Liquidity SpotterIndicator Setup:
The script sets up a TradingView indicator titled "Liquidity Spotter" with a short title "PWWTC LS". It's designed to overlay on the price chart (overlay=true).
Input Variables:
The script defines input variables that allow users to customize the behavior of the indicator:
atr_length: Length of the Average True Range (ATR) used in calculations.
volume_multiplier: Multiplier used to compare the volume of the current bar with the average volume.
range_multiplier: Multiplier used to calculate the range condition.
highlight_color: Color used to highlight bars when conditions are met.
Calculations:
The script calculates the ATR and average volume using the ta.atr and ta.sma functions provided by TradingView's Pine Script.
It sets the avg_range to the value of the ATR, essentially making it the same as atr_value.
Conditions:
The script checks several conditions based on the calculated values:
range_condition: Compares the range (high - low) of the current bar with the average range multiplied by the range multiplier.
volume_condition: Compares the volume of the current bar with the average volume multiplied by the volume multiplier.
range_volume_condition: Compares the ratio of range to volume with the ratio of average range to average volume.
Plotting:
Based on the conditions being met or not, the script sets the color of the price bars. If all conditions are met, the color of the bars will be set to highlight_color, otherwise, it will remain unchanged (na).
Overall, this script visually highlights price bars on the chart where specific conditions related to range, volume, and their ratio are met, potentially indicating trading opportunities.
Volatilitas
TrippleMACDCryptocurrency Scalping Strategy for 1m Timeframe
Introduction:
Welcome to our cutting-edge cryptocurrency scalping strategy tailored specifically for the 1-minute timeframe. By combining three MACD indicators with different parameters and averaging them, along with applying RSI, we've developed a highly effective strategy for maximizing profits in the cryptocurrency market. This strategy is designed for automated trading through our bot, which executes trades using hooks. All trades are calculated for long positions only, ensuring optimal performance in a fast-paced market.
Key Components:
MACD (Moving Average Convergence Divergence):
We've utilized three MACD indicators with varying parameters to capture different aspects of market momentum.
Averaging these MACD indicators helps smooth out noise and provides a more reliable signal for trading decisions.
RSI (Relative Strength Index):
RSI serves as a complementary indicator, providing insights into the strength of bullish trends.
By incorporating RSI, we enhance the accuracy of our entry and exit points, ensuring timely execution of trades.
Strategy Overview:
Long Position Entries:
Initiate long positions when all three MACD indicators signal bullish momentum and the RSI confirms bullish strength.
This combination of indicators increases the probability of successful trades, allowing us to capitalize on uptrends effectively.
Utilizing Linear Regression:
Linear regression is employed to identify consolidation phases in the market.
Recognizing consolidation periods helps us avoid trading during choppy price action, ensuring optimal performance.
Suitability for Grid Trading Bots:
Our strategy is well-suited for grid trading bots due to frequent price fluctuations and opportunities for grid activation.
The strategy's design accounts for price breakthroughs, which are advantageous for grid trading strategies.
Benefits of the Strategy:
Consistent Performance Across Cryptocurrencies:
Through rigorous testing on various cryptocurrency futures contracts, our strategy has demonstrated favorable results across different coins.
Its adaptability makes it a versatile tool for traders seeking consistent profits in the cryptocurrency market.
Integration of Advanced Techniques:
By integrating multiple indicators and employing linear regression, our strategy leverages advanced techniques to enhance trading performance.
This strategic approach ensures a comprehensive analysis of market conditions, leading to well-informed trading decisions.
Conclusion:
Our cryptocurrency scalping strategy offers a sophisticated yet user-friendly approach to trading in the fast-paced environment of the 1-minute timeframe. With its emphasis on automation, accuracy, and adaptability, our strategy empowers traders to navigate the complexities of the cryptocurrency market with confidence. Whether you're a seasoned trader or a novice investor, our strategy provides a reliable framework for achieving consistent profits and maximizing returns on your investment.
Effort Versus ResultsThis indicator, named "Effort Versus Results" (CCB), is designed to visually highlight price bars on a TradingView chart based on user-defined criteria. The purpose of this indicator is to identify potential trading opportunities or signal areas of interest for further analysis.
Once the inputs are specified, the indicator calculates the ratio of the first ATR to the average volume and compares it to the product of the multiplier and the ratio of the second ATR to the average volume. If the calculated condition is met, indicating that the first ATR relative to volume is greater than the second ATR relative to volume multiplied by the specified multiplier, the indicator colors the corresponding price bars red.
By customizing the parameters, traders can adapt the indicator to suit their trading strategies, risk tolerance, and market conditions. The highlighted bars may signify potential areas of increased volatility or trading activity, prompting traders to further investigate potential trading opportunities. However, as with any technical indicator, it is essential to use this tool in conjunction with other analysis techniques and risk management strategies for informed decision-making.
