Position Sizer (FinPip)Position Sizer (FinPip)
The Position Sizer (FinPip) indicator is a crucial, all-in-one risk management tool designed to calculate the precise trade size required to limit your risk to a predetermined percentage of your total account capital.
This indicator helps you consistently execute sound risk management, regardless of the instrument's volatility or the trade's price levels.
Key Features:
Calculates Position Size: Based on your configurable Account Capital, desired Risk Percentage (default 2.5%), and the price distance between your Entry and Stop-Loss levels.
Visual Trade Planning: Plots three clear levels directly on the chart for easy visualization:
Entry Price (Blue)
Stop-Loss Price (SL) (Red)
Profit Target (Lime Green, calculated using the Reward:Risk Ratio).
Custom Risk Management: Easily adjust the Risk Percentage and the Reward:Risk Ratio (default 4.0) in the indicator's settings.
Heads-Up Display (HUD): A clean, fixed table in the bottom-left corner of the chart clearly displays all calculated metrics, including your Required Position Size (in units/shares/contracts), Risk Amount, and Potential Profit.
How to Use:
Enter your Account Capital and desired Risk % in the settings panel.
Set your desired Entry Price and Stop-Loss Price.
The indicator immediately calculates and displays the exact number of units you need to trade to maintain your risk limit.
Quản lý danh mục đầu tư
The Position Sizer (FinPip)The Position Sizer (FinPip) indicator is a crucial, all-in-one risk management tool designed to calculate the precise trade size required to limit your risk to a predetermined percentage of your total account capital.
This indicator helps you consistently execute sound risk management, regardless of the instrument's volatility or the trade's price levels.
Key Features:
Calculates Position Size: Based on your configurable Account Capital, desired Risk Percentage (default 2.5%), and the price distance between your Entry and Stop-Loss levels.
Visual Trade Planning: Plots three clear levels directly on the chart for easy visualization:
Entry Price (Blue)
Stop-Loss Price (SL) (Red)
Profit Target (Lime Green, calculated using the Reward:Risk Ratio).
Custom Risk Management: Easily adjust the Risk Percentage and the Reward:Risk Ratio (default 4.0) in the indicator's settings.
Heads-Up Display (HUD): A clean, fixed table in the bottom-left corner of the chart clearly displays all calculated metrics, including your Required Position Size (in units/shares/contracts), Risk Amount, and Potential Profit.
How to Use:
Enter your Account Capital and desired Risk % in the settings panel.
Set your desired Entry Price and Stop-Loss Price.
The indicator immediately calculates and displays the exact number of units you need to trade to maintain your risk limit.
Position Sizer (FinPip)The Position Sizer (FinPip) indicator is a crucial, all-in-one risk management tool designed to calculate the precise trade size required to limit your risk to a predetermined percentage of your total account capital.
This indicator helps you consistently execute sound risk management, regardless of the instrument's volatility or the trade's price levels.
Key Features:
Calculates Position Size: Based on your configurable Account Capital, desired Risk Percentage (default 2.5%), and the price distance between your Entry and Stop-Loss levels.
Visual Trade Planning: Plots three clear levels directly on the chart for easy visualization:
Entry Price (Blue)
Stop-Loss Price (SL) (Red)
Profit Target (Lime Green, calculated using the Reward:Risk Ratio).
Custom Risk Management: Easily adjust the Risk Percentage and the Reward:Risk Ratio (default 4.0) in the indicator's settings.
Heads-Up Display (HUD): A clean, fixed table in the bottom-left corner of the chart clearly displays all calculated metrics, including your Required Position Size (in units/shares/contracts), Risk Amount, and Potential Profit.
How to Use:
Enter your Account Capital and desired Risk % in the settings panel.
Set your desired Entry Price and Stop-Loss Price.
The indicator immediately calculates and displays the exact number of units you need to trade to maintain your risk limit.
Hash Supertrend [Hash Capital Research]Hash Supertrend Strategy by Hash Capital Research
Overview
Hash Supertrend is a professional-grade trend-following strategy that combines the proven Supertrend indicator with institutional visual design and flexible time filtering.
The strategy uses ATR-based volatility bands to identify trend direction and executes position reversals when the trend flips.This implementation features a distinctive fluorescent color system with customizable glow effects, making trend changes immediately visible while maintaining the clean, professional aesthetic expected in quantitative trading environments.
Entry Signals:
Long Entry: Price crosses above the Supertrend line (trend flips bullish)
Short Entry: Price crosses below the Supertrend line (trend flips bearish)
Controls the lookback period for volatility calculation
Lower values (7-10): More sensitive to price changes, generates more signals
Higher values (12-14): Smoother response, fewer signals but potentially delayed entries
Recommended range: 7-14 depending on market volatility
Factor (Default: 3.0)
Restricts trading to specific hours
Useful for avoiding low-liquidity sessions, overnight gaps, or known choppy periods
When disabled, strategy trades 24/7
Start Hour (Default: 9) & Start Minute (Default: 30)
Define when the trading session begins
Uses exchange timezone in 24-hour format
Example: 9:30 = 9:30 AM
End Hour (Default: 16) & End Minute (Default: 0)
Controls the vibrancy of the fluorescent color system
1-3: Subtle, muted colors
4-6: Balanced, moderate saturation
7-10: Bright, highly saturated fluorescent appearance
Affects both the Supertrend line and trend zones
Glow Effect (Default: On)
Adds luminous halo around the Supertrend line
Creates a multi-layered visual with depth
Particularly effective during strong trends
Glow Intensity (Default: 5.0)
Displays tiny fluorescent dots at entry points
Green dot below bar: Long entry
Red dot above bar: Short entry
Provides clear visual confirmation of executed trades
Show Trend Zone (Default: On)
Strong trending markets (2020-style bull runs, sustained bear markets)
Markets with clear directional bias
Instruments with consistent volatility patterns
Timeframes: 15m to Daily (optimal on 1H-4H)
Challenging Conditions:
Choppy, range-bound markets
Low volatility consolidation periods
Highly news-driven instruments with frequent gaps
Very low timeframes (1m-5m) prone to noise
Recommended AssetsCryptocurrency:
GVI-1 - Guendogan Valuation Index 1The Guendogan Valuation Index 1 (GVI-1) incorporates the total market capitalization of all U.S. companies, U.S. GDP, and the share of revenues generated outside the United States to provide an undistorted long-term valuation of the U.S. equity market across the past decades.
Disclaimer: The Guendogan Valuation Index 1 (GVI-1) is a research-based macro indicator provided solely for educational and informational purposes. It does not constitute financial advice, investment advice, trading advice, or a recommendation to buy or sell any asset. Financial markets involve risk, and past performance does not guarantee future results. All users are solely responsible for their own investment decisions.
GVI – Guendogan Valuation IndexGlobalization-adjusted valuation indicator modeling rising international revenue exposure since 1990. Includes a long-term fair-value framework.
Stock Management (Zeiierman)█ Overview
Stock Management (Zeiierman) gives investors a complete, real-time view of their portfolio directly inside TradingView. It tracks performance, allocation, volatility, and dividends in one unified interface, making it easy to understand both how your portfolio is performing and how it behaves in terms of risk and exposure.
Rather than analyzing each chart in isolation, Stock Management (Zeiierman) turns TradingView into a lightweight portfolio cockpit. You can define up to 20 stock positions (ticker, shares, average cost), and the tool will:
Normalize all positions into a single user-selected currency
Calculate live position value, PnL, PnL%, and daily movement
Compute total portfolio value, performance, and volatility
Optionally generate a risk-parity style Recommended Allocation
Display upcoming dividend amounts, ex-dates, and pay-dates for your holdings
All of this appears as clean on-chart tables, including a main portfolio table, an optional dividend table, and an optional summary panel, allowing you to manage your portfolio while still watching price action. It is a visual portfolio layer built entirely around your own inputs, integrated seamlessly into the TradingView environment.
⚪ Why This One Is Unique
Most investors rely on basic broker dashboards that show position values but provide little insight into risk, exposure, or how each holding interacts with the rest of the portfolio. Stock Management (Zeiierman) goes far beyond that by building an intelligent, unified portfolio layer directly inside TradingView.
It automatically normalizes global holdings into a single reporting currency using live FX data, stabilizes allocation with a volatility-aware weighting engine, and structures your information through an adaptive column framework that highlights performance and risk in real time. A weighted summary blends portfolio movement, volatility, and long-horizon behavior into a clean snapshot, while dividend schedules and projected payouts are fully integrated into the same interface.
█ Main Features
⚪ 1. Portfolio Tracker
The core of Stock Management (Zeiierman) is a dynamic, real-time portfolio table that brings all key position data into one intelligent view. Each holding is displayed with:
Ticker
Sector
Price
Average Paid Price
Shares
Position Value
Position Weight
Profit & Loss
Profit & Loss %
Today % Change
Recommended Allocation
The table updates continuously with market prices, giving investors an immediate understanding of performance, exposure, and risk across all positions.
⚪ 2. Dividend Information
Dividend data for your holdings is automatically fetched, organized, and presented alongside your positions. This includes dividend amount, ex-date, and pay-date, along with projected payouts based on your share count. All dividend-related information is integrated directly into the portfolio view, so you can plan cash flow without switching tools.
⚪ 3. Portfolio Summary
A dedicated summary panel consolidates the entire portfolio into a single snapshot: total value, total PnL, YTD %, today’s change, and overall volatility. The volatility reading is particularly valuable, providing a quick gauge of your portfolio’s risk level and how sensitive it may be to market movement.
⚪ 4. Portfolio Weight Recommendation
An intelligent weighting engine reviews your current allocations and highlights where your portfolio is overexposed or underweighted. It offers recommended allocation levels designed to reduce concentration risk and improve balance, giving you a clearer path toward a more stable long-term positioning.
█ How to Use
⚪ Performance Tracking
Quickly assess your entire portfolio’s profit, loss, daily movement, and volatility from one centralized dashboard. The summary panel gives you an instant read on how your holdings are performing and how sensitive they are to market swings.
⚪ Dividend Management
Monitor upcoming dividend amounts, ex-dates, and pay-dates directly inside your portfolio table. This ensures you never miss a payout opportunity and can plan your expected cash flow with complete clarity.
⚪ Risk Management & Optimization
Use portfolio-wide volatility and the intelligent Recommended Allocation engine to identify imbalances in your holdings. These insights help you adjust position sizes, reduce concentration risk, and maintain a more stable long-term portfolio profile.
⚪ Currency Comparison
Switch between different base currencies to evaluate performance in local or international terms. All positions are automatically normalized using live FX data, making global portfolio management effortless.
█ How It Works
Stock Management (Zeiierman) continuously gathers price, currency, dividend, and volatility data for every ticker you track. All values are automatically converted into your selected reporting currency, so global holdings remain comparable in one unified view.
It builds a live portfolio snapshot of each bar, updating position values, PnL, daily returns, YTD performance, and overall volatility. This gives you an always-current understanding of how your portfolio is performing and how each holding contributes to risk and exposure.
An intelligent, volatility-aware allocation model generates recommended portfolio weights and position sizes, helping you identify where you may be overexposed or underweighted. Dividend information is integrated directly into the table, projecting future payouts and highlighting upcoming ex-dates and pay-dates.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Kill Zone GridCaca Poo-Poo Kill Zone (12pm–4pm) — Avoid the Death Hours
This indicator highlights the worst trading window of the day — the midday chop zone where liquidity dies, algo volume disappears, spreads widen, and your account slowly bleeds out from boredom and paper cuts.
From 12pm to 4pm (New York Time) the script:
• Shades the background with a bold kill-zone color
• Adds red gridline stripes to visually scream “STOP TRADING, YOU DONKEY”
• Makes the entire chart look hostile so you avoid revenge trading, boredom trading, and all forms of midday stupidity
Perfect for scalpers and trend traders who only want the clean morning moves and want a visual reminder to step away, go outside, touch grass, eat lunch, or hit the gym instead of forcing trades in garbage hours.
If you trade futures, options, or zero-day anything — this script will save you money, sanity, and years off your life.
Mini Checklist (Left-side, static)It's a mini checklist on the left side of the chart serving as a note for when you trade.
Pretty simple
ATH대비 지정하락률에 도착 시 매수 - 장기홀딩 선물 전략(ATH Drawdown Re-Buy Long Only)본 스크립트는 과거 하락 데이터를 이용하여, 정해진 하락 %가 발생하는 경우 자기 자본의 정해진 %만큼을 진입하게 설계되어진 스트레티지입니다.
