KingEMA8-21-55-89I used the moving average with the habit of 21-55, so added two moving average, one is the short line 8EMA, the other is the medium and long line 89ema
Explain the application of moving averages through the disk surface:
When the price runs above 89, it only looks for the buy signal.
When the price runs below 89, it only looks for sell signals.
The first step up through the 89 moving average after the first confirmation can buy homeoply,
The first pull down after crossing the 89 moving average for the first time confirms that it can be sold in line with the trend.
Price horizontal finishing, moving average frequently across the field observation.
The yellow area in the interval from 8 to 21 is the homeopathic warehouse addition signal.
When the price is above the 89 moving average, the k-line closes below the 21-day moving average as a callback signal
Prices below the 89 ema close above the 21 - day ema as a rebound signal
After the correction and rebound signals come out, we should make half of the profit and the other half of the stop loss in the break-even place.
Moving average is very suitable for the trend of strong varieties, is not suitable for volatile market.
Only at the end of the shock market moving average upward or downward divergent when it is possible to be used.
1. Repeatedly entangle the mean line of horizontal disk stage and observe it from the field
2. Sell the three EMA moving averages when they can't exceed 89EMA with downward crossing
3, many times can not break the new low when prices go sideways profit
4. Buy when the price reaches 89EMA after the convergence of triangle 3 is broken
5, the Angle of price rise slowed and closed below the 21 moving average when profit
6. Left field observation during transverse oscillation.
Sit tight while news or data cause prices to fall quickly
8. Buy when the price triangle breaks through the 89 moving average upward
9, the price does not rise to slow down when the horizontal closed below the 21 moving average when profit
10, price horizontal shock finishing at the same time the average line also transverse finishing field observation
11, the price of the triangle after finishing through the 89 moving average to buy.At this point all the averages have turned up
12, the second time can not break through the new high when the negative line can profit
13, the price of the first time in the same period of time through 89 after the first step back can be re-bought.
中文翻译
价格在89上面运行时时只找买入信号、
价格在89下面运行时只寻找卖出信号、
第一次向上穿过89均线后的第一次回踩确认可以顺势买入、
第一次向下穿过89均线后的第一次回抽确认可以顺势卖出、
价格横盘整理，均线频繁穿越时离场观察。
8-21区间里面黄色区域为顺势加仓信号，
价格在89均线上面时K线收盘在21天均线下面时为回调信号
价格在89均线下面时K线收盘在21天均线上面时为反弹信号
在回调和反弹信号出来之后我们应该获利一半的头寸，另外一半止损放到盈亏平衡的地方。
均线非常适合趋势性很强的品种，并不适合震荡行情。
只有在震荡行情结束时均线向上或向下发散时才有被运用的可能。
1、横盘阶段均线反复纠缠，离场观察
2、三条EMA均线向下交叉回抽无法超越89EMA时卖出
3、多次不能破新低时价格走横时获利
4、价格在3处三角形收敛被突破后站上了89EMA时买入
5、价格上涨角度变缓并收盘在21均线下面时获利
6、横盘震荡时离场观察。
7、见死不救新闻或数据导致价格快速下跌时观望
8、价格三角形向上突破时穿过89均线时买入
9、价格不升减速走横时收盘于21均线下面时获利
10、价格横盘震荡整理同时均线也横向整理时离场观察
11、价格突破三角形整理后重新穿过89均线时买入。此时所有均线已经向上翘头
12、第二次不能突破新高时收阴线可以获利
13、价格在同一个时间周期内第一次穿过89以后的第一次回踩可以重新买入
14、21-55作为牛熊的分水岭。在21-55区域之下只考虑做空，21-55之上只考虑做多。如果21-55走横则以位置决定高位倾向空低位倾向多。
15、K线会因为指标的设置自动变成两个颜色块，绿色看涨，红色看跌。做趋势看K线颜色。牛市的红色可以当成入场K熊市绿色当成入场K
Cari dalam skrip untuk "美国11月非农数据"
Bernoulli Process - Binary Entropy FunctionThis indicator is the Bernoulli Process or Wikipedia - Binary Entropy Function . Within Information Theory, Entropy is the measure of available information, here we use a binary variable 0 or 1 (P) and (1-P) (Bernoulli Function/Distribution), and combined with the Shannon Entropy measurement. As you can see below, it produces some wonderful charts and signals, using price, volume, or both summed together. The chart below shows you a couple of options and some critical details on the indicator. The best part about this is the simplicity, all of this information in a couple of lines of code.
Using the indicator:
The longer the Entropy measurement the more information you are capturing, so the analogy is, the shorter the signal, the less information you have available to utilize. You'll run into your Nyquist frequencies below a length of 5. I've found values between 9 and 22 work well to gather enough measurements. You also have an averaging summation that measures the weight or importance of the information over the summation period. This is also used for highlighting when you have an information signal above the 5% level (2 sigma) and then can be adjusted using the Percent Rank Variable. Finally, you can plot the individual signals (Price or Volume) to get another set of measurements to utilize. As can be seen in the chart below, the volume moves before price (but hopefully you already knew that)
At its core, this is taking the Binary Entropy measurement (using a Bernoulli distribution) for price and volume. I've subtracted the volume from the price so that you can use it like a MACD, also for shorter time frames (7, 9, 11) you can get divergences on the histogram. These divergences are primarily due to the weekly nature of the markets (5 days, 10 days is two weeks,...so 9 is measuring the last day of the past two weeks...so 11 is measuring the current day and the past two weeks).
Here are a couple of other examples, assuming you just love BTC, Stocks, or FOREX. I fashioned up a strategy to show the potential of the indicator.
BTC-Strategy
Stock-Strategy (#loveyouNFLX)
FOREX - (for everyone hopped up on 40X leverage)
Divergence Histogram for Many IndicatorHello Traders,
This script analyses divergences for 11 predefined indicators and then draws column on the graph. Red columns for negatif divergence (means prices may go down or trend reversal), Lime columns for positive divergences (means prices may go up or trend reversal)
The script uses Pivot Points and on each bar it checks divergence between last Pivot Point and current High/Low and if it finds any divergence then immediately draws column. There is no Latency/Lag.
There are predefined 11 indicators in the script, which are RSI , MACD , MACD Histogram, Stochastic , CCI , Momentum, OBV, Diosc, VWMACD, CMF and MFI.
Smaller Pivot Point Period check smaller areas and if you use smaller numbers it would be more sensitive and may give alerts very often. So you should set it accordingly.
There is "Check Cut-Through in indicators" option, I recomment you to enable it. it checks that there is cut-through in indicators or not, if no cut-through then it's shown as valid divergence.
You should see following one as well if you haven't yet:
Enjoy!
candlestick patternsCleaning up and updating vcsWo8mh-Candlestick-Patterns-Identified-updated-3-11-15 .
As I learn more candlestick patterns I'll add them in.
Please post requests and any potential implementations I could port to pine script.
I'm applying autopep8 as best I can for readability.
MAC-Z & MACD Leader signal [ChuckBanger]This is a combination of my MACD Leader script and MAC-Z with option to add Laguerre filter. The advantage of the MAC-Z over MACD is that it is a more accurate and “assumption-free” indicator that can more accurately describe how a market actually perform. But you can use this as a regular MACD indicator.
Crossovers signals
The MAC-Z line and signal line can be utilized in the same way as a stochastic oscillator, with the crossover between the two lines providing buy and sell signals. As with most crossover strategies, a buy signal comes when the shorter-term, more reactive line – in this case the MAC-Z line (blue line) crosses above the slower signal line (orange line). For example, when the MAC-Z line crosses below the signal line it provides a bearish sell signal.
Zero line crossing
The zero cross strategy is based on either of the lines crossing the zero line. If the MAC-Z crosses the zero line from below, it is a signal for a possible new uptrend, while the MAC-Z crossing from above is a signal that a new downtrend may be starting. This is special powerful if the lines has a fast up or down movement but the price action doesn't reflect that movement.
Divergences
Bearish and bullish divergences is my favorite signals. When price action and oscillators follow the same path it is called Convergences, when they don’t, it’s called a Divergence. Don't confuse the two because they have not the same meaning. But be aware that for example during consolidation or low liquidity, some small divergences between price and indicators might form, but that doesn't mean we should consider them as real divergences.
There is many different types of divergences. It is easier to show a picture then explaining it so I recommend you to check out the link below. Especially the top image. It sums this up very well
medium.com
MACD Leader
The MACD leader is only showing the crossing of MACD as a vertical line
Green vertical line = MACD Leader Bullish Cross
Red vertical line = MACD Leader Bearish Cross
MACD Leader:
MAC-Z:
More Information
cssanalytics.wordpress.com
en.wikipedia.org
drive.google.com
Edward EMA 8-21-89-144Explain the application of moving averages through the disk surface:
When the price runs above 89, it only looks for the buy signal.
When the price runs below 89, it only looks for sell signals.
The first step up through the 89 moving average after the first confirmation can buy homeoply,
The first pull down after crossing the 89 moving average for the first time confirms that it can be sold in line with the trend.
Price horizontal finishing, moving average frequently across the field observation.
The yellow area in the interval from 8 to 21 is the homeopathic warehouse addition signal.
When the price is above the 89 moving average, the k-line closes below the 21-day moving average as a callback signal
Prices below the 89 ema close above the 21 - day ema as a rebound signal
After the correction and rebound signals come out, we should make half of the profit and the other half of the stop loss in the break-even place.
Moving average is very suitable for the trend of strong varieties, is not suitable for volatile market.
Only at the end of the shock market moving average upward or downward divergent when it is possible to be used.
1. Repeatedly entangle the mean line of horizontal disk stage and observe it from the field
2. Sell the three EMA moving averages when they can't exceed 89EMA with downward crossing
3, many times can not break the new low when prices go sideways profit
4. Buy when the price reaches 89EMA after the convergence of triangle 3 is broken
5, the Angle of price rise slowed and closed below the 21 moving average when profit
6. Left field observation during transverse oscillation.
Sit tight while news or data cause prices to fall quickly
8. Buy when the price triangle breaks through the 89 moving average upward
9, the price does not rise to slow down when the horizontal closed below the 21 moving average when profit
10, price horizontal shock finishing at the same time the average line also transverse finishing field observation
11, the price of the triangle after finishing through the 89 moving average to buy.At this point all the averages have turned up
12, the second time can not break through the new high when the negative line can profit
13, the price of the first time in the same period of time through 89 after the first step back can be re-bought.
通过盘面讲解均线运用：
价格在89上面运行时时只找买入信号、
价格在89下面运行时只寻找卖出信号、
第一次向上穿过89均线后的第一次回踩确认可以顺势买入、
第一次向下穿过89均线后的第一次回抽确认可以顺势卖出、
价格横盘整理，均线频繁穿越时离场观察。
8-21区间里面黄色区域为顺势加仓信号，
价格在89均线上面时K线收盘在21天均线下面时为回调信号
价格在89均线下面时K线收盘在21天均线上面时为反弹信号
在回调和反弹信号出来之后我们应该获利一半的头寸，另外一半止损放到盈亏平衡的地方。
均线非常适合趋势性很强的品种，并不适合震荡行情。
只有在震荡行情结束时均线向上或向下发散时才有被运用的可能。
1、横盘阶段均线反复纠缠，离场观察
2、三条EMA均线向下交叉回抽无法超越89EMA时卖出
3、多次不能破新低时价格走横时获利
4、价格在3处三角形收敛被突破后站上了89EMA时买入
5、价格上涨角度变缓并收盘在21均线下面时获利
6、横盘震荡时离场观察。
7、见死不救新闻或数据导致价格快速下跌时观望
8、价格三角形向上突破时穿过89均线时买入
9、价格不升减速走横时收盘于21均线下面时获利
10、价格横盘震荡整理同时均线也横向整理时离场观察
11、价格突破三角形整理后重新穿过89均线时买入。此时所有均线已经向上翘头
12、第二次不能突破新高时收阴线可以获利
13、价格在同一个时间周期内第一次穿过89以后的第一次回踩可以重新买入
14、89-144作为牛熊的分水岭。在89-144区域之下只考虑做空，89-144只考虑做多。如果89-144走横则以位置决定高位倾向空低位倾向多。
15、K线会因为指标的设置自动变成两个颜色块，绿色看涨，红色看跌。做趋势看K线颜色。牛市的红色可以当成入场K熊市绿色当成入场K
Moving Averages & Bollinger Bands with ForecastsMoving Averages & Bollinger Bands with Forecasts
11 Moving Averages
SMA, EMA, WMA
Highly Customizable
Linear Regression Forecast
Bollonger Bands
Personal Setup: Add indicator twice
1st indicator = SMA using #4, 7, 10, 11 (20, 50, 100, 200 SMAs) with bollonger bands on 20.
2nd indicator = EMA using #1, 2, 3, 5, 6, 8, 9 (5, 8, 13, 21 ,34, 55, 89 EMAs).
This allows easy toggling between SMAs/Bolls and Fib EMAs
Thank you to yatrader2 for the forecast code
Moving Averages & Bollinger Bands with ForecastsMoving Averages & Bollinger Bands with Forecasts
11 Moving Averages
SMA, EMA, WMA
Highly Customizable
Linear Regression Forecast
Bollonger Bands
Personal Setup: Add indicator twice
1st indicator = SMA using #4, 7, 10, 11 (20, 50, 100, 200 SMAs) with bollonger bands on 20.
2nd indicator = EMA using #1, 2, 3, 5, 6, 8, 9 (5, 8, 13, 21 ,34, 55, 89 EMAs).
This allows easy toggling between SMAs/Bolls and Fib EMAs
Thank you to yatrader2 for the forecast code
Moving Averages & Bollinger Bands with ForecastsMoving Averages & Bollinger Bands with Forecasts
11 Moving Averages
SMA, EMA, WMA
Highly Customizable
Linear Regression Forecast
Bollonger Bands
Personal Setup: Add indicator twice
1st indicator = SMA using #4, 7, 10, 11 (20, 50, 100, 200 SMAs) with bollonger bands on 20.
2nd indicator = EMA using #1, 2, 3, 5, 6, 8, 9 (5, 8, 13, 21 ,34, 55, 89 EMAs).
This allows easy toggling between SMAs/Bolls and Fib EMAs
Thank you to yatrader2 for the forecast code
Moving Averages & Bollinger Bands with ForecastsMoving Averages & Bollinger Bands with Forecasts
11 Moving Averages
SMA, EMA, WMA
Highly Customizable
Linear Regression Forecast
Bollonger Bands
Personal Setup: Add indicator twice
1st indicator = SMA using #4, 7, 10, 11 (20, 50, 100, 200 SMAs) with bollonger bands on 20.
2nd indicator = EMA using #1, 2, 3, 5, 6, 8, 9 (5, 8, 13, 21 ,34, 55, 89 EMAs).
This allows easy toggling between SMAs/Bolls and Fib EMAs
Thank you to yatrader2 for the forecast code
[astropark] MACD, RSI+, AO, DMI, ADX, OBV, ADI//******************************************************************************
// Copyright by astropark v4.1.0
// MACD, RSI+, Awesome Oscillator, DMI, ADX, OBV, ADI
// 24/10/2018 Added RSI with Center line to have clear glue of current trend
// 10/12/2018 Added MACD
// 13/12/2018 Added multiplier for MACD in order to make it clearly visible over RSI graph
// 11/01/2019 Added Awesome Ascillator (AO)
// 11/01/2019 Added Directional Movement Index (DMI) with ADX
// 14/01/2019 Added On Balance Volume (OBV)
// 14/01/2019 Added Accelerator Decelerator Indicator (ADI)
//******************************************************************************
[astropark] MACD, RSI+, Awesome Oscillator, DMI, ADX, OBV//******************************************************************************
// Copyright by astropark v4.0.0
// MACD, RSI+, Awesome Oscillator, DMI, ADX, OBV
// 24/10/2018 Added RSI with Center line to have clear glue of current trend
// 10/12/2018 Added MACD
// 13/12/2018 Added multiplier for MACD in order to make it clearly visible over RSI graph
// 11/01/2019 Added Awesome Oscillator (AO)
// 11/01/2019 Added Directional Movement Index (DMI) with ADX
// 14/01/2019 Added On Balance Volume (OBV)
//******************************************************************************
[astropark] MACD, RSI+, Awesome Oscillator, DMI with ADX//******************************************************************************
// Copyright by astropark v3.1.0
// MACD, RSI+, Awesome Oscillator, DMI, ADX
// 24/10/2018 Added RSI with Center line to have clear glue of current trend
// 10/12/2018 Added MACD
// 13/12/2018 Added multiplier for MACD in order to make it clearly visible over RSI graph
// 11/01/2019 Added Awesome Ascillator (AO)
// 11/01/2019 Added Directional Movement Index (DMI) with ADX
//******************************************************************************
King 4EMA TraderKing 4EMA trader 8/21/89EMA+(233)V3.3
Explain the application of moving averages through the disk surface:
When the price runs above 89, it only looks for the buy signal.
