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อินดิเคเตอร์และกลยุทธ์

QUARTERS THEORY XAUUSDThe “Quarter Theory XAUUSD” indicator on TradingView is designed to automatically plot horizontal price levels in $25 increments on your chart, providing traders with a clear visual representation of key psychological and technical price points. These levels are particularly useful for instruments like XAU/USD, where price often reacts to round numbers, forming support and resistance zones that can be leveraged for both scalping and swing trading strategies. By showing all $25 increments as horizontal white lines, the indicator ensures that traders can quickly identify potential entry and exit points, without the need for manual drawing or repeated calculations. The indicator works by calculating the nearest $25 multiple relative to the current market price and then drawing horizontal lines across the chart for all increments within a defined range. This range can be customized to suit the instrument being traded; for example, for gold (XAU/USD), a typical range might extend from 0 to 5000, covering all practical price levels that could be relevant in both high and low market conditions. By using Pine Script’s persistent variables, the indicator efficiently creates these lines only once at the start of the chart, avoiding unnecessary resource usage and preventing TradingView from slowing down, which can happen if lines are redrawn every bar. From a trading perspective, these levels serve multiple purposes. For scalpers, the $25 increments act as micro support and resistance points, helping to determine short-term price reactions and potential breakout zones. Scalpers can use these levels to enter positions with tight stop-loss orders just beyond a level and take profits near the next $25 increment, which aligns with common price behavior patterns in highly liquid instruments. For swing traders, the same levels provide broader context, allowing them to identify areas where price might pause or reverse over several days. Swing traders can use these levels to align trades with the prevailing trend, particularly when combined with other indicators such as moving averages or trendlines. Another key advantage of the Quarterly Levels indicator is its simplicity and visual clarity. By plotting lines in a uniform white color and extending them to the right, the chart remains clean and easy to read, allowing traders to focus on price action and market dynamics rather than cluttered technical drawings. This visual consistency also helps in backtesting and strategy development, as traders can quickly see how price interacts with each level over time. Additionally, the use of round-number increments leverages the psychological tendencies of market participants, as many traders place stop orders or entry points near these levels, making them natural zones of interest. Overall, the Quarterly Levels indicator combines efficiency, clarity, and practical trading utility into a single tool. It streamlines chart analysis, highlights meaningful price zones, and supports both scalping and swing trading approaches, making it an essential addition to a trader’s toolkit. By understanding how to integrate these levels into trading strategies, traders can make more informed decisions, manage risk effectively, and identify high-probability trade setups across various market conditions.
อินดิเคเตอร์ Pine Script®
โดย ElvinLing
CausalityLib - granger casuality and transfer entropy helpersLibrary "CausalityLib" Causality Analysis Library - Transfer Entropy, Granger Causality, and Causality Filtering f_shannon_entropy(data, num_bins)   Calculate Shannon entropy of data distribution   Parameters:      data (array) : Array of continuous values      num_bins (int) : Number of bins for discretization   Returns: Entropy value (higher = more randomness) f_calculate_te_score(primary_arr, ticker_arr, window, bins, lag)   Calculate Transfer Entropy from source to target   Parameters:      primary_arr (array) : Target series (e.g., primary ticker returns)      ticker_arr (array) : Source series (e.g., basket ticker returns)      window (int) : Window size for TE calculation      bins (int) : Number of bins for discretization      lag (int) : Lag for source series   Returns: - TE score and direction (-1 or 1) f_correlation_at_lag(primary_arr, ticker_arr, lag, window, correlation_method)   Calculate Pearson correlation at specific lag   Parameters:      primary_arr (array) : Primary series      ticker_arr (array) : Ticker series      lag (int) : Lag value (positive = ticker lags primary)      window (int) : Window size for correlation      correlation_method (string) : Correlation method to use ("Pearson", "Spearman", "Kendall")   Returns: Correlation coefficient f_calculate_granger_score(primary_arr, ticker_arr, window, max_lag, correlation_method)   Calculate Granger causality score with lag testing   Parameters:      primary_arr (array) : Primary series      ticker_arr (array) : Ticker series      window (int) : Window size for correlation      max_lag (int) : Maximum lag to test      correlation_method (string) : Correlation method to use   Returns: - Granger score and directional beta f_partial_correlation(x_arr, y_arr, z_arr, window)   Calculate partial correlation between X and Y controlling for Z   Parameters:      x_arr (array) : First series      y_arr (array) : Second series      z_arr (array) : Mediator series      window (int) : Window size for correlation   Returns: Partial correlation coefficient f_pcmci_filter_score(raw_score, primary_arr, ticker_arr, mediator1, mediator2, mediator3, mediator4, window)   PCMCI Filter: Adjust Granger score by checking for mediating tickers   Parameters:      raw_score (float) : Original Granger score      primary_arr (array) : Primary series      ticker_arr (array) : Ticker series      mediator1 (array) : First potential mediator series      mediator2 (array) : Second potential mediator series      mediator3 (array) : Third potential mediator series      mediator4 (array) : Fourth potential mediator series      window (int) : Window size for correlation   Returns: Filtered score (reduced if causality is indirect/spurious)