레버리지를 사용할 수 있으며 기본적으로 셋팅해둔 값이 내장되어있습니다.(자유롭게 바꿔서 쓰시면 됩니다.) 추가적으로 2번의 진입 외에도 다른 진입 기준, 진입 %를 설정하실 수 있으며 - ChatGPT에게 요청하면 수정해줄 것입니다.
실제 사용용도로는 KillSwitch 기능을 꺼주세요. 바 돋보기 기능을 켜주세요.
ATH Drawdown Re-Buy Long Only 전략 설명
1. 전략 개요
ATH Drawdown Re-Buy Long Only 전략은 자산의 역대 최고가(ATH, All-Time High)를 기준으로 한 하락폭(드로우다운)을 활용하여,
특정 구간마다 단계적으로 롱 포지션을 구축하는 자동 재매수(Long Only) 전략입니다.
본 전략은 다음과 같은 목적을 가지고 설계되었습니다.
급격한 조정 구간에서 체계적인 분할 매수 및 레버리지 활용
ATH를 기준으로 한 명확한 진입 규칙 제공
실시간으로
평단가
레버리지
청산가 추정
계좌 MDD
수익률
등을 시각적으로 제공하여 리스크와 포지션 상태를 직관적으로 확인할 수 있도록 지원
※ 본 전략은 교육·연구·백테스트 용도로 제공되며,
어떠한 형태의 투자 권유 또는 수익을 보장하지 않습니다.
2. 전략의 핵심 개념
2-1. ATH(역대 최고가) 기준 드로우다운
전략은 차트 상에서 항상 가장 높은 고가(High)를 ATH로 기록합니다.
새로운 고점이 형성될 때마다 ATH를 갱신하고, 해당 ATH를 기준으로 다음을 계산합니다.
현재 바의 저가(Low)가 ATH에서 몇 % 하락했는지
현재 바의 종가(Close)가 ATH에서 몇 % 하락했는지
그리고 사전에 설정한 두 개의 드로우다운 구간에서 매수를 수행합니다.
1차 진입 구간: ATH 대비 X% 하락 시
2차 진입 구간: ATH 대비 Y% 하락 시
각 구간은 ATH가 새로 갱신될 때마다 한 번씩만 작동하며,
새로운 ATH가 생성되면 다시 “1차 / 2차 진입 가능 상태”로 초기화됩니다.
2-2. 첫 포지션 100% / 300% 특수 규칙
이 전략의 중요한 특징은 **“첫 포지션 진입 시의 예외 규칙”**입니다.
전략이 현재 어떠한 포지션도 들고 있지 않은 상태에서
최초로 롱 포지션을 진입하는 시점(첫 포지션)에 대해:
기본적으로는 **자산의 100%**를 기준으로 포지션을 구축하지만,
만약 그 순간의 가격이 ATH 대비 설정값 이상(예: 약 –72.5% 이상 하락한 상황) 이라면
→ 자산의 300% 규모로 첫 포지션을 진입하도록 설계되어 있습니다.
이 규칙은 다음과 같이 동작합니다.
첫 진입이 1차 드로우다운 구간에서 발생하든,
첫 진입이 2차 드로우다운 구간에서 발생하든,
현재 하락폭이 설정된 기준 이상(예: –72.5% 이상) 이라면
→ “이 정도 하락이면 첫 진입부터 더 공격적으로 들어간다”는 의미로 300% 규모로 진입
그 이하의 하락폭이라면
→ 첫 진입은 100% 규모로 제한
즉, 전략은 다음 두 가지 모드로 동작합니다.
일반적인 상황의 첫 진입: 자산의 100%
심각한 드로우다운 구간에서의 첫 진입: 자산의 300%
이 특수 규칙은 깊은 하락에서는 공격적으로, 평소에는 상대적으로 보수적으로 진입하도록 설계된 것입니다.
3. 전략 동작 구조
3-1. 매수 조건
차트 상 High 기준으로 ATH를 추적합니다.
각 바마다 해당 ATH에서의 하락률을 계산합니다.
사용자가 설정한 두 개의 드로우다운 구간(예시):
1차 구간: 예를 들어 ATH – 50%
2차 구간: 예를 들어 ATH – 72.5%
각 구간에 대해 다음과 같은 조건을 확인합니다.
“이번 ATH 구간에서 아직 해당 구간 매수를 한 적이 없는 상태”이고,
현재 바의 저가(Low)가 해당 구간 가격 이하를 찍는 순간
→ 해당 바에서 매수 조건 충족으로 간주
실제 주문은:
해당 구간 가격에 맞춰 롱 포지션 진입(리밋/시장가 기반 시뮬레이션) 으로 처리됩니다.
3-2. ATH 갱신과 진입 기회 리셋
차트 상에서 새로운 고점(High)이 기존 ATH를 넘어서는 순간,
ATH가 갱신되고,
1차 / 2차 진입 여부를 나타내는 내부 플래그가 초기화됩니다.
이를 통해, 시장이 새로운 고점을 돌파해 나갈 때마다,
해당 구간에서 다시 한 번씩 1차·2차 드로우다운 진입 기회를 갖게 됩니다.
4. 포지션 사이징 및 레버리지
4-1. 계좌 자산(Equity) 기준 포지션 크기 결정
전략은 현재 계좌 자산을 다음과 같이 정의하여 사용합니다.
현재 자산 = 초기 자본 + 실현 손익 + 미실현 손익
각 진입 구간에서의 포지션 가치는 다음과 같이 결정됩니다.
1차 진입 구간:
“자산의 몇 %를 사용할지”를 설정값으로 입력
설정된 퍼센트를 계좌 자산에 곱한 뒤,
다시 전략 내 레버리지 배수(Leverage) 를 곱하여 실제 포지션 가치를 계산
2차 진입 구간:
동일한 방식으로, 독립된 퍼센트 설정값을 사용
즉, 포지션 가치는 다음과 같이 계산됩니다.
포지션 가치 = 현재 자산 × (해당 구간 설정 % / 100) × 레버리지 배수
그리고 이를 해당 구간의 진입 가격으로 나누어 실제 수량(토큰 단위) 를 산출합니다.
4-2. 첫 포지션의 예외 처리 (100% / 300%)
첫 포지션에 대해서는 위의 일반적인 퍼센트 설정 대신,
다음과 같은 고정 비율이 사용됩니다.
기본: 자산의 100% 규모로 첫 포지션 진입
단, 진입 시점의 ATH 대비 하락률이 설정값 이상(예: –72.5% 이상) 일 경우
→ 자산의 300% 규모로 첫 포지션 진입
이때 역시 다음 공식을 사용합니다.
포지션 가치 = 현재 자산 × (100% 또는 300%) × 레버리지
그리고 이를 가격으로 나누어 실제 진입 수량을 계산합니다.
이 규칙은:
첫 진입이 1차 구간이든 2차 구간이든 동일하게 적용되며,
“충분히 깊은 하락 구간에서는 첫 진입부터 더 크게,
평소에는 비교적 보수적으로” 라는 운용 철학을 반영합니다.
4-3. 실레버리지(Real Leverage)의 추적
전략은 각 바 단위로 다음을 추적합니다.
바가 시작할 때의 기존 포지션 크기
해당 바에서 새로 진입한 수량
이를 바탕으로, 진입이 발생한 시점에 다음을 계산합니다.
실제 레버리지 = (포지션 가치 / 현재 자산)
그리고 차트 상에 예를 들어:
Lev 2.53x 와 같은 형식의 레이블로 표시합니다.
이를 통해, 매수 시점마다 실제 계좌 레버리지가 어느 정도였는지를 직관적으로 확인할 수 있습니다.
5. 시각화 및 모니터링 요소
5-1. 차트 상 시각 요소
전략은 차트 위에 다음과 같은 정보를 직접 표시합니다.
ATH 라인
High 기준으로 계산된 역대 최고가를 주황색 선으로 표시
평단가(평균 진입가) 라인
현재 보유 포지션이 있을 때,
해당 포지션의 평균 진입가를 노란색 선으로 표시
추정 청산가(고정형 청산가) 라인
포지션 수량이 변화하는 시점을 감지하여,
당시의 평단가와 실제 레버리지를 이용해 근사적인 청산가를 계산
이를 빨간색 선으로 차트에 고정 표시
포지션이 없거나 레버리지가 1배 이하인 경우에는 청산가 라인을 제거
매수 마커 및 레이블
1차/2차 매수 조건이 충족될 때마다 해당 지점에 매수 마커를 표시
"Buy XX% @ 가격", "Lev XXx" 형태의 라벨로
진입 비율과 당시 레버리지를 함께 시각화
레이블의 위치는 설정에서 선택 가능:
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
5-2. 우측 상단 정보 테이블
차트 우측 상단에는 현재 계좌·포지션 상태를 요약한 정보 테이블이 표시됩니다.
대표적으로 다음 항목들이 포함됩니다.
Pos Qty (Token)
현재 보유 중인 포지션 수량(토큰 기준, 절대값 기준)
Pos Value (USDT)
현재 포지션의 시장 가치 (수량 × 현재 가격)
Leverage (Now)
현재 실레버리지 (포지션 가치 / 현재 자산)
DD from ATH (%)
현재 가격 기준, 최근 ATH에서의 하락률(%)
Avg Entry
현재 포지션의 평균 진입 가격
PnL (%)
현재 포지션 기준 미실현 손익률(%)
Max DD (Equity %)
전략 전체 기간 동안 기록된 계좌 기준 최대 손실(MDD, Max Drawdown)
Last Entry Price
가장 최근에 포지션을 추가로 진입한 직후의 평균 진입 가격
Last Entry Lev
위 “Last Entry Price” 시점에서의 실레버리지
Liq Price (Fixed)
위에서 설명한 고정형 추정 청산가
Return from Start (%)
전략 시작 시점(초기 자본) 대비 현재 계좌 자산의 총 수익률(%)
이 테이블을 통해 사용자는:
현재 계좌와 포지션의 상태
리스크 수준
누적 성과
를 직관적으로 파악할 수 있습니다.
6. 시간 필터 및 라벨 옵션
6-1. 전략 동작 기간 설정
전략은 옵션으로 특정 기간에만 전략을 동작시키는 시간 필터를 제공합니다.
“Use Date Range” 옵션을 활성화하면:
시작 시각과 종료 시각을 지정하여
해당 구간에 한해서만 매매가 발생하도록 제한
옵션을 비활성화하면:
전략은 전체 차트 구간에서 자유롭게 동작
6-2. 진입 라벨 위치 설정
사용자는 매수/레버리지 라벨의 위치를 선택할 수 있습니다.
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
이를 통해 개인 취향 및 차트 가독성에 맞추어
시각화 방식을 유연하게 조정할 수 있습니다.
7. 활용 대상 및 사용 예시
본 전략은 다음과 같은 목적에 적합합니다.
현물 또는 선물 롱 포지션 기준 장기·스윙 관점 추매 전략 백테스트
“고점 대비 하락률”을 기준으로 한 규칙 기반 운용 아이디어 검증
레버리지 사용 시
계좌 레버리지·청산가·MDD를 동시에 모니터링하고자 하는 경우
특정 자산에 대해
“새로운 고점이 형성될 때마다
일정한 규칙으로 깊은 조정 구간에서만 분할 진입하고자 할 때”
실거래에 그대로 적용하기보다는,
전략 아이디어 검증 및 리스크 프로파일 분석,
자신의 성향에 맞는 파라미터 탐색 용도로 사용하는 것을 권장합니다.
8. 한계 및 유의사항
백테스트 결과는 미래 성과를 보장하지 않습니다.
과거 데이터에 기반한 시뮬레이션일 뿐이며,
실제 시장에서는
유동성
슬리피지
수수료 체계
강제청산 규칙
등 다양한 변수가 존재합니다.
청산가는 단순화된 공식에 따른 추정치입니다.
거래소별 실제 청산 규칙, 유지 증거금, 수수료, 펀딩비 등은
본 전략의 계산과 다를 수 있으며,
청산가 추정 라인은 참고용 지표일 뿐입니다.
레버리지 및 진입 비율 설정에 따라 손실 폭이 매우 커질 수 있습니다.
특히 **“첫 포지션 300% 진입”**과 같이 매우 공격적인 설정은
시장 급락 시 계좌 손실과 청산 리스크를 크게 증가시킬 수 있으므로
신중한 검토가 필요합니다.