When the price runs below 89, it only looks for sell signals.
The first step up through the 89 moving average after the first confirmation can buy homeoply,
The first pull down after crossing the 89 moving average for the first time confirms that it can be sold in line with the trend.
Price horizontal finishing, moving average frequently across the field observation.
The yellow area in the interval from 8 to 21 is the homeopathic warehouse addition signal.
When the price is above the 89 moving average, the k-line closes below the 21-day moving average as a callback signal
Prices below the 89 ema close above the 21 - day ema as a rebound signal
After the correction and rebound signals come out, we should make half of the profit and the other half of the stop loss in the break-even place.
Moving average is very suitable for the trend of strong varieties, is not suitable for volatile market.
Only at the end of the shock market moving average upward or downward divergent when it is possible to be used.
1. Repeatedly entangle the mean line of horizontal disk stage and observe it from the field
2. Sell the three EMA moving averages when they can't exceed 89EMA with downward crossing
3, many times can not break the new low when prices go sideways profit
4. Buy when the price reaches 89EMA after the convergence of triangle 3 is broken
5, the Angle of price rise slowed and closed below the 21 moving average when profit
6. Left field observation during transverse oscillation.
Sit tight while news or data cause prices to fall quickly
8. Buy when the price triangle breaks through the 89 moving average upward
9, the price does not rise to slow down when the horizontal closed below the 21 moving average when profit
10, price horizontal shock finishing at the same time the average line also transverse finishing field observation
11, the price of the triangle after finishing through the 89 moving average to buy.At this point all the averages have turned up
12, the second time can not break through the new high when the negative line can profit
13, the price of the first time in the same period of time through 89 after the first step back can be re-bought.
通过盘面讲解均线运用：
价格在89上面运行时时只找买入信号、
价格在89下面运行时只寻找卖出信号、
第一次向上穿过89均线后的第一次回踩确认可以顺势买入、
第一次向下穿过89均线后的第一次回抽确认可以顺势卖出、
价格横盘整理，均线频繁穿越时离场观察。
8-21区间里面黄色区域为顺势加仓信号，
价格在89均线上面时K线收盘在21天均线下面时为回调信号
价格在89均线下面时K线收盘在21天均线上面时为反弹信号
在回调和反弹信号出来之后我们应该获利一半的头寸，另外一半止损放到盈亏平衡的地方。
均线非常适合趋势性很强的品种，并不适合震荡行情。
只有在震荡行情结束时均线向上或向下发散时才有被运用的可能。
1、横盘阶段均线反复纠缠，离场观察
2、三条EMA均线向下交叉回抽无法超越89EMA时卖出
3、多次不能破新低时价格走横时获利
4、价格在3处三角形收敛被突破后站上了89EMA时买入
5、价格上涨角度变缓并收盘在21均线下面时获利
6、横盘震荡时离场观察。
7、见死不救新闻或数据导致价格快速下跌时观望
8、价格三角形向上突破时穿过89均线时买入
9、价格不升减速走横时收盘于21均线下面时获利
10、价格横盘震荡整理同时均线也横向整理时离场观察
11、价格突破三角形整理后重新穿过89均线时买入。此时所有均线已经向上翘头
12、第二次不能突破新高时收阴线可以获利
13、价格在同一个时间周期内第一次穿过89以后的第一次回踩可以重新买入。
Bitfinex Longs/Shorts Multi-Coin [acatwithcharts]This script plots the longs/shorts ratio derived from Bitfinex for BTCUSDLONGS, BTCUSDSHORTS, and similar for 11 top cryptocurrencies chosen selected based on marketcap, trading volume on Bitfinex, and the maximum number of times that TradingView would let me call the "security" function in one script. Included coins:
BTC, ETH, LTC, BCH, XRP, EOS, IOT (IOTA), ETC, ZEC, NEO, XMR
In addition to just plotting the ratios for the individual coins, this script also calculates for a customizable selection of the 11 coins both the average ratio and a weighted average weighted by (USD price of coin * sum of long and short positions).
I wrote it both to use both for a big picture overview of leveraged positions across major coins and to use as a Swiss army knife of longs/shorts ratio indicators for individual coins, most of which do not currently have individual scripts published.
I'm an amateur and you definitely shouldn't take anything I say or use any of my scripts as financial advice. I'd appreciate any feedback.
Stochastic Momentum IndexStochastic Momentum Index indicator script. This indicator was originally developed by William Blau (Stocks & Commodities V. 11:1 (11-18)).
NCL Noise FilterOne of our Favorite Indicators - the NeoChartLabs Noise Filter.
FILTER OUT THE NOISE and focus on the moves that matter, toggle the settings to match your preference.
Or switch the Duration Setting to Institutional on a high timeframe (1W+) to locate great spot buying opportunities near cycle tops and bottoms.
Volume Filter: The volume filter automatically turns OFF when you switch to Major Macro Cycle or Institutional Baseline, as those high-timeframe structural breaks are often valid even on lower relative volume.
You can change the volume requirement by checking the volume of the current breakout bar against its Relative Volume (RVOL) - A setting of 0 turns this OFF.
A common professional standard is to require the breakout volume to be at least 1.5x to 2x higher than the 20-period average volume.
*we recommend using a higher volume setting on low timeframes under the 4HR to reduce false signals.
MTF Filter:
*we recommend to set at least 1 timeframe above your trade (i.e if you enter on the 2hour set to the 4 hour)
It prevents entering trades that are essentially minor pullbacks in a much larger opposing trend.
By integrating a higher timeframe EMA (e.g., a 200-period EMA from a 4x higher timeframe), you can filter out counter-trend trades that have a higher probability of failing.
ATR Filter:
Filters "Fake-Outs": It forces the price to not just "touch" the trendline, but to break it with enough force to clear the current average volatility.
Adaptive: Unlike a fixed pip/dollar amount, the ATR adjusts to the asset. On Bitcoin, the threshold might be $500; on a penny stock, it might be $0.05.
Bullish Cross: The price must close above the support trendline + (0.5 * ATR).
Bearish Cross: The price must close below the resistance trendline - (0.5 * ATR).
MACD Filter:
Bullish Crosses require the MACD Histogram to be increasing (showing positive momentum acceleration).
Bearish Crosses require the MACD Histogram to be decreasing (showing negative momentum acceleration).
RSI Filter:
Bullish Breakout (Cross of the lower/support trendline): You would want the RSI to be rising or above 50, showing that buyers are in control.
Bearish Breakdown (Cross of the upper/resistance trendline): You would want the RSI to be falling or below 50, showing sellers are in control.
Market Structure Shifts (CHoCH) - identifying Trends with bullish/bearish dashed horizontal lines for each CHoCH providing a cleaner visualization of the support or resistance level that price has just violated.
Duration Table for 1Week Charts
Trading Style Fractal Length (p) Pattern Span Confirmation Delay
Standard Swing 2 5 Weeks 2 Weeks
Intermediate Trend 5 11 Weeks 5 Weeks
Major Macro Cycle 10–20 21–41 Weeks 10–20 Weeks
Institutional Baseline 44 ~2 Years ~10 Months
ORB Fusion🎯 CORE INNOVATION: INSTITUTIONAL ORB FRAMEWORK WITH FAILED BREAKOUT INTELLIGENCE
ORB Fusion represents a complete institutional-grade Opening Range Breakout system combining classic Market Profile concepts (Initial Balance, day type classification) with modern algorithmic breakout detection, failed breakout reversal logic, and comprehensive statistical tracking. Rather than simply drawing lines at opening range extremes, this system implements the full trading methodology used by professional floor traders and market makers—including the critical concept that failed breakouts are often higher-probability setups than successful breakouts .
The Opening Range Hypothesis:
The first 30-60 minutes of trading establishes the day's value area —the price range where the majority of participants agree on fair value. This range is formed during peak information flow (overnight news digestion, gap reactions, early institutional positioning). Breakouts from this range signal directional conviction; failures to hold breakouts signal trapped participants and create exploitable reversals.
Why Opening Range Matters:
1. Information Aggregation : Opening range reflects overnight news, pre-market sentiment, and early institutional orders. It's the market's initial "consensus" on value.
2. Liquidity Concentration : Stop losses cluster just outside opening range. Breakouts trigger these stops, creating momentum. Failed breakouts trap traders, forcing reversals.
3. Statistical Persistence : Markets exhibit range expansion tendency —when price accepts above/below opening range with volume, it often extends 1.0-2.0x the opening range size before mean reversion.
4. Institutional Behavior : Large players (market makers, institutions) use opening range as reference for the day's trading plan. They fade extremes in rotation days and follow breakouts in trend days.
Historical Context:
Opening Range Breakout methodology originated in commodity futures pits (1970s-80s) where floor traders noticed consistent patterns: the first 30-60 minutes established a "fair value zone," and directional moves occurred when this zone was violated with conviction. J. Peter Steidlmayer formalized this observation in Market Profile theory, introducing the "Initial Balance" concept—the first hour (two 30-minute periods) defining market structure.
📊 OPENING RANGE CONSTRUCTION
Four ORB Timeframe Options:
1. 5-Minute ORB (0930-0935 ET):
Captures immediate market direction during "opening drive"—the explosive first few minutes when overnight orders hit the tape.
Use Case:
• Scalping strategies
• High-frequency breakout trading
• Extremely liquid instruments (ES, NQ, SPY)
Characteristics:
• Very tight range (often 0.2-0.5% of price)
• Early breakouts common (7 of 10 days break within first hour)
• Higher false breakout rate (50-60%)
• Requires sub-minute chart monitoring
Psychology: Captures panic buyers/sellers reacting to overnight news. Range is small because sample size is minimal—only 5 minutes of price discovery. Early breakouts often fail because they're driven by retail FOMO rather than institutional conviction.
2. 15-Minute ORB (0930-0945 ET):
Balances responsiveness with statistical validity. Captures opening drive plus initial reaction to that drive.
Use Case:
• Day trading strategies
• Balanced scalping/swing hybrid
• Most liquid instruments
Characteristics:
• Moderate range (0.4-0.8% of price typically)
• Breakout rate ~60% of days
• False breakout rate ~40-45%
• Good balance of opportunity and reliability
Psychology: Includes opening panic AND the first retest/consolidation. Sophisticated traders (institutions, algos) start expressing directional bias. This is the "Goldilocks" timeframe—not too reactive, not too slow.
3. 30-Minute ORB (0930-1000 ET):
Classic ORB timeframe. Default for most professional implementations.
Use Case:
• Standard intraday trading
• Position sizing for full-day trades
• All liquid instruments (equities, indices, futures)
Characteristics:
• Substantial range (0.6-1.2% of price)
• Breakout rate ~55% of days
• False breakout rate ~35-40%
• Statistical sweet spot for extensions
Psychology: Full opening auction + first institutional repositioning complete. By 10:00 AM ET, headlines are digested, early stops are hit, and "real" directional players reveal themselves. This is when institutional programs typically finish their opening positioning.
Statistical Advantage: 30-minute ORB shows highest correlation with daily range. When price breaks and holds outside 30m ORB, probability of reaching 1.0x extension (doubling the opening range) exceeds 60% historically.
4. 60-Minute ORB (0930-1030 ET) - Initial Balance:
Steidlmayer's "Initial Balance"—the foundation of Market Profile theory.
Use Case:
• Swing trading entries
• Day type classification
• Low-frequency institutional setups
Characteristics:
• Wide range (0.8-1.5% of price)
• Breakout rate ~45% of days
• False breakout rate ~25-30% (lowest)
• Best for trend day identification
Psychology: Full first hour captures A-period (0930-1000) and B-period (1000-1030). By 10:30 AM ET, all early positioning is complete. Market has "voted" on value. Subsequent price action confirms (trend day) or rejects (rotation day) this value assessment.
Initial Balance Theory:
IB represents the market's accepted value area . When price extends significantly beyond IB (>1.5x IB range), it signals a Trend Day —strong directional conviction. When price remains within 1.0x IB, it signals a Rotation Day —mean reversion environment. This classification completely changes trading strategy.
🔬 LTF PRECISION TECHNOLOGY
The Chart Timeframe Problem:
Traditional ORB indicators calculate range using the chart's current timeframe. This creates critical inaccuracies:
Example:
• You're on a 5-minute chart
• ORB period is 30 minutes (0930-1000 ET)
• Indicator sees only 6 bars (30min ÷ 5min/bar = 6 bars)
• If any 5-minute bar has extreme wick, entire ORB is distorted
The Problem Amplifies:
• On 15-minute chart with 30-minute ORB: Only 2 bars sampled
• On 30-minute chart with 30-minute ORB: Only 1 bar sampled
• Opening spike or single large wick defines entire range (invalid)
Solution: Lower Timeframe (LTF) Precision:
ORB Fusion uses `request.security_lower_tf()` to sample 1-minute bars regardless of chart timeframe:
```
For 30-minute ORB on 15-minute chart:
- Traditional method: Uses 2 bars (15min × 2 = 30min)
- LTF Precision: Requests thirty 1-minute bars, calculates true high/low
```
Why This Matters:
Scenario: ES futures, 15-minute chart, 30-minute ORB
• Traditional ORB: High = 5850.00, Low = 5842.00 (range = 8 points)
• LTF Precision ORB: High = 5848.50, Low = 5843.25 (range = 5.25 points)
Difference: 2.75 points distortion from single 15-minute wick hitting 5850.00 at 9:31 AM then immediately reversing. LTF precision filters this out by seeing it was a fleeting wick, not a sustained high.
Impact on Extensions:
With inflated range (8 points vs 5.25 points):
• 1.5x extension projects +12 points instead of +7.875 points
• Difference: 4.125 points (nearly $200 per ES contract)
• Breakout signals trigger late; extension targets unreachable
Implementation:
```pinescript
getLtfHighLow() =>
float ha = request.security_lower_tf(syminfo.tickerid, "1", high)
float la = request.security_lower_tf(syminfo.tickerid, "1", low)
```
Function returns arrays of 1-minute high/low values, then finds true maximum and minimum across all samples.
When LTF Precision Activates:
Only when chart timeframe exceeds ORB session window:
• 5-minute chart + 30-minute ORB: LTF used (chart TF > session bars needed)
• 1-minute chart + 30-minute ORB: LTF not needed (direct sampling sufficient)
Recommendation: Always enable LTF Precision unless you're on 1-minute charts. The computational overhead is negligible, and accuracy improvement is substantial.
⚖️ INITIAL BALANCE (IB) FRAMEWORK
Steidlmayer's Market Profile Innovation:
J. Peter Steidlmayer developed Market Profile in the 1980s for the Chicago Board of Trade. His key insight: market structure is best understood through time-at-price (value area) rather than just price-over-time (traditional charts).
Initial Balance Definition:
IB is the price range established during the first hour of trading, subdivided into:
• A-Period : First 30 minutes (0930-1000 ET for US equities)
• B-Period : Second 30 minutes (1000-1030 ET)
A-Period vs B-Period Comparison:
The relationship between A and B periods forecasts the day:
B-Period Expansion (Bullish):
• B-period high > A-period high
• B-period low ≥ A-period low
• Interpretation: Buyers stepping in after opening assessed
• Implication: Bullish continuation likely
• Strategy: Buy pullbacks to A-period high (now support)
B-Period Expansion (Bearish):
• B-period low < A-period low
• B-period high ≤ A-period high
• Interpretation: Sellers stepping in after opening assessed
• Implication: Bearish continuation likely
• Strategy: Sell rallies to A-period low (now resistance)
B-Period Contraction:
• B-period stays within A-period range
• Interpretation: Market indecisive, digesting A-period information
• Implication: Rotation day likely, stay range-bound
• Strategy: Fade extremes, sell high/buy low within IB
IB Extensions:
Professional traders use IB as a ruler to project price targets:
Extension Levels:
• 0.5x IB : Initial probe outside value (minor target)
• 1.0x IB : Full extension (major target for normal days)
• 1.5x IB : Trend day threshold (classifies as trending)
• 2.0x IB : Strong trend day (rare, ~10-15% of days)
Calculation:
```
IB Range = IB High - IB Low
Bull Extension 1.0x = IB High + (IB Range × 1.0)
Bear Extension 1.0x = IB Low - (IB Range × 1.0)
```
Example:
ES futures:
• IB High: 5850.00
• IB Low: 5842.00
• IB Range: 8.00 points
Extensions:
• 1.0x Bull Target: 5850 + 8 = 5858.00
• 1.5x Bull Target: 5850 + 12 = 5862.00
• 2.0x Bull Target: 5850 + 16 = 5866.00
If price reaches 5862.00 (1.5x), day is classified as Trend Day —strategy shifts from mean reversion to trend following.
