Yearly History Calendar-Aligned Price up to 10 Years)Overview
This indicator helps traders compare historical price patterns from the past 10 calendar years with the current price action. It overlays translucent lines (polylines) for each year’s price data on the same calendar dates, providing a visual reference for recurring trends. A dynamic table at the top of the chart summarizes the active years, their price sources, and history retention settings.
Key Features
Historical Projections
Displays price data from the last 10 years (e.g., January 5, 2023 vs. January 5, 2024).
Price Source Selection
Choose from Open, Low, High, Close, or HL2 ((High + Low)/2) for historical alignment.
The selected source is shown in the legend table.
Bulk Control Toggles
Show All Years : Display all 10 years simultaneously.
Keep History for All : Preserve historical lines on year transitions.
Hide History for All : Automatically delete old lines to update with current data.
Individual Year Settings
Toggle visibility for each year (-1 to -10) independently.
Customize color and line width for each year.
Control whether to keep or delete historical lines for specific years.
Visual Alignment Aids
Vertical lines mark yearly transitions for reference.
Polylines are semi-transparent for clarity.
Dynamic Legend Table
Shows active years, their price sources, and history status (On/Off).
Updates automatically when settings change.
How to Use
Configure Settings
Projection Years : Select how many years to display (1–10).
Price Source : Choose Open, Low, High, Close, or HL2 for historical alignment.
History Precision : Set granularity (Daily, 60m, or 15m).
Daily (D) is recommended for long-term analysis (covers 10 years).
60m/15m provides finer precision but may only cover 1–3 years due to data limits.
Adjust Visibility & History
Show Year -X : Enable/disable specific years for comparison.
Keep History for Year -X : Choose whether to retain historical lines or delete them on new year transitions.
Bulk Controls
Show All Years : Display all 10 years at once (overrides individual toggles).
Keep History for All / Hide History for All : Globally enable/disable history retention for all years.
Customize Appearance
Line Width : Adjust polyline thickness for better visibility.
Colors : Assign unique colors to each year for easy identification.
Interpret the Legend Table
The table shows:
Year : Label (e.g., "Year -1").
Source : The selected price type (e.g., "Close", "HL2").
Keep History : Indicates whether lines are preserved (On) or deleted (Off).
Tips for Optimal Use
Use Daily Timeframes for Long-Term Analysis :
Daily (1D) allows 10+ years of data. Smaller timeframes (60m/15m) may have limited historical coverage.
Compare Recurring Patterns :
Look for overlaps between historical polylines and current price to identify potential support/resistance levels.
Customize Colors & Widths :
Use contrasting colors for years you want to highlight. Adjust line widths to avoid clutter.
Leverage Global Toggles :
Enable Show All Years for a quick overview. Use Keep History for All to maintain continuity across transitions.
Example Workflow
Set Up :
Select Projection Years = 5.
Choose Price Source = Close.
Set History Precision = 1D for long-term data.
Customize :
Enable Show Year -1 to Show Year -5.
Assign distinct colors to each year.
Disable Keep History for All to ensure lines update on year transitions.
Analyze :
Observe how the 2023 close prices align with 2024’s price action.
Use vertical lines to identify yearly boundaries.
Common Questions
Why are some years missing?
Ensure the chart has sufficient historical data (e.g., daily charts cover 10 years, 60m/15m may only cover 1–3 years).
How do I update the data?
Adjust the Price Source or toggle years/history settings. The legend table updates automatically.
Cari skrip untuk "2024年5月黄金价格"
BTC Markup/Markdown Zones by Koenigsegg📈 BTC Markup/Markdown Zones
A handcrafted indicator designed to mark Bitcoin's most critical High Time Frame (HTF) structure shifts. This tool overlays true institutional-level Markup and Markdown Zones, selected manually after deep market review. Whether you're testing strategies or actively trading, this tool gives you the bigger picture at all times.
🔍 Key Features:
✅ HTF Markup & Markdown Zones
Every zone is manually selected — no indicators, no repainting. Just raw market history and real structure.
✅ Two Display Modes
• Background Zones — soft overlays with low opacity for visual context — with the option to increase opacity manually if desired.
• Start Candle Highlight — sharply highlighted candle marking the final pivot before a macro reversal.
✅ Custom Color Controls (Style Tab)
All visual styling lives in the Style tab, with clearly labeled fields:
• Markup Zone
• Markdown Zone
• Start Candle Highlight Markup
• Start Candle Highlight Markdown
✅ Minimal Input Section
Just one toggle: display mode. Everything else is kept clean and intuitive.
🧠 Purpose:
This script is made for any timeframe:
• Zoom into lower timeframes to know whether you're trading inside a Markup or Markdown
• Use it during strategy testing for true structural awareness
📅 Handpicked Macro Turning Points:
Each zone originates from a manually confirmed candle — the last meaningful candle before a shift in control between bulls and bears:
• FRI 19 AUG 2011 12PM – MARK DOWN
• THU 20 OCT 2011 12AM – MARK UP
• WED 10 APR 2013 12PM – MARK DOWN
• FRI 12 APR 2013 12PM – MARK UP
• SAT 30 NOV 2013 12AM – MARK DOWN
• WED 14 JAN 2015 12PM – MARK UP
• SUN 17 DEC 2017 12PM – MARK DOWN
• SAT 15 DEC 2018 12PM – MARK UP
• WED 14 APR 2021 4AM – MARK DOWN
• TUE 22 JUN 2021 12PM – MARK UP
• WED 10 NOV 2021 12PM – MARK DOWN
• MON 21 NOV 2022 8PM – MARK UP
• THU 14 MAR 2024 4AM – MARK DOWN
• MON 5 AUG 2024 12PM – MARK UP
• MON 20 JAN 2025 4AM – MARK DOWN
💡 Zones are manually updated by me after each new confirmed Markup or Markdown.
🧬 Fractal Structure for MTF Systems
Price is fractal — meaning the same principles of structure repeat across all timeframes. In Version 2, this tool evolves by introducing manually selected sub-zones inside each High Time Frame (HTF) Markup or Markdown. These sub-zones reflect Medium Timeframe (MTF) structure shifts, offering precision for traders who operate on both intraday and swing levels.
This makes the indicator ideal for low timeframe (LTF) Markup/Markdown awareness — whether you're managing 15m entries or building multi-timeframe confluence systems.
No auto-zones. No guesswork. Just clean, intentional structure division within the broader trend, handpicked for maximum clarity and edge.
💡 Pro Tip:
When price is inside a Markup Zone, shorting becomes riskier — you're trading against a macro bullish structure.
When inside a Markdown Zone, longing becomes riskier — you're fighting against confirmed bearish momentum.
Use this tool to stay aligned with the broader move, especially when zoomed into smaller timeframes or managing entries/exits during intraday setups.
📈 Markup Phase – Bullish Sentiment
Definition: A period where price makes higher highs and higher lows — the uptrend is in full force.
Why sentiment is bullish:
- Institutions and smart money are already positioned long.
- Public/institutional demand drives prices up.
- Momentum is supported by positive news, breakouts, and FOMO.
- Higher highs confirm buyers are in control.
📉 Markdown Phase – Bearish Sentiment
Definition: A period where price makes lower lows and lower highs — clear downtrend.
Why sentiment is bearish:
- Distribution has already occurred, and supply outweighs demand.
- Smart money is short or sidelined, waiting for deeper prices.
- Panic selling or trend-following traders add downside momentum.
- Lower lows confirm sellers are in control.
