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Smooth Fibonacci BandsSmooth Fibonacci Bands This indicator overlays adaptive Fibonacci bands on your chart, creating dynamic support and resistance zones based on price volatility. It combines a simple moving average with ATR-based Fibonacci levels to generate multiple bands that expand and contract with market conditions. ## Features - Creates three pairs of upper and lower Fibonacci bands - Smoothing option for cleaner, less noisy bands - Fully customizable colors and line thickness - Adapts automatically to changing market volatility ## Settings Adjust the SMA and ATR lengths to match your trading timeframe. For short-term trading, try lower values; for longer-term analysis, use higher values. The Fibonacci factors determine how far each band extends from the center line - standard Fibonacci ratios (1.618, 2.618, and 4.236) are provided as defaults. ## Trading Applications - Use band crossovers as potential entry and exit signals - Look for price bouncing off bands as reversal opportunities - Watch for price breaking through multiple bands as strong trend confirmation - Identify potential support/resistance zones for placing stop losses or take profits Fibonacci Bands combines the reliability of moving averages with the adaptability of ATR and the natural market harmony of Fibonacci ratios, offering a robust framework for both trend and range analysis.
Pine Script® göstergesi
ShadowTraderBali tarafından
1
EMA CCI SSL Buy Sell Signal [THANHCONG]📘 Full Description 🔍 Overview This indicator combines three key technical elements to generate trend-based buy/sell signals: EMA (Exponential Moving Averages), CCI (Commodity Channel Index), and the SSL Channel. 📊 Key Features: ✅ Multi-timeframe EMA alignment (8, 21, 89) to confirm trend direction ✅ CCI to detect short-term momentum shifts ✅ Higher Time Frame (HTF) SSL Channel integration for trend filtering ✅ Automatic HTF detection (Auto Mode) or manual timeframe selection ✅ On-chart visual signals with labels and clear color cues ✅ Signal info panel displaying real-time profit/loss percentage since entry ⚙️ Signal Logic Buy Signal: EMA 8 > EMA 21 > EMA 89 (strong uptrend) Turbo CCI > 50 (bullish momentum) Price crosses above HTF SSL upper band Sell Signal: EMA 8 < EMA 21 < EMA 89 (strong downtrend) Turbo CCI < -50 (bearish momentum) Price crosses below HTF SSL lower band 💡 Highlights: Early signals: Displayed immediately once conditions are met (no candle close required) Flexible HTF filtering (Auto/Manual option) Optimized for use on 15-minute to 4-hour or daily charts 📌 How to Use: Apply the indicator on charts from 15-minute timeframe and above Watch for "Buy Signal" or "Sell Signal" labels to appear on the chart Combine with your own analysis and trade management strategy Optional: backtest on historical data for confirmation ⚠️ Disclaimer (as per TradingView policy): This tool does not constitute financial advice or guarantee profits. Users should test thoroughly and manage risk appropriately. Past performance does not guarantee future results. This script is original and manually coded, inspired by well-known methods, without direct copying from any other public or private source. ✅ Author & License: Author: @ThanhCong_ License: Mozilla Public License 2.0 🙏 Thank you for using this indicator! If you find it helpful, feel free to leave a comment, share it with others, or follow me for future updates and tools. Happy and safe trading! 🚀📈..
Pine Script® göstergesi
ThanhCong_ tarafından
MACDtechnical analysis. It consists of three components: ‌MACD Line‌: Calculated by subtracting the 26-period EMA from the 12-period EMA. ‌Signal Line‌: A 9-period EMA of the MACD Line (acts as a trigger). ‌Histogram‌: Visualizes the difference between the MACD and Signal lines. Key interpretations: ‌Bullish Signal‌: When the MACD line crosses above the Signal line. ‌Bearish Signal‌: When the MACD line crosses below the Signal line. ‌Divergence‌: Price and MACD moving opposite directions may indicate trend reversal. Developed by Gerald Appel in the 1970s, it combines trend and momentum analysis. Traders use it for entries/exits and confirming trends.