실거래 연동 시에는 별도의 리스크 관리가 필수입니다.
개별 손절 기준
포지션 상한선
전체 포트폴리오 내 비중 관리 등
본 전략 외부에서 추가적인 안전장치가 필요합니다.
9. 결론
ATH Drawdown Re-Buy Long Only 전략은 단순한 “저가 매수”를 넘어서,
ATH 기준으로 드로우다운을 구조적으로 활용하고,
첫 포지션에 대한 **특수 규칙(100% / 300%)**을 적용하며,
레버리지·청산가·MDD·수익률을 통합적으로 시각화함으로써,
하락 구간에서의 규칙 기반 롱 포지션 구축과
리스크 모니터링을 동시에 지원하는 전략입니다.
사용자는 본 전략을 통해:
자신의 시장 관점과 리스크 허용 범위에 맞는
드로우다운 구간
진입 비율
레버리지 설정
다양한 시나리오에 대한 백테스트와 분석
을 수행할 수 있습니다.
다시 한 번 강조하지만,
본 전략은 연구·학습·백테스트를 위한 도구이며,
실제 투자 판단과 책임은 전적으로 사용자 본인에게 있습니다.
/ENG Version.
This script is designed to use historical drawdown data and automatically enter positions when a predefined percentage drop from the all-time high occurs, using a predefined percentage of your account equity.
You can use leverage, and default parameter values are provided out of the box (you can freely change them to suit your style).
In addition to the two main entry levels, you can add more entry conditions and custom entry percentages – just ask ChatGPT to modify the script.
For actual/live usage, please turn OFF the KillSwitch function and turn ON the Bar Magnifier feature.
ATH Drawdown Re-Buy Long Only Strategy
1. Strategy Overview
The ATH Drawdown Re-Buy Long Only strategy is an automatic re-buy (Long Only) system that builds long positions step-by-step at specific drawdown levels, based on the asset’s all-time high (ATH) and its subsequent drawdown.
This strategy is designed with the following goals:
Systematic scaled buying and leverage usage during sharp correction periods
Clear, rule-based entry logic using drawdowns from ATH
Real-time visualization of:
Average entry price
Leverage
Estimated liquidation price
Account MDD (Max Drawdown)
Return / performance
This allows traders to intuitively monitor both risk and position status.
※ This strategy is provided for educational, research, and backtesting purposes only.
It does not constitute investment advice and does not guarantee any profits.
2. Core Concepts
2-1. Drawdown from ATH (All-Time High)
On the chart, the strategy always tracks the highest high as the ATH.
Whenever a new high is made, ATH is updated, and based on that ATH the following are calculated:
How many percent the current bar’s Low is below the ATH
How many percent the current bar’s Close is below the ATH
Using these, the strategy executes buys at two predefined drawdown zones:
1st entry zone: When price drops X% from ATH
2nd entry zone: When price drops Y% from ATH
Each zone is allowed to trigger only once per ATH cycle.
When a new ATH is created, the “1st / 2nd entry possible” flags are reset, and new opportunities open up for that ATH leg.
2-2. Special Rule for the First Position (100% / 300%)
A key feature of this strategy is the special rule for the very first position.
When the strategy currently holds no position and is about to open the first long position:
Under normal conditions, it builds the position using 100% of account equity.
However, if at that moment the price has dropped by at least a predefined threshold from ATH (e.g. around –72.5% or more),
→ the strategy will open the first position using 300% of account equity.
This rule works as follows:
Whether the first entry happens at the 1st drawdown zone or at the 2nd drawdown zone,
If the current drawdown from ATH is at or below the threshold (e.g. –72.5% or worse),
→ the strategy interprets this as “a sufficiently deep crash” and opens the initial position with 300% of equity.
If the drawdown is less severe than the threshold,
→ the first entry is capped at 100% of equity.
So the strategy has two modes for the first entry:
Normal market conditions: 100% of equity
Deep drawdown conditions: 300% of equity
This special rule is intended to be aggressive in extremely deep crashes while staying more conservative in normal corrections.
3. Strategy Logic & Execution
3-1. Entry Conditions
The strategy tracks the ATH using the High price.
For each bar, it calculates the drawdown from ATH.
The user defines two drawdown zones, for example:
1st zone: ATH – 50%
2nd zone: ATH – 72.5%
For each zone, the strategy checks:
If no buy has been executed yet for that zone in the current ATH leg, and
If the current bar’s Low touches or falls below that zone’s price level,
→ That bar is considered to have triggered a buy condition.
Order simulation:
The strategy simulates entering a long position at that zone’s price level
(using a limit/market-like approximation for backtesting).
3-2. ATH Reset & Entry Opportunity Reset
When a new High goes above the previous ATH:
The ATH is updated to this new high.
Internal flags that track whether the 1st and 2nd entries have been used are reset.
This means:
Each time the market makes a new ATH,
The strategy once again has a fresh opportunity to execute 1st and 2nd drawdown entries for that new ATH leg.
4. Position Sizing & Leverage
4-1. Position Size Based on Account Equity
The strategy defines current equity as:
Current Equity = Initial Capital + Realized PnL + Unrealized PnL
For each entry zone, the position value is calculated as follows:
The user inputs:
“What % of equity to use at this zone”
The strategy:
Multiplies current equity by that percentage
Then multiplies by the strategy’s leverage factor
Thus:
Position Value = Current Equity × (Zone % / 100) × Leverage
Finally, this position value is divided by the entry price to determine the actual position size in tokens.
4-2. Exception for the First Position (100% / 300%)
For the very first position (when there is no open position),
the strategy does not use the zone % parameters. Instead, it uses fixed ratios:
Default: Enter the first position with 100% of equity.
If the drawdown from ATH at that moment is greater than or equal to a predefined threshold (e.g. –72.5% or more)
→ Enter the first position with 300% of equity.
The position value is computed as:
Position Value = Current Equity × (100% or 300%) × Leverage
Then it is divided by the entry price to obtain the token quantity.
This rule:
Applies regardless of whether the first entry occurs at the 1st zone or 2nd zone.
Embeds the philosophy:
“In very deep crashes, go much larger on the first entry; otherwise, stay more conservative.”
4-3. Tracking Real Leverage
On each bar, the strategy tracks:
The existing position size at the start of the bar
The newly added size (if any) on that bar
When a new entry occurs, it calculates the real leverage at that moment:
Real Leverage = (Position Value / Current Equity)
This is then displayed on the chart as a label, for example:
Lev 2.53x
This makes it easy to see the actual leverage level at each entry point.
5. Visualization & Monitoring
5-1. On-Chart Visual Elements
The strategy plots the following directly on the chart:
ATH Line
The all-time high (based on High) is plotted as an orange line.
Average Entry Price Line
When a position is open, the average entry price of that position is plotted as a yellow line.
Estimated Liquidation Price (Fixed) Line
The strategy detects when the position size changes.
At each size change, it uses the current average entry price and real leverage to compute an approximate liquidation price.
This “fixed liquidation price” is then plotted as a red line on the chart.
If there is no position, or if leverage is 1x or lower, the liquidation line is removed.
Entry Markers & Labels
When 1st/2nd entry conditions are met, the strategy:
Marks the entry point on the chart.
Displays labels such as "Buy XX% @ Price" and "Lev XXx",
showing both entry percentage and real leverage at that time.
The label placement is configurable:
Below Bar
Above Bar
At Price
5-2. Information Table (Top-Right Panel)
In the top-right corner of the chart, the strategy displays a summary table of the current account and position status. It typically includes:
Pos Qty (Token)
Absolute size of the current position (in tokens)
Pos Value (USDT)
Market value of the current position (qty × current price)
Leverage (Now)
Current real leverage (position value / current equity)
DD from ATH (%)
Current drawdown (%) from the latest ATH, based on current price
Avg Entry
Average entry price of the current position
PnL (%)
Unrealized profit/loss (%) of the current position
Max DD (Equity %)
The maximum equity drawdown (MDD) recorded over the entire backtest period
Last Entry Price
Average entry price immediately after the most recent add-on entry
Last Entry Lev
Real leverage at the time of the most recent entry
Liq Price (Fixed)
The fixed estimated liquidation price described above
Return from Start (%)
Total return (%) of equity compared to the initial capital
Through this table, users can quickly grasp:
Current account and position status
Current risk level
Cumulative performance
6. Time Filters & Label Options
6-1. Strategy Date Range Filter
The strategy provides an option to restrict trading to a specific time range.
When “Use Date Range” is enabled:
You can specify start and end timestamps.
The strategy will only execute trades within that range.
When this option is disabled:
The strategy operates over the entire chart history.
6-2. Entry Label Placement
Users can customize where entry/leverage labels are drawn:
Below Bar (Below Bar)
Above Bar (Above Bar)
At the actual price level (At Price)
This allows you to adjust visualization according to personal preference and chart readability.
7. Use Cases & Applications
This strategy is suitable for the following purposes:
Long-term / swing-style re-buy strategies for spot or futures long positions
Testing rule-based strategies that rely on “drawdown from ATH” as a main signal
Monitoring account leverage, liquidation price, and MDD when using leverage
Handling situations where, for a given asset:
“Every time a new ATH is formed,
you want to wait for deep corrections and enter only at specific drawdown zones”
It is generally recommended to use this strategy not as a direct plug-and-play live system, but as a tool for:
Strategy idea validation
Risk profile analysis
Parameter exploration to match your personal risk tolerance and style
8. Limitations & Warnings
Backtest results do not guarantee future performance.
They are based on historical data only.
In live markets, additional factors exist:
Liquidity
Slippage
Fee structures
Exchange-specific liquidation rules
Funding fees, etc.
The liquidation price is only an approximate estimate, derived from a simplified formula.
Actual liquidation rules, maintenance margin requirements, fees, and other details differ by exchange.
The liquidation line should be treated as a reference indicator, not an exact guarantee.
Depending on the configured leverage and entry percentages, losses can be very large.
In particular, extremely aggressive settings such as “first position 300% of equity” can greatly increase the risk of large account drawdowns and liquidation during sharp market crashes.
Use such settings with extreme caution.
For live trading, additional risk management is essential:
Your own stop-loss rules
Maximum position size limits
Portfolio-level exposure controls
And other external safety mechanisms beyond this strategy
9. Conclusion
The ATH Drawdown Re-Buy Long Only strategy goes beyond simple “buy the dip” logic. It:
Systematically utilizes drawdowns from ATH as a structural signal
Applies a special first-position rule (100% / 300%)
Integrates visualization of leverage, liquidation price, MDD, and returns
All of this supports rule-based long position building in drawdown phases and comprehensive risk monitoring.
With this strategy, users can:
Explore different:
Drawdown zones
Entry percentages
Leverage levels
Run various backtests and scenario analyses
Better understand the risk/return profile that fits their own market view and risk tolerance
Once again, this strategy is intended for research, learning, and backtesting only.
All real trading decisions and their consequences are solely the responsibility of the user.
Liquidation Cascade Detector [QuantAlgo]🟢 Overview
The Liquidation Cascade Detector employs multi-dimensional microstructure analysis to identify forced liquidation events by synthesizing volume anomalies, price acceleration dynamics, and volatility regime shifts. Unlike conventional momentum indicators that merely track directional bias, this indicator isolates the specific market conditions where leveraged positions experience forced unwinding, creating asymmetric opportunities for mean reversion traders and market makers to take advantage of temporary liquidity imbalances.
These liquidation cascades manifest through various catalysts: overwhelming spot selling coupled with leveraged long liquidation forced unwinding creates downward spirals where organic sell pressure triggers margin calls, which generate additional selling that triggers more margin calls. Conversely, sudden large buy orders or coordinated buying can squeeze overleveraged shorts, forcing buy-to-cover orders that push price higher, triggering additional short stops in a self-reinforcing feedback loop. The indicator captures both scenarios, regardless of whether the initial catalyst is organic flow or forced liquidation.
For sophisticated traders/market makers deploying amplification strategies, this indicator serves as an early warning system for distressed order flow. By detecting the moments when cascading stop-losses and margin calls create self-reinforcing price movements, the system enables traders to: (1) identify forced participants experiencing capital pressure, (2) strategically add liquidity in the direction of panic flow to amplify displacement, (3) accumulate contra-positions during the overshoot phase, and (4) capture mean reversion profits as equilibrium pricing reasserts itself. This approach transforms destructive liquidation events into potential profit opportunities by systematically front-running and then fading coordinated forced selling/buying.
