Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
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### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
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### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
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### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
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### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
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### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
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### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
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### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
Cerca negli script per "profit"
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
MACD Volume Strategy for XAUUSD (15m) [PineIndicators]The MACD Volume Strategy is a momentum-based trading system designed for XAUUSD on the 15-minute timeframe. It integrates two key market indicators: the Moving Average Convergence Divergence (MACD) and a volume-based oscillator to identify strong trend shifts and confirm trade opportunities. This strategy uses dynamic position sizing, incorporates leverage customization, and applies structured entry and exit conditions to improve risk management.
⚙️ Core Strategy Components
1️⃣ Volume-Based Momentum Calculation
The strategy includes a custom volume oscillator to filter trade signals based on market activity. The oscillator is derived from the difference between short-term and long-term volume trends using Exponential Moving Averages (EMAs)
Short EMA (default = 5) represents recent volume activity.
Long EMA (default = 8) captures broader volume trends.
Positive values indicate rising volume, supporting momentum-based trades.
Negative values suggest weak market activity, reducing signal reliability.
By requiring positive oscillator values, the strategy ensures momentum confirmation before entering trades.
2️⃣ MACD Trend Confirmation
The strategy uses the MACD indicator as a trend filter. The MACD is calculated as:
Fast EMA (16-period) detects short-term price trends.
Slow EMA (26-period) smooths out price fluctuations to define the overall trend.
Signal Line (9-period EMA) helps identify crossovers, signaling potential trend shifts.
Histogram (MACD – Signal) visualizes trend strength.
The system generates trade signals based on MACD crossovers around the zero line, confirming bullish or bearish trend shifts.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when all the following conditions are met:
✅ MACD crosses above 0, signaling bullish momentum.
✅ Volume oscillator is positive, confirming increased trading activity.
✅ Current volume is at least 50% of the previous candle’s volume, ensuring market participation.
🔻 Short Entry Conditions
A sell signal is generated when:
✅ MACD crosses below 0, indicating bearish momentum.
✅ Volume oscillator is positive, ensuring market activity is sufficient.
✅ Current volume is less than 50% of the previous candle’s volume, showing decreasing participation.
This multi-factor approach filters out weak or false signals, ensuring that trades align with both momentum and volume dynamics.
📏 Position Sizing & Leverage
Dynamic Position Calculation:
Qty = strategy.equity × leverage / close price
Leverage: Customizable (default = 1x), allowing traders to adjust risk exposure.
Adaptive Sizing: The strategy scales position sizes based on account equity and market price.
Slippage & Commission: Built-in slippage (2 points) and commission (0.01%) settings provide realistic backtesting results.
This ensures efficient capital allocation, preventing overexposure in volatile conditions.
🎯 Trade Management & Exits
Take Profit & Stop Loss Mechanism
Each position includes predefined profit and loss targets:
Take Profit: +10% of risk amount.
Stop Loss: Fixed at 10,100 points.
The risk-reward ratio remains balanced, aiming for controlled drawdowns while maximizing trade potential.
Visual Trade Tracking
To improve trade analysis, the strategy includes:
📌 Trade Markers:
"Buy" label when a long position opens.
"Close" label when a position exits.
📌 Trade History Boxes:
Green for profitable trades.
Red for losing trades.
📌 Horizontal Trade Lines:
Shows entry and exit prices.
Helps identify trend movements over multiple trades.
This structured visualization allows traders to analyze past performance directly on the chart.
⚡ How to Use This Strategy
1️⃣ Apply the script to a XAUUSD (Gold) 15m chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Enable backtesting to assess past performance.
4️⃣ Monitor volume and MACD conditions to understand trade triggers.
5️⃣ Use the visual trade markers to review historical performance.
The MACD Volume Strategy is designed for short-term trading, aiming to capture momentum-driven opportunities while filtering out weak signals using volume confirmation.
Hanzo_Wave_Price %Hanzo_Wave_Price % is a custom indicator for the TradingView platform that combines RSI (Relative Strength Index) and Stochastic RSI while also displaying the percentage price change over a specified period. This indicator helps traders identify overbought and oversold conditions, analyze price waves, and forecast potential market movements.
How It Works
1. RSI and Stochastic RSI Calculation
RSI is calculated based on the selected price source (default: close) with a user-defined Main Line period.
Stochastic RSI is then applied and smoothed using a moving average.
The Main Line represents the smoothed Stochastic RSI, serving as a wave indicator to help identify potential entry and exit points.
2. Overbought and Oversold Zones
The 70 and 30 levels indicate overbought and oversold zones, displayed as dashed lines on the chart.
Additional 20% and 10% levels provide a visual reference for historical price changes, aiding in future predictions.
3. Percentage Price Change Calculation
The indicator calculates the percentage price change over a Barsback period (default: 30 candles).
Users can choose a multiplier (100 or 1000) for better visualization (1000 scales the values by dividing by 10).
The data is displayed as a colored area:
Red (Short) → Negative price change.
Green (Buy) → Positive price change.
Settings & Parameters
Multiplier 💪 – Selects the scaling factor (100 or 1000) for percentage values.
Main Line ✈️ – Stochastic smoothing period (smoothK).
Don't touch ✋ – Reserved value (do not modify).
RSI 🔴 – RSI calculation period.
Stochastic 🔵 – Stochastic RSI calculation period.
Source ⚠️ – Price source for calculations (default: close).
Price changes % 🔼🔽 – Enables percentage price change display.
Barsback ↩️ – Number of candles used to calculate price change.
Visual Representation
Gray Line (Takeprofit Line 🎯) – Smoothed Stochastic RSI.
Red Dashed Line (70) – Overbought zone.
Blue Dashed Line (30) – Oversold zone.
Percentage Price Change Display:
Green Fill → Price increase.
Red Fill → Price decrease.
Advantages
✅ Combined Analysis – Uses RSI and Stochastic RSI for more accurate market condition identification.
✅ Flexibility – Customizable parameters allow adaptation for different markets and strategies.
✅ Visual Clarity – Clearly defined zones and dynamic percentage change display.
✅ Additional Market Insights – The percentage price change helps assess market volatility.
Disadvantages
⚠ Lagging Signals – Smoothing may cause delayed response.
⚠ False Breakouts – The 70/30 levels may not always work effectively for all assets.
⚠ IMPORTANT!
This indicator is for informational and educational purposes only. Past performance does not guarantee future profits! Use it in combination with other technical analysis tools. 🚀
Example 1: Identifying a Long Position
📌 Scenario:
The asset price has dropped significantly (1-hour timeframe), and the Main Line (gray line) crosses below the 30 level. This signals oversold conditions, which may indicate a potential reversal or upward correction.
✅ How to Use:
1️⃣ Identifying the Entry Zone:
If the Main Line is below 30, consider looking for a long entry point.
2️⃣ Confirming the Signal:
Place a vertical line at the moment when the Main Line crosses the 30 level from below.
3️⃣ Confirmation on a Lower Timeframe:
Switch to a 30-minute timeframe and wait for the Main Line to cross above the 70 level.
Enter a long position at this point.
4️⃣ Analyzing Percentage Price Change:
Check the historical indicator behavior:
If a similar past movement resulted in a ~10% price increase (green fill), this may indicate potential upward momentum.
5️⃣ Setting Take-Profit:
Set a take-profit level at 10%, based on previous price movements.
Also, monitor when the Main Line crosses the 70 level, as this may signal a potential profit-taking point.
📊 Conclusion:
This method helps to precisely determine entry points by confirming signals across multiple timeframes and analyzing the historical volatility of the asset. 🚀
Example 2: Analyzing Percentage Price Change
📌 Scenario:
You have set the Barsback parameter to 30, and the indicator shows +3.5%. This means that over the last 30 candles, the price has increased by 3.5%.
However, such small changes might be visually difficult to notice. To improve visibility, you can enable the multiplier (1000), which will scale the displayed percentage change to 35%. This is purely for visual convenience—the actual price movement remains 3.5%.
✅ How to Use:
1️⃣ Identifying Trend Direction:
If the percentage change is positive (green area) → Uptrend.
If the percentage change is negative (red area) → Downtrend.
2️⃣ Analyzing Movement Strength:
Compare the current percentage change with previous waves to evaluate the strength of the movement.
For example:
If previous waves reached 10% or more, a current wave of 3.5% might indicate a weak trend or a local correction.
3️⃣ Additional Filtering with the Main Line (Gray Line):
Use the Main Line to confirm the trend.
If the percentage change shows an increase, but the Main Line is still below 30, further upward movement can be expected.
If the percentage change indicates a decline, but the Main Line is above 70, there is a higher probability of a downward reversal.
"It's unfortunate that TradingView restricts adding images to indicator descriptions unless you have a paid subscription. This makes it harder to share free tools effectively."