Pine Script® göstergesi
jzpvgaive467 tarafından
Chattes-SwingCount Chattes-SwingCount // This indicator detects swings using a custom ZigZag algorithm and calculates: // - Average pip movement per swing // - Standard deviation of pip movement // - Average number of candles per swing // - Standard deviation of candle count // // The stats are displayed in a compact box at the top-right corner of the chart. // // An alert is triggered when a swing's pip size exceeds 1.5× the standard deviation, // helping identify unusual volatility or significant market moves. // // Inputs allow customization of ZigZag detection parameters and swing sample size.
Pine Script® göstergesi
chattesTrader1981 tarafından
MACD of RSI [TORYS]MACD of RSI — Momentum & Divergence Scanner Description: This enhanced oscillator applies MACD logic directly to the Relative Strength Index (RSI) rather than price, giving traders a clearer look at internal momentum and early shifts in trend strength. Now featuring a custom histogram, dual MA types, and RSI-based divergence detection — it’s a complete toolkit for identifying exhaustion, acceleration, and hidden reversal points in real time. How It Works: Calculates the MACD line as the difference between a fast and slow moving average of RSI. Adds a Signal Line (MA of the MACD) and plots a Histogram to show momentum acceleration/deceleration. Both RSI MAs and the Signal Line can be toggled between EMA and SMA for custom tuning. Divergence Detection: Bullish Divergence : Price makes a lower low while RSI makes a higher low → labeled with a green “D” below the curve. Bearish Divergence : Price makes a higher high while RSI makes a lower high → labeled with a red “D” above the curve. Configurable lookback window for tuning sensitivity to pivots, with 4 as the sweet spot. RSI Pivot Dot Signals: Plots green dots at RSI oversold pivot lows below 30, Plots red dots at overbought pivot highs above 70. Helps detect short-term exhaustion or bounce zones, plotted right on the MACD-RSI curve. RSI 50 Crosses (Optional): Optional ▲ and ▼ labels when RSI crosses its 50 midline — useful for momentum trend shifts or pullback confirmation, or to detect consolidation. Histogram: Plotted as a column chart showing the distance between MACD and Signal Line. Colored dynamically: Bright green : Momentum rising above zero Light green : Weakening above zero Bright red : Momentum falling below zero Light red : Weakening below zero The zero line serves as the mid-point: Above = Bullish Bias Below = Bearish Bias How to Interpret: Momentum Confirmation: Use MACD cross above Signal Line with a rising histogram to confirm breakouts or trend entries. Histogram shrinking near zero = momentum weakening → caution or reversal. Exhaustion & Reversals: Dot signals near RSI extremes + histogram peak can suggest overbought/oversold pressure. Use divergence labels ("D") to spot early reversal signals before price breaks structure. Inputs & Settings: RSI Length Fast/Slow MA Lengths for MACD (applied to RSI) Signal Line Length MA Type: Choose between EMA and SMA for MACD and Signal Line Pivot Sensitivity for dot markers Divergence Logic Toggle Show/hide RSI 50 Crosses Best For: Traders who want momentum insight from inside RSI, not price Scalpers using divergence or exhaustion entries Swing traders seeking entry confirmation from signal crossovers Anyone using multi-timeframe confluence with RSI and trend filters Pro Tips: Combine this with: Bollinger Bands breakouts and reversals VWAP or EMAs to filter entries by trend Volume spikes or BBW squeezes for volatility confirmation TTM Scalper Alert to sync structure and momentum
Pine Script® göstergesi
alexrainman tarafından
Enhanced Market Structure & Trading SignalsEnhanced Market Structure & Trading Signals A Smart Support/Resistance Indicator with Buy/Sell Alerts This indicator identifies key support & resistance levels and generates high-probability buy/sell signals based on price action and candle structure. It helps traders spot potential reversals at critical levels, just like manual analysis but with algorithmic precision. 🔹 Key Features ✅ Clean Support/Resistance Lines – Draws horizontal levels like manual charting ✅ Smart Buy/Sell Signals – Detects reversals at key levels with confirmation ✅ Price Action Filter – Only triggers signals on strong bullish/bearish candles ✅ ATR-Based Proximity Check – Ensures signals occur near valid S/R zones ✅ Customizable Settings – Adjust sensitivity, confirmation bars, and visibility 🔹 How It Works Support/Resistance Detection – Uses pivot highs/lows to mark key levels Bullish Signals (Green ▲) – Triggers near support after a strong bullish candle + confirmation Bearish Signals (Red ▼) – Triggers near resistance after a strong bearish candle + confirmation 🔹 Recommended Settings Timeframe: 1H or higher (works best on swing trading) Confirmation Bars: 2-3 (for stricter signals) Left/Right Bars: 10-20 (adjust based on market volatility) 🔹 How to Trade with This Indicator Go Long when a green ▲ appears near support Go Short when a red ▼ appears near resistance Combine with: Trend analysis, volume confirmation, or RSI for higher accuracy 📌 Note: Works best in trending or ranging markets. Avoid using in choppy/low-liquidity conditions.