📈 DAY TYPE CLASSIFICATION SYSTEM
Four Day Types (Market Profile Framework):
1. TREND DAY:
Definition: Price extends ≥1.5x IB range in one direction and stays there.
Characteristics:
• Opens and never returns to IB
• Persistent directional movement
• Volume increases as day progresses (conviction building)
• News-driven or strong institutional flow
Frequency: ~20-25% of trading days
Trading Strategy:
• DO: Follow the trend, trail stops, let winners run
• DON'T: Fade extremes, take early profits
• Key: Add to position on pullbacks to previous extension level
• Risk: Getting chopped in false trend (see Failed Breakout section)
Example: FOMC decision, payroll report, earnings surprise—anything creating one-sided conviction.
2. NORMAL DAY:
Definition: Price extends 0.5-1.5x IB, tests both sides, returns to IB.
Characteristics:
• Two-sided trading
• Extensions occur but don't persist
• Volume balanced throughout day
• Most common day type
Frequency: ~45-50% of trading days
Trading Strategy:
• DO: Take profits at extension levels, expect reversals
• DON'T: Hold for massive moves
• Key: Treat each extension as a profit-taking opportunity
• Risk: Holding too long when momentum shifts
Example: Typical day with no major catalysts—market balancing supply and demand.
3. ROTATION DAY:
Definition: Price stays within IB all day, rotating between high and low.
Characteristics:
• Never accepts outside IB
• Multiple tests of IB high/low
• Decreasing volume (no conviction)
• Classic range-bound action
Frequency: ~25-30% of trading days
Trading Strategy:
• DO: Fade extremes (sell IB high, buy IB low)
• DON'T: Chase breakouts
• Key: Enter at extremes with tight stops just outside IB
• Risk: Breakout finally occurs after multiple failures
Example: [/b> Pre-holiday trading, summer doldrums, consolidation after big move.
4. DEVELOPING:
Definition: Day type not yet determined (early in session).
Usage: Classification before 12:00 PM ET when IB extension pattern unclear.
ORB Fusion's Classification Algorithm:
```pinescript
if close > ibHigh:
ibExtension = (close - ibHigh) / ibRange
direction = "BULLISH"
else if close < ibLow:
ibExtension = (ibLow - close) / ibRange
direction = "BEARISH"
if ibExtension >= 1.5:
dayType = "TREND DAY"
else if ibExtension >= 0.5:
dayType = "NORMAL DAY"
else if close within IB:
dayType = "ROTATION DAY"
```
Why Classification Matters:
Same setup (bullish ORB breakout) has opposite implications:
• Trend Day : Hold for 2.0x extension, trail stops aggressively
• Normal Day : Take profits at 1.0x extension, watch for reversal
• Rotation Day : Fade the breakout immediately (likely false)
Knowing day type prevents catastrophic errors like fading a trend day or holding through rotation.
🚀 BREAKOUT DETECTION & CONFIRMATION
Three Confirmation Methods:
1. Close Beyond Level (Recommended):
Logic: Candle must close above ORB high (bull) or below ORB low (bear).
Why:
• Filters out wicks (temporary liquidity grabs)
• Ensures sustained acceptance above/below range
• Reduces false breakout rate by ~20-30%
Example:
• ORB High: 5850.00
• Bar high touches 5850.50 (wick above)
• Bar closes at 5848.00 (inside range)
• Result: NO breakout signal
vs.
• Bar high touches 5850.50
• Bar closes at 5851.00 (outside range)
• Result: BREAKOUT signal confirmed
Trade-off: Slightly delayed entry (wait for close) but much higher reliability.
2. Wick Beyond Level:
Logic: [/b> Any touch of ORB high/low triggers breakout.
Why:
• Earliest possible entry
• Captures aggressive momentum moves
Risk:
• High false breakout rate (60-70%)
• Stop runs trigger signals
• Requires very tight stops (difficult to manage)
Use Case: Scalping with 1-2 point profit targets where any penetration = trade.
3. Body Beyond Level:
Logic: [/b> Candle body (close vs open) must be entirely outside range.
Why:
• Strictest confirmation
• Ensures directional conviction (not just momentum)
• Lowest false breakout rate
Example: Trade-off: [/b> Very conservative—misses some valid breakouts but rarely triggers on false ones.
Volume Confirmation Layer:
All confirmation methods can require volume validation:
Volume Multiplier Logic: Rationale: [/b> True breakouts are driven by institutional activity (large size). Volume spike confirms real conviction vs. stop-run manipulation.
Statistical Impact: [/b>
• Breakouts with volume confirmation: ~65% success rate
• Breakouts without volume: ~45% success rate
• Difference: 20 percentage points edge
Implementation Note: [/b>
Volume confirmation adds complexity—you'll miss breakouts that work but lack volume. However, when targeting 1.5x+ extensions (ambitious goals), volume confirmation becomes critical because those moves require sustained institutional participation.
Recommended Settings by Strategy: [/b>
Scalping (1-2 point targets): [/b>
• Method: Close
• Volume: OFF
• Rationale: Quick in/out doesn't need perfection
Intraday Swing (5-10 point targets): [/b>
• Method: Close
• Volume: ON (1.5x multiplier)
• Rationale: Balance reliability and opportunity
Position Trading (full-day holds): [/b>
• Method: Body
• Volume: ON (2.0x multiplier)
• Rationale: Must be certain—large stops require high win rate
🔥 FAILED BREAKOUT SYSTEM
The Core Insight: [/b>
Failed breakouts are often more profitable [/b> than successful breakouts because they create trapped traders with predictable behavior.
Failed Breakout Definition: [/b>
A breakout that:
1. Initially penetrates ORB level with confirmation
2. Attracts participants (volume spike, momentum)
3. Fails to extend (stalls or immediately reverses)
4. Returns inside ORB range within N bars
Psychology of Failure: [/b>
When breakout fails:
• Breakout buyers are trapped [/b>: Bought at ORB high, now underwater
• Early longs reduce: Take profit, fearful of reversal
• Shorts smell blood: See failed breakout as reversal signal
• Result: Cascade of selling as trapped bulls exit + new shorts enter
Mirror image for failed bearish breakouts (trapped shorts cover + new longs enter).
Failure Detection Parameters: [/b>
1. Failure Confirmation Bars (default: 3): [/b>
How many bars after breakout to confirm failure?
Logic: Settings: [/b>
• 2 bars: Aggressive failure detection (more signals, more false failures)
• 3 bars Balanced (default)
• 5-10 bars: Conservative (wait for clear reversal)
Why This Matters:
Too few bars: You call "failed breakout" when price is just consolidating before next leg.
Too many bars: You miss the reversal entry (price already back in range).
2. Failure Buffer (default: 0.1 ATR): [/b>
How far inside ORB must price return to confirm failure?
Formula: Why Buffer Matters: clear rejection [/b> (not just hovering at level).
Settings: [/b>
• 0.0 ATR: No buffer, immediate failure signal
• 0.1 ATR: Small buffer (default) - filters noise
• [b>0.2-0.3 ATR: Large buffer - only dramatic failures count
Example: Reversal Entry System: [/b>
When failure confirmed, system generates complete reversal trade:
For Failed Bull Breakout (Short Reversal): [/b>
Entry: [/b> Current close when failure confirmed
Stop Loss: [/b> Extreme high since breakout + 0.10 ATR padding
Target 1: [/b> ORB High - (ORB Range × 0.5)
Target 2: Target 3: [/b> ORB High - (ORB Range × 1.5)
Example:
• ORB High: 5850, ORB Low: 5842, Range: 8 points
• Breakout to 5853, fails, reverses to 5848 (entry)
• Stop: 5853 + 1 = 5854 (6 point risk)
• T1: 5850 - 4 = 5846 (-2 points, 1:3 R:R)
• T2: 5850 - 8 = 5842 (-6 points, 1:1 R:R)
• T3: 5850 - 12 = 5838 (-10 points, 1.67:1 R:R)
[b>Why These Targets? [/b>
• T1 (0.5x ORB below high): Trapped bulls start panic
• T2 (1.0x ORB = ORB Mid): Major retracement, momentum fully reversed
• T3 (1.5x ORB): Reversal extended, now targeting opposite side
Historical Performance: [/b>
Failed breakout reversals in ORB Fusion's tracking system show:
• Win Rate: 65-75% (significantly higher than initial breakouts)
• Average Winner: 1.2x ORB range
• Average Loser: 0.5x ORB range (protected by stop at extreme)
• Expectancy: Strongly positive even with <70% win rate
Why Failed Breakouts Outperform: [/b>
1. Information Advantage: You now know what price did (failed to extend). Initial breakout trades are speculative; reversal trades are reactive to confirmed failure.
2. Trapped Participant Pressure: Every trapped bull becomes a seller. This creates sustained pressure.
3. Stop Loss Clarity: Extreme high is obvious stop (just beyond recent high). Breakout trades have ambiguous stops (ORB mid? Recent low? Too wide or too tight).
4. Mean Reversion Edge: Failed breakouts return to value (ORB mid). Initial breakouts try to escape value (harder to sustain).
Critical Insight: [/b>
"The best trade is often the one that trapped everyone else."
Failed breakouts create asymmetric opportunity because you're trading against [/b> trapped participants rather than with [/b> them. When you see a failed breakout signal, you're seeing real-time evidence that the market rejected directional conviction—that's exploitable.
📐 FIBONACCI EXTENSION SYSTEM
Six Extension Levels: [/b>
Extensions project how far price will travel after ORB breakout. Based on Fibonacci ratios + empirical market behavior.
1. 1.272x (27.2% Extension): [/b>
Formula: [/b> ORB High/Low + (ORB Range × 0.272)
Psychology: [/b> Initial probe beyond ORB. Early momentum + trapped shorts (on bull side) covering.
Probability of Reach: [/b> ~75-80% after confirmed breakout
Trading: [/b>
• First resistance/support after breakout
• Partial profit target (take 30-50% off)
• Watch for rejection here (could signal failure in progress)
Why 1.272? [/b> Related to harmonic patterns (1.272 is √1.618). Empirically, markets often stall at 25-30% extension before deciding whether to continue or fail.
2. 1.5x (50% Extension):
Formula: [/b> ORB High/Low + (ORB Range × 0.5)
Psychology: [/b> Breakout gaining conviction. Requires sustained buying/selling (not just momentum spike).
Probability of Reach: [/b> ~60-65% after confirmed breakout
Trading: [/b>
• Major partial profit (take 50-70% off)
• Move stops to breakeven
• Trail remaining position
Why 1.5x? [/b> Classic halfway point to 2.0x. Markets often consolidate here before final push. If day type is "Normal," this is likely the high/low for the day.
3. 1.618x (Golden Ratio Extension): [/b>
Formula: [/b> ORB High/Low + (ORB Range × 0.618)
Psychology: [/b> Strong directional day. Institutional conviction + retail FOMO.
Probability of Reach: [/b> ~45-50% after confirmed breakout
Trading: [/b>
• Final partial profit (close 80-90%)
• Trail remainder with wide stop (allow breathing room)
Why 1.618? [/b> Fibonacci golden ratio. Appears consistently in market geometry. When price reaches 1.618x extension, move is "mature" and reversal risk increases.
4. 2.0x (100% Extension): [/b>
Formula: ORB High/Low + (ORB Range × 1.0)
Psychology: [/b> Trend day confirmed. Opening range completely duplicated.
Probability of Reach: [/b> ~30-35% after confirmed breakout
Trading: Why 2.0x? [/b> Psychological level—range doubled. Also corresponds to typical daily ATR in many instruments (opening range ~ 0.5 ATR, daily range ~ 1.0 ATR).
5. 2.618x (Super Extension):
Formula: [/b> ORB High/Low + (ORB Range × 1.618)
Psychology: [/b> Parabolic move. News-driven or squeeze.
Probability of Reach: [/b> ~10-15% after confirmed breakout
[b>Trading: Why 2.618? [/b> Fibonacci ratio (1.618²). Rare to reach—when it does, move is extreme. Often precedes multi-day consolidation or reversal.
6. 3.0x (Extreme Extension): [/b>
Formula: [/b> ORB High/Low + (ORB Range × 2.0)
Psychology: [/b> Market melt-up/crash. Only in extreme events.
[b>Probability of Reach: [/b> <5% after confirmed breakout
Trading: [/b>
• Close immediately if reached
• These are outlier events (black swans, flash crashes, squeeze-outs)
• Holding for more is greed—take windfall profit
Why 3.0x? [/b> Triple opening range. So rare it's statistical noise. When it happens, it's headline news.
Visual Example:
ES futures, ORB 5842-5850 (8 point range), Bullish breakout:
• ORB High : 5850.00 (entry zone)
• 1.272x : 5850 + 2.18 = 5852.18 (first resistance)
• 1.5x : 5850 + 4.00 = 5854.00 (major target)
• 1.618x : 5850 + 4.94 = 5854.94 (strong target)
• 2.0x : 5850 + 8.00 = 5858.00 (trend day)
• 2.618x : 5850 + 12.94 = 5862.94 (extreme)
• 3.0x : 5850 + 16.00 = 5866.00 (parabolic)
Profit-Taking Strategy:
Optimal scaling out at extensions:
• Breakout entry at 5850.50
• 30% off at 1.272x (5852.18) → +1.68 points
• 40% off at 1.5x (5854.00) → +3.50 points
• 20% off at 1.618x (5854.94) → +4.44 points
• 10% off at 2.0x (5858.00) → +7.50 points
[b>Average Exit: Conclusion: [/b> Scaling out at extensions produces 40% higher expectancy than holding for home runs.
📊 GAP ANALYSIS & FILL PSYCHOLOGY
[b>Gap Definition: [/b>
Price discontinuity between previous close and current open:
• Gap Up : Open > Previous Close + noise threshold (0.1 ATR)
• Gap Down : Open < Previous Close - noise threshold
Why Gaps Matter: [/b>
Gaps represent unfilled orders [/b>. When market gaps up, all limit buy orders between yesterday's close and today's open are never filled. Those buyers are "left behind." Psychology: they wait for price to return ("fill the gap") so they can enter. This creates magnetic pull [/b> toward gap level.
Gap Fill Statistics (Empirical): [/b>
• Gaps <0.5% [/b>: 85-90% fill within same day
• Gaps 0.5-1.0% [/b>: 70-75% fill within same day, 90%+ within week
• Gaps >1.0% [/b>: 50-60% fill within same day (major news often prevents fill)
Gap Fill Strategy: [/b>
Setup 1: Gap-and-Go
Gap opens, extends away from gap (doesn't fill).
• ORB confirms direction away from gap
• Trade WITH ORB breakout direction
• Expectation: Gap won't fill today (momentum too strong)
Setup 2: Gap-Fill Fade
Gap opens, but fails to extend. Price drifts back toward gap.
• ORB breakout TOWARD gap (not away)
• Trade toward gap fill level
• Target: Previous close (gap fill complete)
Setup 3: Gap-Fill Rejection
Gap fills (touches previous close) then rejects.
• ORB breakout AWAY from gap after fill
• Trade away from gap direction
• Thesis: Gap filled (orders executed), now resume original direction
[b>Example: Scenario A (Gap-and-Go):
• ORB breaks upward to $454 (away from gap)
• Trade: LONG breakout, expect continued rally
• Gap becomes support ($452)
Scenario B (Gap-Fill):
• ORB breaks downward through $452.50 (toward gap)
• Trade: SHORT toward gap fill at $450.00
• Target: $450.00 (gap filled), close position
Scenario C (Gap-Fill Rejection):
• Price drifts to $450.00 (gap filled) early in session
• ORB establishes $450-$451 after gap fill
• ORB breaks upward to $451.50
• Trade: LONG breakout (gap is filled, now resume rally)
ORB Fusion Integration: [/b>
Dashboard shows:
• Gap type (Up/Down/None)
• Gap size (percentage)
• Gap fill status (Filled ✓ / Open)
This informs setup confidence:
• ORB breakout AWAY from unfilled gap: +10% confidence (gap becomes support/resistance)
• ORB breakout TOWARD unfilled gap: -10% confidence (gap fill may override ORB)
[b>📈 VWAP & INSTITUTIONAL BIAS [/b>
[b>Volume-Weighted Average Price (VWAP): [/b>
Average price weighted by volume at each price level. Represents true "average" cost for the day.
[b>Calculation: Institutional Benchmark [/b>: Institutions (mutual funds, pension funds) use VWAP as performance benchmark. If they buy above VWAP, they underperformed; below VWAP, they outperformed.
