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Tìm kiếm tập lệnh với "Cycle"

QLitCycle QuarterlyQLITCYCLE QLitCycle is an intraday cycle visualization tool that divides each trading day into multiple segments, helping traders identify time-based patterns and recurring market behaviors. By splitting the day into distinct periods, this indicator allows for better analysis of intraday rhythms, cycle alignment, and time-specific market tendencies. It can be applied to various markets and timeframes, but is most effective on intraday charts where precise time segmentation can reveal valuable insights.
Chỉ báo Pine Script®
của grttat
CirclesCircles - Support & Resistance Levels Overview This indicator plots horizontal support and resistance levels based on W.D. Gann's mathematical approach of dividing 360 degrees by 2 and by 3. These divisions create natural price magnetism points that have historically acted as significant support and resistance levels across all markets and timeframes. How It Works 360÷2 Levels (Blue): 5.63, 11.25, 33.75, 56.25, 78.75, etc. 360÷3 Levels (Red): 7.5, 15, 30, 37.5, 52.5, 60, 75, etc. Both Levels (Yellow): 22.5, 45, 67.5, 90, 112.5, 135, 157.5, 180 - These are "doubly strong" as they appear in both calculations Key Features Auto-Scaling: Automatically adjusts for any price range (from $0.001 altcoins to $100K+ Bitcoin) Manual Scaling: Choose from 0.001x to 1000x multipliers or set custom values Full Customization: Colors, line widths, styles (solid/dashed/dotted) Historical View: Option to show all levels regardless of current price Clean Display: Adjustable label positioning and line extensions Use Cases Identify potential reversal zones before price reaches them Set profit targets and stop losses at key mathematical levels Confirm breakouts when price decisively moves through major levels Works on all timeframes and all markets (stocks, crypto, forex, commodities) Gann Theory W.D. Gann believed that markets move in mathematical harmony based on geometric angles and time cycles. These 360-degree divisions represent natural balance points where price often finds support or resistance, making them valuable for both short-term trading and long-term analysis. Perfect for traders who use: Support/Resistance trading Fibonacci levels Pivot points Mathematical/geometric analysis Multi-timeframe analysis
Chỉ báo Pine Script®
của polyslyme
16
Bitcoin NUPL IndicatorThe Bitcoin NUPL (Net Unrealized Profit/Loss) Indicator is a powerful metric that shows the difference between Bitcoin's market cap and realized cap as a percentage of market cap. This indicator helps identify different market cycle phases, from capitulation to euphoria. // How It Works NUPL measures the aggregate profit or loss held by Bitcoin investors, calculated as: ``` NUPL = ((Market Cap - Realized Cap) / Market Cap) * 100 ``` // Market Cycle Phases The indicator automatically color-codes different market phases: • **Deep Red (< 0%)**: Capitulation Phase - Most coins held at a loss, historically excellent buying opportunities • **Orange (0-25%)**: Hope & Fear Phase - Early accumulation, price uncertainty and consolidation • **Yellow (25-50%)**: Optimism & Anxiety Phase - Emerging bull market, increasing confidence • **Light Green (50-75%)**: Belief & Denial Phase - Strong bull market, high conviction • **Bright Green (> 75%)**: Euphoria & Greed Phase - Potential market top, historically good profit-taking zone // Features • Real-time NUPL calculation with customizable smoothing • RSI indicator for additional momentum confirmation • Color-coded background reflecting current market phase • Reference lines marking key transition zones • Detailed metrics table showing NUPL value, market sentiment, market cap, realized cap, and RSI // Strategy Applications • **Long-term investors**: Use extreme negative NUPL values (deep red) to identify potential bottoms for accumulation • **Swing traders**: Look for transitions between phases for potential trend changes • **Risk management**: Consider taking profits when entering the "Euphoria & Greed" phase (bright green) • **Mean reversion**: Watch for overbought/oversold conditions when NUPL reaches historical extremes // Settings • **RSI Length**: Adjusts the period for RSI calculation • **NUPL Smoothing Length**: Applies moving average smoothing to reduce noise // Notes • Premium TradingView subscription required for Glassnode and Coin Metrics data • Best viewed on daily timeframes for macro analysis • Historical NUPL extremes have often marked cycle bottoms and tops • Use in conjunction with other indicators for confirmation
Chỉ báo Pine Script®
của toeron
Simple Parallel Channel TrackerThis script will automatically draw price channels with two parallel trends lines, the upper trendline and lower trendline. These lines can be changed in terms of appearance at any time. The Script takes in fractals from local and historic price action points and connects them over a certain period or amount of candles as inputted by the user. It tracks the most recent highs and lows formed and uses this data to determine where the channel begins. The Script will decide whether to use the most recent high, or low, depending on what comes first. Why is this useful? Often, Traders either have no trend lines on their charts, or they draw them incorrectly. Whichever category a trader falls into, there can only be benefits from having Trend lines and Parallel Channels drawn automatically. Trends naturally occur in all Markets, all the time. These oscillations when tracked allow for a more reliable following of Markets and management of Market cycles.