❌ Trading Against the Trend — Consequences:
-Reduced Probability of Success
-You’re fighting the dominant flow. Most participants are pushing in the opposite direction.
-Drawdowns & Stop-Outs
-Countertrend trades often get wicked or flushed before any meaningful move, especially without structure-based entries.
-Low Risk-Reward Ratio
-Trends offer sustained moves. Countertrend trades may have small take-profit zones or chop.
-Mental Drain & Doubt
-Fighting momentum causes anxiety, second-guessing, and emotional reactions.
-Missed Opportunities
-Focusing on fighting the trend makes you blind to the high-probability setups with the trend.
-Increased Transaction Costs
-More stop-outs and re-entries mean more fees, more friction.
-FOMO from Watching the Trend Run
-Entering countertrend means you might watch the trend explode without you.
-Confirmation Bias & Stubbornness
-Countertrend traders often look for reasons to justify staying in the wrong direction — leading to bigger losses.
🧠 Summary
In markup = bulls dominate → you swim with the current.
In markdown = bears dominate → going long is like pushing a rock uphill.
Trading with the trend is not just safer, it's smarter. The edge lives in momentum — not ego.
⚠️ Disclaimer
This indicator is for educational and analytical use only. It is not financial advice and should not be relied on for decision-making without personal analysis.
This is not a predictive tool. No indicator can forecast upcoming price movements.
What you see here is based purely on past market behavior — specifically, historical tops and bottoms that marked the start of confirmed reversals.
This script does not know where the next reversal begins, nor can it determine where a new Markup or Markdown starts or ends. It is designed to provide context, not prediction.
Always trade with responsibility and perform your own due diligence.
BTC Daily DCA CalculatorThe BTC Daily DCA Calculator is an indicator that calculates how much Bitcoin (BTC) you would own today by investing a fixed dollar amount daily (Dollar-Cost Averaging) over a user-defined period. Simply input your start date, end date, and daily investment amount, and the indicator will display a table on the last candle showing your total BTC, total invested, portfolio value, and unrealized yield (in USD and percentage).
Features
Customizable Inputs: Set the start date, end date, and daily dollar amount to simulate your DCA strategy.
Results Table: Displays on the last candle (top-right of the chart) with:
Total BTC: The accumulated Bitcoin from daily purchases.
Total Invested ($): The total dollars invested.
Portfolio Value ($): The current value of your BTC holdings.
Unrealized Yield ($): Your profit/loss in USD.
Unrealized Yield (%): Your profit/loss as a percentage.
Visual Markers: Green triangles below the chart mark each daily investment.
Overlay on Chart: The table and markers appear directly on the BTCUSD price chart for easy reference.
Daily Timeframe: Designed for Daily (1D) charts to ensure accurate calculations.
How to Use
Add the Indicator: Apply the indicator to a BTCUSD chart (e.g., Coinbase:BTCUSD, Binance:BTCUSDT).
Set Daily Timeframe: Ensure your chart is on the Daily (1D) timeframe, or the script will display an error.
Configure Inputs: Open the indicator’s Settings > Inputs tab and set:
Start Date: When to begin the DCA strategy (e.g., 2024-01-01).
End Date: When to end the strategy (e.g., 2025-04-27 or earlier).
Daily Investment ($): The fixed dollar amount to invest daily (e.g., $100).
View Results: Scroll to the last candle in your date range to see the results table in the top-right corner of the chart. Green triangles below the bars indicate investment days.
Settings
Start Date: Choose the start date for your DCA strategy (default: 2024-01-01).
End Date: Choose the end date (default: 2025-04-27). Must be after the start date and within available chart data.
Daily Investment ($): Set the daily investment amount (default: $100). Minimum is $0.01.
Notes
Timeframe: The indicator requires a Daily (1D) chart. Other timeframes will trigger an error.
Data: Ensure your BTCUSD chart has historical data for the selected date range. Use reliable pairs like Coinbase:BTCUSD or Binance:BTCUSDT.
Limitations: Does not account for trading fees or slippage. Future dates (beyond the current date) will not display results.
Performance: Works best with historical data. Free TradingView accounts may have limited historical data; consider premium for longer ranges.
UB Short Signal (10Y Yield Future Spike)"This indicator identifies short opportunities on UB futures based on inverse correlation with 10Y Yield Futures. A macro trading tool to be used with additional confirmations."
🎯 Indicator Strategy
This tool generates sell signals for Ultra Bond (UB) futures when:
The Micro 10-Year Yield Future shows an upward spike (> adjustable threshold)
Trading volume is significant (false signal filter)
Inverse correlation is confirmed (UB falls when 10Y rises)
⚙️ Parameters
Spike Threshold: Sensitivity adjustment (e.g., 0.08% for swing trading)
Minimum Volume: Default 100 (optimized for Micro 10Y contracts)
📊 Recent Backtest
06/15/2024: +0.10% spike → UB dropped -0.3% within 15 minutes
06/18/2024: Valid signal post-CPI release
⚠️ Disclaimer
Analytical tool only – not financial advice
Must be combined with proper risk management
Daily Bollinger Band StrategyOverview of the Daily Bollinger Band Strategy
1. Strategy Overview and Features
This strategy is a tool for backtesting a trading method that uses Bollinger Bands. It is *not* a tool for automated trading.
1-1. Main Display Items
The main chart displays the Bollinger Bands and the 200-day moving average.
It also shows the entry and exit points along with the position size (in units of 100 shares).
1-2. Summary of Trading Rules
For long (buy) strategies, the trade enters when the price crosses above the +1σ line of the Bollinger Bands, aiming to ride an upward trend. The position is exited when the price crosses below the middle band.
For short (sell) strategies, the trade enters when the price crosses below the -1σ line of the Bollinger Bands, aiming to ride a downward trend. The position is exited when the price crosses above the middle band.
1-3. Strategic Enhancements
The strategy uses the slope of the 200-day moving average to determine the trend direction and enter trades accordingly. This improves the win rate and payoff ratio.
Additionally, to reduce the probability of ruin, the risk per trade is limited to 1.0% of capital, and position sizing is adjusted using ATR (a volatility indicator).
2. Trading Rules
2-1. Chart Type
Only daily charts are used.
2-2. Indicators Used
(1) Bollinger Bands** (used for entry and exit signals)
- Period: Fixed at 80 days
- Upper and lower bands: Fixed at ±1σ
(2) Moving Average** (used to determine trend direction)
- Period: Fixed at 200 days
- Trend direction is judged based on whether the difference from the previous day is positive (upward) or negative (downward)
2-3. Buy Rules
Setup:
- Price crosses above the +1σ line from below
- Both the middle band and 200-day moving average are upward sloping
Entry:
- Buy at the next day’s market open using a market order
Exit:
- If the price crosses below the middle band, sell at the next day’s open using a market order
2-4. Sell Rules
Setup:
- Price crosses below the -1σ line from above
- Both the middle band and 200-day moving average are downward sloping
Entry:
- Sell at the next day’s market open using a market order
Exit:
- If the price crosses above the middle band, buy back at the next day’s open using a market order
2-5. Risk Management Rules
- Risk per trade: 1.0% of total capital (acceptable loss = capital × 1.0%)
- Position size: Acceptable loss ÷ 2ATR (rounded down to the nearest unit of 100 shares)
2-6. Other Notes
- No brokerage fees
- No pyramiding
- No partial exits
- No reverse positions (no “stop-and-reverse” trades)
3. Strategy Parameters
The following settings can be specified:
3-1. Period Settings
- Start date: Set the start date for the backtest period
- Stop date: Set the end date for the backtest period
3-2. Display of Trend and Signals
- Show trend: When checked, the background color of the bars is light red for an uptrend and light blue for a downtrend
- Show signal: When checked, entry and exit signals are displayed (note: signals are executed at the next day’s open, so there is a one-day lag in the display)
3-3. Capital Management Settings
- Funds: Capital available for trading (in JPY)
- Risk rate: Specify what percentage of the capital to risk per trade
Settings in the “Properties” tab are not used in this strategy.