2. [b>Algorithmic Target [/b>: Many algos are programmed to buy below VWAP and sell above VWAP to achieve "fair" execution.
3. [b>Support/Resistance [/b>: VWAP acts as dynamic support (price above) or resistance (price below).
[b>VWAP Bands (Standard Deviations): [/b>
• [b>1σ Band [/b>: VWAP ± 1 standard deviation
- Contains ~68% of volume
- Normal trading range
- Bounces common
• [b>2σ Band [/b>: VWAP ± 2 standard deviations
- Contains ~95% of volume
- Extreme extension
- Mean reversion likely
ORB + VWAP Confluence: [/b>
Highest-probability setups occur when ORB and VWAP align:
Bullish Confluence: [/b>
• ORB breakout upward (bullish signal)
• Price above VWAP (institutional buying)
• Confidence boost: +15%
Bearish Confluence: [/b>
• ORB breakout downward (bearish signal)
• Price below VWAP (institutional selling)
• Confidence boost: +15%
[b>Divergence Warning:
• ORB breakout upward BUT price below VWAP
• Conflict: Breakout says "buy," VWAP says "sell"
• Confidence penalty: -10%
• Interpretation: Retail buying but institutions not participating (lower quality breakout)
📊 MOMENTUM CONTEXT SYSTEM
[b>Innovation: Candle Coloring by Position
Rather than fixed support/resistance lines, ORB Fusion colors candles based on their [b>relationship to ORB :
[b>Three Zones: [/b>
1. Inside ORB (Blue Boxes): [/b>
[b>Calculation:
• Darker blue: Near extremes of ORB (potential breakout imminent)
• Lighter blue: Near ORB mid (consolidation)
[b>Trading: [/b> Coiled spring—await breakout.
[b>2. Above ORB (Green Boxes):
[b>Calculation: 3. Below ORB (Red Boxes):
Mirror of above ORB logic.
[b>Special Contexts: [/b>
[b>Breakout Bar (Darkest Green/Red): [/b>
The specific bar where breakout occurs gets maximum color intensity regardless of distance. This highlights the pivotal moment.
[b>Failed Breakout Bar (Orange/Warning): [/b>
When failed breakout is confirmed, that bar gets orange/warning color. Visual alert: "reversal opportunity here."
[b>Near Extension (Cyan/Magenta Tint): [/b>
When price is within 0.5 ATR of an extension level, candle gets tinted cyan (bull) or magenta (bear). Indicates "target approaching—prepare to take profit."
[b>Why Visual Context? [/b>
Traditional indicators show lines. ORB Fusion shows [b>context-aware momentum [/b>. Glance at chart:
• Lots of blue? Consolidation day (fade extremes).
• Progressive green? Trend day (follow).
• Green then orange? Failed breakout (reversal setup).
This visual language communicates market state instantly—no interpretation needed.
🎯 TRADE SETUP GENERATION & GRADING [/b>
[b>Algorithmic Setup Detection: [/b>
ORB Fusion continuously evaluates market state and generates current best trade setup with:
• Action (LONG / SHORT / FADE HIGH / FADE LOW / WAIT)
• Entry price
• Stop loss
• Three targets
• Risk:Reward ratio
• Confidence score (0-100)
• Grade (A+ to D)
[b>Setup Types: [/b>
[b>1. ORB LONG (Bullish Breakout): [/b>
[b>Trigger: [/b>
• Bullish ORB breakout confirmed
• Not failed
[b>Parameters:
• Entry: Current close
• Stop: ORB mid (protects against failure)
• T1: ORB High + 0.5x range (1.5x extension)
• T2: ORB High + 1.0x range (2.0x extension)
• T3: ORB High + 1.618x range (2.618x extension)
[b>Confidence Scoring:
[b>Trigger: [/b>
• Bearish breakout occurred
• Failed (returned inside ORB)
[b>Parameters: [/b>
• Entry: Close when failure confirmed
• Stop: Extreme low since breakout + 0.10 ATR
• T1: ORB Low + 0.5x range
• T2: ORB Low + 1.0x range (ORB mid)
• T3: ORB Low + 1.5x range
[b>Confidence Scoring:
[b>Trigger:
• Inside ORB
• Close > ORB mid (near high)
[b>Parameters: [/b>
• Entry: ORB High (limit order)
• Stop: ORB High + 0.2x range
• T1: ORB Mid
• T2: ORB Low
[b>Confidence Scoring: [/b>
Base: 40 points (lower base—range fading is lower probability than breakout/reversal)
[b>Use Case: [/b> Rotation days. Not recommended on normal/trend days.
[b>6. FADE LOW (Range Trade):
Mirror of FADE HIGH.
[b>7. WAIT:
[b>Trigger: [/b>
• ORB not complete yet OR
• No clear setup (price in no-man's-land)
[b>Action: [/b> Observe, don't trade.
[b>Confidence: [/b> 0 points
[b>Grading System:
```
Confidence → Grade
85-100 → A+
75-84 → A
65-74 → B+
55-64 → B
45-54 → C
0-44 → D
```
[b>Grade Interpretation: [/b>
• [b>A+ / A: High probability setup. Take these trades.
• [b>B+ / B [/b>: Decent setup. Trade if fits system rules.
• [b>C [/b>: Marginal setup. Only if very experienced.
• [b>D [/b>: Poor setup or no setup. Don't trade.
[b>Example Scenario: [/b>
ES futures:
• ORB: 5842-5850 (8 point range)
• Bullish breakout to 5851 confirmed
• Volume: 2.0x average (confirmed)
• VWAP: 5845 (price above VWAP ✓)
• Day type: Developing (too early, no bonus)
• Gap: None
[b>Setup: [/b>
• Action: LONG
• Entry: 5851
• Stop: 5846 (ORB mid, -5 point risk)
• T1: 5854 (+3 points, 1:0.6 R:R)
• T2: 5858 (+7 points, 1:1.4 R:R)
• T3: 5862.94 (+11.94 points, 1:2.4 R:R)
[b>Confidence: LONG with 55% confidence.
Interpretation: Solid setup, not perfect. Trade it if your system allows B-grade signals.
[b>📊 STATISTICS TRACKING & PERFORMANCE ANALYSIS [/b>
[b>Real-Time Performance Metrics: [/b>
ORB Fusion tracks comprehensive statistics over user-defined lookback (default 50 days):
[b>Breakout Performance: [/b>
• [b>Bull Breakouts: [/b> Total count, wins, losses, win rate
• [b>Bear Breakouts: [/b> Total count, wins, losses, win rate
[b>Win Definition: [/b> Breakout reaches ≥1.0x extension (doubles the opening range) before end of day.
[b>Example: [/b>
• ORB: 5842-5850 (8 points)
• Bull breakout at 5851
• Reaches 5858 (1.0x extension) by close
• Result: WIN
[b>Failed Breakout Performance: [/b>
• [b>Total Failed Breakouts [/b>: Count of breakouts that failed
• [b>Reversal Wins [/b>: Count where reversal trade reached target
• [b>Failed Reversal Win Rate [/b>: Wins / Total Failed
[b>Win Definition for Reversals: [/b>
• Failed bull → reversal short reaches ORB mid
• Failed bear → reversal long reaches ORB mid
[b>Extension Tracking: [/b>
• [b>Average Extension Reached [/b>: Mean of maximum extension achieved across all breakout days
• [b>Max Extension Overall [/b>: Largest extension ever achieved in lookback period
[b>Example: 🎨 THREE DISPLAY MODES
[b>Design Philosophy: [/b>
Not all traders need all features. Beginners want simplicity. Professionals want everything. ORB Fusion adapts.
[b>SIMPLE MODE: [/b>
[b>Shows: [/b>
• Primary ORB levels (High, Mid, Low)
• ORB box
• Breakout signals (triangles)
• Failed breakout signals (crosses)
• Basic dashboard (ORB status, breakout status, setup)
• VWAP
[b>Hides: [/b>
• Session ORBs (Asian, London, NY)
• IB levels and extensions
• ORB extensions beyond basic levels
• Gap analysis visuals
• Statistics dashboard
• Momentum candle coloring
• Narrative dashboard
[b>Use Case: [/b>
• Traders who want clean chart
• Focus on core ORB concept only
• Mobile trading (less screen space)
[b>STANDARD MODE:
[b>Shows Everything in Simple Plus: [/b>
• Session ORBs (Asian, London, NY)
• IB levels (high, low, mid)
• IB extensions
• ORB extensions (1.272x, 1.5x, 1.618x, 2.0x)
• Gap analysis and fill targets
• VWAP bands (1σ and 2σ)
• Momentum candle coloring
• Context section in dashboard
• Narrative dashboard
[b>Hides: [/b>
• Advanced extensions (2.618x, 3.0x)
• Detailed statistics dashboard
[b>Use Case: [/b>
• Most traders
• Balance between information and clarity
• Covers 90% of use cases
[b>ADVANCED MODE:
[b>Shows Everything:
• All session ORBs
• All IB levels and extensions
• All ORB extensions (including 2.618x and 3.0x)
• Full gap analysis
• VWAP with both 1σ and 2σ bands
• Momentum candle coloring
• Complete statistics dashboard
• Narrative dashboard
• All context metrics
[b>Use Case: [/b>
• Professional traders
• System developers
• Those who want maximum information density
[b>Switching Modes: [/b>
Single dropdown input: "Display Mode" → Simple / Standard / Advanced
Entire indicator adapts instantly. No need to toggle 20 individual settings.
📖 NARRATIVE DASHBOARD
[b>Innovation: Plain-English Market State [/b>
Most indicators show data. ORB Fusion explains what the data [b>means [/b>.
[b>Narrative Components: [/b>
[b>1. Phase: [/b>
• "📍 Building ORB..." (during ORB session)
• "📊 Trading Phase" (after ORB complete)
• "⏳ Pre-Market" (before ORB session)
[b>2. Status (Current Observation): [/b>
• "⚠️ Failed breakout - reversal likely"
• "🚀 Bullish momentum in play"
• "📉 Bearish momentum in play"
• "⚖️ Consolidating in range"
• "👀 Monitoring for setup"
[b>3. Next Level:
Tells you what to watch for:
• "🎯 1.5x @ 5854.00" (next extension target)
• "Watch ORB levels" (inside range, await breakout)
[b>4. Setup: [/b>
Current trade setup + grade:
• "LONG " (bullish breakout, A-grade)
• "🔥 SHORT REVERSAL " (failed bull breakout, A+-grade)
• "WAIT " (no setup)
[b>5. Reason: [/b>
Why this setup exists:
• "ORB Bullish Breakout"
• "Failed Bear Breakout - High Probability Reversal"
• "Range Fade - Near High"
[b>6. Tip (Market Insight):
Contextual advice:
• "🔥 TREND DAY - Trail stops" (day type is trending)
• "🔄 ROTATION - Fade extremes" (day type is rotating)
• "📊 Gap unfilled - magnet level" (gap creates target)
• "📈 Normal conditions" (no special context)
[b>Example Narrative:
```
📖 ORB Narrative
━━━━━━━━━━━━━━━━
Phase | 📊 Trading Phase
Status | 🚀 Bullish momentum in play
Next | 🎯 1.5x @ 5854.00
📈 Setup | LONG
Reason | ORB Bullish Breakout
💡 Tip | 🔥 TREND DAY - Trail stops
```
[b>Glance Interpretation: [/b>
"We're in trading phase. Bullish breakout happened (momentum in play). Next target is 1.5x extension at 5854. Current setup is LONG with A-grade. It's a trend day, so trail stops (don't take early profits)."
Complete market state communicated in 6 lines. No interpretation needed.
[b>Why This Matters:
Beginner traders struggle with "So what?" question. Indicators show lines and signals, but what does it mean [/b>? Narrative dashboard bridges this gap.
Professional traders benefit too—rapid context assessment during fast-moving markets. No time to analyze; glance at narrative, get action plan.
🔔 INTELLIGENT ALERT SYSTEM
[b>Four Alert Types: [/b>
[b>1. Breakout Alert: [/b>
[b>Trigger: [/b> ORB breakout confirmed (bull or bear)
[b>Message: [/b>
```
🚀 ORB BULLISH BREAKOUT
Price: 5851.00
Volume Confirmed
Grade: A
```
[b>Frequency: [/b> Once per bar (prevents spam)
[b>2. Failed Breakout Alert: [/b>
[b>Trigger: [/b> Breakout fails, reversal setup generated
[b>Message: [/b>
```
🔥 FAILED BULLISH BREAKOUT!
HIGH PROBABILITY SHORT REVERSAL
Entry: 5848.00
Stop: 5854.00
T1: 5846.00
T2: 5842.00
Historical Win Rate: 73%
```
[b>Why Comprehensive? [/b> Failed breakout alerts include complete trade plan. You can execute immediately from alert—no need to check chart.
[b>3. Extension Alert:
[b>Trigger: [/b> Price reaches extension level for first time
[b>Message: [/b>
```
🎯 Bull Extension 1.5x reached @ 5854.00
```
[b>Use: [/b> Profit-taking reminder. When extension hit, consider scaling out.
[b>4. IB Break Alert: [/b>
[b>Trigger: [/b> Price breaks above IB high or below IB low
[b>Message: [/b>
```
📊 IB HIGH BROKEN - Potential Trend Day
```
[b>Use: [/b> Day type classification. IB break suggests trend day developing—adjust strategy to trend-following mode.
[b>Alert Management: [/b>
Each alert type can be enabled/disabled independently. Prevents notification overload.
[b>Cooldown Logic: [/b>
Alerts won't fire if same alert type triggered within last bar. Prevents:
• "Breakout" alert every tick during choppy breakout
• Multiple "extension" alerts if price oscillates at level
Ensures: One clean alert per event.
⚙️ KEY PARAMETERS EXPLAINED
[b>Opening Range Settings: [/b>
• [b>ORB Timeframe [/b> (5/15/30/60 min): Duration of opening range window
- 30 min recommended for most traders
• [b>Use RTH Only [/b> (ON/OFF): Only trade during regular trading hours
- ON recommended (avoids thin overnight markets)
• [b>Use LTF Precision [/b> (ON/OFF): Sample 1-minute bars for accuracy
- ON recommended (critical for charts >1 minute)
• [b>Precision TF [/b> (1/5 min): Timeframe for LTF sampling
- 1 min recommended (most accurate)
[b>Session ORBs: [/b>
• [b>Show Asian/London/NY ORB [/b> (ON/OFF): Display multi-session ranges
- OFF in Simple mode
- ON in Standard/Advanced if trading 24hr markets
• [b>Session Windows [/b>: Time ranges for each session ORB
- Defaults align with major session opens
[b>Initial Balance: [/b>
• [b>Show IB [/b> (ON/OFF): Display Initial Balance levels
- ON recommended for day type classification
• [b>IB Session Window [/b> (0930-1030): First hour of trading
- Default is standard for US equities
• [b>Show IB Extensions [/b> (ON/OFF): Project IB extension targets
- ON recommended (identifies trend days)
• [b>IB Extensions 1-4 [/b> (0.5x, 1.0x, 1.5x, 2.0x): Extension multipliers
- Defaults are Market Profile standard
[b>ORB Extensions: [/b>
• [b>Show Extensions [/b> (ON/OFF): Project ORB extension targets
- ON recommended (defines profit targets)
• [b>Enable Individual Extensions [/b> (1.272x, 1.5x, 1.618x, 2.0x, 2.618x, 3.0x)
- Enable 1.272x, 1.5x, 1.618x, 2.0x minimum
- Disable 2.618x and 3.0x unless trading very volatile instruments
[b>Breakout Detection:
• [b>Confirmation Method [/b> (Close/Wick/Body):
- Close recommended (best balance)
- Wick for scalping
- Body for conservative
• [b>Require Volume Confirmation [/b> (ON/OFF):
- ON recommended (increases reliability)
• [b>Volume Multiplier [/b> (1.0-3.0):
- 1.5x recommended
- Lower for thin instruments
- Higher for heavy volume instruments
[b>Failed Breakout System: [/b>
• [b>Enable Failed Breakouts [/b> (ON/OFF):
- ON strongly recommended (highest edge)
• [b>Bars to Confirm Failure [/b> (2-10):
- 3 bars recommended
- 2 for aggressive (more signals, more false failures)
- 5+ for conservative (fewer signals, higher quality)
• [b>Failure Buffer [/b> (0.0-0.5 ATR):
- 0.1 ATR recommended
- Filters noise during consolidation near ORB level
• [b>Show Reversal Targets [/b> (ON/OFF):
- ON recommended (visualizes trade plan)
• [b>Reversal Target Mults [/b> (0.5x, 1.0x, 1.5x):
- Defaults are tested values
- Adjust based on average daily range
[b>Gap Analysis:
• [b>Show Gap Analysis [/b> (ON/OFF):
- ON if trading instruments that gap frequently
- OFF for 24hr markets (forex, crypto—no gaps)
• [b>Gap Fill Target [/b> (ON/OFF):
- ON to visualize previous close (gap fill level)
[b>VWAP:
• [b>Show VWAP [/b> (ON/OFF):
- ON recommended (key institutional level)
• [b>Show VWAP Bands [/b> (ON/OFF):
- ON in Standard/Advanced
- OFF in Simple
• [b>Band Multipliers (1.0σ, 2.0σ):
- Defaults are standard
- 1σ = normal range, 2σ = extreme
[b>Day Type: [/b>
• [b>Show Day Type Analysis [/b> (ON/OFF):
- ON recommended (critical for strategy adaptation)
• [b>Trend Day Threshold [/b> (1.0-2.5 IB mult):
- 1.5x recommended
- When price extends >1.5x IB, classifies as Trend Day
[b>Enhanced Visuals:
• [b>Show Momentum Candles [/b> (ON/OFF):
- ON for visual context
- OFF if chart gets too colorful
• [b>Show Gradient Zone Fills [/b> (ON/OFF):
- ON for professional look
- OFF for minimalist chart
• [b>Label Display Mode [/b> (All/Adaptive/Minimal):
- Adaptive recommended (shows nearby labels only)
- All for information density
- Minimal for clean chart
• [b>Label Proximity [/b> (1.0-5.0 ATR):
- 3.0 ATR recommended
- Labels beyond this distance are hidden (Adaptive mode)
[b>🎓 PROFESSIONAL USAGE PROTOCOL [/b>
[b>Phase 1: Learning the System (Week 1) [/b>
[b>Goal: [/b> Understand ORB concepts and dashboard interpretation
[b>Setup: [/b>
• Display Mode: STANDARD
• ORB Timeframe: 30 minutes
• Enable ALL features (IB, extensions, failed breakouts, VWAP, gap analysis)
• Enable statistics tracking
[b>Actions: [/b>
• Paper trade ONLY—no real money
• Observe ORB formation every day (9:30-10:00 AM ET for US markets)
• Note when ORB breakouts occur and if they extend
• Note when breakouts fail and reversals happen
• Watch day type classification evolve during session
• Track statistics—which setups are working?