ไลบรารี Pine Script®
โดย cybermediaboy
LEVENT: Lifetime Estimation via Efficiency-Regime EventLEVENT — Lifetime Estimation via Efficiency-Regime Event Transitions LEVENT is a research-grade indicator that estimates the remaining structural lifetime of the current market regime. Unlike trend, volatility, or momentum tools, LEVENT does not measure price movement — it measures how long the current market structure is likely to survive before breaking. This script implements the LEVENT model published on Zenodo (Bülent Duman, 2026) and is built on top of the open-source DERYA (Dynamic Efficiency Regime Yield Analyzer) microstructural efficiency framework. What LEVENT measures LEVENT outputs a single continuous variable L that represents the remaining survival capacity of the active efficiency regime. High L → the current regime has strong structural endurance Falling L → the regime is consuming its capacity L → 0 → regime exhaustion and elevated probability of transition This makes LEVENT a forward-looking structural time variable, not a price indicator. What is inside this script This implementation contains the following components: 1. DERYA (open-source microstructure efficiency) DERYA is computed from OHLC data as: Net close-to-close movement divided by total intrabar range It is smoothed with an EMA and normalized over a rolling window to produce a bounded efficiency state (0–100). This is an open-source indicator and is explicitly credited in the LEVENT paper. 2. Transition Strength (S) S measures how unstable the regime is by combining: the slope of DERYA the acceleration of DERYA This is not RSI, MACD, or ATR — it is a state-transition intensity metric. 3. Regime Engine Markets are classified into four structural regimes: Expansion Exhaustion Collapse Base / Recovery A debounce + persistence filter is used to avoid noise-based flickering. 4. Structural Lifetime (LEVENT L) Each regime is assigned a capacity (Λ) and a fragility (α). LEVENT then evolves as a jump-and-countdown survival process: On regime change → L resets to full capacity Inside a regime → L decays deterministically High instability → faster decay This is not a moving average, oscillator, or probability estimate — it is a structural survival clock. How to use LEVENT LEVENT is designed to be used as a regime-health overlay, not a buy/sell trigger. Typical uses: Detect late-stage trends when L is low Avoid initiating positions when the regime is near collapse Compare structural stability across assets Combine with price, trend, or volume systems Do not use LEVENT alone as a trading signal. LEVENT tells you “how long the structure may last”, not “where price will go.” Visuals Background colors show the current regime The LEVENT line shows remaining structural lifetime A table displays the active regime and current L value Important notes LEVENT is not RSI, MACD, ATR, or trend LEVENT does not predict price direction LEVENT does not issue entry/exit signals LEVENT is a research-grade structural model The DERYA component used here is an open-source microstructural efficiency estimator and is credited accordingly. Risk and disclaimer This script is provided for research and analytical purposes only. It is not financial advice and must not be used as a standalone trading system. Markets are uncertain. All trading decisions and risks remain entirely the responsibility of the user. LEVENT: Lifetime Estimation via Efficiency-regime Event Transitions Introducing a Regime-Dependent Structural Lifetime Estimator for Financial Markets Using OHLC Data Author: DUMAN,Bülent Affiliation: Independent Researcher zenodo.org
อินดิเคเตอร์ Pine Script®
โดย blntduman
Korean Trading Value in 100M KRW (KRX Standard)이 지표는 한국 시장(KOSPI, KOSDAQ) 투자자들을 위해 거래대금을 가장 직관적인 '억 원' 단위로 변환하여 보여줍니다. 주요 특징: 직관적인 수치: 우측 가격축(Y축)에 표시되는 숫자 '1'은 '1억 원'을 의미합니다. (예: 1000 = 1000억) KRX 표준 최적화: 한국거래소 기준에 맞춰 금액을 환산하여 시장 주도주와 자금 유입을 즉각 파악할 수 있습니다. (참고: 본 지표는 KRX 데이터를 기준으로 하며, NXT 거래대금은 포함되지 않습니다.) 깔끔한 UI: 차트 화면을 가리는 라벨을 제거하고 트레이딩뷰 기본 색상 테마를 유지하여 가독성이 뛰어납니다. 실시간 확인: trackprice 기능을 통해 현재 진행 중인 봉의 거래대금을 우측 라벨에서 실시간으로 확인할 수 있습니다. ***** This indicator is designed for the Korean stock market (KRX), converting trading values into the most intuitive unit for local traders: 'Eok' (100 million KRW). Key Features: Intuitive Scaling: The numbers on the Y-axis represent 100 million KRW per unit. (e.g., 1000 = 100 billion KRW) KRX Standard Optimized: Easily identify market leaders and capital flow based on KRX data. (Note: This indicator is based on KRX standards and does not include NXT trading value.) Clean UI: Minimizes on-screen clutter and maintains TradingView's default color theme for maximum readability. Real-time Tracking: The trackprice feature allows you to monitor the current bar's trading value directly on the price scale in real-time.
