Point and Figure (PnF) RSIThis is live and non-repainting Point and Figure Chart RSI tool. The script has it’s own P&F engine and not using integrated function of Trading View.
Point and Figure method is over 150 years old. It consist of columns that represent filtered price movements. Time is not a factor on P&F chart but as you can see with this script P&F chart created on time chart.
P&F chart provide several advantages, some of them are filtering insignificant price movements and noise, focusing on important price movements and making support/resistance levels much easier to identify.
P&F RSI is calculated and shown by using its own P&F engine.
If you are new to Point & Figure Chart then you better get some information about it before using this tool. There are very good web sites and books. Please PM me if you need help about resources.
Options in the Script
Box size is one of the most important part of Point and Figure Charting. Chart price movement sensitivity is determined by the Point and Figure scale. Large box sizes see little movement across a specific price region, small box sizes see greater price movement on P&F chart. There are four different box scaling with this tool: Traditional, Percentage, Dynamic (ATR), or User-Defined
4 different methods for Box size can be used in this tool.
User Defined: The box size is set by user. A larger box size will result in more filtered price movements and fewer reversals. A smaller box size will result in less filtered price movements and more reversals.
ATR: Box size is dynamically calculated by using ATR, default period is 20.
Percentage: uses box sizes that are a fixed percentage of the stock's price. If percentage is 1 and stock’s price is $100 then box size will be $1
Traditional: uses a predefined table of price ranges to determine what the box size should be.
Price Range Box Size
Under 0.25 0.0625
0.25 to 1.00 0.125
1.00 to 5.00 0.25
5.00 to 20.00 0.50
20.00 to 100 1.0
100 to 200 2.0
200 to 500 4.0
500 to 1000 5.0
1000 to 25000 50.0
25000 and up 500.0
Default value is “ATR”, you may use one of these scaling method that suits your trading strategy.
If ATR or Percentage is chosen then there is rounding algorithm according to mintick value of the security. For example if mintick value is 0.001 and box size (ATR/Percentage) is 0.00124 then box size becomes 0.001.
And also while using dynamic box size (ATR or Percentage), box size changes only when closing price changed.
Reversal : It is the number of boxes required to change from a column of Xs to a column of Os or from a column of Os to a column of Xs. Default value is 3 (most used). For example if you choose reversal = 2 then you get the chart similar to Renko chart.
Source: Closing price or High-Low prices can be chosen as data source for P&F charting.
you can use PNF type RSI or RENKO type RSI.
What is the difference between them?
While calculating PNF type RSI, the script checks last X/O column's closing price but when using RENKO type RSI the scipt calculates RSI on every price changes according to number of boxes. and also with RENKO type RSI, calculation is made for each boxes on price changes.
Important note if you use this PNF script with reversal = 2 then you get RENKO chart. So, with this RENKO chart better to use RENKO type RSI ;)
Tìm kiếm tập lệnh với "美股标普500"
Point and Figure (PnF) ChartThis is live and non-repainting Point and Figure Charting tool. The tool has it’s own P&F engine and not using integrated function of Trading View.
Point and Figure method is over 150 years old. It consist of columns that represent filtered price movements. Time is not a factor on P&F chart but as you can see with this script P&F chart created on time chart.
P&F chart provide several advantages, some of them are filtering insignificant price movements and noise, focusing on important price movements and making support/resistance levels much easier to identify.
If you are new to Point & Figure Chart then you better get some information about it before using this tool. There are very good web sites and books. Please PM me if you need help about resources.
Options in the Script
Box size is one of the most important part of Point and Figure Charting. Chart price movement sensitivity is determined by the Point and Figure scale. Large box sizes see little movement across a specific price region, small box sizes see greater price movement on P&F chart. There are four different box scaling with this tool: Traditional, Percentage, Dynamic (ATR), or User-Defined
4 different methods for Box size can be used in this tool.
User Defined: The box size is set by user. A larger box size will result in more filtered price movements and fewer reversals. A smaller box size will result in less filtered price movements and more reversals.
ATR: Box size is dynamically calculated by using ATR, default period is 20.
Percentage: uses box sizes that are a fixed percentage of the stock's price. If percentage is 1 and stock’s price is $100 then box size will be $1
Traditional: uses a predefined table of price ranges to determine what the box size should be.
Price Range Box Size
Under 0.25 0.0625
0.25 to 1.00 0.125
1.00 to 5.00 0.25
5.00 to 20.00 0.50
20.00 to 100 1.0
100 to 200 2.0
200 to 500 4.0
500 to 1000 5.0
1000 to 25000 50.0
25000 and up 500.0
Default value is “ATR”, you may use one of these scaling method that suits your trading strategy.
If ATR or Percentage is chosen then there is rounding algorithm according to mintick value of the security. For example if mintick value is 0.001 and box size (ATR/Percentage) is 0.00124 then box size becomes 0.001.
And also while using dynamic box size (ATR or Percentage), box size changes only when closing price changed.
Reversal : It is the number of boxes required to change from a column of Xs to a column of Os or from a column of Os to a column of Xs. Default value is 3 (most used). For example if you choose reversal = 2 then you get the chart similar to Renko chart.
Source: Closing price or High-Low prices can be chosen as data source for P&F charting.
Chart Style: There are 3 options for chart style: “Candle”, “Area” or “Don’t show”.
As Area:
As Candle:
X/O Column Style: it can show all columns from opening price or only last Xs/Os.
Color Theme: different themes exist => Green/Red, Yellow/Blue, White/Yellow, Orange/Blue, Lime/Red, Blue/Red
Show Breakouts is the option to show Breakouts
This tool detects & shows following Breakouts:
Triple Top/Bottom,
Triple Top Ascending,
Triple Bottom Descending,
Simple Buy/Sell (Double Top/Bottom),
Simple Buy With Rising Bottom,
Simple Sell With Declining Top
Catapult bullish/bearish
Show Horizontal Count Targets: Finds the congestion or consolidation pattern and if there is breakout then it calculates the Target by using Horizontal Count method (based on the width of congestion pattern). It shows how many column exist on congestion area. There is no guarantee that prices will reach the target.
Show Vertical Count Targets: When Triple Top/Bottom Breakouts occured the script calculates the target by using Vertical Count Method (based on the length of the column). There is no guarantee that prices will reach the target.
For both methods there is auto target cancellation if price goes below congestion bottom or above congestion top.
trend is calculated by EMA of closing price of the P&F
Whipsaw protection:
Last options are “Show info panel” and Labeling Offset. Script shows current box size, reversal, and recommanded minimum and maximum box size. And also it shows the price level to reverse the column (Xs <-> Os) and the price level to add at least 1 more box to column. This is the option to put these labels 10, 20, 30, 50 or 100 bars away from the last bar. Labeling content and color change according to X/O column.
do not hesitate to comment.
Candlesticks ANN for Stock Markets TF : 1WHello, this script consists of training candlesticks with Artificial Neural Networks (ANN).
In addition to the first series, candlesticks' bodies and wicks were also introduced as training inputs.
The inputs are individually trained to find the relationship between the subsequent historical value of all candlestick values 1.(High,Low,Close,Open)
The outputs are adapted to the current values with a simple forecast code.
Once the OHLC value is found, the exponential moving averages of 5 and 20 periods are used.
Reminder : OHLC = (Open + High + Close + Low ) / 4
First version :
Script is designed for S&P 500 Indices,Funds,ETFs, especially S&P 500 Stocks,and for all liquid Stocks all around the World.
NOTE: This script is only suitable for 1W time-frame for Stocks.
The average training error rates are less than 5 per thousand for each candlestick variable. (Average Error < 0.005 )
I've just finished it and haven't tested it in detail.
So let's use it carefully as a supporter.