[b>Key Learning: [/b>
• How often do breakouts reach 1.5x extension? (typically 50-60% of confirmed breakouts)
• How often do breakouts fail? (typically 30-40%)
• Which setup grade (A/B/C) actually performs best? (should see A-grade outperforming)
• What day type produces best results? (trend days favor breakouts, rotation days favor fades)
[b>Phase 2: Parameter Optimization (Week 2) [/b>
[b>Goal: [/b> Tune system to your instrument and timeframe
[b>ORB Timeframe Selection:
• Run 5 days with 15-minute ORB
• Run 5 days with 30-minute ORB
• Compare: Which captures better breakouts on your instrument?
• Typically: 30-minute optimal for most, 15-minute for very liquid (ES, SPY)
[b>Volume Confirmation Testing:
• Run 5 days WITH volume confirmation
• Run 5 days WITHOUT volume confirmation
• Compare: Does volume confirmation increase win rate?
• If win rate improves by >5%: Keep volume confirmation ON
• If no improvement: Turn OFF (avoid missing valid breakouts)
[b>Failed Breakout Bars:
[b>Goal: [/b> Develop personal trading rules based on system signals
[b>Setup Selection Rules: [/b>
Define which setups you'll trade:
• [b>Conservative: [/b> Only A+ and A grades
• [b>Balanced: [/b> A+, A, B+ grades
• [b>Aggressive: [/b> All grades B and above
Test each approach for 5-10 trades, compare results.
[b>Position Sizing by Grade: [/b>
Consider risk-weighting by setup quality:
• A+ grade: 100% position size
• A grade: 75% position size
• B+ grade: 50% position size
• B grade: 25% position size
Example: If max risk is $1000/trade:
• A+ setup: Risk $1000
• A setup: Risk $750
• B+ setup: Risk $500
This matches bet sizing to edge.
[b>Day Type Adaptation: [/b>
Create rules for different day types:
Trend Days:
• Take ALL breakout signals (A/B/C grades)
• Hold for 2.0x extension minimum
• Trail stops aggressively (1.0 ATR trail)
• DON'T fade—reversals unlikely
Rotation Days:
• ONLY take failed breakout reversals
• Ignore initial breakout signals (likely to fail)
• Take profits quickly (0.5x extension)
• Focus on fade setups (Fade High/Fade Low)
Normal Days:
• Take A/A+ breakout signals only
• Take ALL failed breakout reversals (high probability)
• Target 1.0-1.5x extensions
• Partial profit-taking at extensions
Time-of-Day Rules: [/b>
Breakouts at different times have different probabilities:
10:00-10:30 AM (Early Breakout):
• ORB just completed
• Fresh breakout
• Probability: Moderate (50-55% reach 1.0x)
• Strategy: Conservative position sizing
10:30-12:00 PM (Mid-Morning):
• Momentum established
• Volume still healthy
• Probability: High (60-65% reach 1.0x)
• Strategy: Standard position sizing
12:00-2:00 PM (Lunch Doldrums):
• Volume dries up
• Whipsaw risk increases
• Probability: Low (40-45% reach 1.0x)
• Strategy: Avoid new entries OR reduce size 50%
2:00-4:00 PM (Afternoon Session):
• Late-day positioning
• EOD squeezes possible
• Probability: Moderate-High (55-60%)
• Strategy: Watch for IB break—if trending all day, follow
[b>Phase 4: Live Micro-Sizing (Month 2) [/b>
[b>Goal: [/b> Validate paper trading results with minimal risk
[b>Setup: [/b>
• 10-20% of intended full position size
• Take ONLY A+ and A grade setups
• Follow stop loss and targets religiously
[b>Execution: [/b>
• Execute from alerts OR from dashboard setup box
• Entry: Close of signal bar OR next bar market order
• Stop: Use exact stop from setup (don't widen)
• Targets: Scale out at T1/T2/T3 as indicated
[b>Tracking: [/b>
• Log every trade: Entry, Exit, Grade, Outcome, Day Type
• Calculate: Win rate, Average R-multiple, Max consecutive losses
• Compare to paper trading results (should be within 15%)
[b>Red Flags: [/b>
• Win rate <45%: System not suitable for this instrument/timeframe
• Major divergence from paper trading: Execution issues (slippage, late entries, emotional exits)
• Max consecutive losses >8: Hitting rough patch OR market regime changed
[b>Phase 5: Scaling Up (Months 3-6)
[b>Goal: [/b> Gradually increase to full position size
[b>Progression: [/b>
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
[b>Milestones Required to Scale Up: [/b>
• Minimum 30 trades at current size
• Win rate ≥48%
• Profit factor ≥1.2
• Max drawdown <20%
• Emotional control (no revenge trading, no FOMO)
[b>Advanced Techniques:
[b>Multi-Timeframe ORB: Assumes first 30-60 minutes establish value. Violation: Market opens after major news, price discovery continues for hours (opening range meaningless).
2. [b>Volume Indicates Conviction: ES, NQ, RTY, SPY, QQQ—high liquidity, clean ORB formation, reliable extensions
• [b>Large-Cap Stocks: AAPL, MSFT, TSLA, NVDA (>$5B market cap, >5M daily volume)
• [b>Liquid Futures: CL (crude oil), GC (gold), 6E (EUR/USD), ZB (bonds)—24hr markets benefit from session ORBs
• [b>Major Forex Pairs: [/b> EUR/USD, GBP/USD, USD/JPY—London/NY session ORBs work well
[b>Performs Poorly On: [/b>
• [b>Illiquid Stocks: <$1M daily volume, wide spreads, gappy price action
• [b>Penny Stocks: [/b> Manipulated, pump-and-dump, no real price discovery
• [b>Low-Volume ETFs: Exotic sector ETFs, leveraged products with thin volume
• [b>Crypto on Sketchy Exchanges: Wash trading, spoofing invalidates volume analysis
• [b>Earnings Days: [/b> ORB completes before earnings release, then completely resets (useless)
• Binary Event Days: FDA approvals, court rulings—discontinuous price action
[b>Known Weaknesses: [/b>
• [b>Slow Starts: ORB doesn't complete until 10:00 AM (30-min ORB). Early morning traders have no signals for 30 minutes. Consider using 15-minute ORB if this is problematic.
• [b>Failure Detection Lag: [/b> Failed breakout requires 3+ bars to confirm. By the time system signals reversal, price may have already moved significantly back inside range. Manual traders watching in real-time can enter earlier.
• [b>Extension Overshoot: [/b> System projects extensions mathematically (1.5x, 2.0x, etc.). Actual moves may stop short (1.3x) or overshoot (2.2x). Extensions are targets, not magnets.
• [b>Day Type Misclassification: [/b> Early in session, day type is "Developing." By the time it's classified definitively (often 11:00 AM+), half the day is over. Strategy adjustments happen late.
• [b>Gap Assumptions: [/b> System assumes gaps want to fill. Strong trend days never fill gaps (gap becomes support/resistance forever). Blindly trading toward gaps can backfire on trend days.
• [b>Volume Data Quality: Forex doesn't have centralized volume (uses tick volume as proxy—less reliable). Crypto volume is often fake (wash trading). Volume confirmation less effective on these instruments.
• [b>Multi-Session Complexity: [/b> When using Asian/London/NY ORBs simultaneously, chart becomes cluttered. Requires discipline to focus on relevant session for current time.
[b>Risk Factors: [/b>
• [b>Opening Gaps: Large gaps (>2%) can create distorted ORBs. Opening range might be unusually wide or narrow, making extensions unreliable.
• [b>Low Volatility Environments:[/b> When VIX <12, opening ranges can be tiny (0.2-0.3%). Extensions are equally tiny. Profit targets don't justify commission/slippage.
• [b>High Volatility Environments:[/b> When VIX >30, opening ranges are huge (2-3%+). Extensions project unrealistic targets. Failed breakouts happen faster (volatility whipsaw).
• [b>Algorithm Dominance:[/b> In heavily algorithmic markets (ES during overnight session), ORB levels can be manipulated—algos pin price to ORB high/low intentionally. Breakouts become stop-runs rather than genuine directional moves.
[b>⚠️ RISK DISCLOSURE[/b>
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Opening Range Breakout strategies, while based on sound market structure principles, do not guarantee profits and can result in significant losses.
The ORB Fusion indicator implements professional trading concepts including Opening Range theory, Market Profile Initial Balance analysis, Fibonacci extensions, and failed breakout reversal logic. These methodologies have theoretical foundations but past performance—whether backtested or live—is not indicative of future results.
Opening Range theory assumes the first 30-60 minutes of trading establish a meaningful value area and that breakouts from this range signal directional conviction. This assumption may not hold during:
• Major news events (FOMC, NFP, earnings surprises)
• Market structure changes (circuit breakers, trading halts)
• Low liquidity periods (holidays, early closures)
• Algorithmic manipulation or spoofing
Failed breakout detection relies on patterns of trapped participant behavior. While historically these patterns have shown statistical edges, market conditions change. Institutional algorithms, changing market structure, or regime shifts can reduce or eliminate edges that existed historically.
Initial Balance classification (trend day vs rotation day vs normal day) is a heuristic framework, not a deterministic prediction. Day type can change mid-session. Early classification may prove incorrect as the day develops.
Extension projections (1.272x, 1.5x, 1.618x, 2.0x, etc.) are probabilistic targets derived from Fibonacci ratios and empirical market behavior. They are not "support and resistance levels" that price must reach or respect. Markets can stop short of extensions, overshoot them, or ignore them entirely.
Volume confirmation assumes high volume indicates institutional participation and conviction. In algorithmic markets, volume can be artificially high (HFT activity) or artificially low (dark pools, internalization). Volume is a proxy, not a guarantee of conviction.
LTF precision sampling improves ORB accuracy by using 1-minute bars but introduces additional data dependencies. If 1-minute data is unavailable, inaccurate, or delayed, ORB calculations will be incorrect.
The grading system (A+/A/B+/B/C/D) and confidence scores aggregate multiple factors (volume, VWAP, day type, IB expansion, gap context) into a single assessment. This is a mechanical calculation, not artificial intelligence. The system cannot adapt to unprecedented market conditions or events outside its programmed logic.
Real trading involves slippage, commissions, latency, partial fills, and rejected orders not present in indicator calculations. ORB Fusion generates signals at bar close; actual fills occur with delay. Opening range forms during highest volatility (first 30 minutes)—spreads widen, slippage increases. Execution quality significantly impacts realized results.
Statistics tracking (win rates, extension levels reached, day type distribution) is based on historical bars in your lookback window. If lookback is small (<50 bars) or market regime changed, statistics may not represent future probabilities.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively (100+ trades minimum) before risking capital. Start with micro position sizing (5-10% of intended size) for 50+ trades to validate execution quality matches expectations.
Never risk more than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every single trade without exception. Understand that most retail traders lose money—sophisticated indicators do not change this fundamental reality. They systematize analysis but cannot eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, or fitness for any purpose. Users assume full responsibility for all trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
[b>═══════════════════════════════════════════════════════════════════════════════[/b>
[b>CLOSING STATEMENT[/b>
[b>═══════════════════════════════════════════════════════════════════════════════[/b>
Opening Range Breakout is not a trick. It's a framework. The first 30-60 minutes reveal where participants believe value lies. Breakouts signal directional conviction. Failures signal trapped participants. Extensions define profit targets. Day types dictate strategy. Failed breakouts create the highest-probability reversals.
ORB Fusion doesn't predict the future—it identifies [b>structure[/b>, detects [b>breakouts[/b>, recognizes [b>failures[/b>, and generates [b>probabilistic trade plans[/b> with defined risk and reward.
The edge is not in the opening range itself. The edge is in recognizing when the market respects structure (follow breakouts) versus when it violates structure (fade breakouts). The edge is in detecting failures faster than discretionary traders. The edge is in systematic classification that prevents catastrophic errors—like fading a trend day or holding through rotation.
Most indicators draw lines. ORB Fusion implements a complete institutional trading methodology: Opening Range theory, Market Profile classification, failed breakout intelligence, Fibonacci projections, volume confirmation, gap psychology, and real-time performance tracking.
Whether you're a beginner learning market structure or a professional seeking systematic ORB implementation, this system provides the framework.