The indicator utilizes three main inputs that users can customize:
1. **ATR Length 1 (`atr_length_1`)**: This parameter allows users to specify the length of the first Average True Range (ATR) period. ATR is a measure of market volatility and represents the average range of price movement over a specified period.
2. **ATR Length 2 (`atr_length_2`)**: Users can set the length of the second ATR period, allowing for comparison between two different ATR values.
3. **Volume Length (`volume_length`)**: This input enables users to define the length of the volume period. Volume is a measure of the number of shares or contracts traded during a given period and is often used to confirm price movements.
4. **Multiplier (`multiplier`)**: Users can specify a multiplier value to adjust the threshold for comparison between the two ATR values divided by volume. This parameter allows for flexibility in setting the sensitivity of the indicator.
Dynamic Bern TrailThis indicator will help you following price movements in trending or ranging markets. Within it's calculations it uses ATR, EMA with a smoothing effect. It includes a buffer zone to help determine where price may turn around and reverse or to identify when a breakout occurs by breaking through the ATR trail. You can customize and play around with several settings to adjust it for your asset. Adjustments that can be made besides visuals are ATR Length, ATR Multiplier, EMA Length, Smoothing Length and the Buffer Multiplier.
SVMKR_UT_Bot_HMA_UCS_LRSThis Pine Script code is a TradingView study script titled "SVMKR_UT_Bot_HMA_UCS_LRS". It combines two separate trading indicators: the UT Bot (Ultimate Trailing Stop Bot) and the UCS_LRS (Linear Regression Slope) indicator.
UT Bot (Ultimate Trailing Stop Bot):
The UT Bot is designed to provide buy and sell signals based on a trailing stop strategy.
It calculates the trailing stop level using the Average True Range (ATR) and Heikin Ashi candle signals if enabled.
Buy signals are generated when the price crosses above the trailing stop, while sell signals occur when the price crosses below the trailing stop.
Additionally, buy and sell signals are visually represented on the chart with corresponding labels and shapes.
The script also includes options to customize the sensitivity of the trailing stop and to color the bars based on buy or sell signals.
Hull Moving Average (HMA):
This section calculates and plots the Hull Moving Average, a type of moving average that reduces lag and improves smoothing compared to traditional moving averages.
It uses the weighted moving average (WMA) to compute the HMA, which helps to identify trend direction and potential reversal points.
UCS_LRS (Linear Regression Slope):
The UCS_LRS indicator calculates the linear regression slope of the closing prices over a specified period.
It then applies exponential smoothing to the slope values and calculates an average slope.
Buy signals are generated when the current slope is greater than the average slope and positive, indicating an uptrend.
Conversely, sell signals are generated when the current slope is less than the average slope and negative, suggesting a downtrend.
The linear regression slope and its average are plotted on the chart, allowing traders to visually identify trend strength and potential reversal points.
Overall, this combined script provides traders with a comprehensive set of tools for trend following and momentum trading strategies, integrating trailing stop analysis, moving average smoothing, and linear regression slope analysis into a single script for technical analysis on TradingView charts.
Trend AngleThe "Trend Angle" indicator serves as a tool for traders to decipher market trends through a methodical lens. It quantifies the inclination of price movements within a specified timeframe, making it easy to understand current trend dynamics.
Conceptual Foundation:
Angle Measurement: The essence of the "Trend Angle" indicator is its ability to compute the angle between the price trajectory over a defined period and the horizontal axis. This is achieved through the calculation of the arctangent of the percentage price change, offering a straightforward measure of market directionality.
Smoothing Mechanisms: The indicator incorporates options for "Moving Average" and "Linear Regression" as smoothing mechanisms. This adaptability allows for refined trend analysis, catering to diverse market conditions and individual preferences.
Functional Versatility:
Source Adaptability: The indicator affords the flexibility to select the desired price source, enabling users to tailor the angle calculation to their analytical framework and other indicators.
Detrending Capability: With the detrending feature, the indicator allows for the subtraction of the smoothing line from the calculated angle, highlighting deviations from the main trend. This is particularly useful for identifying potential trend reversals or significant market shifts.
Customizable Period: The 'Length' parameter empowers traders to define the observation window for both the trend angle calculation and its smoothing, accommodating various trading horizons.
Visual Intuition: The optional colorization enhances interpretability, with the indicator's color shifting based on its relation to the smoothing line, thereby providing an immediate visual cue regarding the trend's direction.
Interpretative Results:
Market Flatness: An angle proximate to 0 suggests a flat market condition, indicating a lack of significant directional movement. This insight can be pivotal for traders in assessing market stagnation.
Trending Market: Conversely, a relatively high angle denotes a trending market, signifying strong directional momentum. This distinction is crucial for traders aiming to capitalize on trend-driven opportunities.
Analytical Nuance vs. Simplicity:
While the "Trend Angle" indicator is underpinned by mathematical principles, its utility lies in its simplicity and interpretative clarity. However, it is imperative to acknowledge that this tool should be employed as part of a comprehensive trading strategy , complemented by other analytical instruments for a holistic market analysis.
