SuperTrade Ichimoku Cloud StrategyUnlike SuperTrade's Super Trend the Ichimoku Cloud Strategy is a trend-following system derived from the Ichimoku Kinko Hyo indicator. It helps identify market direction, momentum, and potential support/resistance zones. This strategy uses key components of the Ichimoku Cloud to determine bullish or bearish trends and executes trades accordingly.
🔍 Key Components Used
Conversion Line (Tenkan-sen) – short-term average (9-period Donchian midpoint by default)
Base Line (Kijun-sen) – medium-term average (26-period Donchian midpoint)
Leading Span A (Senkou Span A) – average of Conversion Line and Base Line, plotted forward by 26 periods.
Leading Span B (Senkou Span B) – 52-period Donchian midpoint, plotted forward by 26 periods.
Lagging Span (Chikou Span) – current close price, plotted backward by 26 periods (for visual reference only in this version).
The cloud (Kumo) is the area between Leading Span A and B, representing trend direction and potential support/resistance.
📈 Entry Rules (Buy Condition)
A long trade is entered when:
LeadLine1 > LeadLine2 → This implies a bullish cloud.
Close > LeadLine1 and Close > LeadLine2 → The price is trading above the cloud, confirming upward momentum.
This combination indicates a strong bullish trend, so the strategy enters a long position.
📉 Exit Rules (Sell Condition / Close Position)
The long trade is closed when:
LeadLine1 < LeadLine2 → This implies a bearish cloud.
Close < LeadLine1 and Close < LeadLine2 → The price has fallen below the cloud, signaling trend weakness or reversal.
This confirms a bearish trend, prompting the strategy to exit the long position.
✅ Must-Have Elements in This Strategy
Entry Logic – based on price position relative to the cloud and cloud direction.
Exit Logic – closes the position when price shifts to a bearish trend.
Overlay Enabled – plotted over price for visual confirmation of signals.
Dynamic Parameters – inputs for conversion/base/cloud lengths and displacement.
Visualization – plots all Ichimoku components including cloud fill for clarity.
No Shorting Logic Yet – this version only handles long trades; shorting can be added optionally.
No Stop-Loss or Take-Profit – trades are closed purely based on Ichimoku trend reversal.
Indicatori e strategie
SMA ExtensionsExplanation of the SMA Extensions Indicator
The SMA Extensions indicator, designed for TradingView, overlays a 200-period Simple Moving Average (SMA) and its extensions (1.5x, 2x, 2.5x, 3x) on the price chart to identify price zones. Users can customize the SMA source, length, and line colors (default: blue, green, yellow, orange, red). Each level is plotted as a line, with transparent colored fills between them and below the SMA to highlight zones. Labels ("Very Cheap," "Cheap," "Fair Value," "Expensive," "Very Expensive") appear only on the last bar, slightly right-shifted, matching line colors for clarity. This helps traders assess whether prices are undervalued or overvalued relative to the SMA.
The idea originated from a video from the YouTube channel Crypto Currently
OBV by readCrypto
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OBV is used as a leading indicator to predict stock price movements by measuring changes in trading volume.
Reflecting the cumulative value of trading volume,
- When the price rises, if the trading volume increases, OBV rises,
- When the price falls, if the trading volume decreases, OBV falls.
Therefore, the movement of the OBV indicator must be checked along with the price movement, and it has the disadvantage of being unreliable for coins (tokens) with low trading volume.
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(First interpretation method)
By adding a signal line for the OBV indicator,
- If the OBV indicator moves above the signal line, it is likely to show an upward trend,
- If the OBV indicator moves beyond the signal line, it is likely to show a downward trend.
This interpretation method is difficult to use in actual trading strategies because the OBV indicator often moves up and down repeatedly based on the signal line.
Therefore, it is recommended to use this interpretation method as reference when analyzing charts.
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(Second interpretation method)
Draw support and resistance lines based on the high and low points of the OBV indicator
- If the OBV indicator breaks through the previous high point, it is likely to show an upward trend,
- If the OBV indicator breaks through the previous low point, it is likely to show a downward trend.
This interpretation method is a bit more reliable than the first interpretation method, but it has the disadvantage of having to consider support and resistance lines separately based on the high and low points.
-
To compensate for this, a High line for the high point and a Low line for the low point were added.
- If the OBV indicator shows an upward breakout of each line (Low, HL2, High), the price is likely to rise,
- If the OBV indicator shows a downward breakout of each line (Low, HL2, High), the price is likely to fall.
-
Also, the Low and High lines can be interpreted like Bollinger Bands.
That is, if the Low and High lines show a contraction, the price is likely to move sideways, and if they show an expansion, the price is likely to show a trend.
Therefore, if the High line breaks upward in a contracted state,
- It is likely to show an upward trend,
- If the Low line breaks downward, it is likely to show a downward trend.
In an expanded state, you should focus on finding the point to realize profits rather than conducting new transactions.
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It is not easy to interpret the change in actual transaction volume and use it to create a trading strategy.
In particular, it is more difficult in the coin market where multiple exchanges are linked to show movements for one coin (token).
Therefore, the coin market is actively conducting transactions without referring to trading volume at all by following trends.
However, I think that if you interpret the change in trading volume and use it to find a trading point, it can help you find a more accurate trading point.
In that sense, I think that an indicator that adds the High and Low lines of the OBV indicator can be used as meaningful reference material.
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OBV는 거래량의 변화를 측정하여 주가 움직임을 예측하는 선행 지표로 활용됩니다.
거래량의 누적값을 반영하여
- 가격이 상승할 때 거래량이 증가면 OBV가 상승하고,
- 가격이 하락할 때 거래량이 줄면 OBV가 하락하게 됩니다.
따라서, 가격의 움직임과 함께 OBV 지표의 움직임을 확인하여야 하고 거래량이 적은 코인(토큰)에서는 신뢰성이 떨어지는 단점도 가지고 있습니다.
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(첫번째 해석 방법)
OBV 지표에 대한 Signal선을 추가하여
- OBV 지표가 Signal선 이상에서 이동하게 되면 상승세를 보일 가능성이 높고,
- OBV 지표가 Signal선 이항에서 이동하게 되면 하락세를 보일 가능성이 높습니다.
이러한 해석 방법은 Signal선을 기준으로 OBV 지표가 반복적으로 위아래로 움직임을 보이는 경우가 많기 때문에 실제 거래 전략에 활용되기가 어려운 면이 있습니다.
따라서, 이러한 해설 방법은 차트 분석을 할 때 참고 자료로 활용하는 것이 좋습니다.
