Johnny's Adjusted BB Buy/Sell Signal"Johnny's Adjusted BB Buy/Sell Signal" leverages Bollinger Bands and moving averages to provide dynamic buy and sell signals based on market conditions. This indicator is particularly useful for traders looking to identify strategic entry and exit points based on volatility and trend analysis.
How It Works
Bollinger Bands Setup: The indicator calculates Bollinger Bands using a specified length and multiplier. These bands serve to identify potential overbought (upper band) or oversold (lower band) conditions.
Moving Averages: Two moving averages are calculated — a trend moving average (trendMA) and a long-term moving average (longTermMA) — to gauge the market's direction over different time frames.
Market Phase Determination: The script classifies the market into bullish or bearish phases based on the relationship of the closing price to the long-term moving average.
Strong Buy and Sell Signals: Enhanced signals are generated based on how significantly the price deviates from the Bollinger Bands, coupled with the average candle size over a specified lookback period. The signals are adjusted based on whether the market is bullish or bearish:
In bullish markets, a strong buy signal is triggered if the price significantly drops below the lower Bollinger Band. Conversely, a strong sell signal is activated when the price rises well above the upper band.
In bearish markets, these signals are modified to be more conservative, adjusting the thresholds for triggering strong buy and sell signals.
Features:
Flexibility: Users can adjust the length of the Bollinger Bands and moving averages, as well as the multipliers and factors that determine the strength of buy and sell signals, making it highly customizable to different trading styles and market conditions.
Visual Aids: The script vividly plots the Bollinger Bands and moving averages, and signals are visually represented on the chart, allowing traders to quickly assess trading opportunities:
Regular buy and sell signals are indicated by simple shapes below or above price bars.
Strong buy and sell signals are highlighted with distinctive colors and placed prominently to catch the trader's attention.
Background Coloring: The background color changes based on the market phase, providing an immediate visual cue of the market's overall sentiment.
Usage:
This indicator is ideal for traders who rely on technical analysis to guide their trading decisions. By integrating both Bollinger Bands and moving averages, it provides a multi-faceted view of market trends and volatility, making it suitable for identifying potential reversals and continuation patterns. Traders can use this tool to enhance their understanding of market dynamics and refine their trading strategies accordingly.
Ketidakstabilan
Daily Chart ATR & Movement %This Pine Script, titled "Daily ATR & Movement %," is designed for traders looking to gauge volatility and price movements relative to that volatility directly on their trading chart. The script calculates and displays the Average True Range (ATR) over a 14-day period using daily data, alongside the percentage movement of the current price from the previous day's close, scaled by the ATR. These metrics provide a snapshot of daily volatility and the magnitude of price movements within that context, which can be crucial for making informed trading decisions, especially in markets where volatility is a significant factor.
Key Features:
Daily ATR Calculation: Utilizes the ta.atr(14) function to compute the Average True Range on a daily basis, which measures market volatility by decomposing the entire range of asset prices for that day.
Movement Percentage: The script calculates the movement from yesterday’s closing price to today’s current price as a percentage of the daily ATR. This shows how significant today's price change is relative to the typical daily volatility, which helps in understanding whether the price movement is substantial or trivial.
Customizable Label Display: Traders can customize the display through a user input dropdown menu for label size ("small", "normal", "large", "huge") and a slider for vertical offset. This allows for better visibility and customization based on user preference and screen setup.
Dynamic Label Updates: A label is dynamically updated each bar with the latest ATR value and movement percentage. This ongoing update keeps traders informed in real-time without manual recalculations.
How to Use:
Setup: Apply the indicator to any chart.
Customization: Adjust the label size and vertical position to suit your viewing preference using the script’s input options.
Interpretation: Monitor the displayed ATR value and movement percentage to assess volatility and relative price movements. High percentages could indicate significant moves worth trading, while low percentages suggest minor changes.
This script is particularly useful for traders who rely on volatility-based trading strategies, such as breakout trading, where understanding the context of price movements relative to typical market fluctuations can provide a strategic edge.
ATR Stop Loss Zones [ziksfx]The indicator is a dynamic tool that helps traders identify potential stop-loss levels in trending markets. It calculates the Average True Range (ATR) and uses it to create upper and lower boxes around the closing price. These boxes visually represent potential stop-loss zones for long and short positions.
Originality and Usefulness:
This indicator stands out for its unique ability to dynamically adjust stop-loss zones based on market volatility using the ATR approach. This provides traders with a flexible and adaptable risk management tool that adapts to changing market conditions. By visually representing potential stop-loss levels, taking into account the inherent uncertainty of market movements, the indicator empowers traders to make informed decisions about placing stop loses ONLY in trend markets. This allows them to maximize profit potential while minimizing potential downside risk.
Functionality:
Calculates the ATR based on the closing price.
Creates upper and lower of box by adding and subtracting the ATR multiplied by a predefined multiplier (1.5) to the closing price, then generates dynamic boxes based on the upper and lower ATR values.
Indicator allows traders to choose to display boxes for long, short, or both positions simultaneously.
Enables customization of box colors to suit individual preferences and trading styles.
Can be used as a dynamic trailing stop-loss mechanism.
Long box: Enable or disable the display of box for long positions.
Short box: Enable or disable the display of box for short positions.
Color Long Box: Set the color of the box for long positions.
Color Short Box: Set the color of the box for short positions.
Disclaimer:
This information is for educational purposes only and should not be considered financial advice. Remember that trading involves risk, and you could lose money. Always do your own research and consult with a financial professional before making any investment decisions.
Consolidation Score ScreenerIn trading, a consolidation range is like a timeout after a big move in the price of a stock or symbol.
It's when the market takes a breather, neither pushing the price up nor down too hard.
Visually, it looks like the price moving sideways on a chart , with highs and lows staying within a certain range.
so this indicator is created to help myself and you decide if its a ranging market and what's the score of that consolidation range
The score ranges between 0 and 10 , where 10 is the max consolidation score , meaning this stock or the symbol is at its highest peak of consolidation .
What would you see using this indicator ?
Symbols circles , inside these circles it will print the consolidation score ..
in the middle of the indicator it will show the range of all the 20 symbols scores .
so it will give you like overall ranging value for your 20 symbols
Settings :
TimeFrame : TimeFrame input to select which time frame you want your indicator to analysis
Range length : The Range that you would want your indicator to take into consideration when doing its analysis .
Features :
20 symbols analysis
Multi timeframe capability
Enjoy .
Enhanced Predictive ModelThe "Enhanced Predictive Model" is a sophisticated TradingView indicator designed for traders looking for advanced predictive insights into market trends. This model leverages smoothed price data through an Exponential Moving Average (EMA) to ensure a more stable trend analysis and mitigate the effects of price volatility.
**Features of the Enhanced Predictive Model:**
- **Linear Regression Analysis**: Calculates a regression line over the smoothed price data to determine the prevailing market trend.
- **Predictive Trend Line**: Projects future market behavior by extending the current trend line based on the linear regression analysis.
- **EMA Smoothing**: Utilizes a dynamic smoothing mechanism to provide a clear view of the trend without the noise typically associated with raw price data.
- **Visual Trend Indicators**: Offers immediate visual cues through bar coloring, which changes based on the trend direction detected by the regression slope. Green indicates an uptrend, while red suggests a downtrend.
**Key Inputs:**
- **Regression Length**: Determines the number of bars used for the regression analysis, allowing customization based on the user's trading strategy.
- **EMA Length**: Sets the smoothing parameter for the EMA, balancing responsiveness and stability.
- **Future Bars Prediction**: Defines how many bars into the future the predictive line should extend, providing foresight into potential price movements.
- **Smoothing Length**: Adjusts the sensitivity of the trend detection, ideal for different market conditions.
This tool is ideal for traders focusing on medium to long-term trends and can be used across various markets, including forex, stocks, and cryptocurrencies. Whether you are a day trader or a long-term investor, the "Enhanced Predictive Model" offers valuable insights to help anticipate market moves and enhance your trading decisions.
**Usage Tips:**
- Best used in markets with moderate volatility for clearer trend identification.