In essence, the "Trend Angle" indicator exemplifies the harmonization of simplicity and analytical rigor. Its design respects the complexity of market behaviors while offering straightforward, actionable insights, making it a valuable component in the arsenal of both seasoned and novice traders alike.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
GKD-V Stiffness [Loxx]The Giga Kaleidoscope GKD-V Stiffness is a Volume/Volatility module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-V Stiffness
The stiffness indicator quantifies the market's momentum by analyzing the relationship between price movements and volatility over a specific time frame. It employs a moving average to smooth out price data, providing a baseline for trend assessment. The key element in this calculation is the incorporation of a volatility factor, typically standard deviation, which adjusts the moving average to account for market volatility. This adjusted moving average creates a benchmark that the current price must surpass to signal significant momentum.
By comparing the current price to this volatility-adjusted moving average, the stiffness indicator determines the strength of the market's trend. A higher stiffness value, surpassing a predefined threshold, indicates a strong and potentially profitable trend, either upward or downward, suggesting opportunities for strategic trading positions. Conversely, a stiffness value below the threshold signifies insufficient momentum, advising traders to refrain from entering the market due to the high risk of unpredictability. This method provides a systematic approach to evaluate market trends, enabling traders to make decisions based on the robustness of price movements relative to historical volatility.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from the lower band when using phi * multiplier
B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier
B3 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the upper band when using
S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier
S3 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands.
Calculations
ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Settings
CHANNEL SETTINGS
Baseline EMA Period (Default: 21): Period length of the moving average basis line.
ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated.
Basis MA Type (Default: SMA): The moving average type for the basis line.
Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
ADDITIONAL CHANNELS
Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier.
Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier.
Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier.
WICK SETTINGS FOR CANDLE FILTERS
Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline.
Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size.
VISUAL PREFERENCES - SIGNALS
Show Signals (Default: true): Allows signal labels to be shown.
Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands.
Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands.
Show Baseline Signals (Default: false): Toggle Baseline signals.
VISUAL PREFERENCES - BANDS
Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands.
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Bollinger Band Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger Bands and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional, B1 and S1 signals can be displayed that use the baseline as the pivot level.
Settings
SIGNALS
Show Bollinger Band Signals (Default: True): Allows signal labels to be shown.
Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off.
Show Wick Signals (Defau
lt: True): Displays signals when wicking occurs.
BOLLINGER BAND SETTINGS
Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line.
Basis MA Type (Default: SMA): The moving average type for the BB Basis line.
Source (Default: “close”): The source of time series data.
Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
WICK SETTINGS FOR BOLLINGER BANDS
Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline.
WICK SETTINGS FOR CANDLE SIGNALS
Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size.
Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size.
Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal.
VISUAL PREFERENCES
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals.
Show Bollinger Bands (Default: true): Show the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Calculations
Bollinger Bands are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. Bollinger Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of standard deviations to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of standard deviations from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
CVD Divergence Strategy.1.mmThis is the matching Strategy version of Indicator of the same name.
As a member of the K1m6a Lions discussion community we often use versions of the Cumulative Volume Delta indicator
as one of our primary tools along with RSI, RSI Divergences, Open interest, Volume Profile, TPO and Fibonacci levels.
We also discuss visual interpretations of CVD Divergences across multiple time frames much like RSI divergences.
RSI Divergences can be identified as possible Bullish reversal areas when the RSI is making higher low points while
the price is making lower low points.
RSI Divergences can be identified as possible Bearish reversal areas when the RSI is making lower high points while
the price is making higher high points.
CVD Divergences can also be identified the same way on any timeframe as possible reversal signals. As with RSI, these Divergences
often occur as a trend's momentum is giving way to lower volume and areas when profits are being taken signaling a possible reversal
of the current trending price movement.
Hidden Divergences are identified as calculations that may be signaling a continuation of the current trend.
Having not found any public domain versions of a CVD Divergence indicator I have combined some public code to create this
indicator and matching strategy. The calculations for the Cumulative Volume Delta keep a running total for the differences between
the positive changes in volume in relation to the negative changes in volume. A relative upward spike in CVD is created when
there is a large increase in buying vs a low amount of selling. A relative downward spike in CVD is created when
there is a large increase in selling vs a low amount of buying.
In the settings menu, the is a drop down to be used to view the results in alternate timeframes while the chart remains on current timeframe. The Lookback settings can be adjusted so that the divs show on a more local, spontaneous level if set at 1,1,60,1. For a deeper, wider view of the divs, they can be set higher like 7,7,60,7. Adjust them all to suit your view of the divs.
To create this indicator/strategy I used a portion of the code from "Cumulative Volume Delta" by @ contrerae which calculates
the CVD from aggregate volume of many top exchanges and plots the continuous changes on a non-overlay indicator.
For the identification and plotting of the Divergences, I used similar code from the Tradingview Technical "RSI Divergence Indicator"
This indicator should not be used as a stand-alone but as an additional tool to help identify Bullish and Bearish Divergences and
also Bullish and Bearish Hidden Divergences which, as opposed to regular divergences, may indicate a continuation.
