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.
Komut dosyalarını "雅虎财经+上证指数2024年每天成交额" için ara
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%
---
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! 🌕
Monthly DividerThis Trading View indicator visually marks the beginning of each month starting from January 2024. It draws vertical lines on the chart at the start of each month and labels them with the corresponding month abbreviation (e.g., "Jan", "Feb"). Users can customize the color and thickness of the lines through the indicator settings, allowing for personalized chart aesthetics. This tool is ideal for traders and analysts who want to easily identify month transitions and enhance their technical analysis.
TASC 2025.02 Autocorrelation Indicator█ OVERVIEW
This script implements the Autocorrelation Indicator introduced by John Ehlers in the "Drunkard's Walk: Theory And Measurement By Autocorrelation" article from the February 2025 edition of TASC's Traders' Tips . The indicator calculates the autocorrelation of a price series across several lags to construct a periodogram , which traders can use to identify market cycles, trends, and potential reversal patterns.
█ CONCEPTS
Drunkard's walk
A drunkard's walk , formally known as a random walk , is a type of stochastic process that models the evolution of a system or variable through successive random steps.
In his article, John Ehlers relates this model to market data. He discusses two first- and second-order partial differential equations, modified for discrete (non-continuous) data, that can represent solutions to the discrete random walk problem: the diffusion equation and the wave equation. According to Ehlers, market data takes on a mixture of two "modes" described by these equations. He theorizes that when "diffusion mode" is dominant, trading success is almost a matter of luck, and when "wave mode" is dominant, indicators may have improved performance.
Pink spectrum
John Ehlers explains that many recent academic studies affirm that market data has a pink spectrum , meaning the power spectral density of the data is proportional to the wavelengths it contains, like pink noise . A random walk with a pink spectrum suggests that the states of the random variable are correlated and not independent. In other words, the random variable exhibits long-range dependence with respect to previous states.
Autocorrelation function (ACF)
Autocorrelation measures the correlation of a time series with a delayed copy, or lag , of itself. The autocorrelation function (ACF) is a method that evaluates autocorrelation across a range of lags , which can help to identify patterns, trends, and cycles in stochastic market data. Analysts often use ACF to detect and characterize long-range dependence in a time series.
The Autocorrelation Indicator evaluates the ACF of market prices over a fixed range of lags, expressing the results as a color-coded heatmap representing a dynamic periodogram. Ehlers suggests the information from the periodogram can help traders identify different market behaviors, including:
Cycles : Distinguishable as repeated patterns in the periodogram.
Reversals : Indicated by sharp vertical changes in the periodogram when the indicator uses a short data length .
Trends : Indicated by increasing correlation across lags, starting with the shortest, over time.
█ USAGE
This script calculates the Autocorrelation Indicator on an input "Source" series, smoothed by Ehlers' UltimateSmoother filter, and plots several color-coded lines to represent the periodogram's information. Each line corresponds to an analyzed lag, with the shortest lag's line at the bottom of the pane. Green hues in the line indicate a positive correlation for the lag, red hues indicate a negative correlation (anticorrelation), and orange or yellow hues mean the correlation is near zero.
Because Pine has a limit on the number of plots for a single indicator, this script divides the periodogram display into three distinct ranges that cover different lags. To see the full periodogram, add three instances of this script to the chart and set the "Lag range" input for each to a different value, as demonstrated in the chart above.
With a modest autocorrelation length, such as 20 on a "1D" chart, traders can identify seasonal patterns in the price series, which can help to pinpoint cycles and moderate trends. For instance, on the daily ES1! chart above, the indicator shows repetitive, similar patterns through fall 2023 and winter 2023-2024. The green "triangular" shape rising from the zero lag baseline over different time ranges corresponds to seasonal trends in the data.
To identify turning points in the price series, Ehlers recommends using a short autocorrelation length, such as 2. With this length, users can observe sharp, sudden shifts along the vertical axis, which suggest potential turning points from upward to downward or vice versa.
Session Bar/Candle ColoringChange the color of candles within a user-defined trading session. Borders and wicks can be changed as well, not just the body color.
PREFACE
This script can be used an educational resource for those who are interested in learning Pine Script. Therefore, the script is published open source and is organized in a manner that follows the recommended Style Guide .
While the main premise of the indicator is rather simple, the script showcases various things that can be achieved such as conditional plotting, alignment of indicator settings, user input validation, script optimization, and more. The script also has examples of taking into consideration the chart timeframe and/or different chart types (Heikin Ashi, Renko, etc.) that a user might be running it on. Note: for complete beginners, I strongly suggest going through the Pine Script User Manual (possibly more than once).
