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在腳本中搜尋"GOLD"

EMA & SMA with FRACTAL DEVIATION BANDS by @XeL_ArjonaEMA & SMA with FRACTAL DEVIATION BANDS Ver. 1.0.25.08.2015 By Ricardo M Arjona @XeL_Arjona DISCLAIMER: DISCLAIMER: The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. WHAT IS THIS? This is the adaptation of the FRACTAL DEVIATION BANDS to be used on Traditional Moving Averages (Simple & Exponential). ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingVew accounts at: @XeL_Arjona Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. 2015
Pine Script®指標
由xel_arjona提供
1
Acc/Dist. Cloud with Fractal Deviation Bands by @XeL_ArjonaACCUMULATION / DISTRIBUTION CLOUD with MORPHIC DEVIATION BANDS Ver. 2.0.beta.23:08:2015 by Ricardo M. Arjona @XeL_Arjona DISCLAIMER The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of: Buy (Bull) and Sell (Bear) "Power Balance Algorithm by Vadim Gimelfarb published at Stocks & Commodities V. 21:10 (68-72). Custom Weighting Coefficient for Exponential Moving Average (nEMA) adaptation work by @XeL_Arjona with contribution help from @RicardoSantos at TradingView @pinescript chat room. Morphic Numbers (PHI & Plastic) Pine Script adaptation from it's algebraic generation formulas by @XeL_Arjona Fractal Deviation Bands idea by @XeL_Arjona CHANGE LOG: ACCUMULATION / DISTRIBUTION CLOUD: I decided to change it's name from the Buy to Sell Pressure. The code is essentially the same as older versions and they are the center core (VORTEX?) of all derived New stuff which are: MORPHIC NUMBERS: The "Golden Ratio" expressed by the result of the constant "PHI" and the newer and same in characteristics "Plastic Number" expressed as "PN". For more information about this regard take a look at: HERE! CUSTOM(K) EXPONENTIAL MOVING AVERAGE: Some code has cleaned from last version to include as custom function the nEMA , which use an additional input (K) to customise the way the "exponentially" is weighted from the custom array. For the purpose of this indicator, I implement a volatility algorithm using the Average True Range of last 9 periods multiplied by the morphic number used in the fractal study. (Golden Ratio as default) The result is very similar in response to classic EMA but tend to accelerate or decelerate much more responsive with wider bars presented in trending average. FRACTAL DEVIATION BANDS: The main idea is based on the so useful Standard Deviation process to create Bands in favor of a multiplier (As John Bollinger used in it's own bands) from a custom array, in which for this case is the "Volume Pressure Moving Average" as the main Vortex for the "Fractallitly", so then apply as many "Child bands" using the older one as the new calculation array using the same morphic constant as multiplier (Like Fibonacci but with other approach rather than %ratios). Results are AWSOME! Market tend to accelerate or decelerate their Trend in favor of a Fractal approach. This bands try to catch them, so please experiment and feedback me your own observations. EXTERNAL TICKER FOR VOLUME DATA: I Added a way to input volume data for this kind of study from external tickers. This is just a quicky-hack given that currently TradingView is not adding Volume to their Indexes so; maybe this is temporary by now. It seems that this part of the code is conflicting with intraday timeframes, so You are advised. This CODE is versioned as BETA FOR TESTING PROPOSES. By now TradingView Admins are changing lot's of things internally, so maybe this could conflict with correct rendering of this study with special tickers or timeframes. I will try to code by itself just the core parts of this study in order to use them at discretion in other areas. ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingView accounts at: @XeL_Arjona
Pine Script®指標
由xel_arjona提供
10
AMIT'S EMA'SIndicator Name:** AMIT'S EMA'S **📝 Description:** This all-in-one TradingView indicator is designed for serious traders who want clear trend direction, powerful candlestick signals, and session-based analysis—all in one screen. ### 🔹 Features: #### 1. **Exponential Moving Averages (EMAs):** * Tracks **EMA 21, 50, 100, and 200** to identify short-, medium-, and long-term trends. * Color-coded for quick recognition of crossovers and momentum shifts. * Helps spot golden/death crosses and trend alignment zones. #### 2. **Custom Candlestick Patterns:** * **Big Bar Up:** Highlights large bullish candles indicating potential breakouts or strong buying interest. * **Big Bar Down:** Marks large bearish candles signaling breakdowns or heavy selling pressure. #### 3. **Reversal Candlestick Patterns:** * **3 Line Strike Up:** A strong bullish reversal signal after three consecutive down candles, followed by a large bullish candle engulfing them. * **3 Line Strike Down:** A strong bearish reversal signal after three up candles, followed by a large bearish engulfing candle. * Patterns are plotted with icons/labels for easy spotting. #### 4. **Session Timings with Background Highlight:** * Visual background shading to mark major **trading sessions**: * Asian * London * New York * Helps identify volatility zones and session overlap opportunities. #### 5. **Trend Cloud:** * A dynamic cloud formed using a combination of EMAs or custom logic to represent **overall trend bias**. * Green cloud = bullish trend. * Red cloud = bearish trend. * Acts as a visual filter to avoid counter-trend trades. --- **🛠️ Customization Options:** * Enable/disable specific EMAs or patterns. * Adjustable candle size threshold for "Big Bar" detection. * Session times and cloud smoothing periods can be tailored. **📈 Best For:** * Intraday traders * Swing traders * Trend followers * Price action traders ---
Pine Script®指標
由FinanceWithAmit提供
EU Session Only StrategyThe name of the strategy is the EU session only, but you choose which time is important for you to follow, it can also be the beginning of the US session, a few hours after the news (2 hours after the US open level) or based on the daily open level. 📌 Indicator Description: "EU Session Only Strategy" This TradingView indicator, written in Pine Script version 6, represents a simple yet effective intraday trading strategy focused exclusively on the European trading session. 🎯 Purpose and Use The goal of this strategy is to: Automatically identify the European session open price for the current trading day. Trade only during a defined intraday time window (e.g., between 08:00 and 18:00 UTC). Enter a trade only if the price moves a certain distance (in pips) away from the EU open level. Limit the number of trades per day to avoid overtrading. Automatically close all open positions at the end of the day to minimize overnight risk. ⚙️ How It Works 🔹 1. EU Open Level When the European session opens (e.g., 09:00 UTC), the strategy records the opening price at that moment (eu_open_price). This level is displayed as a red horizontal line on the chart. 🔹 2. Entry Conditions The strategy checks if the current price: Is above the EU open level by at least a defined number of pips → Buy signal. Is below the EU open level by at least a defined number of pips → Sell signal. Trading is allowed only within the specified time range (e.g., 08:00 to 18:00 UTC). A maximum number of trades per day is enforced (e.g., 2 trades max). 🔹 3. Exit Conditions If an opposite signal appears during the day, the strategy automatically closes the current position. At the start of each new day, all open positions are closed, regardless of direction or profit. ✅ Advantages A clear and efficient system based on price reaction around a key daily level. Suitable for automated backtesting and optimization on TradingView. Reduces risk with daily trade limits and end-of-day auto-closing. Ideal for forex pairs that show volatility during the European session (e.g.,GOLD, EUR/USD, GBP/USD, etc.).