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(두번째 해석 방법)
OBV 지표의 고점과 저점을 기준하여 지지와 저항선을 그려
- OBV 지표가 이전 고점을 상향 돌파하면 상승세를 보일 가능성이 높고,
- OBV 지표가 이전 저점을 하향 돌파하면 하락세를 보일 가능성이 높습니다.
이러한 해석 방법은 첫번째 해석 방법보다 좀 더 신뢰성이 있는 방법이지만, 고점과 저점을 기준으로 지지와 저항선을 나누어 생각해야 하는 단점이 있습니다.
-
이를 보완하고자 고점에 대한 High선과 저점에 대한 Low선을 추가하였습니다.
- OBV 지표가 각 선(Low, HL2, High)을 상향 돌파하는 모습을 보이면 가격이 상승할 가능성이 높고,
- OBV 지표가 각 선(Low, HL2, High)을 하향 돌파하는 모습을 보이면 가격이 하락할 가능성이 높습니다.
-
또한, Low선과 High선을 볼린저밴드와 같이 해석할 수 있습니다.
즉, Low선과 High선이 수축하는 모습을 보이면 가격은 횡보할 가능성이 높고, 확장하는 모습을 보이면 가격은 추세를 나타낼 가능성이 높습니다.
따라서, 수축한 상태에서
- High선을 상향 돌파하게 되면 상승세를 나타낼 가능성이 높고,
- Low선을 하향 돌파하게 되면 하락세를 나타낼 가능성이 높습니다.
확장된 상태에서는 신규 거래를 진행하기 보다 수익 실현할 시점을 찾는데 집중해야 합니다.
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실제 거래량의 변화를 해석하여 거래 전략을 만드는데 활용하기가 쉽지 않습니다.
특히, 하나의 코인(토큰)에 대해서 여러 개의 거래소가 연동되어 움직임을 나타내는 코인 시장에서는 더욱 어려움이 있습니다.
따라서, 코인 시장은 추세 추종으로 아예 거래량을 참고하지 않고 거래를 진행하는 방법이 활성화되어 있기도 합니다.
하지만, 거래량의 변화를 해석하여 거래 시점을 찾는데 활용한다면 보다 정확한 거래 시점을 찾는데 도움을 받을 수 있다고 생각합니다.
그러한 의미에서 OBV 지표의 High선과 Low선을 추가한 지표가 의미 있는 참고 자료로 활용될 수 있다고 생각합니다.
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ODR/PDR in Prices@DrGirishSawhneyversion 2 with customized movement rally by operator or promotor. dt 11-05-2023
ODR/PDR in Prices@DrGirishSawhneythis is a promotor driven rally published on chart for identifying a non stop upmove of minimum 20% , all in green candle.
RSI Candle Trend🎯 Purpose:
This TradingView script is designed to visualize trend strength using RSI values as candle data, instead of traditional price candles. It transforms RSI data into custom candles using various smoothing and filtering methods (like Heikin-Ashi, Linear Regression, Rational Quadratic Filter, or McGinley Dynamic). It allows traders to:
📌Track RSI-based momentum using visual candle representation
📌Apply advanced smoothing/filters to the RSI to reduce noise
📌Highlight candle trend strength using dynamic coloring
📌Identify overbought/oversold zones using reference lines (RSI 80 and 20)
🧩 How It Works:
It calculates RSI values for open, high, low, close prices.
These RSI values are then optionally smoothed with user-selected moving averages (EMA, SMA, etc.).
Depending on the selected mode (Normal, Heikin-Ashi, Linear, Rational Quadratic), the RSI values are transformed into synthetic candles.
Candles are colored cyan (uptrend) or red (downtrend) based on RSI movement.
⚙️ Key Inputs:
Method: Type of moving average to smooth the RSI (e.g. EMA, SMA, VWMA, etc.)
Length: Length for RSI and smoothing filters
Candle: Type of candle transformation (Normal, Heikin-Ashi, Linear, Rational Quadratic)
Rational Quadratic: Parameter for the Rational Quadratic smoothing method
📊 Outputs:
Custom candles plotted using RSI-transformed values
Candle colors based on RSI strength:
Cyan for strong bullish RSI movement
Red for strong bearish RSI movement
Horizontal lines at RSI levels 80 and 20 (overbought/oversold)
🧠 Why Use This Indicator?
Unlike traditional RSI indicators that show a line, this tool:
Converts RSI into candle-style visualization
Helps traders visually interpret trend strength, reversals, or continuation patterns
Offers more refined control over RSI behavior and filtering
Provides a unique blend of momentum and candle analysis
❗Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
VCP Scanner (Basic)Scans last 30 candles for at least 2 contractions
Confirms breakout above recent resistance
Validates volume spike on breakout
Plots green label when VCP breakout is detected
Order Block Matrix [Alpha Extract]The Order Block Matrix indicator identifies and visualizes key supply and demand zones on your chart, helping traders recognize potential reversal points and high-probability trading setups.
This tool helps traders:
Visualize key order blocks with volume profile histograms showing liquidity distribution.
Identify high-volume price levels where institutional activity occurs.
rank historical order blocks and analyze their strength based on volume.
Receive alerts for potential trading opportunities based on price-block interactions.
🔶 CALCULATION
The indicator processes chart data to identify and analyze order blocks:
Order Block Detection
Inputs:
Price action patterns (consolidation areas followed by breakouts).
Volume data from current and lower timeframes.
User-defined lookback periods and thresholds.
Detection Logic:
Identifies consolidation areas using a dynamic range comparison.
Confirms breakout patterns with percentage threshold validation.
Maps volume distribution across price levels within each order block.
🔶Volume Analysis
Volume Profiling:
Divides each order block into configurable grid segments.
Maps volume distribution across price segments within blocks.
Highlights zones with highest volume concentration.
Strength Assessment:
Calculates total block volume and relative strength metrics.
Compares block volume to historical averages.
Determines probability of reversal based on volume patterns.
isConsolidation(len) =>
high_range = ta.highest(high, len) - ta.lowest(high, len)
low_range = ta.highest(low, len) - ta.lowest(low, len)
avg_range = (high_range + low_range) / 2
current_range = high - low
current_range <= avg_range * (1 + obThreshold)
🔶 DETAILS
Visual Features
Volume Profile Histograms:
Color-coded bars showing volume concentration within order blocks.
Gradient coloring based on relative volume (high volume = brighter colors).
Bull blocks (green/teal) and bear blocks (red) with varying opacity.
Block Visualization:
Dynamic box sizing based on volume concentration.
Optional block borders and background fills.