4. Backtest Results (Example)
Here are the backtest results conducted by the author:
- Target Stocks: All components of the Nikkei 225
- Test Period: January 4, 2000 – December 30, 2024
- Data Points: 12,886
- Win Rate: 33.45%
- Net Profit: ¥82,132,380
- Payoff Ratio: 2.450
- Expected Value: ¥6,373.8
- Risk Rate: 1.0%
- Probability of Ruin: 0.00%
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デイリー・ボリンジャーバンド・ストラテジーの概要
1. ストラテジーの概要と特徴
このストラテジーは、ボリンジャーバンドを使ったトレード手法のバックテストを行うツールです。自動売買を行うツールではありません。
1-1. 主な表示項目
メインチャートにボリンジャーバンドと 200日移動平均線を表示します。
また、エントリーと手仕舞いのタイミングと数量（100株単位）も表示されます。
1-2. トレードルールの概要
買い戦略の場合、ボリンジャーバンドの +1σ 超えでエントリーして上昇トレンドに乗り、ミドルバンドを割ったら決済します。
売り戦略の場合、ボリンジャーバンドの -1σ 割りでエントリーして下降トレンドに乗り、ミドルバンドを上抜けたら決済します。
1-3. ストラテジーの工夫点
200日移動平均線の傾きを見てトレンド方向にエントリーをしています。こうして勝率とペイオフレシオの成績を向上しています。
また、破産確率を抑えるために、リスク資金比率を 1.0% にして、ATR（ボラティリティ指標） を使って注文数を調整しています。
2. 売買ルール
2-1. 使用するチャート
日足チャートに限定します
2-2. 使用する指標
(1) ボリンジャーバンド（仕掛けと手仕舞いのシグナルに使用）
期間は80日に固定
上下バンドは ±1σ に固定
(2) 移動平均線（トレンドの方向を見るために使用）
期間は200日に固定
移動平均の値の前日との差がプラスのとき上向き、マイナスのとき下向きと判断
2-3. 買いのルール
セットアップ：ボリンジャーバンドの +1σ を価格が下から上に交差 かつ ミドルバンドと 200日移動平均線が上向き
仕掛け：翌日の寄り付きに成行で買う
手仕舞い：ボリンジャーバンドのミドルバンドを価格が上から下に交差したら、翌日の寄り付きに成行で売る
2-4. 売りのルール
セットアップ：ボリンジャーバンドの -1σ を価格が上から下に交差 かつ ミドルバンドと 200日移動平均線が下向き
仕掛け：翌日の寄り付きに成行で売る
手仕舞い：ボリンジャーバンドのミドルバンドを価格が下から上に交差したら、翌日の寄り付きに成行で買い戻す
2-5. 資金管理のルール
リスク資金比率：資産の 1.0%（許容損失 = 資産 × 1.0%）
注文数：許容損失 ÷ 2ATR（単元株数未満は切り捨て）
2-6. その他
仲介手数料：なし
ピラミッディング：なし
分割決済：なし
ドテン：しない
3. ストラテジーのパラメーター
次の項目が指定できます。
3-1. 期間の設定
Staer date : バックテストの検証期間の開始日を指定します
Stop date : バックテストの検証期間の終了日を指定します
3-2. トレンドとシグナルの表示
Show trend : チェックを入れると、バーの背景色が、トレンドが上昇のときは薄い赤で、下落のときは薄い青で表示されます
Show signal : チェックを入れると、エントリーと手仕舞いのシグナルを表示します（シグナルの出た翌日の寄り付きに売買をするので表示に1日のずれがあります）
3-3. 資金管理用の設定
Funds : トレード用の資金(円)
Risk rate : 許容損失を資金の何%にするかで指定します
「プロパティタブ」で設定する値は、このストラテジーでは有効ではありません。
4. バックテストの結果（例）
作者がバックテストを実施した結果をお知らせします。
対象銘柄：日経225構成銘柄すべて
対象期間：2000年1月4日～2024年12月30日
データ件数：12,886
勝率：33.45%
純利益：82,132,380
ペイオフレシオ：2.450
期待値：6,373.8
リスク資金比率：1.0%
破産確率：0.00%
Gann & Fibonacci Analysis for MSTRYes! Below is a step-by-step guide to performing Gann Analysis on MSTR in TradingView for the last year.
Step 1: Set Up the Chart
Open TradingView and search for MSTR (MicroStrategy).
Select the 1-day (D) timeframe to analyze the past year.
Set your chart to logarithmic scale (⚙ Settings → Scale → Log).
Enable grid lines for alignment (⚙ Settings → Appearance → Grid Lines).
Step 2: Identify Key Highs and Lows (Last Year)
Find the 52-week high and 52-week low for MSTR.
As of now:
52-Week High: ~$999 (March 2024).
52-Week Low: ~$280 (October 2023).
Step 3: Plot Gann Angles
Using TradingView's Gann Fan Tool:
Select "Gann Fan" (Press / and type “Gann Fan” to find it).
Start at the 52-week low (~$280, October 2023) and drag upwards.
Adjust the angles to match key levels:
1x1 (45°) → Main trendline
2x1 (26.5°) → Strong uptrend
4x1 (15°) → Weak trendline
1x2 (63.75°) → Strong resistance
Repeat the process from the 52-week high (~$999, March 2024) downward to see bearish angles.
Step 4: Apply Fibonacci & Gann Retracement Levels
Using Fibonacci Retracement:
Select "Fibonacci Retracement" tool.
Draw from 52-week high ($999) to 52-week low ($280).
Enable key Fibonacci levels:
23.6% ($816)
38.2% ($678)
50% ($640)
61.8% ($550)
78.6% ($430)
Watch for price reactions near these levels.
Using Gann Retracement Levels:
Select "Gann Box" in TradingView.
Draw from 52-week high ($999) to low ($280).
Enable key Gann retracement levels:
12.5% ($912)
25% ($850)
37.5% ($768)
50% ($640)
62.5% ($550)
75% ($480)
87.5% ($350)
Identify confluences with Gann angles and Fibonacci levels.
Step 5: Identify Significant Dates & Time Cycles
Use "Date Range" Tool in TradingView.
Mark major turning points:
High → Low: ~180 days (Half-year cycle).
Low → High: ~90 days (Quarter cycle).
Use Square-Outs (Time = Price method):
Example: If MSTR hit $500, check 500 days from key events.
Mark key anniversaries of past highs/lows for possible reversals.
Step 6: Analyze and Trade Execution
✅ If MSTR is at a Gann angle + Fibonacci level + key date → Expect a reaction.
✅ Use RSI, MACD, and Volume for extra confirmation.
✅ Set Stop-Loss at nearest Gann support/resistance.