Pine Script®策略
由Aleksin_Aleksandar提供
XAU/USD Custom Levels XAU/USD Dynamic Support & Resistance Levels This indicator automatically draws horizontal support and resistance levels for Gold (XAU/USD) based on the current market price, eliminating the need for manual price range adjustments. **Key Features:** - **Dynamic Price Range**: Automatically calculates levels above and below the current price using a customizable percentage range (default 5%) - **Multi-Tier Level System**: Four distinct level types with different visual styling: - Major Levels (100s) - Blue, thick lines - Sub Levels (50s) - Red, medium lines - Sub-Sub Levels (25s) - Yellow, thin lines - Mini Levels (12.5s) - Gray, dotted lines - **Fully Customizable**: Adjust range percentage, step size, colors, and line history through input settings - **Universal Compatibility**: Works at any gold price level - whether $1800, $2500, $3300 or beyond **How It Works:** The script centers the level grid around the current closing price and extends lines from a specified number of bars back to the right edge of the chart. The hierarchical level system helps identify key psychological price points and potential support/resistance zones commonly used in gold trading. **Settings:** - Price Range %: Control how far above/below current price to draw levels (1-20%) - Level Step Size: Adjust spacing between levels (1.0-50.0) - Bars Back: Set how far back in history to start the lines - Color Customization: Personalize colors for each level type Perfect for gold traders who need clean, automatically-updating support and resistance levels without manual configuration.
Pine Script®指標
由DTMtrading提供
Futures Margin Lookup TableThis script applies a table to the upper right corner of the screen, which provides the intraday and overnight margin requirements of the currently selected symbol. In this indicator the user must provide the broker data in the form of specifically formatted text blocks. The data for which should be found on the broker website. The purpose for it's creation is due to the non-standard way each individual broker may price their margins and lack of information within TradingView when connected to some (maybe all) brokers, including when paper trading, as the flat percentage rule is not accurate. An example of information for NinjaTrader could look like this MES;Micro S&P;$50;$2406 ES;E-Mini S&P;$500;$24,053 GC;Gold;$500;$16500 NQ;E-Mini Nasdaq;$1,000;$34,810 FDAX;Dax Index;€2,000;€44,311 Each symbol begins a new line, and the values on that line are separated by semicolons (;) Each line consists of the following... SYMBOL : Search string used to match to the beginning of the current chart symbol. NAME: Human readable name INTRA: Intraday trading margin requirement per contract OVERNIGHT: Overnight trading margin requirement per contract The script simply finds a matching line within your provided information using the current chart symbol. So for example the continuous chart for NQ1! would match to the user specified line starting with NQ... as would the individual contract dates such as NQM2025, NQK2025, etc. NOTES: There is a possibility that symbols with similar starting characters could match. If this is the case put the longer symbol higher in the list. There is also a line / character limit to the text input fields within pinescript Ensure the text you paste into them is not truncated. If so there are 3 input fields for just this purpose. Find the last complete line and continue the remaining symbol lines on the subsequent inputs.
Pine Script®指標
由sannyasi007提供
布林带与肯特纳通道的「挤压」Dr.Lazarus小红书油管飞机微信同号： Dr_Lazarus 策略学习介绍视频可以私信留言，目前小红书上有发也可以自行查找。 Small red book oil pipe airplane WeChat the same number: Dr_Lazarus Strategy learning introduction video can be private message message, the current small red book on the hair can also be found on their own. 布林带和肯特纳通道的双通道挤压检测 动量方向彩色柱状图 零轴信号线指示挤压状态 视觉化挤压预警背景色 他的核心机制呢，是双通道博弈以及爆发信号系统。 为什么让交易者疯狂？ 黑科技组合：KC通道过滤噪音 + BB捕捉标准差异动 + 动量回归确认方向 零延迟决策：柱状图颜色秒辨多空强弱，挤压信号提前预警变盘 适用任何市场：加密币、美股、黄金通杀（参数可调） 策略通过比较布林带与肯特纳通道的宽窄，识别市场挤压状态。当布林带被肯特纳通道紧紧包裹时，市场就像被压缩的弹簧，随时准备突破！此时，动量值val将成为您的导航灯，指引突破的动能。 精髓：KC用价格波幅动态扩张，BB用统计概率收窄，两者形成天然对比！ 学习时间到了~模型部分 关键代码揭秘： 指标结合了布林带（Bollinger Bands, BB）和肯特利渠道（Keltner Channels, KC）的概念 旨在识别市场的“挤压”（squeeze）状态，以及在这种状态下的动量变化 ‌1. 布林带（BB）‌：基于收盘价格的简单移动平均（SMA）、标准差来计算的上轨和下轨。 2.肯特纳渠道（KC）‌：基于收盘价格的SMA，选择使用真实波动幅度（TR）高低作为范围以及范围的SMA，来计算 肯特利渠道的上轨和下轨。 ‌3.挤压状态‌：布林带的下轨高于肯特纳渠道的下轨，且布林带的上轨低于肯特纳渠道的上轨时，市场处于挤压状态。当布林带的下轨低于肯特纳渠道的下轨，且布林带的上轨高于肯特纳渠道的上轨时，市场退出挤压状态。 挤压状态标记‌： 挤压状态为黑色叉号。 其他情况为灰色叉号。 在实战中，结合价格行为与动量值val的颜色信号，挤压状态通常被认为是市场即将发生突破的信号，而动量值的变化则提供了额外的交易时机信息。您可以在挤压状态结束后迅速入场。同时，策略中的0线颜色变化，直观展示市场是否处于挤压状态 4.动量值（val）‌使用线性回归（linreg）函数计算。它结合了最高价的最高值、最低价的最低值和收盘价的SMA的平均。 交易信号： 深绿柱：强势上涨动能 猩红柱：猛烈下跌动能 挤压中突破：往往引发趋势行情！颜色变化与动量增减同步，为您的交易决策提供直观依据。 如果动量值持续增加，这可能表明市场有向上的动力；相反，如果动量值持续减少，则可能表明市场有向下的趋势。 💡 独家技巧 参数组合建议： 短线：KC长度20/BB长度20（捕捉快行情） 波段：开启TrueRange模式（过滤假信号） 现在点击安装，让这个"机构弹簧探测器"成为你的交易雷达！ Dual channel squeeze detection of Bollinger Bands and Keltner Channels Colored histogram of momentum direction Zero axis signal line indicates squeeze status Visual squeeze warning background color Its core mechanism is dual channel game and burst signal system. Why does it make traders crazy? Black technology combination: KC channel filters noise + BB captures standard difference momentum + momentum regression confirms direction Zero delay decision: The color of the histogram distinguishes the strength of long and short positions in seconds, and the squeeze signal warns of changes in advance Applicable to any market: cryptocurrencies, US stocks, gold (adjustable parameters) The strategy identifies the market squeeze status by comparing the width of the Bollinger Bands and the Keltner Channel. When the Bollinger Bands are tightly wrapped by the Keltner Channel, the market is like a compressed spring, ready to break through at any time! At this time, the momentum value val will become your navigation light, guiding the kinetic energy of the breakthrough. Essence: KC uses price fluctuations to dynamically expand, and BB uses statistical probability to narrow, forming a natural contrast between the two! It's time to learn~ Model part Key code revealed: The indicator combines the concepts of Bollinger Bands (BB) and Kentley Channels (KC) Aims to identify the "squeeze" state of the market and the change of momentum in this state ‌1. Bollinger Bands (BB): The upper and lower rails are calculated based on the simple moving average (SMA) and standard deviation of the closing price. 