🟢 How It Works
The detection engine operates through a three-tier confirmation framework that validates liquidation events only when multiple independent market stress indicators align simultaneously:
► Tier 1: Volume Anomaly Detection
The system calculates bar-to-bar volume ratios to identify abnormal participation spikes characteristic of forced liquidations. The Volume Spike threshold filters for transactions where current volume significantly exceeds previous bar volume. When leveraged positions hit stop-losses or margin requirements, their simultaneous unwinding creates distinctive volume signatures absent during organic price discovery. This metric isolates moments when market makers face one-sided order flow from distressed participants unable to control execution timing, whether triggered by whale orders absorbing liquidity or cascading margin calls creating relentless directional pressure.
► Tier 2: Price Acceleration Measurement
By comparing current bar's absolute body size against the previous bar's movement, the algorithm quantifies momentum acceleration. The Price Acceleration threshold identifies scenarios where price velocity increases dramatically, a hallmark of cascading liquidations where each stop-loss triggers additional stops in a feedback loop. This calculation distinguishes between gradual trend development (irrelevant for amplification attacks) and explosive moves driven by forced order flow requiring immediate liquidity provision. The metric captures both panic selling scenarios where spot sellers overwhelm bid liquidity triggering long liquidations, and short squeeze dynamics where aggressive buying exhausts offer-side depth forcing short covering.
► Tier 3: Volatility Expansion Analysis
The indicator measures bar range expansion by computing the current high-low range relative to the previous bar. The Volatility Spike threshold captures regime shifts where intrabar price action becomes erratic, evidence that market depth has evaporated and order book imbalance is driving price. Combined with body-to-range analysis indicating strong directional conviction, this metric confirms that volatility expansion reflects genuine liquidation pressure rather than random noise or low-volume chop.
*Supplementary Confirmation Metrics
Beyond the three primary detection tiers, the system analyzes additional candle characteristics that distinguish genuine liquidation events from ordinary volatility:
► Candle Strength: Measures the ratio of candle body size to total bar range. High readings (above 60%) indicate strong directional conviction where price moved decisively in one direction with minimal retracement. During liquidations, distressed traders execute market orders that drive price aggressively without the normal back-and-forth of balanced trading. Strong-bodied candles with minimal wicks confirm forced participants are accepting any available price rather than attempting to minimize slippage, validating that observed volume and price acceleration stem from liquidation pressure rather than routine trading.
► Volume Climax: Identifies when current volume reaches the highest level within recent history. Climax volume events mark terminal liquidation phases where maximum panic or squeeze intensity occurs. These extreme participation spikes typically represent the final wave of forced exits as the last remaining stops are triggered or the final shorts capitulate. For mean reversion traders, volume climax signals provide optimal reversal entry timing, as they mark maximum displacement from equilibrium when all forced sellers/buyers have been exhausted.
*Directional Classification
The system categorizes cascades into two actionable classes:
1. Short Liquidation (Bullish Cascade): Upward price movement combined with cascade patterns equals forced short covering. This occurs when aggressive spot buying (often from whales placing large market orders) or coordinated buy programs exhaust available offer liquidity, spiking price upward and triggering clustered short stop-losses. Short sellers experiencing margin pressure must buy-to-close regardless of price, creating artificial demand spikes that compound the initial buying pressure. The combination of organic buying and forced covering creates explosive upward moves as each liquidated short adds buy-side pressure, triggering additional shorts in a self-reinforcing loop. Market makers can amplify this by lifting offers ahead of forced buy orders, then selling into the exhaustion at elevated levels.
2. Long Liquidation (Bearish Cascade): Downward price movement combined with cascade patterns equals forced long liquidation. This manifests when heavy spot selling (panic sellers, large institutional unwinds, or coordinated distribution) overwhelms bid-side liquidity, breaking through support levels where long stop-losses cluster. Over-leveraged longs facing margin calls must sell-to-close at any price, generating artificial supply waves that compound the initial selling pressure. The dual force of organic selling coupled with forced long liquidation creates downward spirals where each margin call triggers additional margin calls through further price deterioration. Amplification opportunities exist by hitting bids ahead of panic selling, accumulating long positions during the capitulation, and reversing as sellers exhaust.
🟢 How to Use
1. For Mean Reversion Traders
When the indicator highlights a short liquidation cascade (green background), this signals that shorts are experiencing forced buy-to-cover pressure, often initiated by whale bids or aggressive spot buying that triggered the squeeze. Mean reversion traders can interpret this as a temporary upward dislocation from fair value. As the dashboard shows declining momentum metrics and the cascade highlighting stops, this represents a potential fade opportunity. Enter short positions expecting price to revert back toward pre-cascade levels once the forced buying exhausts and the initial large buyer completes their accumulation.
When a long liquidation cascade triggers (red background), longs are undergoing forced sell-to-close liquidation, typically catalyzed by overwhelming spot selling that breached key support levels. This creates artificial downward pressure disconnected from fundamental value, as margin-driven forced selling compounds organic sell flow. Mean reversion traders wait for the cascade to complete (dashboard transitions from active liquidation status to neutral), then enter long positions anticipating snap-back toward equilibrium pricing as panic subsides and forced sellers are exhausted.
You can also monitor the dashboard's Volume Climax indicator. When it displays "YES" during an active cascade, this suggests the liquidation is reaching its terminal phase, whether driven by the final shorts being squeezed out or the last leveraged longs capitulating. Mean reversion entries become highest probability at this point, as maximum displacement from fair value has occurred. Wait for the next 1-3 bars after climax confirmation, then enter contra-trend positions with tight stops.
The Candle Strength metric also helps validate entry timing. When candle strength readings drop significantly after maintaining elevated levels during the cascade, this divergence indicates absorption is occurring. Market makers are stepping in to provide liquidity, supporting your mean reversion thesis. Strong candle bodies during the cascade followed by weaker bodies signal the forced flow is diminishing.
2. For Momentum & Trend Following Traders
When price breaks through a significant resistance level and immediately triggers a short liquidation cascade (green background), this confirms breakout validity through forced participation. Shorts positioned against the breakout are now experiencing margin pressure from the combination of breakout momentum and potential whale buying, creating self-reinforcing buying that propels price higher. Enter long positions during the cascade or immediately after, as the forced covering provides fuel for extended momentum continuation.
Conversely, when price breaks below key support and triggers a long liquidation cascade (red background), the breakdown is validated by forced selling from trapped longs. Heavy spot selling coupled with margin liquidations creates accelerated downside momentum as liquidations cascade through clustered stop-loss levels. Enter short positions as the cascade develops, riding the combined force of organic selling and forced liquidation for extended trend moves.
3. For Sophisticated Traders & Market Makers
► Amplification Attack Execution
Sophisticated operators can exploit cascades through systematic amplification positioning. When a short liquidation is detected (green highlight activating), often initiated by whale bids absorbing offer liquidity, place aggressive buy orders to front-run and amplify the forced short covering. This exacerbates upward pressure, pushing price further from equilibrium and triggering additional clustered stops. Simultaneously begin accumulating short positions at these artificially elevated levels. As dashboard metrics indicate cascade exhaustion (volume spike declining, climax signal appearing, candle strength weakening), flatten amplification longs and hold accumulated shorts into the mean reversion.
For long liquidations (red highlight), typically catalyzed by heavy spot selling overwhelming bid depth, execute the inverse strategy. Place aggressive sell orders to compound the panic selling, amplifying downward displacement and accelerating margin call triggers. Layer long entries at depressed prices during this amplification phase as forced liquidation selling creates artificial supply. When dashboard signals cascade completion (metrics normalizing, volume climax passing), exit amplification shorts and maintain long positions for the reversal trade.
► Market Making During Liquidity Crises
During detected cascades, temporarily adjust quote placement strategy. When dashboard shows all three confirmation metrics activating simultaneously with strong candle bodies, this indicates the highest probability liquidation event, whether from whale order flow or cascading margin calls. Widen spreads dramatically to capture enhanced edge during the liquidity vacuum. Alternatively, step away from quote provision entirely on your natural inventory side (stop offering during short cascades driven by aggressive buying, stop bidding during long cascades driven by overwhelming selling) to avoid adverse selection from forced flow.
Use cascade detection to inform inventory management. During short cascades initiated by large buy orders or short squeezes, reduce existing short inventory exposure while allowing the forced buying to push price higher. Rebuild short inventory only at the inflated levels created by liquidation pressure. During long cascades where spot selling compounds leveraged liquidation, reduce long inventory and use the forced selling to reaccumulate at artificially depressed prices rather than providing stabilizing liquidity too early.
► Sequential Positioning Strategy
Advanced traders can structure trades in phases: (1) Initial amplification orders placed immediately upon cascade detection to front-run forced flow, (2) Contra-position accumulation scaled in as displacement extends and dashboard readings intensify, (3) Amplification trade exit when metrics show deceleration or candle strength weakens, (4) Contra-position hold through mean reversion, targeting pre-cascade price levels. This sequential approach extracts profit from both the dislocation phase and the subsequent equilibrium restoration.
► Risk Monitoring
If cascade highlighting persists across many consecutive bars while dashboard volume readings remain extremely elevated with sustained strong candle bodies, this suggests sustained institutional deleveraging or persistent whale activity rather than simple retail liquidation. Reduce amplification position sizing significantly, as these extended events can exhibit delayed mean reversion. Professional counter-parties may be establishing dominant positions, limiting your edge.
When volatility spike metrics decline while cascade highlighting continues, professional absorption is occurring. Proceed cautiously with amplification strategies, as intelligent liquidity providers are already positioning for the reversal, potentially front-running your intended reversal trade. Similarly, if large liquidation wicks appear during cascades, this indicates partial absorption is happening, suggesting more sophisticated players are taking the opposite side of distressed flow.
Calc. Risco/Lote – Multi Ativos (v2)Works for:
Forex (EURUSD, GBPUSD, USDCHF, USDCAD, USDJPY etc.)
Indices (US30, NAS100, GER40…)
Gold (XAUUSD), etc.
You manually enter:
Cash / Balance (USD)
Risk per trade (%)
Direction (Buy/Sell)
Entry Price
Stop Price (SL)
Target Price (TP)
The indicator calculates:
Distance between SL and TP in points
Value per point (automatic per asset)
Ideal lot / position size
Loss if SL hits (USD)
Profit if TP hits (USD)
Risk/Reward (R:R)
Multi-Asset % Performance Table | v2.1 | TCP Multi-Asset % Performance Table | v2.1 | TCP
ESSENTIAL SUMMARY:
Multi-Asset % Performance Table eliminates the need to manually draw and manage individual "Price Range" tools for every asset. It automatically tracks up to 15 tickers independently in a single dashboard, calculating a TOTAL SCORE (Portfolio Average) for you. Unlike manual drawings, it supports a Global Range while allowing Custom Dates for specific assets, ensuring each ticker is calculated based on its own precise entry/exit. The Smart Visuals dynamically draw the correct date lines only for the ticker you are currently viewing, keeping your chart automatic, accurate, and clutter-free.
FUL DESCRIPTION:
📊 What is this tool?
The Multi-Asset % Performance Table is a powerful portfolio dashboard designed to track the percentage performance of up to 15 different assets simultaneously.
Instead of checking tickers one by one or manually drawing price ranges, this indicator aggregates everything into a single, clean table. It allows you to compare the ROI (Return on Investment) of a basket of coins or stocks over a specific time period and calculates an aggregate TOTAL SCORE (Average %) for your selection.
🚀 Key Features
15 Asset Slots: Monitor up to 15 different tickers (Crypto, Stocks, Forex, etc.) in one view.
Global vs. Custom Dates: Set a "Global" start/end date for the whole portfolio, but override specific assets with Custom Dates if they entered the portfolio at a different time.
Smart Visuals: Automatically draws vertical dashed lines on your chart representing the start and end dates of the ticker you are currently viewing.
Total Score Calculation: Calculates the average percentage change of your portfolio. You can dynamically include or exclude specific assets from this average using the settings.
Status Column: A quick visual reference (✔ or ✘) in the table showing which assets are currently included in the Total Score calculation.
⚙️ How it Works
Data Fetching: The script pulls "Close" prices from the Daily timeframe to ensure accuracy across long periods.