Pivot Candles with MFI Opacity (No Plot)How to Use the Pivot Candles with MFI Opacity Indicator for Trade Entries and Position Management
Overview
This indicator is designed not only to display key pivot levels (support and resistance) and Money Flow Index (MFI) signals on your chart, but also to help you structure systematic order entries and position management. By combining pivot levels with dynamic MFI-based candle opacity, the indicator provides a visual framework that technical analysts and quants can use to time buy and sell stop orders as well as to pyramid positions or take profits.
Trade Entry with Pivot Levels
Buy Stop Orders Above R1:
Concept: In many technical setups, resistance levels such as R1 are viewed as potential breakout points. A buy stop order placed just above R1 allows you to enter a long position only when price decisively breaks the prior resistance, confirming bullish momentum.
How It Works:
The indicator calculates pivot levels based on the previous higher‑timeframe bar, so R1 is “locked in” for the current period.
When the current candle closes above R1, it may signal a breakout.
Technical analysts often place a buy stop order slightly above R1 (for example, a few ticks or pips above the level) to confirm the move.
Practical Application:
Quants and systematic traders can program their models to monitor when the current close exceeds R1.
Once this condition is met, a buy stop order is triggered to capture the breakout move, ensuring that you only participate if the price decisively moves upward.
Sell Stop Orders Below S1:
Concept: Conversely, S1 acts as a support level. A sell stop order placed just below S1 is designed to capture a breakdown. This order is activated when price closes below S1, indicating that selling pressure may be overwhelming.
How It Works:
With pivot levels fixed from the previous higher‑timeframe bar, S1 provides a reference for potential support.
A close below S1 can be interpreted as a sign of a bearish reversal or a continuation of a downtrend.
Practical Application:
Quants set up their systems to watch for a break below S1.
A sell stop order is positioned just below S1 to ensure that if the support level fails, the system can quickly initiate a short position to capture the downward move.
Using MFI for Position Management
Pyramiding and Profit Taking:
Dynamic Candle Opacity:
The Money Flow Index (MFI) in this indicator not only provides overbought/oversold alerts but also controls the opacity of your candlesticks. When MFI readings are high, the candles become more opaque, indicating strong buying pressure. Conversely, lower MFI values lead to more transparent candles, suggesting reduced momentum.
Pyramiding Long Positions:
Strategy:
In a strong trend, technical analysts might choose to add to a winning position gradually—a process known as pyramiding.
Implementation:
As long as the price remains above R1 and MFI readings are supportive (high and consistent), you may consider adding to your long position incrementally.
Each new buy stop order can be set above R1 with slightly adjusted trigger levels to capture further breakout strength.
Risk Management:
Quants use the MFI reading as a risk filter; if MFI begins to drop or the candles become significantly more transparent, it may be a cue to stop pyramiding or even begin taking profits.
Taking Profit Using MFI and Pivot Reversals:
Profit Targeting:
When price reaches higher resistance levels (e.g., R2 or R3) or shows signs of overextension in conjunction with extreme MFI levels (for instance, a sudden drop in MFI after a strong rally), you can begin taking partial profits.
Systematic Exit:
A systematic strategy might include scaling out of the position as the price approaches the next resistance level or when the MFI indicates that buying momentum is waning.
Similarly, for short positions entered below S1, profit targets might be set near subsequent support levels, with exits triggered if MFI suggests a reversal.
Summary
Entry Orders:
Place buy stop orders just above R1 to capture breakouts.
Place sell stop orders just below S1 to capture breakdowns.
Position Management with MFI:
Use MFI-based candle opacity as a visual indicator of momentum.
Pyramid positions in the direction of the trend when MFI confirms strength.
Consider partial exits if MFI readings start to reverse or if the price nears the next pivot level.
By following this systematic approach, technical analysts and quants can use the indicator not only as a visual tool but as an integral part of an automated or semi-automated trading system that emphasizes disciplined entries, pyramiding, and profit-taking.
2xSPYTIPS Strategy by Fra public versionThis is a test strategy with S&P500, open source so everyone can suggest everything, I'm open to any advice.
Rules of the "2xSPYTIPS" Strategy :
This trading strategy is designed to operate on the S&P 500 index and the TIPS ETF. Here’s how it works:
1. Buy Conditions ("BUY"):
- The S&P 500 must be above its **200-day simple moving average (SMA 200)**.
- This condition is checked at the **end of each month**.
2. Position Management:
- If leverage is enabled (**2x leverage**), the purchase quantity is increased based on a configurable percentage.
3. Take Profit:
- A **Take Profit** is set at a fixed percentage above the entry price.
4. Visualization & Alerts:
- The **SMA 200** for both S&P 500 and TIPS is plotted on the chart.
- A **BUY signal** appears visually and an alert is triggered.
What This Strategy Does NOT Do
- It does not use a **Stop Loss** or **Trailing Stop**.
- It does not directly manage position exits except through Take Profit.
AdvancedLines (FiboBands) - PaSKaL
Overview :
AdvancedLines (FiboBands) - PaSKaL is an advanced technical analysis tool designed to automate the plotting of key Fibonacci retracement levels based on the highest high and lowest low over a customizable period. This indicator helps traders identify critical price zones such as support, resistance, and potential trend reversal or continuation points.
By using AdvancedLines (FiboBands) - PaSKaL , traders can easily spot key areas where the price is likely to reverse or consolidate, or where the trend may continue. It is particularly useful for trend-following, scalping, and range-trading strategies.
Key Features:
Automatic Fibonacci Level Calculation :
- The indicator automatically calculates and plots key Fibonacci levels (0.236, 0.382, 0.5, 0.618, and 0.764), which are crucial for identifying potential support and resistance levels in the market.
Adjustable Parameters :
- Bands Length: You can adjust the bands_length setting to change the number of bars used for calculating the highest high and lowest low. This gives flexibility for using the indicator on different timeframes and trading styles.
- Visibility: The Fibonacci levels, as well as the midline (0.5 Fibonacci level), can be shown or hidden based on your preference.
- Color Customization: You can change the color of each Fibonacci level and background fills to suit your chart preferences.
Fibonacci Levels
- The main Fibonacci levels plotted are:
- 0.236 – Minor support/resistance level
- 0.382 – Moderate retracement level
- 0.5 – Midpoint retracement, often used as a key level
- 0.618 – Golden ratio, considered one of the most important Fibonacci levels
- 0.764 – Strong reversal level, often indicating a continuation or change in trend
Background Fill
- The indicator allows you to fill the background between the Fibonacci levels and the bands with customizable colors. This makes it easier to visually highlight key zones on the chart.
How the Indicator Works:
AdvancedLines (FiboBands) - PaSKaL calculates the range (difference between the highest high and the lowest low) over a user-defined number of bars (e.g., 300). Fibonacci levels are derived from this range, helping traders identify potential price reversal points.
Mathematical Basis :
Fibonacci retracement levels are based on the Fibonacci sequence, where each number is the sum of the previous two (0, 1, 1, 2, 3, 5, 8, 13, etc.). The ratios derived from this sequence (such as 0.618 and 0.382) have been widely observed in nature, market cycles, and price movements. These ratios are used to forecast potential price retracements or continuation points after a major price move.
Fibonacci Levels Calculation :
Identify the Range: The highest high and the lowest low over the defined period are calculated.
Apply Fibonacci Ratios: Fibonacci ratios (0.236, 0.382, 0.5, 0.618, and 0.764) are applied to this range to calculate the corresponding price levels.
Plot the Levels: The indicator automatically plots these levels on your chart.
Customizing Fibonacci Levels & Colors:
The "AdvancedLines (FiboBands) - PaSKaL" indicator offers various customization options for Fibonacci levels, colors, and visibility:
Fibonacci Level Ratios:
- You can customize the Fibonacci level ratios through the following inputs:
- Fibo Level 1: 0.764
- Fibo Level 2: 0.618
- Fibo Level 3: 0.5
- Fibo Level 4: 0.382
- Fibo Level 5: 0.236
- These levels determine key areas where price may reverse or pause. You can adjust these ratios based on your trading preferences.
Fibonacci Level Colors:
- Each Fibonacci level can be assigned a different color to make it more distinguishable on your chart:
- Fibo Level 1 Color (default: Yellow)
- Fibo Level 2 Color (default: Orange)
- Fibo Level 3 Color (default: Green)
- Fibo Level 4 Color (default: Red)
- Fibo Level 5 Color (default: Blue)
- You can change these colors to fit your visual preferences or to align with your existing chart themes.
Visibility of Fibonacci Levels:
- You can choose whether to display each Fibonacci level using the following visibility inputs:
- Show Fibo Level 1 (0.764): Display or hide this level.
- Show Fibo Level 2 (0.618): Display or hide this level.
- Show Fibo Level 3 (0.5): Display or hide this level.
- Show Fibo Level 4 (0.382): Display or hide this level.
- Show Fibo Level 5 (0.236): Display or hide this level.