2. Keltner Channels (KC): Based on the SMA of the closing price, choose to use the high and low true fluctuation range (TR) as the range and the SMA of the range to calculate the upper and lower rails of the Kentley Channel. ‌3. Squeeze state ‌: When the lower rail of the Bollinger Band is higher than the lower rail of the Keltner Channel, and the upper rail of the Bollinger Band is lower than the upper rail of the Keltner Channel, the market is in a squeeze state. When the lower rail of the Bollinger Band is lower than the lower rail of the Keltner Channel, and the upper rail of the Bollinger Band is higher than the upper rail of the Keltner Channel, the market exits the squeeze state. Squeeze state mark: The squeeze state is a black cross. Other situations are gray crosses. In actual combat, the squeeze state is usually considered a signal that the market is about to break out, combining the price behavior and the color signal of the momentum value val, and the change of the momentum value provides additional trading opportunity information. You can enter the market quickly after the squeeze state ends. At the same time, the color change of the 0 line in the strategy intuitively shows whether the market is in a squeeze state. 4. The momentum value (val) is calculated using the linear regression (linreg) function. It combines the highest value of the highest price, the lowest value of the lowest price, and the average of the SMA of the closing price. Trading signals: Dark green column: strong upward momentum Scarlet column: violent downward momentum Breakout in squeeze: often triggers a trend market! The color change is synchronized with the increase and decrease of momentum, providing an intuitive basis for your trading decisions. If the momentum value continues to increase, this may indicate that the market has upward momentum; on the contrary, if the momentum value continues to decrease, it may indicate that the market has a downward trend. 💡 Exclusive tips Parameter combination suggestions: Short-term: KC length 20/BB length 20 (to capture fast market conditions) Band: Enable TrueRange mode (to filter false signals) Click to install now and let this "Institutional Spring Detector" become your trading radar!
Pine Script®指標
由frisa0042提供
聪明钱SMC_Dr_Lazarus小红书油管飞机微信同号： Dr_Lazarus 策略学习介绍视频可以私信留言，目前小红书上有发也可以自行查找。 Small red book oil pipe airplane WeChat the same number: Dr_Lazarus Strategy learning introduction video can be private message message, the current small red book on the hair can also be found on their own. 概念 BOS（突破结构）：趋势加速信号（蓝/黄色实线） CHoCH（结构转变）：趋势反转信号（黄/紫色虚线） FVG（恐惧价值缺口）：三根K线形成的价格真空区（红/绿方框） 黄色虚线CHoCH + 绿色FVG = 多头反转 蓝色BOS线 + 0.786斐波位 = 趋势延续 1 定位结构 等待BOS/CHoCH信号（指标画结构线） 口诀："结构破位才行动" 2 锁定FVG 在结构附近寻找红/绿供需区（指标自动标记） 规则：价格首次回补FVG时入场 3 斐波那契确认 观察价格在0.618/0.786的反应（指标彩色水平线） 经典配合：FVG+0.705斐波位=高概率反转区 斐波那契关键位 机构最爱在0.618/0.786回撤位布局（指标中的彩色水平线） 统计规律：80%反转发生在0.705黄金位（指标紫色线） 4 止盈止损管理 止盈 止损设在结构外或FVG另一端 止损就是氧气：单笔亏损永远不超过本金2% Concept BOS (Breakout Structure): Trend acceleration signal (blue/yellow solid line) CHoCH (Structural Transformation): Trend reversal signal (yellow/purple dotted line) FVG (Fear Value Gap): Price vacuum zone formed by three candlesticks (red/green box) Yellow dotted line CHoCH + green FVG = bullish reversal Blue BOS line + 0.786 Fibonacci level = trend continuation 1 Positioning structure Wait for BOS/CHoCH signal (indicator draws structure line) Mantra: "Structure breaks before taking action" 2 Locking FVG Look for red/green supply and demand zone near the structure (indicator automatically marks) Rule: Enter the market when the price first covers FVG 3 Fibonacci confirmation Observe the price reaction at 0.618/0.786 (indicator colored horizontal line) Classic combination: FVG+0.705 Fibonacci level = high probability reversal zone Fibonacci key level Institutions prefer to layout at 0.618/0.786 retracement level (colored horizontal line in the indicator) Statistical law: 80% of reversals occur at 0.705 golden level (indicator purple line) 4 Stop profit and stop loss management Stop profit Stop loss is set outside the structure or at the other end of FVG Stop loss is oxygen: a single loss will never exceed 2% of the principal
Pine Script®指標
由frisa0042提供
FVG Highlighter v5 – corps+mèchesndicator Description: “FVG15 – 2 Trades/Day (Asia + US)” By Jack, optimized for Steven & Lauryne 📖 Overview This strategy automates detection and execution of trades based on 15-minute Fair Value Gaps (FVG), only during two daily “kill-zones,” and limits you to two trades per day to control risk and preserve discipline. 🔍 Key Features FVG Detection (15m) Bullish and bearish gaps identified anywhere, any time. Marked on the origin candle with ▲ (bullish) or ▼ (bearish). Kill-Zones (UTC / Paris UTC+2) Asia Session: 03:00–06:00 Paris (01:00–04:00 UTC) US Session: 15:30–17:00 Paris (13:30–15:00 UTC) Background shading highlights active session. Automated Position Management Max 2 trades/day: stops trading after one winner at RR 2 or two losers. Limit entry at 50% of the gap, SL behind the “candle 1” extreme, TP at RR = 2. Position size auto-calculated to risk a fixed dollar amount (riskDollars). Daily Counters tradesToday and lossesToday reset on a new day. Signal lockout after two consecutive losses to prevent overtrading. Customizable Inputs Fixed Risk $: amount risked per trade. Risk/Reward: TP/SL ratio (1.5–3). FVG Look-back: number of candles used to define the gap (default 1). 📐 Input Parameters Parameter Type Default Description riskDollars Float 100 Fixed dollar amount risked per trade RR Float 2.0 Reward/Risk ratio (min 1.5, max 3) fvgLength Integer 1 Look-back candles for FVG calculation default_qty_* Strategy 1% Position size as % of equity calc_on_every_tick Bool true Recalculate strategy on every tick 🚀 Quick Start Open a 15m chart (e.g., MGC1! for Micro-Gold). Paste the Pine v6 script into TradingView’s Pine Editor. Ensure the chart’s timezone is set to UTC. Adjust riskDollars, RR, or fvgLength to suit your profile. Add to chart and view backtest results in the Strategy Tester. 📝 Notes for Steven, Lauryne & Jack Steven: Monitor gap sizes on thinly-traded markets; tweak fvgLength as needed. Lauryne: Use alongside manual SMT/ICT confirmations for extra filter power. Jack: Integrate into your pre-session routine and log each trade to sharpen discipline. Changelog v6: Full port to Pine v6; fixed session detection and daily counters. v5→v6: Renamed to strategy.closed_trades, simplified inKill, updated to current Pine standards. Enjoy trading—and please share your feedback with the community!