- Combine with volume indicators or oscillators for a comprehensive trading strategy.
**Recommended for:**
- Trend Following
- Market Prediction
- Volatility Assessment
By employing this indicator, traders can not only follow the market trend but also anticipate changes, giving them a strategic edge in their trading activities.
speed of tradesThis indicator calculates the speed of trades, on other platform that is called speed of tape, but they said you need delta and others for the calculation.
Calculation method
This indicator calculates the number of trades per bar and filter it, if they are above a sma it highlights the column to know that could be a bar where there are more trades than usual.
It's based on an example of pinescript v5 user manual where explain the use of varip
HF Bots filter and common uses
know where there are more trades than usual help you to have an idea that could be HF Bots working on that bar, also if you dont belive on that, can also help you to have an idea of momentum or stoping action.
Why is this indicator original?
The speed of trades indicator give you an counter of number of trades and a filter for bars where there are a lot of trades, so searching speed of tape/trades indicator that don't exist on tradingview, this indicator is original.
How to charge data?
By default it doesn't load historical tick data, this indicator only works on realtime bars.
ATR Oscillator with DotsThe ATR Oscillator with Dots utilizes the Average True Range (ATR), a traditional measure that captures the extent of an asset's price movements within a given timeframe. Rather than depicting these values in a continuous line, the ATR Oscillator represents them as discrete dots, colored according to the price movement direction: green for upward movements when the current close is higher than the previous, and red for downward movements when the current close is lower.
In terms of functionality, the key feature of this oscillator is how it visualizes volatility through the spacing of the dots. During periods of high market volatility, the shifts between red and green dots tend to occur more frequently and with greater disparity in their positioning along the oscillator’s axis. This indicates sharp price changes and high trading activity. Conversely, periods of market consolidation are characterized by fewer color changes and a more clustered arrangement of dots, reflecting less price movement and lower volatility.
Traders can leverage the insights from the ATR Oscillator with Dots to better understand the market's behavior. For instance, a tight clustering of dots around the zero line suggests a consolidation phase, where the price is relatively stable and may be preparing for a breakout. On the other hand, widely spaced dots alternating between red and green signify strong price movements, offering opportunities for traders to capitalize on trends or prepare for potential reversals.
Imagine a scenario where a trader is monitoring a currency pair in a fluctuating forex market. An observed increase in the frequency and gap of alternating red and green dots would suggest a rise in volatility, possibly triggered by economic news or events. This could be an optimal time for the trader to seek entry or exit points, aligning their strategy with the increased activity. Conversely, a reduction in the frequency and gap of dot changes could signal an impending consolidation phase, prompting the trader to adopt a more cautious approach or explore range-bound trading strategies.
Therefore, the ATR Oscillator with Dots not only simplifies the interpretation of volatility and price momentum through visual cues but also enriches the trader’s strategy by highlighting periods of high activity and consolidation. This tool can be crucial for making informed decisions, particularly in fast-moving or uncertain market conditions, and can be effectively paired with other indicators to confirm trends and refine trading tactics.
Multi-Timeframe Trend TableThe "Multi-Timeframe Trend Table" indicator is a tool that consolidates a variety of critical trading metrics into a single, easy-to-read table format. This indicator is especially useful for traders who need to analyze multiple timeframes and indicators simultaneously to make informed trading decisions. By displaying a broad spectrum of data including trend information, rangebound status, volatility levels, VWAP (Volume Weighted Average Price), and specific candlestick patterns, the indicator provides a comprehensive overview of market conditions across different timeframes.
Functionality and Components
At its core, the indicator provides real-time insights into market trends by showing whether each timeframe is experiencing an upward, downward, or neutral trend based on simple moving averages. This is complemented by the "Rangebound" status, which indicates whether the price is trading within a defined range, giving insights into market consolidation periods. This can be critical for identifying breakouts or breakdowns from established ranges.
Volatility Measurement
Another key feature of the indicator is the "Volatility" column, which rates the market's volatility on a scale from 1 to 10. This feature uses the Average True Range (ATR) to assess how drastically prices are changing within a given timeframe, providing a numerical value that helps traders understand the intensity of price movements. High volatility levels (scores above 6) are highlighted, which can be crucial for strategies that prefer high volatility.
VWAP and Candlestick Patterns
The indicator also displays the VWAP, which is essential for traders who focus on volume as it shows the average price a security has traded at throughout the day, based on both volume and price. It is especially useful for traders looking to confirm trend directions or catch potential reversals. Additionally, the "Candle" column enhances the indicator's utility by identifying specific candlestick patterns like Doji, Hammer, Inverted Hammer, Bullish Engulfing, and Bearish Engulfing, which are pivotal for pinpointing momentum changes and potential entry or exit points.
Usage Strategy
Traders can utilize this indicator by setting up specific rules based on the information provided. For instance, a possible strategy could involve entering a trade when a Bullish Engulfing pattern appears in a low-volatility environment as indicated by a volatility score under 6, suggesting a potential uptrend start with limited downside risk. Similarly, a trader might consider exiting a position or taking a short position when a Bearish Engulfing pattern is identified during high volatility periods, signaling possible sharp price declines.
Adaptability and Customization
An added advantage is the indicator’s adaptability; traders can customize which columns to display based on their trading preferences and strategies. Whether focusing on trends, volatility, or candlestick patterns, users can configure the table to match their specific needs. This makes it a versatile tool suited for various trading styles and objectives, from day trading to swing trading.
Overall Utility
Overall, the "Multi-Timeframe Trend Table" indicator is an invaluable asset for traders who manage multiple instruments across different timeframes, offering a bird's-eye view of the markets in one concise table. It aids in quick decision-making by providing all necessary data points at a glance, reducing the need to switch between multiple charts and potentially missing critical market movements. By integrating trend analysis with volatility and candlestick patterns, it equips traders with a powerful synthesis of technical analysis tools to enhance their trading strategies and improve market timing.
Stochastic Z-Score Oscillator Strategy [TradeDots]The "Stochastic Z-Score Oscillator Strategy" represents an enhanced approach to the original "Buy Sell Strategy With Z-Score" trading strategy. Our upgraded Stochastic model incorporates an additional Stochastic Oscillator layer on top of the Z-Score statistical metrics, which bolsters the affirmation of potential price reversals.
We also revised our exit strategy to when the Z-Score revert to a level of zero. This amendment gives a much smaller drawdown, resulting in a better win-rate compared to the original version.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
Following this, the Stochastic Oscillator is utilized to affirm the Z-Score overbought and oversold indicators. This indicator operates within a 0 to 100 range, so a base adjustment to match the Z-Score scale is required. Post Stochastic Oscillator calculation, we recalibrate the figure to lie within the -4 to 4 range.
Finally, we compute the average of both the Stochastic Oscillator and Z-Score, signaling overpriced or underpriced conditions when the set threshold of positive or negative is breached.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURAUD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Stochastic Length: 14
Stochastic Smooth Period: 7
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 40%
FURTHER IMPLICATION
The Stochastic Oscillator imparts minimal impact on the current strategy. As such, it may be beneficial to adjust the weightings between the Z-Score and Stochastic Oscillator values or the scale of Stochastic Oscillator to test different performance outcomes.
Alternative momentum indicators such as Keltner Channels or RSI could also serve as robust confirmations of overbought and oversold signals when used for verification.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Uptrick: Bullish/Bearish Highlight -DEMO 1 Indicator Purpose:
• The indicator serves as a technical analysis tool for traders to identify potential bullish
and bearish trends in the market.
• It highlights periods where the closing price is above or below a 50-period simple
moving average (SMA), indicating potential bullish or bearish sentiment, respectively.
2 Moving Averages:
• The indicator calculates a 50-period SMA (sma50) to smooth out price fluctuations
and identify the overall trend direction.
• It also computes an 8-period exponential moving average (EMA), which responds
more quickly to recent price changes compared to the SMA.
3 Bollinger Bands:
• Bollinger Bands are plotted around the SMA, indicating volatility in the price
movement.
• The bands are typically set at two standard deviations above and below the SMA,
representing approximately 95% of the price data within that range.