- This allows you to customize the indicator according to the specific Fibonacci levels that are most relevant to your trading strategy.
Background Fill Color
- The background between the Fibonacci levels and price bands can be filled with customizable colors:
- Fill Color for Upper Band & Fibo Level 1: This color will fill the area between the upper band and Fibonacci Level 1.
- Fill Color for Lower Band & Fibo Level 5: This color will fill the area between the lower band and Fibonacci Level 5.
- Adjusting these colors helps highlight critical zones where price may reverse or consolidate.
How to Use AdvancedLines (FiboBands) - PaSKaL in Trading :
Range Trading :
Range traders typically buy at support and sell at resistance. Fibonacci levels provide excellent support and resistance zones in a ranging market.
Example: If price reaches the 0.618 level in an uptrend, it may reverse, providing an opportunity to sell.
Conversely, if price drops to the 0.382 level, a bounce might occur, and traders can buy, anticipating the market will stay within the range.
Trend-following Trading :
For trend-following traders, Fibonacci levels act as potential entry points during a retracement. After a strong trend, price often retraces to one of the Fibonacci levels before continuing in the direction of the trend.
Example: In a bullish trend, when price retraces to the 0.382 level, it could be a signal to buy, as the price might resume its upward movement after the correction.
In a bearish trend, retracements to levels like 0.618 or 0.764 could provide optimal opportunities for shorting as the price resumes its downward movement.
Scalping :
Scalpers focus on short-term price movements. Fibonacci levels can help identify precise entry and exit points for quick trades.
Example: If price is fluctuating in a narrow range, a scalper can enter a buy trade at 0.236 and exit at the next Fibonacci level, such as 0.382 or 0.5, capturing small but consistent profits.
Stop-Loss and Take-Profit Levels :
Fibonacci levels can also help in setting stop-loss and take-profit levels.
Example: In a bullish trend, you can set a stop-loss just below the 0.236 level and a take-profit at 0.618.
In a bearish trend, set the stop-loss just above the 0.382 level and the take-profit at 0.764.
Identifying Reversals and Continuations :
Reversals: When price reaches a Fibonacci level and reverses direction, it may indicate the end of a price move.
Trend Continuation: If price bounces off a Fibonacci level and continues in the same direction, this may signal that the trend is still intact.
Conclusion :
AdvancedLines (FiboBands) - PaSKaL is an essential tool for any trader who uses Fibonacci retracements in their trading strategy. By automatically plotting key Fibonacci levels, this indicator helps traders quickly identify support and resistance zones, forecast potential reversals, and make more informed trading decisions.
For Trend-following Traders: Use Fibonacci levels to find optimal entry points after a price retracement.
For Range Traders: Identify key levels where price is likely to reverse or bounce within a range.
For Scalpers: Pinpoint small price movements and take advantage of quick profits by entering and exiting trades at precise Fibonacci levels.
By incorporating AdvancedLines (FiboBands) - PaSKaL into your trading setup, you will gain a deeper understanding of price action, improve your decision-making process, and enhance your overall trading performance.
CCI Buy and Sell Signals with 20/30 EMACCI Buy and Sell Signals with EMA and ATR Stop Loss/Take Profit
This indicator is designed to identify buy and sell signals based on a combination of the Commodity Channel Index (CCI) and Exponential Moving Averages (EMA). It also includes an optional ATR-based stop loss and take profit system, which is useful for traders who want to manage their trades with dynamic risk levels.
Features:
CCI Buy and Sell Signals:
Buy Signal: A buy signal is triggered when the CCI crosses up through -100 (from an oversold condition), the 20-period EMA is above the 30-period EMA, and the price is above the 200-period EMA. This suggests that the market is entering an upward trend.
Sell Signal: A sell signal is triggered when the CCI crosses down through +100 (from an overbought condition), the 20-period EMA is below the 30-period EMA, and the price is below the 200-period EMA. This suggests that the market is entering a downward trend.
Exponential Moving Averages (EMA):
The script plots three EMAs:
20-period EMA (Green): Used to identify short-term trends.
30-period EMA (Red): Used to capture medium-term trends.
200-period EMA (Orange): A long-term trend filter, with the price above it generally indicating bullish conditions and below it indicating bearish conditions.
ATR-Based Stop Loss and Take Profit:
Optional Feature: The ATR (Average True Range) indicator can be used to set stop loss and take profit levels based on market volatility.
Stop Loss: Set at a multiple of the ATR below the entry price for long positions and above the entry price for short positions.
Take Profit: Set at a multiple of the ATR above the entry price for long positions and below the entry price for short positions.
Customizable: You can adjust the ATR length, Stop Loss Multiplier, and Take Profit Multiplier through the settings.
Dots: The stop loss and take profit levels are plotted as dots on the chart when the ATR feature is enabled.
Alert Conditions:
Buy Signal Alert: Triggered when a buy signal occurs based on CCI crossing up -100 and other conditions being met.
Sell Signal Alert: Triggered when a sell signal occurs based on CCI crossing down +100 and other conditions being met.
Any Signal Alert: This is a combined alert that triggers for either a buy or sell signal. It helps you stay updated on both types of signals simultaneously.
How to Use:
The indicator will plot buy and sell arrows on the chart, giving clear entry points for trades based on CCI and EMA conditions.
The ATR stop loss and take profit dots (when enabled) provide automatic risk management levels, adjusting dynamically with market volatility.
Traders can customize the ATR settings to fine-tune their stop loss and take profit levels, making this strategy adaptable to different trading styles and market conditions.
Reversal rehersal v1This indicator was designed to identify potential market reversal zones using a combination of RSI thresholds (shooting range/falling range), candlestick patterns, and Fair Value Gaps (FVGs). By combining all these elements into one indicator, it allow for outputting high probability buy/sell signals for use by scalpers on low timeframes like 1-15 mins, for quick but small profits.
Note: that this has been mainly tested on DE40 index on the 1 min timeframe, and need to be adjusted to whichever timeframe and symbol you intend to use. Refer to the backtester feature for checking if this indicator may work for you.
The indicator use RSI ranges from two timeframes to highlight where momentum is building up. During these areas, it will look for certain candlestick patterns (Sweeps as the primary one) and check for existance of fair value gaps to further enhance the hitrate of the signal.
The logic for FVG detection was based on ©pmk07's work with MTF FVG tiny indicator. Several major changes was implemented though and incorporated into this indicator. Among these are:
Automatically adjustments of FVG boxes when mitigated partially and options to extend/cull boxes for performance and clarity.
Backtesting Table (Experimental):
This indicator also features an optional simplified table to review historical theoretical performance of signals, including win rate, profit/loss, and trade statistics. This does not take commision or slippage into consideration.
Usage Notes:
Setup:
1. Add the indicator to your chart.
2. Decide if you want to use Long or Short (or both).
3. If you're scalping on ie. 1 min time frame, make sure to set FVG's to higher timeframes (ie. 5, 15, 60).
4. Enable the 'Show backtest results' and adjust the 'Signals' og 'Take profit' and 'Stop loss' values until you are satisfied with the results.
Use:
1. Setup an alert based on either of the 'BullishShooting range' or 'BearishFalling range' alerts. This will draw your attention to watch for the possible setups.
2. Verify if there's a significant imbalance prior to the signal before taking the trade. Otherwise this may invalidate the setup.
3. Once a signal is shown on the graph (either Green arrow up for buys/Red arrow down for sells) - you should enter a trade with the given 'Take profit' and 'Stop loss' values.
4. (optional) Setup an alert for either the Strong/Weak signals. Which corresponds to when one of the arrows are printed.
Important: This is the way I use it myself, but use at own risk and remember to combine with other indicators for further confluence. Remember this is no crystal ball and I do not guarantee profitable results. The indicator merely show signals with high probability setups for scalping.
SMA + RSI + Volume + ATR StrategySMA + RSI + Volume + ATR Strategy
1. Indicators Used:
SMA (Simple Moving Average): This is a trend-following indicator that calculates the average price of a security over a specified period (50 periods in this case). It's used to identify the overall trend of the market.
RSI (Relative Strength Index): This measures the speed and change of price movements. It tells us if the market is overbought (too high) or oversold (too low). Overbought is above 70 and oversold is below 30.
Volume: This is the amount of trading activity. A higher volume often indicates strong interest in a particular price move.
ATR (Average True Range): This measures volatility, or how much the price is moving in a given period. It helps us adjust stop losses and take profits based on market volatility.
2. Conditions for Entering Trades:
Buy Signal (Green Up Arrow):
Price is above the 50-period SMA (indicating an uptrend).
RSI is below 30 (indicating the market might be oversold or undervalued, signaling a potential reversal).
Current volume is higher than average volume (indicating strong interest in the move).
ATR is increasing (indicating higher volatility, suggesting that the market might be ready for a move).
Sell Signal (Red Down Arrow):
Price is below the 50-period SMA (indicating a downtrend).