Volume labels showing total block volume.
Screener Table:
Real-time analysis of order block metrics.
Shows block direction, proximity, retest count, and volume metrics.
Color-coded for quick reference.
Interpretation
High Volume Areas: Zones with institutional interest and potential reversal points.
Block Direction: Bullish blocks typically support price, bearish blocks typically resist price.
Retests: Multiple tests of an order block may strengthen or weaken its influence.
Block Age: Newer blocks often have stronger influence than older ones.
Volume Concentration: Brightest segments within blocks represent the highest volume areas.
🔶 EXAMPLES
The indicator helps identify key trading opportunities:
Bullish Order Blocks
Support Zones: Identify strong support levels where price is likely to bounce.
Breakout Confirmation: Validate breakouts with volume analysis to avoid false moves.
Retest Strategies: Enter trades when price retests a bullish order block with high volume.
Bearish Order Blocks
Resistance Zones: Identify strong resistance levels where price is likely to reverse.
Distribution Areas: Detect zones where smart money is distributing to retail.
Short Opportunities: Find optimal short entry points at high-volume bearish blocks.
Combined Strategies
Order Block Stacking: Multiple aligned blocks create stronger support/resistance zones.
Block Mitigation: When price breaks through a block, it often indicates a strong trend continuation.
Volume Profile Applications: Higher volume segments provide more precise entry and exit points.
🔶 SETTINGS
Customization Options
Order Block Detection:
Consolidation Lookback: Adjust the period for consolidation detection.
Breakout Threshold: Set minimum percentage for breakout confirmation.
Historical Lookback Limit: Control how far back to scan for historical order blocks.
Maximum Order Blocks: Limit the number of visible blocks on the chart.
Visual Style:
Grid Segments: Adjust the number of volume profile segments.
Extend Blocks to Right: Enable/disable extending blocks to current price.
Show Block Borders: Toggle border visibility.
Border Width: Adjust thickness of block borders.
Show Volume Text: Enable/disable volume labels.
Volume Text Position: Control placement of volume labels.
Color Settings:
Bullish High/Low Volume Colors: Customize appearance of bullish blocks.
Bearish High/Low Volume Colors: Customize appearance of bearish blocks.
Border Color: Set color for block outlines.
Background Fill: Adjust color and transparency of block backgrounds.
Volume Text Color: Customize label appearance.
Screener Table:
Show Screener Table: Toggle table visibility.
Table Position: Select positioning on the chart.
Table Size: Adjust display size.
The Order Block Matrix indicator provides traders with powerful insights into market structure, helping to identify key levels where smart money is active and where high-probability trading opportunities may exist.
Hassan Zig ZagDisplay ZigZag with volume value. This will help to indicate the support and resistance levels based on the top and bottom created by the zigzag when the price is moving. also, the volume will support in taking decision to buy or sill
MirPapaTrendConditionsLibrary "MirPapaTrendConditions"
getMaColor(level)
Parameters:
level (int) : : 1= lowest, 2= low, 3= mid, 4= high, 5= highest, 6= Base
getMA(mode, src, len)
Parameters:
mode (string) : MA 종류
/ @param src 소스
/ @param len 기간
/ @returns 선택된 MA
src (float)
len (simple int)
getMA(maName, src, intLow, intMid, intHigh)
Parameters:
maName (string) : 이동평균 종류
/ @param src 기준 소스
/ @param intLow 단기
/ @param intMid 중기
/ @param intHigh 장기
/ @returns 배열
src (float)
intLow (simple int)
intMid (simple int)
intHigh (simple int)
getMA(maName, src, intLowest, intLow, intMid, intHigh, intHighest, intBase)
Parameters:
maName (string) : 이동평균 종류
/ @param src 기준 소스
/ @param intLowest 초단기
/ @param intLow 단기
/ @param intMid 중기
/ @param intHigh 장기
/ @param intHighest 초장기
/ @param intBase 기준선
/ @returns 배열
src (float)
intLowest (simple int)
intLow (simple int)
intMid (simple int)
intHigh (simple int)
intHighest (simple int)
intBase (simple int)
getStochastic(src, intLen)
Parameters:
src (float) : 기준 소스
/ @param Len 기간
/ @returns 선택된 스토캐스틱
intLen (int)
getStochastic(src, intLow, intMid, intHigh)
Parameters:
src (float) : 기준 소스
/ @param intLow 단기 기간
/ @param intMid 중기 기간
/ @param intHigh 장기 기간
/ @returns
intLow (int)
intMid (int)
intHigh (int)
getStochastic(src, intLowest, intLow, intMid, intHigh, intHighest, intBase)
Parameters:
src (float) : 기준 소스
/ @param intLowest 초단기 기간
/ @param intLow 단기 기간
/ @param intMid 중기 기간
/ @param intHigh 장기 기간
/ @param intHighest 최장기 기간
/ @param intBase 기준선 기간
/ @returns
intLowest (int)
intLow (int)
intMid (int)
intHigh (int)
intHighest (int)
intBase (int)
getRSX(src, intLen)
Parameters:
src (float) : 기준 소스
/ @param intLen 기간
/ @returns 선택된 rsx
intLen (int)
getRSX(src, intLow, intMid, intHigh)
Parameters:
src (float) : 기준 소스
/ @param intLow 중단기
/ @param intMid 중기
/ @param intHigh 장기
/ @returns
intLow (int)
intMid (int)
intHigh (int)
getRSX(src, intLowest, intLow, intMid, intHigh, intHighest, intBase)
Parameters:
src (float) : 기준 소스
/ @param intTiny 초단기
/ @param intLowest 단기
/ @param intLow 중단기
/ @param intMid 중기
/ @param intHigh 장기
/ @param intHighest 초장기
/ @returns
intLowest (int)
intLow (int)
intMid (int)
intHigh (int)
intHighest (int)
intBase (int)
getMACD(src, fastLen, slowLen, signalLen)
Parameters:
src (float) : 기준 소스
/ @param fastLen 빠른 EMA 기간
/ @param slowLen 느린 EMA 기간
/ @param signalLen 시그널 기간
/ @returns
fastLen (simple int)
slowLen (simple int)
signalLen (simple int)
getBollingerBand(src, len, mult)
Parameters:
src (float) : 기준 소스