Smart Matching: The visual lines automatically detect which asset you are viewing. For example, if you are looking at BTCUSDT and have custom dates set for it, the vertical lines will jump to those specific dates. If you view a ticker not in your list, it defaults to the Global dates.
Visual Protection: The script uses advanced logic to ensure only one set of range lines appears on the chart at a time, keeping your workspace clean.
🛠️ Instructions & Settings
1. Setting up your Assets
Open the Settings (Cogwheel icon).
Under ASSET 1 through ASSET 15, enter the tickers you want to track (e.g., BINANCE:BTCUSDT).
Include in Avg?: Uncheck this if you want to see the asset in the table but exclude it from the "TOTAL SCORE" average.
2. Defining Time Ranges
Global Settings: Set the Global Start and Global End dates at the top. This applies to all assets by default.
Custom Dates: If a specific asset (e.g., Asset 4) was bought on a different day, check the "Custom Dates?" box for that asset and enter its specific Start/End time.
3. Reading the Table
The table appears on the chart (default: Bottom Right) with three columns:
Asset: The name of the ticker.
% Change: The percentage move from Start Date to End Date. (Green = Positive, Red = Negative).
Inc: Shows a ✔ if the asset is included in the Total Score average, or a ✘ if excluded.
4. The Visual Lines
Two vertical dashed lines will appear on your chart.
Note: These lines are visual references only. You cannot drag them to change the dates. To change the dates, you must use the Settings menu.
💡 Tips
Hover for Details: Hover your mouse over the % Change value in the table to see a tooltip showing the exact Start Price and End Price used for the calculation.
Resolution: The script defaults to 1 Day resolution for optimal accuracy on historical data.
v2.1 | TCP - Custom Built for Precision Performance Tracking
calculator contracts MNQ PIPEGAVTRADESThis is a Risk Management indicator that calculates the exact contracts to trade based on your defined Max Risk ($) and Stop Loss Ticks.
It displays all key Position Sizing metrics (including Account Capital and Risk %) in a fixed table on the chart.
TernTable: Crypto SectorsTernTables:CryptoSecs
This was hung on my Sector ETFs script to see if I could filter some noise from crypto by applying a GICS (Global Industry Classification Standard) style sector model to the crypto markets.
Crypto classification is certainly a little more nuanced so not completely straightforward.
It was designed to filter a researched and organised view of generally recognised cryptocurrency sectors and their confirmed constituent components.
The main purpose was a shot at displaying live crypto market data on my chart with instantaneous visual analysis, using leader laggard colour logic for performance indication, plus bullish bearish colour logic using the header for instant visual sector strength analysis.
This was never going to be an exhaustive tool of course and amazingly only or two of the sector lists wont fit on your laptop screen without zooming but it’s UI versatility both in custom display and custom threshold functionality is very effective. Viewing a coin on your watchlist with its sector overlayed in the chart brings the optional visual alert function into consideration. All basic but all effective and all customisable
Can't ignore the educational value either it’s teaching by osmosis what the sectors do and which coins go where clues to why.
As an after thought - I added a live stock market filter for 20 sector-specific ETFs like SPY, QQQ, XLV, XLF, allowing the comparison of the live performance of traditional financial sectors to live crypto sector data without leaving your chart.
Not certain how often it will need to be updated and any feedback re the legitimacy and accuracy of its components is kindly welcomed it is up to date at date of publishing.
It’s pretty easy to use, here is a list what you're getting with sector classifications with brief descriptions
CMC 20
CoinMarketCap Top 20: the largest cryptos by market cap. Great starting point to see what the overall market is doing
ETFs
All major U.S.-listed Bitcoin & Ethereum ETFs. Lets you compare crypto performance directly with traditional finance
Layer 0
Foundational interoperability protocols (Polkadot, Cosmos, ICP, etc.). These are the “bridges” that allow different blockchains to communicate
Layer 1
Independent base-layer blockchains that run their own consensus and security (Bitcoin, Ethereum, Solana, Cardano, TON, etc.).
Layer 2
Scaling networks built on top of Layer 1s to increase speed and lower fees (Arbitrum, Optimism, Base, Polygon, zk-rollups, etc.)
Layer 3
Application-specific chains or rollups designed for one purpose (gaming chains, DeFi-specific, social, etc.)
Web3
The “ownership internet”: gaming tokens, NFTs, metaverse land, music/streaming platforms, social tokens, and creator-economy projects
DeFi
Decentralised Finance: lending platforms, decentralized exchanges, derivatives, yield aggregators, and insurance protocols
Decentralised Storage
Blockchain-based alternatives to AWS/Google Cloud (Filecoin, Arweave, Storj, etc.)
Oracles
Data providers that feed off-chain information (prices, weather, sports results) into smart contracts
Privacy
Privacy coins and protocols that obfuscate transaction details (Monero, Zcash, Beam, etc.)
Yield & Lending
Protocols focused purely on lending, borrowing, and yield generation
DEX
Pure decentralized exchanges (Uniswap, SushiSwap, Jupiter, GMX, etc.)
DAO
Governance tokens of major decentralized autonomous organizations (Maker, Lido, Aave, ENS, etc.)
Infrastructure / Middleware
The picks-and-shovels layer: node services, RPC providers, indexing, cross-chain bridges, etc
Real World Assets (RWA)
Tokenised traditional assets: treasuries, real estate, private credit, stablecoins backed by real-world collateral
Restaking & Liquid Restaking
EigenLayer ecosystem and liquid-restaking tokens (eigen, ether.fi, Pendle, etc.). Currently the fastest-growing narrative
Traditional Sector ETFs
Classic U.S. sector ETFs (SPY, QQQ, XLF, XLE, XLV, XLY, etc.). Extra layer of analysis by comparing live stock market conditions with livecrypto market conditions
A list of the UI Toggles
* Sector Dropdown
• Select Sector: Choose the sector to display (e.g., CMC 20, Layer 1, DeFi, etc.)
* Custom Tickers
• Enter Tickers: Input custom coin tickers (e.g., BTCUSD, ETHUSD) to track specific assets
* Show % Change Row
• Toggle On/Off: Display the % change row for each sector/coin
* Show Current Price Row
• Toggle On/Off: Display the current price for each sector/coin
* Show Price-Diff Row
• Toggle On/Off: Display the price difference (current price - previous day's price)
* Show Spacer Row
• Toggle On/Off: Add a spacer row between data rows for clarity
* Table Position
• Select Position: Choose the position of the data table on your chart (Top Left, Top Right, etc.)
Visual Options:
* Show Sector Name
• Toggle On/Off: Display the sector name pane label on chart
* Custom Bull/Bear Threshold
• Toggle On/Off: Set a custom threshold for bullish/bearish sector performance
• Threshold (%): Set the percentage threshold (e.g., 50%) for bullish/bearish classification
* Show Live % in Header
• Toggle On/Off: Display the live percentage change in the table header
* Dynamic Decimal Formatting
• Toggle On/Off: Enable dynamic formatting for numbers display.
* Sort by % Change
• Toggle On/Off: Sort sectors by % change in performance
* Enable Alerts
• Toggle On/Off: Enable alerts based on performance thresholds
* Alert Threshold (%)
• Set Threshold: Define the percentage threshold (e.g.,70%) for triggering alerts
* Cooldown (bars)
• Toggle On/Off: Enable cooldown to prevent alerts from triggering too quickly
• Cooldown Duration: Set the cooldown period in bars (e.g., 10 bars)
* % Threshold Mode
• Toggle On/Off: Enable % Threshold Mode to filter sectors based on a percentage change threshold
• Threshold %: Set the percentage for filtering sectors (e.g., only show sectors with > 5% change)
A lot of toggles probably left once favourites are set but this UI interface does allow experimentation with the utility of channelling raw live data through custom designed filters. Just saying !
I need to include this of course
This indicator provides sector-based organisation and real-time performance visualisation for cryptocurrencies. It is not intended to predict price movements or guarantee outcomes. Crypto assets carry significant risk, including loss of capital. Past performance does not guarantee future results. All data and sector classifications are best-effort and may be incomplete, inaccurate, or outdated. Nothing in this script should be interpreted as financial advice. You are solely responsible for your own trading decisions.
That’s it really, I am currently pleased with how this indicator turned out, if you have a crypto trading toolkit put this in it.
ICT/SMC DOL Detector PRO (Final)This indicator is designed to operate only on the 1-hour timeframe.
The ICT/SMC DOL Detector PRO is an educational indicator designed to identify and visualize Draw on Liquidity (DOL) levels across multiple time-frames. It tracks unmitigated daily highs and lows, clusters them into zones, and calculates confidence scores based on multiple factors including time decay, cluster size, and time-frame alignment.
This indicator is based on ICT (Inner Circle Trader) concepts and liquidity theory, which suggests that price tends to seek out areas of concentrated unfilled orders before reversing or continuing its trend.
What is a DOL (Draw on Liquidity)?
A Draw on Liquidity represents a daily high or low that has not been revisited (mitigated) by price. These levels act as "magnets" that draw price toward them because:
1. They represent untapped liquidity pools where unfilled orders exist
2. Market makers and institutions often target these levels to fill large orders
3. Price is drawn to these zones to clear pending orders
4. They can serve as potential reversal or continuation zones once liquidity is taken
Methodology
1. Level Tracking
The indicator monitors daily session highs and lows on the 1-hour time-frame, tracking:
- Session high price and time of formation
- Session low price and time of formation
- Whether each level has been breached (mitigated)
- Time elapsed since level formation
2. Clustering Algorithm
Unmitigated levels within a defined tolerance (default 0.5% of price) are grouped together to identify zones where multiple DOLs cluster. Larger clusters indicate stronger liquidity pools.
3. Confidence Scoring (The "AI" Logic)
Each DOL receives a confidence score (0-100%) based on three weighted factors. This is the core "AI" intelligence of the indicator:
**Factor 1: Cluster Size (50% weight)**
- Counts how many unmitigated levels exist within 0.5% of the price zone
- Formula: (levels_in_cluster / total_unmitigated_levels) × 50
- Logic: More unfilled orders clustered together = stronger liquidity pool = higher confidence
- Example: If 5 out of 10 total unmitigated levels cluster at 27,500, cluster score = (5/10) × 50 = 25%
**Factor 2: Time Decay (25% weight)**
- Calculates age of the level since formation
- Fresh levels (< 1 week old): Full 25% score
- Aging penalty: Loses 5% per week of age
- Maximum penalty: 25% (very old levels = 0% time score)
- Formula: max(0, 25 - (weeks_old × 5))
- Logic: Recent liquidity is more relevant than old liquidity that price has ignored for months
**Factor 3: Timeframe Alignment (25% weight)**
- Checks how many timeframes (1H, 4H, D1, W1) point in the same direction
- If multiple timeframes identify DOLs on the same side (all bullish or all bearish): Higher score
- If mixed signals: Lower score
- Formula: (aligned_timeframes / total_timeframes) × 25
- Logic: When multiple timeframes agree, the liquidity zone is validated across different time perspectives
**Total Confidence Score:**
```
Confidence = Cluster_Score + Time_Score + Alignment_Score
= (0-50%) + (0-25%) + (0-25%)
= 0-100%
```
**Example Calculation:**
```
DOL at 27,500:
- 6 out of 12 unmitigated levels cluster here → (6/12) × 50 = 25%
- Level is 2 weeks old → 25 - (2 × 5) = 15%
- 3 out of 4 timeframes bullish toward this level → (3/4) × 25 = 18.75%
- Total Confidence = 25% + 15% + 18.75% = 58.75% ≈ 59%
```
This mathematical approach removes subjectivity and provides objective, data-driven confidence scoring.
4. Multi-Timeframe Analysis
The indicator analyzes DOLs across four timeframes:
- **1H:** Intraday levels (fastest reaction)
- **4H:** Short-term swing levels
- **Daily:** Intermediate-term levels
- **Weekly:** Long-term structural levels
For each timeframe, it identifies:
- Highest confidence unmitigated high
- Highest confidence unmitigated low
- Directional bias (bullish if high > low confidence, bearish if low > high confidence)
5. Primary DOL Selection (AI Auto-Selection Logic)
When "Show AI DOL" is enabled, the indicator uses an automated selection algorithm to identify the most important targets:
**Step 1: Collect All Candidates**
The algorithm gathers all identified DOLs from all timeframes (1H, 4H, D1, W1) that meet minimum criteria:
- Must be unmitigated (not yet swept)
- Must have confidence score > 0%
- Must have at least 1 level in cluster
**Step 2: Calculate Confidence for Each**
Each candidate DOL receives its confidence score using the three-factor formula described above (Cluster + Time + Alignment).