Pine Script®指標
由Jack_Kinosky提供
Bull & Bear Power Separados📄 English Description for TradingView Bull & Bear Power – Elder Style This indicator displays the strength of buyers (Bull Power) and sellers (Bear Power) separately, based on Alexander Elder’s original concept. It uses a 13-period Exponential Moving Average (EMA) as the baseline, calculating: Bull Power = High – EMA Bear Power = Low – EMA ✔️ Bull Power (green) shows buying pressure. ✔️ Bear Power (red) shows selling pressure. Great for analyzing true market momentum and spotting early signs of potential trend reversals. Can be used as confirmation together with moving averages (e.g., MMA30 and MMA50) or price action signals. ✅ On 1H gold charts (XAUUSD), it has shown solid behavior in filtering entries during clear trends. Developed and shared for educational purposes by El Bit Criollo.
Pine Script®指標
由gastonferraro提供
Enhanced Daily Sentiment & Auction Area Trading StrategyDetermine Daily Sentiment (Anchor Chart - Daily TF): Analyze Yesterday's Daily Candle: Look at the previous day's daily candlestick (high, low, open, close). This is the "most important information." Establish Bias: If yesterday's candle was bullish (closed higher), the bias for today is generally long (approx. 80% of the time). If bearish, the bias is short. Moving Average Context: Note if the daily price is above or below its short-term moving average (e.g., 21 or 50 MA). This should align with the candle's bias (e.g., bullish daily candle above its MA). Pre-Market & Opening Analysis (Information Gathering): Check for Gaps: Observe if the market is gapping up or down in the pre-market session relative to yesterday's close. This provides an early clue to current sentiment. Consider Overall Sentiment: Briefly factor in relevant news or overarching market sentiment (e.g., data releases, overall market feeling from yields, gold etc.). Trading Window: Focus primarily on trading within the first hour of the U.S. market open, as this is when volatility is typically highest, which the strategy relies on. Setup 5-Minute Chart for Execution (Trading TF - 5-min): Apply Moving Average: Use the same short-term moving average (e.g., 21 or 50 MA) as on the daily chart. Seek Alignment (Crucial): The 5-minute chart's trend and price action relative to its MA must align with the daily chart's bias and MA relationship. If Daily bias is LONG (price above daily MA), the 5-minute chart should also show price establishing itself above its 5-min MA, ideally with a similar "45-degree angle" uptrend. If Daily bias is SHORT (price below daily MA), the 5-minute chart should also show price establishing itself below its 5-min MA, with a similar downtrend. If there's no clear alignment between the daily and 5-minute chart structure/MA, do not trade. Identify the "Auction Area" (Value/Congestion) on the 5-Minute Chart: This is a recent area of congestion, a small support/resistance flip, or where price has paused, consolidated, and is retesting, often near the 5-minute MA. Uptrend (Long Bias): Look for a pullback (a small "V" shape dip) towards the 5-minute MA or a recent small resistance-turned-support area. This is the "auction retest" before a potential breakout higher. Downtrend (Short Bias): Look for a pullback rally (an inverted "V" shape) towards the 5-minute MA or a recent small support-turned-resistance area.
Pine Script®指標
由KashCharts提供
LANZ Strategy 4.0 [Backtest]🔷 LANZ Strategy 4.0 — Strategy Execution Based on Confirmed Structure + Risk-Based SL/TP LANZ Strategy 4.0 is the official backtesting engine for the LANZ Strategy 4.0 trading logic. It simulates real-time executions based on breakout of Strong/Weak Highs or Lows, using a consistent structural system with SL/TP dynamically calculated per trade. With integrated risk management and lot size logic, this script allows traders to validate LANZ Strategy 4.0 performance with real strategy metrics. 🧠 Core Components: Confirmed Breakout Entries: Trades are executed only when price breaks the most recent structural level (Strong High or Strong Low), detected using swing pivots. Dynamic SL and TP Logic: SL is placed below/above the breakout point with a customizable buffer. TP is defined using a fixed Risk-Reward (RR) ratio. Capital-Based Risk Management: Lot size is calculated based on account equity, SL distance, and pip value (e.g. $10 per pip on XAUUSD). Clean and Controlled Executions: Only one trade is active at a time. No new entries are allowed until the current position is closed. 📊 Visual Features: Automatic plotting of Entry, SL, and TP levels. Full control of swing sensitivity (swingLength) and SL buffer. SL and TP lines extend visually for clarity of trade risk and reward zones. ⚙️ How It Works: Detects pivots and classifies trend direction. Waits for breakout above Strong High (BUY) or below Strong Low (SELL). Calculates dynamic SL and TP based on buffer and RR. Computes trade size automatically based on risk per trade %. Executes entry and manages exits via strategy engine. 📝 Notes: Ideal for evaluating the LANZ Strategy 4.0 logic over historical data. Must be paired with the original indicator (LANZ Strategy 4.0) for live trading. Best used on assets with clear structural behavior (gold, indices, FX). 📌 Credits: Backtest engine developed by LANZ based on the official rules of LANZ Strategy 4.0. This script ensures visual and logical consistency between live charting and backtesting simulations.