RSI is above 70 (indicating the market might be overbought or overvalued, signaling a potential reversal).
Current volume is higher than average volume (indicating strong interest in the move).
ATR is increasing (indicating higher volatility, suggesting that the market might be ready for a move).
3. Take Profit & Stop Loss:
Take Profit: When a trade is made, the strategy will set a target price at a certain percentage above or below the entry price (1.5% in this case) to automatically exit the trade once that target is hit.
Stop Loss: If the price goes against the position, a stop loss is set at a percentage below or above the entry price (0.5% in this case) to limit losses.
4. Execution of Trades:
When the buy condition is met, the strategy will enter a long position (buying).
When the sell condition is met, the strategy will enter a short position (selling).
5. Visual Representation:
Green Up Arrow: Appears on the chart when the buy condition is met.
Red Down Arrow: Appears on the chart when the sell condition is met.
These arrows help you see at a glance when the strategy suggests you should buy or sell.
In Summary:
This strategy uses a combination of trend-following (SMA), momentum (RSI), volume, and volatility (ATR) to decide when to buy or sell a stock. It looks for opportunities when the market is either oversold (buy signal) or overbought (sell signal) and makes sure there’s enough volume and volatility to back up the move. It also includes take-profit and stop-loss levels to manage risk.
Bollinger Bands Reversal Strategy Analyzer█ OVERVIEW
The Bollinger Bands Reversal Overlay is a versatile trading tool designed to help traders identify potential reversal opportunities using Bollinger Bands. It provides visual signals, performance metrics, and a detailed table to analyze the effectiveness of reversal-based strategies over a user-defined lookback period.
█ KEY FEATURES
Bollinger Bands Calculation
The indicator calculates the standard Bollinger Bands, consisting of:
A middle band (basis) as the Simple Moving Average (SMA) of the closing price.
An upper band as the basis plus a multiple of the standard deviation.
A lower band as the basis minus a multiple of the standard deviation.
Users can customize the length of the Bollinger Bands and the multiplier for the standard deviation.
Reversal Signals
The indicator identifies potential reversal signals based on the interaction between the price and the Bollinger Bands.
Two entry strategies are available:
Revert Cross: Waits for the price to close back above the lower band (for longs) or below the upper band (for shorts) after crossing it.
Cross Threshold: Triggers a signal as soon as the price crosses the lower band (for longs) or the upper band (for shorts).
Trade Direction
Users can select a trade bias:
Long: Focuses on bullish reversal signals.
Short: Focuses on bearish reversal signals.
Performance Metrics
The indicator calculates and displays the performance of trades over a user-defined lookback period ( barLookback ).
Metrics include:
Win Rate: The percentage of trades that were profitable.
Mean Return: The average return across all trades.
Median Return: The median return across all trades.
These metrics are calculated for each bar in the lookback period, providing insights into the strategy's performance over time.
Visual Signals
The indicator plots buy and sell signals on the chart:
Buy Signals: Displayed as green triangles below the price bars.
Sell Signals: Displayed as red triangles above the price bars.
Performance Table
A customizable table is displayed on the chart, showing the performance metrics for each bar in the lookback period.
The table includes:
Win Rate: Highlighted with gradient colors (green for high win rates, red for low win rates).
Mean Return: Colored based on profitability (green for positive returns, red for negative returns).
Median Return: Colored similarly to the mean return.
Time Filtering
Users can define a specific time window for the indicator to analyze trades, ensuring that performance metrics are calculated only for the desired period.
Customizable Display
The table's font size can be adjusted to suit the user's preference, with options for "Auto," "Small," "Normal," and "Large."
█ PURPOSE
The Bollinger Bands Reversal Overlay is designed to:
Help traders identify high-probability reversal opportunities using Bollinger Bands.
Provide actionable insights into the performance of reversal-based strategies.
Enable users to backtest and optimize their trading strategies by analyzing historical performance metrics.
█ IDEAL USERS
Swing Traders: Looking for reversal opportunities within a trend.
Mean Reversion Traders: Interested in trading price reversals to the mean.
Strategy Developers: Seeking to backtest and refine Bollinger Bands-based strategies.
Performance Analysts: Wanting to evaluate the effectiveness of reversal signals over time.
ATR-Based Suitability CheckerPurpose:
This indicator helps traders identify the most suitable timeframe for trading by comparing fees to market volatility (ATR). Instead of filtering out specific assets or strategies, it focuses on finding optimal trading conditions for the selected timeframe. It is designed to adapt dynamically, ensuring that traders can align their approach with the current market environment.
Key Features:
Dynamic ATR Analysis: Measures volatility using the Average True Range (ATR) and evaluates how fees impact potential profitability across timeframes.
Fee-to-ATR Ratio: Calculates the proportion of fees to ATR, highlighting conditions where fees are too large relative to price movements.
Visual Feedback: **Red Background:** Indicates unsuitable trading conditions where fees dominate. **Green Background:** Highlights suitable conditions for trading efficiency. Markers provide quick visual identification of suitability.
Custom Transparency: Enables users to adjust the background’s transparency for better chart visibility.
How to Use:
Timeframe Optimization: When volatility rises, price movements become larger, making shorter timeframes more suitable for trading. Conversely, during periods of low volatility, longer timeframes are preferable to avoid overtrading within a narrow price range.
Spot & Leverage Trading: For spot trading, this tool identifies conditions where fees (e.g., 0.25%-0.3%) might excessively impact profitability. For instance, if ATR is comparable to fees, the trading environment may not be ideal. In leveraged trading, the indicator helps assess whether the current volatility supports your chosen leverage level, ensuring that leverage does not amplify undue risks.
Efficiency Focus: The indicator emphasizes finding a balance between market conditions and your trading strategy. Not all timeframes need to be "suitable" at all times; instead, it highlights the best opportunities based on current market dynamics. Utilize the suitability ratio across different timeframes to guide and adjust your trading strategies effectively.
Input Parameters:
ATR Length: Defines the period for ATR calculation (default: 14).
Fee Percentage (%): Trading fee as a percentage of the closing price (default: 0.1%).
Unsuitable Threshold (% of 1 ATR): Sets the maximum acceptable fee-to-ATR ratio for suitable conditions (default: 20%).
Background Transparency (0-100): Adjusts the opacity of the background highlight (default: 80).
Who Should Use This:
This tool is ideal for traders seeking to align their strategy with market conditions by finding the most suitable timeframe. It applies to both spot and leveraged markets, helping optimize efficiency while managing fees and volatility.
Notes:
The ATR-Based Suitability Checker is a supplementary tool. Combine it with other forms of analysis for comprehensive decision-making.
Regularly adjust the parameters to match your trading preferences and market conditions.
MMXM ICT [TradingFinder] Market Maker Model PO3 CHoCH/CSID + FVG🔵 Introduction
The MMXM Smart Money Reversal leverages key metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, Market Structure Shift (MSS) or (ChoCh), CISD, and Fair Value Gap (FVG) to identify critical turning points in the market. Designed for traders aiming to analyze the behavior of major market participants, this setup pinpoints strategic areas for making informed trading decisions.
The document introduces the MMXM model, a trading strategy that identifies market maker activity to predict price movements. The model operates across five distinct stages: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. This systematic approach allows traders to differentiate between buyside and sellside curves, offering a structured framework for interpreting price action.
Market makers play a pivotal role in facilitating these movements by bridging liquidity gaps. They continuously quote bid (buy) and ask (sell) prices for assets, ensuring smooth trading conditions.
By maintaining liquidity, market makers prevent scenarios where buyers are left without sellers and vice versa, making their activity a cornerstone of the MMXM strategy.
SMT Divergence serves as the first signal of a potential trend reversal, arising from discrepancies between the movements of related assets or indices. This divergence is detected when two or more highly correlated assets or indices move in opposite directions, signaling a likely shift in market trends.
Liquidity Sweep occurs when the market targets liquidity in specific zones through false price movements. This process allows major market participants to execute their orders efficiently by collecting the necessary liquidity to enter or exit positions.
The HTF PD Array refers to premium and discount zones on higher timeframes. These zones highlight price levels where the market is in a premium (ideal for selling) or discount (ideal for buying). These areas are identified based on higher timeframe market behavior and guide traders toward lucrative opportunities.
Market Structure Shift (MSS), also referred to as ChoCh, indicates a change in market structure, often marked by breaking key support or resistance levels. This shift confirms the directional movement of the market, signaling the start of a new trend.
CISD (Change in State of Delivery) reflects a transition in price delivery mechanisms. Typically occurring after MSS, CISD confirms the continuation of price movement in the new direction.
Fair Value Gap (FVG) represents zones where price imbalance exists between buyers and sellers. These gaps often act as price targets for filling, offering traders opportunities for entry or exit.