4 Bullish and Bearish Conditions:
• The indicator defines conditions for identifying bullish and bearish market sentiments.
• When the closing price is above the SMA50, it indicates a bullish condition, and when
it's below, it suggests a bearish condition.
5 Plotting:
• The indicator visualizes the bullish and bearish conditions by changing the
background color accordingly.
• It also plots the SMA50, EMA, and Bollinger Bands to provide a graphical
representation of the market dynamics.
6 User Interface:
• The indicator is designed to be used as an overlay on price charts, allowing traders to
easily incorporate it into their analysis.
Overall, the "Uptrick: Bullish/Bearish Highlight" indicator offers traders a comprehensive view of market trends and potential reversal points, helping them make informed trading decisions.
TIP: When the white line, which is the EMA , crosses above the SMA (the orange line), it is usually a good idea to buy, but when the EMA crosses below the SMA it is a good idea to sell.
Garman-Klass-Yang-Zhang Volatility EstimatorThe Garman-Klass-Yang-Zhang Volatility Estimator (GKYZVE) is yet another attempt to robustly measure volatility, integrating intra-candle and inter-candle dynamics. It is an extension of the Garman-Klass Volatility Estimator (GKVE) incorporating insights from the Yang-Zhang Volatility Estimator (YZVE) . Like the YZVE, the GKYZVE holistically considers open, high, low, and close prices. The formula for GKYZ is:
GKYZVE = 0.5 * σ_HL² + * σ_CC² + σ_OC²
Where:
σ_HL² is the variance based on the high and low prices (σ_HL² = (high - low)² / (4 * math.log(2))), weighted at 0.5.
σ_CC² is the close-to-close variance (σ_CC² = (close - close)²), weighted at (2 ln 2) -1 for the logarithmic distribution of returns and emphasizing the impact of day-to-day price changes.
σ_OC² is the variance of the opening price against the closing price (σ_OC² = 0.5 * (open - close)²), weighted at 1.
The GKYZVE differs from the YZVE by using fixed weighing factors derived from theoretical calculations, leaning heavier into the assumption that returns are log-distributed.
This script also offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both options are off by default.
References:
Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. The Journal of Business, 53(1), 67-78.
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-492.
Volatility Estimator - YZ & RSThe Yang-Zheng Volatility Estimator (YZVE) integrates both intra-candle and inter-candle dynamics, such as overnight and weekend price changes, offering a more detailed analysis compared to traditional methods. The YZVE is proposed to improve over the standard deviation by accounting for the open, high, low, and close prices of trading periods, instead of only the close prices, and attempts to supplant the Parkinson's Volatility Estimator (PVE) by a also capturing inter-candle dynamics. The YZVE is calculated by this formula:
YZ Volatility Squared σ_YZ² = k * σ_o² + σ_rs² + (1 - k) * σ_c²
where k is a weighting factor that adjusts the emphasis between the overnight and close-to-close components, popularly estimated as:
k = 0.34 / (1.34 + (N+1) / (N-1))
where N is the lookback period. Optionally, users may opt to override this calculation with a specified constant (off by default). Next, the
Overnight Volatility Squared σ_o² = (log(O_t / C_(t-1)))²
measures the volatility associated with overnight price changes, from the previous candle's closing price C_(t-1) to the current candle's opening price O_t. It captures the market's reaction to news and events that occur outside of regular trading hours to reflect risk associated with holding positions over non-trading hours and gaps.
Next, the The Rogers-Satchell Volatility Estimator (RSVE) serves as an intermediary step in the computation of YZVE. It aggregates the logarithmic ratios between high, low, open, and close prices within each trading period, focusing on intra-candle volatility without assuming zero inter-candle drift as commonly implicitly assumed in other volatility models:
Rogers-Satchell Volatility Squared σ_rs² = (log(H_t / C_t) * log(H_t / O_t)) + (log(L_t / C_t) * log(L_t / O_t))
Finally,
Close-to-Close Volatility Squared σ_c² = (log(C_t / C_(t-1)))²
measures the volatility from the close of one candle to the close of the next. It reflects the typical candle volatility, similar to naive standard deviation.
This script also includes an option for users to apply the simpler RS Volatility exclusively, focusing on intraday price movements. Additionally, it offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both are off by default.
References:
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-491.
Rogers, L.C.G., & Satchell, S.E. (1991). Estimating variance from high, low and closing prices. Annals of Applied Probability, 1(4), 504-512.
Parkinson's Volatility EstimatorThe Parkinson's Volatility Estimator (PVE) provides an alternative method for assessing market volatility using the highest and lowest prices within a given period. Unlike traditional models that predominantly rely on closing prices, the PVE considers the full range of intra-candle price movements, thereby potentially offering a more comprehensive gauge of market volatility. The estimator is derived from the logarithm of the ratio of the high to low prices, squared and then averaged over the period of interest. This calculation is rooted in the assumption that the logarithmic high-to-low ratio represents a normalized measure of price movements, capturing both upward and downward volatility in a symmetric manner (Parkinson, 1980).
In this specific implementation, the estimator is calculated as follows:
Parkinson’s Volatility = (1/4 log(2)) * (1/n) * Σ from i=1 to n of (log(High_i/Low_i))^2
where n is the lookback period defined by the user, and High_i and Low_i are the highest and lowest prices at each interval i within that period. This formulation takes advantage of the logarithmic properties to scale the volatility measure appropriately, utilizing a factor of 1/4 log(2) to normalize the variance estimate (Parkinson, 1980).
This implementation includes options for output normalization between 0 and 1 and for plotting horizontal lines at specified levels, allowing the estimator to function like an oscillator to evaluate volatility relative to recent market regimes. Users can customize these features through script inputs, enhancing flexibility for various trading scenarios and improving its utility for real-time volatility assessments on the TradingView platform.
Reference:
Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. The Journal of Business, 53(1), 61-65.
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
Sector Rotation Hedging With Volatility Index [TradeDots]The "Sector Rotation Hedging Strategy With Volatility Index" is a comprehensive trading indicator developed to optimally leverage the S&P500 volatility index. It is designed to switch between distinct ETF sectors, strategically hedging to moderate risk exposure during harsh market volatility.
HOW DOES IT WORK
The core of this indicator is grounded on the S&P500 volatility index (VIX) close price and its 60-day moving average. This serves to determine whether the prevailing market volatility is above or below the quarterly average.
In periods of elevated market volatility, risk exposure escalates significantly. Traders retaining stocks in sectors with disproportionately high volatility face increased vulnerability to negative returns. To tackle this, our indicator employs a two-pronged approach utilizing two sequential candlestick close prices to confirm if volatility surpasses the average value.
Upon confirming above-average volatility, a hedging table is deployed to spotlight ETFs with low volatility, such as the Utilities Select Sector SPDR Fund (XLU), to derisk the overall portfolio.
Conversely, in low-volatility conditions, sectors yielding higher returns like the Technology Select Sector SPDR Fund (XLK) are preferred. The hedging table is utilized to earmark high-return sector ETFs.
Thus, during highly volatile market periods, the strategy recommends enhancing portfolio allocation to low-volatility ETFs. During low-volatility windows, the portfolio is calibrated towards high-volatility ETFs for heightened returns.
IMPORTANT CONSIDERATION
In real trading, additional considerations encompassing trading commissions, management fees, and ancillary rotation costs should be factored in. False signals may arise, potentially leading to losses from these fees.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Pullback_Power [JackTz]Welcome to Pullback_Power
Pullback_Power is a scalping strategy designed to capitalize on market retracements while incorporating unique dynamic features to enhance profitability.
Calculation
Pullback_Power purely uses moving averages to calculate both entry and exits. Exits can also be set to fixed percentages for both take profit and stop loss.
How the Strategy Works
Statistics show that markets normally do a recovery after each drop. Crypto markets can easily drop up to 20% within a few hours and then do a complete or partial recovery. Pullback_Power utilizes this known pattern alongside pyramiding. The strategy aims to catch one or more entries when the price drops, hoping to make profits when the market recovers from the drop. The fixed take profit and stop loss can be used to define your risk management, while the dynamic exit opportunity is riskier but provides the ability to stay in the trade longer while it recovers. Pullback_Power can make up to four entries. This means it utilizes pyramiding to spread out the entry points, but every exit is a full exit. It is not possible to partially exit.