CVD Divergence Indicator.1.mmAs a member of the K1m6a Lions discussion community we often use versions of the Cumulative Volume Delta indicator
as one of our primary tools along with RSI, RSI Divergences, Open interest, Volume Profile, TPO and Fibonacci levels.
We also discuss visual interpretations of CVD Divergences across multiple time frames much like RSI divergences.
RSI Divergences can be identified as possible Bullish reversal areas when the RSI is making higher low points while
the price is making lower low points.
RSI Divergences can be identified as possible Bearish reversal areas when the RSI is making lower high points while
the price is making higher high points.
CVD Divergences can also be identified the same way on any timeframe as possible reversal signals. As with RSI, these Divergences
often occur as a trend's momentum is giving way to lower volume and areas when profits are being taken signaling a possible reversal
of the current trending price movement.
Hidden Divergences are identified as calculations that may be signaling a continuation of the current trend.
Having not found any public domain versions of a CVD Divergence indicator I have combined some public code to create this
indicator and matching strategy. The calculations for the Cumulative Volume Delta keep a running total for the differences between
the positive changes in volume in relation to the negative changes in volume. A relative upward spike in CVD is created when
there is a large increase in buying vs a low amount of selling. A relative downward spike in CVD is created when
there is a large increase in selling vs a low amount of buying.
In the settings menu, the is a drop down to be used to view the results in alternate timeframes while the chart remains on current timeframe. The Lookback settings can be adjusted so that the divs show on a more local, spontaneous level if set at 1,1,60,1. For a deeper, wider view of the divs, they can be set higher like 7,7,60,7. Adjust them all to suit your view of the divs.
To create this indicator/strategy I used a portion of the code from "Cumulative Volume Delta" by @ contrerae which calculates
the CVD from aggregate volume of many top exchanges and plots the continuous changes on a non-overlay indicator.
For the identification and plotting of the Divergences, I used similar code from the Tradingview Technical "RSI Divergence Indicator"
This indicator should not be used as a stand-alone but as an additional tool to help identify Bullish and Bearish Divergences and
also Bullish and Bearish Hidden Divergences which, as opposed to regular divergences, may indicate a continuation.
Deck@r True Range IndexThis Pine Script calculates the True Range Index (TRI) using ATR and Fib Levels and uses the result to generate buy and sell signals based on certain conditions.
Here's a breakdown of the code:
Inputs:
atr_period: Determines the period for calculating the Average True Range (ATR), preferred setting at 14.
atr_multiplier: Multiplier used to set the width of the ATR bands preferred setting at 1.
Calculations:
atr_value: Calculates the Average True Range (ATR) using the input period.
upper_band: Calculates the upper band of the ATR bands using a Simple Moving Average (SMA) of the close price plus the ATR multiplied by the multiplier.
lower_band: Calculates the lower band of the ATR bands using a Simple Moving Average (SMA) of the close price minus the ATR multiplied by the multiplier.
midline_75 and midline_25: Calculate midlines at Fibonacci retracement levels of 0.75 and 0.25, respectively, between the upper and lower bands.
Plotting:
Plots the upper and lower bands of the ATR bands.
Optionally plots midlines for the ATR bands (commented out in the code).
Buy and Sell Conditions:
buy_condition: Defines a condition for a buy signal, which occurs when the close price is above the midline at the Fibonacci retracement level of 0.25.
sell_condition: Defines a condition for a sell signal, which occurs when the close price is below the midline at the Fibonacci retracement level of 0.75.
Candle Color:
Sets the candle color based on the buy and sell conditions.
Buy and Sell Signals:
buy_signal: Checks for a buy signal when the close price crosses above the midline at the Fibonacci retracement level of 0.25.
sell_signal: Checks for a sell signal when the close price crosses below the midline at the Fibonacci retracement level of 0.75.
Plots buy and sell signals on the chart.
BTC Spread Indicator"Hot potato, Bitcoin style!
In the dynamic world of cryptocurrency, keeping an eye on price movements across different exchanges can be as exhilarating as a game of hot potato. By calculating the average Bitcoin price across major exchanges, we can then dive deeper to identify the spreads between this global average and the prices on individual exchanges. This analysis reveals who's currently 'holding the potato'—or dealing with higher prices—and predicts who might be next. It's a fun, yet insightful way to visualize market volatility and trading opportunities. Let's see where the potato lands next!"
RWEDT Weighted Moving Average Overview:
The RWEDT MA, which is short for rolling, weighted, exponential, double exponential, and triple exponential, is a group of moving averages that were subjected to a log transformation to deal with the skewness of price, and the weight of each of these moving averages was also used for calculating the standard deviations from the mean.
