PGO For Loop | mad_tiger_slayerPGO For Loop Indicator
The PGO For Loop indicator, inspired by Alex Orekhov's "Pretty Good Oscillator," and indicator originally made by Mark Johnson, the PGO designed as a fast and responsive tool to capture quick price movements in financial markets. This oscillator leverages a combination of moving averages and Average True Range (ATR) to measure price deviations, providing a concise yet powerful framework for identifying potential trade entry and exit points. What makes this
"enhanced" PGO indicator special is its ability to identify trending periods more accurately. By using thresholds, this allows the script to enter accurate long and short conditions extremely quickly.
Intended Uses:
Used to capture long-term trends:
Used to identify quick reversals:
Used on higher timeframes above 8hrs for more accurate signals
Used in strategies to enter and exit trades quickly
Can be used for Scalping
NOT Intended Uses:
Not to be used as Mean Reversion
Not to be used as valuation (Overbought or Oversold)
Key Features:
Quick Detection of Market Movements:
The indicator's primary focus is on speed, making it suitable for medium-term traders looking to capitalize on rapid price changes. It is particularly effective in trending or volatile markets.
Customizable Thresholds:
Users can set upper and lower thresholds to define long and short conditions, offering flexibility to adapt the indicator to different trading styles and asset classes.
Noisy but Purposeful:
While the PGO For Loop may generate frequent signals, it is specifically tuned for traders aiming to enter and exit trades quickly, embracing the noise as part of its effectiveness in capturing rapid market dynamics.
Integrated Visuals:
The script plots key levels and provides dynamic visual feedback through colored candles and shapes, enabling intuitive and quick decision-making.
How It Works:
Oscillator Calculation:
The PGO value is derived by comparing the source price's deviation from its moving average to the ATR. This highlights price movements relative to recent volatility.
Signal Identification:
When the oscillator exceeds the upper threshold, it signals potential long opportunities UNTIL the PGO reaches the lower threshold.
When the oscillator drops below the lower threshold, it signals potential short opportunities UNTIL the oscillator reaches above the upper threshold.
No signals occur when the oscillator lies between these thresholds.
Visual Cues:
Color-coded candles indicate market bias (green for long, red for short, gray for neutral).
Upward and downward triangles highlight changes in signal direction.
Note:
This indicator is intentionally "noisy," as it prioritizes capturing fast movements over filtering out minor fluctuations. Users should pair it with other tools or techniques to confirm signals and manage risk effectively.
FAST
AI x Meme Impulse Tracker [QuantraSystems]AI x Meme Impulse Tracker
Quantra Systems guarantees that the information created and published within this document and on the Tradingview platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors.
Important Note!
The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script.
Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance.
This ensures that the system is less likely to degrade in performance over time, compared to hyper-optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post-backtest.
Even More Important Note!!
The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing.
While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes.
Introduction
The AI x Meme Impulse Tracker is a cutting-edge, fast-acting rotational algorithm designed to capitalize on the strength of assets within pre-selected categories. Using a custom function built on top of the RSI Pulsar, the system measures momentum through impulses rather than traditional trend following methods. This allows for swifter reallocations based on short bursts of strength.
This system focuses on precision and agility - making it highly adaptable in volatile markets. The strategy is built around three independent asset categories - with allocations only made to the strongest asset in each - ensuring that capital movement (in particular between blockchains) is kept to a minimum for efficiency purposes while maintaining exposure to the highest performing tokens.
Legend
Token Inputs:
The Impulse Tracker is designed with dynamic asset selection - allowing traders to customize the inputs for each category. This feature enables flexible system management, as the number of active tokens within each category can be adjusted at any time. Whether the user chooses the default of 13 tokens per category, or fewer, the system will automatically recalibrate. This ensures that all calculations, from relative strength to individual performance assessments, adjust as required. Disabled tokens are treated by the system as if they don’t exist - seamlessly updating performance metrics and the Impulse Tracker’s allocation behavior to maintain the highest level of efficiency and accuracy.
System Equity Curve:
The Impulse Tracker plots both the rotational system’s equity and the Buy-and-Hold (or ‘HODL’) benchmark of Bitcoin for comparison. While the HODL approach allocates the entire portfolio to Bitcoin and functions as an index to compare to, the Impulse Tracker dynamically allocates based on strength impulses within the chosen tokens and categories. The system equity curve is representative of adding an equal capital split between the strongest assets of each category. The relative strength system does handle ‘ties’ of strength - in this situation multiple tokens from a single category can be included in the final equity curve, with the allocated weight to that category split between the tied assets.