Utility
Pullback_Power is a scalping strategy suitable for traders who operate with small trades and don't want to stay in the market for too long. Pullback_Power offers precise signals with no repainting. The strategy thrives in volatility, so crypto pairs might yield the best results, although this strategy can be adapted to work on all pairs and markets.
How to Automate It
Pullback_Power utilizes the standard placeholders of strategies on TradingView. This enables the trader to add every data point into a webhook, making it fully flexible to suit every trader's needs. To automate, create an alert, set the webhook URL, and add the JSON body needed for the webhook. An example of a simple JSON webhook with some of the standard strategy placeholders:
{
"side": "{{strategy.order.action}}",
"symbol": "{{ticker}}",
"amount": "{{strategy.order.contracts}}"
}
Read about all the standard placeholders that you can use here: TradingView - Standard strategy placeholders
Originality
Pullback_Power is unique in its ability to create precise signals without repainting while maintaining a solid approach to the pullback strategy. Its simplicity not only makes the strategy easy to use and understand but also highly effective. The simplicity reduces inputs, eliminating overfitting and limits each input to avoid incorrect usage. Many times, default settings are enough to achieve good backtesting results on almost all pairs available. Pullback_Power also differs from many other strategies by its solid code, which enhances performance and provides more reliable backtesting. The clean code increases the resilience and precision of the entries, making it less prone to errors.
Many pullback/scalping strategies normally only works on specific scopes of timeframes or pairs. Pullback_Power can easily be adapted to work on almost every scenario. The biggest change needed is the length of the moving average. The lower the timeframe, the higher a length is needed for proper results. I.e. on a 2H timeframe a length of 3 can yield good results. On a 5min timeframe the length might need to be as high as 70.
How to Use
To use Pullback_Power, add the script to your trading chart. By default, Pullback_Power opens four orders to optimize trade opportunities with a default fee value set at 0.1%. You can change these default settings in the Settings window under the Properties tab. To tailor Pullback_Power to your individual trading style, navigate to the Settings under the Input tab. Here you can configure various inputs to fit your trading style.
- Backtest settings , Start Date:
Defines the date of when the calculation starts. Use this to set the date of when the first trade could potentially emit.
- Backtest settings , End Date:
Defines the date of when the calculation ends. If there are any open trades after this date the close calculations are still live. It only makes sure that new orders cannot be opened after this date.
- Backtest settings , Only trade on weekdays:
This is a toggle you can enable or disable. If enabled it only allows new entries to happen during the normal week days, meaning Monday, Tuesday, Wednesday, Thursday and Friday.
Disable this to enable the script to open trades on all 7 days of the week.
- Open settings , Use dynamic long positions:
This toggle allows you to enable or disable the pullback level calculations after first trade.
If enabled, the calculations of level 2, 3 and 4 continues to happen after each bar, making the levels follow the price with the moving averages calculations.
If disabled, the calculations of the levels stop after the first trade. This means that the levels calculation at the point of the first trade stay fixed until all trades are closed.
You can see the difference of the green lines on the chart when you toggle this flag.
- Open settings , Data type:
This is the bar data used for the moving average calculation when opening trades. The possible data types are Open, High, Low, Close, HL2, HLC3, OHLC4, OC2 and HC2.
- Open settings , Source type:
This is the source used to calculate the moving average. The types available are: SMA, PCMA, EMA, WMA, DEMA, ZLEMA and HMA.
- Open settings , Length:
This is the length used for the moving average calculations. 3 means it takes the last 3 bars of historical data for the calculation.
- Open settings , Offset:
This defines if the calculation should use an offset for the historical data. This does not use a look-forward feature, but a look-backward feature. To prevent any possible repaints the offset can only be positive, not negative.
For instance, if the length is 3 and the offset is 0 the calculation is made from the last 3 bars, making it bar1, bar2 and bar3. If the length is 3 and the offset is 1 the calculation is made from bar2, bar3, and bar4 – offsetting the calculation by 1 bar.
- Leverage settings , Leverage liquidation (1-125):
The script itself does not handle any custom leverage calculation – this must be done in the Properties tabs and increasing the order size.
This setting is made to test a possible liquidation event if using leverage.
By setting this to higher than 1, a red line is visible after the first trade on the chart. This indicates the liquidation price.
If this setting is set to 25, the script will calculate the liquidation price from a x25 leverage. If this price is hit, the scripts stops emitting any orders and the background turns red.
You can use this to test if your settings could handle a certain level of leverage.
- Pullback settings , Pullback 1, 2, 3 and 4:
Each of these settings defines the entry price of each pullback level. If Pullback 1 is set to -6 it means that the moving average calculation should be 6% lower than the actual price.
The same logic applies to Pullback 2, 3 and 4.
Setting any level to 0 will disable the level – eliminating any orders to emit on that level.
This can be used to change the level of pyramiding down from 4 if needed.
If you do this, remember to also change the order size and the pyramiding value in the Properties tab accordingly.
- Close settings , Use dynamic TP and SL:
If enabled, script will exit all orders using the same but separate algorithm for moving averages. This enables the user to define if you want the orders to be closed if the price level of this moving average is hit. The price level for this calculation is visible on the chart by the blue line.
Although you can change the length and offset, as described underneath, this calculation uses the same data and source type defined in the Open settings area.
- Close settings , Length, Close:
This is the length used for the closing moving average calculations. 3 means it takes the last 3 bars of historical data for the calculation.
- Close settings , Offset, Close:
This defines if the calculation for the closing moving average should use an offset for the historical data. Just as the offset used for opening order, this does not use a look-forward feature, but a look-backward feature. To prevent any possible repaints the offset can only be positive, not negative.
For instance, if the length is 3 and the offset is 0 the calculation is made from the last 3 bars, making it bar1, bar2 and bar3. If the length is 3 and the offset is 1 the calculation is made from bar2, bar3, and bar4 – offsetting the calculation by 1 bar.
- Close settings , Use TakeProfit:
This toggle enables/disables a fixed take profit percentage.
- Close settings , TP %:
This sets the wanted % to reach on a take profit. This setting is ignored if the toggle above is disabled.
- Close settings , Use StopLoss:
This toggle enables/disables a fixed stop loss percentage.
- Close settings , SL %:
This sets the wanted % to reach on a stop loss. This setting is ignored if the toggle above is disabled.
Exit on Same Bar as Entry
By default, the script doesn't emit any exit orders on the same bar as the first entry order. Enable "Recalculation: After order is filled" to change this behavior.
Troubleshooting
While Pullback_Power is designed to provide reliable trading signals, you may encounter rare issues. One such issue could be receiving an error message stating "can't open orders with 0 or negative qty." If you encounter this error, it is likely due to specific conditions on the selected timeframe. To resolve this issue, change the timeframe on your trading chart.
Underlying Principles and Value Proposition
Pullback_Power leverages moving averages and volatility behavior to identify market retracements and capitalize on them. The strategy is rooted in the understanding that markets often experience temporary reversals or "pullbacks" before resuming their primary trend. By identifying these pullbacks and entering trades at opportune moments, Pullback_Power aims to capture quick profits from short-term market movements.
The dynamic and fixed calculations of Take Profit (TP) and Stop Loss (SL) levels enhances risk management, ensuring that potential losses are controlled while allowing room for profits to grow. The adaptive approach using the moving averages considers current market conditions, making the strategy flexible and responsive to changing volatility.
Moreover, Pullback_Power's non-repainting nature ensures the reliability of its signals, eliminating hindsight bias and providing traders with actionable insights based on real-time market data.
The strategy's simplicity and effectiveness make it accessible for traders of all experience levels. Whether you're a beginner looking to start scalping or an experienced trader seeking to diversify your trading approach, Pullback_Power offers a balanced blend of simplicity and sophistication to help you navigate the markets with confidence.