Clearing a misunderstanding on Standard Deviation Bands and Moving Averages
Bands, such as standard deviation bands, are frequently misinterpreted as indicators of support and resistance levels or as "mean-reverting" indicators." However, this is not their intended purpose. Bands are statistical tools that provide ranges within which price (in this case) movements are expected to occur based on historical data. Deviations beyond these bands suggest a decrease in confidence in the model rather than a reversal back to a moving average or a "support/resistance level."
Example : Assuming you correctly applied a log transformation to your standard deviation bands to remove the right skew, and assuming your data closely resembles a normal distribution or some other type of symmetrical distribution, then the probability of a value being in the 2 standard deviation range is around 95%. This does not mean it will reject or go up, or mean revert. The price won't bounce from -2 STDEV 95% of the time; that is incorrect. It just tells you that around 95% of the values will be within the 2 SD range.
Moving averages, including the ones in this indicator, are often misinterpreted as signals of trend reversals or levels of "bouncing." What moving averages actually tell you is what the expected value is. It does not show where you expect the price to be in the future; it tells you that based on the lookback, the expected value is in the center, and the confidence you have in the estimate is the confidence interval or the standard deviation range.
Example: Let's say you enter a trade with a positive expected value (expecting the price to drift up), and we have the limits set at 95%. What it tells you is that as long as the price stays within the limits, you can be 95% certain the model isn't completely random. As the price moves further away from the average, or expected value, it tells you that the model is less likely to be correct.
RWEDT MA
This indicator comes with 5 moving averages, each log transformed to reduce the skewness and asymmetry of price as much as possible
Rolling
Weighted
Exponential
Double Exponential
Triple Exponential
The band standard deviation can be adjusted, and the standard deviations have the weight of all of the moving averages that are present in the indicator. The weight is not customizable.
Why this indicator is useful:
This indicator can tell you what the expected value is. Above the moving average signifies a positive expected value, and below the moving average signifies a negative expected value. As previously stated above, the price moving further from the expected value lets you know that you should have less confidence that the model is "correct," and you could see this as taking profits as the price deviates further from the expected value.
The importance of log-transforming prices for standard deviations and moving averages.
Symmetry: Logarithmic transformations can help achieve symmetry in the distribution of price data. Stock prices, for example, exhibit some type of right-skewed distribution, where large positive price movements are more common than large negative movements. Price also can't go below 0 but can go towards positive infinity, so having a right-skew makes sense; all the outliers will be towards infinity, while all the average occurrences are "near" 0.
Stabilizing Variance: Price data typically exhibit heteroscedasticity, meaning that the variance of price movements changes over time. Log transformations can stabilize the variance and make it more consistent across different price levels. This is important for ensuring that the variability in price moves is not disproportionately influenced by extreme values.
Statistical Assumptions: Many retail indicators like Bollinger Bands use the standard deviation and moving average models of a normal distribution to attempt to model price, whose distribution more closely resembles some type of right-skew distribution. Even with the log-transformation, it still won't always resemble a perfect symmetrical distribution, and you still should not use it for mean reversion. You can still use it to understand the expected value and whether or not you should have confidence in your model.
Kalman Filter by TenozenAnother useful indicator is here! Kalman Filter is a quantitative tool created by Rudolf E. Kalman. In the case of trading, it can help smooth out the price data that traders observe, making it easier to identify underlying trends. The Kalman Filter is particularly useful for handling price data that is noisy and unpredictable. As an adaptive-based algorithm, it can easily adjust to new data, which makes it a handy tool for traders operating in markets that are prone to change quickly.
Many people may assume that the Kalman Filter is the same as a Moving Average, but that is not the case. While both tools aim to smooth data and find trends, they serve different purposes and have their own sets of advantages and disadvantages. The Kalman Filter provides a more dynamic and adaptive approach, making it suitable for real-time analysis and predictive capabilities, but it is also more complex. On the other hand, Moving Averages offer a simpler and more intuitive way to visualize trends, which makes them a popular choice among traders for technical analysis. However, the Moving Average is a lagging indicator and less adaptive to market change, if it's adjusted it may result in overfitting. In this case, the Kalman Filter would be a better choice for smoothing the price up.
I hope you find this indicator useful! It's been an exciting and extensive journey since I began diving into the world of finance and trading. I'll keep you all updated on any new indicators I discover that could benefit the community in the future. Until then, take care, and happy trading! Ciao.
SqueeZe Score [UAlgo]The "SqueeZe Score" is a script based on the "Squeeze Momentum Indicator". It utilizes Bollinger Bands (BB) and Keltner Channels (KC) to identify periods of low volatility, indicating potential upcoming price movements. The Z-Score method is employed to measure deviations from the mean, highlighting extreme price movements within the context of the current volatility environment. This script provides traders with visual cues for potential bullish and bearish divergences, aiding in decision-making during trading activities.
🔶Key Features:
SqueeZe Settings: Users can customize parameters such as the length and multiplier factors for Bollinger Bands and Keltner Channels, providing flexibility to adapt the indicator to different trading strategies and market conditions.