**Step 3: Sort by Confidence**
All candidates are ranked from highest to lowest confidence score.
**Step 4: Select Primary and Secondary**
- **P1 (Primary DOL):** The DOL with the absolute highest confidence score
- **P2 (Secondary DOL):** The DOL with the second highest confidence score
**Why This Matters:**
Instead of manually scanning multiple timeframes and guessing which level is most important, the AI objectively identifies the two highest-probability liquidity targets based on quantifiable data.
**Example AI Selection:**
```
Available DOLs:
- 1H High: 27,400
- 4H High: 27,500
- D1 High: 27,500 ← P1 (Highest)
- W1 High: 27,650 ← P2 (Second Highest)
- 1H Low: 26,800
- D1 Low: 26,500
AI Selection:
P1 = 27,500 (Daily High with 92% confidence)
P2 = 27,650 (Weekly High with 88% confidence)
```
This provides a data-driven target selection rather than subjective manual interpretation. The AI removes emotion and bias, selecting targets based purely on mathematical probability.
Features
Why "AI" DOL?
The term "AI" in this indicator refers to the automated algorithmic selection process, not machine learning or neural networks. Specifically:
**What the AI Does:**
- Automatically evaluates all available DOLs across all timeframes
- Applies a weighted scoring algorithm (Cluster 50%, Time 25%, Alignment 25%)
- Objectively ranks DOLs by probability
- Selects the top 2 highest-confidence targets (P1 and P2)
- Removes human bias and emotion from target selection
**What the AI Does NOT Do:**
- It does not use machine learning or train on historical data
- It does not predict future price movements
- It does not adapt or "learn" over time
- It does not guarantee accuracy
The "AI" is simply an automated decision-making algorithm that applies consistent mathematical rules to identify the most statistically significant liquidity zones. Think of it as a "smart filter" rather than artificial intelligence in the traditional sense.
Visual Components
**Daily Level Lines:**
- Green lines: Unmitigated (not yet breached) levels
- Red lines: Mitigated (already breached) levels
- Dots at origin point showing where level was formed
- X marker when level gets breached
- Lines extend forward to show projection
**DOL Labels:**
- Display timeframe (1H, 4H, D1, W1) or "DOL" for AI selection
- Show confidence percentage in brackets
- Color-coded by timeframe:
- Lime: AI DOL (Smart selection)
- Aqua: 1-hour timeframe
- Blue: 4-hour timeframe
- Purple: Daily timeframe
- Orange: Weekly timeframe
**Info Box (Top Right):**
Displays comprehensive liquidity metrics:
- Total levels tracked
- Active (unmitigated) levels count
- Cleared (mitigated) levels count
- Flow direction (BID PRESSURE / OFFER PRESSURE)
- Most recent sweep
- Primary and Secondary DOL targets
- Multi-timeframe bias analysis
- Overall directional bias
Settings Explained
**Daily Levels Group:**
- Show Daily Highs/Lows: Toggle visibility of all daily level tracking
- Unbreached Color: Color for levels not yet hit
- Breached Color: Color for levels that have been swept
- Show X on Breach: Display marker when level is breached
- Show Dot at Origin: Display marker at level formation point
- Line Width: Thickness of level lines (1-5)
- Line Extension: How many bars forward to project (1-24)
- Max Days to Track: Historical lookback period (5-200 days)
**DOL Settings Group:**
- Cluster Tolerance %: Price range to group DOLs (0.1-2.0%)
- Show Price on Labels: Display actual price value on labels
- Backtest Mode: Only show recent labels for clean historical analysis
- Labels Lookback: Number of bars to show labels when backtesting (10-500)
**Info Box Group:**
- Show Info Box: Toggle info panel visibility
**DOL Toggles Group:**
- Show AI DOL: Display smart auto-selected primary target
- Show 1HR DOL: Display 1-hour timeframe DOLs
- Show 4HR DOL: Display 4-hour timeframe DOLs
- Show Daily DOL: Display daily timeframe DOLs
- Show Weekly DOL: Display weekly timeframe DOLs
**Advanced Group:**
- Manual Mode: Simplified display showing only daily high/low clusters
How to Use This Indicator
Educational Application
This indicator is intended for educational purposes to help traders:
1. **Understand Liquidity Concepts:** Visualize where unfilled orders may exist
2. **Identify Key Levels:** See where price may be drawn to
3. **Analyze Market Structure:** Understand how price interacts with liquidity
4. **Study Multi-Timeframe Alignment:** Observe when multiple timeframes agree
5. **Learn ICT Concepts:** Apply liquidity theory in practice
Interpretation Guidelines
**BID PRESSURE (Flow):**
When lows are being swept more than highs, it suggests:
- Sell-side liquidity being taken
- Potential for upward move to unfilled buy-side liquidity
- Market may be clearing the way for a bullish move
**OFFER PRESSURE (Flow):**
When highs are being swept more than lows, it suggests:
- Buy-side liquidity being taken
- Potential for downward move to unfilled sell-side liquidity
- Market may be clearing the way for a bearish move
**Confidence Scores:**
- 90-100%: Very high probability zone (strong cluster, recent, aligned)
- 80-89%: High probability zone (good cluster, relatively recent)
- 70-79%: Moderate probability zone (decent cluster or older)
- 60-69%: Lower probability zone (small cluster or very old)
- Below 60%: Weak zone (minimal confluence)
**Timeframe Analysis:**
- All timeframes LONG: Strong bullish alignment
- All timeframes SHORT: Strong bearish alignment
- Mixed: Conflicting signals, exercise caution
- Higher timeframes (D1, W1) carry more weight than lower (1H, 4H)
**DIRECTIONAL Indicator:**
- BULLISH: Overall bias suggests upward movement toward buy-side DOLs
- BEARISH: Overall bias suggests downward movement toward sell-side DOLs
- NEUTRAL: No clear directional bias, conflicting signals
Practical Application Examples
**Example 1: Bullish Setup**
```
Flow: BID PRESSURE (lows being swept)
P1: 27,500 (price above current market)
D1: LONG 27,500
W1: LONG 27,650
DIRECTIONAL: BULLISH
```
Interpretation: Price has cleared sell-side liquidity. High confidence buy-side DOL at 27,500. Daily and Weekly timeframes aligned bullish. Watch for move toward 27,500 target.
**Example 2: Bearish Setup**
```
Flow: OFFER PRESSURE (highs being swept)
P1: 26,200 (price below current market)
D1: SHORT 26,200
W1: SHORT 26,100
DIRECTIONAL: BEARISH
```
Interpretation: Price has cleared buy-side liquidity. High confidence sell-side DOL at 26,200. Daily and Weekly timeframes aligned bearish. Watch for move toward 26,200 target.
**Example 3: Mixed Signals - Wait**
```
Flow: BID PRESSURE
P1: 26,800
D1: LONG 27,000
W1: SHORT 26,200
DIRECTIONAL: NEUTRAL
```
Interpretation: Conflicting signals. Flow suggests up, but Weekly bias is down. Confidence scores moderate. Better to wait for clarity.
Important Considerations
This Indicator Does NOT:
- Predict the future
- Guarantee profitable trades
- Provide buy/sell signals
- Replace proper risk management
- Work in isolation without other analysis
This Indicator DOES:
- Visualize liquidity concepts
- Identify potential target zones
- Show timeframe alignment
- Calculate objective confidence scores
- Help understand market structure
Proper Usage:
1. Use as one component of a complete trading strategy
2. Combine with price action analysis
3. Confirm with other technical indicators
4. Consider fundamental factors
5. Always use proper risk management
6. Backtest any strategy before live trading
Risk Disclaimer
**FOR EDUCATIONAL PURPOSES ONLY**
This indicator is for educational purposes only. Trading financial markets involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions.
**Important Limitations:**
- No indicator is 100% accurate, including the AI selection
- The "AI" is an automated algorithm, not predictive artificial intelligence
- DOL levels can be swept and price can continue in the same direction
- Confidence scores are mathematical calculations, not predictions or probabilities of success
- High confidence does not mean guaranteed profit
- Markets can remain irrational longer than you can remain solvent
- Always use stop losses and proper position sizing
**Understanding the AI Component:**
The AI auto-selection feature uses a fixed mathematical formula to rank DOLs. It does not:
- Predict where price will go
- Learn from past performance
- Adapt to market conditions
- Guarantee any level of accuracy
The confidence score represents the mathematical strength of a liquidity cluster based on objective factors (cluster size, recency, timeframe alignment), NOT a probability of the trade succeeding.
**Risk Warning:**
Trading is risky. Most traders lose money. This indicator cannot change that fundamental reality. Use it as an educational tool to understand market structure, not as a trading signal or system.
Technical Requirements
- **Timeframe:** Best used on 1-hour charts (required for accurate daily level tracking)
- **Markets:** Works on any market (forex, crypto, stocks, futures, indices)
- **Updates:** Real-time calculation on each bar close
- **Resources:** Uses max 500 lines and 500 labels (TradingView limits)
Backtesting Features
The indicator includes "Backtest Mode" to keep historical charts clean:
- When enabled, only shows labels from recent bars
- Adjustable lookback period (10-500 bars)
- All lines remain visible
- Helps review past setups without clutter
To use:
1. Enable "Backtest Mode" in settings
2. Adjust "Labels Lookback" to desired period
3. Review historical price action
4. Disable for live trading
Credits and Methodology
This indicator implements concepts from:
- ICT (Inner Circle Trader) liquidity theory
- Smart Money Concepts (SMC)
- Order flow analysis
- Multi-timeframe analysis principles
The clustering algorithm, confidence scoring, and timeframe synthesis are original implementations designed to quantify and visualize these concepts.
Version History
**v1.0 - Initial Release**
- Multi-timeframe DOL detection
- Confidence scoring system
- Info box with liquidity metrics
- Backtest mode for clean charts
- Black/white professional theme
Support and Updates
For questions, feedback, or suggestions, please use the TradingView comments section. Updates and improvements will be released as needed based on user feedback and market evolution.
**Remember:** This is an educational tool. Successful trading requires knowledge, discipline, risk management, and continuous learning. Use this indicator to enhance your understanding of market structure and liquidity, not as a standalone trading system.
Golden Cross 50/200 EMATrend-following systems are characterized by having a low win rate, yet in the right circumstances (trending markets and higher timeframes) they can deliver returns that even surpass those of systems with a high win rate.
Below, I show you a simple bullish trend-following system with clear execution rules:
System Rules
-Long entries when the 50-period EMA crosses above the 200-period EMA.
-Stop Loss (SL) placed at the lowest low of the 15 candles prior to the entry candle.
-Take Profit (TP) triggered when the 50-period EMA crosses below the 200-period EMA.
Risk Management
-Initial capital: $10,000
-Position size: 10% of capital per trade
-Commissions: 0.1% per trade
Important Note:
In the code, the stop loss is defined using the swing low (15 candles), but the position size is not adjusted based on the distance to the stop loss. In other words, 10% of the equity is risked on each trade, but the actual loss on the trade is not controlled by a maximum fixed percentage of the account — it depends entirely on the stop loss level. This means the loss on a single trade could be significantly higher or lower than 10% of the account equity, depending on volatility.
Implementing leverage or reducing position size based on volatility is something I haven’t been able to include in the code, but it would dramatically improve the system’s performance. It would fix a consistent percentage loss per trade, preventing losses from fluctuating wildly with changes in volatility.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to stop loss
And when volatility is high and would exceed the fixed percentage we want to expose per trade (if the SL is hit), we could reduce the position size accordingly.
Practical example:
Imagine we only want to risk 15% of the position value if the stop loss is triggered on Tesla (which has high volatility), but the distance to the SL represents a potential 23.57% drop. In this case, we subtract the desired risk (15%) from the actual volatility-based loss (23.57%):
23.57% − 15% = 8.57%
Now suppose we normally use $200 per trade.
To calculate 8.57% of $200:
200 × (8.57 / 100) = $17.14
Then subtract that amount from the original position size:
$200 − $17.14 = $182.86
In summary:
If we reduce the position size to $182.86 (instead of the usual $200), even if Tesla moves 23.57% against us and hits the stop loss, we would still only lose approximately 15% of the original $200 position — exactly the risk level we defined. This way, we strictly respect our risk management rules regardless of volatility swings.