/ @param len 기준 기간
/ @param mult 표준편차 배수
/ @returns
len (int)
mult (float)
getATR(intLen)
Parameters:
intLen (simple int) : ATR 기간
/ @returns 선택된 ATR
getATR(intLow, intMid, intHigh)
Parameters:
intLow (simple int) : 단기 ATR 기간
/ @param intMid 중기 ATR 기간
/ @param intHigh 장기 ATR 기간
/ @returns 배열
intMid (simple int)
intHigh (simple int)
getATR(intLowest, intLow, intMid, intHigh, intHighest, intBase)
Parameters:
intLowest (simple int)
intLow (simple int)
intMid (simple int)
intHigh (simple int)
intHighest (simple int)
intBase (simple int)
isCross(fastLine, baseLine)
Parameters:
fastLine (float) : 빠른선
/ @param baseLine 기준선
/ @returns 상태
baseLine (float)
isMAtrend(maLow, maMid, maHigh)
Parameters:
maLow (float) : 가장 빠른 MA
/ @param maMid 중간 MA
/ @param maHigh 느린 MA
/ @returns 상태
maMid (float)
maHigh (float)
isMAline(val, valPrev, intBaseLine)
Parameters:
val (float) : 현재 값
/ @param valPrev 이전 값
/ @param intBaseLine 기준값
/ @returns 상태
valPrev (float)
intBaseLine (int)
getStage(v1, v2, v3)
Parameters:
v1 (float) : 첫 번째 값
/ @param v2 두 번째 값
/ @param v3 세 번째 값
/ @returns 1~6
v2 (float)
v3 (float)
getBgColor(stage)
Parameters:
stage (int) : 스테이지 값
/ @returns 색상
getBgColor(stage, transp)
Parameters:
stage (int) : 스테이지 값
/ @param transp 투명도
/ @returns 색상
transp (int)
getBGColor(v1, v2, v3)
Parameters:
v1 (float) : 첫 번째 값
/ @param v2 두 번째 값
/ @param v3 세 번째 값
/ @param transp 투명도
/ @param customColor 사용자 지정 색 (옵션)
/ @returns 색상
v2 (float)
v3 (float)
getBGColor(v1, v2, v3, transp)
Parameters:
v1 (float) : 첫 번째 값
/ @param v2 두 번째 값
/ @param v3 세 번째 값
/ @param transp 투명도
/ @param customColor 사용자 지정 색 (옵션)
/ @returns 색상
v2 (float)
v3 (float)
transp (int)
createStackedLabel(labelText, isUp, maLowest, maLow, maMid, maHigh, maHighest, maBase)
Parameters:
labelText (string) : 라벨 텍스트
/ @param isUp 위/아래 여부
/ @param maTiny~maHighest MA 값들
/ @returns 생성된 라벨
isUp (bool)
maLowest (float)
maLow (float)
maMid (float)
maHigh (float)
maHighest (float)
maBase (float)
isDoubleBottom(src, left, right)
Parameters:
src (float) : 기준 시리즈 (예: 중간 MA 값, low 등)
/ @param left PivotLow 검색 시 좌측 봉 개수
/ @param right PivotLow 검색 시 우측 봉 개수
/ @returns true: 이번 봉에 쌍바닥(이전 PivotLow < 현재 PivotLow) 발생
left (int)
right (int)
isDoubleTop(src, left, right)
Parameters:
src (float) : 기준 시리즈 (예: 중간 MA 값, high 등)
/ @param left PivotHigh 검색 시 좌측 봉 개수
/ @param right PivotHigh 검색 시 우측 봉 개수
/ @returns true: 이번 봉에 쌍봉(이전 PivotHigh > 현재 PivotHigh) 발생
left (int)
right (int)
isFractalHigh(src, left, right)
Parameters:
src (float) : 고가 시리즈 (예: high, 중간 MA 값 등)
/ @param left 좌측 확인 봉 개수
/ @param right 우측 확인 봉 개수
/ @returns true: 프랙탈 하이 발생
left (int)
right (int)
isFractalLow(src, left, right)
Parameters:
src (float) : 저가 시리즈 (예: low, 중간 MA 값 등)
/ @param left 좌측 확인 봉 개수
/ @param right 우측 확인 봉 개수
/ @returns true: 프랙탈 로우 발생
left (int)
right (int)
Long-Term Investing Signals + Trend Formation (Daily)Steven Paul Jobs (February 24, 1955 – October 5, 2011) was an American businessman, inventor, and investor best known for co-founding the technology company Apple Inc. Jobs was also the founder of NeXT and chairman and majority shareholder of Pixar. He was a pioneer of the personal computer revolution of the 1970s and 1980s, along with his early business partner and fellow Apple co-founder Steve Wozniak.
Jobs was born in San Francisco in 1955 and adopted shortly afterwards. He attended Reed College in 1972 before withdrawing that same year. In 1974, he traveled through India, seeking enlightenment before later studying Zen Buddhism. He and Wozniak co-founded Apple in 1976 to further develop and sell Wozniak's Apple I personal computer. Together, the duo gained fame and wealth a year later with production and sale of the Apple II, one of the first highly successful mass-produced microcomputers.
Jobs saw the commercial potential of the Xerox Alto in 1979, which was mouse-driven and had a graphical user interface (GUI). This led to the development of the largely unsuccessful Apple Lisa in 1983, followed by the breakthrough Macintosh in 1984, the first mass-produced computer with a GUI. The Macintosh launched the desktop publishing industry in 1985 (for example, the Aldus Pagemaker) with the addition of the Apple LaserWriter, the first laser printer to feature vector graphics and PostScript.
In 1985, Jobs departed Apple after a long power struggle with the company's board and its then-CEO, John Sculley. That same year, Jobs took some Apple employees with him to found NeXT, a computer platform development company that specialized in computers for higher-education and business markets, serving as its CEO. In 1986, he bought the computer graphics division of Lucasfilm, which was spun off independently as Pixar. Pixar produced the first computer-animated feature film, Toy Story (1995), and became a leading animation studio, producing dozens of commercially successful and critically acclaimed films.
In 1997, Jobs returned to Apple as CEO after the company's acquisition of NeXT. He was largely responsible for reviving Apple, which was on the verge of bankruptcy. He worked closely with British designer Jony Ive to develop a line of products and services that had larger cultural ramifications, beginning with the "Think different" advertising campaign, and leading to the iMac, iTunes, Mac OS X, Apple Store, iPod, iTunes Store, iPhone, App Store, and iPad. Jobs was also a board member at Gap Inc. from 1999 to 2002. In 2003, Jobs was diagnosed with a pancreatic neuroendocrine tumor. He died of tumor-related respiratory arrest in 2011; in 2022, he was posthumously awarded the Presidential Medal of Freedom. Since his death, he has won 141 patents; Jobs holds over 450 patents in total.