By focusing on clear, transparent principles and offering practical tools for risk management, Pullback_Power aims to provide tangible value to traders, empowering them to make informed decisions and optimize their trading outcomes.
Thank you for choosing Pullback_Power. I wish you successful trading!
Buy Sell Strategy With Z-Score [TradeDots]The "Buy Sell Strategy With Z-Score" is a trading strategy that harnesses Z-Score statistical metrics to identify potential pricing reversals, for opportunistic buying and selling opportunities.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
This approach provides an estimation of the price's departure from its traditional trajectory, thereby identifying market conditions conducive to an asset being overpriced or underpriced.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURUSD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Commission: 0.03%
Initial Capital: $10,000
Equity per Trade: 30%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Rise Sense Capital - RSI MACD Spot Buying IndicatorToday, I'll share a spot buying strategy shared by a member @KR陳 within the DATA Trader Alliance Alpha group. First, you need to prepare two indicators:
今天分享一個DATA交易者聯盟Alpha群組裏面的群友@KR陳分享的現貨買入策略。
首先需要準備兩個指標
RSI Indicator (Relative Strength Index) - RSI is a technical analysis tool based on price movements over a period of time to evaluate the speed and magnitude of price changes. RSI calculates the changes in price over a period to determine whether the recent trend is relatively strong (bullish) or weak (bearish).
RSI指標，(英文全名:Relative Strength Index)，中文稱為「相對強弱指標」，是一種以股價漲跌為基礎，在一段時間內的收盤價，用於評估價格變動的速度 (快慢) 與變化 (幅度) 的技術分析工具，RSI藉由計算一段期間內股價的漲跌變化，判斷最近的趨勢屬於偏強 (偏多) 還是偏弱 (偏空)。
MACD Indicator (Moving Average Convergence & Divergence) - MACD is a technical analysis tool proposed by Gerald Appel in the 1970s. It is commonly used in trading to determine trend reversals by analyzing the convergence and divergence of fast and slow lines.
MACD 指標 (Moving Average Convergence & Divergence) 中文名為平滑異同移動平均線指標，MACD 是在 1970 年代由美國人 Gerald Appel 所提出，是一項歷史悠久且經常在交易中被使用的技術分析工具，原理是利用快慢線的交錯，藉以判斷股價走勢的轉折。
In MACD analysis, the most commonly used values are 12, 26, and 9, known as MACD (12,26,9). The market often uses the MACD indicator to determine the future direction of assets and to identify entry and exit points.
在 MACD 的技術分析中，最常用的值為 12 天、26 天、9 天，也稱為 MACD (12,26,9)，市場常用 MACD 指標來判斷操作標的的後市走向，確定波段漲幅並找到進、出場點。
Strategy analysis by member KR陳:
策略解析 by群友 KR陳 ：
Condition 1: RSI value in the previous candle is below oversold zone(30).
條件1：RSI 在前一根的數值低於超賣區（30）
buycondition1 = RSI <30
Condition 2: MACD histogram changes from decreasing to increasing.
條件2：MACD柱由遞減轉遞增
buycondition2 = hist >hist and hist <hist
Strategy Effect Display:
策略效果展示：
Slight modification:
稍微修改：
I've added the ATR-MACD, developed earlier, as a filter signal alongside the classic MACD. The appearance of an upward-facing triangle indicates that the ATR MACD histogram also triggers the condition, aiming to serve as a filtering mechanism.
我在經典的macd作爲條件的同時 也加入了之前開發的ATR-MACD作爲過濾信號 出現朝上的三角圖示代表ATR MACD的柱狀圖一樣觸發條件 希望可以以此起到過濾的作用
Asset/Usage Instructions:
使用標的/使用説明
Through backtesting, it's found that it's not suitable for smaller time frames as there's a lot of noise. It's recommended to use it in assets with a long-term bullish view, focusing on time frames of 12 hours or longer such as 12H, 16H, 1D, 1W to find spot buying opportunities.
經過回測發現 并不適用與一些小級別時區 噪音會非常多，建議在一些長期看漲的標的中切入12小時以上的時區如12H，16H, 1D, 1W 中間尋找現貨買入的機會。
A few thoughts:
Overall, it's a very good indicator strategy for spot buying in the physical market. Thanks to member @KR陳 for sharing!
一些小感言 綜合來看是一個針對現貨買入非常好的指標策略，感謝群友@KR陳的分享！
DSI - Depth Strength IndexDescription:
The DSI consists of three primary components:
Mid-Term Line (MTL): Captures medium-term price movements over a 50-candle period, optimized for swift response to trend changes.
Long-Term Line (LTL): Analyzes price extremes over a longer period of 500 candles, providing a comprehensive view of long-term trends and stabilizing signals by filtering out short-term fluctuations.
Volume-adjusted RSI: Enhances the traditional Relative Strength Index (RSI) by incorporating volume data, improving the detection of bullish and bearish divergences.
Functioning:
MTL: Utilizes price extremes over 50 candles to identify medium-term trends.
LTL: Analyzes price extremes over 500 candles to identify long-term trends and stabilize signals.
Volume-adjusted RSI: Incorporates volume data to provide more accurate signals of market forces.
Application of MA: The MTL and LTL are recalculated using Moving Average to enhance signal clarity and reduce lag.
Advantages:
Increased Responsiveness and Precision: Adapts to various market conditions and enhances signal relevance for different trading strategies.
Noise Reduction: The application of MA helps clarify market trends, reducing false signals.
Visual Usage Guide:
Accelerating Trend: MTL crossing above LTL indicates increased momentum in the trend.
Trend Weakening: MTL crossing below LTL suggests the current trend is losing strength.
Reversal Trade Opportunity: MTL trending while LTL remains flat indicates potential for reversal, suggesting MTL may align with LTL soon.
Volatile Sideways Market: Conflicting directions between MTL and LTL signal a volatile, sideways market.
Price Prediction With Rolling Volatility [TradeDots]The "Price Prediction With Rolling Volatility" is a trading indicator that estimates future price ranges based on the volatility of price movements within a user-defined rolling window.
HOW DOES IT WORK
This indicator utilizes 3 types of user-provided data to conduct its calculations: the length of the rolling window, the number of bars projecting into the future, and a maximum of three sets of standard deviations.
Firstly, the rolling window. The algorithm amasses close prices from the number of bars determined by the value in the rolling window, aggregating them into an array. It then calculates their standard deviations in order to forecast the prospective minimum and maximum price values.
Subsequently, a loop is initiated running into the number of bars into the future, as dictated by the second parameter, to calculate the maximum price change in both the positive and negative direction.
The third parameter introduces a series of standard deviation values into the forecasting model, enabling users to dictate the volatility or confidence level of the results. A larger standard deviation correlates with a wider predicted range, thereby enhancing the probability factor.
APPLICATION
The purpose of the indicator is to provide traders with an understanding of the potential future movement of the price, demarcating maximum and minimum expected outcomes. For instance, if an asset demonstrates a substantial spike beyond the forecasted range, there's a significantly high probability of that price being rejected and reversed.
However, this indicator should not be the sole basis for your trading decisions. The range merely reflects the volatility within the rolling window and may overlook significant historical price movements. As with any trading strategies, synergize this with other indicators for a more comprehensive and reliable analysis.
Note: In instances where the number of predicted bars is exceedingly high, the lines may become scattered, presumably due to inherent limitations on the TradingView platform. Consequently, when applying three SD in your indicator, it is advised to limit the predicted bars to fewer than 80.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Mxwll Liquidation Ranges - Mxwll CapitalIntroducing: Mxwll Liquidation Ranges
Mxwll Liquidation Ranges gathers data outside of TradingView to provide the highest quality, highest accuracy liquidation levels and ranges for popular crypto currencies.
Features
Real liquidation ranges and levels calculated outside of TradingView.
Real net position delta
Average leverage for long positions
Average leverage for short positions
Real number of bids for the cryptocurrency by the day
Real number of asks for the cryptocurrency by the day
Real Bid/Ask Ratio
Real Bid/Ask Delta
Real number of long market orders
Real number of short market orders
Real number of long limit orders
Real number of short limit orders
How do we obtain this data?