Chỉ báo Pine Script®
của WillSebastian
2
Abdozo - Highlight First DaysAbdozo - Highlight First Days Indicator This Pine Script indicator helps traders easily identify key timeframes by highlighting the first trading day of the week and the first day of the month. It provides visual markers directly on your chart, helping you stay aware of potential market trends and turning points. Features: - Highlight First Day of the Week (Monday): Automatically marks Mondays to help you track weekly market cycles. - Highlight First Day of the Month: Spot the start of each month with ease to analyze monthly performance and trends.
Chỉ báo Pine Script®
của Abdozo
Market Health MonitorThe Market Health Monitor is a comprehensive tool designed to assess and visualize the economic health of a market, providing traders with vital insights into both current and future market conditions. This script integrates a range of critical economic indicators, including unemployment rates, inflation, Federal Reserve funds rates, consumer confidence, and housing market indices, to form a robust understanding of the overall economic landscape. Drawing on a variety of data sources, the Market Health Monitor employs moving averages over periods of 3, 12, 36, and 120 months, corresponding to quarterly, annual, three-year, and ten-year economic cycles. This selection of timeframes is specifically chosen to capture the nuances of economic movements across different phases, providing a balanced view that is sensitive to both immediate changes and long-term trends. Key Features: Economic Indicators Integration: The script synthesizes crucial economic data such as unemployment rates, inflation levels, and housing market trends, offering a multi-dimensional perspective on market health. Adaptability to Market Conditions: The inclusion of both short-term and long-term moving averages allows the Market Health Monitor to adapt to varying market conditions, making it a versatile tool for different trading strategies. Oscillator Thresholds for Recession and Growth: The script sets specific thresholds that, when crossed, indicate either potential economic downturns (recessions) or periods of growth (expansions), allowing traders to anticipate and react to changing market conditions proactively. Color-Coded Visualization: The Market Health Monitor employs a color-coding system for ease of interpretation: -- A red background signals unhealthy economic conditions, cautioning traders about potential risks. -- A bright red background indicates a confirmed recession, as declared by the NBER, signaling a critical time for traders to reassess risk exposure. -- A green background suggests a healthy market with expected economic expansion, pointing towards growth-oriented opportunities. Comprehensive Market Analysis: By combining various economic indicators, the script offers a holistic view of the market, enabling traders to make well-informed decisions based on a thorough understanding of the economic environment. Key Criteria and Parameters: Economic Indicators: Labor Market: The unemployment rate is a critical indicator of economic health. High or rising unemployment indicates reduced consumer spending and economic stress. Inflation: Key for understanding monetary policy and consumer purchasing power. Persistent high inflation can lead to economic instability, while deflation can signal weak demand. Monetary Policy: Reflected by the Federal Reserve funds rate. Changes in the rate can influence economic activity, borrowing costs, and investor sentiment. Consumer Confidence: A predictor of consumer spending and economic activity. Reflects the public’s perception of the economy Housing Market: The housing market often leads the economy into recession and recovery. Weakness here can signal broader economic problems. Market Data: Stock Market Indices: Reflect overall investor sentiment and economic expectations. No gains in a stock market could potentially indicate that economy is slowing down. Credit Conditions: Indicated by the tightness of bank lending, signaling risk perception. Commodity Insight: Crude Oil Prices: A proxy for global economic activity. Indicator Timeframe: A default monthly timeframe is chosen to align with the release frequency of many economic indicators, offering a balanced view between timely data and avoiding too much noise from short-term fluctuations. Surely, it can be chosen by trader / analyst. The Market Health Monitor is more than just a trading tool—it's a comprehensive economic guide. It's designed for traders who value an in-depth understanding of the economic climate. By offering insights into both current conditions and future trends, it encourages traders to navigate the markets with confidence, whether through turbulent times or in periods of growth. This tool doesn't just help you follow the market—it helps you understand it.
