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:
Indicators and strategies
Paulinho Signals โ Cripto 5m/15m com Filtro de LateralidadeThis script is an automated Pine Script v6 strategy designed for short-term cryptocurrency trading, especially on 5-minute and 15-minute timeframes. It combines moving average crossovers, trend strength (ADX), volatility (ATR), and candlestick patterns to generate buy and sell signals with a fixed risk/reward management system.
How to Use:
- Apply to cryptocurrency charts on 5m or 15m timeframes.
- Adjust parameters to fit your preferences (EMA, RSI, ADX, ATR).
- Use for backtesting or as a decision-support tool.
Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Always test on demo accounts before applying to live trading.
Vital Wave 20-50Simplicity is almost always the most effective approach, and here Iโm giving you a trend-following system that exploits the bullish bias of traditional markets and their trending nature, with very basic rules.
Rules (long entries only)
โข Market entry: When the EMA 20 crosses above the EMA 50 (from below)
โข Main market exit: When the EMA 20 crosses below the EMA 50 (from above)
โข Fixed Stop Loss: Placed at the price level of the Lower Bollinger Band at the moment the trade is entered.
In my strategy, the primary exit is when the EMA 20 crosses below the EMA 50. However, this crossover can sometimes take a while to occur, and in the meantime the price may have already dropped significantly. The Stop Loss based on the Lower Bollinger Band is designed to limit losses in case the market moves sharply against the position without giving the bearish crossover signal in time. Having two exit conditions makes the strategy much more robust in terms of risk management.
Risk Management:
โข Initial capital: $10,000
โข Position size: 10% of available capital per trade
โข Commissions: 0.1% on traded volume
โข Stop Loss: Based on the Lower Bollinger Band
โข Take Profit / Exit: When EMA 20 crosses below EMA 50
Recommended Markets:
XAUUSD (OANDA) (Daily)
Period: January 3, 1833 โ November 23, 2025
Total Profit & Loss: +$6,030.62 USD (+57.57%)
Maximum Drawdown: $541.53 USD (3.83%)
Total Trades: 136
Winning Trades (Win Rate): 36.03% (49/136)
Profit Factor: 2.483
XAUUSD (OANDA) (12-hour)
Period: March 19, 2006 โ November 23, 2025
Total Profit & Loss: +$1,209.56 USD (+11.89%)
Maximum Drawdown: $384.58 USD (3.61%)
Total Trades: 97
Winning Trades (Win Rate): 35.05% (34/97)
Profit Factor: 1.676
XAUUSD (OANDA) (8-hour)
Period: March 19, 2006 โ November 23, 2025
Total Profit & Loss: +$1,179.36 USD (+11.81%)
Maximum Drawdown: $246.88 USD (2.32%)
Total Trades: 147
Winning Trades (Win Rate): 31.97% (47/147)
Profit Factor: 1.626
Tesla (NASDAQ) (4-hour)
Period: June 29, 2010 โ November 23, 2025
Total Profit & Loss (Absolute): +$11,687.90 USD (+116.88%)
Maximum Drawdown: $922.05 USD (6.50%)
Total Trades: 68
Winning Trades (Win Rate): 39.71% (27/68)
Profit Factor: 4.156
Tesla (NASDAQ) (3-hour)
Total Profit & Loss: +$11,522.33 USD (+115.22%)
Maximum Drawdown: $1,247.60 USD (8.80%)
Total Trades: 114
Winning Trades: 33.33% (38/114)
Profit Factor: 2.811
Additional Recommendations
(These assets have shown good trending behavior with the same strategy across multiple timeframes):
โข NVDA (15 min, 30 min, 1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
โข NFLX (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
โข MA (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
โข META (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
โข AAPL (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
โข SPY (12h, Daily)
About the Code
The user can modify:
โข EMA periods (20 and 50 by default)
โข Bollinger Bands length (20 periods)
โข Standard deviation (2.0)
Visualization
โข EMA 20: Blue line
โข EMA 50: Red line
โข Green background when EMA20 > EMA50 (bullish trend)
โข Red background when EMA20 < EMA50 (bearish trend)
Important Note:
We can significantly increase the profit factor and overall profitability by risking a fixed percentage per trade instead of a fixed amount. This would prevent losses from fluctuating with changes in volatility.
This could be implemented by reducing position size or adjusting leverage based on the volatility percentage required for each trade, but Iโm not sure if this is fully possible in Pine Script. In my other script, โ Golden Cross 50/200 EMA ,โ I go deeper into this topic and provide examples.
I hope you enjoy this contribution. Best regards!
MTF Scalper - alemicihanMulti-Timeframe Scalper Strategy: Aligning the Big Picture for Quick Gains
This article presents a robust futures trading strategy designed for high-frequency scalping in the crypto market. Itโs built on the principle of minimizing risk by ensuring that short-term entries are always aligned with the dominant, higher-timeframe trend.
The Core Concept: Alignment is Key
A Balanced Trend Follower approach, now refined for rapid scalping, uses a Multi-Timeframe (MTF) confirmation system to filter out market noise and increase the probability of a successful trade.
The strategy operates on a Low Timeframe (LTF) chart (e.g., 3m, 5m, or 15m) but only executes trades if the direction is validated by three Higher Timeframes (HTF).
ComponentPurposeFunctionHTF (D, 4h, 1h) EMA => Trend Confirmation =>Checks if the current price is above/below all three Exponential Moving Averages (EMA 20). This provides a strong directional bias.
LTF (5m) Stochastic RSI => Momentum Entry => Generates the actual buy/sell signal by spotting a swift crossover, indicating fresh momentum in the direction of the confirmed HTF trend.
How The Signal Is Generated
Trend Alignment: The system first confirms the trend. If the price is trading above the Daily, 4-Hour, and 1-Hour EMAs, the market is deemed to be in a Strong LONG Trend. Only LONG signals are permitted.
Momentum Trigger: Once the trend is confirmed, a Long Signal is generated only when the Stochastic K-Line crosses above the D-Line, indicating a momentum shift (a pullback ending) towards the main trend direction.
Short Signal: The inverse logic applies to the Short Trend confirmation and entry signal.
Mandatory Risk Management: ATR-Based Exit
Given the high leverage nature of futures and scalping, static Stop-Loss (SL) and Take-Profit (TP) levels are inefficient. This strategy uses the Average True Range (ATR) indicator to dynamically set profit and loss targets based on current market volatility.
Stop Loss (SL): Set dynamically at 1.5 x ATR below (for long) or above (for short) the entry price. This gives the trade enough room to breathe without risking excessive capital.
Take Profit (TP): Set dynamically at 3.0 x ATR, establishing a robust Risk-to-Reward Ratio of 1:2.
Final Thoughts on Testing
This sophisticated approach combines the reliability of MTF analysis with the speed of momentum indicators. However, data analysis is key. Backtesting these parameters (EMA, ATR Multipliers, RSI/Stochastic lengths) on your chosen asset (like BTC/USDT or ETH/USDT) and timeframe is crucial to achieving optimal performance.
Hull VWMA Crossover StrategyA simple variation on the Hull Moving Average which reacts faster to high volume events, making it more responsive in those cases than even the standard Hull average -- CREDIT GOES TO Saolof - -- Edited into a strategy with some more options that im going to continue to refine. LMK if theres any features or confluence you want me to add -- cheers!
BTC Risk Metric DCA Adapter (3Commas Webhook Strategy)Risk Metric DCA Adapter (3Commas Webhook Strategy) - WORK IN PROGRESS
This Pine Script strategy, originally inspired by the Risk Metric Indicator, is fundamentally engineered as an Adapter to interface with external trading bots like 3Commas via Webhooks. It calculates a dynamic market risk score and translates that score into specific dollar-cost averaging (DCA) entry levels and tiered profit-taking exits.
Key Features & Logic
Risk Metric Calculation (Credit to The Trading Parrot):
The strategy incorporates a complex, multi-timeframe Risk Metric calculation based on daily and weekly moving averages (SMA) and standard deviation (StDev). This metric aims to quantify the current market overextension or compression relative to long-term historical data. The resulting score dictates the level of conviction for a new trade.
Tiered DCA Entry Sizing:
The strategy defines three distinct Buy Levels (L1, L2, L3) corresponding to increasingly favorable (lower) Risk Metric scores.
L1 (Base): Risk is moderate, initiating the minimum defined trade amount.
L2 (Scaled): Risk is low, initiating L1 amount + L2 amount.
L3 (Aggressive): Risk is very low, initiating L1 + L2 + L3 amounts.
Tiered Profit-Taking Exits:
The strategy implements a staggered, partial profit-taking approach based on the Risk Metric rising:
Sell L1 & L2: Closes a percentage of the current position when the Risk Metric reaches defined high thresholds, locking in partial profits.
Sell L3 (Full Exit): Closes the remaining position when the Risk Metric reaches the highest defined threshold.
The Adapter Function (Webhook Integration)
This script is unique because it uses the Pine Script strategy() function to trigger Order Fills, which are necessary to access powerful placeholders in the TradingView alert system.
Trigger Type: The alert must be set to trigger on Any order fill.
Dynamic Webhook Data: Instead of using fixed alert() commands, the strategy generates dynamic labels (e.g., BUY_ENTRY_L3_USD_1000 or SELL_L1_PCT_25) using the strategy.entry and strategy.close commands.
Data Transfer: The alert message then uses the placeholder {{strategy.order.comment}} to pass these dynamic labels to the 3Commas bot, allowing the bot to execute the precise action (e.g., start_deal_with_volume_in_quote_currency or close_deal_at_market_percentage).
Full Strategy Webhook payload
{
"secret": "YOUR_3COMMAS_SECRET_KEY",
"max_lag": "300",
"timestamp": "{{timenow}}",
"trigger_price": "{{close}}",
"tv_exchange": "{{exchange}}",
"tv_instrument": "{{ticker}}",
"action": "{{strategy.order.action}}",
"bot_uuid": "YOUR_BOT_UUID",
"strategy_info": {
"market_position": "{{strategy.market_position}}",
"market_position_size": "{{strategy.market_position_size}}",
"prev_market_position": "{{strategy.prev_market_position}}",
"prev_market_position_size": "{{strategy.prev_market_position_size}}"
},
"order": {
"amount": "{{strategy.order.contracts}}",
"currency_type": "base",
"comment": "{{strategy.order.comment}}"
}
}
Disclaimer: This script is an adapter tool and does not guarantee profit. Trading requires manual configuration of risk settings, bot parameters, and adherence to platform-specific setup instructions.