"The market's first word is its opening range. Everything after is commentary." — ORB Fusion
MNO_2Step_Strategy_MOU_KAKU (Publish-Clear)//@version=5
strategy("MNO_2Step_Strategy_MOU_KAKU (Publish-Clear)", overlay=true, pyramiding=0,
max_labels_count=500, max_lines_count=500,
initial_capital=100000,
default_qty_type=strategy.percent_of_equity, default_qty_value=10)
// =========================
// Inputs
// =========================
emaSLen = input.int(5, "EMA Short (5)")
emaMLen = input.int(13, "EMA Mid (13)")
emaLLen = input.int(26, "EMA Long (26)")
macdFast = input.int(12, "MACD Fast")
macdSlow = input.int(26, "MACD Slow")
macdSignal = input.int(9, "MACD Signal")
macdZeroTh = input.float(0.2, "MOU: MACD near-zero threshold", step=0.05)
volLookback = input.int(5, "Volume MA days", minval=1)
volMinRatio = input.float(1.3, "MOU: Volume ratio min", step=0.1)
volStrong = input.float(1.5, "Strong volume ratio (Breakout/KAKU)", step=0.1)
volMaxRatio = input.float(3.0, "Volume ratio max (filter)", step=0.1)
wickBodyMult = input.float(2.0, "Pinbar: lowerWick >= body*x", step=0.1)
pivotLen = input.int(20, "Resistance lookback", minval=5)
pullMinPct = input.float(5.0, "Pullback min (%)", step=0.1)
pullMaxPct = input.float(15.0, "Pullback max (%)", step=0.1)
breakLookbackBars = input.int(5, "Pullback route: valid bars after break", minval=1)
// --- Breakout route (押し目なし初動ブレイク) ---
useBreakoutRoute = input.bool(true, "Enable MOU Breakout Route (no pullback)")
breakConfirmPct = input.float(0.3, "Break confirm: close > R*(1+%)", step=0.1)
bigBodyLookback = input.int(20, "Break candle body MA length", minval=5)
bigBodyMult = input.float(1.2, "Break candle: body >= MA*mult", step=0.1)
requireCloseNearHigh = input.bool(true, "Break candle: close near high")
closeNearHighPct = input.float(25.0, "Close near high threshold (% of range)", step=1.0)
allowMACDAboveZeroInstead = input.bool(true, "Breakout route: allow MACD GC above zero instead")
// 表示
showEMA = input.bool(true, "Plot EMAs")
showMouLabels = input.bool(true, "Show MOU/MOU-B labels")
showKakuLabels = input.bool(true, "Show KAKU labels")
showDebugTbl = input.bool(true, "Show debug table (last bar)")
showStatusLbl = input.bool(true, "Show status label (last bar always)")
locChoice = input.string("Below Bar", "Label location", options= )
lblLoc = locChoice == "Below Bar" ? location.belowbar : location.abovebar
// =========================
// 必ず決済が起きる設定（投稿クリア用）
// =========================
enableTPSL = input.bool(true, "Enable TP/SL")
tpPct = input.float(2.0, "Take Profit (%)", step=0.1, minval=0.1) // ←投稿クリア向けに近め
slPct = input.float(1.0, "Stop Loss (%)", step=0.1, minval=0.1) // ←投稿クリア向けに近め
maxHoldBars = input.int(30, "Max bars in trade (force close)", minval=1)
entryMode = input.string("MOU or KAKU", "Entry trigger", options= )
// ✅ 保険：トレード0件を避ける（投稿クリア用）
// 1回でもクローズトレードができたら自動で沈黙
publishAssist = input.bool(true, "Publish Assist (safety entry if 0 trades)")
// =========================
// EMA
// =========================
emaS = ta.ema(close, emaSLen)
emaM = ta.ema(close, emaMLen)
emaL = ta.ema(close, emaLLen)
plot(showEMA ? emaS : na, color=color.new(color.yellow, 0), title="EMA 5")
plot(showEMA ? emaM : na, color=color.new(color.blue, 0), title="EMA 13")
plot(showEMA ? emaL : na, color=color.new(color.orange, 0), title="EMA 26")
emaUpS = emaS > emaS
emaUpM = emaM > emaM
emaUpL = emaL > emaL
goldenOrder = emaS > emaM and emaM > emaL
above26_2days = close > emaL and close > emaL
baseTrendOK = (emaUpS and emaUpM and emaUpL) and goldenOrder and above26_2days
// =========================
// MACD
// =========================
= ta.macd(close, macdFast, macdSlow, macdSignal)
macdGC = ta.crossover(macdLine, macdSig)
macdUp = macdLine > macdLine
macdNearZero = math.abs(macdLine) <= macdZeroTh
macdGCAboveZero = macdGC and macdLine > 0 and macdSig > 0
macdMouOK = macdGC and macdNearZero and macdUp
macdBreakOK = allowMACDAboveZeroInstead ? (macdMouOK or macdGCAboveZero) : macdMouOK
// =========================
// Volume
// =========================
volMA = ta.sma(volume, volLookback)
volRatio = volMA > 0 ? (volume / volMA) : na
volumeMouOK = volRatio >= volMinRatio and volRatio <= volMaxRatio
volumeStrongOK = volRatio >= volStrong and volRatio <= volMaxRatio
// =========================
// Candle patterns
// =========================
body = math.abs(close - open)
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
pinbar = (lowerWick >= wickBodyMult * body) and (lowerWick > upperWick) and (close >= open)
bullEngulf = close > open and close < open and close >= open and open <= close
bigBull = close > open and open < emaM and close > emaS and (body > ta.sma(body, 20))
candleOK = pinbar or bullEngulf or bigBull
// =========================
// Resistance / Pullback route
// =========================
res = ta.highest(high, pivotLen)
pullbackPct = res > 0 ? (res - close) / res * 100.0 : na
pullbackOK = pullbackPct >= pullMinPct and pullbackPct <= pullMaxPct
brokeRes = ta.crossover(close, res )
barsSinceBreak = ta.barssince(brokeRes)
afterBreakZone = (barsSinceBreak >= 0) and (barsSinceBreak <= breakLookbackBars)
pullbackRouteOK = afterBreakZone and pullbackOK
// =========================
// Breakout route (押し目なし初動ブレイク)
// =========================
breakConfirm = close > res * (1.0 + breakConfirmPct / 100.0)
bullBreak = close > open
bodyMA = ta.sma(body, bigBodyLookback)
bigBodyOK = bodyMA > 0 ? (body >= bodyMA * bigBodyMult) : false
rng = math.max(high - low, syminfo.mintick)
closeNearHighOK = not requireCloseNearHigh ? true : ((high - close) / rng * 100.0 <= closeNearHighPct)
mou_breakout = useBreakoutRoute and baseTrendOK and breakConfirm and bullBreak and bigBodyOK and closeNearHighOK and volumeStrongOK and macdBreakOK
mou_pullback = baseTrendOK and volumeMouOK and candleOK and macdMouOK and pullbackRouteOK
mou = mou_pullback or mou_breakout
// =========================
// KAKU (Strict): 8条件 + 最終三点
// =========================
cond1 = emaUpS and emaUpM and emaUpL
cond2 = goldenOrder
cond3 = above26_2days
cond4 = macdGCAboveZero
cond5 = volumeMouOK
cond6 = candleOK
cond7 = pullbackOK
cond8 = pullbackRouteOK
all8_strict = cond1 and cond2 and cond3 and cond4 and cond5 and cond6 and cond7 and cond8
final3 = pinbar and macdGCAboveZero and volumeStrongOK
kaku = all8_strict and final3
// =========================
// Entry (strategy)
// =========================
entrySignal = entryMode == "KAKU only" ? kaku : (mou or kaku)
canEnter = strategy.position_size == 0
newEntryKaku = canEnter and kaku and entrySignal
newEntryMouB = canEnter and (not kaku) and mou_breakout and entrySignal
newEntryMou = canEnter and (not kaku) and mou_pullback and entrySignal
// --- Publish Assist（保険エントリー） ---
// 条件が厳しすぎて「トレード0件」だと投稿時に警告が出る。
// closedtradesが0の間だけ、軽いEMAクロスで1回だけ拾う（その後は沈黙）。
assistFast = ta.ema(close, 5)
assistSlow = ta.ema(close, 20)
assistEntry = publishAssist and strategy.closedtrades == 0 and canEnter and ta.crossover(assistFast, assistSlow)
// 実エントリー
if newEntryKaku or newEntryMouB or newEntryMou or assistEntry
strategy.entry("LONG", strategy.long)
// ラベル（視認）
if showMouLabels and newEntryMou
label.new(bar_index, low, "猛(IN)", style=label.style_label_up, color=color.new(color.lime, 0), textcolor=color.black)
if showMouLabels and newEntryMouB
label.new(bar_index, low, "猛B(IN)", style=label.style_label_up, color=color.new(color.lime, 0), textcolor=color.black)
if showKakuLabels and newEntryKaku
label.new(bar_index, low, "確(IN)", style=label.style_label_up, color=color.new(color.yellow, 0), textcolor=color.black)
if assistEntry
label.new(bar_index, low, "ASSIST(IN)", style=label.style_label_up, color=color.new(color.aqua, 0), textcolor=color.black)
// =========================
// Exit (TP/SL + 強制クローズ)
// =========================
inPos = strategy.position_size > 0
tpPx = inPos ? strategy.position_avg_price * (1.0 + tpPct/100.0) : na
slPx = inPos ? strategy.position_avg_price * (1.0 - slPct/100.0) : na
if enableTPSL
strategy.exit("TP/SL", from_entry="LONG", limit=tpPx, stop=slPx)
// 最大保有バーで強制決済（これが「レポート無し」回避の最後の保険）
var int entryBar = na
if strategy.position_size > 0 and strategy.position_size == 0
entryBar := bar_index
if strategy.position_size == 0
entryBar := na
forceClose = inPos and not na(entryBar) and (bar_index - entryBar >= maxHoldBars)
if forceClose
strategy.close("LONG")
// =========================
// 利確/損切/強制クローズのラベル
// =========================
closedThisBar = (strategy.position_size > 0) and (strategy.position_size == 0)
avgPrev = strategy.position_avg_price
tpPrev = avgPrev * (1.0 + tpPct/100.0)
slPrev = avgPrev * (1.0 - slPct/100.0)
hitTP = closedThisBar and high >= tpPrev
hitSL = closedThisBar and low <= slPrev
// 同一足TP/SL両方は厳密に判断できないので、表示は「TP優先」で簡略（投稿ギリギリ版）
if hitTP
label.new(bar_index, high, "利確", style=label.style_label_down, color=color.new(color.lime, 0), textcolor=color.black)
else if hitSL
label.new(bar_index, low, "損切", style=label.style_label_up, color=color.new(color.red, 0), textcolor=color.white)
else if closedThisBar and forceClose
label.new(bar_index, close, "時間決済", style=label.style_label_left, color=color.new(color.gray, 0), textcolor=color.white)
// =========================
// Signals (猛/猛B/確)
// =========================
plotshape(showMouLabels and mou_pullback and not kaku, title="MOU_PULLBACK", style=shape.labelup, text="猛",
color=color.new(color.lime, 0), textcolor=color.black, location=lblLoc, size=size.tiny)
plotshape(showMouLabels and mou_breakout and not kaku, title="MOU_BREAKOUT", style=shape.labelup, text="猛B",
color=color.new(color.lime, 0), textcolor=color.black, location=lblLoc, size=size.tiny)
plotshape(showKakuLabels and kaku, title="KAKU", style=shape.labelup, text="確",
color=color.new(color.yellow, 0), textcolor=color.black, location=lblLoc, size=size.small)
// =========================
// Alerts
// =========================
alertcondition(mou, title="MNO_MOU", message="MNO: MOU triggered")
alertcondition(mou_breakout, title="MNO_MOU_BREAKOUT", message="MNO: MOU Breakout triggered")
alertcondition(mou_pullback, title="MNO_MOU_PULLBACK", message="MNO: MOU Pullback triggered")
alertcondition(kaku, title="MNO_KAKU", message="MNO: KAKU triggered")
alertcondition(assistEntry, title="MNO_ASSIST_ENTRY", message="MNO: ASSIST ENTRY (publish safety)")
// =========================
// Status label（最終足に必ず表示）
// =========================
var label status = na
if showStatusLbl and barstate.islast
label.delete(status)
statusTxt =
"MNO RUNNING\n" +
"ClosedTrades: " + str.tostring(strategy.closedtrades) + "\n" +
"BaseTrend: " + (baseTrendOK ? "OK" : "NO") + "\n" +
"MOU: " + (mou ? "YES" : "no") + " (猛=" + (mou_pullback ? "Y" : "n") + " / 猛B=" + (mou_breakout ? "Y" : "n") + ")\n" +
"KAKU: " + (kaku ? "YES" : "no") + "\n" +
"VolRatio: " + (na(volRatio) ? "na" : str.tostring(volRatio, format.mintick)) + "\n" +
"Pull%: " + (na(pullbackPct) ? "na" : str.tostring(pullbackPct, format.mintick)) + "\n" +
"Pos: " + (inPos ? "IN" : "OUT")
status := label.new(bar_index, high, statusTxt, style=label.style_label_left, textcolor=color.white, color=color.new(color.black, 0))
// =========================
// Debug table（最終足のみ）
// =========================
var table t = table.new(position.top_right, 2, 14, border_width=1, border_color=color.new(color.white, 60))
fRow(_name, _cond, _r) =>
bg = _cond ? color.new(color.lime, 70) : color.new(color.red, 80)
tx = _cond ? "OK" : "NO"
table.cell(t, 0, _r, _name, text_color=color.white, bgcolor=color.new(color.black, 0))
table.cell(t, 1, _r, tx, text_color=color.white, bgcolor=bg)
if showDebugTbl and barstate.islast
table.cell(t, 0, 0, "MNO Debug", text_color=color.white, bgcolor=color.new(color.black, 0))
table.cell(t, 1, 0, "", text_color=color.white, bgcolor=color.new(color.black, 0))
fRow("BaseTrend", baseTrendOK, 1)
fRow("MOU Pullback", mou_pullback, 2)
fRow("MOU Breakout", mou_breakout, 3)
fRow("Break confirm", breakConfirm, 4)
fRow("Break big body", bigBodyOK, 5)
fRow("Break close high", closeNearHighOK, 6)
fRow("Break vol strong", volumeStrongOK, 7)
fRow("Break MACD", macdBreakOK, 8)
fRow("KAKU all8", all8_strict, 9)
fRow("KAKU final3", final3, 10)
fRow("AssistEntry", assistEntry, 11)
fRow("ClosedTrades>0", strategy.closedtrades > 0, 12)
just takesi TimeMNO_2Step_Strategy_MOU_KAKU (Publish-Clear)//@version=5
strategy("MNO_2Step_Strategy_MOU_KAKU (Publish-Clear)", overlay=true, pyramiding=0,
max_labels_count=500, max_lines_count=500,
initial_capital=100000,
default_qty_type=strategy.percent_of_equity, default_qty_value=10)
// =========================
// Inputs
// =========================
emaSLen = input.int(5, "EMA Short (5)")
emaMLen = input.int(13, "EMA Mid (13)")
emaLLen = input.int(26, "EMA Long (26)")
macdFast = input.int(12, "MACD Fast")
macdSlow = input.int(26, "MACD Slow")
macdSignal = input.int(9, "MACD Signal")
macdZeroTh = input.float(0.2, "MOU: MACD near-zero threshold", step=0.05)
volLookback = input.int(5, "Volume MA days", minval=1)
volMinRatio = input.float(1.3, "MOU: Volume ratio min", step=0.1)
volStrong = input.float(1.5, "Strong volume ratio (Breakout/KAKU)", step=0.1)
volMaxRatio = input.float(3.0, "Volume ratio max (filter)", step=0.1)
wickBodyMult = input.float(2.0, "Pinbar: lowerWick >= body*x", step=0.1)
pivotLen = input.int(20, "Resistance lookback", minval=5)
pullMinPct = input.float(5.0, "Pullback min (%)", step=0.1)
pullMaxPct = input.float(15.0, "Pullback max (%)", step=0.1)
breakLookbackBars = input.int(5, "Pullback route: valid bars after break", minval=1)
// --- Breakout route (押し目なし初動ブレイク) ---
useBreakoutRoute = input.bool(true, "Enable MOU Breakout Route (no pullback)")
breakConfirmPct = input.float(0.3, "Break confirm: close > R*(1+%)", step=0.1)
bigBodyLookback = input.int(20, "Break candle body MA length", minval=5)
bigBodyMult = input.float(1.2, "Break candle: body >= MA*mult", step=0.1)
requireCloseNearHigh = input.bool(true, "Break candle: close near high")
closeNearHighPct = input.float(25.0, "Close near high threshold (% of range)", step=1.0)
allowMACDAboveZeroInstead = input.bool(true, "Breakout route: allow MACD GC above zero instead")
// 表示
showEMA = input.bool(true, "Plot EMAs")
showMouLabels = input.bool(true, "Show MOU/MOU-B labels")
showKakuLabels = input.bool(true, "Show KAKU labels")
showDebugTbl = input.bool(true, "Show debug table (last bar)")
showStatusLbl = input.bool(true, "Show status label (last bar always)")
locChoice = input.string("Below Bar", "Label location", options= )
lblLoc = locChoice == "Below Bar" ? location.belowbar : location.abovebar
// =========================
// 必ず決済が起きる設定（投稿クリア用）
// =========================
enableTPSL = input.bool(true, "Enable TP/SL")
tpPct = input.float(2.0, "Take Profit (%)", step=0.1, minval=0.1) // ←投稿クリア向けに近め
slPct = input.float(1.0, "Stop Loss (%)", step=0.1, minval=0.1) // ←投稿クリア向けに近め
maxHoldBars = input.int(30, "Max bars in trade (force close)", minval=1)
entryMode = input.string("MOU or KAKU", "Entry trigger", options= )
// ✅ 保険：トレード0件を避ける（投稿クリア用）
// 1回でもクローズトレードができたら自動で沈黙
publishAssist = input.bool(true, "Publish Assist (safety entry if 0 trades)")