I hope this clearly explains the importance of capping losses at a fixed percentage per trade. This keeps risk under control while maintaining a consistent percentage of capital invested per trade — preventing both statistical distortion of the system and the potential destruction of the account.
About the code:
Strategy declaration:
The strategy is named 'Golden Cross 50/200 EMA'.
overlay=true means it will be drawn directly on the price chart.
initial_capital=10000 sets the initial capital to $10,000.
default_qty_type=strategy.percent_of_equity and default_qty_value=10 means each trade uses 10% of available equity.
margin_long=0 indicates no margin is used for long positions (this is likely for simulation purposes only; in real trading, margin would be required).
commission_type=strategy.commission.percent and commission_value=0.1 sets a 0.1% commission per trade.
Indicators:
Calculates two EMAs: a 50-period EMA (ema50) and a 200-period EMA (ema200).
Crossover detection:
bullCross is triggered when the 50-period EMA crosses above the 200-period EMA (Golden Cross).
bearCross is triggered when the 50-period EMA crosses below the 200-period EMA (Death Cross).
Recent swing:
swingLow calculates the lowest low of the previous 15 periods.
Stop Loss:
entryStopLoss is a variable initialized as na (not available) and is updated to the current swingLow value whenever a bullCross occurs.
Entry and exit conditions:
Entry: When a bullCross occurs, the initial stop loss is set to the current swingLow and a long position is opened.
Exit on opposite signal: When a bearCross occurs, the long position is closed.
Exit on stop loss: If the price falls below entryStopLoss while a position is open, the position is closed.
Visualization:
Both EMAs are plotted (50-period in blue, 200-period in red).
Green triangles are plotted below the bar on a bullCross, and red triangles above the bar on a bearCross.
A horizontal orange line is drawn that shows the stop loss level whenever a position is open.
Alerts:
Alerts are created for:Long entry
Exit on bearish crossover (Death Cross)
Exit triggered by stop loss
Favorable Conditions:
Tesla (45-minute timeframe)
June 29, 2010 – November 17, 2025
Total net profit: $12,458.73 or +124.59%
Maximum drawdown: $1,210.40 or 8.29%
Total trades: 107
Winning trades: 27.10% (29/107)
Profit factor: 3.141
Tesla (1-hour timeframe)
June 29, 2010 – November 17, 2025
Total net profit: $7,681.83 or +76.82%
Maximum drawdown: $993.36 or 7.30%
Total trades: 75
Winning trades: 29.33% (22/75)
Profit factor: 3.157
Netflix (45-minute timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $11,380.73 or +113.81%
Maximum drawdown: $699.45 or 5.98%
Total trades: 134
Winning trades: 36.57% (49/134)
Profit factor: 2.885
Netflix (1-hour timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $11,689.05 or +116.89%
Maximum drawdown: $844.55 or 7.24%
Total trades: 107
Winning trades: 37.38% (40/107)
Profit factor: 2.915
Netflix (2-hour timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $12,807.71 or +128.10%
Maximum drawdown: $866.52 or 6.03%
Total trades: 56
Winning trades: 41.07% (23/56)
Profit factor: 3.891
Meta (45-minute timeframe)
May 18, 2012 – November 17, 2025
Total net profit: $2,370.02 or +23.70%
Maximum drawdown: $365.27 or 3.50%
Total trades: 83
Winning trades: 31.33% (26/83)
Profit factor: 2.419
Apple (45-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $8,232.55 or +80.59%
Maximum drawdown: $581.11 or 3.16%
Total trades: 140
Winning trades: 34.29% (48/140)
Profit factor: 3.009
Apple (1-hour timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $9,685.89 or +94.93%
Maximum drawdown: $374.69 or 2.26%
Total trades: 118
Winning trades: 35.59% (42/118)
Profit factor: 3.463
Apple (2-hour timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $8,001.28 or +77.99%
Maximum drawdown: $755.84 or 7.56%
Total trades: 67
Winning trades: 41.79% (28/67)
Profit factor: 3.825
NVDA (15-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $11,828.56 or +118.29%
Maximum drawdown: $1,275.43 or 8.06%
Total trades: 466
Winning trades: 28.11% (131/466)
Profit factor: 2.033
NVDA (30-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $12,203.21 or +122.03%
Maximum drawdown: $1,661.86 or 10.35%
Total trades: 245
Winning trades: 28.98% (71/245)
Profit factor: 2.291
NVDA (45-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $16,793.48 or +167.93%
Maximum drawdown: $1,458.81 or 8.40%
Total trades: 172
Winning trades: 33.14% (57/172)
Profit factor: 2.927
Major Crypto Relative Strength Portfolio System Majors RSPS - Relative Strength Portfolio System for Major Cryptocurrencies
Overview
Majors RSPS (Relative Strength Portfolio System) is an advanced portfolio allocation indicator that combines relative strength analysis, trend consensus, and macro risk factors to dynamically allocate capital across major cryptocurrency assets. The system leverages the NormalizedIndicators Library to evaluate both absolute trends and relative performance, creating an adaptive portfolio that automatically adjusts exposure based on market conditions.
This indicator is designed for portfolio managers, asset allocators, and systematic traders who want a data-driven approach to cryptocurrency portfolio construction with automatic rebalancing signals.
🎯 Core Concept
What is RSPS?
RSPS (Relative Strength Portfolio System) evaluates each asset on two key dimensions:
Relative Strength: How is the asset performing compared to other major cryptocurrencies?
Absolute Trend: Is the asset itself in a bullish trend?
Assets that show both strong relative performance AND positive absolute trends receive higher allocations. Weak performers are automatically filtered out, with capital reallocated to cash or stronger assets.
Dual-Layer Architecture
Layer 1: Majors Portfolio (Orange Zone)
Evaluates 14 major cryptocurrency assets
Calculates relative strength against all other majors
Applies trend filters to ensure absolute momentum
Dynamically allocates capital based on comparative strength
Layer 2: Cash/Risk Position (Navy Zone)
Evaluates macro risk factors and market conditions
Determines optimal cash allocation
Acts as a risk-off mechanism during adverse conditions
Provides downside protection through dynamic cash holdings
📊 Tracked Assets
Major Cryptocurrencies (14 Assets)
BTC - Bitcoin (Benchmark L1)
ETH - Ethereum (Smart Contract L1)
SOL - Solana (High-Performance L1)
SUI - Sui (Move-Based L1)
TRX - Tron (Payment-Focused L1)
BNB - Binance Coin (Exchange L1)
XRP - Ripple (Payment Network)
FTM - Fantom (DeFi L1)
CELO - Celo (Mobile-First L1)
TAO - Bittensor (AI Network)
HYPE - Hyperliquid (DeFi Exchange)
HBAR - Hedera (Enterprise L1)
ADA - Cardano (Research-Driven L1)
THETA - Theta (Video Network)
🔧 How It Works
Step 1: Relative Strength Calculation
For each asset, the system calculates relative strength by:
RSPS Score = Average of:
- Asset/BTC trend consensus
- Asset/ETH trend consensus
- Asset/SOL trend consensus
- Asset/SUI trend consensus
- ... (all 14 pairs)
- Asset's absolute trend consensus
Key Logic:
Each pair is evaluated using the eth_4d_cal() calibration from NormalizedIndicators
If an asset's absolute trend is extremely weak (≤ 0.1), it receives a penalty score (-0.5)
Otherwise, it gets the average of all its relative strength comparisons
Step 2: Trend Filtering
Assets must pass a trend filter to receive allocation:
Trend Score = Average of:
- Asset/BTC trend (filtered for positivity)
- Asset/ETH trend (filtered for positivity)
- Asset's absolute trend (filtered for positivity)
Only positive values contribute to the trend score, ensuring bearish assets don't receive allocation.
Step 3: Portfolio Allocation
Capital is allocated proportionally based on filtered RSPS scores:
Asset Allocation % = (Asset's Filtered RSPS Score / Sum of All Filtered Scores) × Main Portfolio %
Example:
SOL filtered score: 0.6
BTC filtered score: 0.4
All others: 0
Total: 1.0
SOL receives: (0.6 / 1.0) × Main% = 60% of main portfolio
BTC receives: (0.4 / 1.0) × Main% = 40% of main portfolio
Step 4: Cash/Risk Allocation
The system evaluates macro conditions across 6 factors:
Inverse Major Crypto Trends (40% weight)
When BTC, ETH, SOL, SUI, DOGE, etc. trend down → Cash allocation increases
Evaluates total market cap trends (TOTAL, TOTAL2, OTHERS)
Stablecoin Dominance (10% weight)
USDC dominance vs. major crypto dominances
Higher stablecoin dominance → Higher cash allocation
MVRV Ratios (10% weight)
BTC and ETH Market Value to Realized Value
High MVRV (overvaluation) → Higher cash allocation
BTC/ETH Ratio (15% weight)
Relative performance between two market leaders
Indicates market phase (BTC dominance vs. alt season)
Active Address Ratios (5% weight)
USDC active addresses vs. BTC/ETH active addresses
Network activity comparison
Macro Indicators (15% weight)
Global currency circulation (USD, EUR, CNY, JPY)
Treasury yield curve (10Y-2Y)
High yield spreads
Central bank balance sheets and money supply
Cash Allocation Formula:
Cash % = (Sum of Risk Factors × 0.5) / (Risk Factors + Majors TPI)
When risk factors are elevated, cash allocation increases, reducing exposure to volatile assets.
📈 Visual Components
Orange Zone (Majors Portfolio)
Fill: Light orange area showing aggregate portfolio strength
Line: Average trend power index (TPI) of allocated assets
Baseline: 0 level (neutral)
Interpretation:
Above 0: Bullish allocation environment
Rising: Strengthening portfolio momentum
Falling: Weakening portfolio momentum
Below 0: No allocation (100% cash)
Navy Zone (Cash Position)
Fill: Navy blue area showing cash allocation strength
Line: Risk-adjusted cash allocation signal
Baseline: 0 level
Interpretation:
Higher navy zone: Elevated risk-off signal → More cash
Lower navy zone: Risk-on environment → Less cash
Zero: No cash allocation (100% invested)
Performance Line (Orange/Blue)
Orange: Main portfolio allocation dominant (risk-on mode)
Blue: Cash allocation dominant (risk-off mode)
Tracks: Cumulative portfolio returns with dynamic rebalancing
Allocation Table (Bottom Left)
Shows real-time portfolio composition:
ColumnDescriptionAssetCryptocurrency nameRSPS ValuePercentage allocation (of main portfolio)CashDollar amount (if enabled)
Color Coding:
Orange: Active allocation
Gray: Weak signal (borderline)
Blue: Cash position
Missing: No allocation (filtered out)
⚙️ Settings & Configuration
Required Setup
Chart Symbol
MUST USE: INDEX:BTCUSD or similar major crypto index
Recommended Timeframe: 1D (Daily) or 4D (4-Day)
Why: System needs price data for all 14 majors, BTC provides stable reference
Hide Chart Candles
For clean visualization:
Right-click on chart
Select "Hide Symbol" or set candle opacity to 0
This allows the indicator fills and table to be clearly visible
User Inputs
plot_table (Default: true)
Enable/disable the allocation table
Set to false if you only want the visual zones
use_cash (Default: false)
Enable portfolio dollar value calculations
Shows actual dollar allocations per asset
cash (Default: 100)
Total portfolio size in dollars/currency units
Used when use_cash is enabled
Example: Set to 10000 for a $10,000 portfolio
💡 Interpretation Guide
Entry Signals
Strong Allocation Signal:
✓ Orange zone elevated (> 0.3)
✓ Navy zone low (< 0.2)
✓ Performance line orange
✓ Multiple assets in allocation table
→ Action: Deploy capital to allocated assets per table percentages
Risk-Off Signal:
✓ Orange zone near zero
✓ Navy zone elevated (> 0.4)
✓ Performance line blue
✓ Few or no assets in table (high cash %)
→ Action: Reduce exposure, increase cash holdings
Rebalancing Triggers
Monitor the allocation table for changes:
New assets appearing: Add to portfolio
Assets disappearing: Remove from portfolio
Percentage changes: Rebalance existing positions
Cash % changes: Adjust overall exposure
Market Regime Detection
Risk-On (Bull Market):
Orange zone high and rising
Navy zone minimal
Many assets allocated (8-12)
High individual allocations (15-30% each)
Risk-Off (Bear Market):
Orange zone near zero or negative
Navy zone elevated
Few assets allocated (0-3)
Cash allocation dominant (70-100%)
Transition Phase:
Both zones moderate
Medium number of assets (4-7)
Balanced cash/asset allocation (40-60%)
🎯 Trading Strategies
Strategy 1: Pure RSPS Following
1. Check allocation table daily
2. Rebalance portfolio to match percentages
3. Follow cash allocation strictly
4. Review weekly, act on significant changes (>5%)
Best For: Systematic portfolio managers, passive allocators
Strategy 2: Threshold-Based
Entry Rules:
- Orange zone > 0.4 AND Navy zone < 0.3
- At least 5 assets in allocation table
- Total non-cash allocation > 60%
Exit Rules:
- Orange zone < 0.1 OR Navy zone > 0.5
- Fewer than 3 assets allocated
- Cash allocation > 70%
Best For: Active traders wanting clear rules
Strategy 3: Relative Strength Overlay
1. Use RSPS for broad allocation framework
2. Within allocated assets, overweight top 3 performers
3. Scale position sizes by RSPS score
4. Use individual asset charts for entry/exit timing
Best For: Discretionary traders with portfolio focus
Strategy 4: Risk-Adjusted Position Sizing
For each allocated asset:
Position Size = Base Position × (Asset's RSPS Score / Max RSPS Score) × (1 - Cash Allocation)
Example:
- $10,000 portfolio
- SOL RSPS: 0.6 (highest)
- BTC RSPS: 0.4
- Cash allocation: 30%
SOL Size = $10,000 × (0.6/0.6) × (1-0.30) = $7,000
BTC Size = $10,000 × (0.4/0.6) × (1-0.30) = $4,667
Cash = $10,000 × 0.30 = $3,000
Best For: Risk-conscious allocators
📊 Advanced Usage
Multi-Timeframe Confirmation
Use on multiple timeframes for robust signals:
1D Chart: Tactical allocation (daily rebalancing)
4D Chart: Strategic allocation (weekly review)
Strong Confirmation:
- Both timeframes show same top 3 assets
- Both show similar cash allocation levels
- Orange zones aligned on both
Weak/Conflicting:
- Different top performers
- Diverging cash allocations
→ Wait for alignment or use shorter timeframe
Sector Rotation Analysis
Group assets by type and watch rotation:
L1 Dominance: BTC, ETH, SOL, SUI, ADA high → Layer 1 season
Alt L1s: TRX, FTM, CELO rising → Alternative platform season
Specialized: TAO, THETA, HYPE strong → Niche narrative season
Payment/Stable: XRP, BNB allocation → Risk reduction phase
Divergence Trading
Bullish Divergence:
Navy zone declining (less risk-off)
Orange zone flat or slightly rising
Few assets still allocated but strengthening
→ Early accumulation signal
Bearish Divergence:
Orange zone declining
Navy zone rising
Asset count decreasing in table
→ Distribution/exit signal
Performance Tracking
The performance line (overlay) shows cumulative strategy returns:
Compare to BTC/ETH: Is RSPS outperforming?