HPAS mean reversion strategy testerTakes Krown HPAS values hardcoded and simulates longs and short with configurable standard deviation multiplier TP/SL. Best used on lower timeframes
RSI + 55 EMA + Volume (SL Marked, No Engulfing)This is to help entering in trades by considering 50 EMA and RSI indicators, Volume is used for confirmations
ParabolicSAR+EMA[TS_Indie]๐ EMA + Parabolic SAR Reversal Trading Strategy
This trading system effectively combines the use of Exponential Moving Averages (EMA) with the Parabolic SAR to identify both price trends and key reversal points. The EMA Fast is used to signal the primary short-term trend, while the EMA Slow acts as a filter for the long-term trend direction. The Parabolic SAR then helps to confirm the reversal signals.
๐ ๏ธ Tools Used
1. EMA Fast โ Primary Short-Term Trend
2. EMA Slow โ Long-Term Trend Filter
3. Parabolic SAR โ Reversal Confirmation
๐ฏ Entry Rules
๐ Buy Setup
1. Trend Filter: EMA Fast > EMA Slow โ Uptrend
2. Pullback: Price pulls back and closes below the EMA Fast line.
3. Reversal: Price reverses/pulls back up and closes above the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is above the high, and the dot in the current candle is below the low โ Reversal signal confirmed.
5. Entry: Enter Buy immediately.
๐ Sell Setup
1. Trend Filter: EMA Fast < EMA Slow โ Downtrend
2. Pullback: Price pulls back and closes above the EMA Fast line.
3. Reversal: Price reverses/pulls back down and closes below the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is below the low, and the dot in the current candle is above the high โ Reversal signal confirmed.
5. Entry: Enter Sell immediately.
๐ฐ Exit Management (Entry, Stop Loss, Take Profit)
1. Entry: Enter the order at the closing price of the signal candle.
2. Stop Loss (SL): Set the Stop Loss at the Parabolic SAR dot.
3. Take Profit (TP): Calculated from the Entry and Stop Loss points, multiplied by the Risk Reward Ratio.
โ๏ธ Optional Parameters
โญ Custom Risk/Reward Ratio for Take Profit.
โญ Option to add an ATR buffer to the Stop Loss.
โญ Adjustable EMA Fast period.
โญ Adjustable EMA Slow period.
โญ Adjustable Parabolic SAR parameters.
โญ Option to enable Long-only / Short-only positions.
โญ Customizable Backtest start and end date.
โญ Customizable trading session time.
๐ Alert Function
Alerts display:
โญ Entry Price
โญ Stop Loss Price
โญ Take Profit Price
๐ก This strategy allows for many parameter adjustments, such as the MA type, adding/subtracting from the Stop Loss using ATR, and selecting specific sessions for backtesting. If you find interesting or profitable results after adjusting the parameters, please share your comments with other traders!
โ ๏ธ Disclaimer
This indicator is designed for educational and research purposes only. It does not guarantee profits and should not be considered financial advice. Trading in financial markets involves significant risk , including the potential loss of capital.
Simple MA Crossover w/ SLTPPicture two cheetahs on a racetrack made of price candles. One cheetah is fast and twitchy (the short-term EMA). The other is chill, lumbering, and takes its sweet time (the long-term EMA). When the twitchy cheetah sprints ahead and crosses above the chill one โ โBUY, YOU MAGNIFICENT DEGEN!โ When the twitchy one gets tired, slows down, and gets lapped from above โ โSELL before this turns into a horror movie!โ
That, my friend, is the EMA crossover strategy in its purest, most dramatic form.
ATH๋๋น ์ง์ ํ๋ฝ๋ฅ ์ ๋์ฐฉ ์ ๋งค์ - ์ฅ๊ธฐํ๋ฉ ์ ๋ฌผ ์ ๋ต(ATH Drawdown Re-Buy Long Only)๋ณธ ์คํฌ๋ฆฝํธ๋ ๊ณผ๊ฑฐ ํ๋ฝ ๋ฐ์ดํฐ๋ฅผ ์ด์ฉํ์ฌ, ์ ํด์ง ํ๋ฝ %๊ฐ ๋ฐ์ํ๋ ๊ฒฝ์ฐ ์๊ธฐ ์๋ณธ์ ์ ํด์ง %๋งํผ์ ์ง์
ํ๊ฒ ์ค๊ณ๋์ด์ง ์คํธ๋ ํฐ์ง์
๋๋ค.
๋ ๋ฒ๋ฆฌ์ง๋ฅผ ์ฌ์ฉํ ์ ์์ผ๋ฉฐ ๊ธฐ๋ณธ์ ์ผ๋ก ์
ํ
ํด๋ ๊ฐ์ด ๋ด์ฅ๋์ด์์ต๋๋ค.(์์ ๋กญ๊ฒ ๋ฐ๊ฟ์ ์ฐ์๋ฉด ๋ฉ๋๋ค.) ์ถ๊ฐ์ ์ผ๋ก 2๋ฒ์ ์ง์
์ธ์๋ ๋ค๋ฅธ ์ง์
๊ธฐ์ค, ์ง์
%๋ฅผ ์ค์ ํ์ค ์ ์์ผ๋ฉฐ - ChatGPT์๊ฒ ์์ฒญํ๋ฉด ์์ ํด์ค ๊ฒ์
๋๋ค.
์ค์ ์ฌ์ฉ์ฉ๋๋ก๋ KillSwitch ๊ธฐ๋ฅ์ ๊บผ์ฃผ์ธ์. ๋ฐ ๋๋ณด๊ธฐ ๊ธฐ๋ฅ์ ์ผ์ฃผ์ธ์.
ATH Drawdown Re-Buy Long Only ์ ๋ต ์ค๋ช
1. ์ ๋ต ๊ฐ์
ATH Drawdown Re-Buy Long Only ์ ๋ต์ ์์ฐ์ ์ญ๋ ์ต๊ณ ๊ฐ(ATH, All-Time High)๋ฅผ ๊ธฐ์ค์ผ๋ก ํ ํ๋ฝํญ(๋๋ก์ฐ๋ค์ด)์ ํ์ฉํ์ฌ,
ํน์ ๊ตฌ๊ฐ๋ง๋ค ๋จ๊ณ์ ์ผ๋ก ๋กฑ ํฌ์ง์
์ ๊ตฌ์ถํ๋ ์๋ ์ฌ๋งค์(Long Only) ์ ๋ต์
๋๋ค.
๋ณธ ์ ๋ต์ ๋ค์๊ณผ ๊ฐ์ ๋ชฉ์ ์ ๊ฐ์ง๊ณ ์ค๊ณ๋์์ต๋๋ค.
๊ธ๊ฒฉํ ์กฐ์ ๊ตฌ๊ฐ์์ ์ฒด๊ณ์ ์ธ ๋ถํ ๋งค์ ๋ฐ ๋ ๋ฒ๋ฆฌ์ง ํ์ฉ
ATH๋ฅผ ๊ธฐ์ค์ผ๋ก ํ ๋ช
ํํ ์ง์
๊ท์น ์ ๊ณต
์ค์๊ฐ์ผ๋ก
ํ๋จ๊ฐ
๋ ๋ฒ๋ฆฌ์ง
์ฒญ์ฐ๊ฐ ์ถ์
๊ณ์ข MDD
์์ต๋ฅ
๋ฑ์ ์๊ฐ์ ์ผ๋ก ์ ๊ณตํ์ฌ ๋ฆฌ์คํฌ์ ํฌ์ง์
์ํ๋ฅผ ์ง๊ด์ ์ผ๋ก ํ์ธํ ์ ์๋๋ก ์ง์
โป ๋ณธ ์ ๋ต์ ๊ต์กยท์ฐ๊ตฌยท๋ฐฑํ
์คํธ ์ฉ๋๋ก ์ ๊ณต๋๋ฉฐ,
์ด๋ ํ ํํ์ ํฌ์ ๊ถ์ ๋๋ ์์ต์ ๋ณด์ฅํ์ง ์์ต๋๋ค.
2. ์ ๋ต์ ํต์ฌ ๊ฐ๋
2-1. ATH(์ญ๋ ์ต๊ณ ๊ฐ) ๊ธฐ์ค ๋๋ก์ฐ๋ค์ด
์ ๋ต์ ์ฐจํธ ์์์ ํญ์ ๊ฐ์ฅ ๋์ ๊ณ ๊ฐ(High)๋ฅผ ATH๋ก ๊ธฐ๋กํฉ๋๋ค.
์๋ก์ด ๊ณ ์ ์ด ํ์ฑ๋ ๋๋ง๋ค ATH๋ฅผ ๊ฐฑ์ ํ๊ณ , ํด๋น ATH๋ฅผ ๊ธฐ์ค์ผ๋ก ๋ค์์ ๊ณ์ฐํฉ๋๋ค.
ํ์ฌ ๋ฐ์ ์ ๊ฐ(Low)๊ฐ ATH์์ ๋ช % ํ๋ฝํ๋์ง
ํ์ฌ ๋ฐ์ ์ข
๊ฐ(Close)๊ฐ ATH์์ ๋ช % ํ๋ฝํ๋์ง
๊ทธ๋ฆฌ๊ณ ์ฌ์ ์ ์ค์ ํ ๋ ๊ฐ์ ๋๋ก์ฐ๋ค์ด ๊ตฌ๊ฐ์์ ๋งค์๋ฅผ ์ํํฉ๋๋ค.
1์ฐจ ์ง์
๊ตฌ๊ฐ: ATH ๋๋น X% ํ๋ฝ ์
2์ฐจ ์ง์
๊ตฌ๊ฐ: ATH ๋๋น Y% ํ๋ฝ ์
๊ฐ ๊ตฌ๊ฐ์ ATH๊ฐ ์๋ก ๊ฐฑ์ ๋ ๋๋ง๋ค ํ ๋ฒ์ฉ๋ง ์๋ํ๋ฉฐ,
์๋ก์ด ATH๊ฐ ์์ฑ๋๋ฉด ๋ค์ โ1์ฐจ / 2์ฐจ ์ง์
๊ฐ๋ฅ ์ํโ๋ก ์ด๊ธฐํ๋ฉ๋๋ค.
2-2. ์ฒซ ํฌ์ง์
100% / 300% ํน์ ๊ท์น
์ด ์ ๋ต์ ์ค์ํ ํน์ง์ **โ์ฒซ ํฌ์ง์
์ง์
์์ ์์ธ ๊ท์นโ**์
๋๋ค.
์ ๋ต์ด ํ์ฌ ์ด๋ ํ ํฌ์ง์
๋ ๋ค๊ณ ์์ง ์์ ์ํ์์
์ต์ด๋ก ๋กฑ ํฌ์ง์
์ ์ง์
ํ๋ ์์ (์ฒซ ํฌ์ง์
)์ ๋ํด:
๊ธฐ๋ณธ์ ์ผ๋ก๋ **์์ฐ์ 100%**๋ฅผ ๊ธฐ์ค์ผ๋ก ํฌ์ง์
์ ๊ตฌ์ถํ์ง๋ง,
๋ง์ฝ ๊ทธ ์๊ฐ์ ๊ฐ๊ฒฉ์ด ATH ๋๋น ์ค์ ๊ฐ ์ด์(์: ์ฝ โ72.5% ์ด์ ํ๋ฝํ ์ํฉ) ์ด๋ผ๋ฉด
โ ์์ฐ์ 300% ๊ท๋ชจ๋ก ์ฒซ ํฌ์ง์
์ ์ง์
ํ๋๋ก ์ค๊ณ๋์ด ์์ต๋๋ค.