Best regards !
TNZ - Index above MA Use this indicator to filter stock selection based on the relevant index value being above the selected simple moving average.
For example, only buying the S+P 500 stock if the S+P 500 index value is above the 10 period moving average.
The time frame used is that displayed
Macroeconomic Artificial Neural Networks
This script was created by training 20 selected macroeconomic data to construct artificial neural networks on the S&P 500 index.
No technical analysis data were used.
The average error rate is 0.01.
In this respect, there is a strong relationship between the index and macroeconomic data.
Although it affects the whole world,I personally recommend using it under the following conditions: S&P 500 and related ETFs in 1W time-frame (TF = 1W SPX500USD, SP1!, SPY, SPX etc. )
Macroeconomic Parameters
Effective Federal Funds Rate (FEDFUNDS)
Initial Claims (ICSA)
Civilian Unemployment Rate (UNRATE)
10 Year Treasury Constant Maturity Rate (DGS10)
Gross Domestic Product , 1 Decimal (GDP)
Trade Weighted US Dollar Index : Major Currencies (DTWEXM)
Consumer Price Index For All Urban Consumers (CPIAUCSL)
M1 Money Stock (M1)
M2 Money Stock (M2)
2 - Year Treasury Constant Maturity Rate (DGS2)
30 Year Treasury Constant Maturity Rate (DGS30)
Industrial Production Index (INDPRO)
5-Year Treasury Constant Maturity Rate (FRED : DGS5)
Light Weight Vehicle Sales: Autos and Light Trucks (ALTSALES)
Civilian Employment Population Ratio (EMRATIO)
Capacity Utilization (TOTAL INDUSTRY) (TCU)
Average (Mean) Duration Of Unemployment (UEMPMEAN)
Manufacturing Employment Index (MAN_EMPL)
Manufacturers' New Orders (NEWORDER)
ISM Manufacturing Index (MAN : PMI)
Artificial Neural Network (ANN) Training Details :
Learning cycles: 16231
AutoSave cycles: 100
Grid
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 998
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Controls
Learning rate: 0.1000
Momentum: 0.8000 (Optimized)
Target error: 0.0100
Training error: 0.010000
NOTE : Alerts added . The red histogram represents the bear market and the green histogram represents the bull market.
Bars subject to region changes are shown as background colors. (Teal = Bull , Maroon = Bear Market )
I hope it will be useful in your studies and analysis, regards.
Damped Sine Wave Weighted FilterIntroduction
Remember that we can make filters by using convolution, that is summing the product between the input and the filter coefficients, the set of filter coefficients is sometime denoted "kernel", those coefficients can be a same value (simple moving average), a linear function (linearly weighted moving average), a gaussian function (gaussian filter), a polynomial function (lsma of degree p with p = order of the polynomial), you can make many types of kernels, note however that it is easy to fall into the redundancy trap.
Today a low-lag filter who weight the price with a damped sine wave is proposed, the filter characteristics are discussed below.
A Damped Sine Wave
A damped sine wave is a like a sine wave with the difference that the sine wave peak amplitude decay over time.
A damped sine wave
Used Kernel
We use a damped sine wave of period length as kernel.
The coefficients underweight older values which allow the filter to reduce lag.
Step Response
Because the filter has overshoot in the step response we can conclude that there are frequencies amplified in the passband, we could have reached to this conclusion by simply seeing the negative values in the kernel or the "zero-lag" effect on the closing price.
Enough ! We Want To See The Filter !
I should indeed stop bothering you with transient responses but its always good to see how the filter act on simpler signals before seeing it on the closing price. The filter has low-lag and can be used as input for other indicators
Filter with length = 100 as input for the rsi.
The bands trailing stop utility using rolling squared mean average error with length 500 using the filter of length 500 as input.
Approximating A Least Squares Moving Average
A least squares moving average has a linear kernel with certain values under 0, a lsma of length k can be approximated using the proposed filter using period p where p = k + k/4 .
Proposed filter (red) with length = 250 and lsma (blue) with length = 200.
Conclusions
The use of damping in filter design can provide extremely useful filters, in fact the ideal kernel, the sinc function, is also a damped sine wave.
VIX reversion-Buschi
English:
A significant intraday reversion (commonly used: 3 points) on a high (over 20 points) S&P 500 Volatility Index (VIX) can be a sign of a market bottom, because there is the assumption that some of the "big guys" liquidated their options / insurances because the worst is over.
This indicator shows these reversions (3 points as default) when the VIX was over 20 points. The character "R" is then shown directly over the daily column, the VIX need not to be loaded explicitly.
Deutsch:
Eine deutliche Intraday-Umkehr (3 Punkte im Normalfall) bei einem hohen (über 20 Punkte) S&P 500 Volatility Index (VIX) kann ein Zeichen für eine Bodenbildung im Markt sein, weil möglicherweise einige "große Jungs" ihre Optionen / Versicherungen auflösen, weil das schlimmste vorbei ist.
Dieser Indikator zeigt diese Umkehr (Standardwert: 3 Punkte), wenn der VIX vorher über 20 Punkte lag. Der Buchstabe "R" wird dabei direkt über dem Tagesbalken angezeigt, wobei der VIX nicht explizit geladen werden muss.
Relative Price StrengthThe strength of a stock relative to the S&P 500 is key part of most traders decision making process. Hence the default reference security is SPY, the most commonly trades S&P 500 ETF.
Most profitable traders buy stocks that are showing persistence intermediate strength verses the S&P as this has been shown to work. Hence the default period is 63 days or 3 months.
TICK Extremes IndicatorSimple TICK indicator, plots candles and HL2 line
Conditional green/red coloring for highs above 500, 900 and lows above 0, and for lows below -500, -900, and highs above 0
Probably best used for 1 - 5 min timeframes
Always open to suggestions if criteria needs tweaking or if something else would make it more useful or user-friendly!
Market direction and pullback based on S&P 500.A simple indicator based on www.swing-trade-stocks.com The link is also the guide for how to use it.
0 - nothing. If the indicator is showing 0 for a prolonged amount of time, it is likely the market is in "momentum mode" (referred to in the link above).
1 - indicates an uptrend based on SMA and EMA and also a place where a reversal to the upside is likely to occur. You should look only for long trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
-1 - indicates a downtrend based on SMA and EMA and also a place where a reversal to the downside is likely to occur. You should look only for short trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
Net XRP Margin PositionTotal XRP Longs minus XRP Shorts in order to give you the total outstanding XRP margin debt.
ie: If 500,000 XRP has been longed, and 400,000 XRP has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 XRP (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
Net DASH Margin PositionTotal DASH Longs minus DASH Shorts in order to give you the total outstanding DASH margin debt.
ie: If 500,000 DASH has been longed, and 400,000 DASH has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 DASH (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Net NEO Margin PositionTotal NEO Longs minus NEO Shorts in order to give you the total outstanding NEO margin debt.
ie: If 500,000 NEO has been longed, and 400,000 NEO has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 NEO (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project.
Like I wrote the last time - my goal is to create a new strategy everyday
for the rest of 2016 and post it here on TradingView.
I'm a complete beginner so this is my way of learning about coding strategies.
I'll give myself between 15 minutes and 2 hours to complete each creation.
This is basically a repetition of the first strategy I wrote - a Moving Average Crossover,
but I added a tiny thing.
I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time."
(source: )
My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility
and because of this missed one nice bull run and a very nice bear run.
So I added this single line: if time("60", "1000-1600") regarding when to take exits:
if time("60", "1000-1600")
strategy.exit("Close Long", "Long", profit=2000, loss=500)
strategy.exit("Close Short", "Short", profit=2000, loss=500)
Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually.
Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility.
When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily.
On the other hand I'll have to test this on various stocks .
Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs
to read on this topic is very welcome!
Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated!
/pbergden
indicator("MouNoOkite_InitialMove_Screener", overlay=true)//@version=5
indicator("猛の掟・初動スクリーナー（5EMA×MACD×出来高×ローソク）", overlay=true, max_labels_count=500)
// =========================
// 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")
volLookback = input.int(5, "出来高平均（日数）", minval=1)
volMinRatio = input.float(1.3, "出来高倍率(初動点灯)", step=0.1)
volStrong = input.float(1.5, "出来高倍率(本物初動)", step=0.1)
volMaxRatio = input.float(2.0, "出来高倍率(上限目安)", step=0.1)
wickBodyMult = input.float(2.0, "ピンバー判定: 下ヒゲ >= (実体×倍率)", step=0.1)
pivotLen = input.int(20, "直近高値/レジスタンス判定のLookback", minval=5)
pullMinPct = input.float(5.0, "押し目最小(%)", step=0.1)
pullMaxPct = input.float(15.0, "押し目最大(%)", step=0.1)
showDebug = input.bool(true, "デバッグ表示（条件チェック）")
// =========================
// EMA
// =========================
emaS = ta.ema(close, emaSLen)
emaM = ta.ema(close, emaMLen)
emaL = ta.ema(close, emaLLen)
plot(emaS, color=color.new(color.yellow, 0), title="EMA 5")
plot(emaM, color=color.new(color.blue, 0), title="EMA 13")
plot(emaL, color=color.new(color.orange, 0), title="EMA 26")
emaUpS = emaS > emaS
emaUpM = emaM > emaM
emaUpL = emaL > emaL
// 26EMA上に2日定着
above26_2days = close > emaL and close > emaL
// 黄金隊列
goldenOrder = emaS > emaM and emaM > emaL
// =========================
// MACD
// =========================
= ta.macd(close, macdFast, macdSlow, macdSignal)
// ヒストグラム縮小（マイナス圏で上向きの準備）も見たい場合の例
histShrinking = math.abs(macdHist) < math.abs(macdHist )
histUp = macdHist > macdHist
// ゼロライン上でGC（最終シグナル）
macdGCAboveZero = ta.crossover(macdLine, macdSig) and macdLine > 0 and macdSig > 0
// 参考：ゼロ直下で上昇方向（勢い準備）
macdRisingNearZero = (macdLine < 0) and (macdLine > macdLine ) and (math.abs(macdLine) <= math.abs(0.5))
// =========================
// Volume
// =========================
volMA = ta.sma(volume, volLookback)
volRatio = volMA > 0 ? (volume / volMA) : na
volumeOK = volRatio >= volMinRatio and volRatio <= volMaxRatio
volumeStrongOK = volRatio >= volStrong
// =========================
// Candle patterns
// =========================
body = math.abs(close - open)
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
// 長い下ヒゲ（ピンバー系）: 実体が小さく、下ヒゲが優位
pinbar = (lowerWick >= wickBodyMult * body) and (lowerWick > upperWick) and (close >= open)
// 陽線包み足（前日陰線を包む）
bullEngulf =
close > open and close < open and
close >= open and open <= close
// 5EMA・13EMA を貫く大陽線（勢い）
bigBull =
close > open and
open < emaM and close > emaS and
(body > ta.sma(body, 20)) // “相対的に大きい”目安
candleOK = pinbar or bullEngulf or bigBull
// =========================
// 押し目 (-5%〜-15%) & レジブレ後
// =========================
recentHigh = ta.highest(high, pivotLen)
pullbackPct = recentHigh > 0 ? (recentHigh - close) / recentHigh * 100.0 : na
pullbackOK = pullbackPct >= pullMinPct and pullbackPct <= pullMaxPct
// “レジスタンスブレイク”簡易定義：直近pivotLen高値を一度上抜いている
// → その後に押し目位置にいる（現在が押し目）
brokeResistance = ta.crossover(close, recentHigh ) or (close > recentHigh )
afterBreakPull = brokeResistance or brokeResistance or brokeResistance or brokeResistance or brokeResistance
breakThenPullOK = afterBreakPull and pullbackOK
// =========================
// 最終三点シグナル（ヒゲ × 出来高 × MACD）
// =========================
final3 = pinbar and macdGCAboveZero and volumeStrongOK
// =========================
// 猛の掟 8条件チェック（1つでも欠けたら「見送り」）
// =========================
// 1) 5EMA↑ 13EMA↑ 26EMA↑
cond1 = emaUpS and emaUpM and emaUpL
// 2) 5>13>26 黄金隊列
cond2 = goldenOrder
// 3) ローソク足が26EMA上に2日定着
cond3 = above26_2days
// 4) MACD(12,26,9) ゼロライン上でGC
cond4 = macdGCAboveZero
// 5) 出来高が直近5日平均の1.3〜2.0倍
cond5 = volumeOK
// 6) ピンバー or 包み足 or 大陽線
cond6 = candleOK
// 7) 押し目 -5〜15%
cond7 = pullbackOK
// 8) レジスタンスブレイク後の押し目
cond8 = breakThenPullOK
all8 = cond1 and cond2 and cond3 and cond4 and cond5 and cond6 and cond7 and cond8
// =========================
// 判定（2択のみ）
// =========================
isBuy = all8 and final3
decision = isBuy ? "買い" : "見送り"
// =========================
// 表示
// =========================
plotshape(isBuy, title="BUY", style=shape.labelup, text="買い", color=color.new(color.lime, 0), textcolor=color.black, location=location.belowbar, size=size.small)
plotshape((not isBuy) and all8, title="ALL8_OK_but_noFinal3", style=shape.labelup, text="8条件OK\n(最終3未)", color=color.new(color.yellow, 0), textcolor=color.black, location=location.belowbar, size=size.tiny)
// デバッグ（8項目チェック結果）
if showDebug and barstate.islast
var label dbg = na
label.delete(dbg)
txt =
"【8項目チェック】\n" +
"1 EMA全上向き: " + (cond1 ? "達成" : "未達") + "\n" +
"2 黄金隊列: " + (cond2 ? "達成" : "未達") + "\n" +
"3 26EMA上2日: " + (cond3 ? "達成" : "未達") + "\n" +
"4 MACDゼロ上GC: " + (cond4 ? "達成" : "未達") + "\n" +
"5 出来高1.3-2.0: "+ (cond5 ? "達成" : "未達") + "\n" +
"6 ローソク条件: " + (cond6 ? "達成" : "未達") + "\n" +
"7 押し目5-15%: " + (cond7 ? "達成" : "未達") + "\n" +
"8 ブレイク後押し目: " + (cond8 ? "達成" : "未達") + "\n\n" +
"最終三点(ヒゲ×出来高×MACD): " + (final3 ? "成立" : "未成立") + "\n" +
"判定: " + decision
dbg := label.new(bar_index, high, txt, style=label.style_label_left, textcolor=color.white, color=color.new(color.black, 0))
// アラート
alertcondition(isBuy, title="猛の掟 BUY", message="猛の掟: 買いシグナル（8条件＋最終三点）")
11-MA Institutional System (ATR+HTF Filters)11-MA Institutional Trading System Analysis.