Drawdown analysis: How deep are pullbacks?
Correlation: Does it track market or provide diversification?
🔬 Technical Details
Data Sources
Price Data:
COINEX: Primary exchange for alt data
CRYPTO: Alternative price feeds
INDEX: Aggregated index prices (recommended for BTC)
Macro Data:
Dominance metrics (SUI.D, BTC.D, etc.)
MVRV ratios (on-chain valuation)
Active addresses (network activity)
Global money supply and macro indicators
Calculation Methodology
RSPS Scoring:
For each asset, calculate 14 relative trends (vs. all others)
Calculate asset's absolute trend
Average all 15 values
Apply penalty filter for extremely weak trends (≤ 0.1)
Trend Consensus:
Uses eth_4d_cal() from NormalizedIndicators library
Combines 8 normalized indicators per measurement
Returns value from -1 (bearish) to +1 (bullish)
Performance Calculation:
Daily Return = Σ(Asset ROC × Asset Allocation)
Cumulative Performance = Previous Perf × (1 + Daily Return / 100)
Assumes perfect rebalancing and no slippage (theoretical performance).
Filtering Logic
filter() function:
pinescriptfilter(input) => input >= 0 ? input : 0
This zero-floor filter ensures:
Only positive trend values contribute to allocation
Bearish assets receive 0 weight
No short positions or inverse allocations
Anti-Manipulation Safeguards
Null Handling:
All values wrapped in nz() to handle missing data
Prevents calculation errors from data gaps
Normalization:
Allocations always sum to 100%
Prevents over/under-allocation
Conditional Logic:
Assets need positive values on multiple metrics
Single metric cannot drive allocation alone
⚠️ Important Considerations
Required Timeframes
1D (Daily): Recommended for most users
4D (4-Day): More stable, fewer rebalances
Other timeframes: Use at your own discretion, may require recalibration
Data Requirements
Needs INDEX:BTCUSD or equivalent major crypto symbol
All 14 tracked assets must have available data
Macro indicators require specific TradingView data feeds
Rebalancing Frequency
System provides daily allocation updates
Practical rebalancing: Weekly or on significant changes (>10%)
Consider transaction costs and tax implications
Performance Notes
Theoretical returns: No slippage, fees, or execution delays
Backtest carefully: Validate on your specific market conditions
Past performance: Does not guarantee future results
Risk Warnings
⚠️ High Concentration Risk: May allocate heavily to 1-3 assets
⚠️ Volatility: Crypto markets are inherently volatile
⚠️ Liquidity: Some allocated assets may have lower liquidity
⚠️ Correlation: All assets correlated to BTC/ETH to some degree
⚠️ System Risk: Relies on continued availability of data feeds
Not Financial Advice
This indicator is a tool for analysis and research. It does not constitute:
Investment advice
Portfolio management services
Trading recommendations
Guaranteed returns
Always perform your own due diligence and risk assessment.
🎓 Use Cases
For Portfolio Managers
Systematic allocation framework
Objective rebalancing signals
Risk-adjusted exposure management
Performance tracking vs. benchmarks
For Active Traders
Identify strongest assets to focus trading on
Gauge overall market regime (risk-on/off)
Time entry/exit for portfolio shifts
Complement technical analysis with allocation data
For Institutional Allocators
Quantitative portfolio construction
Multi-asset exposure optimization
Drawdown management through cash allocation
Compliance-friendly systematic approach
For Researchers
Study relative strength dynamics in crypto markets
Analyze correlation between majors
Test macro factor impact on crypto allocations
Develop derived strategies and signals
🔧 Setup Checklist
✅ Chart Configuration
Set chart to INDEX:BTCUSD
Set timeframe to 1D or 4D
Hide chart candles for clean visualization
Add indicator from library
✅ Indicator Settings
Enable plot_table (see allocation table)
Set use_cash if tracking dollar amounts
Input your portfolio size in cash parameter
✅ Monitoring Setup
Bookmark chart for daily review
Set alerts for major allocation changes (optional)
Create spreadsheet to track allocations (optional)
Establish rebalancing schedule (weekly recommended)
✅ Validation
Verify all 14 assets appear in table (when allocated)
Check that percentages sum to ~100%
Confirm performance line is tracking
Test cash allocation calculation if enabled
📋 Quick Reference
Signal Interpretation
ConditionOrange ZoneNavy ZoneActionStrong BullHigh (>0.4)Low (<0.2)Full allocationModerate BullMid (0.2-0.4)Low-MidStandard allocationNeutralLow (0.1-0.2)Mid (0.3-0.4)Balanced allocationModerate BearVery Low (<0.1)Mid-HighReduce exposureStrong BearZero/NegativeHigh (>0.5)High cash/exit
Rebalancing Thresholds
Change TypeThresholdActionIndividual asset±5%Consider rebalanceIndividual asset±10%Strongly rebalanceCash allocation±10%Adjust exposureAsset entry/exitAnyAdd/remove position
Color Legend
Orange: Main portfolio strength/allocation
Navy: Cash/risk-off allocation
Blue text: Cash position in table
Orange text: Active asset allocation
Gray text: Weak/borderline allocation
White: Headers and labels
🚀 Getting Started
Beginner Path
Add indicator to INDEX:BTCUSD daily chart
Hide candles for clarity
Enable plot_table to see allocations
Check table daily, note top 3-5 assets
Start with small allocation, observe behavior
Gradually increase allocation as you gain confidence
Intermediate Path
Set up on both 1D and 4D charts
Enable use_cash with your portfolio size
Create tracking spreadsheet
Implement weekly rebalancing schedule
Monitor divergences between timeframes
Compare performance to buy-and-hold BTC
Advanced Path
Modify code to add/remove tracked assets
Adjust relative strength calculation methodology
Customize cash allocation factors and weights
Integrate with portfolio management platform
Develop algorithmic rebalancing system
Create alerts for specific allocation conditions
📖 Additional Resources
Related Indicators
NormalizedIndicators Library: Core calculation engine
Individual asset trend indicators for deeper analysis
Macro indicator dashboards for cash allocation factors
Complementary Analysis
On-chain metrics (MVRV, active addresses, etc.)
Order book liquidity for execution planning
Correlation matrices for diversification analysis
Volatility indicators for position sizing
Learning Materials
Study relative strength portfolio theory
Research tactical asset allocation strategies
Understand crypto market cycles and phases
Learn about risk management in volatile assets
🎯 Key Takeaways
✅ Systematic allocation across 14 major cryptocurrencies
✅ Dual-layer approach: Asset selection + Cash management
✅ Relative strength focused: Invests in comparatively strong assets
✅ Trend filtering: Only allocates to assets in positive trends
✅ Dynamic rebalancing: Automatically adjusts to market conditions
✅ Risk-managed: Increases cash during adverse conditions
✅ Transparent methodology: Clear calculation logic
✅ Practical visualization: Easy-to-read table and zones
✅ Performance tracking: See cumulative strategy returns
✅ Highly customizable: Adjust assets, weights, and factors
📋 License
This code is subject to the Mozilla Public License 2.0 at mozilla.org
Majors RSPS transforms complex multi-asset portfolio management into a systematic, data-driven process. By combining relative strength analysis with trend consensus and macro risk factors, it provides traders and portfolio managers with a robust framework for navigating cryptocurrency markets with discipline and objectivity.WiederholenClaude kann Fehler machen. Bitte überprüfen Sie die Antworten. Sonnet 4.5
Price Drop CounterThe Price Drop Counter is a very basic statistical indicator.
See it as an analytical tool that tracks how many times an asset's price has dropped by a specified percentage from its recent peak within a defined date range.
The indicator monitors the highest price reached and counts each occurrence when the price falls by your chosen threshold, then resets its peak tracking point after each drop is registered.
Uses
Volatility Assessment: Measure how frequently significant price corrections occur during specific periods
Market Behavior Analysis: Compare drop frequency across different timeframes or market conditions
Risk Evaluation: Identify assets or periods with higher downside volatility
Historical Pattern Recognition: Study how often major pullbacks happened during bull or bear markets
Backtesting Support: Analyze how your strategy would perform based on the frequency of drawdowns
How to use it
Add the indicator to your TradingView chart
Configure the Percent Drop (%) to define your threshold (default: 10%). The indicator will count each time price falls by this percentage from the most recent high
IMPORTANT Set your Start Date and End Date to analyze a specific period of interest
The blue step-line plot shows the cumulative count of drops within your date range
Adjust the percentage threshold based on your analysis needs - use smaller values (2-5%) for more frequent signals or larger values (15-20%) for major corrections only
The counter resets its high-water mark after each qualifying drop, allowing it to track multiple sequential drops within the same period.
Rendement périodes (finary compass)Rendement sur une période donnée,
Outil de décision pour stratégie Momentum
Net Liquidity (WALCL - TGA - ON RRP)//@version=5
indicator("Net Liquidity (WALCL - TGA - ON RRP)", overlay=false, timeframe="W")
a = request.security("FRED:WALCL", "W", close) // Fed total assets (millions)
b = request.security("FRED:WTREGEN", "W", close) // TGA (millions)
c = request.security("FRED:RRPONTSYD","W", close) // ON RRP (millions)
netliq = (a - b - c) / 1000.0 // billions
plot(netliq, color=color.new(color.blue, 0), linewidth=2)
Expsoure Guide by Tradewith_GaryDaily Guide for exposure building. Use this Indicator to improve your profitability by avoiding over-trading and picking the best days to initiate new trades. Valid only for swing trading format.