TABLES:
Equity Stats:
This table is held in Quantra System's typical UI design language. It offers a comprehensive snapshot of the system’s performance, with key metrics organized to help traders quickly assess both short-term and cumulative results. The left side provides details on individual asset performance, while the right side presents a comparison of the system’s risk-adjusted metrics against a simple BTC Hodl strategy.
The leftmost column of the Equity Stats table showcases performance indicators for the system’s current allocations. This provides quick identification of the current strongest tokens, based on confirmed and non-repainting data as soon as the current opens and the last bar closes.
The right-hand side compares the performance differences between the system and Hodl profits, both on a cumulative basis and analyzing only the previous bar. The total number of position changes is also tracked in this table - an important metric when calculating total slippage and should be used to determine how ‘hands-on’ the strategy will be on the current timeframe.
The lower part of the table highlights a direct comparison of the AI x Memes Impulse strategy with buy-and-hold Bitcoin. The risk adjusted performance ratios, Sharpe, Sortino and Omega, are shown side by side, as well as the maximum drawdown experienced by both strategies within the set testing window.
Screener Table:
This table provides a detailed breakdown of the performance for each asset that has been the strongest in its category at some point and thus received an allocation. The table tracks several key metrics for each asset - including returns, volatility, Sharpe ratio, Sortino ratio, Omega ratio, and maximum drawdown. It also displays the signals for both current and previous periods, as well as the assets weight in the theoretical portfolio. Assets that have never received a signal are also included, giving traders an overview of which assets have contributed to the portfolio's performance and which have not played a role so far.
The position changes cell also offers important insights, as it shows the frequency of not just total position changes, but also rebalancing events.
Detailed Slippage Table:
The Detailed Slippage Table provides a comprehensive breakdown of the calculated slippage and fees incurred throughout the strategy’s operations. It contains several key metrics that give traders a granular view of the costs associated with executing the system:
Selected Slippage - Displays the current slippage rate, as defined in the input menu.
Removal Slippage - This accounts for any slippage or fees incurred when removing an allocation from a token.
Reallocation Slippage - Tracks the slippage or fees when reallocating capital to existing positions.
Addition Slippage - Measures the slippage or fees incurred when allocating capital to new tokens.
Final Slippage - Is the sum of all the individual slippage points and provides a quick view of the total slippage accounted for by the system.
The table is also divided into two columns:
Last Transaction Slippage + Fees - Displays any slippage or fees incurred based on position changes within the current bar.
Total Slippage + Fees - Shows the cumulative slippage and fees incurred since the portfolio’s selected start date.
Visual Customization:
Several customizable features are included within the input menu to enhance user experience. These include custom color palettes, both preloaded and user-selectable. This allows traders to personalize the visual appearance of the tables, ensuring clarity and consistency with their preferred interface themes and background coloring.
Additionally, users can adjust both the position and sizes of all the tables - enabling complete tailoring to the trader’s layout and specific viewing preferences and screen configurations. This level of customization ensures a more intuitive and flexible interaction with the system’s data.
Core Features and Methodologies
Advanced Risk Management - A Unique Filtering Approach:
The Equity Curve Activation Filter introduces an innovative way to dynamically manage capital allocation, aligning with periods of market trend strength. This filter is rooted in the understanding that markets move cyclically - altering between periods trending and mean-reverting periods. This cycle is especially pronounced in the crypto markets, where strong uptrends are often followed by prolonged periods of sideways movements or corrections as participants take profits and momentum fades.
The Cyclical Nature of Markets and Trend Following:
Financial markets do not trend indefinitely. Each uptrend or downtrend, whether over high and low timeframes, tends to culminate in a phase where momentum exhausts - leading to the sideways or corrective phases. This cycle results from the natural dynamics of market participants: during extended trends, more participants jump in, riding the momentum until profit taking causes the trend to slow down or reverse. This cyclical behavior occurs across all timeframes and in all markets - making it essential to adapt trading strategies in attempt to minimize losses during less favorable conditions.
In a trend following system, profitability often mirrors this cyclical pattern. Trend following strategies thrive when markets are moving directionally, capturing gains as price moves with strength in a single direction. However in phases where the market chops sideways, trend following strategies will usually experience drawdowns and reduced returns due to the impersistent nature of any trends. This fluctuation in trend following profitability can actually serve as one of the best coincident indicators of broader market regime change - when profitability begins to fade, it often signals a transition to drawn out unfavorable trend trading conditions.