This is a comprehensive Trading View Pine Script indicator that implements a sophisticated multi-timeframe moving average system with institutional-grade filters. Let me break down its key components and functionality:
🎯 Core Features
1. 11 Moving Average System. The indicator plots 11 customizable moving averages with different roles:
MA1-MA4 (5, 8, 10, 12): Fast-moving averages for short-term trends
MA5 (21 EMA): Short-term anchor - critical pivot point
MA6 (34 EMA): Intermediate support/resistance
MA7 (50 EMA): Medium-term bridge between short and long trends
MA8-MA9 (89, 100): Transition zone indicators
MA10-MA11 (150, 200): Long-term anchors for major trend identification
Each MA is fully customizable:
Type: SMA, EMA, WMA, TMA, RMA
Color, width, and enable/disable toggle
📊 Signal Generation System
Three Signal Tiers: Short-Term Signals (ST)
Trigger: MA8 (EMA 8) crossing MA21 (EMA 21)
Filters Applied:
✅ ATR-based post-cross confirmation (optional)
✅ Momentum confirmation (RSI > 50, MACD positive)
✅ Volume spike requirement
✅ HTF (Higher Timeframe) alignment
✅ Strong candle body ratio (>50%)
✅ Multi-MA confirmation (3+ MAs supporting direction)
✅ Price beyond MA21 with conviction
✅ Minimum bar spacing (prevents signal clustering)
✅ Consolidation filter
✅ Whipsaw protection (ATR-based price threshold)
Medium-Term Signals (MT)
Trigger: MA21 crossing MA50
Less strict filtering for swing trades
Major Signals
Golden Cross: MA50 crossing above MA200 (major bullish)
Death Cross: MA50 crossing below MA200 (major bearish)
🔍 Advanced Filtering System1. ATR-Based ConfirmationPrice must move > (ATR × 0.25) beyond the MA after crossover
This prevents false signals during low-volatility consolidation.2. Momentum Filters
RSI (14)
MACD Histogram
Rate of Change (ROC)
Composite momentum score (-3 to +3)
3. Volume Analysis
Volume spike detection (2x MA)
Volume classification: LOW, MED, HIGH, EXPL
Directional volume confirmation
4. Higher Timeframe Alignment
HTF1: 60-minute (default)
HTF2: 4-hour (optional)
HTF3: Daily (optional)
Signals only trigger when current TF aligns with HTF trend
5. Market Structure Detection
Break of Structure (BOS): Price breaking recent swing highs/lows
Order Blocks (OB): Institutional demand/supply zones
Fair Value Gaps (FVG): Imbalance areas for potential fills
📈 Comprehensive DashboardReal-Time Metrics Display: {scrollbar-width:none;-ms-overflow-style:none;-webkit-overflow-scrolling:touch;} ::-webkit-scrollbar{display:none}MetricDescriptionPriceCurrent close priceTimeframeCurrent chart timeframeSHORT/MEDIUM/MAJORTrend classification (🟢BULL/🔴BEAR/⚪NEUT)HTF TrendsHigher timeframe alignment indicatorsMomentumSTR↑/MOD↑/WK↑/WK↓/MOD↓/STR↓VolatilityLOW/MOD/HIGH/EXTR (based on ATR%)RSI(14)Color-coded: >70 red, <30 greenATR%Volatility as % of priceAdvanced Dashboard Features (Optional):
Price Distance from Key MAs
vs MA21, MA50, MA200 (percentage)
Color-coded: green (above), red (below)
MA Alignment Score
Calculates % of MAs in proper order
🟢 for bullish alignment, 🔴 for bearish
Trend Strength
Based on separation between MA21 and MA200
NONE/WEAK/MODERATE/STRONG/EXTREME
Consolidation Detection
Identifies low-volatility ranges
Prevents signals during sideways markets
⚙️ Customization OptionsFilter Toggles:
☑️ Require Momentum
☑️ Require Volume
☑️ Require HTF Alignment
☑️ Use ATR post-cross confirmation
☑️ Whipsaw filter
Min bars between signals (default: 5)
Dashboard Styling:
9 position options
6 text sizes
Custom colors for header, rows, and text
Toggle individual metrics on/off
🎨 Visual Elements
Signal Labels:
ST▲/ST▼ (green/red) - Short-term
MT▲/MT▼ (blue/orange) - Medium-term
GOLDEN CROSS / DEATH CROSS - Major signals
Volume Spikes:
Small labels showing volume class + direction
Example: "HIGH🟢" or "EXPL🔴"
Market Structure:
Dashed lines for Break of Structure levels
Automatic detection of swing highs/lows
🔔 Alert Conditions
Pre-configured alerts for:
Short-term bullish/bearish crosses
Medium-term bullish/bearish crosses
Golden Cross / Death Cross
Volume spikes
💡 Key Strengths
Institutional-Grade Filtering: Multiple confirmation layers reduce false signals
Multi-Timeframe Analysis: Ensures alignment across timeframes
Adaptive to Market Conditions: ATR-based thresholds adjust to volatility
Comprehensive Dashboard: All critical metrics in one view
Highly Customizable: 100+ input parameters
Signal Quality Over Quantity: Strict filters prioritize high-probability setups
⚠️ Usage Recommendations
Best for: Swing trading and position trading
Timeframes: Works on all TFs, optimized for 15m-Daily
Markets: Stocks, Forex, Crypto, Indices
Signal Frequency: Conservative (quality over quantity)
Combine with: Support/resistance, price action, risk management
🔧 Technical Implementation Notes
Uses Pine Script v6 syntax
Efficient calculation with minimal repainting
Maximum 500 labels for performance
Security function for HTF data (no lookahead bias)
Array-based MA alignment calculation
State variables to track signal spacing
This is a professional-grade trading system that combines classical technical analysis (moving averages) with modern institutional concepts (market structure, order blocks, multi-timeframe alignment).
The extensive filtering system is designed to eliminate noise and focus on high-probability trade setups.
Kalkulator pozycji XAUUSD PLN, 1:500, 1100 to 100 kontaPosition calculator based on the number of pips that you quickly enter from the tool, this device will select the appropriate lot for you and you can quickly take a position
ICT Breaker Blocks [Exponential-X]🔄 Breaker Blocks
Overview
Breaker Blocks automatically identifies failed order blocks that have reversed their polarity. When an order block gets broken, it often becomes a powerful support or resistance zone in the opposite direction. This indicator tracks these institutional "flips" based on ICT (Inner Circle Trader) concepts, helping identify where price is likely to find strong support or resistance after a structural break.
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🎯 What This Indicator Does
Detects Breaker Blocks:
• 🔵 Bullish Breaker Blocks (BB+) - Failed bearish order blocks that became support
• 🟣 Bearish Breaker Blocks (BB-) - Failed bullish order blocks that became resistance
• Tracks order blocks first, then monitors when they break
• Converts broken order blocks into breaker blocks automatically
• Shows when breakers get tested by price
How Breakers Form:
1. Order block forms (last opposite candle before strong move)
2. Price returns and breaks through the order block
3. Broken order block becomes a breaker block with flipped polarity
4. Old resistance becomes new support (or vice versa)
Visual Display: Smart Features:
• Auto-timeframe adjustment for optimal detection
• ATR-based strength filtering
• Active block highlighting
• Test tracking
• Distance calculator
• Duplicate prevention
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📚 Understanding Breaker Blocks
What Are Breaker Blocks?
Breaker blocks are failed order blocks that price has broken through. In ICT methodology:
• When institutions place orders creating an order block
• If that level fails and price breaks through
• The zone often becomes strong support/resistance in the opposite direction
• This represents institutional position flipping
Why Breakers Form:
• Failed Defense: Institutions couldn't defend the original level
• Position Flip: Institutions reversed their position
• Stop Hunt Complete: After sweeping stops, new levels form
• Polarity Change: Old resistance becomes new support (or vice versa)
Key Difference From Order Blocks: [/b>
• Order Block: Original institutional level (unbroken)
• Breaker Block: Failed order block that flipped polarity
• Breakers often provide STRONGER reactions than original OBs
• Represents where institutions changed their strategy
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🔵 Bullish Breaker Blocks Explained
Formation Process:
1. Step 1: Bearish order block forms (last bullish candle before drop)
2. Step 2: Price breaks ABOVE this bearish OB
3. Step 3: The broken bearish OB becomes a bullish breaker
4. Step 4: Now acts as SUPPORT when price returns
What It Means:
• Old resistance level failed
• Institutions flipped from selling to buying
• When price returns, zone acts as strong support
• Higher probability long setup than regular support
Trading Bullish Breakers:
Entry Setup:
• Wait for price to retrace back to bullish breaker
• Look for rejection/bounce from the breaker zone
• Enter long when price respects the breaker as support
• Stop loss: Below the breaker block
• Target: Recent high or opposite breaker
Why It Works:
Failed resistance becoming support is a strong technical signal indicating structural change in market sentiment.
