Threshold = μ ± (k × σ) Where k is the threshold multiplier adjusted for market volatility regime. ### 3.6 Composite Score Calculation The fundamental score integrates component scores through weighted averaging: Fundamental_Score = Σ(w_i × Score_i × Quality_i) Where: - w_i = Normalized component weight - Score_i = Component fundamental score - Quality_i = Data quality adjustment factor ## 4. Implementation Architecture ### 4.1 Adaptive Parameter Framework The model incorporates regime-specific adjustments based on market volatility: Volatility_Regime = σ_price / μ_price × 100 High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors. ### 4.2 Data Synchronization Protocol Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators. ### 4.3 Quality-Adjusted Scoring Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal: Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor) This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise. ## 5. Usage Guidelines and Best Practices ### 5.1 Configuration Recommendations For Short-term Analysis (1-4 weeks): - Lookback Period: 26 weeks - Smoothing Length: 3-5 periods - Confidence Period: 13 weeks - Increase inventory and sentiment weights For Medium-term Analysis (1-3 months): - Lookback Period: 52 weeks - Smoothing Length: 5-8 periods - Confidence Period: 26 weeks - Balanced component weights For Long-term Analysis (3+ months): - Lookback Period: 104 weeks - Smoothing Length: 8-12 periods - Confidence Period: 52 weeks - Increase supply and demand weights ### 5.2 Signal Interpretation Framework Bullish Signals (Score > 70): - Fundamental conditions favor price appreciation - Consider long positions or reduced short exposure - Monitor for trend confirmation across multiple timeframes Bearish Signals (Score < 30): - Fundamental conditions suggest price weakness - Consider short positions or reduced long exposure - Evaluate downside protection strategies Neutral Range (30-70): - Mixed fundamental environment - Favor range-bound or volatility strategies - Wait for clearer directional signals ### 5.3 Risk Management Considerations 1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution. 2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure. 3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness. 4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes. ### 5.4 Alert System Optimization Configure alerts conservatively to avoid false signals: - Set alert threshold at 75+ for high-confidence signals - Enable data quality warnings to maintain system integrity - Use trend reversal alerts for early regime change detection ## 6. Model Validation and Performance Metrics ### 6.1 Statistical Validation The model's statistical robustness is ensured through: - Out-of-sample testing protocols - Rolling window validation - Bootstrap confidence intervals - Regime-specific performance analysis ### 6.2 Economic Validation Fundamental accuracy is validated against: - Energy Information Administration (EIA) official reports - International Energy Agency (IEA) market assessments - Commercial inventory data verification ## 7. Limitations and Considerations ### 7.1 Model Limitations 1. Data Dependency: Model performance is contingent on data availability and quality from external sources. 2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability. 3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation. 4. Regime Shifts: Structural market changes may require model recalibration. ### 7.2 Market Environment Considerations The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals. ## References Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160. Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill. Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall. Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403. Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons. Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417. Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206. Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069. Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons. Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360. Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58. Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
Pine Script®指标
由EdgeTools提供
Divergences RefurbishedJust as "a butterfly can flap its wings over a flower in China and cause a hurricane in the Caribbean" (Edward Lorenz), small divergences in markets can signal big trading opportunities. █Introduction This is a script forked from LonesomeTheBlue's Divergence for Many Indicators v4. It is a script that checks for divergence between price and many indicators. In this version, I added more indicators and also added 40 symbols to check for divergences. More info on the original script can be found here: █ Improvements The following improvements have been implemented over v4: 1. Added parameters to customize indicators. 2. Added new indicators: - Stoch RSI - Volume Oscillator - PVT (Price Volume Trend) - Ultimate Oscillator - Fisher Transform - Z-Score/T-Score 3. Now there is the possibility of using 2 external indicators. 4. New option to show tooltips inside labels. This allows you to save space on the screen if you choose the option to only show the number of divergences or just the abbreviations. 