The Equity Curve as a Market Signal
Within the Impulse Tracker, a continuous equity curve is calculated based upon the system's allocation to the strongest tokens. This equity curve effectively tracks the system’s performance under all market conditions. However, instead of solely relying on the direct performance of the selected tokens, the system applies additional filters to analyze the trend strength of this equity curve itself.
In the same way you only want to purchase an asset that is moving up in price, you only want to allocate capital to a strategy whose equity curve is trending upwards!
The Equity Curve Activation Filter consistently monitors the trend of this equity curve through various filter indicators, such as the “Wave Pendulum Trend”, the “Quasar QSM” and the “MAQSM” (an aggregate of multiple types of averages). These filters help determine whether the equity curve is trending upwards, signaling a favorable period for trend following. When the equity curve is in a positive trend, capital is allocated to the system as normal - allowing it to capture gains during favorable market conditions, Conversely, when the trend weakens and the equity curves begins to stagnate or decline, the activation filter shifts the system into a “cash” positions - temporarily halting allocations in order to prevent market exposure during choppy or mean reverting phases.
Timing Allocation With Market Conditions
This unique filtering approach ensures that the system is primarily active during periods when market trends are most supportive. By aligning capital allocations with the uptrend in trend following profitability, the system is designed to enter during periods of strong momentum and move to cash when momentum with the equity curve wanes. This approach reduces the risk of overtrading in less favorable conditions and preserves capital for the next favorable trend.
In essence the Equity Curve Allocation Filter serves as a dynamic risk management layer that leverages the cyclicality of trend following profitability in order to navigate shifting market phases.
Sensitivity and Signal Responsiveness:
The Quasar Sensitivity Setting allows users to fine-tune the system’s responsiveness to asset signals. High sensitivity settings lead to quicker position changes, making the system highly reactive to short term strength impulses. This is especially useful in fast moving markets where token strength can shift rapidly. The Sensitive setting might be more applicable to higher volatility or lower market cap assets - as the increased volatility increases the necessity of faster position cutting in order to front run the crowd. Of course - a balanced approach is ideal, as if the signals are too fast there will be too many whips and false signals. (And extra fees + slippage!)
The benefit of this script is because of the advanced slippage calculations, false signals are sufficiently punished (unlike systems without fees or slippage) - so it will become immediately apparent if the false signals have a significantly detrimental impact on the system’s equity curve.
Asset specific signals within each category are re-evaluated after the close of each bar to ensure that capital is always allocated to the highest performing asset. If a token’s momentum begins to fade the system swiftly reallocates to the next strongest asset within that category.
Category Filter - Allocates only to the Strongest Asset per group
One of the core innovations of the AI x Meme Impulse Tracker is the customizable Category Filter, which ensures that only the strongest-performing asset within each predefined group receives capital allocation. This approach not only increases the precision of asset selection but also allows traders to tailor the system to specific token narratives or categories. Sectors can include trending themes such as high-attention meme tokens, AI-driven tokens, or even categorize assets by blockchain ecosystems like Ethereum, Solana, or Base chain. This flexibility enables users to align their strategies with the latest market narratives or to optimize for specific groups, focusing on high-beta tokens within well defined sectors for a more targeted exposure. By keeping the focus on category leaders, the system avoids diluting its impact across underperforming assets, thereby maximizing capital efficiency and reducing unnecessary trading costs.
Dynamic Asset Reallocation:
Dynamic reallocation ensures that the system remains nimble and adapts to changing market conditions. Unlike slower systems, the Quasar method continually monitors for changes in asset strength and reallocates capital accordingly - ensuring that the system is always positioned in the highest performing assets within each category.
Position Changes and Slippage:
The Impulse Tracker places a strong emphasis on realistic simulation, prioritizing accuracy over inflated backtest results. This approach ensures that slippage is accounted for in a more aggressive manner than what may be experienced in real-world execution.
Each position change within the system - whether it’s buying, selling, reallocating, or rebalancing between assets - incurs slippage. Slippage is applied to both ends of every transaction: when a position is entered and exited, and when reallocating capital from one token to another. This dynamic behavior is further enhanced by a customizable slippage/fees input, allowing users to simulate realistic transaction costs based on their own market conditions and execution behaviors.