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🟣 Bearish Breaker Blocks Explained
Formation Process:
1. Step 1: Bullish order block forms (last bearish candle before rally)
2. Step 2: Price breaks BELOW this bullish OB
3. Step 3: The broken bullish OB becomes a bearish breaker
4. Step 4: Now acts as RESISTANCE when price returns
What It Means:
• Old support level failed
• Institutions flipped from buying to selling
• When price returns, zone acts as strong resistance
• Higher probability short setup than regular resistance
Trading Bearish Breakers:
Entry Setup:
• Wait for price to retrace back to bearish breaker
• Look for rejection/reversal from the breaker zone
• Enter short when price respects the breaker as resistance
• Stop loss: Above the breaker block
• Target: Recent low or opposite breaker
Why It Works:
Failed support becoming resistance indicates structural change and often leads to continuation moves.
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📊 How To Use This Indicator
Strategy 1: Breaker Block Retest
Timeframes: 15min, 1H, 4H
Style: [/b> Swing trading, reversal entries
Rules:
1. Identify active breaker block (bright color, not gray)
2. Wait for price to return to the breaker zone
3. Look for reversal confirmation (pin bar, engulfing, rejection)
4. Enter in the direction the breaker suggests
5. Stop: Beyond opposite side of breaker
6. Target: 2-3R or previous structure
Example - Bullish Breaker:
• Bullish breaker at $48,000-$48,500
• Price drops to $48,200 (enters breaker)
• Bullish pin bar forms
• Enter long at $48,600, stop at $47,800
• Target: $50,000+
Strategy 2: Multi-Timeframe Breakers
Timeframes: Combine 1H + 4H or 15min + 1H
Style: [/b> High-probability setups
Rules:
1. Identify breaker on higher timeframe (4H or Daily)
2. Switch to lower timeframe (1H or 15min)
3. Look for lower TF breaker WITHIN higher TF breaker
4. Trade the lower TF breaker in same direction as HTF
5. Stop: Below lower TF breaker
6. Target: Edge of higher TF breaker or beyond
Why It Works: Alignment across timeframes increases probability
Strategy 3: Breaker + Order Block Confluence
Timeframes: 1H, 4H
Style: High-conviction trades
Rules:
1. Find breaker block that overlaps with fresh order block
2. This creates double institutional zone
3. Wait for price to reach confluence area
4. Enter on first touch with confirmation
5. Stop: Beyond confluence zone
6. Target: 3-5R
Why It Works: Two ICT concepts aligned = maximum probability
Strategy 4: Breaker Breakout
Timeframes: [/b> 5min, 15min, 1H
Style: Trend continuation
Rules:
1. Price approaches breaker block
2. Instead of respecting it, price breaks THROUGH
3. This indicates very strong momentum
4. Enter breakout in direction of break
5. Stop: Back inside the breaker
6. Target: 2-3R
Why It Works: When breakers fail, momentum is extremely strong
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⚙️ Settings Explained
Core Settings
Auto-Adjust for Timeframe (Default: ON)
• Automatically optimizes detection for current chart
• 1min: 3 bars lookback
• 5min: 4 bars lookback
• 15min: 5 bars lookback
• 1H: 6 bars lookback
• 4H+: 8-12 bars lookback
• Recommended: Keep ON
Manual Detection Length (Default: 5)
• Only used when Auto-Adjust is OFF
• Lookback period for finding order blocks
• Lower = more sensitive
• Higher = more selective
Display Settings
Show Bullish/Bearish Breaker Blocks
• Toggle each type independently
• Customize colors (default: cyan and fuchsia)
• Tip: Use colors that stand out from order blocks
Max Breaker Blocks to Display (Default: 10) [/b>
• Limits visible breakers
• Lower (5-8): Cleaner chart
• Higher (15-30): More context
• Recommended: 10-15
Show Breaker Block Labels [/b>
• Displays BB+ and BB- text
• Shows 🎯 on active (nearest) breaker
• Turn OFF for minimal appearance
Extend Blocks (bars) (Default: 50)
• How far to extend boxes to the right
• Recommended: 40-60 bars
Filters
Block Strength Filter (Default: Medium)
• Low: 0.5x ATR - More breakers, more noise
• Medium: 1x ATR - Balanced
• High: 1.5x ATR - Only strongest breakers
• Note: Breakers are naturally less common than OBs
• For learning: Use Low to see more examples
• For trading: Use Medium or High
Min Block Size % (Default: 0.1)
• Minimum breaker size as % of price
• Filters tiny insignificant blocks
• Adjust based on instrument volatility
Advanced
Show Tested Blocks (Default: OFF) [/b>
• When ON: Shows gray boxes for tested breakers
• When OFF: Breakers disappear after test
• Use ON: For learning and analysis
• Use OFF: For clean active trading
Highlight Active Block (Default: ON)
• Highlights nearest breaker to current price
• Active block shown with brighter color and 🎯
• Recommended: Keep ON
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📱 Info Panel Guide
Bullish BB Count Bearish BB Count
• Number of active (untested) bearish breaker blocks
• More bearish breakers = More resistance zones above
Bias Indicator [/b>
• ⬆ Bullish: More bullish breakers (support > resistance)
• ⬇ Bearish: More bearish breakers (resistance > support)
• ↔ Neutral: Equal breakers on both sides
Near Indicator
• Shows nearest active breaker and distance
• Example: "Bull BB -1.5%" = Bullish breaker 1.5% below price
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📱 Alert Setup
This indicator includes 2 alert types:
1. Price Entering Bullish Breaker [/b>
• Fires when price touches bullish breaker block
• Action: Watch for bounce/support
2. Price Entering Bearish Breaker
• Fires when price touches bearish breaker block
• Action: Watch for rejection/resistance
To Set Up Alerts:
1. Click "Alert" button (clock icon)
2. Select "Breaker Blocks"
3. Choose alert type
4. Configure notifications
5. Click "Create"
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💎 Pro Tips & Best Practices
✅ DO:
• Wait for confirmation before entering at breakers
• First touch of breaker has highest reliability
• Use breakers with trend direction for best results
• Combine with order blocks and FVGs for confluence
• Check multiple timeframes for breaker alignment
• Respect breakers - they're stronger than regular S/R
• Use proper stop placement beyond the breaker
⚠️ DON'T:
• Don't trade every breaker - quality over quantity
• Don't ignore breaker breaks - very strong momentum signal
• Don't use tight stops - allow room for wicks
• Don't expect all breakers to hold
• Don't trade against strong momentum through breakers
• Don't confuse breakers with regular order blocks
🎯 Best Timeframes:
• Scalping: 5min, 15min (quick breaker tests)
• Day Trading: 15min, 1H (balanced)
• Swing Trading: 1H, 4H, Daily (major breakers)
🔥 Best Markets:
• Excellent: BTC, ETH, Forex majors, ES, NQ
• Good: Gold, Oil, Major indices
• Note: Breakers need volatility to form
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🎓 Advanced Concepts
Breaker Strength Hierarchy
From weakest to strongest:
1. Support/Resistance lines
2. Order Blocks (unbroken)
3. Breaker Blocks (broken OBs) ← Often strongest
4. Multiple breakers stacked together
Breaker vs Order Block Priority
If breaker and order block overlap:
• Breaker takes precedence
• Failed levels are more significant
• Price respects breakers more reliably
Nested Breakers [/b>
When lower timeframe breaker exists within higher timeframe breaker:
• Trade lower TF breaker first
• Use higher TF breaker as final target
• Highest probability setups
Multiple Breaker Tests [/b>
• First test: Highest probability
• Second test: Still valid but weaker
• Third test: Likely to break through
Breaker Breakouts [/b>
When price breaks through breaker:
• Extremely strong momentum signal
• Old level completely invalidated
• Trade the breakout aggressively
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📈 Common Patterns [/b>
Pattern 1: The Perfect Flip
• Bearish OB forms
• Price breaks above it cleanly
• Becomes bullish breaker
• First retest bounces perfectly
• High-probability setup
Pattern 2: The Double Break
• Bullish OB breaks down (becomes bearish breaker)
• Price tests it and rejects
• Later breaks back up through breaker
• Very strong momentum signal
Pattern 3: The Breaker Ladder [/b>
• Multiple breakers stacked like stairs
• Price bounces from one to next
• Each breaker provides support/resistance
Pattern 4: The Failed Breaker
• Breaker forms but gets broken immediately
• Shows extreme momentum
• Don't fight it - trade the breakout
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🙏 If You Find This Helpful
• ⭐ Leave your feedback
• 💬 Share your experience in the comments
• 🔔 Follow for updates and new tools
Questions about breaker blocks? Feel free to ask in the comments.