Using a now deprecated feature called "TradingView Pine Seeds", we are able to calculate the metrics listed above outside of TradingView and, consequently, import the data to TradingView for public use.
This means no indicators on TradingView that attempt to show liquidation levels, limit orders, net position delta, etc. can be as accurate as ours.
Why aren't other liquidation ranges indicators on TradingView as accurate as ours?
Simple: the data required to calculate liquidation levels and ranges isn't available on TradingView. No level 2 data, bids, asks, leverage information, pending limit orders, etc. This means any custom-coded indicator on TradingView attempting to use or show this information is just a guess, and is naturally inaccurate.
Mxwll Liquidation Ranges has access to all of the required data outside of TradingView, to which liquidation levels/ranges and other pertinent metrics are calculated and uploaded directly to TradingView using the Pine Seeds feature. This means that all information displayed by our indicator uses legitimate level 2 data outside of TradingView. Which means no "estimates" are required to produce this information. Consequently, unless a custom-coded indicator has access to the Pine Seeds feature and calculates liquidation levels and other level 2 data metrics outside of TradingView, then that indicator is inaccurate.
Liquidation Heatmap
The above image shows our liquidation heatmaps, which are calculated using level 2 data, in action.
Liquidation ranges are color coded. Purple/blue colored ranges indicate a lower number of net liquidations should the range be violated.
Green/yellow ranges indicate a liquidation range where the net number of liquidated positions, should the price range be violated, is substantial. Expect volatile price action around these areas and plan accordingly.
Yellow labels indicate the four highest liquidation ranges for the asset over the period.
Liquidation Levels
In addition to calculating a liquidation heatmap, Mxwll Liquidation Ranges also calculates liquidation levels by leverage. Level 2 data outside of TradingView is used.
Levels are colored coded by leverage used.
Green levels are 25x leverage liquidation areas.
Purple levels are 50x leverage liquidation areas.
Orange levels are 100x leverage liquidation areas.
Use this information to improve your trading plan and better pinpoint entries, exits, and key levels of expected volatility.
Other Metrics
Mxwll Liquidation Ranges uses level 2 data and the orderbook to calculate various metrics.
Average leverage for long positions
Average leverage for short positions
Real number of bids for the cryptocurrency by the day
Real number of asks for the cryptocurrency by the day
Real Bid/Ask Ratio
Real Bid/Ask Delta
Real number of long market orders
Real number of short market orders
Real number of long limit orders
Real number of short limit orders
How To Use
Understanding and interpreting heatmaps for predicting liquidation levels in trading can provide a significant edge. Here’s a basic guide on how to interpret these charts:
Understanding Liquidation Levels: Liquidation levels indicate where traders who are using leverage might be forced to exit their positions due to insufficient margin to cover their trades. These levels are crucial because they can trigger sudden price movements if many positions are liquidated at once.
Clusters on the Heatmap: On the heatmap, clusters of liquidation levels are represented by color-coded areas. These clusters show where significant numbers of leveraged positions are concentrated. The color intensity often indicates the density of liquidation points – darker or brighter colors suggest higher concentrations of liquidation risks.
Price Movements: By knowing where these clusters are, traders can anticipate potential price movements. For example, if a significant price drop moves the market closer to a cluster of liquidation levels, there’s an increased risk of those levels being triggered, potentially causing a sharp further drop due to cascading liquidations.
Strategic Trading: With this information, traders can strategically place their own stop losses or prepare to enter trades. Knowing where others might be forced to close their positions can help in predicting bullish or bearish movements.
Risk Management: Understanding liquidation levels helps in managing your own risk. Setting stop losses away from common liquidation points can avoid being caught in volatile price swings caused by mass liquidations.
- Mxwll Capital
Luxmi AI Filtered Option Scalping Signals (INDEX)Introduction:
Luxmi AI Filtered Option Scalping Signals (INDEX) is an enhanced iteration of the Luxmi AI Directional Option Buying (Long Only) indicator. It's designed for use on index charts alongside the Luxmi AI Smart Sentimeter (INDEX) indicator to enhance performance. This indicator aims to provide refined signals for option scalping strategies, optimizing trading decisions within index markets.
Understanding directional bias is crucial when trading index and index options because it helps traders align their strategies with the expected movement of the underlying index.
The Luxmi AI Filtered Option Scalping Signals (INDEX) indicator aims to simplify and expedite decision-making through comprehensive technical analysis of various data points on a chart. By leveraging advanced analysis of data points, this indicator scrutinizes multiple factors simultaneously to offer traders clear and rapid insights into market dynamics.
The indicator is specifically designed for option scalping, a trading strategy that aims to profit from short-term price fluctuations. It prioritizes signals that are conducive to quick execution and capitalizes on rapid market movements typical of scalping strategies.
Major Features:
Trend Cloud:
Working Principle:
The script utilizes the Relative Strength Index (RSI) to assess market momentum, identifying bullish and bearish phases based on RSI readings. It calculates two boolean variables, bullmove and bearmove, which signal shifts in momentum direction by considering changes in the Exponential Moving Average (EMA) of the closing price. When RSI indicates bullish momentum and the closing price's EMA exhibits positive changes, bullmove is triggered, signifying the start of a bullish phase. Conversely, when RSI suggests bearish momentum and the closing price's EMA shows negative changes, bearmove is activated, marking the beginning of a bearish phase. This systematic approach helps in understanding the current trend of the price. The script visually emphasizes these phases on the chart using plot shape markers, providing traders with clear indications of trend shifts.
Benefits of Using Trend Cloud:
Comprehensive Momentum Assessment: The script offers a holistic view of market momentum by incorporating RSI readings and changes in the closing price's EMA, enabling traders to identify both bullish and bearish phases effectively.
Structured Trend Recognition: With the calculation of boolean variables, the script provides a structured approach to recognizing shifts in momentum direction, enhancing traders' ability to interpret market dynamics.
Visual Clarity: Plotshape markers visually highlight the start and end of bullish and bearish phases on the chart, facilitating easy identification of trend shifts and helping traders to stay informed.
Prompt Response: Traders can promptly react to changing market conditions as the script triggers alerts when bullish or bearish phases begin, allowing them to seize potential trading opportunities swiftly.
Informed Decision-Making: By integrating various indicators and visual cues, the script enables traders to make well-informed decisions and adapt their strategies according to prevailing market sentiment, ultimately enhancing their trading performance.
How to use this feature:
The most effective way to maximize the benefits of this feature is to use it in conjunction with other key indicators and visual cues. By combining the color-coded clouds, which indicate bullish and bearish sentiment, with other features such as IS candles, microtrend candles, volume candles, and sentimeter candles, traders can gain a comprehensive understanding of market dynamics. For instance, aligning the color of the clouds with the trend direction indicated by IS candles, microtrend candles, and sentimeter candles can provide confirmation of trend strength or potential reversals.
Furthermore, traders can leverage the trend cloud as a trailing stop-loss tool for long entries, enhancing risk management strategies. By adjusting the stop-loss level based on the color of the cloud, traders can trail their positions to capture potential profits while minimizing losses. For long entries, maintaining the position as long as the cloud remains green can help traders stay aligned with the prevailing bullish sentiment. Conversely, a shift in color from green to red serves as a signal to exit the position, indicating a potential reversal in market sentiment and minimizing potential losses. This integration of the trend cloud as a trailing stop-loss mechanism adds an additional layer of risk management to trading strategies, increasing the likelihood of successful trades while reducing exposure to adverse market movements.
Moreover, the red cloud serves as an indicator of decay in option premiums and potential theta effect, particularly relevant for options traders. When the cloud turns red, it suggests a decline in option prices and an increase in theta decay, highlighting the importance of managing options positions accordingly. Traders may consider adjusting their options strategies, such as rolling positions or closing out contracts, to mitigate the impact of theta decay and preserve capital. By incorporating this insight into options pricing dynamics, traders can make more informed decisions about their options trades.