Chỉ báo Pine Script®
của mezor13
Dark Energy Divergence OscillatorThe Dark Energy Divergence Oscillator (DEDO) What makes The Universe grow at an accelerating pace? Dark Energy. What makes The Economy grow at an accelerating pace? Debt. Debt is the Dark Energy of The Economy. I pronounce DEDO "Deed-oh", but variations are fine with me. Note: The Pine Script version of DEDO is improved from the original formula, which used a constant all-time high calculation in the normalization factor. This was technically not as accurate for calculating liquidity pressure in historical data because it meant that historical prices were being tested against future liquidity factors. Now using Pine, the functions can be normalized for the bar at the time of calculation, so the liquidity factors are normalized per candle, not across the entire series, which feels like an improvement to me. Thought Process: It's all about the liquidity. What I started with is a correlation between major stock indices such as SPX and WRESBAL , a balance sheet metric on FRED After September 2008, when QE was initiated, many asset valuations started to follow more closely with liquidity factors. This led me to create a function that could combine asset prices and liquidity in WRESBAL , in order to calculate their divergence and chart the signal in TradingView. The original formula: First, we don't want "non-QE" data. we only want data for the market affected by QE . So, find SPX on the day of pre-QE: 1255.08 and subtract that from the 2022 top 4818.62 = 3563.54 With this post-QE SPX range, now you can normalize the price level simply by dividing by the range = ( SPX -1255.08)/3563.54) Normalization produces values from 0 to 1 so that they can be compared with other normalized figures. In order to test the 0 to 1 normalized SPX range measure against the liquidity number, WRESBAL , it's the same idea: normalize it using the max as the denominator and you get a 0 to 1 liquidity index: ( WRESBAL /4276000000000) Subtract one from the other to get the divergence: (( WRESBAL /4276000000000)-(( SPX -1255.08)/3563.54))*10 x10 to reduce decimal places, but this option is configurable in DEDO's input settings tab. Positive values indicate there's ample liquidity to hold up price or even create bullish momentum in some cases. Negative values mean price levels are potentially extended beyond what liquidity levels can support. Note: many viewers of the charts on social media wanted the values to go down in alignment with price moving down, so inverting the chart is what I do with Option + I. I like the fact that negative values represent a deficit in liquidity to hold up price but that's just me. Now with Pine Script and some help from other liquidity focused accounts on TradingView , I was able to derive a script that includes central bank liquidity and Reverse Repo liquidity drain, all in one algorithm, with adjustable settings. Central bank assets included in this version: -JPY (Japan) -CNY (China) -UK (British Pound) -SNB (Swiss National Bank) -ECB (European Central Bank ) Central Bank assets can be adjusted to an allocation % so that the formula is adjusted for the market cap of the asset. A handy table in the lower right corner displays useful information about the asset market cap, and percentage it represents in the liquidity pool. Reverse repo soak is also an optional addition in the Input settings using the RRPONTSYD value from FRED. This value is subtracted from global liquidity used to determine divergence since it is swept away from markets when residing in the Fed's reverse repo facility. There is an option to draw a line at the Zero bound. This provides a convenience so that the line doesn't keep having to be redrawn on every chart. The normalized equation produces a value that should oscillate around zero, as price/valuation grows past liquidity support, falls under it, and repeats in cycles.
Chỉ báo Pine Script®
của DarklyEnergized
3
S&P 500 Quandl Data & RatiosTradingView has a little-known integration that allows you to pull in 3rd party data-sets from Nasdaq Data Link, also known as Quandl. Today, I am open-sourcing for the community an indicator that uses the Quandl integration to pull in historical data and ratios on the S&P500. I originally coded this to study macro P/E ratios during peaks and troughs of boom/bust cycles. The indicator pulls in each of the following datasets, as defined and provided by Quandl. The user can select which datasets to pull in using the indicator settings: Dividend Yield : S&P 500 dividend yield (12 month dividend per share)/price. Yields following June 2022 (including the current yield) are estimated based on 12 month dividends through June 2022, as reported by S&P. Sources: Standard & Poor's for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields. Price Earning Ratio : Price to earnings ratio, based on trailing twelve month as reported earnings. Current PE is estimated from latest reported earnings and current market price. Source: Robert Shiller and his book Irrational