By combining all these metrics, the Smart Money Reversal provides a comprehensive tool for analyzing market behavior and identifying key trading opportunities. It enables traders to anticipate the actions of major players and align their strategies accordingly.
MMBM :
MMSM :
🔵 How to Use
The Smart Money Reversal operates in two primary states: MMBM (Market Maker Buy Model) and MMSM (Market Maker Sell Model). Each state highlights critical structural changes in market trends, focusing on liquidity behavior and price reactions at key levels to offer precise and effective trading opportunities.
The MMXM model expands on this by identifying five distinct stages of market behavior: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. These stages provide traders with a detailed roadmap for interpreting price action and anticipating market maker activity.
🟣 Market Maker Buy Model
In the MMBM state, the market transitions from a bearish trend to a bullish trend. Initially, SMT Divergence between related assets or indices reveals weaknesses in the bearish trend. Subsequently, a Liquidity Sweep collects liquidity from lower levels through false breakouts.
After this, the price reacts to discount zones identified in the HTF PD Array, where major market participants often execute buy orders. The market confirms the bullish trend with a Market Structure Shift (MSS) and a change in price delivery state (CISD). During this phase, an FVG emerges as a key trading opportunity. Traders can open long positions upon a pullback to this FVG zone, capitalizing on the bullish continuation.
🟣 Market Maker Sell Model
In the MMSM state, the market shifts from a bullish trend to a bearish trend. Here, SMT Divergence highlights weaknesses in the bullish trend. A Liquidity Sweep then gathers liquidity from higher levels.
The price reacts to premium zones identified in the HTF PD Array, where major sellers enter the market and reverse the price direction. A Market Structure Shift (MSS) and a change in delivery state (CISD) confirm the bearish trend. The FVG then acts as a target for the price. Traders can initiate short positions upon a pullback to this FVG zone, profiting from the bearish continuation.
Market makers actively bridge liquidity gaps throughout these stages, quoting continuous bid and ask prices for assets. This ensures that trades are executed seamlessly, even during periods of low market participation, and supports the structured progression of the MMXM model.
The price’s reaction to FVG zones in both states provides traders with opportunities to reduce risk and enhance precision. These pullbacks to FVG zones not only represent optimal entry points but also create avenues for maximizing returns with minimal risk.
🔵 Settings
Higher TimeFrame PD Array : Selects the timeframe for identifying premium/discount arrays on higher timeframes.
PD Array Period : Specifies the number of candles for identifying key swing points.
ATR Coefficient Threshold : Defines the threshold for acceptable volatility based on ATR.
Max Swing Back Method : Choose between analyzing all swings ("All") or a fixed number ("Custom").
Max Swing Back : Sets the maximum number of candles to consider for swing analysis (if "Custom" is selected).
Second Symbol for SMT : Specifies the second asset or index for detecting SMT divergence.
SMT Fractal Periods : Sets the number of candles required to identify SMT fractals.
FVG Validity Period : Defines the validity duration for FVG zones.
MSS Validity Period : Sets the validity duration for MSS zones.
FVG Filter : Activates filtering for FVG zones based on width.
FVG Filter Type : Selects the filtering level from "Very Aggressive" to "Very Defensive."
Mitigation Level FVG : Determines the level within the FVG zone (proximal, 50%, or distal) that price reacts to.
Demand FVG : Enables the display of demand FVG zones.
Supply FVG : Enables the display of supply FVG zones.
Zone Colors : Allows customization of colors for demand and supply FVG zones.
Bottom Line & Label : Enables or disables the SMT divergence line and label from the bottom.
Top Line & Label : Enables or disables the SMT divergence line and label from the top.
Show All HTF Levels : Displays all premium/discount levels on higher timeframes.
High/Low Levels : Activates the display of high/low levels.
Color Options : Customizes the colors for high/low lines and labels.
Show All MSS Levels : Enables display of all MSS zones.
High/Low MSS Levels : Activates the display of high/low MSS levels.
Color Options : Customizes the colors for MSS lines and labels.
🔵 Conclusion
The Smart Money Reversal model represents one of the most advanced tools for technical analysis, enabling traders to identify critical market turning points. By leveraging metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, MSS, CISD, and FVG, traders can predict future price movements with precision.
The price’s interaction with key zones such as PD Array and FVG, combined with pullbacks to imbalance areas, offers exceptional opportunities with favorable risk-to-reward ratios. This approach empowers traders to analyze the behavior of major market participants and adopt professional strategies for entry and exit.
By employing this analytical framework, traders can reduce errors, make more informed decisions, and capitalize on profitable opportunities. The Smart Money Reversal focuses on liquidity behavior and structural changes, making it an indispensable tool for financial market success.
On-Chain Analysis [LuxAlgo]The On-Chain Analysis tool offers a comprehensive overview of essential on-chain metrics, enabling traders and investors to grasp the underlying activity and sentiment within the cryptocurrency market. By integrating metrics like wallet profitability, exchange flows, on-chain volume, social sentiment, and more into your charts, users can gain valuable insights into cryptocurrency network behavior, spot emerging trends, and better manage risk in the cryptocurrency market.
🔶 USAGE
🔹 On-Chain Analysis
When analyzing cryptocurrencies, several fundamental metrics are crucial for assessing the value and potential of a digital asset. This indicator is designed to help traders and analysts evaluate the markets by utilizing various data gathered directly from the blockchain. The gathered on-chain data includes wallet profitability, exchange flows, miner flows, on-chain volume, large buyers/sellers, market capitalization, market dominance, active addresses, total value locked (TVL), market value to realized value (MVRV), developer activity, social sentiment, holder behavior, and balance types.
Use wallet profitability and social sentiment metrics to gauge the overall mood of the market, helping to anticipate potential buying or selling pressure.
On-chain volume and active addresses provide insights into how actively a cryptocurrency is being used, indicating network health and adoption levels.
By tracking exchange flows and holder balance types, you can identify significant moves by whales or institutions, which may signal upcoming price shifts.
Market capitalization and miner flows give you an understanding of the supply side of the market, aiding in evaluating whether an asset is overvalued or undervalued.
The distribution of holdings among retail investors, whales, and institutional groups can greatly influence market dynamics. A large concentration of holdings by whales may indicate the potential for significant price swings, given their capacity to execute substantial trades. A higher proportion of institutional investors often suggests confidence in the asset's long-term potential, as these entities typically conduct thorough research before investing. While retail participation indicates broader adoption, it also introduces higher volatility, as these investors tend to be more reactive to market fluctuations.
Understanding the balance and behavior of short-term traders, mid-term cruisers, and long-term hodlers helps traders and analysts predict market trends and assess the underlying confidence in a particular cryptocurrency.
🔶 DETAILS
This script includes some of the most significant and insightful metrics in the crypto space, designed to evaluate and enhance trading decisions by assessing the value and growth potential of cryptocurrencies. The introduced metrics are:
🔹 Wallet Profitability
Definition: Represents the percentage distribution of addresses by profitability at the current price.
Importance: Indicates potential selling pressure or reduced selling pressure based on whether addresses are in profit or loss.
🔹 Exchange Flow
Definition: The total amount of a cryptocurrency moving in and out of exchanges.
Importance: Large inflows to exchanges can indicate potential selling pressure, while large outflows might suggest accumulation or long-term holding.
🔹 Miner Flow
Definition: Tracks the inflow and outflow of funds by miners.
Importance: High inflows could indicate selling pressure, whereas low inflows or outflows might reflect miner confidence.
🔹 On-Chain Volume
Definition: The total value of transactions conducted on a blockchain within a specific period.
Importance: On-chain volume reflects actual usage of the network, indicating how actively a cryptocurrency is being utilized for transactions.
🔹 Large Buyers/Sellers
Definition: Tracks the number of large buyers (bulls) and sellers (bears) based on transaction volume.
Importance: Comparing the number of large buyers (bulls) to large sellers (bears) helps gauge market trends and sentiment.
🔹 Market Capitalization
Definition: The total value of a cryptocurrency's circulating supply, calculated by multiplying the current price by the total supply.
Importance: Market cap is a key indicator of a cryptocurrency’s size and market dominance. It helps compare the relative size of different cryptocurrencies.
🔹 Market Dominance
Definition: Market dominance represents a cryptocurrency’s share of the total market capitalization of all cryptocurrencies. It is calculated by dividing the market cap of the cryptocurrency by the total market cap of the cryptocurrency market.
Importance: Market dominance is a crucial indicator of a cryptocurrency's influence and relative position in the market. It helps assess the strength of a cryptocurrency compared to others and provides insights into its market presence and potential influence.
Special Consideration: Since BTC and ETH dominance is relatively high compared to other cryptocurrencies, specific adjustments are made during the presentation of values and charts. When analyzing BTC, the total market capitalization is used. For ETH analysis, BTC is excluded from the total market cap. For any other cryptocurrency besides BTC and ETH, both BTC and ETH are excluded from the total market cap to provide a more accurate view.