Pine Script®策略
由rau_u_lanz提供
4
LTA - Futures Contract Size CalculatorLTA - Futures Contract Size Calculator This indicator helps futures traders calculate the potential stop-loss (SL) value for their trades with ease. Simply input your entry price, stop-loss price, and number of contracts, and the indicator will compute the ticks moved, price movement, and total SL value in USD. Key Features: Supports a wide range of futures contracts, including: Index Futures: E-mini S&P 500 (ES), Micro E-mini S&P 500 (MES), E-mini Nasdaq-100 (NQ), Micro E-mini Nasdaq-100 (MNQ) Commodity Futures: Crude Oil (CL), Gold (GC), Micro Gold (MGC), Silver (SI), Micro Silver (SIL), Platinum (PL), Micro Platinum (MPL), Natural Gas (NG), Micro Natural Gas (MNG) Bond Futures: 30-Year T-Bond (ZB) Currency Futures: Euro FX (6E), Japanese Yen (6J), Australian Dollar (6A), British Pound (6B), Canadian Dollar (6C), Swiss Franc (6S), New Zealand Dollar (6N) Displays key metrics in a clean table (bottom-right corner): Instrument, Entry Price, Stop-Loss Price, Number of Contracts, Tick Size, Ticks Moved, Price Movement, and Total SL Value. Automatically calculates based on the selected instrument’s tick size and tick value. User-friendly interface with a dark theme for better visibility. How to Use: Add the indicator to your chart. Select your instrument from the dropdown (ensure it matches your chart’s symbol, e.g., "NG1!" for NATURAL GAS (NG)). Input your Entry Price, Stop-Loss Price, and Number of Contracts. View the results in the table, including the Total SL Value in USD. Ideal For: Futures traders looking to quickly assess stop-loss risk. Beginners and pros trading indices, commodities, bonds, or currencies. Note: Ensure your chart symbol matches the selected instrument for accurate calculations. For best results, test with a few contracts and price levels to confirm the output. This description is tailored for TradingView’s audience, providing a clear overview of the indicator’s functionality, supported instruments, and usage instructions. It also includes a note to help users avoid common pitfalls (e.g., mismatched symbols). If you’d like to adjust the tone, add more details, or include specific TradingView tags (e.g., , ), let me know!
Pine Script®指標
由lorenzocorrado_提供
Topological Market Stress (TMS) - Quantum FabricTopological Market Stress (TMS) - Quantum Fabric What Stresses The Market? Topological Market Stress (TMS) represents a revolutionary fusion of algebraic topology and quantum field theory applied to financial markets. Unlike traditional indicators that analyze price movements linearly, TMS examines the underlying topological structure of market data—detecting when the very fabric of market relationships begins to tear, warp, or collapse. Drawing inspiration from the ethereal beauty of quantum field visualizations and the mathematical elegance of topological spaces, this indicator transforms complex mathematical concepts into an intuitive, visually stunning interface that reveals hidden market dynamics invisible to conventional analysis. Theoretical Foundation: Topology Meets Markets Topological Holes in Market Structure In algebraic topology, a "hole" represents a fundamental structural break—a place where the normal connectivity of space fails. In markets, these topological holes manifest as: Correlation Breakdown: When traditional price-volume relationships collapse Volatility Clustering Failure: When volatility patterns lose their predictive power Microstructure Stress: When market efficiency mechanisms begin to fail The Mathematics of Market Topology TMS constructs a topological space from market data using three key components: 1. Correlation Topology ρ(P,V) = correlation(price, volume, period) Hole Formation = 1 - |ρ(P,V)| When price and volume decorrelate, topological holes begin forming. 2. Volatility Clustering Topology σ(t) = volatility at time t Clustering = correlation(σ(t), σ(t-1), period) Breakdown = 1 - |Clustering| Volatility clustering breakdown indicates structural instability. 3. Market Efficiency Topology Efficiency = |price - EMA(price)| / ATR Measures how far price deviates from its efficient trajectory. Multi-Scale Topological Analysis Markets exist across multiple temporal scales simultaneously. TMS analyzes topology at three distinct scales: Micro Scale (3-15 periods): Immediate structural changes, market microstructure stress Meso Scale (10-50 periods): Trend-level topology, medium-term structural shifts Macro Scale (50-200 periods): Long-term structural topology, regime-level changes The final stress metric combines all scales: Combined Stress = 0.3×Micro + 0.4×Meso + 0.3×Macro How TMS Works 1. Topological Space Construction Each market moment is embedded in a multi-dimensional topological space where: - Price efficiency forms one dimension - Correlation breakdown forms another - Volatility clustering breakdown forms the third 2. Hole Detection Algorithm The indicator continuously scans this topological space for: Hole Formation: When stress exceeds the formation threshold Hole Persistence: How long structural breaks maintain Hole Collapse: Sudden topology restoration (regime shifts) 3. Quantum Visualization Engine The visualization system translates topological mathematics into intuitive quantum field representations: Stress Waves: Main line showing topological stress intensity Quantum Glow: Surrounding field indicating stress energy Fabric Integrity: Background showing structural health Multi-Scale Rings: Orbital representations of different timeframes 4. Signal Generation Stable Topology (✨): Normal market structure, standard trading conditions Stressed Topology (⚡): Increased structural tension, heightened volatility expected Topological Collapse (🕳️): Major structural break, regime shift in progress Critical Stress (🌋): Extreme conditions, maximum caution required Inputs & Parameters 🕳️ Topological Parameters Analysis Window (20-200, default: 50) Primary period for topological analysis 20-30: High-frequency scalping, rapid structure detection 50: Balanced approach, recommended for most markets 100-200: Long-term position trading, major structural shifts only Hole Formation Threshold (0.1-0.9, default: 0.3) Sensitivity for detecting topological holes 0.1-0.2: Very sensitive, detects minor structural stress 0.3: Balanced, optimal for most market conditions 0.5-0.9: Conservative, only major structural breaks Density Calculation Radius (0.1-2.0, default: 0.5) Radius for local density estimation in topological space 0.1-0.3: Fine-grained analysis, sensitive to local changes 0.5: Standard approach, balanced sensitivity 1.0-2.0: Broad analysis, focuses on major structural features Collapse Detection (0.5-0.95, default: 0.7) Threshold for detecting sudden topology restoration 0.5-0.6: Very sensitive to regime changes 0.7: Balanced, reliable collapse detection 0.8-0.95: Conservative, only major regime shifts 📊 Multi-Scale Analysis Enable Multi-Scale (default: true) - Analyzes topology across multiple timeframes simultaneously - Provides deeper insight into market structure at different scales - Essential for understanding cross-timeframe topology interactions Micro Scale Period (3-15, default: 5) Fast scale for immediate topology changes 3-5: Ultra-fast, tick/minute data analysis 5-8: Fast, 5m-15m chart optimization 10-15: Medium-fast, 30m-1H chart focus Meso Scale Period (10-50, default: 20) Medium scale for trend topology analysis 10-15: Short trend structures 20-25: Medium trend structures (recommended) 30-50: Long trend structures Macro Scale Period (50-200, default: 100) Slow scale for structural topology 50-75: Medium-term structural analysis 100: Long-term structure (recommended) 150-200: Very long-term structural patterns ⚙️ Signal Processing Smoothing Method (SMA/EMA/RMA/WMA, default: EMA) Method for smoothing stress signals SMA: Simple average, stable but slower EMA: Exponential, responsive and recommended RMA: Running average, very smooth WMA: Weighted average, balanced approach Smoothing Period (1-10, default: 3) Period for signal smoothing 1-2: Minimal smoothing, noisy but fast 3-5: Balanced, recommended for most applications 6-10: Heavy smoothing, slow but very stable Normalization (Fixed/Adaptive/Rolling, default: Adaptive) Method for normalizing stress values Fixed: Static 0-1 range normalization Adaptive: Dynamic range adjustment (recommended) Rolling: Rolling window normalization 🎨 Quantum Visualization Fabric Style Options: Quantum Field: Flowing energy visualization with smooth gradients Topological Mesh: Mathematical topology with stepped lines Phase Space: Dynamical systems view with circular markers Minimal: Clean, simple display with reduced visual elements Color Scheme Options: Quantum Gradient: Deep space blue → Quantum red progression Thermal: Black → Hot orange thermal imaging style Spectral: Purple → Gold full spectrum colors Monochrome: Dark gray → Light gray elegant simplicity Multi-Scale Rings (default: true) - Display orbital rings for different time scales - Visualizes how topology changes across timeframes - Provides immediate visual feedback on cross-scale dynamics Glow Intensity (0.0-1.0, default: 0.6) Controls the quantum glow effect intensity 0.0: No glow, pure line display 0.6: Balanced, recommended setting 1.0: Maximum glow, full quantum field effect 📋 Dashboard & Alerts Show Dashboard (default: true) Real-time topology status display Current market state and trading recommendations Stress level visualization and fabric integrity status Show Theory Guide (default: true) Educational panel explaining topological concepts Dashboard interpretation guide Trading strategy recommendations Enable Alerts (default: true) Extreme stress detection alerts Topological collapse notifications Hole formation and recovery signals Visual Logic & Interpretation Main Visualization Elements Quantum Stress Line Primary indicator showing topological stress intensity Color intensity reflects current market state Line style varies based on selected fabric style Glow effect indicates stress energy field Equilibrium Line Silver line showing average stress level Reference point for normal market conditions Helps identify when stress is elevated or suppressed Upper/Lower Bounds Red upper bound: High stress threshold Green lower bound: Low stress threshold Quantum fabric fill between bounds shows stress field Multi-Scale Rings Aqua circles : Micro-scale topology (immediate changes) Orange circles: Meso-scale topology (trend-level changes) Provides cross-timeframe topology visualization Dashboard Information Topology State Icons: ✨ STABLE: Normal market structure, standard trading conditions ⚡ STRESSED: Increased structural tension, monitor closely 🕳️ COLLAPSE: Major structural break, regime shift occurring 🌋 CRITICAL: Extreme conditions, reduce risk exposure Stress Bar Visualization: Visual representation of current stress level (0-100%) Color-coded based on current topology state Real-time percentage display Fabric Integrity Dots: ●●●●● Intact: Strong market structure (0-30% stress) ●●●○○ Stressed: Weakening structure (30-70% stress) ●○○○○ Fractured: Breaking down structure (70-100% stress) Action Recommendations: ✅ TRADE: Normal conditions, standard strategies apply ⚠️ WATCH: Monitor closely, increased vigilance required 🔄 ADAPT: Change strategy, regime shift in progress 🛑 REDUCE: Lower risk exposure, extreme conditions Trading Strategies In Stable Topology (✨ STABLE) - Normal trading conditions apply - Use standard technical analysis - Regular position sizing appropriate - Both trend-following and mean-reversion strategies viable In Stressed Topology (⚡ STRESSED) - Increased volatility expected - Widen stop losses to account for higher volatility - Reduce position sizes slightly - Focus on high-probability setups - Monitor for potential regime change During Topological Collapse (🕳️ COLLAPSE) - Major regime shift in progress - Adapt strategy immediately to new market character - Consider closing positions that rely on previous regime - Wait for new topology to stabilize before major trades - Opportunity for contrarian plays if collapse is extreme In Critical Stress (🌋 CRITICAL) - Extreme market conditions - Significantly reduce risk exposure - Avoid new positions until stress subsides - Focus on capital preservation - Consider hedging existing positions Advanced Techniques Multi-Timeframe Topology Analysis - Use higher timeframe TMS for regime context - Use lower timeframe TMS for precise entry timing - Alignment across timeframes = highest probability trades Topology Divergence Trading - Most powerful at regime boundaries - Price makes new high/low but topology stress decreases - Early warning of potential reversals - Combine with key support/resistance levels Stress Persistence Analysis - Long periods of stable topology often precede major moves - Extended stress periods often resolve in regime changes - Use persistence tracking for position sizing decisions Originality & Innovation TMS represents a genuine breakthrough in applying advanced mathematics to market analysis: True Topological Analysis: Not a simplified proxy but actual topological space construction and hole detection using correlation breakdown, volatility clustering analysis, and market efficiency measurement. Quantum Aesthetic: Transforms complex topology mathematics into an intuitive, visually stunning interface inspired by quantum field theory visualizations. Multi-Scale Architecture: Simultaneous analysis across micro, meso, and macro timeframes provides unprecedented insight into market structure dynamics. Regime Detection: Identifies fundamental market character changes before they become obvious in price action, providing early warning of structural shifts. Practical Application: Clear, actionable signals derived from advanced mathematical concepts, making theoretical topology accessible to practical traders. This is not a combination of existing indicators or a cosmetic enhancement of standard tools. It represents a fundamental reimagining of how we measure, visualize, and interpret market dynamics through the lens of algebraic topology and quantum field theory. Best Practices Start with defaults: Parameters are optimized for broad market applicability Match timeframe: Adjust scales based on your trading timeframe Confirm with price action: TMS shows market character, not direction Respect topology changes: Reduce risk during regime transitions Use appropriate strategies: Adapt approach based on current topology state Monitor persistence: Track how long topology states maintain Cross-timeframe analysis: Align multiple timeframes for highest probability trades Alerts Available Extreme Topological Stress: Market fabric under severe deformation Topological Collapse Detected: Regime shift in progress Topological Hole Forming: Market structure breakdown detected Topology Stabilizing: Market structure recovering to normal Chart Requirements Recommended Markets: All liquid markets (forex, stocks, crypto, futures) Optimal Timeframes: 5m to Daily (adaptable to any timeframe) Minimum History: 200 bars for proper topology construction Best Performance: Markets with clear regime characteristics Academic Foundation This indicator draws from cutting-edge research in: - Algebraic topology and persistent homology - Quantum field theory visualization techniques - Market microstructure analysis - Multi-scale dynamical systems theory - Correlation topology and network analysis Disclaimer This indicator is for educational and research purposes only. It does not constitute financial advice or provide direct buy/sell signals. Topological analysis reveals market structure characteristics, not future price direction. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results. See markets through the lens of topology. Trade the structure, not the noise. Bringing advanced mathematics to practical trading through quantum-inspired visualization. Trade with insight. Trade with structure. — Dskyz , for DAFE Trading Systems