The slippage model works by applying a weighted slippage to the equity curve, taking into account the actual amount of capital being moved. Slippage is not applied in a blanket manner but rather in proportion to the allocation changes. For example, if the system reallocates from a single 100% position to two 50% allocations, slippage will be applied to the 50% removed from the first asset and the 50% added to the new asset, resulting in a 1x slippage multiplier.
This process becomes more granular when multiple assets are involved. For instance, if reallocating from two 50% positions to three 33% positions, slippage will be incurred on each of the changes, but at a reduced rate (⅔ x slippage), reflecting the smaller percentage of portfolio equity being moved. The slippage model accounts for all types of allocation shifts, whether increasing or decreasing the number of tokens held, providing a realistic assessment of system costs.
Here are some detailed examples to illustrate how slippage is calculated based on different scenarios:
100% → 50% / 50%: 1x slippage applied to both position changes (2 allocation changes).
50% / 50% → 33% / 33% / 33%: ⅔ x slippage multiplier applied across 3 allocation changes.
33% / 33% / 33% → 100%: 4/3 x slippage multiplier applied across 3 allocation changes.
In practice, not every position change will be rebalanced perfectly, leading to a lower number of transactions and lower costs in practice. Additionally, with the use of limit orders, a trader can easily reduce the costs of entering a position, as well as ensuring a competitive entry price.
By simulating slippage in this granular manner, the system captures the absolute maximum level of fees and slippage, in order to ensure that backtest results lean towards an underrepresentation - opposed to inflated results compared with practical execution.
A Special Note on Slippage
In the image above, the system has been applied to four different timeframes - 20h, 15h, 10h, and 5h - using identical settings and a selected slippage amount of 2%. By isolating a recent trend leg, we can illustrate an important concept: while the 15h timeframe is more profitable than the 20h timeframe, this difference stems from a core trading principle. Lower timeframes typically provide more data points and allow for quicker entries and exits in a robust system. This often results in reduced downside and compounding of gains.
However, slippage, fees, and execution constraints are limiting factors, especially in volatile, low-cap cryptocurrencies. Although lower timeframes can improve performance by increasing trade frequency, each trade incurs heavy slippage costs that accumulate - impacting the portfolio’s capital at a compounding rate. In this example, the chosen slippage rate of 2% per trade is designed to reflect the realistic trading costs, emphasizing how lower timeframe trading comes at the cost of increased slippage and fees
Finding the optimal balance between timeframe and slippage impact requires careful consideration of factors such as portfolio size, liquidity of selected tokens, execution speed, and the fee rate of the exchange you execute trades on.
Equity Curve and Performance Calculations
To provide a benchmark, the script also generates a Buy-and-Hold (or "HODL") equity curve that represents a complete allocation to Bitcoin. This allows users to easily compare the performance of the dynamic rotation system with that more traditional benchmark strategy.
The script tracks key performance metrics for both the dynamic portfolio and the HODL strategy, including:
Sharpe Ratio
The Sharpe Ratio is a key metric that evaluates a portfolio’s risk-adjusted return by comparing its ‘excess’ return to its volatility. Traditionally, the Sharpe Ratio measures returns relative to a risk-free rate. However, in our system’s calculation, we omit the risk-free rate and instead measure returns above a benchmark of 0%. This adjustment provides a more universal comparison, especially in the context of highly volatile assets like cryptocurrencies, where a traditional risk-free benchmark, such as the usual 3-month T-bills, is often irrelevant or too distant from the realities of the crypto market.
By using 0% as the baseline, we focus purely on the strategy's ability to generate raw returns in the face of market risk, which makes it easier to compare performance across different strategies or asset classes. In an environment like cryptocurrency, where volatility can be extreme, the importance of relative return against a highly volatile backdrop outweighs comparisons to a risk-free rate that bears little resemblance to the risk profile of digital assets.
Sortino Ratio
The Sortino Ratio improves upon the Sharpe Ratio by specifically targeting downside risk and leaves the upside potential untouched. In contrast to the Sharpe Ratio (which penalizes both upside and downside volatility), the Sortino Ratio focuses only on negative return deviations. This makes it a more suitable metric for evaluating strategies like the AI x Meme Impulse Tracker - that aim to minimize drawdowns without restricting upside capture. By measuring returns relative to a 0% baseline, the Sortino ratio provides a clearer assessment of how well the system generates gains while avoiding substantial losses in highly volatile markets like crypto.