์ด ๊ท์น์ ๋ค์๊ณผ ๊ฐ์ด ๋์ํฉ๋๋ค.
์ฒซ ์ง์
์ด 1์ฐจ ๋๋ก์ฐ๋ค์ด ๊ตฌ๊ฐ์์ ๋ฐ์ํ๋ ,
์ฒซ ์ง์
์ด 2์ฐจ ๋๋ก์ฐ๋ค์ด ๊ตฌ๊ฐ์์ ๋ฐ์ํ๋ ,
ํ์ฌ ํ๋ฝํญ์ด ์ค์ ๋ ๊ธฐ์ค ์ด์(์: โ72.5% ์ด์) ์ด๋ผ๋ฉด
โ โ์ด ์ ๋ ํ๋ฝ์ด๋ฉด ์ฒซ ์ง์
๋ถํฐ ๋ ๊ณต๊ฒฉ์ ์ผ๋ก ๋ค์ด๊ฐ๋คโ๋ ์๋ฏธ๋ก 300% ๊ท๋ชจ๋ก ์ง์
๊ทธ ์ดํ์ ํ๋ฝํญ์ด๋ผ๋ฉด
โ ์ฒซ ์ง์
์ 100% ๊ท๋ชจ๋ก ์ ํ
์ฆ, ์ ๋ต์ ๋ค์ ๋ ๊ฐ์ง ๋ชจ๋๋ก ๋์ํฉ๋๋ค.
์ผ๋ฐ์ ์ธ ์ํฉ์ ์ฒซ ์ง์
: ์์ฐ์ 100%
์ฌ๊ฐํ ๋๋ก์ฐ๋ค์ด ๊ตฌ๊ฐ์์์ ์ฒซ ์ง์
: ์์ฐ์ 300%
์ด ํน์ ๊ท์น์ ๊น์ ํ๋ฝ์์๋ ๊ณต๊ฒฉ์ ์ผ๋ก, ํ์์๋ ์๋์ ์ผ๋ก ๋ณด์์ ์ผ๋ก ์ง์
ํ๋๋ก ์ค๊ณ๋ ๊ฒ์
๋๋ค.
3. ์ ๋ต ๋์ ๊ตฌ์กฐ
3-1. ๋งค์ ์กฐ๊ฑด
์ฐจํธ ์ High ๊ธฐ์ค์ผ๋ก ATH๋ฅผ ์ถ์ ํฉ๋๋ค.
๊ฐ ๋ฐ๋ง๋ค ํด๋น ATH์์์ ํ๋ฝ๋ฅ ์ ๊ณ์ฐํฉ๋๋ค.
์ฌ์ฉ์๊ฐ ์ค์ ํ ๋ ๊ฐ์ ๋๋ก์ฐ๋ค์ด ๊ตฌ๊ฐ(์์):
1์ฐจ ๊ตฌ๊ฐ: ์๋ฅผ ๋ค์ด ATH โ 50%
2์ฐจ ๊ตฌ๊ฐ: ์๋ฅผ ๋ค์ด ATH โ 72.5%
๊ฐ ๊ตฌ๊ฐ์ ๋ํด ๋ค์๊ณผ ๊ฐ์ ์กฐ๊ฑด์ ํ์ธํฉ๋๋ค.
โ์ด๋ฒ ATH ๊ตฌ๊ฐ์์ ์์ง ํด๋น ๊ตฌ๊ฐ ๋งค์๋ฅผ ํ ์ ์ด ์๋ ์ํโ์ด๊ณ ,
ํ์ฌ ๋ฐ์ ์ ๊ฐ(Low)๊ฐ ํด๋น ๊ตฌ๊ฐ ๊ฐ๊ฒฉ ์ดํ๋ฅผ ์ฐ๋ ์๊ฐ
โ ํด๋น ๋ฐ์์ ๋งค์ ์กฐ๊ฑด ์ถฉ์กฑ์ผ๋ก ๊ฐ์ฃผ
์ค์ ์ฃผ๋ฌธ์:
ํด๋น ๊ตฌ๊ฐ ๊ฐ๊ฒฉ์ ๋ง์ถฐ ๋กฑ ํฌ์ง์
์ง์
(๋ฆฌ๋ฐ/์์ฅ๊ฐ ๊ธฐ๋ฐ ์๋ฎฌ๋ ์ด์
) ์ผ๋ก ์ฒ๋ฆฌ๋ฉ๋๋ค.
3-2. ATH ๊ฐฑ์ ๊ณผ ์ง์
๊ธฐํ ๋ฆฌ์
์ฐจํธ ์์์ ์๋ก์ด ๊ณ ์ (High)์ด ๊ธฐ์กด ATH๋ฅผ ๋์ด์๋ ์๊ฐ,
ATH๊ฐ ๊ฐฑ์ ๋๊ณ ,
1์ฐจ / 2์ฐจ ์ง์
์ฌ๋ถ๋ฅผ ๋ํ๋ด๋ ๋ด๋ถ ํ๋๊ทธ๊ฐ ์ด๊ธฐํ๋ฉ๋๋ค.
์ด๋ฅผ ํตํด, ์์ฅ์ด ์๋ก์ด ๊ณ ์ ์ ๋ํํด ๋๊ฐ ๋๋ง๋ค,
ํด๋น ๊ตฌ๊ฐ์์ ๋ค์ ํ ๋ฒ์ฉ 1์ฐจยท2์ฐจ ๋๋ก์ฐ๋ค์ด ์ง์
๊ธฐํ๋ฅผ ๊ฐ๊ฒ ๋ฉ๋๋ค.
4. ํฌ์ง์
์ฌ์ด์ง ๋ฐ ๋ ๋ฒ๋ฆฌ์ง
4-1. ๊ณ์ข ์์ฐ(Equity) ๊ธฐ์ค ํฌ์ง์
ํฌ๊ธฐ ๊ฒฐ์
์ ๋ต์ ํ์ฌ ๊ณ์ข ์์ฐ์ ๋ค์๊ณผ ๊ฐ์ด ์ ์ํ์ฌ ์ฌ์ฉํฉ๋๋ค.
ํ์ฌ ์์ฐ = ์ด๊ธฐ ์๋ณธ + ์คํ ์์ต + ๋ฏธ์คํ ์์ต
๊ฐ ์ง์
๊ตฌ๊ฐ์์์ ํฌ์ง์
๊ฐ์น๋ ๋ค์๊ณผ ๊ฐ์ด ๊ฒฐ์ ๋ฉ๋๋ค.
1์ฐจ ์ง์
๊ตฌ๊ฐ:
โ์์ฐ์ ๋ช %๋ฅผ ์ฌ์ฉํ ์งโ๋ฅผ ์ค์ ๊ฐ์ผ๋ก ์
๋ ฅ
์ค์ ๋ ํผ์ผํธ๋ฅผ ๊ณ์ข ์์ฐ์ ๊ณฑํ ๋ค,
๋ค์ ์ ๋ต ๋ด ๋ ๋ฒ๋ฆฌ์ง ๋ฐฐ์(Leverage) ๋ฅผ ๊ณฑํ์ฌ ์ค์ ํฌ์ง์
๊ฐ์น๋ฅผ ๊ณ์ฐ
2์ฐจ ์ง์
๊ตฌ๊ฐ:
๋์ผํ ๋ฐฉ์์ผ๋ก, ๋
๋ฆฝ๋ ํผ์ผํธ ์ค์ ๊ฐ์ ์ฌ์ฉ
์ฆ, ํฌ์ง์
๊ฐ์น๋ ๋ค์๊ณผ ๊ฐ์ด ๊ณ์ฐ๋ฉ๋๋ค.
ํฌ์ง์
๊ฐ์น = ํ์ฌ ์์ฐ ร (ํด๋น ๊ตฌ๊ฐ ์ค์ % / 100) ร ๋ ๋ฒ๋ฆฌ์ง ๋ฐฐ์
๊ทธ๋ฆฌ๊ณ ์ด๋ฅผ ํด๋น ๊ตฌ๊ฐ์ ์ง์
๊ฐ๊ฒฉ์ผ๋ก ๋๋์ด ์ค์ ์๋(ํ ํฐ ๋จ์) ๋ฅผ ์ฐ์ถํฉ๋๋ค.
4-2. ์ฒซ ํฌ์ง์
์ ์์ธ ์ฒ๋ฆฌ (100% / 300%)
์ฒซ ํฌ์ง์
์ ๋ํด์๋ ์์ ์ผ๋ฐ์ ์ธ ํผ์ผํธ ์ค์ ๋์ ,
๋ค์๊ณผ ๊ฐ์ ๊ณ ์ ๋น์จ์ด ์ฌ์ฉ๋ฉ๋๋ค.
๊ธฐ๋ณธ: ์์ฐ์ 100% ๊ท๋ชจ๋ก ์ฒซ ํฌ์ง์
์ง์
๋จ, ์ง์
์์ ์ ATH ๋๋น ํ๋ฝ๋ฅ ์ด ์ค์ ๊ฐ ์ด์(์: โ72.5% ์ด์) ์ผ ๊ฒฝ์ฐ
โ ์์ฐ์ 300% ๊ท๋ชจ๋ก ์ฒซ ํฌ์ง์
์ง์
์ด๋ ์ญ์ ๋ค์ ๊ณต์์ ์ฌ์ฉํฉ๋๋ค.
ํฌ์ง์
๊ฐ์น = ํ์ฌ ์์ฐ ร (100% ๋๋ 300%) ร ๋ ๋ฒ๋ฆฌ์ง
๊ทธ๋ฆฌ๊ณ ์ด๋ฅผ ๊ฐ๊ฒฉ์ผ๋ก ๋๋์ด ์ค์ ์ง์
์๋์ ๊ณ์ฐํฉ๋๋ค.
์ด ๊ท์น์:
์ฒซ ์ง์
์ด 1์ฐจ ๊ตฌ๊ฐ์ด๋ 2์ฐจ ๊ตฌ๊ฐ์ด๋ ๋์ผํ๊ฒ ์ ์ฉ๋๋ฉฐ,
โ์ถฉ๋ถํ ๊น์ ํ๋ฝ ๊ตฌ๊ฐ์์๋ ์ฒซ ์ง์
๋ถํฐ ๋ ํฌ๊ฒ,
ํ์์๋ ๋น๊ต์ ๋ณด์์ ์ผ๋กโ ๋ผ๋ ์ด์ฉ ์ฒ ํ์ ๋ฐ์ํฉ๋๋ค.