Full Moon and New Moon IndicatorThe Full Moon & New Moon Indicator is a custom Pine Script indicator which marks Full Moon (Pournami) and New Moon (Amavasya) events on the price chart. This indicator helps traders who incorporate lunar cycles into their market analysis, as certain traders believe these cycles influence market sentiment and price action. The current script is added for the year 2024 and 2025 and the dates are considered as per the Telugu calendar.
Features
✅ Identifies and labels Full Moon & New Moon days on the chart for the year 2024 and 2025
How it Works!
On a Full Moon day, it places a yellow label ("Pournami") above the corresponding candle.
On a New Moon day, it places a blue label ("Amavasya") above the corresponding candle.
Example Usage
When a Full Moon label appears, check for potential trend reversals or high volatility.
When a New Moon label appears, watch for market consolidation or a shift in sentiment.
Combine with candlestick patterns, support/resistance, or momentum indicators for a stronger trading setup.
🚀 Add this indicator to your TradingView chart and explore the market’s reaction to lunar cycles! 🌕
US/JP Factor/Sector Performance RankingThis indicator is designed to help you easily understand the strengths and weaknesses of different factors and sectors in the U.S. stock market. It looks at various ETFs, ranks their performance over a specific period (20 days by default), and shows the results visually.
= How the Ranking Works
The best-performing rank is shown as -1, with lower ranks as -2, -3, -4, and so on. This setup makes it easy to see rank order in TradingView’s default view.
If you turn on the “Inverse” setting, ranks will be shown as positive numbers in order (e.g., 1, 2, 3…). In this case, it’s recommended to reverse the TradingView scale for better understanding.
= How the Indicator Reacts to Market Conditions
- Normal Market Conditions
Certain factors or sectors often stay at the top rank. For example, during the rallies at the start of 2024 and in May, the Momentum factor performed well, showing a risk-on market environment.
On the other hand, sectors at the bottom rank also tend to stay in specific positions.
- Market Tops
Capital flows within sectors slow down, and top ranks begin to change frequently. This may suggest a market turning point.
- Bear Markets or High Volatility
Rankings become more chaotic in these conditions. These large changes can help you understand market sentiment and the level of volatility.
= Way of using the Indicator
You can use this indicator in the following ways:
- To apply sector rotation strategies.
- To build positions after volatile markets calm down.
- To take long positions on strong elements (higher ranks) and short positions on weaker ones (lower ranks).
= Things to Keep in Mind
It’s a Lagging Indicator
This indicator calculates rankings using the past 20 days of data. It doesn’t provide signals for the future but is a tool for analyzing past performance. To predict the market, you should combine this with other tools or leading indicators.
However, since trends in capital flows often continue, this indicator can help you spot those trends.
= Customization
This indicator is set up for U.S. and Japanese stock markets. However, you can customize it for other markets by changing the ticker and label description in the script.
==Japanese Description==
このインジケーターは、米国株市場におけるファクターやセクターの強弱を直感的に把握するために設計されています。
各ETFを参照し、特定期間（デフォルトでは20日間）のパフォーマンスを順位付けし、それを視覚的に表示します。
= インジケーターの特徴
- ランク付けの仕様
ランク1位は-1で表され、順位が下がるごとに-2、-3、-4…と減少します。この仕様により、TradingViewの標準状態でランクの高低を直感的に把握できるようにしました。
さらに、Inverse設定をONにすると、1位から順に正の値（例: 1, 2, 3…）で表示されるようになります。この場合、TradingViewのスケールを反転させることを推奨します。
= 市況とインジケーターの動き
- 平常時の市況
特定のファクターやセクターがランク1位を維持することが多いです。
例えば、2024年の年初や同年5月の上昇相場では、Momentumファクターが効果を発揮し、リスクオンの市場環境であったことを示しています。
一方、最下位に位置するセクターも特定の順位を維持する傾向があります。
- 天井圏の市況
セクター内の資金流入や流出が停滞し、上位ランクの変動が起こり始めます。これが市場の転換点を示唆する場合があります。
- 下落相場や荒れた市況
ランク順位が大きく乱れることが特徴です。この変動の大きさは、市況の雰囲気やボラティリティの高さを感じ取る材料として活用できます。
= 活用方法
このインジケーターは以下のような投資戦略に役立てることができます：
- セクターローテーションを活用した投資戦略
- 荒れた相場が落ち着いたタイミングでのポジション構築
- 強い要素（ランク上位）のロング、弱い要素（ランク下位）のショート
= 注意点
- 遅行指標であること
本インジケーターは、過去20日間のデータを基にランクを算出します。そのため、先行的なシグナルを提供するものではなく、過去のパフォーマンスに基づいた分析ツールです。市場を先回りするには、別途先行指標や分析を組み合わせる必要があります。
ただし、特定のファクターやセクターへの資金流入・流出が継続する傾向があるため、これを見極める手助けにはなります。
= カスタマイズについて
このインジケーターは米国・日本株市場に特化しています。ただし、他国のファクターやセクターのETFや指数が利用可能であれば、スクリプト内のtickerとlabel descriptionを変更することでカスタマイズが可能です。
TASC 2024.12 Dynamic ADX Histogram█ OVERVIEW
This script introduces a new version of the ADX oscillator, designed by Neil Jon Harrington and featured in the "Revisualizing The ADX Oscillator" article from the December 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
The directional movement index (DMI+ and DMI−) and average directional index (ADX) indicators have long been popular with technical analysts. Developed by J. Welles Wilder in the 1970s, these indicators provide information about the direction and strength of price movements across bars. The DMI+ measures positive price movement, the DMI- measures negative price movement, and the ADX gauges the average strength of price trends. Although these indicators can provide helpful insights into price action and momentum, Neil Jon Harrington argues they are often misunderstood or misapplied.
Harrington's indicator, the Dynamic ADX Histogram (DADX), applies directional information to the ADX based on DMI+ and DMI- values to create a single oscillator centered around 0. The indicator displays the oscillator as a histogram with dynamic colors based on ADX movements and user-defined strength thresholds. The author believes this modification of the ADX and DMI data offers a more intuitive visualization of the information provided by Wilder's calculations.
An additional feature of the DADX is the option to use average (smooth) DMI+ and DMI- values in the oscillator's calculation, which reduces noise and choppiness at the cost of added lag.
█ USAGE
The "ADX Length" input determines the number of bars in the DMI and ADX calculation. The "DMI Smoothing Length" input controls the number of bars in the DMI smoothing calculation. Use a value of 1 for non-smoothed DMI data.
The sign of the DADX indicates the direction of price movements based on the difference between the smoothed DMI+ and DMI- values. The absolute value of the oscillator corresponds to the ADX, representing the trend strength.
The "Low Threshold" and "High Threshold" inputs define the ADX thresholds for categorizing trending, non-trending, and exhaustion states. The low threshold specifies the minimum absolute oscillator value required to indicate a trend, and the high threshold marks the absolute value where trend strength is excessive, possibly suggesting an upcoming consolidation or reversal. The indicator colors the histogram based on these thresholds and changes in the ADX, with brighter colors denoting a strengthening trend and darker colors signaling a weakening trend.
McRib Bull Market Indicator# McRib Bull Market Indicator
## Overview
The McRib Bull Market Indicator is a unique technical analysis tool that marks McDonald's McRib sandwich release dates on your trading charts. While seemingly unconventional, this indicator serves as a fascinating historical reference point for market analysis, particularly for studying periods of market expansion.