Exuberance for historic S&P 500 PE Ratio. CAPE/Shiller PE Ratio : Shiller PE ratio for the S&P 500. Price earnings ratio is based on average inflation-adjusted earnings from the previous 10 years, known as the Cyclically Adjusted PE Ratio (CAPE Ratio), Shiller PE Ratio, or PE 10 FAQ. Data courtesy of Robert Shiller from his book, Irrational Exuberance. Earnings Yield : S&P 500 Earnings Yield. Earnings Yield = trailing 12 month earnings divided by index price (or inverse PE) Yields following March, 2022 (including current yield) are estimated based on 12 month earnings through March, 2022 the latest reported by S&P. Source: Standard & Poor's Price Book Ratio : S&P 500 price to book value ratio. Current price to book ratio is estimated based on current market price and S&P 500 book value as of March, 2022 the latest reported by S&P. Source: Standard & Poor's Price Sales Ratio : S&P 500 Price to Sales Ratio (P/S or Price to Revenue). Current price to sales ratio is estimated based on current market price and 12 month sales ending March, 2022 the latest reported by S&P. Source: Standard & Poor's Inflation Adjusted SP500 : Inflation adjusted SP500. Other than the current price, all prices are monthly average closing prices. Sources: Standard & Poor's Robert Shiller and his book Irrational Exuberance for historic S&P 500 prices, and historic CPIs. Revenue Per Share : Trailing twelve month S&P 500 Sales Per Share (S&P 500 Revenue Per Share) non-inflation adjusted current dollars. Source: Standard & Poor's Earnings Per Share : S&P 500 Earnings Per Share. 12-month real earnings per share inflation adjusted, constant August, 2022 dollars. Sources: Standard & Poor's for current S&P 500 Earnings. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Earnings. Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Chỉ báo Pine Script®
của TradeAutomation
7
ln(close/20 sma) adjusted for time (BTC)(This indicator was designed for the BTC index chart) Designed for Bitcoin. Plots the log of the close/20W SMA with a linear offset m*t, where m is the gradient I've chosen and t is the candle index. Anything above 1 is a mania phase/market cycle top. If it peaks around 0.92 and rolls over, it could be a local/market cycle top. This will obviously not work at all in the long term as Bitcoin will not continue following the trend line on the log plot (you can even see it start to deviate in the Jan-Feb 2021 peaks where the indicator went to 1.15). It identifies the 2011, 2013 (both of them), 2017 tops as being just above 1. It also identifies the 2019 local peak and 2021 market cycle top at ~0.94. Feel free to change the gradient or even add a function to curve the straight line eventually. I made this for fun, feel free to use it as you wish.
Chỉ báo Pine Script®
của Alliegaytor
Modern Economic Eras DashboardOverview This script provides a historical macroeconomic visualization of U.S. markets, highlighting long-term structural "eras" such as the Bretton Woods period, the inflationary 1970s, and the post-2020 "Age of Disorder." It overlays key economic indicators sourced from FRED (Federal Reserve Economic Data) and displays notable market crashes, all in a clean and rescaled format for easy comparison. Data Sources & Indicators All data is loaded monthly from official FRED series and rescaled to improve readability: 🔵 Real GDP (FRED:GDP): Total output of the U.S. economy. 🔴 Inflation Index (FRED:CPIAUCSL): Consumer price index as a proxy for inflation. ⚪ Debt to GDP (FRED:GFDGDPA188S): Federal debt as % of GDP. 🟣 Labor Force Participation (FRED:CIVPART): % of population in the labor force. 🟠 Oil Prices (FRED:DCOILWTICO): Monthly WTI crude oil prices. 🟡 10Y Real Yield (FRED:DFII10): Inflation-adjusted yield on 10-year Treasuries. 🔵 Symbol Price: Optionally overlays the charted asset’s price, rescaled. Historical Crashes The dashboard highlights 10 major U.S. market crashes, including 1929, 2000, and 2008, with labeled time spans for quick context. Era Classification Six macroeconomic eras based on Deutsche Bank’s Long-Term Asset Return Study (2020) are shaded with background color. Each era reflects dominant economic regimes—globalization, wars, monetary systems, inflationary cycles, and current geopolitical disorder. Best Use Cases ✅ Long-term macro investors studying structural market behavior ✅ Educators and analysts explaining economic transitions ✅ Portfolio managers aligning strategy with macroeconomic phases ✅ Traders using history for cycle timing and risk assessment Technical Notes Designed for monthly timeframe, though it works on weekly. Uses close price and standard request.security calls for consistency. Max labels/lines configured for broader history (from 1860s to present). All plotted series are rescaled manually for better visibility. Originality This indicator is original and not derived from built-in or boilerplate code. It combines multiple economic dimensions and market history into one interactive chart, helping users frame today's markets in a broader structural context.