Omega Ratio
The Omega Ratio is calculated as the ratio of gains to losses across all return thresholds, providing a more complete view of how the system balances upside and downside risk even compared to the Sortino Ratio. While it achieves a similar outcome to the Sortino Ratio by emphasizing the system's ability to capture gains while limiting losses, it is technically a mathematically superior method. However, we include both the Omega and Sortino ratios in our metric table, as the Sortino Ratio remains more widely recognized and commonly understood by traders and investors of all levels.
Usage Summary:
While the backtests in this description are generated as if a trader held a portfolio of just the strongest tokens, this was mainly designed as a method of logical verification and not a recommended investment strategy. In practice, this system can be used in multiple ways.
It can be used as above, or as a factor in forming part of a broader asset selection system, or even a method of filtering tokens by strength in order to inform a day trader which tokens might be optimal to look for long-only trading setups on an intrabar timeframe.
Final Summary:
The AI x Meme Impulse Tracker is a powerful algorithm that leverages a unique strength and impulse based approach to asset allocation within high beta token categories. Built with a robust risk management framework, the system’s Equity Curve Activation Filter dynamically manages capital exposure based on the cyclical nature of market trends, minimizing exposure during weaker phases.
With highly customizable settings, the Impulse Tracker enables precise capital allocation to only the strongest assets, informed by real-time metrics and rigorous slippage modeling in order to provide the best view of historical profitability. This adaptable design, coupled with advanced performance analytics, makes it a versatile tool for traders seeking an edge in fast moving and volatile crypto markets.
Multi-Kernel CCI [BackQuant]Multi-Kernel CCI
Conceptual Foundation and Innovation
It offers a fresh take on the Commodity Channel Index (CCI) by integrating three distinct kernel functions—Exponential Decay, Gaussian Decay, and Cosine Decay—to create a more robust and adaptive momentum indicator. The use of these kernel functions allows the CCI calculation to be more responsive to price changes while smoothing out noise, providing traders with clearer trend signals and reducing false alerts in varying market conditions.
Technical Composition and Calculation
The core of this indicator is a multi-kernel approach to calculating the CCI, where three different decay kernels are applied to the price source. Each kernel provides a unique weighting mechanism for price data over a user-defined lookback period. The result is an average of these three kernel calculations, which serves as the foundation for the CCI calculation. This innovative approach makes the Multi-Kernel CCI more adaptive to different market conditions compared to traditional CCI calculations.
Exponential Decay Kernel: Applies an exponential weighting to recent price data, giving more importance to recent values while smoothing out older data.
Gaussian Decay Kernel: Weights data using a Gaussian function, ensuring smooth transitions between price points and reducing outliers' impact.
Cosine Decay Kernel: Utilizes a cosine function to apply a unique oscillating weight to the data, capturing cyclical market movements more effectively.
Adaptive Thresholding: Like the Adaptive Momentum Oscillator, this indicator adjusts its long and short thresholds dynamically using percentile-based calculations over historical CCI values.
Features and User Inputs The Multi-Kernel CCI offers a wide range of customization options for traders:
Kernel Calculation Length & Alpha: Traders can fine-tune the sensitivity of the CCI by adjusting the length of the kernel calculation and the alpha parameter for the Exponential Decay Kernel.
Adaptive Thresholds: The indicator provides percentile-based thresholds for both long and short signals, allowing traders to dynamically adjust their signals based on historical data.
Extreme Value Detection: This feature highlights extreme overbought and oversold conditions with customizable thresholds and background hues, visually aiding in identifying high-probability reversal zones.
Divergence Detection: The script includes a divergence detection feature, identifying regular and hidden bullish or bearish divergences to help traders spot potential trend reversals.
Practical Applications The Multi-Kernel CCI excels in markets where adaptive trend detection and momentum confirmation are critical. Traders can leverage this tool in several ways:
Adaptive Trend Following: The dynamically adjusting thresholds allow traders to capture trends more effectively while avoiding false signals during consolidations or choppy markets.
Reversal Detection: The multi-kernel approach ensures that reversals are detected with greater precision, particularly in volatile markets where traditional indicators might fail.
Divergence Identification: With built-in divergence detection, the indicator provides traders with an early warning of potential trend reversals, helping to time their entries and exits more effectively.
Advantages and Strategic Value The Multi-Kernel CCI offers several strategic advantages over traditional CCI indicators:
Multi-Kernel Smoothing:
By using multiple decay kernels, this CCI calculation is better suited to detect subtle changes in market momentum, reducing the impact of noise and providing clearer trend signals.