## Key Features
- Visual yellow labels marking verified McRib release dates from 2012 to 2024
- Clean, unobtrusive design that overlays on any chart timeframe
- Covers both U.S. and international releases (including UK and Australia)
## Historical Reference Points
The indicator includes release dates from:
- December 2012
- October-December 2014
- January 2015
- October 2016
- November 2017
- October 2018
- October 2019
- December 2020
- October 2022
- November 2023
- December 2024
## Usage Guide
1. Add the indicator to any chart by searching for "McRib Bull Market Indicator"
2. The indicator will automatically display yellow labels above price candles on McRib release dates
3. Use these reference points to:
- Analyze market conditions during McRib releases
- Study potential correlations between releases and market movements
- Compare market behavior across different McRib release periods
- Identify any patterns in market expansion phases coinciding with releases
## Trading Application
While initially created as a novelty indicator, it can be used to:
- Mark specific historical points of reference for broader market analysis
- Study potential market psychology around major promotional events
- Compare seasonal market patterns with recurring release dates
- Analyze market expansion phases that coincide with releases
Remember: While this indicator provides interesting historical reference points, it should be used as part of a comprehensive trading strategy rather than as a standalone trading signal.
XAUUSD 10-Minute StrategyThis XAUUSD 10-Minute Strategy is designed for trading Gold vs. USD on a 10-minute timeframe. By combining multiple technical indicators (MACD, RSI, Bollinger Bands, and ATR), the strategy effectively captures both trend-following and reversal opportunities, with adaptive risk management for varying market volatility. This approach balances high-probability entries with robust volatility management, making it suitable for traders seeking to optimise entries during significant price movements and reversals.
Key Components and Logic:
MACD (12, 26, 9):
Generates buy signals on MACD Line crossovers above the Signal Line and sell signals on crossovers below the Signal Line, helping to capture momentum shifts.
RSI (14):
Utilizes oversold (below 35) and overbought (above 65) levels as a secondary filter to validate entries and avoid overextended price zones.
Bollinger Bands (20, 2):
Uses upper and lower Bollinger Bands to identify potential overbought and oversold conditions, aiming to enter long trades near the lower band and short trades near the upper band.
ATR-Based Stop Loss and Take Profit:
Stop Loss and Take Profit levels are dynamically set as multiples of ATR (3x for stop loss, 5x for take profit), ensuring flexibility with market volatility to optimise exit points.
Entry & Exit Conditions:
Buy Entry: T riggered when any of the following conditions are met:
MACD Line crosses above the Signal Line
RSI is oversold
Price drops below the lower Bollinger Band
Sell Entry: Triggered when any of the following conditions are met:
MACD Line crosses below the Signal Line
RSI is overbought
Price moves above the upper Bollinger Band
Exit Strategy: Trades are closed based on opposing entry signals, with adaptive spread adjustments for realistic exit points.
Backtesting Configuration & Results:
Backtesting Period: July 21, 2024, to October 30, 2024
Symbol Info: XAUUSD, 10-minute timeframe, OANDA data source
Backtesting Capital: Initial capital of $700, with each trade set to 10 contracts (equivalent to approximately 0.1 lots based on the broker’s contract size for gold).
Users should confirm their broker's contract size for gold, as this may differ. This script uses 10 contracts for backtesting purposes, aligned with 0.1 lots on brokers offering a 100-contract specification.
Key Backtesting Performance Metrics:
Net Profit: $4,733.90 USD (676.27% increase)
Total Closed Trades: 526
Win Rate: 53.99%
Profit Factor: 1.44 (1.96 for Long trades, 1.14 for Short trades)
Max Drawdown: $819.75 USD (56.33% of equity)
Sharpe Ratio: 1.726
Average Trade: $9.00 USD (0.04% of equity per trade)
This backtest reflects realistic conditions, with a spread adjustment of 38 points and no slippage or commission applied. The settings aim to simulate typical retail trading conditions. However, please adjust the initial capital, contract size, and other settings based on your account specifics for best results.
Usage:
This strategy is tuned specifically for XAUUSD on a 10-minute timeframe, ideal for both trend-following and reversal trades. The ATR-based stop loss and take profit levels adapt dynamically to market volatility, optimising entries and exits in varied conditions. To backtest this script accurately, ensure your broker’s contract specifications for gold align with the parameters used in this strategy.
TASC 2024.11 Ultimate Strength Index█ OVERVIEW
This script implements the Ultimate Strength Index (USI) indicator, introduced by John Ehlers in his article titled "Ultimate Strength Index (USI)" from the November 2024 edition of TASC's Traders' Tips . The USI is a modified version of Wilder's original Relative Strength Index (RSI) that incorporates Ehlers' UltimateSmoother lowpass filter to produce an output with significantly reduced lag.
█ CONCEPTS
Many technical indicators, including the RSI, lag due to their heavy reliance on historical data. John Ehlers reformulated the RSI to substantially reduce lag by applying his UltimateSmoother filter to upward movements ( strength up - SU ) and downward movements ( strength down - SD ) in the time series, replacing the standard process of smoothing changes with rolling moving averages (RMAs). Ehlers' recent works, covered in our recent script publications, have shown that the UltimateSmoother is an effective alternative to other classic averages, offering notably less lag in its response.
Ehlers also modified the RSI formula to produce an index that ranges from -1 to +1 instead of 0 to 100. As a result, the USI indicates bullish conditions when its value moves above 0 and bearish conditions when it falls below 0.
The USI retains many of the strengths of the traditional RSI while offering the advantage of reduced lag. It generally uses a larger lookback window than the conventional RSI to achieve similar behavior, making it suitable for trend trading with longer data lengths. When applied with shorter lengths, the USI's peaks and valleys tend to align closely with significant turning points in the time series, making it a potentially helpful tool for timing swing trades.
█ CALCULATIONS
The first step in the USI's calculation is determining each bar's strength up (SU) and strength down (SD) values. If the current bar's close exceeds the previous bar's, the calculation assigns the difference to SU. Otherwise, SU is zero. Likewise, if the current bar's close is below the previous bar's, it assigns the difference to SD. Otherwise, SD is zero.
Next, instead of the RSI's typical smoothing process, the USI's calculation applies the UltimateSmoother to the short-term average SU and SD values, reducing high-frequency chop in the series with low lag.
Finally, this formula determines the USI value:
USI = ( Ult (SU) − Ult (SD)) / ( Ult (SU) + Ult (SD)),
where Ult (SU) and Ult (SD) are the smoothed average strength up and strength down values.
TASC 2024.10 Adaptive Oscillator Threshold█ OVERVIEW
This script introduces a more dynamic approach to generating trading signals using the RSI indicator and a threshold that adapts to price trends and dispersion. This methodology comes from Francesco Bufi's article "Overbought/Oversold Oscillators: Useless Or Just Misused" from the October 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
According to Francesco Bufi's observations, an oscillator-based buy signal should have a threshold that varies with the trend direction: higher during uptrends and lower during downtrends. Additionally, the level should decrease as the distance from the price to its mean increases to reduce signals in volatile conditions. Accordingly, Bufi proposes a formula for an adaptive buy level whose value is proportional to the trend (linear regression slope) and inversely proportional to the typical distance between price and its mean (standard deviation). Traders can apply this method to any oscillator to add adaptivity without modifying the oscillator's calculations, as it's simply an adaptive technique for interpreting the calculated values.
This script demonstrates the application of Bufi's Adaptive Threshold (BAT) in a simple RSI-based strategy and allows users to compare its performance to the traditional fixed-threshold approach. Bufi's observations suggest that using the BAT instead of a static threshold can help improve the backtest performance of oscillator-based systems.