// =========================
// EMA
// =========================
emaS = ta.ema(close, emaSLen)
emaM = ta.ema(close, emaMLen)
emaL = ta.ema(close, emaLLen)
plot(showEMA ? emaS : na, color=color.new(color.yellow, 0), title="EMA 5")
plot(showEMA ? emaM : na, color=color.new(color.blue, 0), title="EMA 13")
plot(showEMA ? emaL : na, color=color.new(color.orange, 0), title="EMA 26")
emaUpS = emaS > emaS
emaUpM = emaM > emaM
emaUpL = emaL > emaL
goldenOrder = emaS > emaM and emaM > emaL
above26_2days = close > emaL and close > emaL
baseTrendOK = (emaUpS and emaUpM and emaUpL) and goldenOrder and above26_2days
// =========================
// MACD
// =========================
= ta.macd(close, macdFast, macdSlow, macdSignal)
macdGC = ta.crossover(macdLine, macdSig)
macdUp = macdLine > macdLine
macdNearZero = math.abs(macdLine) <= macdZeroTh
macdGCAboveZero = macdGC and macdLine > 0 and macdSig > 0
macdMouOK = macdGC and macdNearZero and macdUp
macdBreakOK = allowMACDAboveZeroInstead ? (macdMouOK or macdGCAboveZero) : macdMouOK
// =========================
// Volume
// =========================
volMA = ta.sma(volume, volLookback)
volRatio = volMA > 0 ? (volume / volMA) : na
volumeMouOK = volRatio >= volMinRatio and volRatio <= volMaxRatio
volumeStrongOK = volRatio >= volStrong and volRatio <= volMaxRatio
// =========================
// Candle patterns
// =========================
body = math.abs(close - open)
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
pinbar = (lowerWick >= wickBodyMult * body) and (lowerWick > upperWick) and (close >= open)
bullEngulf = close > open and close < open and close >= open and open <= close
bigBull = close > open and open < emaM and close > emaS and (body > ta.sma(body, 20))
candleOK = pinbar or bullEngulf or bigBull
// =========================
// Resistance / Pullback route
// =========================
res = ta.highest(high, pivotLen)
pullbackPct = res > 0 ? (res - close) / res * 100.0 : na
pullbackOK = pullbackPct >= pullMinPct and pullbackPct <= pullMaxPct
brokeRes = ta.crossover(close, res )
barsSinceBreak = ta.barssince(brokeRes)
afterBreakZone = (barsSinceBreak >= 0) and (barsSinceBreak <= breakLookbackBars)
pullbackRouteOK = afterBreakZone and pullbackOK
// =========================
// Breakout route (押し目なし初動ブレイク)
// =========================
breakConfirm = close > res * (1.0 + breakConfirmPct / 100.0)
bullBreak = close > open
bodyMA = ta.sma(body, bigBodyLookback)
bigBodyOK = bodyMA > 0 ? (body >= bodyMA * bigBodyMult) : false
rng = math.max(high - low, syminfo.mintick)
closeNearHighOK = not requireCloseNearHigh ? true : ((high - close) / rng * 100.0 <= closeNearHighPct)
mou_breakout = useBreakoutRoute and baseTrendOK and breakConfirm and bullBreak and bigBodyOK and closeNearHighOK and volumeStrongOK and macdBreakOK
mou_pullback = baseTrendOK and volumeMouOK and candleOK and macdMouOK and pullbackRouteOK
mou = mou_pullback or mou_breakout
// =========================
// KAKU (Strict): 8条件 + 最終三点
// =========================
cond1 = emaUpS and emaUpM and emaUpL
cond2 = goldenOrder
cond3 = above26_2days
cond4 = macdGCAboveZero
cond5 = volumeMouOK
cond6 = candleOK
cond7 = pullbackOK
cond8 = pullbackRouteOK
all8_strict = cond1 and cond2 and cond3 and cond4 and cond5 and cond6 and cond7 and cond8
final3 = pinbar and macdGCAboveZero and volumeStrongOK
kaku = all8_strict and final3
// =========================
// Entry (strategy)
// =========================
entrySignal = entryMode == "KAKU only" ? kaku : (mou or kaku)
canEnter = strategy.position_size == 0
newEntryKaku = canEnter and kaku and entrySignal
newEntryMouB = canEnter and (not kaku) and mou_breakout and entrySignal
newEntryMou = canEnter and (not kaku) and mou_pullback and entrySignal
// --- Publish Assist（保険エントリー） ---
// 条件が厳しすぎて「トレード0件」だと投稿時に警告が出る。
// closedtradesが0の間だけ、軽いEMAクロスで1回だけ拾う（その後は沈黙）。
assistFast = ta.ema(close, 5)
assistSlow = ta.ema(close, 20)
assistEntry = publishAssist and strategy.closedtrades == 0 and canEnter and ta.crossover(assistFast, assistSlow)
// 実エントリー
if newEntryKaku or newEntryMouB or newEntryMou or assistEntry
strategy.entry("LONG", strategy.long)
// ラベル（視認）
if showMouLabels and newEntryMou
label.new(bar_index, low, "猛(IN)", style=label.style_label_up, color=color.new(color.lime, 0), textcolor=color.black)
if showMouLabels and newEntryMouB
label.new(bar_index, low, "猛B(IN)", style=label.style_label_up, color=color.new(color.lime, 0), textcolor=color.black)
if showKakuLabels and newEntryKaku
label.new(bar_index, low, "確(IN)", style=label.style_label_up, color=color.new(color.yellow, 0), textcolor=color.black)
if assistEntry
label.new(bar_index, low, "ASSIST(IN)", style=label.style_label_up, color=color.new(color.aqua, 0), textcolor=color.black)
// =========================
// Exit (TP/SL + 強制クローズ)
// =========================
inPos = strategy.position_size > 0
tpPx = inPos ? strategy.position_avg_price * (1.0 + tpPct/100.0) : na
slPx = inPos ? strategy.position_avg_price * (1.0 - slPct/100.0) : na
if enableTPSL
strategy.exit("TP/SL", from_entry="LONG", limit=tpPx, stop=slPx)
// 最大保有バーで強制決済（これが「レポート無し」回避の最後の保険）
var int entryBar = na
if strategy.position_size > 0 and strategy.position_size == 0
entryBar := bar_index
if strategy.position_size == 0
entryBar := na
forceClose = inPos and not na(entryBar) and (bar_index - entryBar >= maxHoldBars)
if forceClose
strategy.close("LONG")
// =========================
// 利確/損切/強制クローズのラベル
// =========================
closedThisBar = (strategy.position_size > 0) and (strategy.position_size == 0)
avgPrev = strategy.position_avg_price
tpPrev = avgPrev * (1.0 + tpPct/100.0)
slPrev = avgPrev * (1.0 - slPct/100.0)
hitTP = closedThisBar and high >= tpPrev
hitSL = closedThisBar and low <= slPrev
// 同一足TP/SL両方は厳密に判断できないので、表示は「TP優先」で簡略（投稿ギリギリ版）
if hitTP
label.new(bar_index, high, "利確", style=label.style_label_down, color=color.new(color.lime, 0), textcolor=color.black)
else if hitSL
label.new(bar_index, low, "損切", style=label.style_label_up, color=color.new(color.red, 0), textcolor=color.white)
else if closedThisBar and forceClose
label.new(bar_index, close, "時間決済", style=label.style_label_left, color=color.new(color.gray, 0), textcolor=color.white)
// =========================
// Signals (猛/猛B/確)
// =========================
plotshape(showMouLabels and mou_pullback and not kaku, title="MOU_PULLBACK", style=shape.labelup, text="猛",
color=color.new(color.lime, 0), textcolor=color.black, location=lblLoc, size=size.tiny)
plotshape(showMouLabels and mou_breakout and not kaku, title="MOU_BREAKOUT", style=shape.labelup, text="猛B",
color=color.new(color.lime, 0), textcolor=color.black, location=lblLoc, size=size.tiny)
plotshape(showKakuLabels and kaku, title="KAKU", style=shape.labelup, text="確",
color=color.new(color.yellow, 0), textcolor=color.black, location=lblLoc, size=size.small)
// =========================
// Alerts
// =========================
alertcondition(mou, title="MNO_MOU", message="MNO: MOU triggered")
alertcondition(mou_breakout, title="MNO_MOU_BREAKOUT", message="MNO: MOU Breakout triggered")
alertcondition(mou_pullback, title="MNO_MOU_PULLBACK", message="MNO: MOU Pullback triggered")
alertcondition(kaku, title="MNO_KAKU", message="MNO: KAKU triggered")
alertcondition(assistEntry, title="MNO_ASSIST_ENTRY", message="MNO: ASSIST ENTRY (publish safety)")
// =========================
// Status label（最終足に必ず表示）
// =========================
var label status = na
if showStatusLbl and barstate.islast
label.delete(status)
statusTxt =
"MNO RUNNING\n" +
"ClosedTrades: " + str.tostring(strategy.closedtrades) + "\n" +
"BaseTrend: " + (baseTrendOK ? "OK" : "NO") + "\n" +
"MOU: " + (mou ? "YES" : "no") + " (猛=" + (mou_pullback ? "Y" : "n") + " / 猛B=" + (mou_breakout ? "Y" : "n") + ")\n" +
"KAKU: " + (kaku ? "YES" : "no") + "\n" +
"VolRatio: " + (na(volRatio) ? "na" : str.tostring(volRatio, format.mintick)) + "\n" +
"Pull%: " + (na(pullbackPct) ? "na" : str.tostring(pullbackPct, format.mintick)) + "\n" +
"Pos: " + (inPos ? "IN" : "OUT")
status := label.new(bar_index, high, statusTxt, style=label.style_label_left, textcolor=color.white, color=color.new(color.black, 0))
// =========================
// Debug table（最終足のみ）
// =========================
var table t = table.new(position.top_right, 2, 14, border_width=1, border_color=color.new(color.white, 60))
fRow(_name, _cond, _r) =>
bg = _cond ? color.new(color.lime, 70) : color.new(color.red, 80)
tx = _cond ? "OK" : "NO"
table.cell(t, 0, _r, _name, text_color=color.white, bgcolor=color.new(color.black, 0))
table.cell(t, 1, _r, tx, text_color=color.white, bgcolor=bg)
if showDebugTbl and barstate.islast
table.cell(t, 0, 0, "MNO Debug", text_color=color.white, bgcolor=color.new(color.black, 0))
table.cell(t, 1, 0, "", text_color=color.white, bgcolor=color.new(color.black, 0))
fRow("BaseTrend", baseTrendOK, 1)
fRow("MOU Pullback", mou_pullback, 2)
fRow("MOU Breakout", mou_breakout, 3)
fRow("Break confirm", breakConfirm, 4)
fRow("Break big body", bigBodyOK, 5)
fRow("Break close high", closeNearHighOK, 6)
fRow("Break vol strong", volumeStrongOK, 7)
fRow("Break MACD", macdBreakOK, 8)
fRow("KAKU all8", all8_strict, 9)
fRow("KAKU final3", final3, 10)
fRow("AssistEntry", assistEntry, 11)
fRow("ClosedTrades>0", strategy.closedtrades > 0, 12)
Density Zones (GM Crossing Clusters) + QHO Spin FlipsINDICATOR NAME
Density Zones (GM Crossing Clusters) + QHO Spin Flips
OVERVIEW
This indicator combines two complementary ideas into a single overlay: *this combines my earlier Geometric Mean Indicator with the Quantum Harmonic Oscillator (Overlay) with additional enhancements*
1) Density Zones (GM Crossing Clusters)
A “Density Zone” is detected when price repeatedly crosses a Geometric Mean equilibrium line (GM) within a rolling lookback window. Conceptually, this identifies regions where the market is repeatedly “snapping” across an equilibrium boundary—high churn, high decision pressure, and repeated re-selection of direction.
2) QHO Spin Flips (Regression-Residual σ Breaches)
A “Spin Flip” is detected when price deviates beyond a configurable σ-threshold (κ) from a regression-based equilibrium, using normalized residuals. Conceptually, this marks excursions into extreme states (decoherence / expansion), which often precede a reversion toward equilibrium and/or a regime re-scaling.
These two systems are related but not identical:
- Density Zones identify where equilibrium crossings cluster (a “singularity”/anchor behavior around GM).
- Spin Flips identify when price exceeds statistically extreme displacement from the regression equilibrium (LSR), indicating expansion beyond typical variance.
CORE CONCEPTS AND FORMULAS
SECTION A — GEOMETRIC MEAN EQUILIBRIUM (GM)
We define two moving averages:
(1) MA1_t = SMA(close_t, L1)
(2) MA2_t = SMA(close_t, L2)
We define the equilibrium anchor as the geometric mean of MA1 and MA2:
(3) GM_t = sqrt( MA1_t * MA2_t )
This GM line acts as an equilibrium boundary. Repeated crossings are interpreted as high “equilibrium churn.”
SECTION B — CROSS EVENTS (UP/DOWN)
A “cross event” is registered when the sign of (close - GM) changes:
Define a sign function s_t:
(4) s_t =
+1 if close_t > GM_t
-1 if close_t < GM_t
s_{t-1} if close_t == GM_t (tie-breaker to avoid false flips)
Then define the crossing event indicator:
(5) crossEvent_t = 1 if s_t != s_{t-1}
0 otherwise
Additionally, the indicator plots explicit cross markers:
- Cross Above GM: crossover(close, GM)
- Cross Below GM: crossunder(close, GM)
These provide directional visual cues and match the original Geometric Mean Indicator behavior.
SECTION C — DENSITY MEASURE (CROSSING CLUSTER COUNT)
A Density Zone is based on the number of cross events occurring in the last W bars:
(6) D_t = Σ_{i=0..W-1} crossEvent_{t-i}
This is a “crossing density” score: how many times price has toggled across GM recently.
The script implements this efficiently using a cumulative sum identity:
Let x_t = crossEvent_t.
(7) cumX_t = Σ_{j=0..t} x_j
Then:
(8) D_t = cumX_t - cumX_{t-W} (for t >= W)
cumX_t (for t < W)
SECTION D — DENSITY ZONE TRIGGER
We define a Density Zone state:
(9) isDZ_t = ( D_t >= θ )
where:
- θ (theta) is the user-selected crossing threshold.
Zone edges:
(10) dzStart_t = isDZ_t AND NOT isDZ_{t-1}
(11) dzEnd_t = NOT isDZ_t AND isDZ_{t-1}
SECTION E — DENSITY ZONE BOUNDS
While inside a Density Zone, we track the running high/low to display zone bounds:
(12) dzHi_t = max(dzHi_{t-1}, high_t) if isDZ_t
(13) dzLo_t = min(dzLo_{t-1}, low_t) if isDZ_t
On dzStart:
(14) dzHi_t := high_t
(15) dzLo_t := low_t
Outside zones, bounds are reset to NA.
These bounds visually bracket the “singularity span” (the churn envelope) during each density episode.
SECTION F — QHO EQUILIBRIUM (REGRESSION CENTERLINE)
Define the regression equilibrium (LSR):
(16) m_t = linreg(close_t, L, 0)
This is the “centerline” the QHO system uses as equilibrium.
SECTION G — RESIDUAL AND σ (FIELD WIDTH)
Residual:
(17) r_t = close_t - m_t
Rolling standard deviation of residuals:
(18) σ_t = stdev(r_t, L)
This σ_t is the local volatility/width of the residual field around the regression equilibrium.
SECTION H — NORMALIZED DISPLACEMENT AND SPIN FLIP
Define the standardized displacement:
(19) Y_t = (close_t - m_t) / σ_t
(If σ_t = 0, the script safely treats Y_t = 0.)
Spin Flip trigger uses a user threshold κ:
(20) spinFlip_t = ( |Y_t| > κ )
Directional spin flips:
(21) spinUp_t = ( Y_t > +κ )
(22) spinDn_t = ( Y_t < -κ )
The default κ=3.0 corresponds to “3σ excursions,” which are statistically extreme under a normal residual assumption (even though real markets are not perfectly normal).
SECTION I — QHO BANDS (OPTIONAL VISUALIZATION)
The indicator optionally draws the standard σ-bands around the regression equilibrium:
(23) 1σ bands: m_t ± 1·σ_t
(24) 2σ bands: m_t ± 2·σ_t
(25) 3σ bands: m_t ± 3·σ_t
These provide immediate context for the Spin Flip events.
WHAT YOU SEE ON THE CHART
1) MA1 / MA2 / GM lines (optional)
- MA1 (blue), MA2 (red), GM (green).
- GM is the equilibrium anchor for Density Zones and cross markers.
2) GM Cross Markers (optional)
- “GM↑” label markers appear on bars where close crosses above GM.
- “GM↓” label markers appear on bars where close crosses below GM.
3) Density Zone Shading (optional)
- Background shading appears while isDZ_t = true.
- This is the period where the crossing density D_t is above θ.
4) Density Zone High/Low Bounds (optional)
- Two lines (dzHi / dzLo) are drawn only while in-zone.
- These bounds bracket the full churn envelope during the density episode.
5) QHO Bands (optional)
- 1σ, 2σ, 3σ shaded zones around regression equilibrium.
- These visualize the current variance field.
6) Regression Equilibrium (LSR Centerline)
- The white centerline is the regression equilibrium m_t.
7) Spin Flip Markers
- A circle is plotted when |Y_t| > κ (beyond your chosen σ-threshold).
- Marker size is user-controlled (tiny → huge).
HOW TO USE IT
Step 1 — Pick the equilibrium anchor (GM)
- L1 and L2 define MA1 and MA2.
- GM = sqrt(MA1 * MA2) becomes your equilibrium boundary.