4-3. ์ค๋ ๋ฒ๋ฆฌ์ง(Real Leverage)์ ์ถ์
์ ๋ต์ ๊ฐ ๋ฐ ๋จ์๋ก ๋ค์์ ์ถ์ ํฉ๋๋ค.
๋ฐ๊ฐ ์์ํ ๋์ ๊ธฐ์กด ํฌ์ง์
ํฌ๊ธฐ
ํด๋น ๋ฐ์์ ์๋ก ์ง์
ํ ์๋
์ด๋ฅผ ๋ฐํ์ผ๋ก, ์ง์
์ด ๋ฐ์ํ ์์ ์ ๋ค์์ ๊ณ์ฐํฉ๋๋ค.
์ค์ ๋ ๋ฒ๋ฆฌ์ง = (ํฌ์ง์
๊ฐ์น / ํ์ฌ ์์ฐ)
๊ทธ๋ฆฌ๊ณ ์ฐจํธ ์์ ์๋ฅผ ๋ค์ด:
Lev 2.53x ์ ๊ฐ์ ํ์์ ๋ ์ด๋ธ๋ก ํ์ํฉ๋๋ค.
์ด๋ฅผ ํตํด, ๋งค์ ์์ ๋ง๋ค ์ค์ ๊ณ์ข ๋ ๋ฒ๋ฆฌ์ง๊ฐ ์ด๋ ์ ๋์๋์ง๋ฅผ ์ง๊ด์ ์ผ๋ก ํ์ธํ ์ ์์ต๋๋ค.
5. ์๊ฐํ ๋ฐ ๋ชจ๋ํฐ๋ง ์์
5-1. ์ฐจํธ ์ ์๊ฐ ์์
์ ๋ต์ ์ฐจํธ ์์ ๋ค์๊ณผ ๊ฐ์ ์ ๋ณด๋ฅผ ์ง์ ํ์ํฉ๋๋ค.
ATH ๋ผ์ธ
High ๊ธฐ์ค์ผ๋ก ๊ณ์ฐ๋ ์ญ๋ ์ต๊ณ ๊ฐ๋ฅผ ์ฃผํฉ์ ์ ์ผ๋ก ํ์
ํ๋จ๊ฐ(ํ๊ท ์ง์
๊ฐ) ๋ผ์ธ
ํ์ฌ ๋ณด์ ํฌ์ง์
์ด ์์ ๋,
ํด๋น ํฌ์ง์
์ ํ๊ท ์ง์
๊ฐ๋ฅผ ๋
ธ๋์ ์ ์ผ๋ก ํ์
์ถ์ ์ฒญ์ฐ๊ฐ(๊ณ ์ ํ ์ฒญ์ฐ๊ฐ) ๋ผ์ธ
ํฌ์ง์
์๋์ด ๋ณํํ๋ ์์ ์ ๊ฐ์งํ์ฌ,
๋น์์ ํ๋จ๊ฐ์ ์ค์ ๋ ๋ฒ๋ฆฌ์ง๋ฅผ ์ด์ฉํด ๊ทผ์ฌ์ ์ธ ์ฒญ์ฐ๊ฐ๋ฅผ ๊ณ์ฐ
์ด๋ฅผ ๋นจ๊ฐ์ ์ ์ผ๋ก ์ฐจํธ์ ๊ณ ์ ํ์
ํฌ์ง์
์ด ์๊ฑฐ๋ ๋ ๋ฒ๋ฆฌ์ง๊ฐ 1๋ฐฐ ์ดํ์ธ ๊ฒฝ์ฐ์๋ ์ฒญ์ฐ๊ฐ ๋ผ์ธ์ ์ ๊ฑฐ
๋งค์ ๋ง์ปค ๋ฐ ๋ ์ด๋ธ
1์ฐจ/2์ฐจ ๋งค์ ์กฐ๊ฑด์ด ์ถฉ์กฑ๋ ๋๋ง๋ค ํด๋น ์ง์ ์ ๋งค์ ๋ง์ปค๋ฅผ ํ์
"Buy XX% @ ๊ฐ๊ฒฉ", "Lev XXx" ํํ์ ๋ผ๋ฒจ๋ก
์ง์
๋น์จ๊ณผ ๋น์ ๋ ๋ฒ๋ฆฌ์ง๋ฅผ ํจ๊ป ์๊ฐํ
๋ ์ด๋ธ์ ์์น๋ ์ค์ ์์ ์ ํ ๊ฐ๋ฅ:
๋ฐ ์๋ (Below Bar)
๋ฐ ์ (Above Bar)
์ค์ ๊ฐ๊ฒฉ ์์น (At Price)
5-2. ์ฐ์ธก ์๋จ ์ ๋ณด ํ
์ด๋ธ
์ฐจํธ ์ฐ์ธก ์๋จ์๋ ํ์ฌ ๊ณ์ขยทํฌ์ง์
์ํ๋ฅผ ์์ฝํ ์ ๋ณด ํ
์ด๋ธ์ด ํ์๋ฉ๋๋ค.
๋ํ์ ์ผ๋ก ๋ค์ ํญ๋ชฉ๋ค์ด ํฌํจ๋ฉ๋๋ค.
Pos Qty (Token)
ํ์ฌ ๋ณด์ ์ค์ธ ํฌ์ง์
์๋(ํ ํฐ ๊ธฐ์ค, ์ ๋๊ฐ ๊ธฐ์ค)
Pos Value (USDT)
ํ์ฌ ํฌ์ง์
์ ์์ฅ ๊ฐ์น (์๋ ร ํ์ฌ ๊ฐ๊ฒฉ)
Leverage (Now)
ํ์ฌ ์ค๋ ๋ฒ๋ฆฌ์ง (ํฌ์ง์
๊ฐ์น / ํ์ฌ ์์ฐ)
DD from ATH (%)
ํ์ฌ ๊ฐ๊ฒฉ ๊ธฐ์ค, ์ต๊ทผ ATH์์์ ํ๋ฝ๋ฅ (%)
Avg Entry
ํ์ฌ ํฌ์ง์
์ ํ๊ท ์ง์
๊ฐ๊ฒฉ
PnL (%)
ํ์ฌ ํฌ์ง์
๊ธฐ์ค ๋ฏธ์คํ ์์ต๋ฅ (%)
Max DD (Equity %)
์ ๋ต ์ ์ฒด ๊ธฐ๊ฐ ๋์ ๊ธฐ๋ก๋ ๊ณ์ข ๊ธฐ์ค ์ต๋ ์์ค(MDD, Max Drawdown)
Last Entry Price
๊ฐ์ฅ ์ต๊ทผ์ ํฌ์ง์
์ ์ถ๊ฐ๋ก ์ง์
ํ ์งํ์ ํ๊ท ์ง์
๊ฐ๊ฒฉ
Last Entry Lev
์ โLast Entry Priceโ ์์ ์์์ ์ค๋ ๋ฒ๋ฆฌ์ง
Liq Price (Fixed)
์์์ ์ค๋ช
ํ ๊ณ ์ ํ ์ถ์ ์ฒญ์ฐ๊ฐ
Return from Start (%)
์ ๋ต ์์ ์์ (์ด๊ธฐ ์๋ณธ) ๋๋น ํ์ฌ ๊ณ์ข ์์ฐ์ ์ด ์์ต๋ฅ (%)
์ด ํ
์ด๋ธ์ ํตํด ์ฌ์ฉ์๋:
ํ์ฌ ๊ณ์ข์ ํฌ์ง์
์ ์ํ
๋ฆฌ์คํฌ ์์ค
๋์ ์ฑ๊ณผ
๋ฅผ ์ง๊ด์ ์ผ๋ก ํ์
ํ ์ ์์ต๋๋ค.
6. ์๊ฐ ํํฐ ๋ฐ ๋ผ๋ฒจ ์ต์
6-1. ์ ๋ต ๋์ ๊ธฐ๊ฐ ์ค์
์ ๋ต์ ์ต์
์ผ๋ก ํน์ ๊ธฐ๊ฐ์๋ง ์ ๋ต์ ๋์์ํค๋ ์๊ฐ ํํฐ๋ฅผ ์ ๊ณตํฉ๋๋ค.
โUse Date Rangeโ ์ต์
์ ํ์ฑํํ๋ฉด:
์์ ์๊ฐ๊ณผ ์ข
๋ฃ ์๊ฐ์ ์ง์ ํ์ฌ
ํด๋น ๊ตฌ๊ฐ์ ํํด์๋ง ๋งค๋งค๊ฐ ๋ฐ์ํ๋๋ก ์ ํ
์ต์
์ ๋นํ์ฑํํ๋ฉด:
์ ๋ต์ ์ ์ฒด ์ฐจํธ ๊ตฌ๊ฐ์์ ์์ ๋กญ๊ฒ ๋์
6-2. ์ง์
๋ผ๋ฒจ ์์น ์ค์
์ฌ์ฉ์๋ ๋งค์/๋ ๋ฒ๋ฆฌ์ง ๋ผ๋ฒจ์ ์์น๋ฅผ ์ ํํ ์ ์์ต๋๋ค.
๋ฐ ์๋ (Below Bar)
๋ฐ ์ (Above Bar)
์ค์ ๊ฐ๊ฒฉ ์์น (At Price)
์ด๋ฅผ ํตํด ๊ฐ์ธ ์ทจํฅ ๋ฐ ์ฐจํธ ๊ฐ๋
์ฑ์ ๋ง์ถ์ด
์๊ฐํ ๋ฐฉ์์ ์ ์ฐํ๊ฒ ์กฐ์ ํ ์ ์์ต๋๋ค.
7. ํ์ฉ ๋์ ๋ฐ ์ฌ์ฉ ์์
๋ณธ ์ ๋ต์ ๋ค์๊ณผ ๊ฐ์ ๋ชฉ์ ์ ์ ํฉํฉ๋๋ค.