Chỉ báo Pine Script®
của jtomasfg
Log Regression OscillatorThe Log Regression Oscillator transforms the logarithmic regression curves into an easy-to-interpret oscillator that displays potential cycle tops/bottoms. 🔶 USAGE Calculating the logarithmic regression of long-term swings can help show future tops/bottoms. The relationship between previous swing points is calculated and projected further. The calculated levels are directly associated with swing points, which means every swing point will change the calculation. Importantly, all levels will be updated through all bars when a new swing is detected. The "Log Regression Oscillator" transforms the calculated levels, where the top level is regarded as 100 and the bottom level as 0. The price values are displayed in between and calculated as a ratio between the top and bottom, resulting in a clear view of where the price is situated. The main picture contains the Logarithmic Regression Alternative on the chart to compare with this published script. Included are the levels 30 and 70. In the example of Bitcoin, previous cycles showed a similar pattern: the bullish parabolic was halfway when the oscillator passed the 30-level, and the top was very near when passing the 70-level. 🔹 Proactive A "Proactive" option is included, which ensures immediate calculations of tentative unconfirmed swings. Instead of waiting 300 bars for confirmation, the "Proactive" mode will display a gray-white dot (not confirmed swing) and add the unconfirmed Swing value to the calculation. The above example shows that the "Calculated Values" of the potential future top and bottom are adjusted, including the provisional swing. When the swing is confirmed, the calculations are again adjusted, showing a red dot (confirmed top swing) or a green dot (confirmed bottom swing). 🔹 Dashboard When less than two swings are available (top/bottom), this will be shown in the dashboard. The user can lower the "Threshold" value or switch to a lower timeframe. 🔹 Notes Logarithmic regression is typically used to model situations where growth or decay accelerates rapidly at first and then slows over time, meaning some symbols/tickers will fit better than others. Since the logarithmic regression depends on swing values, each new value will change the calculation. A well-fitted model could not fit anymore in the future. Users have to check the validity of swings; for example, if the direction of swings is downwards, then the dataset is not fitted for logarithmic regression. In the example above, the "Threshold" is lowered. However, the calculated levels are unreliable due to the swings, which do not fit the model well. Here, the combination of downward bottom swings and price accelerates slower at first and faster recently, resulting in a non-fit for the logarithmic regression model. Note the price value (white line) is bound to a limit of 150 (upwards) and -150 (down) In short, logarithmic regression is best used when there are enough tops/bottoms, and all tops are around 100, and all bottoms around 0. Also, note that this indicator has been developed for a daily (or higher) timeframe chart. 🔶 DETAILS In mathematics, the dot product or scalar product is an algebraic operation that takes two equal-length sequences of numbers (arrays) and returns a single number, the sum of the products of the corresponding entries of the two sequences of numbers. The usual way is to loop through both arrays and sum the products. In this case, the two arrays are transformed into a matrix, wherein in one matrix, a single column is filled with the first array values, and in the second matrix, a single row is filled with the second array values. After this, the function matrix.mult() returns a new matrix resulting from the product between the matrices m1 and m2. Then, the matrix.eigenvalues() function transforms this matrix into an array, where the array.sum() function finally returns the sum of the array's elements, which is the dot product. dot(x, y)=> if x.size() > 1 and y.size() > 1 m1 = matrix.new() m2 = matrix.new() m1.add_col(m1.columns(), y) m2.add_row(m2.rows (), x) m1.mult (m2) .eigenvalues() .sum() 🔶 SETTINGS Threshold: Period used for the swing detection, with higher values returning longer-term Swing Levels. Proactive: Tentative Swings are included with this setting enabled. Style: Color Settings Dashboard: Toggle, "Location" and "Text Size"
Chỉ báo Pine Script®
của fikira
4
IDRV – Market Structure & Projection ("cup and handle")1. Market Context 1. IDRV has completed a multi-month bottoming structure resembling a rounded accumulation base. 2. Price has broken above local resistance, confirming a bullish shift in trend. 3. RSI signals alternating bear/bull divergences, showing momentum compression before expansion. 2. Accumulation & Breakout Structure 4. Multiple higher lows since early 2024 indicate sustained accumulation. 5. The breakout above the neckline marks the beginning of an upward trend cycle. 6. Volume and structure support continuation rather than a fake-out. 3. Bullish Continuation Zone 7. The chart highlights a bullish expansion zone between $38 and $42. 8. Holding above this zone confirms trend strength and supports further upside. 9. A clean retest in this area offers a high-probability reload opportunity. 4. Projection Target 10. The projected upside shows a potential +56% move, targeting the $48–$52 region. 11. This aligns with previous supply zones and Fibonacci extension symmetry. 12. Price is expected to follow an ascending impulse pattern into 2026. 5. Risk Management 13. Invalidations occur below the $34–$35 support band where trend structure breaks. 14. A loss of this zone signals a likely return to the accumulation range. 15. Watch RSI bear signals during the climb for early signs of exhaustion. 6. Summary 16. Rounded base → Breakout → Retest → Expansion. 17. Structure supports continued bullish momentum into 2026. 18. Target zone remains $48–$52 if support is maintained.