🔹 Active Addresses
Definition: The number of unique addresses involved in transactions within a specific period.
Importance: A higher number of active addresses suggests greater network activity and user adoption, which can be a sign of a healthy ecosystem.
🔹 Total Value Locked (TVL)
Definition: The total value of assets locked in a decentralized finance (DeFi) protocol.
Importance: TVL is a key metric for DeFi platforms, indicating the level of trust and the amount of liquidity in a protocol.
🔹 Market Value to Realized Value (MVRV)
Definition: A ratio comparing the market cap to realized cap.
Importance: A high ratio may indicate overvaluation (potential selling), while a low ratio could signal undervaluation (potential buying).
🔹 Developer Activity
Definition: The level of activity on a cryptocurrency’s public repositories (e.g., GitHub).
Importance: Strong developer activity is a sign of ongoing innovation, updates, and a healthy project.
🔹 Social Sentiment
Definition: The general sentiment or mood of the community and investors as expressed on social media and forums.
Importance: Positive sentiment often correlates with price increases, while negative sentiment can signal potential downtrends.
🔹 Holder Balance (Behavior)
Definition: Distribution of addresses by holding behavior: Traders (short-term), Cruisers (mid-term), and Hodlers (long-term).
Importance: Helps predict market behavior based on different holder types.
🔹 Holder Balance (Type)
Definition: Distribution of cryptocurrency holdings among Retail (small holders), Whales (large holders), and Investors (institutional players).
Importance: Assesses the potential impact of different user groups on the market. A more decentralized distribution is generally viewed as positive, reducing the risk of price manipulation by large holders.
These metrics provide a comprehensive view of a cryptocurrency’s health, adoption, and potential for growth, making them essential for fundamental analysis in the crypto space.
🔶 SETTINGS
The script offers a range of customizable settings to tailor the analysis to your trading needs.
🔹 On-Chain Analysis
On-Chain Data: Choose the specific on-chain metric from the drop-down menu. Options include Wallet Profitability, Exchange Flow, Miner Flow, On-Chain Volume, Large Buyers/Sellers (Volume), Market Capitalization, Market Dominance, Active Addresses, Total Value Locked, Market Value to Realized Value, Developer Activity, Social Sentiment, Holder Balance (Behavior), and Holder Balance (Type).
Smoothing: Set the smoothing level to refine the displayed data. This can help in filtering out noise and getting a clearer view of trends.
Signal Line: Choose a signal line type (SMA, EMA, RMA, or None) and the length of the moving average for signal line calculation.
🔹 On-Chain Dashboard
On-Chain Stats: Toggle the display of the on-chain statistics.
Dashboard Size, Position, and Colors: Customize the size, position, and colors of the on-chain dashboard on the chart.
🔶 LIMITATIONS
Availability of on-chain data may vary and may not be accessible for all crypto assets.
🔶 RELATED SCRIPTS
Market-Sentiment-Technicals
Bullish Reversal Bar Strategy [Skyrexio]Overview
Bullish Reversal Bar Strategy leverages the combination of candlestick pattern Bullish Reversal Bar (description in Methodology and Justification of Methodology), Williams Alligator indicator and Williams Fractals to create the high probability setups. Candlestick pattern is used for the entering into trade, while the combination of Williams Alligator and Fractals is used for the trend approximation as close condition. Strategy uses only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator or the candlestick pattern invalidation to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Trend Trade Filter: strategy uses Alligator and Fractal combination as high probability trend filter.
Methodology
The strategy opens long trade when the following price met the conditions:
1.Current candle's high shall be below the Williams Alligator's lines (Jaw, Lips, Teeth)(all details in "Justification of Methodology" paragraph)
2.Price shall create the candlestick pattern "Bullish Reversal Bar". Optionally if MFI and AO filters are enabled current candle shall have the decreasing AO and at least one of three recent bars shall have the squat state on the MFI (all details in "Justification of Methodology" paragraph)
3.If price breaks through the high of the candle marked as the "Bullish Reversal Bar" the long trade is open at the price one tick above the candle's high
4.Initial stop loss is placed at the Bullish Reversal Bar's candle's low
5.If price hit the Bullish Reversal Bar's low before hitting the entry price potential trade is cancelled
6.If trade is active and initial stop loss has not been hit, trade is closed when the combination of Alligator and Williams Fractals shall consider current trend change from upward to downward.
Strategy settings
In the inputs window user can setup strategy setting:
Enable MFI (if true trades are filtered using Market Facilitation Index (MFI) condition all details in "Justification of Methodology" paragraph), by default = false)
Enable AO (if true trades are filtered using Awesome Oscillator (AO) condition all details in "Justification of Methodology" paragraph), by default = false)
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. The first and key concept is the Bullish Reversal Bar candlestick pattern. This is just the single bar pattern. The rules are simple:
Candle shall be closed in it's upper half
High of this candle shall be below all three Alligator's lines (Jaw, Lips, Teeth)
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
How we can use all these indicators in this strategy? This strategy is a counter trend one. Candle's high shall be below all Alligator's lines. During this market stage the bullish reversal bar candlestick pattern shall be printed. This bar during the downtrend is a high probability setup for the potential reversal to the upside: bulls were able to close the price in the upper half of a candle. The breaking of its high is a high probability signal that trend change is confirmed and script opens long trade. If market continues going down and break down the bullish reversal bar's low potential trend change has been invalidated and strategy close long trade.
If market really reversed and started moving to the upside strategy waits for the trend change form the downtrend to the uptrend according to approximation of Alligator and Fractals combination. If this change happens strategy close the trade. This approach helps to stay in the long trade while the uptrend continuation is likely and close it if there is a high probability of the uptrend finish.
Optionally users can enable MFI and AO filters. First of all, let's briefly explain what are these two indicators. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
This indicator is filtering signals in the following way: if current AO bar is decreasing this candle can be interpreted as a bullish reversal bar. This logic is applicable because initially this strategy is a trend reversal, it is searching for the high probability setup against the current trend. Decreasing AO is the additional high probability filter of a downtrend.
Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -5.29%
Maximum Single Profit: +29.99%
Net Profit: +5472.66 USDT (+54.73%)
Total Trades: 103 (33.98% win rate)
Profit Factor: 1.634
Maximum Accumulated Loss: 1231.15 USDT (-8.32%)
Average Profit per Trade: 53.13 USDT (+0.94%)
Average Trade Duration: 76 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h ETH/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Financials Score All Description of the "Financials Score All" Script
This Pine Script calculates a financial score for a specific stock, based on various financial metrics. The purpose is to provide a comprehensive numerical score that reflects the financial health of the stock. The score is calculated using multiple financial indicators, including profitability, valuation, debt management, and liquidity. Here’s a breakdown of what each part of the script does:
period = input.string('FQ', 'Period', options= )
FQ refers to Quarterly financial data.
FY refers to Fiscal Year financial data.
Financial Metrics:
The script uses various financial metrics to calculate the score. These are obtained via request.financial, which retrieves financial data for the stock from TradingView's database. Below are the metrics used:
opmar (Operating Margin): Measures the company's profitability as a percentage of revenue.
eps (Earnings Per Share): Represents the portion of a company's profit allocated to each outstanding share.
eps_ttm (Earnings Per Share – Trailing Twelve Months): EPS over the most recent 12 months.
pe_ratio (Price-to-Earnings Ratio): A measure of the price investors are willing to pay for a stock relative to its earnings.
pb_ratio (Price-to-Book Ratio): A valuation ratio comparing a company’s market value to its book value.
de_ratio (Debt-to-Equity Ratio): A measure of the company’s financial leverage, showing how much debt it has compared to shareholders' equity.
roe_pb (Return on Equity Adjusted to Book): Measures the company's profitability relative to its book value.
fcf_per_share (Free Cash Flow per Share): Represents the free cash flow available for dividends, debt reduction, or reinvestment, per share.
pfcf_ratio (Price-to-Free-Cash-Flow Ratio): A measure comparing a company’s market value to its free cash flow.
current_ratio (Current Ratio): A liquidity ratio that measures a company's ability to pay short-term obligations with its current assets.
RSI Calculation:
The script calculates the Relative Strength Index (RSI) for the stock using an 8-period lookback:
rsi = ta.rsi(close, 8)
Score Calculation:
The script calculates a total score by adding points based on the values of the financial metrics. Each metric is checked against a condition, and if the condition is met, the score is incremented:
If the Operating Margin (opmar) is greater than 20, the score is incremented by 20 points.
If Earnings Per Share (EPS) is positive, 10 points are added.
If the P/E ratio is between 0 and 20, 10 points are added.
If the P/B ratio is less than 3, 10 points are added.
If the Debt-to-Equity ratio is less than 0.8, 10 points are added.
If the Return on Equity Adjusted to Book is greater than 10, 10 points are added.
If the P/FCF ratio is between 0 and 15, 10 points are added.