Typical choices:
- Faster equilibrium: L1=20, L2=50 (default-like).
- Slower equilibrium: L1=50, L2=200 (macro anchor).
Interpretation:
- GM acts like a “center of mass” between two moving averages.
- Crosses show when price flips from one side of equilibrium to the other.
Step 2 — Tune Density Zones (W and θ)
- W controls the time window measured (how far back you count crossings).
- θ controls how many crossings qualify as a “density/singularity episode.”
Guideline:
- Larger W = slower, broader density detection.
- Higher θ = only the most intense churn is labeled as a Density Zone.
Interpretation:
- A Density Zone is not “bullish” or “bearish” by itself.
- It is a condition: repeated equilibrium toggling (high churn / high compression).
- These often precede expansions, but direction is not implied by the zone alone.
Step 3 — Tune the QHO spin flip sensitivity (L and κ)
- L controls regression memory and σ estimation length.
- κ controls how extreme the displacement must be to trigger a spin flip.
Guideline:
- Smaller L = more reactive centerline and σ.
- Larger L = smoother, slower “field” definition.
- κ=3.0 = strong extreme filter.
- κ=2.0 = more frequent flips.
Interpretation:
- Spin flips mark when price exits the “normal” residual field.
- In your model language: a moment of decoherence/expansion that is statistically extreme relative to recent equilibrium.
Step 4 — Read the combined behavior (your key thesis)
A) Density Zone forms (GM churn clusters):
- Market repeatedly crosses equilibrium (GM), compressing into a bounded churn envelope.
- dzHi/dzLo show the envelope range.
B) Expansion occurs:
- Price can release away from the density envelope (up or down).
- If it expands far enough relative to regression equilibrium, a Spin Flip triggers (|Y| > κ).
C) Re-coherence:
- After a spin flip, price often returns toward equilibrium structures:
- toward the regression centerline m_t
- and/or back toward the density envelope (dzHi/dzLo) depending on regime behavior.
- The indicator does not guarantee return, but it highlights the condition where return-to-field is statistically likely in many regimes.
IMPORTANT NOTES / DISCLAIMERS
- This indicator is an analytical overlay. It does not provide financial advice.
- Density Zones are condition states derived from GM crossing frequency; they do not predict direction.
- Spin Flips are statistical excursions based on regression residuals and rolling σ; markets have fat tails and non-stationarity, so σ-based thresholds are contextual, not absolute.
- All parameters (L1, L2, W, θ, L, κ) should be tuned per asset, timeframe, and volatility regime.
PARAMETER SUMMARY
Geometric Mean / Density Zones:
- L1: MA1 length
- L2: MA2 length
- GM_t = sqrt(SMA(L1)*SMA(L2))
- W: crossing-count lookback window
- θ: crossing density threshold
- D_t = Σ crossEvent_{t-i} over W
- isDZ_t = (D_t >= θ)
- dzHi/dzLo track envelope bounds while isDZ is true
QHO / Spin Flips:
- L: regression + residual σ length
- m_t = linreg(close, L, 0)
- r_t = close_t - m_t
- σ_t = stdev(r_t, L)
- Y_t = r_t / σ_t
- spinFlip_t = (|Y_t| > κ)
Visual Controls:
- toggles for GM lines, cross markers, zone shading, bounds, QHO bands
- marker size options for GM crosses and spin flips
ALERTS INCLUDED
- Density Zone START / END
- Spin Flip UP / DOWN
- Cross Above GM / Cross Below GM
SUMMARY
This indicator treats the Geometric Mean as an equilibrium boundary and identifies “Density Zones” when price repeatedly crosses that equilibrium within a rolling window, forming a bounded churn envelope (dzHi/dzLo). It also models a regression-based equilibrium field and triggers “Spin Flips” when price makes statistically extreme σ-excursions from that field. Used together, Density Zones highlight compression/decision regions (equilibrium churn), while Spin Flips highlight extreme expansion states (σ-breaches), allowing the user to visualize how price compresses around equilibrium, releases outward, and often re-stabilizes around equilibrium structures over time.
PEAD ScreenerPEAD Screener - Post-Earnings Announcement Drift Scanner
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WHY EARNINGS ANNOUNCEMENTS CREATE OPPORTUNITY
═══════════════════════════════════════════════════════════════
The days immediately following an earnings announcement are among the noisiest periods for any stock. Within hours, the market must digest new information about a company's profits, revenue, and future outlook. Analysts scramble to update their models. Institutions rebalance positions. Retail traders react to headlines.
This chaos creates a well-documented phenomenon called Post-Earnings Announcement Drift (PEAD): stocks that beat expectations tend to keep rising, while those that miss tend to keep falling - often for weeks after the initial announcement. Academic research has confirmed this pattern persists across decades and markets.
But not every earnings surprise is equal. A company that beats estimates by 5 cents might move very differently than one that beats by 5 cents with unusually high volume, or one where both earnings AND revenue exceeded expectations. Raw numbers alone don't tell the full story.
═══════════════════════════════════════════════════════════════
HOW "STANDARDIZED UNEXPECTED" METRICS CUT THROUGH THE NOISE
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This screener uses a statistical technique to measure how "surprising" a result truly is - not just whether it beat or missed, but how unusual that beat or miss was compared to the company's own history.
The core idea: convert raw surprises into Z-scores.
A Z-score answers the question: "How many standard deviations away from normal is this result?"
- A Z-score of 0 means the result was exactly average
- A Z-score of +2 means the result was unusually high (better than ~95% of historical results)
- A Z-score of -2 means the result was unusually low
By standardizing surprises this way, we can compare apples to apples. A small-cap biotech's $0.02 beat might actually be more significant than a mega-cap's $0.50 beat, once we account for each company's typical variability.
This screener applies this standardization to three dimensions: earnings (SUE), revenue (SURGE), and volume (SUV).
═══════════════════════════════════════════════════════════════
THE 9 SCREENING CRITERIA
═══════════════════════════════════════════════════════════════
─────────────────────────────────────────
1. SUE (Standardized Unexpected Earnings)
─────────────────────────────────────────
WHAT IT IS:
SUE measures how surprising an earnings result was, adjusted for the company's historical forecast accuracy.
Calculation: Take the earnings surprise (actual EPS minus analyst estimate), then divide by the standard deviation of past forecast errors. This uses a rolling window of the last 8 quarters by default.
Formula: SUE = (Actual EPS - Estimated EPS) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SUE > +2.0: Strongly positive surprise - earnings beat expectations by an unusually large margin. These stocks often continue drifting higher.
- SUE between 0 and +2.0: Modest positive surprise - beat expectations, but within normal range.
- SUE between -2.0 and 0: Modest negative surprise - missed expectations, but within normal range.
- SUE < -2.0: Strongly negative surprise - significant miss. These stocks often continue drifting lower.
For long positions, look for SUE values above +2.0, ideally combined with positive SURGE.
─────────────────────────────────────────
2. SURGE (Standardized Unexpected Revenue)
─────────────────────────────────────────
WHAT IT IS:
SURGE applies the same standardization technique to revenue surprises. While earnings can be manipulated through accounting choices, revenue is harder to fake - it represents actual sales.
Calculation: Take the revenue surprise (actual revenue minus analyst estimate), then divide by the standard deviation of past revenue forecast errors.
Formula: SURGE = (Actual Revenue - Estimated Revenue) / Standard Deviation of Past Errors
HOW TO INTERPRET:
- SURGE > +1.5: Strongly positive revenue surprise - the company sold significantly more than expected.
- SURGE between 0 and +1.5: Modest positive surprise.
- SURGE < 0: Revenue missed expectations.
The most powerful signals occur when BOTH SUE and SURGE are positive and elevated (ideally SUE > 2.0 AND SURGE > 1.5). This indicates the company beat on both profitability AND top-line growth - a much stronger signal than either alone.
When SUE and SURGE diverge significantly (e.g., high SUE but negative SURGE), treat with caution - the earnings beat may have come from cost-cutting rather than genuine growth.
─────────────────────────────────────────
3. SUV (Standardized Unexpected Volume)
─────────────────────────────────────────
WHAT IT IS:
SUV detects unusual trading volume after accounting for how volatile the stock is. More volatile stocks naturally have higher volume, so raw volume comparisons can be misleading.
Calculation: This uses regression analysis to model the expected relationship between price volatility and volume. The "unexpected" volume is the residual - how much actual volume deviated from what the model predicted. This residual is then standardized into a Z-score.
In plain terms: SUV asks "Given how much this stock typically moves, is today's volume unusually high or low?"
HOW TO INTERPRET:
- SUV > +2.0: Exceptionally high volume relative to the stock's volatility. This often signals institutional activity - big players moving in or out.
- SUV between +1.0 and +2.0: Elevated volume - above normal interest.
- SUV between -1.0 and +1.0: Normal volume range.
- SUV < -1.0: Unusually quiet - less activity than expected.
High SUV combined with positive price movement suggests accumulation (buying). High SUV combined with negative price movement suggests distribution (selling).
─────────────────────────────────────────
4. % From D0 Close
─────────────────────────────────────────
WHAT IT IS:
This measures how far the current price has moved from the closing price on its initial earnings reaction day (D0). The "reaction day" is the first trading day that fully reflects the earnings news - typically the day after an after-hours announcement, or the announcement day itself for pre-market releases.
Calculation: ((Current Price - D0 Close) / D0 Close) × 100
HOW TO INTERPRET:
- Positive values: Stock has gained ground since earnings. The higher the percentage, the stronger the post-earnings drift.
- 0% to +5%: Modest positive drift - earnings were received well but momentum is limited.
- +5% to +15%: Strong drift - buyers continue accumulating.
- > +15%: Exceptional drift - significant institutional interest likely.
- Negative values: Stock has given back gains or extended losses since earnings. May indicate the initial reaction was overdone, or that sentiment is deteriorating.
This metric is most meaningful within the first 5-20 trading days after earnings. Extended drift (maintaining gains over 2+ weeks) is a stronger signal than a quick spike that fades.
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5. # Pocket Pivots
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WHAT IT IS:
Pocket Pivots are a volume-based pattern developed by Chris Kacher and Gil Morales. They identify days where institutional buyers are likely accumulating shares without causing obvious breakouts.
Calculation: A Pocket Pivot occurs when:
- The stock closes higher than it opened (up day)
- The stock closes higher than the previous day's close
- Today's volume exceeds the highest down-day volume of the prior 10 trading sessions
The screener counts how many Pocket Pivots have occurred since the earnings announcement.
HOW TO INTERPRET:
- 0 Pocket Pivots: No detected institutional accumulation patterns since earnings.
- 1-2 Pocket Pivots: Some institutional buying interest - worth monitoring.
- 3+ Pocket Pivots: Strong accumulation signal - institutions appear to be building positions.
Pocket Pivots are most significant when they occur:
- Immediately following earnings announcements
- Near moving average support (10-day, 21-day, or 50-day)
- On above-average volume
- After a period of price consolidation
Multiple Pocket Pivots in a short period suggest sustained institutional demand, not just a one-day event.
─────────────────────────────────────────
6. ADX/DI (Trend Strength and Direction)
─────────────────────────────────────────
WHAT IT IS:
ADX (Average Directional Index) measures trend strength regardless of direction. DI (Directional Indicator) shows whether the trend is bullish or bearish.
Calculation: ADX uses a 14-period lookback to measure how directional (trending) price movement is. Values range from 0 to 100. The +DI and -DI components compare upward and downward movement.
The screener shows:
- ADX value (trend strength)
- Direction indicator: "+" for bullish (price trending up), "-" for bearish (price trending down)
HOW TO INTERPRET:
- ADX < 20: Weak trend - the stock is moving sideways, choppy. Not ideal for momentum trading.
- ADX 20-25: Trend is emerging - potentially starting a directional move.
- ADX 25-40: Strong trend - clear directional movement. Good for momentum plays.
- ADX > 40: Very strong trend - powerful move in progress, but may be extended.
The direction indicator (+/-) tells you which way:
- "25+" means ADX of 25 with bullish direction (uptrend)
- "25-" means ADX of 25 with bearish direction (downtrend)
For post-earnings plays, ideal setups show ADX rising above 25 with positive direction, confirming the earnings reaction is developing into a sustained trend rather than a one-day spike.
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7. Institutional Buying PASS
─────────────────────────────────────────
WHAT IT IS:
This proprietary composite indicator detects patterns consistent with institutional accumulation at three stages after earnings:
EARLY (Days 0-4): Looks for "large block" buying on the earnings reaction day (exceptionally high volume with a close in the upper half of the day's range) combined with follow-through buying on the next day.
MID (Days 5-9): Checks for sustained elevated volume (averaging 1.5x the 20-day average) combined with positive drift and consistent upward price movement (more up days than down days).
LATE (Days 10+): Detects either visible accumulation (positive drift with high volume) OR stealth accumulation (positive drift with unusually LOW volume - suggesting smart money is quietly building positions without attracting attention).
HOW TO INTERPRET:
- Check mark/value of '1': Institutional buying pattern detected. The stock shows characteristics consistent with large players accumulating shares.
- X mark/value of '0': No institutional buying pattern detected. This doesn't mean institutions aren't buying - just that the typical footprints aren't visible.
A passing grade here adds conviction to other bullish signals. Institutions have research teams, information advantages, and long time horizons. When their footprints appear in the data, it often precedes sustained moves.
Important: This is a pattern detection tool, not a guarantee. Always combine with other analysis.
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8. Strong ATR Drift PASS
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WHAT IT IS:
This measures whether the stock has drifted significantly relative to its own volatility. Instead of asking "did it move 10%?", it asks "did it move more than 1.5 ATRs?"
ATR (Average True Range) measures a stock's typical daily movement. A volatile stock might move 5% daily, while a stable stock might move 0.5%. Using ATR normalizes for this difference.
Calculation:
ATR Drift = (Current Close - D0 Close) / D0 ATR in dollars
The indicator passes when ATR Drift exceeds 1.5 AND at least 5 days have passed since earnings.
HOW TO INTERPRET:
- Check mark/value of '1': The stock has drifted more than 1.5 times its average daily range since earnings - a statistically significant move that suggests genuine momentum, not just noise.
- X mark/value of '0': The drift (if any) is within normal volatility bounds - could just be random fluctuation.
Why wait 5 days? The immediate post-earnings reaction (days 0-2) often includes gap fills and noise. By day 5, if the stock is still extended beyond 1.5 ATRs from the earnings close, it suggests real buying pressure, not just a reflexive gap.
A passing grade here helps filter out stocks that "beat earnings" but haven't actually moved meaningfully. It focuses attention on stocks where the market is voting with real capital.
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9. Days Since D0
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WHAT IT IS:
Simply counts the number of trading days since the earnings reaction day (D0).
HOW TO INTERPRET:
- Days 0-5 (Green): Fresh earnings - the information is new, institutional repositioning is active, and momentum trades are most potent. This is the "sweet spot" for PEAD strategies.
- Days 6-10 (Neutral): Mid-period - some edge remains but diminishing. Good for adding to winning positions, less ideal for new entries.
- Days 11+ (Red): Extended period - most of the post-earnings drift has typically played out. Higher risk that momentum fades or reverses.
Research shows PEAD effects are strongest in the first 5-10 days after earnings, then decay. Beyond 20-30 days, the informational advantage of the earnings surprise is largely priced in.
Use this to prioritize: focus on stocks with strong signals that are still in the early window, and be more selective about entries as days accumulate.
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PUTTING IT ALL TOGETHER
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You can use this screener in the chart view or in the Screener.
One combination of the above filters to develop a shortlist of positive drift candidates may be:
- SUE > 2.0 (significant earnings beat)
- SURGE > 1.5 (significant revenue beat)
- Positive % From D0 Close (price confirming the good news)
- Institutional Buying PASS (big players accumulating)
- Strong ATR Drift PASS (statistically significant movement)
- Days Since D0 < 10 (still in the active drift window)
No single indicator is sufficient. The power comes from convergence - when multiple independent measures all point the same direction.
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SETTINGS
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Key adjustable parameters:
- SUE Method: "Analyst-based" uses consensus estimates; "Time-series" uses year-over-year comparison
- Window Size: Number of quarters used for standardization (default: 8)
- ATR Drift Threshold: Minimum ATR multiple for "strong" classification (default: 1.5)
- Institutional Buying thresholds: Adjustable volume and CLV parameters
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DISCLAIMER
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This screener is a research tool, not financial advice. Past patterns do not guarantee future results. Always conduct your own due diligence and manage risk appropriately. Post-earnings trading involves significant uncertainty and volatility. The 'SUE' in this indicator does not represent a real person; any similarity to actual Sue's (or Susans for that matter) living or dead is quite frankly ridiculous, not to mention coincidental.