ํ๋ฌผ ๋๋ ์ ๋ฌผ ๋กฑ ํฌ์ง์
๊ธฐ์ค ์ฅ๊ธฐยท์ค์ ๊ด์ ์ถ๋งค ์ ๋ต ๋ฐฑํ
์คํธ
โ๊ณ ์ ๋๋น ํ๋ฝ๋ฅ โ์ ๊ธฐ์ค์ผ๋ก ํ ๊ท์น ๊ธฐ๋ฐ ์ด์ฉ ์์ด๋์ด ๊ฒ์ฆ
๋ ๋ฒ๋ฆฌ์ง ์ฌ์ฉ ์
๊ณ์ข ๋ ๋ฒ๋ฆฌ์งยท์ฒญ์ฐ๊ฐยทMDD๋ฅผ ๋์์ ๋ชจ๋ํฐ๋งํ๊ณ ์ ํ๋ ๊ฒฝ์ฐ
ํน์ ์์ฐ์ ๋ํด
โ์๋ก์ด ๊ณ ์ ์ด ํ์ฑ๋ ๋๋ง๋ค
์ผ์ ํ ๊ท์น์ผ๋ก ๊น์ ์กฐ์ ๊ตฌ๊ฐ์์๋ง ๋ถํ ์ง์
ํ๊ณ ์ ํ ๋โ
์ค๊ฑฐ๋์ ๊ทธ๋๋ก ์ ์ฉํ๊ธฐ๋ณด๋ค๋,
์ ๋ต ์์ด๋์ด ๊ฒ์ฆ ๋ฐ ๋ฆฌ์คํฌ ํ๋กํ์ผ ๋ถ์,
์์ ์ ์ฑํฅ์ ๋ง๋ ํ๋ผ๋ฏธํฐ ํ์ ์ฉ๋๋ก ์ฌ์ฉํ๋ ๊ฒ์ ๊ถ์ฅํฉ๋๋ค.
8. ํ๊ณ ๋ฐ ์ ์์ฌํญ
๋ฐฑํ
์คํธ ๊ฒฐ๊ณผ๋ ๋ฏธ๋ ์ฑ๊ณผ๋ฅผ ๋ณด์ฅํ์ง ์์ต๋๋ค.
๊ณผ๊ฑฐ ๋ฐ์ดํฐ์ ๊ธฐ๋ฐํ ์๋ฎฌ๋ ์ด์
์ผ ๋ฟ์ด๋ฉฐ,
์ค์ ์์ฅ์์๋
์ ๋์ฑ
์ฌ๋ฆฌํผ์ง
์์๋ฃ ์ฒด๊ณ
๊ฐ์ ์ฒญ์ฐ ๊ท์น
๋ฑ ๋ค์ํ ๋ณ์๊ฐ ์กด์ฌํฉ๋๋ค.
์ฒญ์ฐ๊ฐ๋ ๋จ์ํ๋ ๊ณต์์ ๋ฐ๋ฅธ ์ถ์ ์น์
๋๋ค.
๊ฑฐ๋์๋ณ ์ค์ ์ฒญ์ฐ ๊ท์น, ์ ์ง ์ฆ๊ฑฐ๊ธ, ์์๋ฃ, ํ๋ฉ๋น ๋ฑ์
๋ณธ ์ ๋ต์ ๊ณ์ฐ๊ณผ ๋ค๋ฅผ ์ ์์ผ๋ฉฐ,
์ฒญ์ฐ๊ฐ ์ถ์ ๋ผ์ธ์ ์ฐธ๊ณ ์ฉ ์งํ์ผ ๋ฟ์
๋๋ค.
๋ ๋ฒ๋ฆฌ์ง ๋ฐ ์ง์
๋น์จ ์ค์ ์ ๋ฐ๋ผ ์์ค ํญ์ด ๋งค์ฐ ์ปค์ง ์ ์์ต๋๋ค.
ํนํ **โ์ฒซ ํฌ์ง์
300% ์ง์
โ**๊ณผ ๊ฐ์ด ๋งค์ฐ ๊ณต๊ฒฉ์ ์ธ ์ค์ ์
์์ฅ ๊ธ๋ฝ ์ ๊ณ์ข ์์ค๊ณผ ์ฒญ์ฐ ๋ฆฌ์คํฌ๋ฅผ ํฌ๊ฒ ์ฆ๊ฐ์ํฌ ์ ์์ผ๋ฏ๋ก
์ ์คํ ๊ฒํ ๊ฐ ํ์ํฉ๋๋ค.
์ค๊ฑฐ๋ ์ฐ๋ ์์๋ ๋ณ๋์ ๋ฆฌ์คํฌ ๊ด๋ฆฌ๊ฐ ํ์์
๋๋ค.
๊ฐ๋ณ ์์ ๊ธฐ์ค
ํฌ์ง์
์ํ์
์ ์ฒด ํฌํธํด๋ฆฌ์ค ๋ด ๋น์ค ๊ด๋ฆฌ ๋ฑ
๋ณธ ์ ๋ต ์ธ๋ถ์์ ์ถ๊ฐ์ ์ธ ์์ ์ฅ์น๊ฐ ํ์ํฉ๋๋ค.
9. ๊ฒฐ๋ก
ATH Drawdown Re-Buy Long Only ์ ๋ต์ ๋จ์ํ โ์ ๊ฐ ๋งค์โ๋ฅผ ๋์ด์,
ATH ๊ธฐ์ค์ผ๋ก ๋๋ก์ฐ๋ค์ด์ ๊ตฌ์กฐ์ ์ผ๋ก ํ์ฉํ๊ณ ,
์ฒซ ํฌ์ง์
์ ๋ํ **ํน์ ๊ท์น(100% / 300%)**์ ์ ์ฉํ๋ฉฐ,
๋ ๋ฒ๋ฆฌ์งยท์ฒญ์ฐ๊ฐยทMDDยท์์ต๋ฅ ์ ํตํฉ์ ์ผ๋ก ์๊ฐํํจ์ผ๋ก์จ,
ํ๋ฝ ๊ตฌ๊ฐ์์์ ๊ท์น ๊ธฐ๋ฐ ๋กฑ ํฌ์ง์
๊ตฌ์ถ๊ณผ
๋ฆฌ์คํฌ ๋ชจ๋ํฐ๋ง์ ๋์์ ์ง์ํ๋ ์ ๋ต์
๋๋ค.
์ฌ์ฉ์๋ ๋ณธ ์ ๋ต์ ํตํด:
์์ ์ ์์ฅ ๊ด์ ๊ณผ ๋ฆฌ์คํฌ ํ์ฉ ๋ฒ์์ ๋ง๋
๋๋ก์ฐ๋ค์ด ๊ตฌ๊ฐ
์ง์
๋น์จ
๋ ๋ฒ๋ฆฌ์ง ์ค์
๋ค์ํ ์๋๋ฆฌ์ค์ ๋ํ ๋ฐฑํ
์คํธ์ ๋ถ์
์ ์ํํ ์ ์์ต๋๋ค.
๋ค์ ํ ๋ฒ ๊ฐ์กฐํ์ง๋ง,
๋ณธ ์ ๋ต์ ์ฐ๊ตฌยทํ์ตยท๋ฐฑํ
์คํธ๋ฅผ ์ํ ๋๊ตฌ์ด๋ฉฐ,
์ค์ ํฌ์ ํ๋จ๊ณผ ์ฑ
์์ ์ ์ ์ผ๋ก ์ฌ์ฉ์ ๋ณธ์ธ์๊ฒ ์์ต๋๋ค.
/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 โ 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 assetโs 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.
โป 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 barโs Low is below the ATH
How many percent the current barโs 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 โ1st / 2nd entry possibleโ 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 โ72.5% or more),
โ 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. โ72.5% or worse),
โ the strategy interprets this as โa sufficiently deep crashโ and opens the initial position with 300% of equity.
If the drawdown is less severe than the threshold,
โ 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 โ 50%
2nd zone: ATH โ 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 barโs Low touches or falls below that zoneโs price level,
โ That bar is considered to have triggered a buy condition.
Order simulation:
The strategy simulates entering a long position at that zoneโs 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:
โWhat % of equity to use at this zoneโ
The strategy:
Multiplies current equity by that percentage
Then multiplies by the strategyโs leverage factor
Thus:
Position Value = Current Equity ร (Zone % / 100) ร 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. โ72.5% or more)
โ Enter the first position with 300% of equity.
The position value is computed as:
Position Value = Current Equity ร (100% or 300%) ร 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:
โIn very deep crashes, go much larger on the first entry; otherwise, stay more conservative.โ
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 โfixed liquidation priceโ 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 ร 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 โUse Date Rangeโ 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 โdrawdown from ATHโ as a main signal
Monitoring account leverage, liquidation price, and MDD when using leverage
Handling situations where, for a given asset:
โEvery time a new ATH is formed,
you want to wait for deep corrections and enter only at specific drawdown zonesโ
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 โfirst position 300% of equityโ 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 โbuy the dipโ 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.
Risk-Managed StrategyRisk-Managed Strategy is a complete algorithmic trading framework that blends multiple technical systemsโRSI, MACD, EMA crossover, Bollinger Bands, and SuperTrendโinto a unified signal engine.
The script dynamically calculates position size based on capital, risk percentage, ATR-based stop loss, and reward-ratio targets.
It features:
-Multi-indicator signal voting (BUY / SELL / NEUTRAL)
- Dynamic capital tracking across trades
- Automatic position sizing based on risk amount
- Auto-generated Stop Loss and Take Profit using recent highs/lows
- On-chart SL, TP, and CMP plotting for clarity
This strategy is designed for traders who want a professional, rule-based system that balances accuracy, risk control, and automation.
Disclaimer:
The information provided is for educational and informational purposes only. It does not constitute financial or investment advice. Trading and investing in stocks involves risk, including the possible loss of capital. Any decisions to buy, sell, or hold securities are the sole responsibility of the reader. Past performance is not indicative of future results. Always do your own research and, if necessary, consult with a licensed financial advisor before making investment decisions.
CNN Fear and Greed StrategyAdaptation of the CNN Fear and Greed Index Indicator (Original by EdgeTools)
The following changes have been implemented:
Put/Call Ratio Data Source: The data source for the Put/Call Ratio has been updated.
Bond Data Source: The data sources for the bond components (Safe Haven Demand and Junk Bond Demand) have been updated.
Normalization Adjustment: The normalization method has been adjusted to allow the CNN Fear and Greed Index to display over a longer historical period, optimizing it for backtesting purposes.
Style Modification: The display style has been modified for a simpler and cleaner appearance.
Strategy Logic Addition: Added a new strategy entry condition: index >= 25 AND index crosses over its 5-period Simple Moving Average (SMA), and a corresponding exit condition of holding the position for 252 bars (days).
CNN Fear & Greed Backtest Strategy (Adapted)
This script is an adaptation of the popular CNN Fear & Greed Index, originally created by EdgeTools, with significant modifications to optimize it for long-term backtesting on the TradingView platform.
The core function of the Fear & Greed Index is to measure the current emotional state of the stock market, ranging from 0 (Extreme Fear) to 100 (Extreme Greed). It operates on the principle that excessive fear drives prices too low (a potential buying opportunity), and excessive greed drives them too high (a potential selling opportunity).
Key Components of the Index (7 Factors)
The composite index is calculated as a weighted average of seven market indicators, each normalized to a score between 0 and 100:
Market Momentum: S&P 500's current level vs. its 125-day Moving Average.
Stock Price Strength: Stocks hitting 52-week highs vs. those hitting 52-week lows.