Scalping Cloud:
The scalping cloud serves as a specialized component within the trend cloud feature, specifically designed to pinpoint potential long and short entry points within the overarching trend cloud. Here's how it works:
Trend Identification: The trend cloud feature typically highlights the prevailing trend direction based on various technical indicators, price action, or other criteria. It visually represents the momentum and direction of the market over a given period.
Refined Entry Signals: Within this broader trend context, the scalping cloud narrows its focus to identify shorter-term trading opportunities. It does this by analyzing more granular price movements and shorter timeframes, seeking out potential entry points that align with the larger trend.
Long and Short Entries: The scalping cloud distinguishes between potential long (buy) and short (sell) entry opportunities within the trend cloud. For instance, within an uptrend indicated by the trend cloud, the scalping cloud might identify brief retracements or pullbacks as potential long entry points. Conversely, in a downtrend, it may signal short entry opportunities during temporary upward corrections.
Risk Management: By identifying potential entry points within the context of the trend, the scalping cloud also aids in risk management. Traders can use these signals to place stop-loss orders and manage their positions effectively, reducing the risk of adverse price movements.
The scalping cloud operates by analyzing the crossover and crossunder events between two key indicators: the Double Exponential Moving Average (DEMA) and a Weighted Average. Here's how it works:
Double Exponential Moving Average (DEMA): DEMA is a type of moving average that seeks to reduce lag by applying a double smoothing technique to price data. It responds more quickly to price changes compared to traditional moving averages, making it suitable for identifying short-term trends and potential trading opportunities.
Weighted Average: The weighted average calculates the average price of an asset over a specified period. However, it incorporates a weighting scheme that assigns more significance to recent price data, resulting in a more responsive indicator that closely tracks current market trends.
CE and NO CE Signals:
CE signals typically represent a Long Scalping Opportunity, suggesting that conditions are favorable for entering a long position. These signals indicate a strong upward momentum in the market, which traders can exploit for short-term gains through scalping strategies.
On the other hand, when there are no CE signals present, it doesn't necessarily mean that the trend has reversed or turned bearish. Instead, it indicates that the trend is still bullish, but the market is experiencing an active pullback. During a pullback, prices may temporarily retreat from recent highs as traders take profits or reevaluate their positions. While the overall trend remains upward, the pullback introduces a degree of uncertainty, making it less favorable for entering new long positions.
In such a scenario, traders may opt to exercise caution and refrain from entering new long positions until the pullback phase has concluded. Instead, they might consider waiting for confirmation signals, such as the resumption of CE signals or other bullish indications, before reengaging in long positions.
PE and NO PE Signals:
PE signals typically indicate a Short Entry opportunity, signaling that market conditions are conducive to entering a short position.
Conversely, when there are no PE signals present, it signifies that while the trend remains bearish, the market is currently in an active phase of consolidation or pullback. During such periods, prices may temporarily rise from recent lows, reflecting a pause in the downward momentum. While the overall trend remains downward, the absence of PE signals suggests that it may not be an optimal time to enter new short positions.
In this context, traders may exercise caution and wait for clearer signals before initiating new short positions. They might monitor the market closely for signs of a resumption in bearish momentum, such as the emergence of PE signals or other bearish indications. Alternatively, traders may choose to wait on the sidelines until market conditions stabilize or provide clearer directional signals.
Working Principle Of CE and PE Signals:
The feature calculates candlestick values based on the open, high, low, and close prices of each bar. By comparing these derived candlestick values, it determines whether the current candlestick is bullish or bearish. Additionally, it signals when there is a change in the color (bullish or bearish) of the derived candlesticks compared to the previous bar, enabling traders to identify potential shifts in market sentiment.
Micro Trend Candles:
Working Principle:
This feature begins by initializing variables to determine trend channel width and track price movements. Average True Range (ATR) is then calculated to measure market volatility, influencing the channel's size. Highs and lows are identified within a specified range, and trends are assessed based on price breaches, with potential changes signaled accordingly. The price channel is continually updated to adapt to market shifts, and arrows are placed to indicate potential entry points. Colors are assigned to represent bullish and bearish trends, dynamically adjusting based on current market conditions. Finally, candles on the chart are colored to visually depict the identified micro trend, offering traders an intuitive way to interpret market sentiment and potential entry opportunities.
Benefits of using Micro Trend Candles:
Traders can use these identified micro trends to spot potential short-term trading opportunities. For example:
Trend Following: Traders may decide to enter trades aligned with the prevailing micro trend. If the candles are consistently colored in a certain direction, traders may consider entering positions in that direction.
Reversals: Conversely, if the script signals a potential reversal by changing the candle colors, traders may anticipate trend reversals and adjust their trading strategies accordingly. For instance, they might close existing positions or enter new positions in anticipation of a trend reversal.
It's important to note that these micro trends are short-term in nature and may not always align with broader market trends. Therefore, traders utilizing this script should consider their trading timeframes and adjust their strategies accordingly.
How to use this feature:
This feature assigns colors to candles to represent bullish and bearish trends, with adjustments made based on current market conditions. Green candles accompanied by a green trend cloud signal a potential long entry, while red candles suggest caution, indicating a bearish trend. This visual representation allows traders to interpret market sentiment intuitively, identifying optimal entry points and exercising caution during potential downtrends.
Scalping Candles (Inspired by Elliott Wave and Open Interest Concepts):
Working Principle:
This feature draws inspiration from the Elliot Wave method, utilizing technical analysis techniques to discern potential market trends and sentiment shifts. It begins by calculating the variance between two Exponential Moving Averages (EMAs) of closing prices, mimicking Elliot Wave's focus on wave and trend analysis. The shorter-term EMA captures immediate price momentum, while the longer-term EMA reflects broader market trends. A smoother Exponential Moving Average (EMA) line, derived from the difference between these EMAs, aids in identifying short-term trend shifts or momentum reversals.
Benefits of using Scalping Candles Inspired by Elliott Wave:
The Elliott Wave principle is a form of technical analysis that attempts to predict future price movements by identifying patterns in market charts. It suggests that markets move in repetitive waves or cycles, and traders can potentially profit by recognizing these patterns.
While this script does not explicitly analyze Elliot Wave patterns, it is inspired by the principle's emphasis on trend analysis and market sentiment. By calculating and visualizing the difference between EMAs and assigning colors to candles based on this analysis, the script aims to provide traders with insights into potential market sentiment shifts, which can align with the broader philosophy of Elliott Wave analysis.
How to use this feature:
Candlestick colors are assigned based on the relationship between the EMA line and the variance. When the variance is below or equal to the EMA line, candles are colored red, suggesting a bearish sentiment. Conversely, when the variance is above the EMA line, candles are tinted green, indicating a bullish outlook. Though not explicitly analyzing Elliot Wave patterns, the script aligns with its principles of trend analysis and market sentiment interpretation. By offering visual cues on sentiment shifts, it provides traders with insights into potential trading opportunities, echoing Elliot Wave's emphasis on pattern recognition and trend analysis.
Chart Timeframe Support and Resistance:
Working Principle:
This feature serves to identify and visualize support and resistance levels on the chart, primarily based on the chosen Chart Timeframe (CTF). It allows users to specify parameters such as the number of bars considered on the left and right sides of each pivot point, as well as line width and label color. Moreover, users have the option to enable or disable the display of these levels. By utilizing functions to calculate pivot highs and lows within the specified timeframe, the script determines the highest high and lowest low surrounding each pivot point.
Additionally, it defines functions to create lines and labels for each detected support and resistance level. Notably, this feature incorporates a trading method that emphasizes the concept of resistance turning into support after breakouts, thereby providing valuable insights for traders employing such strategies. These lines are drawn on the chart, with colors indicating whether the level is above or below the current close price, aiding traders in visualizing key levels and making informed trading decisions.
Benefits of Chart Timeframe Support and Resistance:
Identification of Price Levels: Support and resistance levels help traders identify significant price levels where buying (support) and selling (resistance) pressure may intensify. These levels are often formed based on historical price movements and are regarded as areas of interest for traders.
Decision Making: Support and resistance levels assist traders in making informed trading decisions. By observing price reactions near these levels, traders can gauge market sentiment and adjust their strategies accordingly. For example, traders may choose to enter or exit positions, set stop-loss orders, or take profit targets based on price behavior around these levels.