█ DISCLAIMER
This strategy script educates users on the trading systems outlined by the TASC article. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script.
TASC 2024.09 Precision Trend Analysis█ OVERVIEW
This script introduces an approach for detecting and confirming trends in price series based on digital signal processing principles, as presented by John Ehlers in the "Precision Trend Analysis" article from the September 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
Traditional trend-following indicators, such as moving averages , are lowpass filters that pass low-frequency components in a series and remove high-frequency components. Because lowpass filters preserve lengthy cycles in the data while attenuating shorter cycles, such filters have unavoidable lag that impacts the timeliness of trading signals.
In his article, John Ehlers presents an alternative approach that combines two highpass filters with different lengths to remove undesired high-frequency content via cancellation . Highpass filters have nearly zero lag. As such, the resulting trend indicator from this approach is very responsive to changes in the price series, with peaks and valleys that closely align with those of the price data. The indicator signifies an uptrend when its value is positive (i.e., above the balance point) and a downtrend when it is negative.
Subsequently, John Ehlers demonstrates that one can use the trend indicator's rate of change (ROC) to determine the onset of new trend movements. The ROC is zero at peaks and valleys in the trend indicator. Therefore, when the ROC crosses above zero, it signifies the onset or continuation of an uptrend. Likewise, the ROC crossing below zero indicates the onset or continuation of a downtrend. Note, however, that because the ROC does not preserve lower-frequency information, it can produce whipsaw trading signals in sideways or continuously trending price series.
This script implements both the trend indicator and its ROC along with the following on-chart signals:
• Green and red arrows that indicate the possible onset or continuation of an uptrend and downtrend, respectively
• Bar and plot colors that signify the sign (direction) of the trend indicator
█ CALCULATIONS
The math behind the trend indicator comes from digital filter design principles. The first step applies a digital highpass filter that attenuates long cycles with periods above the user-specified critical period. The default value is 250 bars, representing roughly one year for instruments such as stocks on the daily timeframe. The next step applies a highpass filter with a shorter period (40 bars by default). The difference between these filters determines the trend indicator, which preserves cyclic components between 40 and 250 bars by default while attenuating and eliminating others. The ROC represents the scaled one-bar difference in the trend indicator.
Grayscale GSOL Solana Financials [NeoButane]This script shows Grayscale's GSOL financials based on the information from their website. Investors and traders like to use financials when making the decision to buy, sell, or hold.
►Usage
This script is specific to GSOL. Investors and traders use financials when making the decision to buy, sell, or hold. How one interprets financials is up to the individual. For example, investors who believe a Solana ETF is coming soon can view the "% Discount / Premium to NAV", which is currently over 600%, and decide not to buy because the premium would collapse if an ETF began trading.
►Configuration
Data select the data you'd like to display.
Show Highest label show the highest value of the entire data set.
Line Color an expression of self.
Extrapolate Data Using Average or Last Known Value Shows a line beyond the dataset, using the average of all past data or the last data point to predict newer data. % Discount / Premium to NAV, Share Premium, and SOL Per Share are supported.
→Data retrieved from Grayscale
AUM assets under management.
NAV net asset value.
Market Price market price of GSOL.
Shares Outstanding number of shares held in the open market.
→Data retrieved from Grayscale, modified by me
% Discount / Premium to NAV the % away NAV is from the market price of GSOL.
Formula: (GSOL - NAV) / NAV
Share Premium the actual $ premium of GSOL to its NAV.
Formula: GSOL - NAV
SOL Per Share the amount of SOL 1 share of GSOL can redeem. This is derived using Kraken's SOLUSD daily close prices.
Formula: Kraken's SOLUSD / NAV
SOL Price Using Market Price Premium the price of SOL if GSOL's market price was "correct" and the SOL Per Share ratio remained the same.
Formula: GSOL / SOL Per Share
►How this works
Grayscale has a spreadsheet of historical data available on their GSOL page. Since financials are not available for OTC:GSOL, I placed all the data into arrays to emulate a symbol's price (y) coordinates. UNIX time for each day, also in an array, is used as the time (x) coordinates. The UNIX arrays and data arrays are then looped to plot as lines, with data y2 being the next data point, making it appear as a continuous line.
Grayscale's GSOL was downloaded spreadsheet and opened in Excel. SOLUSD prices were exported using TradingView export function. The output of information was pasted into Pine Script. For matching up Kraken's SOLUSD prices to each Grayscale's data since GSOL does not trade daily, dates were converted to UNIX and matched with xlookup(). A library or seed will be used in the future for updating.
References
Data retrieved from Grayscale's website 2024/08/04.
www.grayscale.com
Quantity of Solana held by the trust can be seen in their filings. Ctrl + F "Quantity of
SOL "
www.grayscale.com
Q1 2024: www.grayscale.com
The high premium can partly be explained by private placement currently being closed. This means private sales can't dilute share value.
www.etf.com
TASC 2024.08 Volume Confirmation For A Trend System█ OVERVIEW
This script demonstrates the use of volume data to validate price movements based on the techniques Buff Pelz Dormeier discusses in his "Volume Confirmation For A Trend System" article from the August 2024 edition of TASC's Traders' Tips . It presents a trend-following system implementation that utilizes a combination of three indicators: the Average Directional Index (ADX), the Trend Thrust Indicator (TTI), and the Volume Price Confirmation Indicator (VPCI).
█ CONCEPTS
In his article, Buff Pelz Dormeier recounts his search for an optimal trend-following strategy enhanced with volume data, starting with a simple system combining the ADX , MACD , and OBV indicators. Even in these early tests, the author observed that the volume confirmation from OBV notably improved trading performance. Subsequently, the author replaced OBV with his VPCI, which considers the proportional weights of volume and price, to enhance the validation of trend momentum. Lastly, the author explored the inclusion of his TTI, a modified MACD that features volume-based enhancements, as a strategy component for improved trend-following performance.
According to the author's research, the ADX+TTI+VPCI system outperformed similar strategies he tested in the article, yielding significantly higher returns and enhanced perceived reliability. Because the system's design revolves around catching pronounced trends, it performs best with a portfolio of individual stocks. The author applies the system in the article by allocating 5% of the equity to long positions in S&P 500 components that meet the ADX+TTI+VPCI entry criteria (see the Calculations section below for details). He uses the proceeds from closing positions to enter new positions in other stocks meeting the screening criteria, holding any excess proceeds in cash.
█ CALCULATIONS
The TTI is similar to the MACD. Its calculation entails the following steps:
Calculate fast (short-term) and slow (long-term) volume-weighted moving averages (VWMAs).
Compute the volume multiple (VM) as the square of the ratio of the fast VWMA to the slow VWMA.
Adjust these averages by multiplying the fast VWMA by the VM and dividing the slow VWMA by the VM.
Calculate the difference between the adjusted VWMAs to determine the TTI value, and take the average of that series to determine the signal line value.
The VPCI utilizes differences and ratios between VWMAs and corresponding simple moving averages (SMAs) to provide an alternative volume-price confirmation tool. Its calculation is as follows:
Subtract the slow SMA from the VWMA of the same length to calculate the volume-price confirmation/contradiction (VPC) value.
Divide the fast VWMA by the corresponding fast SMA to determine the volume-price ratio (VPR).
Divide the short-term VWMA by the long-term VWMA to calculate the VM.
Compute the VPCI as the product of the VPC, VPR, and VM values.
The long entry criteria of the ADX+TTI+VPCI system are as follows:
The ADX is above 30.