Stock Price Breadth: Measured by the McClellan Volume Summation Index (or similar volume/breadth metric).
Put/Call Ratio: The relationship between volume of put options (bearish bets) and call options (bullish bets).
Market Volatility: The CBOE VIX Index relative to its 50-day Moving Average.
Safe Haven Demand: The relative performance of stocks (S&P 500) vs. bonds.
Junk Bond Demand: The spread between high-yield (junk) bonds and U.S. Treasury yields.
Critical Adaptations for Backtesting
To improve the index's utility for quantitative analysis, the following changes were made:
Long-Term Normalization: The original normalization method (ta.stdev over a short LENGTH) has been replaced or adjusted to use longer historical data. This change ensures the index generates consistent and comparable sentiment scores across decades of market history, which is crucial for reliable backtesting results.
Updated Data Sources: Specific ticker requests for the Put/Call Ratio and Bond components (Safe Haven and Junk Bond Demand) have been updated to use the most reliable and long-running data available on TradingView, reducing data gaps and improving chart continuity.
Simplified Visuals: The chart display is streamlined, focusing only on the final Fear & Greed Index line and key threshold levels (25, 50, 75) for quick visual assessment.
Integrated Trading Strategy
This script also includes a simple, rules-based strategy designed to test the counter-trend philosophy of the index:
Entry Logic (Long Position): A long position is initiated when the market shows increasing fear, specifically when the index score is less than or equal to the configurable FEAR_LEVEL (default 25) and the index crosses above its own short-term 5-period Simple Moving Average (SMA). This crossover acts as a confirmation that sentiment may be starting to turn around from peak fear.
Exit Logic (Time-Based): All positions are subject to a time-based exit after holding for 252 trading days (approximately one year). This fixed holding period aims to capture the typical duration of a cyclical market recovery following a major panic event.
VIX Counter-Trend StrategyVIX Panic Index VOO Bottom-Fishing Strategy
๐ Strategy Overview
This strategy utilizes the VIX (Volatility Index) as a market sentiment indicator to help investors rationally enter positions during periods of extreme market panic, using objective technical signals to avoid emotional decision-making. It is designed to capture rebound opportunities in VOO (or other US equity ETFs) following panic-driven selloffs.
๐ฏ Entry and Exit Conditions
Entry Conditions (both must be met):
VIX reaches or exceeds the set threshold (default 25, adjustable)
VIX death crosses below its moving average (default 5-day MA), confirming panic sentiment is beginning to recede
Exit Conditions (three modes available):
Holding Period Mode: Exit after holding for the set number of days (default 100 days)
VIX Decline Mode: Exit when VIX falls below the set threshold (default 20)
Either Condition Mode: Exit when either condition is met
โ ๏ธ Important Warnings
Not Suitable for Leveraged ETF Bottom-Fishing: VIX reflects market volatility. Using leveraged ETFs (such as TQQQ, SOXL) increases risk due to decay effects and greater volatility, potentially causing larger losses during panic periods.
Bear Market Inaccuracy Risk: This strategy assumes markets will rebound from panic. However, during prolonged bear markets or systemic risks (such as the 2008 financial crisis or 2022 rate hike cycle), VIX may remain elevated for extended periods, triggering multiple buy signals while prices continue declining, rendering the strategy ineffective.
Recommended to Combine with Market Trend Analysis: Works better in bull market conditions. In bear markets, consider raising VIX thresholds or suspending use.
For Reference Only, Not Investment Advice: Historical performance does not guarantee future results. Please use cautiously according to your personal risk tolerance.
VIX ๆๆ
ๆๆธ VOO ๆๅบ็ญ็ฅ
๐ ็ญ็ฅ็ฎ็
ๆฌ็ญ็ฅๅฉ็จ VIX ๆๆ
ๆๆธไฝ็บๅธๅ ดๆ
็ทๆๆจ๏ผๅนซๅฉๆ่ณไบบๅจๅธๅ ดๆฅตๅบฆๆๆ
ๆ็ๆง้ฒๅ ดๆๅบ๏ผไธฆ้้ๅฎข่ง็ๆ่ก่จ่้ฟๅ
ๆ
็ทๅๆไฝใ้ฉๅ็จๆผๆๆ VOO๏ผๆๅ
ถไป็พ่ก ETF๏ผๅจๆๆ
ๆงไธ่ทๅพ็ๅๅฝๆฉๆใ
๐ฏ ้ฒๅบๅ ดๆขไปถ
้ฒๅ ดๆขไปถ๏ผๅๆๆปฟ่ถณ๏ผ๏ผ
VIX ๆๆธ้ๅฐ่จญๅฎ้ๆชปไปฅไธ๏ผ้ ่จญ 25๏ผๅฏ่ชฟๆด๏ผ
VIX ๆญปไบกไบคๅๅ
ถๅ็ท๏ผ้ ่จญ 5 ๆฅๅ็ท๏ผ๏ผ็ขบ่ชๆๆ
ๆ
็ท้ๅงๅ่ฝ
ๅบๅ ดๆขไปถ๏ผไธ็จฎๆจกๅผๅฏ้ธ๏ผ๏ผ
ๆๆๅคฉๆธๆจกๅผ๏ผๆๆ้ๅฐ่จญๅฎๅคฉๆธๅพๅบๅ ด๏ผ้ ่จญ 100 ๅคฉ๏ผ
VIX ๅ่ฝๆจกๅผ๏ผVIX ้่ณ่จญๅฎ้ๆชปไปฅไธๆๅบๅ ด๏ผ้ ่จญ 20๏ผ
ๅ
ฉ่
็ๅฏๆจกๅผ๏ผไปปไธๆขไปถๆปฟ่ถณๅณๅบๅ ด
โ ๏ธ ้่ฆ่ญฆ่ช
ไธ้ฉๅๆงๆกฟๅ ETF ๆๅบ๏ผVIX ๅๆ ็ๆฏๅธๅ ดๆณขๅๅบฆ๏ผไฝฟ็จๆงๆกฟ ETF๏ผๅฆ TQQQใSOXL๏ผๆๅ ็บ่กฐๆธๆๆๅๆดๅคงๆณขๅ่ๅขๅ ้ขจ้ช๏ผๅฏ่ฝๅจๆๆ
ๆ้้ ๆๆดๅคง่งๆใ
็ฉบ้ ญๅธๅ ดๅคฑๆบ้ขจ้ช๏ผๆฌ็ญ็ฅๅ่จญๅธๅ ดๆๅพๆๆ
ไธญๅๅฝ๏ผไฝๅจ้ทๆ็ฉบ้ ญๆ็ณป็ตฑๆง้ขจ้ช๏ผๅฆ 2008 ้่ๅฑๆฉใ2022 ๅๆฏๅพช็ฐ๏ผไธญ๏ผVIX ๅฏ่ฝ้ทๆ่ๆผ้ซๆช๏ผๅคๆฌก่งธ็ผ่ฒทๅ
ฅ่จ่ๅปๆ็บไธ่ท๏ผๅฐ่ด็ญ็ฅๅคฑๆใ
ๅปบ่ญฐๆญ้
ๅคง็ค่ถจๅขๅคๆท๏ผๅจๅค้ ญๆ ผๅฑไธญไฝฟ็จๆๆ่ผไฝณ๏ผ็ฉบ้ ญๆ ผๅฑๅปบ่ญฐๆ้ซ VIX ้ๆชปๆๆซๅไฝฟ็จใ
ๅ
ไพๅ่๏ผ้ๆ่ณๅปบ่ญฐ๏ผๆญทๅฒ็ธพๆไธไปฃ่กจๆชไพ่กจ็พ๏ผ่ซไพๅไบบ้ขจ้ชๆฟๅๅบฆ่ฌนๆ
ไฝฟ็จใ
Macketings 1min ScalpingThis is a hyper-reactive scalping strategy designed for the 1-minute chart. It utilizes a strict four-EMA hierarchy (80/90/340/500) to ensure trades are only taken in the strongest aligned market trend. The strategy is built to be extremely tight on risk and focuses on capturing the immediate, high-momentum swing that follows a confirmed EMA retest or breakout.
Key Mechanics (How it Works):
Strict Trend Alignment: Entry is only permitted when the faster EMA band (80/90) and the price action are correctly aligned with the slow trend (340/500).
Long: EMA 80/90 must be above EMA 340/500, AND EMA 340 must be above EMA 500. (And vice-versa for Short.)
Expanded Retest Entry: The strategy waits for the price to retest or briefly enter the 80/90 band, then immediately enters upon the confirmed momentum breakout from that band.
Dynamic Risk Management (Tight Ride): The strategy is engineered to ride the wave aggressively while protecting capital immediately:
Extremely Tight Initial Stop Loss (0.2% default): Limits initial risk instantly.
Break-Even Security: Once profit hits 0.3%, the Stop Loss is automatically trailed to secure 0.2% profit (a risk-free trade).
Aggressive Exit Logic: Positions are closed not only upon hitting the Take Profit target (2.5%) but also immediately if the 80/90 EMA band crosses the 340 EMA, signaling a critical loss of momentum.
Disclaimer:
This strategy requires high-liquidity instruments and is best used on low timeframes (1-minute) due to its dependency on fast momentum shifts and tight stops. Backtesting and forward testing are crucial before deployment.
Premarket Breakout (TP1 โ BE โ ATR Trail)this is the best ever you will really like i t and it does a lot its a really good scirpt please use it to make trades
Mirror Blocks: StrategyMirror Blocks is an educational structural-wave model built around a unique concept:
the interaction of mirrored weighted moving averages (โblocksโ) that reflect shifts in market structure as price transitions between layered symmetry zones.
Rather than attempting to โpredictโ markets, the Mirror Blocks framework visualizes how price behaves when it expands away from, contracts toward, or flips across stacked WMA structures. These mirrored layers form a wave-like block system that highlights transitional zones in a clean, mechanical way.
This strategy version allows you to study how these structural transitions behave in different environments and on different timeframes.
The goal is understanding wave structure, not generating signals.
How It Works
Mirror Blocks builds three mirrored layers:
Top Block (Structural High Symmetry)
Base Block (Neutral Wave)
Bottom Block (Structural Low Symmetry)
The relative position of these blocks โ and how price interacts with them โ helps visualize:
Compression and expansion
Reversal zones
Wave stability
Momentum transitions
Structure flips
A structure is considered bullish-stack aligned when:
Top > Base > Bottom
and bearish-stack aligned when:
Bottom > Base > Top
These formations create the core of the Mirror Blocks wave engine.
What the Strategy Version Adds
This version includes:
Long Only, Short Only, or Long & Short modes
Adjustable symmetry distance (Mirror Distance)
Configurable WMA smoothing length
Optional trend filter using fast/slow MA comparison
ENTER / EXIT / LONG / SHORT labels for structural transitions
Fixed stop-loss controls for research
A clean, transparent structure with no hidden components
It is optimized for educational chart study, not automated signals.