Chỉ báo Pine Script®
của Tomerrevaya
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing. What is “seasonality” in markets? Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol. Why seasonality matters It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups. It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly. It improves execution: entering during historically favorable windows, avoiding historically noisy windows. It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves. How traders use seasonality in practice Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering. Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk. Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL. Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you. Why Day-of-Week (DOW) can be especially helpful Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal. Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage. DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced. What this indicator does Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month . Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average). Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level. Sample guards : Enforce a minimum sample size so thin data doesn’t mislead. Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation. Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag. How it’s calculated (under the hood) Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window. Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month). For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval . Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size). How to read the heatmap Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower. Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays). Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability. n = sample size : More samples = more reliability. Treat small-n bins with skepticism. Suggested workflows Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width. Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing. Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage. Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries. Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects. Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.” Parameter guidance Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects. Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window. Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins. Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small. Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding. Interpreting common patterns Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation. Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly. High-volume bins : Better expected execution quality; schedule size here if slippage matters. Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates. Best practices Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates). Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window. Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger. Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1. Limitations & notes History-dependent: short histories or sparse intraday data reduce reliability. Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias. Aggregation bias: changing session hours or symbol migrations can distort older samples. CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing. Quick setup Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge. Flip to Hour of Day on intraday charts to schedule precise entries/exits. Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual. The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
Chỉ báo Pine Script®
của BackQuant
The Mayan CalendarThis indicator displays the current date in the Mayan Calendar, based on real-time UTC time. It calculates and presents: 🌀 Long Count (Baktun.Katun.Tun.Uinal.Kin) – A linear count of days since the Mayan epoch (August 11, 3114 BCE). 🔮 Tzolk'in Date – A 260-day sacred cycle combining a number (1–13) and one of 20 day names (e.g., 4 Ajaw). 🌾 Haab' Date – A 365-day civil cycle divided into 18 months of 20 days + 5 "nameless" days (Wayeb'). The calculations follow Smithsonian standards and align with the Maya Calendar Converter from the National Museum of the American Indian: 👉 maya.nmai.si.edu The results are shown in a table overlay on your chart's top-right corner. This indicator is great for symbolic traders, astro enthusiasts, or anyone interested in ancient timekeeping systems woven into financial timeframes. Enjoy, time travelers! ⌛
Chỉ báo Pine Script®
của BarefootJoey
4
Logarithmic Regression AlternativeLogarithmic regression is typically used to model situations where growth or decay accelerates rapidly at first and then slows over time. Bitcoin is a good example. 𝑦 = 𝑎 + 𝑏 * ln(𝑥) With this logarithmic regression (log reg) formula 𝑦 (price) is calculated with constants 𝑎 and 𝑏, where 𝑥 is the bar_index . Instead of using the sum of log x/y values, together with the dot product of log x/y and the sum of the square of log x-values, to calculate a and b, I wanted to see if it was possible to calculate a and b differently. In this script, the log reg is calculated with several different assumed a & b values, after which the log reg level is compared to each Swing. The log reg, where all swings on average are closest to the level, produces the final 𝑎 & 𝑏 values used to display the levels. 