Dynamic Thresholds:
The adaptive percentile-based thresholds ensure that the indicator remains relevant across different market conditions, enhancing signal accuracy.
Visual and Analytical Aids:
With features like extreme value detection and divergence spotting, this indicator equips traders with powerful tools to confirm trend strength and identify potential reversals.
Summary and Usage Tips
The Multi-Kernel CCI is a highly versatile tool for traders seeking a more adaptive and robust momentum indicator. Its multi-kernel foundation provides smoother, more reliable signals, while the adaptive thresholds and divergence detection features help traders refine their entries and exits. The dynamic nature of this indicator makes it ideal for both trend-following and reversal strategies in volatile markets.
Traders should experiment with the kernel calculation length and alpha parameter to align the indicator's sensitivity with their specific trading style and market conditions. Additionally, the adaptive thresholds can be fine-tuned to ensure the CCI captures the most significant trend changes without being overly reactive to short-term fluctuations.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Neo's %KIn my opinion the %K is the only part of the stochastic that you actually need. It's the fast RSI, so it responds much better to large price movements and reveals divergence a lot sooner than %D. The %D has no real confluence with the rest of my strategy so, I only use %K.
Divergence Macd+RSI Fast[RSU] -- No RepaintThis indicator combines the divergence of rsi and macd and displays it on the candlestick chart.
RSI:
1. When rsi is at a high point, once it falls by 1 k line, it will detect the divergence from the previous high point. This can quickly find the divergence that has taken effect and help you quickly capture the trend before a sharp decline or rise.
The difference between other RSI divergence indicators: the official divergence indicator is to detect the 5 and the k line, which may lead to a large amount of decline.
2. This indicator detects the previous high and the previous low of 5, 10, 20 lengths at the same time, instead of only detecting a fixed length, so that more deviations can be found.
MACD:
1. When MACD-diff line(orange color) is at a high point, once it falls by 1 k line, it will detect the divergence from the previous high point. This can quickly find the divergence that has taken effect and help you quickly capture the trend before a sharp decline or rise.
2. This indicator detects the previous high and the previous low of 5, 10, 20, 40 , 60 lengths at the same time, instead of only detecting a fixed length, so that more divergences can be found.
Notice:
Because it is a quick divergence detection, it is recommended to confirm that the divergence takes effect after the current k is completely closed first. I have identified this state in the indicator as "k not end".
Disadvantages and Risks:
Since it is a quick discovery, there will be error identification. Error divergences will recolor to grey.
Suggestion:
Use Alert catching divergence occurrences.
Please do not:
Don't go short in the uptrend, don't go long in the downtrend.
Top divergences that occur because of a strong uptrend are usually only temporary pullbacks. Bottom divergences in persistent declines are also temporary rallies. Do not attempt to trade such low-return trades.
It is recommended to use the divergence indicator when the stock price has made a new high and retraced, and once again made a new high, because this often leads to the end of the trend.
Divergence how to use:
1. After the previous candlestick was completely closed, a bottom divergence was found.
2. Open an long order at the beginning of the second bar, or as close to the bottom as possible (because the stop loss will be smaller).
3. Break the stop loss price below the previous low where the divergence occurred, which already means that the divergence is wrong.
MACD Divergence Fast by RSUAdvantages:
1. When MACD-diff line(orange color) is at a high point, once it falls by 1 k line, it will detect the divergence from the previous high point. This can quickly find the divergence that has taken effect and help you quickly capture the trend before a sharp decline or rise.
2. This indicator detects the previous high and the previous low of 5, 10, 20, 40, 60 lengths at the same time, instead of only detecting a fixed length, so that more divergences can be found.
Notice:
Because it is a quick divergence detection, it is recommended to confirm that the divergence takes effect after the current k is completely closed first. I have identified this state in the indicator as "k not end".
Disadvantages and Risks:
Since it is a quick discovery, there will be error identification. Error divergences will recolor to grey.
Suggestion:
Use “RSI Divergence Fast by RSU” at the same time, because RSI divergence usually occurs before macd, if the position diverges at the same time, the probability of success will increase.
Please do not:
Don't go short in the uptrend, don't go long in the downtrend.
Top divergences that occur because of a strong uptrend are usually only temporary pullbacks. Bottom divergences in persistent declines are also temporary rallies. Do not attempt to trade such low-return trades.