If the Current Ratio is greater than 1.61, 10 points are added.
If the RSI is less than 35, 10 points are added.
The score is accumulated based on these conditions and stored in the total_score variable.
Displaying the Total Score:
Finally, the total score is plotted on the chart:
Summary of How It Works:
This script calculates a financial score for a stock using a variety of financial indicators. Each metric has a threshold, and when the stock meets certain criteria (for example, a good operating margin, a healthy debt-to-equity ratio, or a low P/E ratio), points are added to the overall score. The result is a single numerical value that reflects the financial health of the stock.
This score can help traders or investors identify companies with strong financials, or serve as a comparison tool between different stocks based on their financial health.
Generally >60 is the best stocks for med and long term trades
Omega_galskyThe strategy uses three Exponential Moving Averages (EMAs) — EMA8, EMA21, and EMA89 — to decide when to open buy or sell trades. It also includes a mechanism to move the Stop Loss (SL) to the Break-Even (BE) point, which is the entry price, once the price reaches a Risk-to-Reward (R2R) ratio of 1:1.
Key Steps:
Calculating EMAs: The script computes the EMA values for the specified periods. These help identify market trends and potential entry points.
Buy Conditions:
EMA8 crosses above EMA21.
The candle that causes the crossover is green (closing price is higher than the opening price).
The closing price is above EMA89.
If all conditions are met, a buy order is executed.
Sell Conditions:
EMA8 crosses below EMA21.
The candle that causes the crossover is red (closing price is lower than the opening price).
The closing price is below EMA89.
If all conditions are met, a sell order is executed.
Stop Loss and Take Profit:
Initial Stop Loss and Take Profit levels are calculated based on the entry price and a percentage defined by the user.
These levels help protect against large losses and lock in profits.
Break-Even Logic:
When the price moves favorably to reach a 1:1 R2R ratio:
For a buy trade, the Stop Loss is moved to the entry price if the price increases sufficiently.
For a sell trade, the Stop Loss is moved to the entry price if the price decreases sufficiently.
This ensures the trade is risk-free after the price reaches the predefined level.
Visual Representation:
The EMAs are plotted on the chart for easy visualization of trends and crossovers.
Entry and exit points are also marked on the chart to track trades.
Purpose:
The strategy is designed to capitalize on EMA crossovers while minimizing risks using Break-Even logic and predefined Stop Loss/Take Profit levels. It automates decision-making for trend-following traders and ensures disciplined risk management.
HOD/LOD/PMH/PML/PDH/PDL Strategy by @tradingbauhaus This script is a trading strategy @tradingbauhaus designed to trade based on key price levels, such as the High of Day (HOD), Low of Day (LOD), Premarket High (PMH), Premarket Low (PML), Previous Day High (PDH), and Previous Day Low (PDL). Below, I’ll explain in detail what the script does:
Core Functionality of the Script:
Calculates Key Price Levels:
HOD (High of Day): The highest price of the current day.
LOD (Low of Day): The lowest price of the current day.
PMH (Premarket High): The highest price during the premarket session (before the market opens).
PML (Premarket Low): The lowest price during the premarket session.
PDH (Previous Day High): The highest price of the previous day.
PDL (Previous Day Low): The lowest price of the previous day.
Draws Horizontal Lines on the Chart:
Plots horizontal lines on the chart for each key level (HOD, LOD, PMH, PML, PDH, PDL) with specific colors for easy visual identification.
Defines Entry and Exit Rules:
Long Entry (Buy): If the price crosses above the PMH (Premarket High) or the PDH (Previous Day High).
Short Entry (Sell): If the price crosses below the PML (Premarket Low) or the PDL (Previous Day Low).
Long Exit: If the price reaches the HOD (High of Day) during a long position.
Short Exit: If the price reaches the LOD (Low of Day) during a short position.
How the Script Works Step by Step:
Calculates Key Levels:
Uses the request.security function to fetch the HOD and LOD of the current day, as well as the highs and lows of the previous day (PDH and PDL).
Calculates the PMH and PML during the premarket session (before 9:30 AM).
Plots Levels on the Chart:
Uses the plot function to draw horizontal lines on the chart representing the key levels (HOD, LOD, PMH, PML, PDH, PDL).
Each level has a specific color for easy identification:
HOD: White.
LOD: Purple.
PDH: Orange.
PDL: Blue.
PMH: Green.
PML: Red.
Defines Trading Rules:
Uses conditions with ta.crossover and ta.crossunder to detect when the price crosses key levels.
Long Entry: If the price crosses above the PMH or PDH, a long position (buy) is opened.
Short Entry: If the price crosses below the PML or PDL, a short position (sell) is opened.
Long Exit: If the price reaches the HOD during a long position, the position is closed.
Short Exit: If the price reaches the LOD during a short position, the position is closed.
Executes Orders Automatically:
Uses the strategy.entry and strategy.close functions to open and close positions automatically based on the defined rules.
Advantages of This Strategy:
Based on Key Levels: Uses important price levels that often act as support and resistance.
Easy to Visualize: Horizontal lines on the chart make it easy to identify levels.
Automated: Entries and exits are executed automatically based on the defined rules.
Limitations of This Strategy:
Dependent on Volatility: Works best in markets with significant price movements.
False Crosses: There may be false crosses that generate incorrect signals.
No Advanced Risk Management: Does not include dynamic stop-loss or take-profit mechanisms.
How to Improve the Strategy:
Add Stop-Loss and Take-Profit: To limit losses and lock in profits.
Filter Signals with Indicators: Use RSI, MACD, or other indicators to confirm signals.
Optimize Levels: Adjust key levels based on the asset’s behavior.
In summary, this script is a trading strategy that operates based on key price levels, such as HOD, LOD, PMH, PML, PDH, and PDL. It is useful for traders who want to trade based on significant support and resistance levels.
Smart DCA Strategy (Public)INSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost.
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on
BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
IU Opening range Breakout StrategyIU Opening Range Breakout Strategy
This Pine Script strategy is designed to capitalize on the breakout of the opening range, which is a popular trading approach. The strategy identifies the high and low prices of the opening session and takes trades based on price crossing these levels, with built-in risk management and trade limits for intraday trading.
Key Features:
1. Risk Management:
- Risk-to-Reward Ratio (RTR):
Set a customizable risk-to-reward ratio to calculate target prices based on stop-loss levels.
Default: 2:1
- Max Trades in a Day:
Specify the maximum number of trades allowed per day to avoid overtrading.
Default: 2 trades in a day.
- End-of-Day Close:
Automatically closes all open positions at a user-defined session end time to ensure no overnight exposure.
Default: 3:15 PM
2. Opening Range Identification
- Opening Range High and Low:
The script detects the high and low of the first trading session using Pine Script's session functions.
These levels are plotted as visual guides on the chart:
- High: Lime-colored circles.
- Low: Red-colored circles.
3. Trade Entry Logic
- Long Entry:
A long trade is triggered when the price closes above the opening range high.
- Entry condition: Crossover of the price above the opening range high.
-Short Entry:
A short trade is triggered when the price closes below the opening range low.
- Entry condition: Crossunder of the price below the opening range low.
Both entries are conditional on the absence of an existing position.
4. Stop Loss and Take Profit
- Long Position:
- Stop Loss: Previous candle's low.
- Take Profit: Calculated based on the RTR.
- **Short Position:**
- **Stop Loss:** Previous candle's high.
- **Take Profit:** Calculated based on the RTR.
The strategy plots these levels for visual reference:
- Stop Loss: Red dashed lines.
- Take Profit: Green dashed lines.
5. Visual Enhancements
-Trade Level Highlighting:
The script dynamically shades the areas between the entry price and SL/TP levels:
- Red shading for the stop-loss region.
- Green shading for the take-profit region.
- Entry Price Line:
A silver-colored line marks the average entry price for active trades.
How to Use:
1.Input Configuration:
Adjust the Risk-to-Reward ratio, max trades per day, and session end time to suit your trading preferences.
2.Visual Cues:
Use the opening range high/low lines and shading to identify potential breakout opportunities.
3.Execution:
The strategy will automatically enter and exit trades based on the conditions. Review the plotted SL and TP levels to monitor the risk-reward setup.
Important Notes:
- This strategy is designed for intraday trading and works best in markets with high volatility during the opening session.
- Backtest the strategy on your preferred market and timeframe to ensure compatibility.
- Proper risk management and position sizing are essential when using this strategy in live markets.
Optimal MA FinderIntroduction to the "Optimal MA Finder" Indicator
The "Optimal MA Finder" is a powerful and versatile tool designed to help traders optimize their moving average strategies. This script combines flexibility, precision, and automation to identify the most effective moving average (MA) length for your trading approach. Whether you're aiming to improve your long-only strategy or implement a buy-and-sell methodology, the "Optimal MA Finder" is your go-to solution for enhanced decision-making.
What Does It Do?