Pine Script®指標
由DskyzInvestments提供
3
Information Asymmetry Gradient (IAG) What is the Information Asymmetry Gradient (IAG)? The Information Asymmetry Gradient (IAG) is a unique market regime and imbalance detector that quantifies the subtle, directional “information flow” in price and volume. Inspired by information theory and market microstructure, IAG is designed to help traders spot the early buildup of conviction or surprise—the kind of hidden imbalance that often precedes major price moves. Unlike traditional volume or momentum indicators, IAG focuses on the efficiency and directionality of information transfer: how much “informational energy” is being revealed by up-moves versus down-moves, normalized by price movement. It’s not just about net flow, but about the quality and asymmetry of that flow. Theoretical Foundation Information Asymmetry: Markets move when new information is revealed. If one side (buyers or sellers) is consistently more “informationally efficient” per unit of price change, an imbalance is building—even if price hasn’t moved much yet. Gradient: By tracking the rate of change (gradient) between fast and slow information flows, IAG highlights when a subtle imbalance is accelerating. Volatility of Asymmetry: Sudden spikes in the volatility of information asymmetry often signal regime uncertainty or the approach of a “surprise” move. How IAG Works Directional Information Content: For each bar, IAG estimates the “information per unit of price change” for both up-moves and down-moves, using volume and price action. Asymmetry Calculation: Computes the difference (or ratio) between up and down information content, revealing directional bias. Gradient Detection: Calculates both a fast and slow EMA of the asymmetry, then measures their difference (the “gradient”), normalized as a Z-score. Volatility of Asymmetry: Tracks the standard deviation of asymmetry over a rolling window, with Z-score normalization to spot “information shocks.” Flow Strength: Quantifies the conviction of the current information flow on a 0–100 scale. Regime Detection: Flags “extreme” asymmetry, “building” flow, and “high volatility” states. Inputs: 🌌 Core Asymmetry Parameters Fast Information Period (short_len, default 8): EMA period for detecting immediate information flow changes. 5–8: Scalping (1–5min) 8–12: Day trading (15min–1hr) 12–20: Swing trading (4hr+) Slow Information Period (long_len, default 34): EMA period for baseline information context. Should be 3–5x fast period. Default (34): Fibonacci number, stable for most assets. Gradient Smoothing (gradient_smooth, default 3): Smooths the gradient calculation. 1–2: Raw, responsive 3–5: Balanced 6–10: Very smooth 📊 Asymmetry Method Calculation Mode (calc_mode, default "Weighted"): “Simple”: Basic volume split by direction “Weighted”: Volume × price movement (default, most robust) “Logarithmic”: Log-scaled for large moves Use Ratio (show_ratio, default false): “Difference”: UpInfo – DownInfo (additive) “Ratio”: UpInfo / DownInfo (multiplicative, better for comparing volatility regimes) 🌊 Volatility Analysis Volatility Window (stdev_len, default 21): Lookback for measuring asymmetry volatility. Volatility Alert Level (vol_threshold, default 1.5): Z-score threshold for volatility alerts. 🎨 Visual Settings Color Theme (color_theme, default "Starry Night"): Van Gogh-inspired palettes: “Starry Night”: Deep blues and yellows “Sunflowers”: Warm yellows and browns “Café Terrace”: Night blues and warm lights “Wheat Field”: Golden and sky blue Show Swirl Effects (show_swirls, default true): Adds swirling background to visualize information turbulence. Show Signal Stars (show_stars, default true): Star markers at significant asymmetry points. Show Info Dashboard (show_dashboard, default true): Top-right panel with current metrics and market state. Show Flow Visualization (show_flow, default true): Main gradient line with artistic effects. Color Schemes Dynamic color gradients adapt to both the direction and intensity of the information gradient, using Van Gogh-inspired palettes for visual clarity and artistic flair. Glow and aura effects: The main line is layered with glows for depth and to highlight strong signals. Swirl background: Visualizes the “turbulence” of information flow, darker and more intense as flow strength and volatility rise. Visual Logic Main Gradient Line: Plots the normalized information gradient (Z-score), color-coded by direction and intensity. Glow/Aura: Multiple layers for visual depth and to highlight strong signals. Threshold Zones: Dotted lines and filled areas mark “Building” and “Extreme” asymmetry zones. Volatility Ribbon: Area plot of volatility Z-score, highlighting information shocks. Signal Stars: Circular markers at each “Extreme” event, color-coded for bullish/bearish; cross markers for volatility spikes. Dashboard: Top-right panel shows current status (Extreme, Building, High Volatility, Balanced), gradient value, flow strength, information balance, and volatility status. Trading Guide: Bottom-left panel explains all states and how to interpret them. How to Use IAG 🌟 EXTREME: Major information imbalance—potential for explosive move or reversal. 🌙 BUILDING: Asymmetry is forming—watch for a breakout or trend acceleration. 🌪️ HIGH VOLATILITY: Information flow is unstable—expect regime uncertainty or “surprise” moves. ☁️ BALANCED: No clear bias—market is in equilibrium. Positive Gradient: Bullish information flow (buyers have the edge). Negative Gradient: Bearish information flow (sellers have the edge). Flow >66%: Strong conviction—crowd is acting in unison. Volatility Spike: Regime uncertainty—be alert for sudden moves. Tips: - Use lower periods for scalping, higher for swing trading. - “Weighted” mode is most robust for most assets. - Combine with price action or your own system for confirmation. - Works on all assets and timeframes—tune to your style. Alerts IAG Extreme Asymmetry: Extreme information asymmetry detected. IAG Building Flow: Information flow building. IAG High Volatility: Information volatility spike. IAG Bullish/Bearish Extreme: Directional extreme detected. Originality & Usefulness IAG is not a mashup of existing indicators. It is a novel approach to quantifying the “surprise” or “conviction” element in market moves, focusing on the efficiency and directionality of information transfer per unit of price change. The multi-layered color logic, artistic visual effects, and regime dashboard are unique to this script. IAG is designed for anticipation, not confirmation—helping you see subtle imbalances before they become obvious in price. Chart Info Script Name: Information Asymmetry Gradient (IAG) – Starry Night Recommended Use: Any asset, any timeframe. Tune parameters to your style. Disclaimer This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results. Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
Pine Script®指標
由DskyzInvestments提供
3