Risk Management: Support and resistance levels aid in risk management by providing reference points for setting stop-loss orders. Traders often place stop-loss orders below support levels for long positions and above resistance levels for short positions to limit potential losses if the market moves against them.
How to use this feature:
Planning Long Positions: When considering long positions, it's advantageous to strategize when the price is in proximity to a support level identified by the script. This suggests a potential area of buying interest where traders may expect a bounce or reversal in price. Additionally, confirm the bullish bias by ensuring that the trend cloud is green, indicating favorable market conditions for long trades.
Waiting for Breakout: If long signals are generated near resistance levels detected by the script, exercise patience and wait for a breakout above the resistance. A breakout above resistance signifies potential strength in the upward momentum and may present a more opportune moment to enter long positions. This approach aligns with trading methodologies that emphasize confirmation of bullish momentum before initiating trades.
StopLoss and Target Lines:
In addition to generating entry signals, this indicator also incorporates predefined stop-loss ray lines and configurable risk-reward (R:R) target lines to enhance risk management and profit-taking strategies. Here's how these features work:
Predefined Stop-loss Ray Lines: The indicator automatically plots stop-loss ray lines on the chart, serving as visual guidelines for setting stop-loss levels. These stop-loss lines are predetermined based on specific criteria, such as volatility levels, support and resistance zones, or predefined risk parameters. Traders can use these lines as reference points to place their stop-loss orders, aiming to limit potential losses if the market moves against their position.
Configurable Risk-Reward (R:R) Target Lines: In addition to stop-loss lines, the indicator allows traders to set configurable risk-reward (R:R) target lines on the chart. These target lines represent predefined price levels where traders intend to take profits based on their desired risk-reward ratio. By adjusting the placement of these lines, traders can customize their risk-reward ratios according to their trading preferences and risk tolerance.
Risk Management: The predefined stop-loss ray lines help traders manage risk by providing clear exit points if the trade goes against their expectations. By adhering to these predetermined stop-loss levels, traders can minimize potential losses and protect their trading capital, thereby enhancing overall risk management.
Profit-taking Strategy: On the other hand, the configurable R:R target lines assist traders in establishing profit-taking strategies. By setting target levels based on their desired risk-reward ratio, traders can aim to capture profits at predefined price levels that offer favorable risk-reward profiles. This allows traders to systematically take profits while ensuring that potential gains outweigh potential losses over the long term.
The stop-loss and target lines incorporated in this indicator are dynamic in nature, providing traders with the flexibility to utilize them as trailing stop-loss and extended take-profit targets. Here's how these dynamic features work:
Trailing Stop-loss: Traders can employ the stop-loss lines as trailing stop-loss levels, allowing them to adjust their stop-loss orders as the market moves in their favor. As the price continues to move in the desired direction, indicator can dynamically adjust the stop-loss line to lock in profits while still allowing room for potential further gains. This trailing stop-loss mechanism helps traders secure profits while allowing their winning trades to continue running as long as the market remains favorable.
Extended Take Profit Targets: Similarly, traders can utilize the target lines as extended take-profit targets, enabling them to capture additional profits beyond their initial profit targets. By adjusting the placement of these target lines based on evolving market conditions or technical signals, traders can extend their profit-taking strategy to capitalize on potential price extensions or trend continuations. This flexibility allows traders to maximize their profit potential by capturing larger price movements while managing their risk effectively.
Rangebound Bars:
When the Rangebound Bars feature is enabled, the indicator represents candles in a distinct purple color to visually denote periods of sideways or range-bound price action. This visual cue helps traders easily identify when the market is consolidating and lacking clear directional momentum. Here's how it works:
Purple Candle Color: When the Rangebound Bars feature is active, the indicator displays candlesticks in a purple color to highlight periods of sideways price movement. This color differentiation stands out against the usual colors used for bullish (e.g., green or white) and bearish (e.g., red or black) candles, making it easier for traders to recognize range-bound conditions at a glance.
Signaling Sideways Price Action: The purple coloration of candles indicates that price movements are confined within a relatively narrow range and lack a clear upward or downward trend. This may occur when the market is consolidating, experiencing indecision, or undergoing a period of accumulation or distribution.
Working Principle:
The Rangebound Bars feature of this indicator is designed to assist traders in identifying and navigating consolidating market conditions, where price movements are confined within a relatively narrow range. This feature utilizes Pivot levels and the Average True Range (ATR) concept to determine when the market is range-bound and provides signals to stay out of such price action. Here's how it works:
Pivot Levels: Pivot levels are key price levels derived from the previous period's high, low, and closing prices. They serve as potential support and resistance levels and are widely used by traders to identify significant price levels where price action may stall or reverse. The Rangebound Bars feature incorporates Pivot levels into its analysis to identify ranges where price tends to consolidate.
Average True Range (ATR): The Average True Range is a measure of market volatility that calculates the average range between the high and low prices over a specified period. It provides traders with insights into the level of price volatility and helps set appropriate stop-loss and take-profit levels. In the context of the Rangebound Bars feature, ATR is used to gauge the extent of price fluctuations within the identified range.
Fibonacci Trend Reversal StrategyIntroduction
This publication introduces the " Fibonacci Retracement Trend Reversal Strategy, " tailored for traders aiming to leverage shifts in market momentum through advanced trend analysis and risk management techniques. This strategy is designed to pinpoint potential reversal points, optimizing trading opportunities.
Overview
The strategy leverages Fibonacci retracement levels derived from @IMBA_TRADER's lance Algo to identify potential trend reversals. It's further enhanced by a method called " Trend Strength Over Time " (TSOT) (by @federalTacos5392b), which utilizes percentile rankings of price action to measure trend strength. This also has implemented Dynamic SL finder by utilizing @veryfid's ATR Stoploss Finder which works pretty well
Indicators:
Fibonacci Retracement Levels : Identifies critical reversal zones at 23.6%, 50%, and 78.6% levels.
TSOT (Trend Strength Over Time) : Employs percentile rankings across various timeframes to gauge the strength and direction of trends, aiding in the confirmation of Fibonacci-based signals.
ATR (Average True Range) : Implements dynamic stop-loss settings for both long and short positions, enhancing trade security.
Strategy Settings :
- Sensitivity: Set default at 18, adjustable for more frequent or sparse signals based on market volatility.
- ATR Stop Loss Finder: Multiplier set at 3.5, applying the ATR value to determine stop losses dynamically.
- ATR Length: Default set to 14 with RMA smoothing.
- TSOT Settings: Hard-coded to identify percentile ranks, with no user-adjustable inputs due to its intrinsic calculation method.
Trade Direction Options : Configurable to support long, short, or both directions, adaptable to the trader's market assessment.
Entry Conditions :
- Long Entry: Triggered when the price surpasses the mid Fibonacci level (50%) with a bullish TSOT signal.
- Short Entry: Activated when the price falls below the mid Fibonacci level with a bearish TSOT indication.
Exit Conditions :
- Employs ATR-based dynamic stop losses, calibrated according to current market volatility, ensuring effective risk management.
Strategy Execution :
- Risk Management: Features adjustable risk-reward settings and enables partial take profits by default to systematically secure gains.
- Position Reversal: Includes an option to reverse positions based on new TSOT signals, improving the strategy's responsiveness to evolving market conditions.
The strategy is optimized for the BYBIT:WIFUSDT.P market on a scalping (5-minute) timeframe, using the default settings outlined above.
I spent a lot of time creating the dynamic exit strategies for partially taking profits and reversing positions so please make use of those and feel free to adjust the settings, tool tips are also provided.
For Developers: this is published as open-sourced code so that developers can learn something especially on dynamic exits and partial take profits!
Good Luck!
Disclaimer
This strategy is shared for educational purposes and must be thoroughly tested under diverse market conditions. Past performance does not guarantee future results. Traders are advised to integrate this strategy with other analytical tools and tailor it to specific market scenarios. I was only sharing what I've crafted while strategizing over a Solana Meme Coin.