Pine Script® göstergesi
w_thejazz tarafından
Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it. EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been. EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac. If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context. ▶️ What is period in EMA used for? What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it. Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name. For example: Period 10 → alpha = 0.1818 Period 11 → alpha = 0.1667 What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels. Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading! ▶️ Calculating EMAs Efficiently The standard textbook formula for EMA is: EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha) But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra: EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction. That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants. Relative CPU cost of float operations : Addition/Subtraction: ~1 cycle Multiplication: ~5 cycles (depending on precision and architecture) Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator. ▶️ The Warmup Problem: how to start the EMA sequence right How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history: Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months. Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward. Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug. Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile. These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record. ▶️ A Better Way to start EMA: Decaying compensation Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday. But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point. Here's how phantom data compensation works: We start our normal EMA calculation: EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday) But we add a correction factor that adjusts for the missing history: Correction = 1 at the start Correction = Correction × (1-α) after each calculation We then apply this correction: True_EMA = Raw_EMA / (1-Correction) This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant. Let's see how this works in practice: For the first price bar: Raw_EMA = 0 Correction = 1 True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price) For the second price bar: Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2 Correction = 1 × (1-α) = (1-α) True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2 For the third price bar: Raw_EMA updates using the standard formula Correction = (1-α) × (1-α) = (1-α)² True_EMA = Raw_EMA ÷ (1-(1-α)²) With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data. This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase. Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible. // Enhanced EMA function with proper initialization and efficient calculation ema(series float source, simple int period=0, simple float alpha=0)=> // Input validation - one of alpha or period must be provided if alpha<=0 and period<=0 runtime.error("Alpha or period must be provided") // Calculate alpha from period if alpha not directly specified float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1) // Initialize variables for EMA calculation var float ema = na // Stores raw EMA value var float result = na // Stores final corrected EMA var float e = 1.0 // Decay compensation factor var bool warmup = true // Flag for warmup phase if not na(source) if na(ema) // First value case - initialize EMA to zero // (we'll correct this immediately with the compensation) ema := 0 result := source else // Standard EMA calculation (optimized formula) ema := a * (source - ema) + ema if warmup // During warmup phase, apply decay compensation e *= (1-a) // Update decay factor float c = 1.0 / (1.0 - e) // Calculate correction multiplier result := c * ema // Apply correction // Stop warmup phase when correction becomes negligible if e <= 1e-10 warmup := false else // After warmup, EMA operates without correction result := ema result // Return the properly compensated EMA value ▶️ CONCLUSION EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques. By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O. The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions. EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Pine Script® göstergesi
mihakralj tarafından