อินดิเคเตอร์ Pine Script®
โดย Ninggimhee
EMA 9/24/50/100/200 with Labels on chart lines This Pine Script® v6 indicator plots five distinct Exponential Moving Averages (EMAs) onto a single trading chart to help identify trend direction and momentum. By calculating the 9, 24, 50, 100, and 200-period averages, the script allows you to visualize short-term price action alongside long-term support and resistance levels. It uses a color-coded hierarchy and varying line thicknesses to make the different timeframes easy to distinguish at a glance. with labels on the lines
อินดิเคเตอร์ Pine Script®
โดย magnergycal
EMA 9/24/50/100/200 v6This Pine Script® v6 indicator plots five distinct Exponential Moving Averages (EMAs) onto a single trading chart to help identify trend direction and momentum. By calculating the 9, 24, 50, 100, and 200-period averages, the script allows you to visualize short-term price action alongside long-term support and resistance levels. It uses a color-coded hierarchy and varying line thicknesses to make the different timeframes easy to distinguish at a glance.
อินดิเคเตอร์ Pine Script®
โดย magnergycal
Strat Master FTFC v1Setup Ready alert fires on the close of the last “setup” candle (the candle right before the entry trigger candle). Entry alert still fires intrabar when the current candle becomes 2U/2D and takes out the trigger. Below is the fully updated, compiling Pine v5 script with: All your reversal patterns Real FTFC (0–3) + flip alerts Calls/Puts bias + strike Gap-safe takeout (no crossover) NEW: Setup Ready alerts for every pattern (bar-close only)
อินดิเคเตอร์ Pine Script®
โดย immortal_itachi7
Signal Architect Stop-Hunt ProxySignal Architect™ — Developer Note These daily posts are intentional. They are designed to help potential users visually observe consistency—not just in outcomes, but in process—across multiple futures products, market conditions, and timeframes, using the Stop Hunt Indicator alongside my proprietary Signal Architect™ framework. The goal is simple: To show how structure, behavior, and probability repeat—every day—despite a constantly changing market. If you follow these posts over time, you will begin to recognize that: • The same behaviors appear across different futures contracts • The same reactions occur on multiple timeframes • The same structural traps and stop events repeat regardless of volatility regime That consistency is not coincidence. Consistency is the signal. Over time, that consistency should become familiar— and familiarity should become your edge. ________________________________________ 🧠 What You’re Seeing (And Why It Matters) This indicator includes a limited visual preview of a proprietary power signal I have personally developed and refined across: • Futures • Algorithmic trading systems • Options structure • Equity market behavior Every tool I release is built around one core principle: Clarity of direction without over-promising or over-fitting. That is why all Signal Architect™ tools emphasize: • Market structure first • High-probability directional context • Clear, visual risk framing • No predictive claims • No curve-fit illusions What you see publicly is not the full system—only controlled, educational previews meant to demonstrate how structure and probability align in real markets. ________________________________________ 📊 Background & Scope Over the years, I have personally developed 800+ programs, including: • Equity systems • Futures strategies • Options structure tools • Dividend & income frameworks • Portfolio construction and allocation logic This includes 40+ Nasdaq-100 trading bots, several operating under extremely strict rule-sets and controlled deployment conditions. Nothing shared publicly represents my complete internal framework. Public posts exist for education, observation, and pattern recognition—not signals, not advice, and not promises. ________________________________________ 🤝 For Those Who Find Value If these daily posts help you see the market more clearly: • Follow, boost, and share my scripts, Ideas, and MINDS posts • Feel free to message me directly with questions or build requests • Constructive feedback and collaboration are always welcome For traders who want to go deeper, optional memberships may include: • Additional signal access • Early previews • Occasional free tools and upgrades 🔗 Membership & Signals: trianchor.gumroad.com ________________________________________ ⚠️ Final Note Everything published publicly is educational and analytical only. Markets carry risk. Discipline, patience, and risk management always come first. Watch the consistency. Study the structure. Let the market repeat itself. — Signal Architect™ ________________________________________ 🔗 Personally Developed GPT Tools • AuctionFlow GPT chatgpt.com • Signal Architect™ Gamma Desk – Market Intelligence chatgpt.com • Gamma Squeeze Watchtower™ chatgpt.com