Intended Purpose
Mirror Blocks is meant to help traders:
Study structural transitions
Understand symmetry-based wave models
Explore how price interacts with mirrored layers
Examine reversals and expansions from a mechanical perspective
Conduct long and short backtesting for research
Develop a deeper sense of market rhythm
This is not a prediction model.
It is a visual and structural framework for understanding movement.
Backtesting Disclaimer
Backtest results can vary depending on:
Slippage settings
Commission settings
Timeframe
Asset volatility
Structural sensitivity parameters
Past performance does not guarantee future results.
Use this as a research tool only.
Warnings & Compliance
This script is educational.
It is not financial advice.
It does not provide signals.
It does not promise profitability.
The purpose is to help visualize structure, not predict price.
The strategy features are simply here to help users study how structural transitions behave under various conditions.
License
Released under the Michael Culpepper Gratitude License (2025).
Use and modify freely for education and research with attribution.
No resale.
No promises of profitability.
Purpose is understanding, not signals.
Premarket Breakout (TP1 โ BE โ ATR Trail)the best one you can find a very good indicator and strategy to help with al l trading needs in every way
Hash Momentum Strategy# Hash Momentum Strategy
## ๐ Overview
The **Hash Momentum Strategy** is a professional-grade momentum trading system designed to capture strong directional price movements with precision timing and intelligent risk management. Unlike traditional EMA crossover strategies, this system uses momentum acceleration as its primary signal, resulting in earlier entries and better risk-to-reward ratios.
---
## โก What Makes This Strategy Unique
### 1. Momentum-Based Entry System
Most strategies rely on lagging indicators like moving average crossovers. This strategy captures momentum *acceleration* - entering when price movement is gaining strength, not after the move has already happened.
### 2. Programmable Risk-to-Reward
Set your exact R:R ratio (1:2, 1:2.5, 1:3, etc.) and the strategy automatically calculates stop loss and take profit levels. No more guessing or manual calculations.
### 3. Smart Partial Profit Taking
Lock in profits at multiple stages:
- **First TP**: Take 50% off at 2R
- **Second TP**: Take 40% off at 2.5R
- **Final TP**: Let 10% ride to maximum target
This approach locks in gains while letting winners run.
### 4. Dynamic Momentum Threshold
Uses ATR (Average True Range) multiplied by your threshold setting to adapt to market volatility. Volatile markets = higher threshold. Quiet markets = lower threshold.
### 5. Trade Cooldown System
Prevents overtrading and revenge trading by enforcing a cooldown period between trades. Configurable from 1-24 bars.
### 6. Optional Session & Weekend Filters
Filter trades by Tokyo, London, and New York sessions. Optional weekend-off toggle to avoid low-liquidity periods.
---
## ๐ฏ How It Works
### Signal Generation
**STEP 1: Calculate Momentum**
- Momentum = Current Price - Price
- Check if Momentum > ATR ร Threshold Multiplier
- Momentum must be accelerating (positive change in momentum)
**STEP 2: Confirm with EMA Trend Filter**
- Long: Price must be above EMA
- Short: Price must be below EMA
**STEP 3: Check Filters**
- Not in cooldown period
- Valid session (if enabled)
- Not weekend (if enabled)
**STEP 4: ENTRY SIGNAL TRIGGERED**
### Risk Management Example
**Example Long Trade:**
- Entry: $100
- Stop Loss: $97.80 (2.2% risk)
- Risk Amount: $2.20
**Take Profit Levels:**
- TP1: $104.40 (2R = $4.40) โ Close 50%
- TP2: $105.50 (2.5R = $5.50) โ Close 40%
- Final: $105.50 (2.5R) โ Close remaining 10%
---
## โ๏ธ Settings Guide
### Core Strategy
**Momentum Length** (Default: 13)
Number of bars for momentum calculation. Higher = stronger but fewer signals.
**Momentum Threshold** (Default: 2.25)
ATR multiplier. Higher = only trade biggest moves.
**Use EMA Trend Filter** (Default: ON)
Only long above EMA, short below EMA.
**EMA Length** (Default: 28)
Period for trend-confirming EMA.
### Filters
**Use Trading Session Filter** (Default: OFF)
Restrict trading to specific sessions.
**Tokyo Session** (Default: OFF)
Trade during Asian hours (00:00-09:00 JST).
**London Session** (Default: OFF)
Trade during European hours (08:00-17:00 GMT).
**New York Session** (Default: OFF)
Trade during US hours (08:00-17:00 EST).
**Weekend Off** (Default: OFF)
Disable trading on Saturdays and Sundays.
### Risk Management
**Stop Loss %** (Default: 2.2)
Fixed percentage stop loss from entry.
**Risk:Reward Ratio** (Default: 2.5)
Your target reward as multiple of risk.
**Use Partial Profit Taking** (Default: ON)
Take profits in stages.
**First TP R:R** (Default: 2.0)
First target as multiple of risk.
**First TP Size %** (Default: 50)
Percentage of position to close at TP1.
**Second TP R:R** (Default: 2.5)
Second target as multiple of risk.
**Second TP Size %** (Default: 40)
Percentage of position to close at TP2.
### Trade Management
**Use Trade Cooldown** (Default: ON)
Prevent overtrading.
**Cooldown Bars** (Default: 6)
Bars to wait after closing a trade.
---
## ๐จ Visual Elements
### Chart Indicators
๐ข **Green Dot** (below bar) = Long entry signal
๐ด **Red Dot** (above bar) = Short entry signal
๐ต **Blue X** (above bar) = Long position closed
๐ **Orange X** (below bar) = Short position closed
**EMA Line** = Trend direction (green when bullish, red when bearish)
**White Line** = Entry price
**Red Line** = Stop loss level
**Green Lines** = Take profit levels (TP1, TP2, Final)
### Dashboard
When not in real-time mode, a dashboard displays:
- Current position (LONG/SHORT/FLAT)
- Entry price
- Stop loss price
- Take profit price
- R:R ratio
- Current momentum strength
- Total trades
- Win rate
- Net profit %
---
## ๐ Recommended Settings by Timeframe
### 1-Hour Timeframe (Default)
- Momentum Length: 13
- Momentum Threshold: 2.25
- EMA Length: 28
- Stop Loss: 2.2%
- R:R Ratio: 2.5
- Cooldown: 6 bars
### 4-Hour Timeframe
- Momentum Length: 24-36
- Momentum Threshold: 2.5
- EMA Length: 50
- Stop Loss: 3-4%
- R:R Ratio: 2.0-2.5
- Cooldown: 6-8 bars
### 15-Minute Timeframe
- Momentum Length: 8-10
- Momentum Threshold: 2.0
- EMA Length: 20
- Stop Loss: 1.5-2%
- R:R Ratio: 2.0
- Cooldown: 4-6 bars
---
## ๐ง Optimization Tips
### Want More Trades?
- Decrease Momentum Threshold (2.0 instead of 2.25)
- Decrease Momentum Length (10 instead of 13)
- Decrease Cooldown Bars (4 instead of 6)
### Want Higher Quality Trades?
- Increase Momentum Threshold (2.5-3.0)
- Increase Momentum Length (18-24)
- Increase Cooldown Bars (8-10)
### Want Lower Drawdown?
- Increase Cooldown Bars
- Use tighter stop loss
- Enable session filters (trade only high-liquidity sessions)
- Enable Weekend Off
### Want Higher Win Rate?
- Increase R:R Ratio (may reduce total profit)
- Increase Momentum Threshold (fewer but stronger signals)
- Use longer EMA for trend confirmation
---
## ๐ Performance Expectations
Based on typical backtesting results:
- **Win Rate**: 35-45%
- **Profit Factor**: 1.5-2.0
- **Risk:Reward**: 1:2.5 (configurable)
- **Max Drawdown**: 10-20%
- **Trades/Month**: 8-15 (1H timeframe)
**Note:** Win rate may appear low, but with 2.5:1 R:R, you only need ~29% win rate to break even. The strategy aims for quality over quantity.
---
## ๐ Strategy Logic Explained
### Why Momentum > EMA Crossover?
**EMA Crossover Problems:**
- Signals lag behind price
- Late entries = poor R:R
- Many false signals in ranging markets
**Momentum Advantages:**
- Catches moves as they start accelerating
- Earlier entries = better R:R
- Adapts to volatility via ATR
### Why Partial Profit Taking?
**Without Partial TPs:**
- All-or-nothing approach
- Winners often turn to losers
- High stress watching open positions
**With Partial TPs:**
- Lock in 50% at first target
- Reduce risk to breakeven
- Let remainder ride for bigger gains
- Lower psychological pressure
### Why Trade Cooldown?
**Without Cooldown:**
- Revenge trading after losses
- Overtrading in choppy markets
- Emotional decision-making
**With Cooldown:**
- Forces discipline
- Waits for new setup to develop
- Reduces transaction costs
- Better signal quality
---
## โ ๏ธ Important Notes
1. **This is a momentum strategy, not an EMA strategy**
The EMA only confirms trend direction. Momentum generates the actual signals.
2. **Backtest thoroughly before live trading**
Past performance โ future results. Test on your specific asset and timeframe.
3. **Use proper position sizing**
Risk 1-2% of account per trade maximum. The strategy uses 100% equity by default (adjust in Properties).
4. **Dashboard auto-hides in real-time**
Clean chart for live trading. Visible during backtesting.
5. **Customize for your trading style**
All settings are fully adjustable. No single "best" configuration.
---
## ๐ Quick Start Guide
1. **Add to Chart**: Apply to your preferred asset and timeframe
2. **Keep Defaults**: Start with default settings
3. **Backtest**: Review historical performance
4. **Paper Trade**: Test with simulated money first
5. **Go Live**: Start small and scale up
---
## ๐ก Pro Tips
**Tip 1: Combine Timeframes**
Use higher timeframe (4H) for trend direction, lower timeframe (1H) for entries.
**Tip 2: Avoid News Events**
Major news can cause whipsaws. Consider manual intervention during high-impact events.
**Tip 3: Monitor Momentum Strength**
Dashboard shows momentum in sigma (ฯ). Values >1.0ฯ indicate very strong momentum.
**Tip 4: Adjust for Volatility**
In high-volatility markets, increase threshold and stop loss. In quiet markets, decrease them.
**Tip 5: Review Losing Trades**
Check if losses are hitting stop loss or reversing. Adjust stop accordingly.
---
## ๐ Changelog
**v1.0** - Initial Release
- Momentum-based signal generation
- EMA trend filter
- Programmable R:R ratio
- Partial profit taking (3 stages)
- Trade cooldown system
- Session filters (Tokyo/London/New York)
- Weekend off toggle
- Smart dashboard (auto-hides in real-time)
- Clean visual design
---
## ๐ Credits
Developed by **Hash Capital Research**
If you find this strategy useful, please give it a like and share with others!