🔶 USAGE The script shows the calculated logarithmic regression value from historical swings, provided there are enough swings, the price pattern fits the log reg model, and previous swings are close to the calculated Top/Bottom levels. When the price approaches one of the calculated Top or Bottom levels, these levels could act as potential cycle Top or Bottom. Since the logarithmic regression depends on swing values, each new value will change the calculation. A well-fitted model could not fit anymore in the future. Swings are based on Weekly bars. A Top Swing, for example, with Swing setting 30, is the highest value in 60 weeks. Thirty bars at the left and right of the Swing will be lower than the Top Swing. This means that a confirmation is triggered 30 weeks after the Swing. The period will be automatically multiplied by 7 on the daily chart, where 30 becomes 210 bars. Please note that the goal of this script is not to show swings rapidly; it is meant to show the potential next cycle's Top/Bottom levels. 🔹 Multiple Levels The script includes the option to display 3 Top/Bottom levels, which uses different values for the swing calculations. Top: 'high', 'maximum open/close' or 'close' Bottom: 'low', 'minimum open/close' or 'close' These levels can be adjusted up/down with a percentage. Lastly, an "Average" is included for each set, which will only be visible when "AVG" is enabled, together with both Top and Bottom levels. 🔹 Notes Users have to check the validity of swings; the above example only uses 1 Top Swing for its calculations, making the Top level unreliable. Here, 1 of the Bottom Swings is pretty far from the bottom level, changing the swing settings can give a more reliable bottom level where all swings are close to that level. Note the display was set at "Logarithmic", it can just as well be shown as "Regular" In the example below, the price evolution does not fit the logarithmic regression model, where growth should accelerate rapidly at first and then slows over time. Please note that this script can only be used on a daily timeframe or higher; using it at a lower timeframe will show a warning. Also, it doesn't work with bar-replay. 🔶 DETAILS The code gathers data from historical swings. At the last bar, all swings are calculated with different a and b values. The a and b values which results in the smallest difference between all swings and Top/Bottom levels become the final a and b values. The ranges of a and b are between -20.000 to +20.000, which means a and b will have the values -20.000, -19.999, -19.998, -19.997, -19.996, ... -> +20.000. As you can imagine, the number of calculations is enormous. Therefore, the calculation is split into parts, first very roughly and then very fine. The first calculations are done between -20 and +20 (-20, -19, -18, ...), resulting in, for example, 4. The next set of calculations is performed only around the previous result, in this case between 3 (4-1) and 5 (4+1), resulting in, for example, 3.9. The next set goes even more in detail, for example, between 3.8 (3.9-0.1) and 4.0 (3.9 + 0.1), and so on. 1) -20 -> +20 , then loop with step 1 (result (example): 4 ) 2) 4 - 1 -> 4 +1 , then loop with step 0.1 (result (example): 3.9 ) 3) 3.9 - 0.1 -> 3.9 +0.1 , then loop with step 0.01 (result (example): 3.93 ) 4) 3.93 - 0.01 -> 3.93 +0.01, then loop with step 0.001 (result (example): 3.928) This ensures complicated calculations with less effort. These calculations are done at the last bar, where the levels are displayed, which means you can see different results when a new swing is found. Also, note that this indicator has been developed for a daily (or higher) timeframe chart. 🔶 SETTINGS Three sets High/Low • color setting • Swing Length settings for 'High' & 'Low' • % adjustment for 'High' & 'Low' • AVG: shows average (when both 'High' and 'Low' are enabled) Max/Min (maximum open/close, minimum open/close) • color setting • Swing Length settings for 'Max' & 'Min' • % adjustment for 'Max' & 'Min' • AVG: shows average (when both 'Max' and 'Min' are enabled) Close H/Close L (close Top/Bottom level) • color setting • Swing Length settings for 'Close H' & 'Close L' • % adjustment for 'Close H' & 'Close L' • AVG: shows average (when both 'Close H' and 'Close L' are enabled) Show Dashboard, including Top/Bottom levels of the desired source and calculated a and b values. Show Swings + Dot size
Chỉ báo Pine Script®
của fikira
9
Intellect_city - Halvings Bitcoin CycleWhat is halving? The halving timer shows when the next Bitcoin halving will occur, as well as the dates of past halvings. This event occurs every 210,000 blocks, which is approximately every 4 years. Halving reduces the emission reward by half. The original Bitcoin reward was 50 BTC per block found. Why is halving necessary? Halving allows you to maintain an algorithmically specified emission level. Anyone can verify that no more than 21 million bitcoins can be issued using this algorithm. Moreover, everyone can see how much was issued earlier, at what speed the emission is happening now, and how many bitcoins remain to be mined in the future. Even a sharp increase or decrease in mining capacity will not significantly affect this process. In this case, during the next difficulty recalculation, which occurs every 2014 blocks, the mining difficulty will be recalculated so that blocks are still found approximately once every ten minutes. How does halving work in Bitcoin blocks? The miner who collects the block adds a so-called coinbase transaction. This