The TTI crosses above its signal line.
The VPCI is above 0, confirming the trend.
Signals to close positions occur when the VPCI is below 0, indicating a contradiction .
NOTE: Unlike in the article, this script applies the ADX+TTI+VPCI system to one stock at a time , not a portfolio of S&P 500 constituents.
█ DISCLAIMER
This strategy script educates users on the trading system outlined by the TASC article. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script.
TASC 2024.07 Gaps and Extreme Closes█ OVERVIEW
This script, inspired by Perry Kaufman's article "Trading Opening Gaps and Extreme Closes in Stocks" from the TASC's July 2024 edition of Traders' Tips , provides analytical insights into stock price behaviors following significant price moves. The information about the frequency, pullbacks, and closing patterns of these extreme price movements can aid in developing more effective trading strategies by understanding what to expect during volatile market conditions.
█ CONCEPTS
Perry Kaufman's article investigates the behavior of stock prices following substantial opening gaps and extreme closing moves to identify patterns and expectations that traders can utilize to make informed decisions. The motivation behind the article is to offer traders a more scientific approach to understanding price movements during volatile market conditions, particularly during earnings season or significant economic events. Kaufman's analysis reveals that stock prices have a history of exhibiting certain behaviors after substantial price gaps and extreme closes. This script follows Perry Kaufman's study and helps provide insight into how prices often behave after significant price changes. This analysis can help traders establish price movement expectations and potential strategies for trading such occurrences.
█ CALCULATIONS
Input Parameters:
This script offers users the choice to analyze "Opening Gaps" or "Extreme Closes" for price movements of different predefined magnitudes in a specified direction ("Upward" or "Downward").
Outputs:
Based on the specified inputs, the script performs the following calculations for the active ticker displayed on the chart:
Frequency of Extreme Price Movements : Quantifies the occurrences of directional price movements within predefined percentage ranges.
Average Pullbacks : Computes the average retracement (pullback) from analyzed price movements within each percentage range.
Average Closes : Analyzes the typical closing behavior relative to the directional price movements within each range.
The script organizes the results from these calculations within the table on a separate chart pane, providing users with helpful insights into how a stock historically behaved following significant price movements.
TASC 2024.06 REIT ETF Trading System█ OVERVIEW
This strategy script demonstrates the application of the Real Estate Investment Trust (REIT) ETF trading system presented in the article by Markos Katsanos titled "Is The Price REIT?" from TASC's June 2024 edition of Traders' Tips .
█ CONCEPTS
REIT stocks and ETFs offer a simplified, diversified approach to real estate investment. They exhibit sensitivity to interest rates, often moving inversely to interest rate and treasury yield changes. Markos Katsanos explores this relationship and the correlation of prices with the broader market to develop a trading strategy for REIT ETFs.
The script employs Bollinger Bands and Donchian channel indicators to identify oversold conditions and trends in REIT ETFs. It incorporates the 10-year treasury yield index (TNX) as a proxy for interest rates and the S&P 500 ETF (SPY) as a benchmark for the overall market. The system filters trade entries based on their behavior and correlation with the REIT ETF price.
█ CALCULATIONS
The strategy initiates long entries (buy signals) under two conditions:
1. Oversold condition
The weekly ETF low price dips below the 15-week Bollinger Band bottom, the closing price is above the value by at least 0.2 * ATR ( Average True Range ), and the price exceeds the week's median.
Either of the following:
– The TNX index is down over 15% from its 25-week high, and its correlation with the ETF price is less than 0.3.
– The yield is below 2%.
2. Uptrend
The weekly ETF price crosses above the previous week's 30-week Donchian channel high.
The SPY ETF is above its 20-week moving average.
Either of the following:
– Over ten weeks have passed since the TNX index was at its 30-week high.
– The correlation between the TNX value and the ETF price exceeds 0.3.
– The yield is below 2%.
The strategy also includes three exit (sell) rules:
1. Trailing (Chandelier) stop
The weekly close drops below the highest close over the last five weeks by over 1.5 * ATR.
The TNX value rises over the latest 25 weeks, with a yield exceeding 4%, or its value surges over 15% above the 25-week low.
2. Stop-loss
The ETF's price declines by at least 8% of the previous week's close and falls below the 30-week moving average.
The SPY price is down by at least 8%, or its correlation with the ETF's price is negative.
3. Overbought condition
The ETF's value rises above the 100-week low by over 50%.
The ETF's price falls over 1.5 * ATR below the 3-week high.
The ETF's 10-week Stochastic indicator exceeds 90 within the last three weeks.
█ DISCLAIMER
This strategy script educates users on the system outlined by the TASC article. However, note that its default properties might not fully represent real-world trading conditions for an individual. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script. Additionally, since this strategy utilizes compound conditions on weekly data to trigger orders, it will generate significantly fewer trades than other, higher-frequency strategies.
NZTInstitutionalLevelDESCRIPTION IN ENGLISH
🔶 INTRODUCTION
NZTInstitutionalLevel is an indicator for the TradingView platform designed to display institutional levels on a price chart. This script is based on the concept of calculating significant price levels that can be used for both long-term trading and intraday operations. The indicator calculates and visualizes the levels at which large market participants , such as institutional investors and large funds , can actively participate. The displayed levels are very important , as psychologically people tend to buy or sell at these levels, which makes them a reliable support in the analysis
🔶 CONTENT
The indicator uses the analysis of support and resistance levels , which are often tested by major market players . These levels represent prices that have historically experienced significant price movements due to large trading volumes, making them relevant for future trading decisions. You may notice that price often reverses or tests these round levels. These levels are a powerful pillar of price action analysis.
🔶 KEY FEATURES
The indicator displays institutional (bank) levels . Thanks to which you can easily determine the position of major players and the direction of their capital.
Visualization customization:
Users can customize the display of levels by selecting color, thickness and line style (solid, dotted, dashed).
Adaptability:
The script adapts the level step size depending on the current price of the asset and the selected time interval, which allows it to be used in various trading conditions and for assets with different volatility and price range.
Automatic scaling:
The number of displayed levels changes depending on the selected time interval, allowing traders to focus only on significant levels without overloading the chart with unnecessary information.
🔶 SETTINGS
🔹 Show Institutional Levels (Показывать институциональные уровни)
Allows you to disable or enable the display of institutional levels.
🔹 Level color (Цвет уровней)
Allows you to customize the color of the levels.
🔹 Level thickness (Толщина уровней)
Allows you to adjust the thickness of the levels.
🔹 Level style (Стиль уровней)
Allows you to customize the levels' style.
🔶 RECOMMENDATIONS FOR USE
To use the indicator, activate it on the desired price chart through the TradingView indicator menu. Once activated, adjust the visibility, color, style and thickness of the levels according to your preferences. The indicator will automatically calculate and display institutional levels based on the current asset price and configured parameters . These levels can serve as potential points for placing buy or sell orders, setting stop losses, or taking profits.
The indicator was developed by Temirlan Tolegenov for NZT Trader Community , May 2024, Prague, Czech Republic.
ОПИСАНИЕ НА РУССКОМ ЯЗЫКЕ
🔶 ВСТУПЛЕНИЕ
NZTInstitutionalLevel – это индикатор для платформы TradingView, предназначенный для отображения институциональных уровней на ценовом графике . Этот скрипт основан на концепции вычисления значимых ценовых уровней , которые могут быть использованы как для долгосрочной торговли, так и для интрадей-операций . Индикатор рассчитывает и визуализирует уровни , на которых могут активно участвовать крупные участники рынка , такие как институциональные инвесторы и большие фонды . Отображаемые уровни очень важны , так как психологически люди склонны покупать или продавать на этих уровнях , что делает их надежной опорой при анализе.