Divergence Detection: The script includes options to detect and display both bullish and bearish divergences, providing additional insights into potential trend reversals or continuations.
Customizable Z-Score Thresholds: Thresholds for the Z-Score are user-defined, enabling traders to set levels at which extreme price movements are highlighted on the chart, facilitating quick identification of significant market conditions.
🔶Credit:
This script is inspired by the work of @LazyBear, who contributed to the original concept and development of the Squeeze Momentum indicator.
🔶Disclaimer:
- The information provided by this script is for educational and informational purposes only and should not be construed as financial advice.
- Users are encouraged to conduct their own research and analysis before making any investment decisions.
Inside Candle StrategyIntroduction
The Inside Candle Breakout Strategy leverages the concept of inside candles as a primary signal for potential breakouts. Unlike common trend-following or scalping strategies, this method focuses on the volatility squeeze indicated by inside candles and aims to capture the momentum that follows these periods of consolidation. The strategy's originality lies in its specific integration of timeframes for signal detection and its application across diverse market conditions without relying on conventional trend indicators.
Strategy Description and Mechanics
Inside Candle Identification: At the heart of this strategy is the detection of inside candles, defined as candles fully contained within the range of the preceding candle. This pattern signifies a temporary balance between buyers and sellers, often preceding significant price movements. The strategy scans for these candles within a user-specified timeframe in the input section of the settings of the strategy, allowing for tailored signal generation based on individual trading preferences.
Entry Points and Market Entries: Upon identifying an inside candle and only once this candle closes, the strategy prepares to enter a trade in the direction of the breakout. Trades are executed in the timeframe selected on the chart, ensuring that entry points are aligned with real-time market movements. This process highlights the strategy's adaptability, making it suitable for various trading styles, from day trading to swing trading.
Overlay Indicator for Enhanced Market Analysis: Accompanying the breakout signals is an overlay indicator comprising two moving averages and a volatility cloud. This feature serves as a secondary tool for market analysis, offering insights into the prevailing market trend and volatility levels. While it doesn't influence the entry or exit signals directly, it provides traders with additional context for refining their decisions, enhancing the strategy's utility. This assistance tool is composed by one moving average and a second line which is calculated adding or subtracting the historical volatility of the asset on the moving average, depending on his momentum.
Strategy Results and Commitment to Realism
Backtesting Protocol: In our commitment to transparency and realism, backtesting results are derived from a dataset that ensures a sufficient number of trades (over 100) to validate the strategy's effectiveness. This approach underscores our dedication to providing traders with reliable and actionable insights.
Risk Management and Trade Sizing: Recognizing the importance of sustainable trading practices, the strategy incorporates strict risk management guidelines. Trades are sized to ensure that only a small percentage of equity is risked on a single trade, adhering to widely accepted risk tolerance levels. The initial account size for this script is set to 10000$.
Strategy Defaults and Justification: The default properties of the strategy, including the risk-reward ratio, average length for moving averages, and other parameters, are carefully chosen based on extensive testing and analysis. These settings represent a balanced approach, aiming to optimize the strategy's performance across a variety of market conditions.
Strategy Components:
- Inside Candles: An inside candle occurs when a candle's high and low are completely contained within the high and low of the previous candle. This pattern indicates a period of consolidation or indecision in the market, often preceding a significant price movement. The strategy detects inside candles based on the user-selected timeframe, allowing traders to capture potential breakouts.
Indicator Overlays:
- Moving Average: A simple moving average (SMA) is calculated over a user-defined length (`Average Length`), providing a dynamic baseline to gauge the market's direction. The strategy offers an option (`Show Moving Average`) to display or hide this moving average on the chart, giving traders control over the visual complexity.
- Volatility Measurement: Alongside the moving average, the strategy assesses market volatility using the standard deviation of the closing prices over the same period defined by the `Average Length`. The moving average is adjusted upwards or downwards by this volatility measure, creating a dynamic channel that reflects the current market conditions.
- Color Gradients for Volatility: The strategy uses a color gradient to fill the area between the moving average and its volatility-adjusted counterpart. This gradient visually represents the volatility level, transitioning from gray (low volatility) to a lighter shade (higher volatility), aiding in the assessment of market sentiment and volatility.
Trading Entries:
- Long Entry: A long position is triggered when the closing price exceeds the high of an inside candle, indicating potential bullish momentum. The strategy places a stop-loss at the low of the inside candle and sets a take-profit level based on the predefined risk-reward ratio (`RR Ratio`).
- Short Entry: Conversely, a short position is initiated when the closing price falls below the low of an inside candle, suggesting bearish pressure. A stop-loss is set at the high of the inside candle, with the take-profit level adjusted according to the risk-reward ratio.
Customization Settings:
- Timeframe: Traders can select the desired timeframe for inside candle detection, tailoring the strategy to fit various trading styles and time horizons.
- RR Ratio: The risk-reward ratio is adjustable, allowing traders to manage the potential risk and return of each trade according to their risk tolerance.