transaction has no entry, only exit with the receipt of emission coins to your address. If the miner's block wins, then the entire network will consider these coins to have been obtained through legitimate means. The maximum reward size is determined by the algorithm; the miner can specify the maximum reward size for the current period or less. If he puts the reward higher than possible, the network will reject such a block and the miner will not receive anything. After each halving, miners have to halve the reward they assign to themselves, otherwise their blocks will be rejected and will not make it to the main branch of the blockchain. The impact of halving on the price of Bitcoin It is believed that with constant demand, a halving of supply should double the value of the asset. In practice, the market knows when the halving will occur and prepares for this event in advance. Typically, the Bitcoin rate begins to rise about six months before the halving, and during the halving itself it does not change much. On average for past periods, the upper peak of the rate can be observed more than a year after the halving. It is almost impossible to predict future periods because, in addition to the reduction in emissions, many other factors influence the exchange rate. For example, major hacks or bankruptcies of crypto companies, the situation on the stock market, manipulation of “whales,” or changes in legislative regulation. --------------------------------------------- Table - Past and future Bitcoin halvings: --------------------------------------------- Date: Number of blocks: Award: 0 - 03-01-2009 - 0 block - 50 BTC 1 - 28-11-2012 - 210000 block - 25 BTC 2 - 09-07-2016 - 420000 block - 12.5 BTC 3 - 11-05-2020 - 630000 block - 6.25 BTC 4 - 20-04-2024 - 840000 block - 3.125 BTC 5 - 24-03-2028 - 1050000 block - 1.5625 BTC 6 - 26-02-2032 - 1260000 block - 0.78125 BTC 7 - 30-01-2036 - 1470000 block - 0.390625 BTC 8 - 03-01-2040 - 1680000 block - 0.1953125 BTC 9 - 07-12-2043 - 1890000 block - 0.09765625 BTC 10 - 10-11-2047 - 2100000 block - 0.04882813 BTC 11 - 14-10-2051 - 2310000 block - 0.02441406 BTC 12 - 17-09-2055 - 2520000 block - 0.01220703 BTC 13 - 21-08-2059 - 2730000 block - 0.00610352 BTC 14 - 25-07-2063 - 2940000 block - 0.00305176 BTC 15 - 28-06-2067 - 3150000 block - 0.00152588 BTC 16 - 01-06-2071 - 3360000 block - 0.00076294 BTC 17 - 05-05-2075 - 3570000 block - 0.00038147 BTC 18 - 08-04-2079 - 3780000 block - 0.00019073 BTC 19 - 12-03-2083 - 3990000 block - 0.00009537 BTC 20 - 13-02-2087 - 4200000 block - 0.00004768 BTC 21 - 17-01-2091 - 4410000 block - 0.00002384 BTC 22 - 21-12-2094 - 4620000 block - 0.00001192 BTC 23 - 24-11-2098 - 4830000 block - 0.00000596 BTC 24 - 29-10-2102 - 5040000 block - 0.00000298 BTC 25 - 02-10-2106 - 5250000 block - 0.00000149 BTC 26 - 05-09-2110 - 5460000 block - 0.00000075 BTC 27 - 09-08-2114 - 5670000 block - 0.00000037 BTC 28 - 13-07-2118 - 5880000 block - 0.00000019 BTC 29 - 16-06-2122 - 6090000 block - 0.00000009 BTC 30 - 20-05-2126 - 6300000 block - 0.00000005 BTC 31 - 23-04-2130 - 6510000 block - 0.00000002 BTC 32 - 27-03-2134 - 6720000 block - 0.00000001 BTC
Chỉ báo Pine Script®
của INTELLECT_city
90cycle @joshuuu90 minute cycle is a concept about certain time windows of the day. This indicator has two different options. One uses the 90 minute cycle times mentioned by traderdaye, the other uses the cls operational times split up into 90 minutes session. e.g. we can often see a fake move happening in the 90 minute window between 2.30am and 4am ny time. The indicator draws vertical lines at the start/end of each session and the user is able to only display certain sessions (asia, london, new york am and pm) For the traderdayes option, the indicator also counts the windows from 1 to 4 and calls them q1,q2,q3,q4 (q-quarter) ⚠️ Open Source ⚠️ Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated. ⚠️ Terms and Conditions ⚠️ This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
Chỉ báo Pine Script®
của joshuuu
15
inverse_fisher_transform_adaptive_stochastic█ Description The indicator is the implementation of inverse fisher transform an indicator transform of the adaptive stochastic (dominant cycle), as in the Cycle Analytics for Trader pg. 198 (John F. Ehlers). Indicator transformation in brief means reshaping the indicator to be more interpretable. The inverse fisher transform is achieved by compressing values near the extremes many extraneous and irrelevant wiggles are removed from the indicator, as cited. █ Inverse Fisher Transform input = 2*(adaptive_stoc - .5) output = e(2*k*input) -1 / e(2*k*input) +1 █ Feature: iFish i.e. output value trigger i.e. previous 1 bar of iFish * 0.90 if iFish crosses above the trigger, consider a buy indicated with the green line while, iFish crosses below the trigger, consider a sell indicate by the red line in addition iFish needs to be greater than the previous iFish
Chỉ báo Pine Script®
của palitoj_endthen
BTC Pi MultipleThe Pi Multiple is a function of 350 and 111-day moving average. When both intersect and the 111-day MA crosses above, it has historically coincided with a cycle top with a 3-day margin. With the Pi Multiple, this intersection is visible when the line crosses zero upwards. The indicator is called the Pi Multiple because 350/111 is close to Pi. It is based on the Pi Cycle Top Indicator developed by Philip Swift and has been modified for better readability by David Bertho.
Chỉ báo Pine Script®
của cryptoonchain
2