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Version History [/b>
• v1.0 - Initial release with auto-timeframe detection and polarity flip tracking
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
Volume Profile VisionVolume Profile Vision - Complete Description
Overview
Volume Profile Vision (VPV) is an advanced volume profile indicator that visualizes where trading activity has occurred at different price levels over a specified time period. Unlike traditional volume indicators that show volume over time, this indicator displays volume distribution across price levels, helping traders identify key support/resistance zones, fair value areas, and potential reversal points.
What Makes This Indicator Original
Volume Profile Vision introduces several unique features not found in standard volume profile tools:
Dual-Direction Histogram Display:
Unlike conventional volume profiles that only show bars extending in one direction, VPV displays volume bars extending both left (into historical candles) and right (as a traditional histogram). This bi-directional approach allows traders to see exactly where historical price action intersected with high-volume nodes.
Real-Time Candle Highlighting: The indicator dynamically highlights volume bars that intersect with the current candle's price range, making it immediately obvious which volume levels are currently in play.
Four Professional Color Schemes: Each color scheme uses distinct gradient algorithms and visual encoding systems:
Traffic Light: Uses red (POC), green (VA boundaries), yellow (HVN), with grayscale gradients outside the value area
Aurora Glass: Modern cyan-to-magenta gradient with hot magenta POC highlighting
Obsidian Precision: Professional dark theme with white POC and electric cyan accents
Black Ice: Monochromatic cyan family with graduated intensity
Adaptive Transparency System: Automatically adjusts bar transparency based on position relative to value area, with special handling for each color scheme to maintain visual clarity.
Core Concepts & Calculations
Volume Distribution Analysis
The indicator divides the visible price range into user-defined price levels (default: 80 levels) and calculates the total volume traded at each level by:
Scanning back through the specified lookback period (customizable or visible range)
For each historical bar, determining which price levels the bar's high/low range intersects
Accumulating volume for each intersected price level
Optionally filtering by bullish/bearish volume only
Point of Control (POC)
The POC is the price level with the highest traded volume during the analyzed period. This represents the "fairest" price where most traders agreed on value. The indicator marks this with distinct coloring (red in Traffic Light, magenta in Aurora Glass, white in Obsidian Precision, cyan in Black Ice).
Trading Significance: POC acts as a strong magnet for price - markets tend to return to fair value. When price is away from POC, traders watch for:
Mean reversion opportunities when price is far from POC
Rejection signals when price tests POC from above/below
Breakout confirmation when price breaks through and holds beyond POC
Value Area (VA)
The Value Area encompasses the price range where a specified percentage (default: 68%) of all volume traded. This represents the range of "accepted value" by market participants.
Calculation Method:
Start at the POC (highest volume level)
Expand upward and downward, adding adjacent price levels
Always add the level with higher volume next
Continue until accumulated volume reaches the VA percentage threshold
Value Area High (VAH): Upper boundary of accepted value - acts as resistance
Value Area Low (VAL): Lower boundary of accepted value - acts as support
Trading Significance:
Price spending time inside VA indicates market equilibrium
Breakouts above VAH suggest bullish momentum shift
Breakdowns below VAL suggest bearish momentum shift
Returns to VA boundaries often provide high-probability entry zones
High Volume Nodes (HVN)
Price levels with volume exceeding a threshold percentage (default: 80%) of POC volume. These represent areas of strong agreement and consolidation.
Trading Significance:
HVNs act as strong support/resistance zones
Price tends to consolidate at HVNs before making directional moves
Breaking through an HVN often signals strong momentum
Low Volume Nodes (LVN)
Price levels within the Value Area with volume ≤30% of POC volume. These are zones price moved through quickly with minimal consolidation.
Trading Significance:
LVNs represent areas of rejection - price finds little acceptance
Price tends to move rapidly through LVN zones
Useful for setting stop-losses (below LVN for longs, above for shorts)
Can identify potential gaps or "air pockets" in the market structure
Grayscale POC Detection
A secondary POC detection system identifies the highest volume level outside the Value Area (with a 2-level buffer to avoid confusion). This helps identify significant volume accumulation zones that exist beyond the main value area.
How to Use This Indicator
Setup
Choose Lookback Period:
Enable "Use Visible Range" to analyze only what's on your chart
Or set "Fixed Range Lookback Depth" (default: 200 bars) for consistent analysis
Adjust Profile Resolution:
"Number of Price Levels" (default: 80) - higher = more granular analysis, lower = broader zones
Select Color Scheme:
Traffic Light: Best for clear POC/VA/HVN identification
Aurora Glass: Modern aesthetic for dark charts
Obsidian Precision: Professional trader preference
Black Ice: Minimalist single-color family
Visual Customization
Left Extension: How far back the left-side histogram extends into historical candles (default: 490 bars)
Right Extension: Width of the traditional histogram bars on the right (default: 50 bars)
Right Margin: Space between current price bar and histogram (default: 0 for flush alignment)
Left Profile Gap: Space between left-side histogram and candles (default: 0)
Trading Strategies
Strategy 1: Value Area Mean Reversion
Wait for price to move outside the Value Area (above VAH or below VAL)
Look for rejection signals (wicks, bearish/bullish candles)
Enter trades toward the POC
Take profits as price returns to POC or opposite VA boundary
Strategy 2: Breakout Confirmation
Identify when price is consolidating within the Value Area
Wait for a strong close above VAH (bullish) or below VAL (bearish)
Enter on the breakout or on first pullback to the VA boundary
Target previous HVNs or swing highs/lows outside the VA
Strategy 3: POC Support/Resistance
Watch for price approaching the POC level
If approaching from below, look for bullish reversal patterns at POC (support)
If approaching from above, look for bearish reversal patterns at POC (resistance)
Trade in the direction of the bounce with stops beyond the POC
Strategy 4: LVN Fast Movement Zones
Identify LVN zones within the Value Area (marked with "LVN" label)
When price enters an LVN, expect rapid movement through the zone
Avoid entering trades within LVNs
Use LVNs as confirmation of directional momentum
Alert System
The indicator includes 7 customizable alert conditions:
POC Touch: Alerts when price comes within 0.5 ATR of POC
VAH/VAL Touch: Alerts at Value Area boundaries
VA Breakout: Alerts on breakouts above VAH or below VAL
HVN Touch: Alerts when price contacts High Volume Nodes
LVN Entry: Alerts when entering Low Volume zones
POC Shift: Alerts when POC moves to a new price level
Reading the Profile
Price Labels (shown on the right side):
POC: Point of Control - highest volume price level
VAH: Value Area High - upper boundary of accepted value
VAL: Value Area Low - lower boundary of accepted value
LVN: Low Volume Node - expect fast movement through this zone
Color Intensity Interpretation:
Brighter colors = higher volume concentration
Dimmer colors = lower volume
Abrupt color changes = transition between volume zones
Gaps in the histogram = price levels with no trading activity
Technical Details
Volume Accumulation Logic:
For each bar in lookback period:
For each price level:
If bar's high/low range intersects price level:
Add bar's volume to that price level's total
Gradient Algorithm:
Traffic Light: Dual-range piecewise gradient (0-50% and 50-100% volume intensity)
Aurora Glass: Linear cyan-to-magenta interpolation
Obsidian Precision: Dark blue gradient with cyan highlights
Black Ice: Three-stage cyan intensity progression
Real-Time Updates:
The profile recalculates on every bar, including real-time tick data, ensuring the volume distribution always reflects current market structure.