อินดิเคเตอร์ Pine Script®
โดย SignalArchitecT_AI
SVE Pivot Points (v2) //@version=6 indicator(title="SVE Pivot Points", overlay=true, max_lines_count=500) // Input Parameters agg_period = input.timeframe("D", title="Aggregation period") extend_bars = input.int(50, title="Bars to extend into future", minval=1, maxval=500) show_labels = input.bool(true, title="Show Labels") // Line width line_width = input.int(1, title="Line Width", minval=1, maxval=4) // Detect new aggregation period bool new_agg_bar = bool(ta.change(time(agg_period))) // Fetch previous period's high, low, close ph = request.security(syminfo.tickerid, agg_period, high , barmerge.gaps_off, barmerge.lookahead_on) pl = request.security(syminfo.tickerid, agg_period, low , barmerge.gaps_off, barmerge.lookahead_on) pc = request.security(syminfo.tickerid, agg_period, close , barmerge.gaps_off, barmerge.lookahead_on) // Calculate pivot points pp = (ph + pl + pc) / 3 r1 = 2 * pp - pl r2 = pp + (ph - pl) r3 = 2 * pp + (ph - 2 * pl) s1 = 2 * pp - ph s2 = pp - (ph - pl) s3 = 2 * pp - (2 * ph - pl) // Calculate mean levels r1m = (pp + r1) / 2 r2m = (r1 + r2) / 2 r3m = (r2 + r3) / 2 s1m = (pp + s1) / 2 s2m = (s1 + s2) / 2 s3m = (s2 + s3) / 2 // Previous high and low hh = ph ll = pl // Colors color_r = color.red color_s = color.green color_pp = color.blue color_hl = color.gray // Persistent line variables var line line_r3 = na var line line_r3m = na var line line_r2 = na var line line_r2m = na var line line_r1 = na var line line_r1m = na var line line_hh = na var line line_pp = na var line line_ll = na var line line_s1m = na var line line_s1 = na var line line_s2m = na var line line_s2 = na var line line_s3m = na var line line_s3 = na // Persistent label variables var label lbl_r3 = na var label lbl_r3m = na var label lbl_r2 = na var label lbl_r2m = na var label lbl_r1 = na var label lbl_r1m = na var label lbl_hh = na var label lbl_pp = na var label lbl_ll = na var label lbl_s1m = na var label lbl_s1 = na var label lbl_s2m = na var label lbl_s2 = na var label lbl_s3m = na var label lbl_s3 = na // Function to create or update line create_line(line ln, float price, color col) => line.new(bar_index, price, bar_index + extend_bars, price, color=col, width=line_width) // Function to create label create_label(float price, string txt, color col) => label.new(bar_index + extend_bars, price, txt, style=label.style_label_left, color=color.new(col, 90), textcolor=col, size=size.small) // On new aggregation period, delete old lines and create new ones if new_agg_bar // Delete old lines line.delete(line_r3) line.delete(line_r3m) line.delete(line_r2) line.delete(line_r2m) line.delete(line_r1) line.delete(line_r1m) line.delete(line_hh) line.delete(line_pp) line.delete(line_ll) line.delete(line_s1m) line.delete(line_s1) line.delete(line_s2m) line.delete(line_s2) line.delete(line_s3m) line.delete(line_s3) // Delete old labels if show_labels label.delete(lbl_r3) label.delete(lbl_r3m) label.delete(lbl_r2) label.delete(lbl_r2m) label.delete(lbl_r1) label.delete(lbl_r1m) label.delete(lbl_hh) l
อินดิเคเตอร์ Pine Script®
โดย thexfounder
Std Deviation RangeWhen you want to know when the standard deviation is outside your boundaries this indicator is for you. It lets you set you SD limit and it can color the background when you are out of bounds. Currently the default is 20 SMA bollinger bands set at 1.1. If it is inside those limits the background is green and when it exceeds that range the background is red. You can change the SMA, the standard deviation, and the colors.
อินดิเคเตอร์ Pine Script®
โดย cpolaritz2
ATR Channels 1-2-3It is an overlay indicator that builds a system of channels around a moving average using ATR as the distance metric. The script first calculates a central moving average of the closing price, which can be either EMA or SMA depending on the selected parameter. This moving average acts as the axis of the channels and is independent of the ATR calculation. Next, it computes the Average True Range using a separate period. The ATR is used directly as an absolute measure of price volatility, without additional smoothing or normalization. Based on the central moving average and the ATR value, three pairs of bands are generated. The first channel is created by adding and subtracting one ATR from the moving average. The second channel is created by adding and subtracting two times the ATR, and the third channel by adding and subtracting three times the ATR. There is no conditional or adaptive logic involved; the distances are linear and strictly proportional to the current ATR value. All lines are recalculated on every bar close. The script does not include signals, filters, or trading logic. It purely visualizes volatility-adjusted price envelopes around a reference moving average.
อินดิเคเตอร์ Pine Script®
โดย danavillanueva