---
## โ๏ธ Disclaimer
This strategy is for educational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always do your own research and consult with a qualified financial advisor before trading.
---
## ๐ฌ Feedback
Have suggestions or found a bug? Leave a comment below! I'm continuously improving this strategy based on community feedback.
---
**Happy Trading! ๐๐**
Pivot Fib 4H โ EAStrategy uses the pivot standard to open position, it has well define entry and exit point with SL, it also has a proper money management plan, maximum 4 trades a day, each trade risk 0.5% of the account, I have it EA version of it also.
ILM & IFVG StrategyPlease feel free to adjust in any way possible. Let me know if you can create something better from this initial coding.
//โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
// Inverted Liquidity Model (ILM) โ Strategy
//โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
//
// The **Inverted Liquidity Model (ILM)** is a liquidity-based algorithm
// built to capture high-probability reversals after:
//
// โข A liquidity sweep (SSL/BSL taken)
// โข Rejection back inside the range
// โข A Fair Value Gap (FVG) forms
// โข That FVG becomes invalidated โ becomes an IFVG entry zone
//
// ILM combines:
// โข LTF BOS / CHOCH structure confirmation
// โข HTF structure (expansion) filtering
// โข Premium / Discount filter (17:00 CST session midline)
// โข Optional ATR volatility filter
// โข Optional trading session restrictions
// โข Optional partial profit-taking + runners
//
// When all conditions align, the strategy enters:
// โ Long after sweep of SSL + valid long IFVG + trend confirmation
// โ Short after sweep of BSL + valid short IFVG + trend confirmation
//
// Stops are placed at the sweep wick.
// Full target is set at the next structural high/low.
// Optional partial TP sends a runner to full target.
//
// Visual tools (labels, sweep lines, IFVG boxes, midline) assist
// with review and forward testing.
//
//โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
// USER CONFIGURABLE FEATURES
//โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
//
// โข **Liquidity & Structure**
// - pivotLen โ swing length for pivots / liquidity
// - htfOn โ toggle higher-timeframe pivots
// - htfTF โ timeframe for HTF structure/liquidity
// - useStructureFilter โ enforce LTF BOS/CHOCH trend
// - useHtfExpansionFilter โ enforce HTF trend
// - showStructureLabels โ show BOS/CHOCH labels
// - showHtfStructureLabels โ show HTF BOS/CHOCH labels
//
// โข **Premium / Discount Midline**
// - usePremiumDiscountFilter โ only long in discount / short in premium
// - pdSession โ session used for midline (default 17:00 CST)
// - showPdMidLine โ show 50% midline
//
// โข **FVG / IFVG Detection**
// - useBodyGapFVG โ FVG uses candle bodies instead of wicks
// - useDisplacementFVG โ require displacement bar
// - dispAtrMult โ minimum ATR threshold for displacement
// - showIFVG โ draw IFVG boxes
//
// โข **ATR / Volatility / Sessions**
// - useRangeFilter โ require minimum ATR%
// - atrLen โ ATR period
// - minAtrPerc โ minimum ATR% of price
// - useSessionFilter โ restrict trading hours
// - sessionTimes โ allowed trading session
//
// โข **Sweep Visualization**
// - showSweepLines โ draw sweep lines at SSL/BSL sweeps
// - sweepLineWidth โ thickness of sweep lines
//
// โข **Exits: Partial Targets & Runners**
// - usePartialTargets โ enable partial TP logic
// - tp1QtyPercent โ percent closed at TP1
// - tp1FractionOfPath โ TP1 relative to path to full target
//
// โข **Formatting / Visibility**
// - labelFontSizeInput โ tiny / small / normal / large / huge
// - showEntries โ entry markers
// - showTargets โ target lines
//
//โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
// END OF STRATEGY DESCRIPTION
//โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Crude Oil Time + Fix Catalyst StrategyHybrid Workflow: Event-Driven Macro + Market DNA Micro
1. Macro Catalyst Layer (Your Overlays)
Event Mapping: Fed decisions, LBMA fixes, EIA releases, OPEC+ meetings.
Regime Filters: Risk-on/off, volatility regimes, macro bias (hawkish/dovish).
Volatility Scaling: ATR-based position sizing, adaptive overlays for London/NY sessions.
Governance: Max trades/day, cool-down logic, session boundaries.
๐ This layer answers when and why to engage.
2. Micro Execution Layer (Market DNA)
Order Flow Confirmation: Tape reading (Level II, time & sales, bid/ask).
Liquidity Zones: Identify support/resistance pools where buyers/sellers cluster.
Imbalance Detection: Aggressive buyers/sellers overwhelming the other side.
Precision Entry: Only trigger trades when order flow confirms macro catalyst bias.
Risk Discipline: Tight stops beyond liquidity zones, conviction-based scaling.
๐ This layer answers how and where to engage.
3. Unified Playbook
Step Macro Overlay (Your Edge) Market DNA (Jayโs Edge) Result
Event Trigger Fed/LBMA/OPEC+ catalyst flagged โ Volatility window opens
Bias Filter Hawkish/dovish regime filter โ Directional bias set
Sizing ATR volatility scaling โ Position size calibrated
Execution โ Tape confirms liquidity imbalance Precision entry
Risk Control Governance rules (cool-down, max trades) Tight stops beyond liquidity zones Disciplined exits
4. Gold & Silver Use Case
Gold (Fed Day):
Overlay flags volatility window โ bias hawkish.
Market DNA shows sellers hitting bids at resistance.
Enter short with volatility-scaled size, stop just above liquidity zone.
Silver (LBMA Fix):
Overlay highlights fix window โ bias neutral.
Market DNA shows buyers stepping in at support.
Enter long with adaptive size, HUD displays risk metrics.
5. HUD Integration
Macro Dashboard: Catalyst timeline, regime filter status, volatility bands.
Micro Dashboard: Live tape imbalance meter, liquidity zone map, conviction score.
Unified View: Macro tells you when to look, micro tells you when to pull the trigger.
โก This hybrid workflow gives you macro awareness + micro precision. Your overlays act as the radar, Jayโs Market DNA acts as the laser scope. Together, they create a disciplined, event-aware, volatility-scaled playbook for gold and silver.
Antonio โ do you want me to draft this into a compile-safe Pine Script v6 template that embeds the macro overlay logic, while leaving hooks for Market DNA-style execution (order flow confirmation)? That way youโd have a production-ready skeleton to extend across TradingView, TradeStation, and NinjaTrader.
Antonio โ do you want me to draft this into a compile-safe Pine Script v6 template that embeds the macro overlay logic, while leaving hooks for Market DNA-style execution (order flow confirmation)? That way youโd have a production-ready skeleton to extend across TradingView, TradeStation, and NinjaTrader.
Liquidity Sweep + BOS Retest System โ Prop Firm Edition๐ฆ Liquidity Sweep + BOS Retest System โ Prop Firm Edition
A High-Probability Smart Money Strategy Built for NQ, ES, and Funding Accounts
๐ Overview
The Liquidity Sweep + BOS Retest System (Prop Firm Edition) is a precision-engineered SMC strategy built specifically for prop firm traders. It mirrors institutional liquidity behavior and combines it with strict account-safe entry rules to help traders pass and maintain funding accounts with consistency.
Unlike typical indicators, this system waits for three confirmations โ liquidity sweep, displacement, and a clean retest โ before executing any trade. Every component is optimized for low drawdown, high R:R, and prop-firm-approved risk management.
Whether youโre trading Apex, TakeProfitTrader, FFF, or OneUp Trader, this system gives you a powerful mechanical framework that keeps you within rules while identifying the marketโs highest-probability reversal zones.
๐ฅ Key Features
1. Liquidity Sweep Detection (Stop Hunt Logic)
Automatically identifies when price clears a previous swing high/low with a sweep confirmation candle.
โ Filters noise
โ Eliminates early entries
โ Locks onto true liquidity grabs
2. Automatic Break of Structure (BOS) Confirmation
Price must show true displacement by breaking structure opposite the sweep direction.
โ Confirms momentum shift
โ Removes fake reversals
โ Ensures institutional intent
3. Precision Retest Entry Model
The strategy enters only when price retests the BOS level at premium/discount pricing.
โ Zero chasing
โ Extremely tight stop loss placement
โ Prop-firm-friendly controlled risk
4. Built-In Risk & Trade Management
SL set at swept liquidity
TP set by user-defined R:R multiplier
Optional session filter (NY Open by default)
One trade at a time (no pyramiding)
Automatically resets logic after each trade
This prevents overtrading โ the #1 cause of evaluation and account breaches.
5. Designed for Prop Firm Futures Trading
This script is optimized for:
Trailing/static drawdown accounts
Micro contract precision
Funding evaluations
Low-risk, high-probability setups
Structured, rule-based execution
It reduces randomness and emotional trading by automating the highest-quality SMC sequence.
๐ฏ The Trading Model Behind the System
Step 1 โ Liquidity Sweep
Price must take out a recent high/low and close back inside structure.
This confirms stop-hunting behavior and marks the beginning of a potential reversal.
Step 2 โ BOS (Break of Structure)
Price must break the opposite side swing with a displacement candle. This validates a directional shift.
Step 3 โ Retest Entry
The system waits for price to retrace into the BOS level and signal continuation.
This creates optimal R:R entry with minimal drawdown.
๐ Best Markets
NQ (NASDAQ Futures) โ Highly recommended
ES, YM, RTY
Gold (XAUUSD)
FX majors
Crypto (with high volatility)
Works best on 1m, 2m, 5m, or 15m depending on your trading style.
๐ง Why Traders Love This System
โ No signals until all confirmations align
โ Reduces overtrading and emotional decisions
โ Follows market structure instead of random indicators
โ Perfect for maintaining long-term funded accounts
โ Built around institutional-grade concepts
โ Makes your trading consistent, calm, and rules-based
โ๏ธ Recommended Settings
Session: 06:30โ08:00 MST (NY Open)
R:R: 1.5R โ 3R
Contracts: Start with 1โ2 micros
Markets: NQ for best structure & volume
๐ฆ Whatโs Included
Complete strategy logic
All plots, labels, sweep markers & BOS alerts
BOS retest entry automation
Session filtering
Stop loss & take profit system
Full SMC logic pipeline
๐ Summary
The Liquidity Sweep + BOS Retest System is a complete, prop-firm-ready, structure-based strategy that automates one of the cleanest and most reliable SMC entry models. It is designed to keep you safe, consistent, and rule-compliant while capturing premium institutional setups.
If you want to trade with confidence, discipline, and prop-firm precision โ this system is for you.
Good Luck -BG