FEATURES
Besides being able to select a specific time window, the indicator also provides additional color settings for changing the background color or changing the colors of neutral/indecisive candles, as shown in the image below.
This allows for a higher level of customization beyond the TradingView chart settings or other similar scripts that are currently available.
HOW TO USE
First, define the intraday trading session that will contain the candles to modify. The session can be limited to specific days of the week.
Next, select the parts of the candles that should be modified: Body, Borders, Wick, and/or Background.
For each of the candle parts that were enabled, you can select the colors that will be used depending on whether a candle is bullish (⇧), bearish (⇩), or neutral (⇆).
All other indicator settings will have a detailed tooltip to describe its usage and/or effect.
LIMITATIONS
The indicator is not intended to function on Daily or higher timeframes due to the intraday nature of session time windows.
The indicator cannot always automatically detect the chart type being used, therefore the user is requested to manually input the chart type via the " Chart Style " setting.
Depending on the available historical data and the selected choice for the " Portion of bar in session " setting, the indicator may not be able to update very old candles on the chart.
EXAMPLE USAGE
This section will show examples of different scenarios that the indicator can be used for.
Emphasizing a main trading session.
Defining a "Pre/post market hours background" like is available for some symbols (e.g., NASDAQ:AAPL ).
Highlighting in which bar the midnight candle occurs.
Hiding indecision bars (neutral candles).
Showing only "Regular Trading Hours" for a chart that does not have the option to toggle ETH/RTH. To achieve this, the actual chart data is hidden, and only the indicator is visible; alternatively, a 2nd instance of the indicator could change colors to match the chart background.
Using a combination of Bars and Japanese Candlesticks. Alternatively, this could be done by hiding the main chart data and using 2 instances of the indicator (one with " Chart Style " setting as Bars , and the other set to Candles ).
Using a combination of thin and thick bars on Range charts. Note: requires disabling the "Thin Bars" setting for Bar charts in the TradingView chart settings.
NOTES
If using more than one instance of this indicator on the same chart, you can use the TradingView "Save Indicator Template" feature to avoid having to re-configure the multiple indicators at a later time.
This indicator is intended to work "out-of-the-box" thanks to the behind_chart option introduced to Pine Script in October 2024. But you can always manually bring the indicator to the front just in case the color changes are not being seen (using the "More" option in the indicator status line: More > Visual Order > Bring to front ).
Many thanks to fikira for their help and inspiring me to create open source scripts.
Any feedback including bug reports or suggestions for improving the indicator (or source code itself) are always welcome in the comments section.
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.
Portfolio SnapShot v0.3Here is a Tradingview Pinescript that I call "Portfolio Snapshot". It is based on two other separate scripts that I combined, modified and simplified - shoutout to RedKTrader (Portfolio Tracker - Table Version) and FriendOfTheTrend (Portfolio Tracker For Stocks & Crypto) for their inspiration and code. I was using both of these scripts, and decided to combine the two and increase the number of stocks to 20. I was looking for an easy way to track my entire portfolio (scattered across 5 accounts) PnL on a total and stock basis. PnL - that's it, very simple by design. The features are:
1) Track PnL across multiple accounts, from inception and current day.
2) PnL is reported in two tables, at the portfolio level and individual stock level
3) Both tables can be turned on/off and placed anywhere on the chart.
4) Input up to 20 assets (stocks, crypto, ETFs)
The user has to manually calculate total shares and average basis for stocks in multiple accounts, and then inputs this in the user input dialog. I update mine as each trade is made, or you can just update once a week or so.
I've pre-loaded it with the major indices and sector ETFs, plus URA, GLD, SLV. 100 shares of each, and prices are based on the close Jan 2 2024. So if you don't want to track your portfolio, you can use it to track other things you find interesting, such as annual performance of each sector.
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.
[ALGOA+] Markov Chains Library by @metacamaleoLibrary "MarkovChains"
Markov Chains library by @metacamaleo. Created in 09/08/2024.
This library provides tools to calculate and visualize Markov Chain-based transition matrices and probabilities. This library supports two primary algorithms: a rolling window Markov Chain and a conditional Markov Chain (which operates based on specified conditions). The key concepts used include Markov Chain states, transition matrices, and future state probabilities based on past market conditions or indicators.
Key functions:
- `mc_rw()`: Builds a transition matrix using a rolling window Markov Chain, calculating probabilities based on a fixed length of historical data.