(DAFE) DEVMA - Crossover (Deviation Moving Average) (DAFE) DEVMA - Crossover (Deviation Moving Average)
Let’s keep pushing the edge. After the breakthrough of Deviation over Deviation (DoD)—which gave traders a true lens into volatility’s hidden regime shifts—many asked: “What’s next?” The answer is DEVMA: a crossover engine built not on price, but on the heartbeat of the market itself.
Why is this different?
DEVMA isn’t just a moving average crossover. It’s a regime detector that tracks the expansion and contraction of deviation—giving you a real-time readout of when the market’s energy is about to shift. This is the next step for anyone who wants to anticipate volatility, not just react to it.
What sets DEVMA apart:
Volatility-First Logic: Both fast and slow lines are moving averages of deviation, not price. You’re tracking the market’s “energy,” not just its direction. This is the quant edge that most scripts miss.
Regime-Colored Lines:
The fast and slow DEVMA lines change color in real time—green/aqua for expansion, maroon/orange for contraction—so you can see regime shifts at a glance.
Quant-Pro Visuals:
Subtle glow, clean cross markers, and a minimalist dashboard keep your focus on what matters: the regime, not the noise.
Static Regime Thresholds:
Reference lines at 1.5 and 0.5 (custom colors) give you instant context for “normal” vs. “extreme” volatility states.
No Price Chasing:
This isn’t about following price. It’s about anticipating the next volatility regime—before the crowd even knows what’s coming.
How this builds on DoD:
DoD showed you when volatility itself was about to change. DEVMA takes that insight and turns it into a crossover engine—so you can see, filter, and act on regime shifts in real time. If DoD was the radar, DEVMA is the navigation system.
Inputs/Signals—explained for clarity:
Deviation Lookback:
Controls the sensitivity of the regime detector. Shorter = more signals, longer = only the rarest events.
Fast/Slow DEVMA Lengths:
Fine-tune how quickly the regime lines react. Fast for scalping, slow for swing trading.
Source Selection:
Choose from price, volume, volatility, or VoVix. Each source gives you a different lens on market stress. VoVix is for those who want to see the “regime quake” before the aftershocks.
VoVix Parameters:
Fine-tune the volatility-of-volatility engine for your market. Lower ATR Fast = more responsive; higher ATR Slow = more selective.
Bottom line:
DEVMA is for those who want to see the market’s heartbeat, not just its shadow. Use it to filter your trades, time your entries, or simply understand the market’s true rhythm. Every input is there for a reason. Every plot is a direct readout of the quant logic. Use with discipline, and make it your own.
Disclaimer:
Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
To TradingView mods and serious users:
This isn’t just another indicator. This is a quant tool for the next era. If flagged, we’ll keep adapting and republishing until real quant innovation gets its place.
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
US Net Liquidity Tracker with Sentiment & OffsetU.S. Net Liquidity Tracker with Sentiment & Offset - Documentation
This document explains the rationale behind the Pine Script indicator "U.S. Net Liquidity Tracker with Sentiment & Offset" and why it provides an accurate representation of liquidity in the U.S. financial system.
The indicator leverages data from the Federal Reserve's Economic Data (FRED) to calculate net liquidity, offering traders and analysts a tool to assess market conditions influenced by monetary policy.
Purpose of the Indicator
The U.S. Net Liquidity Tracker is designed to measure the amount of liquidity available in the U.S. financial system by accounting for both liquidity injections and drains. Liquidity is a critical factor in financial markets: high liquidity often supports rising asset prices, while low liquidity can signal potential market downturns. This indicator helps users anticipate market trends by providing a clear, data-driven view of net liquidity dynamics.
! raw.githubusercontent.com
Rationale Behind the Indicator
What is U.S. Net Liquidity?
Net liquidity represents the money available in the financial system after subtracting liquidity-draining factors from the total liquidity provided by the Federal Reserve. The indicator calculates this by combining key data points that reflect both the creation and removal of liquidity.
Data Sources
The indicator uses the following FRED datasets:
Fed Balance Sheet (WALCL): Total assets held by the Federal Reserve, including securities from quantitative easing (QE). An expanding balance sheet adds liquidity, while a shrinking one (quantitative tightening, QT) reduces it.
Treasury General Account (WTREGEN): The U.S. Treasury’s cash balance at the Fed. A high balance drains liquidity, while spending releases it into the system.
Overnight Reverse Repurchase Agreements (RRPONTSYD): Short-term operations where the Fed borrows cash from institutions, temporarily reducing available liquidity.
Earnings Remittances (RESPPLLOPNWW): Payments from the Fed to the Treasury, which remove liquidity from circulation.
These components are chosen because they collectively represent the primary sources and drains of liquidity in the U.S. economy, providing a comprehensive view of net liquidity.
Calculation
The core formula for net liquidity is:
global_balance = fed_balance - us_tga_balance - overnight_rrp_balance - earnings_remittances_balance
fed_balance: Total Fed assets (WALCL).
us_tga_balance: Treasury General Account (WTREGEN).
overnight_rrp_balance: Reverse repo operations (RRPONTSYD).
earnings_remittances_balance: Fed remittances to Treasury (RESPPLLOPNWW).
This subtraction isolates the liquidity remaining after accounting for major drains, offering a net perspective on funds available to influence markets.
Additional Features
Smoothing: A Simple Moving Average (SMA) is applied to the net liquidity value to reduce noise and emphasize longer-term trends.
Sentiment Coloring: An Exponential Moving Average (EMA) determines market sentiment:
Bullish (Green): Smoothed liquidity is above the EMA, indicating improving liquidity conditions.
Bearish (Red): Smoothed liquidity is below the EMA, signaling deteriorating conditions.
Offset: Users can shift the liquidity plot forward or backward in time to align it with market data (e.g., S&P 500) for correlation analysis.
Rate of Change (ROC): A plot of the Fed balance sheet’s ROC highlights the pace of monetary policy shifts.
Why This is an Accurate Picture of U.S. Liquidity
The indicator accurately reflects U.S. liquidity for several reasons:
Comprehensive Data:
It incorporates all major liquidity-affecting factors: the Fed’s balance sheet (source) and TGA, reverse repos, and remittances (drains). This holistic approach ensures no significant component is overlooked.
Real-Time Insights:
By pulling data directly from FRED, the indicator reflects current economic conditions, making it relevant for timely decision-making.
Customizability:
Features like toggling components, adjusting smoothing periods, and offsetting the plot allow users to tailor the indicator to their specific analytical needs, enhancing its practical accuracy.