The script evaluates a wide range of moving average lengths, from 10 to 500, to determine which one produces the best results based on historical data. By calculating critical metrics such as the total number of trades and the profit factor for each MA length, it identifies the one that maximizes profitability. It supports both simple moving averages (SMA) and exponential moving averages (EMA), allowing you to tailor the analysis to your preferred method.
The logic works by backtesting each MA length against the price data and assessing the performance under two strategies:
Buy & Sell: Includes both long and short trades.
Long Only: Focuses solely on long positions for more conservative strategies.
Once the optimal MA length is identified, the script overlays it on the chart, highlighting periods when the price crosses over or under the optimal MA, helping traders identify potential entry and exit points.
Why Is It Useful?
This indicator stands out for its ability to automate a task that is often labor-intensive and subjective: finding the best MA length. By providing a clear, data-driven answer, it saves traders countless hours of manual testing while significantly enhancing the accuracy of their strategies. For example, instead of guessing whether a 50-period EMA is more effective than a 200-period SMA, the "Optimal MA Finder" will pinpoint the exact length and type of MA that has historically yielded the best results for your chosen strategy.
Key Benefits:
Precision: Identifies the MA length with the highest profit factor for maximum profitability.
Automation: Conducts thorough backtesting without manual effort.
Flexibility: Adapts to your preferred MA type (SMA or EMA) and trading strategy (Buy & Sell or Long Only).
Real-Time Feedback: Provides actionable insights by plotting the optimal MA directly on your chart and highlighting relevant trading periods.
Example of Use: Imagine you're trading a volatile stock and want to optimize your long-only strategy. By applying the "Optimal MA Finder," you discover that a 120-period EMA results in the highest profit factor. The indicator plots this EMA on your chart, showing you when to consider entering or exiting positions based on price movements relative to the EMA.
In short, the "Optimal MA Finder" empowers traders by delivering data-driven insights and improving the effectiveness of trading strategies. Its clear logic, combined with robust automation, makes it an invaluable tool for both novice and experienced traders seeking consistent results.
Triple CCI Strategy MFI Confirmed [Skyrexio]Overview
Triple CCI Strategy MFI Confirmed leverages 3 different periods Commodity Channel Index (CCI) indicator in conjunction Money Flow Index (MFI) and Exponential Moving Average (EMA) to obtain the high probability setups. Fast period CCI is used for having the high probability to enter in the direction of short term trend, middle and slow period CCI are used for confirmation, if market now likely in the mid and long-term uptrend. MFI is used to confirm trade with the money inflow/outflow with the high probability. EMA is used as an additional trend filter. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Four layers trade filtering system: Strategy utilizes two different period CCI indicators, MFI and EMA indicators to confirm the signals produced by fast period CCI.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Fast period CCI shall crossover the zero-line.
Slow and Middle period CCI shall be above zero-lines.
Price shall close above the EMA. Crossover is not obligatory
MFI shall be above 50
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 14, used for calculation short term period CCI)
CCI Middle Length (by default = 25, used for calculation short term period CCI)
CCI Slow Length (by default = 50, used for calculation long term period CCI)
MFI Length (by default = 14, used for calculation MFI
EMA Length (by default = 50, period of EMA, used for trend filtering EMA calculation)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI, MFI and EMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator that measures the deviation of a security's price from its average price over a specific period. It helps traders identify overbought or oversold conditions and potential trend reversals.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Money Flow Index (MFI) is a technical indicator that measures the strength of money flowing into and out of a security. It combines price and volume data to assess buying and selling pressure and is often used to identify overbought or oversold conditions. The formula for MFI involves several steps:
1. Calculate the Typical Price (TP):
TP = (high + low + close) / 3
2. Calculate the Raw Money Flow (RMF):
Raw Money Flow = TP × Volume
3. Determine Positive and Negative Money Flow:
If the current TP is greater than the previous TP, it's Positive Money Flow.
If the current TP is less than the previous TP, it's Negative Money Flow.
4. Calculate the Money Flow Ratio (MFR):
Money Flow Ratio = Sum of Positive Money Flow (over n periods) / Sum of Negative Money Flow (over n periods)
5. Calculate the Money Flow Index (MFI):
MFI = 100 − (100 / (1 + Money Flow Ratio))
MFI above 80 can be considered as overbought, below 20 - oversold.
The Exponential Moving Average (EMA) is a type of moving average that places greater weight and significance on the most recent data points. It is widely used in technical analysis to smooth price data and identify trends more quickly than the Simple Moving Average (SMA).
Formula:
1. Calculate the multiplier
Multiplier = 2 / (n + 1) , Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
This strategy leverages Fast period CCI, which shall break the zero line to the upside to say that probability of short term trend change to the upside increased. This zero line crossover shall be confirmed by the Middle and Slow periods CCI Indicators. At the moment of breakout these two CCIs shall be above 0, indicating that there is a high probability that price is in middle and long term uptrend. This approach increases chances to have a long trade setup in the direction of mid-term and long-term trends when the short-term trend starts to reverse to the upside.
Additionally strategy uses MFI to have a greater probability that fast CCI breakout is confirmed by this indicator. We consider the values of MFI above 50 as a higher probability that trend change from downtrend to the uptrend is real. Script opens long trades only if MFI is above 50. As you already know from the MFI description, it incorporates volume in its calculation, therefore we have another one confirmation factor.
Finally, strategy uses EMA an additional trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses another one EMA (by default = 20 period) as a trailing profit level.
Backtest Results
Operating window: Date range of backtests is 2022.04.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -4.13%
Maximum Single Profit: +19.66%
Net Profit: +5421.21 USDT (+54.21%)
Total Trades: 108 (44.44% win rate)
Profit Factor: 2.006
Maximum Accumulated Loss: 777.40 USDT (-7.77%)
Average Profit per Trade: 50.20 USDT (+0.85%)
Average Trade Duration: 44 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Breaks and Retests - Free990Strategy Description: "Breaks and Retests - Free990"
The "Breaks and Retests - Free990" strategy is based on identifying breakout and retest opportunities for potential entries in both long and short trades. The idea is to detect price breakouts above resistance levels or below support levels, and subsequently identify retests that confirm the breakout levels. The strategy offers an automated approach to enter trades after a breakout followed by a retest, which serves as a confirmation of trend continuation.
Key Components:
Support and Resistance Detection:
The strategy calculates pivot levels based on historical price movements to define support and resistance areas. A lookback range is used to determine these key levels.
Breakouts and Retests:
The system identifies when a breakout occurs above a resistance level or below a support level.
It then waits for a retest of the previously broken level as confirmation, which is often a better entry opportunity.
Trade Direction Selection:
Users can choose between "Long Only," "Short Only," or "Both" directions for trading based on their market view.
Stop Loss and Trailing Stop:
An initial stop loss is placed at a defined percentage away from the entry.
The trailing stop loss is activated after the position gains a specified percentage in profit.
Long Entry:
A long entry is triggered if the price breaks above a resistance level and subsequently retests that level successfully.
The entry condition checks if the breakout was confirmed and if a retest was valid.
The long entry is only executed if the user-selected direction is either "Long Only" or "Both."
Short Entry:
A short entry is triggered if the price breaks below a support level and subsequently retests that level.
The short entry is only executed if the user-selected direction is either "Short Only" or "Both."
sell_condition checks whether the support has been broken and whether the retest condition is valid.
An initial stop loss is placed when the trade is opened to limit the risk if the trade moves against the position.
The stop loss is calculated based on a user-defined percentage (stop_loss_percent) of the entry price.
pinescript
Copy code
stop_loss_price := strategy.position_avg_price * (1 - stop_loss_percent / 100)
For long positions, the stop loss is placed below the entry price.
For short positions, the stop loss is placed above the entry price.
Trailing Stop:
When a position achieves a certain profit threshold (profit_threshold_percent), the trailing stop mechanism is activated.
For long positions, the trailing stop follows the highest price reached, ensuring that some profit is locked in if the price reverses.
For short positions, the trailing stop follows the lowest price reached.
Code Logic for Trailing Stop:
Exit Execution:
The strategy exits the position when the price hits the calculated stop loss level.
This includes both the initial stop loss and the trailing stop that adjusts as the trade progresses.
Code Logic for Exit:
Summary:
Breaks and Retests - Free990 uses support and resistance levels to identify breakouts, followed by retests for confirmation.
Entry Points: Triggered when a breakout is confirmed and a retest occurs, for both long and short trades.
Exit Points:
Initial Stop Loss: Limits risk for both long and short trades.
Trailing Stop Loss: Locks in profits as the price moves in favor of the position.
This strategy aims to capture the momentum after breakouts and minimize losses through effective use of stop loss and trailing stops. It gives the flexibility of selecting trade direction and ensures trades are taken with confirmation through the retest, which helps to reduce false breakouts.
Original Code by @HoanGhetti