- Average Length: This setting determines the period over which the moving average and volatility are calculated, affecting the sensitivity of the strategy to price movements.
- Visual Settings: Users can customize the appearance of the strategy on their charts, including the colors of the moving average and volatility lines, as well as the line width, enhancing chart readability and personal preference adherence.
Disclaimer
Trading involves significant risk, and it is crucial for traders to conduct their own due diligence before engaging with any strategy. The Inside Candle Breakout Strategy is presented for informational purposes only and does not constitute financial advice.
True Median (With EMA)
This indicator was inspired by the concept of mean revision and is best to be used with that strategy in mind. True median takes the high and low within a determined length and finds the average between those two points and then plots an EMA for the median with an optional EMA for both the high and low.
HOW TO USE:
This indicator has a few uses it can be implemented with.
The first and most obvious is that it can act as an area of support and resistance within bigger and smaller time frames. Second, the median can act as an entry or exit point, as generally big movements will occur within the mediums of price points. EMA crossovers are also a way to use this indicator, if the median, high, or low cross over their EMA, that can act as a signal for price movement and continuation of a pre existing trend. Of course this is also a good indicator of volatility, as the wider the channels are between high and low the more volatile things are becoming.
I hope you enjoy and let me know how this indicator works for you!
Bitcoin Bubble Risk (Adjusted for Diminishing Returns)Description:
This indicator offers a unique lens through which traders can assess risk in the Bitcoin market, specifically tailored to recognize the phenomenon of diminishing returns. By calculating the natural logarithm of the price relative to a 20-month Simple Moving Average (SMA) and applying a dynamic normalization process, this tool highlights periods of varying risk based on historical price movements and adjusted returns. The indicator is designed to provide nuanced insights into potential risk levels, aiding traders in their decision-making processes.
Usage:
To effectively use this indicator, apply it to your chart while ensuring that Bitcoin's price is set to display in monthly candles. This setting is vital for the indicator to accurately reflect the market's risk levels, as it relies on long-term data aggregation to inform its analysis.
This tool is especially beneficial for traders focused on medium to long-term investment horizons in Bitcoin, offering insights into when the market may be entering higher or lower risk phases. By incorporating this indicator into your analysis, you can gain a deeper understanding of potential risk exposures based on the adjusted price trends and market conditions.
Originality and Utility:
This script stands out for its innovative approach to risk analysis in the cryptocurrency space. By adjusting for the diminishing returns seen in mature markets, it provides a refined perspective on risk levels, enhancing traditional methodologies. This script is a significant contribution to the TradingView community, offering a unique tool for traders aiming to navigate the complexities of the Bitcoin market with informed risk management strategies.
Important Note:
This indicator is for informational purposes only and should not be considered investment advice. Users are encouraged to conduct their own research and consult with financial professionals before making investment decisions. The accuracy of the indicator's predictions can only be ensured when applied to monthly candlestick charts of Bitcoin.
Daily Range AnalysisThis indicator helps quickly identify if a stock is making a "price expansion" or a "price contraction". If today's range is larger than yesterday, then the stock is having a price expansion. This will be represented with a positive number. If today's range is smaller, the stock is making a contraction, and the indicator will display a negative number.
Indicator Features:
1. **Dark and Light Themes**: Users can choose between dark and light themes based on their preference. Dark themes are easier on the eyes in low-light conditions, reducing eye strain, while light themes are more suitable for well-lit environments.
2. **Customizable Text Colors**: Users can customize the text color for each data element displayed in the table. Customization allows users to tailor the appearance of the indicator to their liking and enhance readability.
3. **Show/Hide Data Options**: Users have the flexibility to show or hide each data element in the table individually. This feature enables users to focus on specific information they find most relevant, decluttering the chart and improving readability.
4. **Daily Range Analysis**: The script calculates and displays important metrics related to the daily price range of a financial instrument. These metrics include:
- Closing Range: Percentage indicating how close the closing price is to the daily low relative to the daily range. Helps traders assess where the closing price lies within the day's price action.
- Range Expansion: Percentage indicating the change in the daily price range compared to the previous day. Useful for identifying potential volatility shifts and trend continuation or reversal.
- StopH: Price level representing the midpoint between the day's open and close, commonly used as a reference for setting stop-loss orders.
- StopL: The low of the day, providing information about the lowest price reached during the trading session. Some traders like to use the Low of Day as a Stop Loss.
Overall, this script provides traders with essential insights into daily price movements, enabling them to make more informed trading decisions based on key price action metrics. The customization options enhance user experience and adaptability, catering to individual preferences and trading styles
Breaker Blocks Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Breaker Blocks Screener! This screener can provide information about the latest breaker blocks in up to 5 tickers. You can also customize the algorithm that finds the breaker blocks and the styling of the screener.
Features of the new Breaker Blocks Screener :
Find Latest Breaker Blocks Accross 5 Tickers
Latest Status, Restests & Volume
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
Breaker blocks form when an order block fails, or "breaks". It is often associated with market going in the opposite direction of the broken order block, and they can be spotted by following order blocks and finding the point they get broken, ie. price goes below a bullish order block.