Volumen + Agotamiento + Tendencia Vol ↓This script detects potential exhaustion zones based on volume behavior, ideal for intraday trading on the 5-minute timeframe. 🔍 What it highlights: - **Exhaustion signals** (bullish or bearish) when: - Current volume is **below the 30-period moving average**. - The previous candle had higher volume. - Price attempts to continue in one direction but shows weakness. 📉 It also displays: - A subtle "Vol ↓" label when there is a **volume downtrend**, defined as at least 60% of the last 5 candles showing decreasing volume. 🕒 Time filter: - Signals only appear between **9:00 AM and 2:00 PM (New York time)**, aligning with the most liquid trading hours. ✅ Recommended usage: - Best suited for **5-minute charts** and **intraday setups**. - Works great as a confirmation layer for support/resistance levels, VWAP zones, or trend exhaustion. - Can be combined with order flow tools like Bookmap or delta-based analysis for precise execution. ⚠️ Note: This is not a delta or absorption-based indicator. It simplifies visual exhaustion detection based on volume structure. Use it as a **contextual alert**, not a standalone signal generator. 📎 Script by: Daniel Gonzalez 🔁 100% open-source and customizable
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daniel_glz18 tarafından
Sector Relative StrengthDescription This script compares sector performance relative to the S&P 500. Sector price levels or charts alone can mislead, because they tend to move with the broader market. An increase in a sector’s price does not necessarily indicate strength, as it may simply be following the index. For more a more reliable picture, the script calculates a ratio between each sector ETF and SPY. If the ratio has increased, the sector has outperformed the index. In case it has declined, the sector has underperformed. If the value is near zero, the sector has moved in line with the index. The sectors are presented in a table and sorted on relative performance. Calculation Method The performance is expressed as a percentage change in the ratio over a user-defined lookback period. The default lookback is set to 21 bars, which corresponds to one month on a daily chart. This value can be adopted in the settings to match preferred time period. Z-Score In addition to the percentage change, the script calculates a Z-score of the ratio, which measures how far the current value deviates from its recent mean. A high positive Z-score indicates that the ratio is significantly above its average, while a negative value indicates it is below. This normalization allows for comparison between sectors with different price levels or volatility profiles. Table Columns - Relative %: The sector's performance relative to SPY over the selected lookback period - Z-Score: Standardized measure of current performance ratio is relative to its average - Trend Arrow: Indicates the direction of relative performance up down or flat Example Interpretation For example, if XLK shows a 3.7% change, it has outperformed SPY over the selected period. Another sector might show a -2.1% change, which indicates underperformance. While both values shows relative strength or weakness, the Z-score is optional and can provide additional context based on how unusual that performance is compared to the sector's own recent behavior. Use Case This approach helps evaluate overall market conditions and supports a top-down method. By starting with sector performance, it becomes easier to identify where the market is showing leadership or weakness. This allows the stock selection process to be more deliberate and can help refine or customize screeners based on certain sectors.
Pine Script® göstergesi
StockLeave tarafından
First 15-Min Candle High/Low### 📘 Description of the Script This Pine Script indicator draws **horizontal lines** at the **high and low of the first 15-minute candle after the market opens at 9:30 AM (New York time)**. It is designed for use on **intraday charts** (e.g., 1m, 5m) for U.S. stock markets. --- ### 🔍 What the Script Does * **Fetches 15-minute candle data** using `request.security()` from the `"15"` timeframe. * **Detects the first 15-minute candle starting at 9:30 AM** (i.e., the 9:30–9:45 candle). * **Saves the high and low** of that first 15-minute candle. * **Plots horizontal lines** at those high/low levels for the rest of the trading day. * **Resets at the start of each new day**, so the levels are updated fresh each morning. --- ### 🕒 When It Updates * At exactly 9:45 AM (when the first 15-minute candle closes), it captures the high/low. * Lines remain plotted for the rest of the day until the script resets on a new day. --- ### 🧠 Why This Is Useful Traders often watch the **initial 15-minute range** as a key zone for: * Breakouts or breakdowns * Trend direction confirmation * Entry or exit signals This script helps visualize that range clearly and automatically. --- Let me know if you want to: * Extend the line beyond today * Add alerts for breakouts * Support different market open times (e.g., futures or forex markets)
Pine Script® göstergesi
1680bdb8dabe49f29e9c0ab1e3b4c6 tarafından