Visual Clarity:
Sentiment coloring and the ROC plot provide intuitive cues about liquidity trends and monetary policy impacts, making complex data actionable.
Conclusion
The "U.S. Net Liquidity Tracker with Sentiment & Offset" is a robust tool for understanding liquidity dynamics in the U.S. financial system. By combining key FRED datasets into a net liquidity calculation, smoothing the results, and adding sentiment and offset features, it delivers an accurate and user-friendly picture of liquidity. This makes it invaluable for traders and analysts seeking to correlate liquidity with market movements and anticipate economic shifts.
Source Code
The source code for this indicator is available on GitHub: ebasurtop/Macro
Disclaimer
All codes and indicators provided by Enrique Basurto are 100% free and open for public use. If you find this work valuable, please consider donating to The Brain Foundation through the Autism Research Coalition to support critical translational research for individuals with autism.
Your contributions help fund vital research initiatives.
Donation Link: Autism Research Coalition
Follow Enrique Basurto on X: @EnriqueBasurto
HMA 200 + EMA 20 Crossover StrategyThis strategy combines a long-term trend filter using the Hull Moving Average (HMA 200) with a short-term entry trigger using the Exponential Moving Average (EMA 20).
📈 Entry Logic:
Buy Entry: When price is above the HMA 200 and crosses above the EMA 20.
Sell Entry: When price is below the HMA 200 and crosses below the EMA 20.
The strategy closes the current position and reverses on the opposite signal.
⚙️ Strategy Settings (Backtest Configuration):
Position size: 10% of equity per trade
Commission: 0.1% per trade (to simulate broker fees)
Slippage: 2 ticks (to reflect realistic fill conditions)
✅ Purpose:
This script is designed to identify high-probability trades in the direction of the overall trend, avoiding whipsaw conditions. It is useful for traders looking for a dynamic crossover-based system that filters trades based on longer-term momentum.
🔎 Make sure to test across multiple assets and timeframes. For best results, apply this strategy to liquid trending markets like major FX pairs, indices, or high-cap stocks.
Multi-Timeframe Continuity Custom Candle ConfirmationMulti-Timeframe Continuity Custom Candle Confirmation
Overview
The Timeframe Continuity Indicator is a versatile tool designed to help traders identify alignment between their current chart’s candlestick direction and higher timeframes of their choice. By coloring bars on the current chart (e.g., 1-minute) based on the directional alignment with selected higher timeframes (e.g., 10-minute, daily), this indicator provides a visual cue for confirming trends across multiple timeframes—a concept known as Timeframe Continuity. This approach is particularly useful for day traders, swing traders, and scalpers looking to ensure their trades align with broader market trends, reducing the risk of trading against the prevailing momentum.
Originality and Usefulness
This indicator is an original creation, built from scratch to address a common challenge in trading: ensuring that price action on a lower timeframe aligns with the trend on higher timeframes. Unlike many trend-following indicators that rely on moving averages, oscillators, or other lagging metrics, this script directly compares the bullish or bearish direction of candlesticks across timeframes. It introduces the following unique features:
Customizable Timeframes: Users can select from a range of higher timeframes (5m, 10m, 15m, 30m, 1h, 2h, 4h, 1d, 1w, 1M) to check for alignment, making it adaptable to various trading styles.
Neutral Candle Handling: The script accounts for neutral candles (where close == open) on the current timeframe by allowing them to inherit the direction of the higher timeframe, ensuring continuity in trend visualization.
Table: A table displays the direction of each selected timeframe and the current timeframe, helping identify direction in the event you don't want to color bars.
Toggles for Flexibility: Options to disable bar coloring and the debug table allow users to customize the indicator’s visual output for cleaner charts or focused analysis.
This indicator is not a mashup of existing scripts but a purpose-built tool to visualize timeframe alignment directly through candlestick direction, offering traders a straightforward way to confirm trend consistency.
What It Does
The Timeframe Continuity Indicator colors bars on your chart when the direction of the current timeframe’s candlestick (bullish, bearish, or neutral) aligns with the direction of the selected higher timeframes:
Lime: The current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes (e.g., 10m) are bullish.
Pink: The current bar is bearish or neutral, and all selected higher timeframes are bearish.
Default Color: If the directions don’t align (e.g., 1m bar is bearish but 10m is bullish), the bar remains the default chart color.
The indicator also includes a debug table (toggleable) that shows the direction of each selected timeframe and the current timeframe, helping traders diagnose alignment issues.
How It Works
The script uses the following methodology:
1. Direction Calculation: For each timeframe (current and selected higher timeframes), the script determines the candlestick’s direction:
Bullish (1): close > open / Bearish (-1): close < open / Neutral (0): close == open
Higher timeframe directions are fetched using Pine Script’s request.security function, ensuring accurate data retrieval.
2. Alignment Check: The script checks if all selected higher timeframes are uniformly bullish (full_bullish) or bearish (full_bearish).
o A higher timeframe must have a clear direction (bullish or bearish) to trigger coloring. If any selected timeframe is neutral, alignment fails, and no coloring occurs.
3. Coloring Logic: The current bar is colored only if its direction aligns with the higher timeframes:
Lime if the higher timeframes are bullish and the current bar is bullish or neutral.
Maroon if the higher timeframes are bearish and the current bar is bearish or neutral.
If the current bar’s direction opposes the higher timeframe (e.g., 1m bearish, 10m bullish), the bar remains uncolored.
Users can disable bar coloring entirely via the settings, leaving bars in their default chart color.
4. Direction Table:
A table in the top-right corner (toggleable) displays the direction of each selected timeframe and the current timeframe, using color-coded labels (green for bullish, red for bearish, gray for neutral).
This feature helps traders understand why a bar is or isn’t colored, making the indicator accessible to users unfamiliar with Pine Script.
How to Use
1. Add the Indicator: Add the "Timeframe Continuity Indicator" to your chart in TradingView (e.g., a 1m chart of SPY).
2. Configure Settings:
Timeframe Selection: Check the boxes for the higher timeframes you want to compare against (default: 10m). Options include 5m, 10m, 15m, 30m, 1h, 2h, 4h, 1D, 1W, and 1M. Select multiple timeframes if you want to ensure alignment across all of them (e.g., 10m and 1d).
Enable Bar Coloring: Default: true (bars are colored lime or maroon when aligned). Set to false to disable coloring and keep the default chart colors.
Show Table: Default: true (table is displayed in the top-right corner). Set to false to hide the table for a cleaner chart.