Best Practices
Timeframe Selection: Use higher timeframes (4H, Daily) for swing trading, lower timeframes (5min, 15min) for day trading
Combine with Price Action: Volume profile shows WHERE, price action shows WHEN
Multiple Timeframe Analysis: Check daily VP for major levels, then drill down to intraday for entries
Volume Type Selection: Use "Bullish" volume in uptrends, "Bearish" in downtrends, or "Both" for complete picture
Adjust VA Percentage: 68% (default) captures one standard deviation; try 70% for tighter or 60% for broader value areas
Performance Notes
Maximum bars back: 5000 (handles deep historical analysis)
Maximum boxes: 500 (handles complex profiles)
Optimized calculation: Only recalculates on last bar for efficiency
Real-time capable: Updates as new ticks arrive
Swing Trading IndicatorThis script is a swing‑trading dashboard designed for BTC, ETH, S&P 500 (for now). It combines weekly RSI, USDT.D, VIX, moving averages and Fisher Transform into a single visual tool, with background highlights, an on‑chart info table and ready‑made alerts to help you time high‑probability swing entries and manage risk.
1. Overview
The indicator is intended to work on daily timeframe.
Signals are context‑aware: BTC and ETH get USDT.D conditions, SPX gets VIX and EMA‑100 logic, and all non‑ETH symbols can also use Fisher Transform as a mean‑reversion filter.
2. Conditions and background highlights
Each component sets a boolean condition and, when active, paints a background layer:
Weekly RSI condition
True when weekly RSI is below its symbol‑specific threshold.
USDT.D conditions
BTC: triggered when USDT.D is above the user threshold and the chart symbol is BTC.
ETH: same logic for ETH, but tracked separately..
VIX condition (SPX only)
True when VIX high is at or above the VIX threshold while the chart is SPX.
EMA condition (BTC & SPX)
BTC: daily close below EMA‑200.
SPX: daily close below EMA‑100.
Fisher Transform condition (non‑ETH)
Fisher Transform on the chart timeframe, using the configured period.
True when Fisher value is below the Fisher threshold.
3. Intended use and notes
This indicator is designed as a confluence tool for swing traders, not a standalone buy/sell system. It works best on assets that are in a clear uptrend, where the main idea is to accumulate during corrections within that broader bullish structure.
During larger market shocks, deep corrections, or black‑swan events, trend‑based and mean‑reversion filters can produce false signals, because volatility and correlations often behave abnormally in those periods. For that reason, this script should always be combined with independent risk management, higher‑timeframe trend analysis, and your own discretion.
SMC N-Gram Probability Matrix [PhenLabs]📊 SMC N-Gram Probability Matrix
Version: PineScript™ v6
📌 Description
The SMC N-Gram Probability Matrix applies computational linguistics methodology to Smart Money Concepts trading. By treating SMC patterns as a discrete “alphabet” and analyzing their sequential relationships through N-gram modeling, this indicator calculates the statistical probability of which pattern will appear next based on historical transitions.
Traditional SMC analysis is reactive—traders identify patterns after they form and then anticipate the next move. This indicator inverts that approach by building a transition probability matrix from up to 5,000 bars of pattern history, enabling traders to see which SMC formations most frequently follow their current market sequence.
The indicator detects and classifies 11 distinct SMC patterns including Fair Value Gaps, Order Blocks, Liquidity Sweeps, Break of Structure, and Change of Character in both bullish and bearish variants, then tracks how these patterns transition from one to another over time.
🚀 Points of Innovation
First indicator to apply N-gram sequence modeling from computational linguistics to SMC pattern analysis
Dynamic transition matrix rebuilds every 50 bars for adaptive probability calculations
Supports bigram (2), trigram (3), and quadgram (4) sequence lengths for varying analysis depth
Priority-based pattern classification ensures higher-significance patterns (CHoCH, BOS) take precedence
Configurable minimum occurrence threshold filters out statistically insignificant predictions
Real-time probability visualization with graphical confidence bars
🔧 Core Components
Pattern Alphabet System: 11 discrete SMC patterns encoded as integers for efficient matrix indexing and transition tracking
Swing Point Detection: Uses ta.pivothigh/pivotlow with configurable sensitivity for non-repainting structure identification
Transition Count Matrix: Flattened array storing occurrence counts for all possible pattern sequence transitions
Context Encoder: Converts N-gram pattern sequences into unique integer IDs for matrix lookup
Probability Calculator: Transforms raw transition counts into percentage probabilities for each possible next pattern
🔥 Key Features
Multi-Pattern SMC Detection: Simultaneously identifies FVGs, Order Blocks, Liquidity Sweeps, BOS, and CHoCH formations
Adjustable N-Gram Length: Choose between 2-4 pattern sequences to balance specificity against sample size
Flexible Lookback Range: Analyze anywhere from 100 to 5,000 historical bars for matrix construction
Pattern Toggle Controls: Enable or disable individual SMC pattern types to customize analysis focus
Probability Threshold Filtering: Set minimum occurrence requirements to ensure prediction reliability
Alert Integration: Built-in alert conditions trigger when high-probability predictions emerge
🎨 Visualization
Probability Table: Displays current pattern, recent sequence, sample count, and top N predicted patterns with percentage probabilities
Graphical Probability Bars: Visual bar representation (█░) showing relative probability strength at a glance
Chart Pattern Markers: Color-coded labels placed directly on price bars identifying detected SMC formations
Pattern Short Codes: Compact notation (F+, F-, O+, O-, L↑, L↓, B+, B-, C+, C-) for quick pattern identification
Customizable Table Position: Place probability display in any corner of your chart
📖 Usage Guidelines
N-Gram Configuration
N-Gram Length: Default 2, Range 2-4. Lower values provide more samples but less specificity. Higher values capture complex sequences but require more historical data.
Matrix Lookback Bars: Default 500, Range 100-5000. More bars increase statistical significance but may include outdated market behavior.
Min Occurrences for Prediction: Default 2, Range 1-10. Higher values filter noise but may reduce prediction availability.
SMC Detection Settings
Swing Detection Length: Default 5, Range 2-20. Controls pivot sensitivity for structure analysis.
FVG Minimum Size: Default 0.1%, Range 0.01-2.0%. Filters insignificant gaps.
Order Block Lookback: Default 10, Range 3-30. Bars to search for OB formations.