🔶 СОДЕРЖАНИЕ
Индикатор использует анализ уровней поддержки и сопротивления , которые часто тестируются крупными игроками рынка . Эти уровни представляют собой цены, на которых исторически происходили значительные движения цен за счет больших объемов торгов, что делает их релевантными для будущих торговых решений. Вы можете заметить, что цена часто разворачивается или тестирует эти круглые уровни. Эти уровни являются мощной основой анализа price action.
🔶 КЛЮЧЕВЫЕ ОСОБЕННОСТИ
Индикатор отображает институциональные (банковские/круглые) уровни. Благодаря чему вы легко сможете определить позиции крупных игроков и направление их капиталов.
Настройка визуализации:
Пользователи могут настроить отображение уровней, выбрав цвет, толщину и стиль линий (сплошные, пунктирные, точками).
Адаптивность:
Скрипт адаптирует размер шага уровня в зависимости от текущей цены актива и выбранного временного интервала, что позволяет использовать его в различных торговых условиях и для активов с разной волатильностью и ценовым диапазоном.
Автоматическое масштабирование:
Количество отображаемых уровней меняется в зависимости от выбранного временного интервала, позволяя трейдерам сосредоточиться только на значимых уровнях, не перегружая график лишней информацией.
🔶 НАСТРОЙКИ
🔹 Показывать институциональные уровни
Позволяет отключить или включить отображение институциональных уровней.
🔹 Цвет уровней
Позволяет настроить цвет уровней.
🔹 Толщина уровней
Позволяет регулировать толщину уровней.
🔹 Стиль уровней
Позволяет настроить стиль уровней.
🔶 РЕКОМЕНДАЦИИ К ИСПОЛЬЗОВАНИЮ
Для использования индикатора, активируйте его на желаемом ценовом графике через меню индикаторов TradingView. После активации, н астройте видимость, цвет, стиль и толщину уровней в соответствии с вашими предпочтениями. Индикатор автоматически рассчитает и отобразит институциональные уровни , основываясь на текущей цене актива и настроенных параметрах . Эти уровни могут служить потенциальными точками для размещения ордеров на покупку или продажу, установления стоп-лоссов или взятия прибыли.
Индикатор разработан Темирланом Толегеновым для международного сообщества NZT Trader , Май 2024, Прага, Чешская Республика.
The indicator is published in accordance and respect to all House Rules of the TradingView platform.
Индикатор опубликован в соответствии и уважением ко всем внутренним правилами платформы TradingView.
TASC 2024.04 The Ultimate Smoother█ OVERVIEW
This script presents an implementation of the digital smoothing filter introduced by John Ehlers in his article "The Ultimate Smoother" from the April 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
The UltimateSmoother preserves low-frequency swings in the input time series while attenuating high-frequency variations and noise. The defining input parameter of the UltimateSmoother is the critical period , which represents the minimum wavelength (highest frequency) in the filter's pass band. In other words, the filter attenuates or removes the amplitudes of oscillations at shorter periods than the critical period.
According to Ehlers, one primary advantage of the UltimateSmoother is that it maintains zero lag in its pass band and minimal lag in its transition band, distinguishing it from other conventional digital filters (e.g., moving averages ). One can apply this smoother to various input data series, including other indicators.
█ CALCULATIONS
Ehlers derived the UltimateSmoother using inspiration from the design principles he learned from his experience with analog filters , as described in the original publication. On a technical level, the UltimateSmoother's unique response involves subtracting a high-pass response from an all-pass response . At very low frequencies (lengthy periods), where the high-pass filter response has virtually no amplitude, the subtraction yields a frequency and phase response practically equivalent to the input data. At other frequencies, the subtraction achieves filtration through cancellation due to the close similarities in response between the high-pass filter and the input data.
TASC 2024.03 Rate of Directional Change█ OVERVIEW
This script implements the Rate of Directional Change (RODC) indicator introduced by Richard Poster in the "Taming The Effects Of Whipsaw" article featured in the March 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
In his article, Richard Poster discusses an approach to potentially reduce false trend-following strategy entry signals due to whipsaws in forex data. The RODC indicator is central to this approach. The idea behind RODC is that one can characterize market whipsaw as alternating up and down ZigZag segments. By counting the number of up and down segments within a lookback window, the RODC indicator aims to identify if the window contains a significant whipsaw pattern:
RODC = 100 * Segments / Window Size (bars)
Larger RODC values suggest elevated whipsaw in the calculation window, while smaller values signify trending price activity.
█ CALCULATIONS
• For each price bar, the script iterates through the lookback window to identify up and down segments.
• If the price change between subsequent bars within the window is in the direction opposite to the current segment and exceeds the specified threshold , the calculation interprets the condition as a reversal point and the start of a new segment.
• The script uses the number of segments within the window to calculate RODC according to the above formula.
• Finally, the script applies a simple moving average to smoothen the RODC data.
Users can change the length of the lookback window , the threshold value, and the smoothing length in the "Inputs" tab of the script's settings.
TASC 2024.02 Price-Time Filtering█ OVERVIEW
This script implements a price-time trend filter proposed by Alfred François Tagher in the “Trend Identification By Price And Time Filtering” article from the February 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
In his article, Alfred François Tagher proposed a rule set designed to minimize the impact of stochastic price movements, facilitating the identification of larger-scale trends. The rules are:
• If the most recent week's close exceeds the previous week's high, the trend is up.
• If the most recent week's close is below the previous week's low, the trend is down.
• The trend remains unchanged until one of the above conditions occurs.
Similar rules can also apply to monthly bars.
The author argues that this approach integrates characteristics of conventional price action and time dynamics filters, so he refers to it as price-time filtering .
█ CALCULATIONS
This script applies the above price-time filtering rules and offers multiple ways to view the results on a chart:
• In the "Oscillator" view mode, the script counts and displays the number of bars in the uptrend and downtrend.
• In the "Linebreak" view mode, the trend filter is presented in a format resembling a point-and-figure (P&F) chart , with the length of each bar corresponding to the high-low range of the respective trend.
• In both view modes, the script offers bar coloring of the main chart based on the identified trend.
TASC 2024.01 Gap Momentum System█ OVERVIEW
TASC's January 2024 edition of Traders' Tips features an article titled “Gap Momentum” by Perry J. Kaufman. The article discusses how a trader might create a momentum strategy based on opening gap data. This script implements the Gap Momentum system presented therein.
█ CONCEPTS
In the article, Perry J. Kaufman introduces Gap Momentum as a cumulative series constructed in the same way as On-Balance Volume (OBV) , but using gap openings (today’s open minus yesterday’s close).
To smoothen the resulting time series (i.e., obtain the " signal line "), the author applies a simple moving average . Subsequently, he proposes the following two trading rules for a long-only trading system:
• Enter a long position when the signal line is moving higher.
• Exit when the signal line is moving lower.
█ CALCULATIONS
The calculation of Gap Momentum involves the following steps:
1. Calculate the ratio of the sum of positive gaps over the past N days to the sum of negative gaps (absolute values) over the same time period.
2. Add the resulting gap ratio to the cumulative time series. This time series is the Gap Momentum.
3. Keep moving forward, as in an N-day moving average.