- `mc_cond()`: Builds a conditional Markov Chain transition matrix, calculating probabilities based on the current market condition or indicator state.
Basically, you will just need to use the above functions on your script to default outputs and displays.
Exported UDTs include:
- s_map: An UDT variable used to store a map with dummy states, i.e., if possible states are bullish, bearish, and neutral, and current is bullish, it will be stored
in a map with following keys and values: "bullish", 1; "bearish", 0; and "neutral", 0. You will only use it to customize your own script, otherwise, it´s only for internal use.
- mc_states: This UDT variable stores user inputs, calculations and MC outputs. As the above, you don´t need to use it, but you may get features to customize your own script.
For example, you may use mc.tm to get the transition matrix, or the prob map to customize the display. As you see, functions are all based on mc_states UDT. The s_map UDT is used within mc_states´s s array.
Optional exported functions include:
- `mc_table()`: Displays the transition matrix in a table format on the chart for easy visualization of the probabilities.
- `display_list()`: Displays a map (or array) of string and float/int values in a table format, used for showing transition counts or probabilities.
- `mc_prob()`: Calculates and displays probabilities for a given number of future bars based on the current state in the Markov Chain.
- `mc_all_states_prob()`: Calculates probabilities for all states for future bars, considering all possible transitions.
The above functions may be used to customize your outputs. Use the returned variable mc_states from mc_rw() and mc_cond() to display each of its matrix, maps or arrays using mc_table() (for matrices) and display_list() (for maps and arrays) if you desire to debug or track the calculation process.
See the examples in the end of this script.
Have good trading days!
Best regards,
@metacamaleo
-----------------------------
KEY FUNCTIONS
mc_rw(state, length, states, pred_length, show_table, show_prob, table_position, prob_position, font_size)
Builds the transition matrix for a rolling window Markov Chain.
Parameters:
state (string) : The current state of the market or system.
length (int) : The rolling window size.
states (array) : Array of strings representing the possible states in the Markov Chain.
pred_length (int) : The number of bars to predict into the future.
show_table (bool) : Boolean to show or hide the transition matrix table.
show_prob (bool) : Boolean to show or hide the probability table.
table_position (string) : Position of the transition matrix table on the chart.
prob_position (string) : Position of the probability list on the chart.
font_size (string) : Size of the table font.
Returns: The transition matrix and probabilities for future states.
mc_cond(state, condition, states, pred_length, show_table, show_prob, table_position, prob_position, font_size)
Builds the transition matrix for conditional Markov Chains.
Parameters:
state (string) : The current state of the market or system.
condition (string) : A string representing the condition.
states (array) : Array of strings representing the possible states in the Markov Chain.
pred_length (int) : The number of bars to predict into the future.
show_table (bool) : Boolean to show or hide the transition matrix table.
show_prob (bool) : Boolean to show or hide the probability table.
table_position (string) : Position of the transition matrix table on the chart.
prob_position (string) : Position of the probability list on the chart.
font_size (string) : Size of the table font.
Returns: The transition matrix and probabilities for future states based on the HMM.
Black-Scholes option price model & delta hedge strategyBlack-Scholes Option Pricing Model Strategy
The strategy is based on the Black-Scholes option pricing model and allows the calculation of option prices, various option metrics (the Greeks), and the creation of synthetic positions through delta hedging.
ATTENTION!
Trading derivative financial instruments involves high risks. The author of the strategy is not responsible for your financial results! The strategy is not self-sufficient for generating profit! It is created exclusively for constructing a synthetic derivative financial instrument. Also, there might be errors in the script, so use it at your own risk! I would appreciate it if you point out any mistakes in the comments! I would be even more grateful if you send the corrected code!
Application Scope
This strategy can be used for delta hedging short positions in sold options. For example, suppose you sold a call option on Bitcoin on the Deribit exchange with a strike price of $60,000 and an expiration date of September 27, 2024. Using this script, you can create a delta hedge to protect against the risk of loss in the option position if the price of Bitcoin rises.
Another example: Suppose you use staking of altcoins in your strategies, for which options are not available. By using this strategy, you can hedge the risk of a price drop (Put option). In this case, you won't lose money if the underlying asset price increases, unlike with a short futures position.
Another example: You received an airdrop, but your tokens will not be fully unlocked soon. Using this script, you can fully hedge your position and preserve their dollar value by the time the tokens are fully unlocked. And you won't fear the underlying asset price increasing, as the loss in the event of a price rise is limited to the option premium you will pay if you rebalance the portfolio.