3. Interpret the Output:
Colored Bars: Lime bars indicate the current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes are bullish. Maroon bars indicate the current bar is bearish or neutral, and all selected higher timeframes are bearish. Uncolored bars (default chart color) indicate a mismatch (e.g., 1m bar is bearish while 10m is bullish) or no coloring if disabled.
Direction Table: Check the table to see the direction of each selected timeframe and the current timeframe.
4. Example Use Case:
On a 1m chart of SPY, select the 10m timeframe.
If the 10m timeframe is bearish, 1m bars that are bearish or neutral will color maroon, confirming you’re trading with the higher timeframe’s trend.
If a 1m bar is bullish while the 10m is bearish, it remains uncolored, signaling a potential misalignment to avoid trading.
Underlying Concepts
The indicator is based on the concept of Timeframe Continuity, a strategy used by traders to ensure that price action on a lower timeframe aligns with the trend on higher timeframes. This reduces the risk of entering trades against the broader market direction. The script directly compares candlestick directions (bullish, bearish, or neutral) rather than relying on lagging indicators like moving averages or RSI, providing a real-time, price-action-based confirmation of trend alignment. The handling of neutral candles ensures that minor indecision on the lower timeframe doesn’t interrupt the visualization of the higher timeframe’s trend.
Why This Indicator?
Simplicity: Directly compares candlestick directions, avoiding complex calculations or lagging indicators.
Flexibility: Customizable timeframes and toggles cater to various trading strategies.
Transparency: The debug table makes the indicator’s logic accessible to all users, not just those who can read Pine Script.
Practicality: Helps traders confirm trend alignment, a key factor in successful trading across timeframes.
[blackcat] L3 Volume Sync TradeOVERVIEW
The L3 Volume Sync Trade indicator empowers traders 📈💹 with advanced tools to pinpoint precise entry and exit points leveraging intricate volume and price momentum analyses. By encapsulating sophisticated technical calculations into an intuitive visual format, this script aids in identifying high-probability trades while minimizing guesswork. Whether you're a seasoned trader looking to enhance your strategy or a newcomer seeking structured guidance, this indicator offers invaluable insights tailored to elevate your trading precision.
FEATURES
Advanced Volume Analysis 📊✨: Employs comprehensive volume dynamics to spot underlying market trends and resonance levels, allowing you to align your trades with significant movements.
Dynamic Price Momentum Metrics ⚡️: Computes both immediate and sustained price strengths, providing a holistic view of market directionality.
Customizable Indicators 🎯: Adjustable periods across multiple moving averages ensure flexibility in adapting the script to diverse trading styles and timeframes.
Intuitive Visual Representation 🖼️: Displays critical information via colorful histograms and candlestick patterns, facilitating quick comprehension even amidst fast-paced markets.
Automated Buy/Sell Labels 🔍: Clearly marks chart locations where buy/sell actions are recommended, reducing the need for constant manual monitoring.
Real-Time Alert Capabilities 🔔: Stay ahead with customizable alerts that notify you instantly whenever favorable trading conditions arise.
HOW TO USE
Initial Setup:
Begin by adding the L3 Volume Sync Trade indicator to your TradingView chart.
Familiarize yourself with the default settings provided within the script’s input parameters.
Configuring Input Parameters:
Short Period: Adjust if focusing on shorter-term fluctuations; defaults at 5 bars.
Long Period: Ideal for capturing broader trends over extended intervals; set initially at 27 bars.
EMA and SMA Periods: Tweak these for fine-tuning the sensitivity of trend-following mechanisms; default values are 3 and 3 respectively.
Long/EMA Periods: These influence smoothing effects; start with 360 and 21 respectively but experiment based on volatility.
Capital Threshold: Defines minimal risk level per trade; default set at 1 unit but can be increased/decreased based on your risk appetite.
Understanding Chart Elements:
Histograms & Candles: Blue/green histograms represent positive-negative resonances, red/green bands signify crossover events, aqua candles denote resonance points, orange highlights trade signals.
Labels: Green “BUY” tags appear above bars indicating bullish conditions; red “SELL” tags below bars suggest bearish reversals.
Activating Alarms:
Go to the alert settings in TradingView.
Enable conditional alerts for buy/sell signals ensuring timely responses without missing crucial moves.
Monitoring Performance:
Keep track of how often alerts trigger versus actual winning trades.
Periodically revisit input adjustments to optimize responsiveness under varying market phases.
ADVANCED USAGE TIPS
Backtesting Your Strategy: Before going live, apply historical data tests to gauge reliability.
Combining With Other Tools: Enhance accuracy by integrating additional indicators like RSI or MACD alongside Volume Sync.
Risk Management Integration: Use stop-loss/take-profit markers derived from script outputs to safeguard capital efficiently.
LIMITATIONS
Market Conditions Variability: Different assets or volatile environments might yield inconsistent outcomes.
Dependent On User Expertise: Best utilized by those familiar with technical analysis fundamentals.
Limited Flexibility In Real-time Adjustments: Once applied, real-time tweaking requires reloading script which might delay responses during rapid market shifts.
NOTES
Parameter Sensitivity: Minor changes can lead to drastic differences; always test modifications cautiously.
Regular Reviews: Continuously assess indicator efficacy against evolving market behaviors.
Complementary Techniques: Supplement this script with fundamental analysis or news-driven insights for well-rounded decisions.
THANKS
A heartfelt acknowledgment goes to our community of developers and enthusiasts whose feedback has been instrumental in refining this powerful indicator.
Historical & Periodic Key LevelsThis TradingView indicator ("Historical & Periodic Key Levels" 📈) automatically plots significant price levels on your chart, providing a clear visual reference for potential support and resistance areas.
Key Levels Displayed 🔑:
* All-Time High (ATH) 🔼: The highest price reached in the available history for the instrument.
* All-Time Low (ATL) 🔽: The lowest price reached in the available history for the instrument.
* Previous Daily Close D: The closing price of the previous trading day.
* Previous Weekly Close W: The closing price of the previous trading week.
* Previous Monthly Close M: The closing price of the previous trading month.
* Previous Yearly Close Y: The closing price of the previous trading year.
Features ✨:
* Clear Visualization 👁️: Levels are plotted as horizontal lines, extending to the most recent bar.
* Customizable Visibility 🕶️: Toggle the display of each key level type (ATH, ATL, Daily, Weekly, Monthly, Yearly closes) individually via the input settings.
* Customizable Colors 🎨: Set distinct colors for ATH, ATL, and each of the periodic close lines to suit your charting preferences.
* Adjustable Line Width ―: Control the thickness of the ATH/ATL lines and the periodic close lines separately.