5. New option to show additional text next to the indicator name. This allows for grouping of indicators and symbols and better visualization, whether through emojis, for example. 6. Added 40 customizable symbols to check for divergences. 7. Option "show only the first letter" of the indicator replaced by: "show the abbreviation of the indicator". Reason: the indicator abbreviation is more informative and easier to read. 8. Script converted to PineScript version 5. █ CONCEPTS Below I present a brief description of the available indicators. 1. Moving Average Convergence/Divergence (MACD): Shows the difference between short-term and long-term exponential moving averages. 2. MACD Histogram: Shows the difference between MACD and its signal line. 3. Relative Strength Index (RSI): Measures the relative strength of recent price gains to recent price losses of an asset. 4. Stochastic Oscillator (Stoch): Compares the current price of an asset to its price range over a specified time period. 5. Stoch RSI: Stochastic of RSI. 6. Commodity Channel Index (CCI): Measures the relationship between an asset's current price and its moving average. 7. Momentum: Shows the difference between the current price and the price a few periods ago. Shows the difference between the current price and the price of a certain period in the past. 8. Chaikin Money Flow (CMF): A variation of A/D that takes into account the daily price variation and weighs trading volume accordingly. Accumulation/Distribution (A/D) identifies buying and selling pressure by tracking the flow of money into and out of an asset based on volume patterns. 9. On-Balance Volume (OBV): Identify divergences between trading volume and an asset's price. Sum of trading volume when the price rises and subtracts volume when the price falls. 10. Money Flow Index (MFI): Measures volume pressure in a range of 0 to 100. Calculates the ratio of volume when the price goes up and when the price goes down. 11. Volume Oscillator (VO): Identify divergences between trading volume and an asset's price. Ratio of change of volume, from a fast period in relation to a long period. 12. Price-Volume Trend (PVT): Identify the strength of an asset's price trend based on its trading volume. Cumulative change in price with volume factor. The PVT calculation is similar to the OBV calculation, but it takes into account the percentage price change multiplied by the current volume, plus the previous PVT value. 13. Ultimate Oscillator (UO): Combines three different time periods to help identify possible reversal points. 14. Fisher Transform (FT): Normalize prices into a Gaussian normal distribution. 15. Z-Score/T-Score: Shows the difference between the current price and the price a few periods ago. I is a statistical measurement that indicates how many standard deviations a data point is from the mean of a data set. When to use t-score instead of z-score? When the sample size is small (length < 30). Here, the use of z-score or t-score is chosen automatically based on the length parameter. █ What to look for The operation is simple. The script checks for divergences between the price and the selected indicators. Now with the possibility of using multiple symbols, it is possible to check divergences between different assets. A well-described view on divergences can be found in this cheat sheet: ◈ Examples with SPY ETF versus indicators: 1. Regular bullish divergence with external indicator: 1. Regular bearish divergence with Fisher Transform: 1. Positive hidden divergence with Momentum indicator: 1. Negative hidden divergence with RSI: ◈ Examples with SPY ETF versus other symbols: 1. Regular bearish divergence with European Stoch Market: 2. Regular bearish divergence with DXY inverted: 3. Regular bullish divergence with Taiwan Dollar: 4. Regular bearish divergence with US10Y (10-Year US Treasury Note): 5. Regular bullish divergence with QQQ ETF (Nasdaq 100): 6. Regular bullish divergence with ARKK ETF (ARK Innovation): 7.Positive hidden divergence with RSP ETF (S&P 500 Equal Weight): 8. Negative hidden divergence with EWZ ETF (Brazil): ◈ Examples with BTCUSD versus other symbols: 1. Regular bearish divergence with BTCUSDLONGS from Bitfinex: 2. Regular bearish divergence with BLOK ETF (Amplify Transformational Data Sharing): 3. Negative hidden divergence with NATGAS (Natural Gas): 4. Positive hidden divergence with TOTALDEFI (Total DeFi Market Cap): █ Conclusion The symbols available to check divergences were chosen in such a way as to cover the main markets, in the most generic way possible. You can adjust them according to your needs. A trader in the American market, for example, could add more ETFs, American stocks, and sectoral indices, such as the XLF (Financial Select Sector SPDR Fund), the XLK (Technology Select Sector SPDR), etc. On the other hand, a cryptocurrency trader could add more currency pairs and sector indicators, such as BTCUSDSHORTS (Bitfinex), USDT.D (Tether Dominance), etc. If the chart becomes too cluttered, you can use the option to show only the number of divergences or only the indicator abbreviations. Or even disable certain indicators and symbols, if they are not of interest to you. I hope this script is useful. Don't forget to support LonesomeTheBlue's work too.
Pine Script®指标
由andre_007提供
58