Of course, this script can also be used for simple directional trading of momentum and mean reversion strategies!
Key Features and Input Parameters
1. Option settings:
- Style of option: "European vanilla", "Binary", "Asian geometric".
- Type of option: "Call" (bet on the rise) or "Put" (bet on the fall).
- Strike price: the option contract price.
- Expiration: the expiry date and time of the option contract.
2. Market statistic settings:
- Type of price source: open, high, low, close, hl2, hlc3, ohlc4, hlcc4 (using hl2, hlc3, ohlc4, hlcc4 allows smoothing the price in more volatile series).
- Risk-free return symbol: the risk-free rate for the market where the underlying asset is traded. For the cryptocurrency market, the return on the funding rate arbitrage strategy is accepted (a special function is written for its calculation based on the Premium Price).
- Volatility calculation model: realized (standard deviation over a moving period), implied (e.g., DVOL or VIX), or custom (you can specify a specific number in the field below). For the cryptocurrency market, the calculation of implied volatility is implemented based on the product of the realized volatility ratio of the considered asset and Bitcoin to the Bitcoin implied volatility index.
- User implied volatility: fixed implied volatility (used if "Custom" is selected in the "Volatility Calculation Method").
3. Display settings:
- Choose metric: what to display on the indicator scale – the price of the underlying asset, the option price, volatility, or Greeks (all are available).
- Measure: bps (basis points), percent. This parameter allows choosing the unit of measurement for the displayed metric (for all except the Greeks).
4. Trading settings:
- Hedge model: None (do not trade, default), Simple (just open a position for the full volume when the strike price is crossed), Synthetic option (creating a synthetic option based on the Black-Scholes model).
- Position side: Long, Short.
- Position size: the number of units of the underlying asset needed to create the option.
- Strategy start time: the moment in time after which the strategy will start working to create a synthetic option.
- Delta hedge interval: the interval in minutes for rebalancing the portfolio. For example, a value of 5 corresponds to rebalancing the portfolio every 5 minutes.
Post scriptum
My strategy based on the SegaRKO model. Many thanks to the author! Unfortunately, I don't have enough reputation points to include a link to the author in the description. You can find the original model via the link in the code, as well as through the search indicators on the charts by entering the name: "Black-Scholes Option Pricing Model". I have significantly improved the model: the calculation of volatility, risk-free rate and time value of the option have been reworked. The code performance has also been significantly optimized. And the most significant change is the execution, with which you can now trade 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.
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.
Concretum BandsDefinition
The Concretum Bands indicator recreates the Upper and Lower Bound of the Noise Area described in the paper "Beat the Market: An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" published by Concretum founder Zarattini, along with Barbon and Aziz, in May 2024.
Below we provide all the information required to understand how the indicator is calculated, the rationale behind it and how people can use it.
Idea Behind
The indicator aims to outline an intraday price region where the stock is expected to move without indicating any demand/supply imbalance. When the price crosses the boundaries of the Noise Area, it suggests a significant imbalance that may trigger an intraday trend.
How the Indicator is Calculated
The bands at time HH:MM are computed by taking the open price of day t and then adding/subtracting the average absolute move over the last n days from market open to minute HH:MM . The bands are also adjusted to account for overnight gaps. A volatility multiplier can be used to increase/decrease the width of the bands, similar to other well-known technical bands. The bands described in the paper were computed using a lookback period (length) of 14 days and a Volatility Multiplier of 1. Users can easily adjust these settings.
How to use the indicator
A trader may use this indicator to identify intraday moves that exceed the average move over the most recent period. A break outside the bands could be used as a signal of significant demand/supply imbalance.
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.
NCI - Timeframe + WatermarkDeveloped by Jayce in June 2022 and later updated by Light in January 2024.
Key Features:
Customizable Watermark: Enhance your chart with a personalized watermark. Enter any text, like your trading mantra or brand name, to keep your focus aligned with your trading strategy.
Adjustable Font Size: Tailor the appearance of your watermark and notes with adjustable font sizes, ranging from "Tiny" to "Huge," ensuring optimal visibility and integration with your chart setup.
Timeframe Display: Stay informed of the current chart's timeframe, neatly displayed alongside your chosen watermark. Whether you're analyzing trends in minutes, hours, or days, this feature keeps you oriented without cluttering your workspace.
Inspirational Note: Complement your watermark with an inspirational note or a quick reminder of your trading discipline and risk management strategies, keeping your principles front and center.