* Informative Labels 🏷️: On the most recent bar, labels display the value and type of each active level (e.g., "ATH - 01/01/23", "D Close"). The ATH/ATL labels also include the date the level was established.
* Dynamic Updates 🔄: ATH and ATL levels update automatically if new highs or lows are made.
How to Use 🛠️:
1. Add the "Key Levels" indicator to your TradingView chart.
2. In the indicator settings, customize which levels you want to see (ATH, ATL, Daily Close, etc.).
3. Adjust the colors and line widths for optimal visibility on your chart setup.
4. Use the plotted lines as potential reference points for support, resistance, and overall market context.
This indicator is useful for traders who employ key historical and periodic price levels in their technical analysis strategy. It helps in quickly identifying significant price points without manual plotting.
Created by YouNesta ✍️
Linear Regression Volume | Lyro RSLinear Regression Volume | Lyro RS
⚠️Disclaimer⚠️
Always combine this indicator with other forms of analysis and risk management. Please do your own research before making any trading decisions.
The LR Volume | 𝓛𝔂𝓻𝓸 𝓡𝓢 indicator blends linear regression with volume-adjusted moving average s to dynamically outline price equilibrium and trend intensity. By integrating volume into its regression model, it highlights meaningful price movement relative to trading activity.
📌 How It Works:
Volume-Weighted Regression Baseline
Price is filtered through one of four volume-adjusted moving averages (SMA, RMA, HMA, ALMA) before being passed through a linear regression model, forming a dynamic fair value line.
Deviation Bands
The indicator plots 1x, 2x, and 3x standard deviation zones above and below the baseline, helping identify potential extremes, volatility spikes, and mean reversion areas.
Slope-Based Color Logic
The baseline and fill areas are dynamically colored:
- 🟢 Green for positive slope (uptrend)
- 🔴 Red for negative slope (downtrend)
- ⚪ Gray for neutral movement
⚙️ Inputs & Options:
Regression Length – Controls how many bars are used in the moving average and regression calculation.
Deviation Multiplier – Adjusts the width of the bands surrounding the regression baseline.
MA Type – Choose from 4 types:
SMA (Simple Moving Average)
RMA (Relative Moving Average)
HMA (Hull Moving Average)
ALMA (Arnaud Legoux Moving Average)
Band Colors – Customizable upper/lower band colors to match your visual style.
🔔 Alerts:
Long Signal – Triggers when the regression slope turns positive.
Short Signal – Triggers when the regression slope turns negative.
Economic Event DatesThis TradingView indicator ("Economic Event Dates") plots significant economic event dates directly on your chart, helping you stay informed about potential market-moving announcements. It includes pre-configured dates for:
* **FOMC Meetings:** Key policy meetings of the Federal Open Market Committee.
* **CPI Releases:** Consumer Price Index data releases, a key measure of inflation.
* **Bitcoin Halvings:** Programmatic reductions in Bitcoin's new supply issuance.
**Features:**
* **Customizable Dates:** Easily input and manage dates for FOMC, CPI, and Halving events for current and future years (2025, 2026, and beyond for Halvings).
* **Visual Cues:** Displays vertical lines on the chart at the precise time of each event.
* **Event Labels:** Shows clear labels (e.g., "FOMC", "CPI", "Halving") for each event line.
* **Color Coding:** Distinct colors for FOMC (blue), CPI (orange), and Halving (purple) events for quick identification.
* **Future Events Focus:** Option to display only upcoming events relative to the current real time.
* **Morning Alerts:** (Optional) Triggers an alert on the morning of a scheduled event, providing a timely reminder.
* **Customizable Appearance:** Adjust line width and toggle label visibility.
**How to Use:**
1. Add the indicator to your TradingView chart.
2. Review and update the input dates for FOMC, CPI, and Halving events in the indicator settings. The script includes placeholders and notes for future dates that may require verification from official sources (e.g., federalreserve.gov, bls.gov).
3. Customize colors, line width, label visibility, and alert preferences as needed.
4. Observe the vertical lines on your chart indicating upcoming economic events.
This tool is designed for traders and investors who want to incorporate awareness of major economic events into their market analysis. Remember to verify future event dates as they are officially announced.
Created by YouNesta
remaLibrary " REMA "
Custom Regional Exponential Moving Average with enhanced sensitivity to recent price action
Description: What Makes REMA Unique?
REMA introduces a dual-region weighting system that intelligently balances short-term responsiveness with long-term trend context, solving the fundamental limitation of standard EMAs where longer periods necessarily sacrifice recent price sensitivity.
Key Differences from Standard EMA:
Adaptive Regional Weighting: Applies stronger exponential decay to recent price data while maintaining appropriate weighting for historical context.
Maintains Responsiveness at Any Length: Unlike standard EMAs where longer periods become progressively less responsive, REMA preserves significant sensitivity to recent price action even at 100+ period lengths.
Mathematically Sound Enhancement: Preserves the core mathematical integrity of exponential averaging while introducing region-specific weighting that better reflects how traders actually interpret price action.
Value to TradingView Community:
Improved Signal Timing: Detects reversals 1-3 bars earlier than traditional EMAs without increasing false signals.
Better Multi-Timeframe Analysis: Provides more consistent behavior across different period settings, reducing conflicting signals between timeframes.
Ideal for Modern Markets: Better handles today's high-volatility, algorithm-driven markets where traditional indicators often lag too much to be effective.
Optimized for Both Trend and Reversal Trading: Simultaneously provides strong trend-following capabilities while remaining sensitive to legitimate reversal signals.
Computation Efficiency: The fast implementation offers enhanced capabilities with minimal computational overhead, making it practical for real-time analysis.
REMA fills a critical gap between lagging long-period EMAs and noisy short-period EMAs, giving traders a single, versatile tool that adapts to market conditions more effectively than standard technical indicators.
Implementation:
rema(src, length, recency_bias, transition_point)
Regional Exponential Moving Average that maintains recent price sensitivity even with long lookback periods
Parameters:
src (float) : Input source series
length (int) : Overall EMA period length
recency_bias (float) : Weighting factor to increase sensitivity to recent prices (1.0-3.0 recommended)
transition_point (float) : Percentage point (0.0-1.0) in the lookback period where weighting shifts from recent to historical
Returns: Custom exponentially weighted moving average with regional bias
rema_fast(src, length, recency_bias)
Simplified Regional EMA that uses a recursive calculation method
Parameters:
src (float) : Input source series
length (int) : Overall EMA period
recency_bias (float) : Factor to increase sensitivity to recent price (1.0-3.0 recommended)
Returns: Computationally efficient regional EMA