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike. ## Theoretical Foundation ### Historical Context of Bear Market Prediction Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models. Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data. ### Methodological Framework The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment. The mathematical foundation follows the general form: Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100 Where: - Wi = Category weight (i = 1,2,3,4) - Ci = Normalized category score - Categories: Macroeconomic, Technical, Sentiment, Breadth ## Component Analysis ### 1. Macroeconomic Risk Factors #### Yield Curve Analysis The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations. Implementation: - 2Y-10Y Spread: Captures market expectations of monetary policy trajectory - 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure. #### Credit Risk Premium Assessment High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress. Threshold Calibration: - Normal conditions: < 350 basis points - Elevated risk: 350-500 basis points - Severe stress: > 500 basis points #### Currency and Commodity Stress Indicators The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress. ### 2. Technical Analysis Factors #### Multi-Timeframe Moving Average Analysis The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules. Implementation: - Price relative to 50-day and 200-day simple moving averages - Moving average convergence/divergence analysis - Multi-timeframe MACD assessment (daily and weekly) #### Momentum and Volatility Analysis The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement. ### 3. Market Sentiment Factors #### Volatility Index Analysis The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average. Calibration: - Low volatility: VIX < 20 - Elevated concern: VIX 20-25 - High fear: VIX > 25 - Panic conditions: VIX > 30 #### Put-Call Ratio Analysis Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets. ### 4. Market Breadth Factors #### Advance-Decline Analysis Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns. Components: - Daily advance-decline ratio - Advance-decline line momentum - McClellan Oscillator (Ema19 - Ema39 of A-D difference) #### New Highs-New Lows Analysis The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990). ## Dynamic Threshold Methodology The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions. Dynamic Threshold Calculation: - Warning Level: Base threshold ± (Volatility × 1.0) - Danger Level: Base threshold ± (Volatility × 1.5) - Bounds: ±10-20 points from base threshold ## Professional Implementation ### Institutional Usage Patterns Professional risk managers typically employ multi-factor bear market models in several contexts: #### 1. Portfolio Risk Management - Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70% - Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached - Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods #### 2. Risk Budgeting - Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations - Stress Testing: Using probability levels to calibrate stress test scenarios - Capital Requirements: Adjusting regulatory capital based on systemic risk assessment #### 3. Client Communication - Risk Reporting: Quantifying market risk for client presentations - Investment Committee Decisions: Providing objective risk metrics for strategic decisions - Performance Attribution: Explaining defensive positioning during market stress ### Implementation Framework Professional traders typically implement such models through: #### Signal Hierarchy: 1. Probability < 30%: Normal risk positioning 2. Probability 30-50%: Increased hedging, reduced leverage 3. Probability 50-70%: Defensive positioning, cash building 4. Probability > 70%: Maximum defensive posture, short exposure consideration #### Risk Management Integration: - Position Sizing: Inverse relationship between probability and position size - Stop-Loss Adjustment: Tighter stops during elevated risk periods - Correlation Monitoring: Increased attention to cross-asset correlations ## Strengths and Advantages ### 1. Comprehensive Coverage The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes. ### 2. Dynamic Adaptability The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes. ### 3. Real-Time Processing Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management. ### 4. Transparency and Interpretability The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals. ### 5. Historical Validation Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power. ## Limitations and Weaknesses ### 1. Data Dependencies The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions. ### 2. Regime Change Sensitivity Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007). ### 3. False Signal Risk Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods. ### 4. Currency and Geographic Bias The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets. ### 5. Correlation Breakdown During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002). ## References Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851. Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680. Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292. Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24. Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764. Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27. Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26. Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street. Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61. Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49. Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261. Fosback, N. G. (1976). 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Pine Script®指標
由EdgeTools提供
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Normalized DXY+Custom USD Index (DXY+) – Normalized Dollar Strength with Bitcoin, Gold, and Yuan. This custom USD strength index replicates the structure of the official U.S. Dollar Index (DXY), while expanding it to include modern financial assets such as Bitcoin (BTC), Ethereum (ETH), gold (XAU), and the Chinese yuan (CNY). Weights for the core fiat currencies (EUR, JPY, GBP, CAD, SEK, CHF) follow the official ICE DXY methodology. Additional components are weighted proportionally based on their estimated global economic influence. The index is normalized from its initial valid data point, meaning it starts at 100 on the first day all asset inputs are available. From that point forward, it tracks the relative strength of the U.S. dollar against this expanded basket. This provides a more comprehensive and modernized view of the dollar's strength—not only against traditional fiat currencies, but also in the context of rising decentralized assets and non-Western trade power.
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由travisryno提供
Custom USD IndexThis is a modernized, expanded version of the U.S. Dollar Index (DXY), designed to provide a more accurate representation of the dollar’s global strength in today’s diversified economy. Unlike the traditional DXY, which excludes major players like China and entirely omits real-world stores of value, this custom index (DXY+) includes: Fiat Currencies (78.3% total weight): EUR, JPY, GBP, CAD, AUD, CHF, and CNY — equally weighted to reflect the global currency landscape. Gold (17.5%): Gold (XAUUSD) is included as a traditional reserve asset and inflation hedge, acknowledging its continued monetary relevance. Cryptocurrencies (2.8% total weight): Bitcoin (BTC) and Ethereum (ETH) represent the emerging digital monetary layer. The index rises when the U.S. dollar strengthens relative to this blended basket, and falls when the dollar weakens against it. This is ideal for traders, economists, and macro analysts seeking a more inclusive and up-to-date measure of dollar performance.
Pine Script®指標
由travisryno提供