Liquidity Sweep Threshold: Default 0.3%, Range 0.05-1.0%. Minimum wick extension beyond swing points.
Display Settings
Show Probability Table: Toggle the probability matrix display on/off.
Show Top N Probabilities: Default 5, Range 3-10. Number of predicted patterns to display.
Show SMC Markers: Toggle on-chart pattern labels.
✅ Best Use Cases
Anticipating continuation or reversal patterns after liquidity sweeps
Identifying high-probability BOS/CHoCH sequences for trend trading
Filtering FVG and Order Block signals based on historical follow-through rates
Building confluence by comparing predicted patterns with other technical analysis
Studying how SMC patterns typically sequence on specific instruments or timeframes
⚠️ Limitations
Predictions are based solely on historical pattern frequency and do not account for fundamental factors
Low sample counts produce unreliable probabilities—always check the Samples display
Market regime changes can invalidate historical transition patterns
The indicator requires sufficient historical data to build meaningful probability matrices
Pattern detection uses standardized parameters that may not capture all institutional activity
💡 What Makes This Unique
Linguistic Modeling Applied to Markets: Treats SMC patterns like words in a language, analyzing how they “flow” together
Quantified Pattern Relationships: Transforms subjective SMC analysis into objective probability percentages
Adaptive Learning: Matrix rebuilds periodically to incorporate recent pattern behavior
Comprehensive SMC Coverage: Tracks all major Smart Money Concepts in a unified probability framework
🔬 How It Works
1. Pattern Detection Phase
Each bar is analyzed for SMC formations using configurable detection parameters
A priority hierarchy assigns the most significant pattern when multiple detections occur
2. Sequence Encoding Phase
Detected patterns are stored in a rolling history buffer of recent classifications
The current N-gram context is encoded into a unique integer identifier
3. Matrix Construction Phase
Historical pattern sequences are iterated to count transition occurrences
Each context-to-next-pattern transition increments the appropriate matrix cell
4. Probability Calculation Phase
Current context ID retrieves corresponding transition counts from the matrix
Raw counts are converted to percentages based on total context occurrences
5. Visualization Phase
Probabilities are sorted and the top N predictions are displayed in the table
Chart markers identify the current detected pattern for visual reference
💡 Note:
This indicator performs best when used as a confluence tool alongside traditional SMC analysis. The probability predictions highlight statistically common pattern sequences but should not be used as standalone trading signals. Always verify predictions against price action context, higher timeframe structure, and your overall trading plan. Monitor the sample count to ensure predictions are based on adequate historical data.
VWAP-Anchored MACD [BOSWaves]VWAP-Anchored MACD - Volume-Weighted Momentum Mapping With Zero-Line Filtering
Overview
The VWAP-Anchored MACD delivers a refined momentum model built on volume-weighted price rather than raw closes, giving you a more grounded view of trend strength during sessions, weeks, or months.
Instead of tracking two EMAs of price like a standard MACD, this tool reconstructs the MACD engine using anchored VWAP as the core input. The result is a momentum structure that reacts to real liquidity flow, filters out weak crossovers near the zero line, and visualizes acceleration shifts with clear, high-contrast gradients.
This indicator acts as a precise momentum map that adapts in real time. You see how weighted price is accelerating, where valid crossovers form, and when trend conviction is strong enough to justify execution.
It uses gradient line coloring to show bullish or bearish momentum, histogram shading to highlight energy shifts, cross dots to mark valid crossovers, optional buy/sell diamonds for execution cues, and candle coloring to display trend strength at a glance.
Theoretical Foundation
Traditional MACD compares the difference between two exponential moving averages of price.
This variant replaces price with anchored VWAP, making the calculation sensitive to actual traded volume across your chosen period (Session, Week, or Month).
Three principles drive the logic:
Anchored VWAP Momentum : Price is weighted by volume and aggregated across the selected anchor. The fast and slow VWAP-EMAs then expose how liquidity-corrected momentum is expanding or contracting.
Zero-Line Distance Filtering : Crossover signals that occur too close to the zero line are removed. This eliminates the common MACD problem of generating weak, directionless signals in choppy phases.
Directional Visualization : MACD line, signal line, histogram, candle colors, and optional diamond markers all react to shifts in VWAP-momentum, giving you a clean structural read on market pressure.
Anchoring VWAP to session, weekly, or monthly resets creates a systematic framework for tracking how capital flow is driving momentum throughout each trading cycle.
How It Works
The core engine processes momentum through several mapped layers:
VWAP Aggregation : Price × volume is accumulated until the anchor resets. This creates a continuous, liquidity-corrected VWAP curve.
MACD Construction : Fast and slow VWAP-EMAs define the MACD line, while a smoothed signal line identifies edges where momentum shifts.
Zero-Line Distance Filter : MACD and signal must both exceed a threshold distance from zero for a crossover to count as valid. This prevents fake crossovers during compression.
Visual Momentum Layers : It uses gradient line coloring to show bullish or bearish momentum, histogram shading to highlight energy shifts, cross dots to mark valid crossovers, optional buy/sell diamonds for execution cues, and candle coloring to display trend strength at a glance.
This layered structure ensures you always know whether momentum is strengthening, fading, or transitioning.
Interpretation
You get a clean, structural understanding of VWAP-based momentum:
Bullish Phases : MACD > Signal, histogram expands, candles turn bullish, and crossovers occur above the threshold.
Bearish Phases : MACD < Signal, histogram drives lower, candles shift bearish, and downward crossovers trigger below the threshold.
Neutral/Compression : Both lines remain near the zero boundary, histogram flattens, and signals are suppressed to avoid noise.
This creates a more disciplined version of MACD momentum reading - less noise, more conviction, and better alignment with liquidity.
Strategy Integration
Trend Continuation : Use VWAP-MACD crossovers that occur far from the zero line as higher-conviction entries.
Zero-Line Rejection : Watch for histogram contractions near zero to anticipate flattening momentum and potential reversal setups.
Session/Week/Month Anchors : Session anchor works best for intraday flows. Weekly or monthly anchor structures create cleaner macro momentum reads for swing trading.
Signal-Only Execution : Optional buy/sell diamonds give you direct points to trigger trades without overanalyzing the chart.
This indicator slots cleanly into any momentum-following system and offers higher signal quality than classic MACD variants due to the volume-weighted core.
Technical Implementation Details
VWAP Reset Logic : Session (D), Week (W), or Month (M)
Dynamic Fast/Slow VWAP EMAs : Fully configurable lengths, smoothing and anchor settings
MACD/Signal Line Framework : Traditional structure with volume-anchored input
Zero-Line Filtering : Adjustable threshold for structural confirmation
Dual Visualization Layers : MACD body + histogram + crosses + candle coloring
Optimized Performance : Lightweight, fast rendering across all timeframes
Optimal Application Parameters
Timeframes:
1- 15 min : Short-term momentum scalping and rapid trend shifts
30- 240 min : Balanced momentum mapping with clear structural filtering
Daily : Macro VWAP regime identification
Suggested Configuration:
Fast Length : 12
Slow Length : 26
Signal Length : 9
Zero Threshold : 200 - 500 depending on asset range
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Performance Characteristics
High Effectiveness:
Assets with strong intraday or session-based volume cycles
Markets where volume-weighted momentum leads price swings
Trend environments with strong acceleration
Reduced Effectiveness:
Ultra-choppy markets hugging the VWAP axis
Sessions with abnormally low volume
Ranges where MACD naturally compresses
Disclaimer
The VWAP-Anchored MACD is a structural momentum tool designed to enhance directional clarity - not a guaranteed predictor. Performance depends on market regime, volatility, and disciplined execution. Use it alongside broader trend, volume, and structural analysis for optimal results.