The volume of a breaker block is simply the total volume of the bar that the original order block is broken. Often the higher the breaking bar's volume, the stronger the breaker block is.
This screener then finds breaker blocks accross 5 different tickers, and shows the latest information about them.
Status ->
Far -> The current price is far away from the breaker block.
Approaching ⬆️/⬇️ -> The current price is approaching the breaker block, and the direction it's approaching from.
Inside -> The price is currently inside the breaker block.
Retests -> Retest means the price to invalidate the breaker block, but failed to do so. Here you can see how many times the price retested the breaker block.
For the volume, check the top of the "How Does It Work" section.
🚩UNIQUENESS
This screener can detect latest breaker blocks and give information about them for up to 5 tickers. This saves the user time by showing them all in a dashboard at the same time. The screener shows the number of the retests of the breaker block as an unique trait. Another unique ability of the screener is that it shows the latest valid breaker block's volume in the dashboard.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan breaker blocks here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
Zone Invalidations -> Select between Wick & Close price for Order & Breaker Block Invalidation.
Swing Length -> Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
Median Supertrend [BackQuant]Median Supertrend Concept by BackQuant ©
This was created since the normal supertrend is noisy, in the attempts to remove that and still get a good signal we decided to use a special median calculation as the source to a modified supertrend. This allows us to reduce noise, and make the supertrend adaptive to volatility. The full description and reasoning, including definitions and backtests are as follows:
1. Definition of Median
The median is a statistical measure that identifies the middle value in a given set of numbers when those numbers are arranged in either ascending or descending order. If the dataset has an even number of observations, the median is calculated as the average of the two middle numbers. This measure is particularly useful in understanding the central tendency of data, especially in cases where the dataset may contain outliers that could skew the mean. For example, in a dataset representing the earnings of families, the median provides a more accurate reflection of the typical income than the mean if the dataset includes extreme values.
2. Understanding Supertrend and Its Use Case
Supertrend is a popular trend-following indicator used in technical analysis. It is computed using the Average True Range (ATR) to capture volatility, combined with a moving average. The indicator provides clear signals to traders about bullish or bearish trends, indicating potential entry and exit points. Traders often use Supertrend in various market conditions to enhance their trading strategies, leveraging its simplicity and effectiveness in identifying ongoing trends and reversals.
3. Rationale Behind Combining Median with Supertrend
The integration of the median into the Supertrend indicator seeks to mitigate the impact of outliers and sudden market spikes that can affect trend analysis. By using the median value of price data for trend determination, the Median Supertrend aims to offer a more stable and reliable indicator that reflects the underlying market conditions more accurately than traditional methods. This modification is intended to improve the timing of trend detection and the precision of entry and exit signals.
4. Key Differences and Benefits
Enhanced Stability: The use of median values reduces sensitivity to extreme price movements, offering a smoother trend line that can lead to more reliable trading signals.
Adaptive Sensitivity: Users can adjust the indicator's sensitivity to align with different trading styles and market conditions through customizable parameters like the ATR multiplier and lookback period.
Explicit Trading Signals: The indicator simplifies the trading process by providing clear, actionable long and short signals based on trend reversals, aiding in decision-making.
Customizability: Options to use Heikin Ashi candles, paint candles based on the trend, and toggle signal visibility allow traders to personalize the indicator to their preference.
5. User Inputs
The Median Supertrend indicator includes several user inputs to tailor its operation:
Use HA Candles as Source?: Option to base calculations on Heikin Ashi candles for smoother price data.
Paint Candles According to Trend?: Visual aid that colors candles based on the current trend direction, enhancing chart readability.
ATR Period and Multiplier: Parameters to adjust the sensitivity of the trend detection, allowing users to fine-tune the indicator.
Adaptive Lookback Period: Defines the period for the median calculation, offering flexibility in trend assessment.
Show Long and Short Signals: Enables traders to visualize entry signals directly on the chart.
6. Application in Trading
Traders can incorporate the Median Supertrend into their strategies as a standalone indicator for trend following or as a filter in a multi-indicator system. It is particularly useful in markets known for having outliers or sudden price jumps, as the median-based calculation provides a grounded trend analysis. This indicator can be applied across various timeframes and asset classes, making it a versatile tool for day traders, swing traders, and long-term investors alike.
7. Summary and Empirical Soundness
The integration of median values into the Supertrend indicator represents an innovative approach to trend analysis, addressing some of the volatility and outlier-related challenges inherent in traditional methods. This combination is empirically sound as it leans on the statistical robustness of the median to offer a more stable and reliable trend determination mechanism.
8. Relavant Backtests on Major Assets (1D Timeframe)
We include these backtests as a general proxy for how they work.
Please do your own calibrating to suit it to your own needs and backtest.
Past results don't = future results but they can help you understand how it functions.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