It is recommended to use the divergence indicator when the stock price has made a new high and retraced, and once again made a new high, because this often leads to the end of the trend.
Divergence how to use:
1. After the previous K line was completely closed, a bottom divergence was found.
2. Open an long order at the beginning of the second bar, or as close to the bottom as possible (because the stop loss will be smaller).
3. Break the stop loss price below the previous low where the divergence occurred, which already means that the divergence is wrong.
RSI Divergence Fast by RSUAdvantages:
1. When rsi is at a high point, once it falls by 1 k line, it will detect the divergence from the previous high point. This can quickly find the divergence that has taken effect and help you quickly capture the trend before a sharp decline or rise.
The difference between other RSI divergence indicators: the official divergence indicator is to detect the 5 and the k line, which may lead to a large amount of decline.
2. This indicator detects the previous high and the previous low of 5, 10, 20 lengths at the same time, instead of only detecting a fixed length, so that more deviations can be found.
Notice:
Because it is a quick divergence detection, it is recommended to confirm that the divergence takes effect after the current k is completely closed first. I have identified this state in the indicator as "k not end"
Disadvantages and Risks
Since it is a quick discovery, there will be error identification. I listed the difference between the two indicators when deleting errors. The indicator turns off the "delete error" option by default.
Please do not:
Don't go short in the uptrend, don't go long in the downtrend.
Top divergences that occur because of a strong uptrend are usually only temporary pullbacks. Bottom divergences in persistent declines are also temporary rallies. Do not attempt to trade such low-return trades.
It is recommended to use the divergence indicator when the stock price has made a new high and retraced, and once again made a new high, because this often leads to the end of the trend.
Divergence how to use:
1. After the previous K line was completely closed, a bottom divergence was found.
2. Open an long order at the beginning of the second bar, or as close to the bottom as possible (because the stop loss will be smaller).
3. Break the stop loss price below the previous low where the divergence occurred, which already means that the divergence is wrong.
RSI usage:
1. RSI is above the 50 line, in an uptrend, below 50 in a downtrend.
2. Above 70 is overbought, falling below the oversold zone may mean the end of the uptrend.
Below 30 is oversold, above the oversold zone may mean the end of the downtrend.
Buff Averages [CC]The Buff Averages were created by Buff Dormeier (Stocks and Commodities Feb 2001) and this is another hidden gem that is a combo of a volume weighted indicator and a moving average crossover system. It uses a special method to calculate the weighting based on volume. The colored line (fast buff) will follow the price closely and you use the other line to act as a trend confirmation. I have included strong buy and sell signals in addition to normal ones so strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish!
RSI Cross [xaurr]This is simple but profitable rsi cross strategy, to find optimal values you can change rsi and ema periods.
Good Luck!
LSMA Wave RiderThe LSMA Wave Rider uses Least Squares Moving Average to make a fast oscillator ideal for scalping lower timeframe charts. Upper and lower bands contract during pullback and expand as it "booms". The perfect entry is the first crossover after bands expand. This is a great tool for entering trades.
The above image shows two examples of perfect entries:
1. The upper and lower bands contract getting tighter as it pulls back.
2. The upper and lower bands then begin to expand as it gets ready to fly.
3. The oscillator crosses over showing entry point.
* Please note that this strategy may not work during major downtrends. *
Oscillator 2 is used to detect diversions. Reduce the number to pick up shorter diversions and increase to 200 to pickup larger diversions.
Mix signal-rileksdevMix Signal Indicator by rileksdev
Indikator ini mengandungi
-3 line bewarna hjau,merah,biru
-1 indikator MACD yang sudah diubahsuai supaya boleh mengesan pergerakan awal harga akan turun atau naik.
-Support & Resistance sudah tersedia pada chart,jadi tidak perlu susah payah cari sendiri
-Buy signal & Sell signal yang keluar apabila harga akan membuat kenaikan atau penurunan
Cara guna:
Line biru: digunakan untuk intraday timetrame 5minit.
Line hijau & merah digunakan untuk Intraday pada timeframe 15minit timeframe 30minit untuk swing short term atau midterm.
MACD MOD untuk mengesan pergerakan awal harga akan turun atau naik.
Garis bintik hijau(Support) & Garis bintik merah (Resistance) yang sudah tersedia pada Chart
Buy signal apabila harga akan membuat kenaikan
Sell signal apabila harga akan membuat penurunan
Double Stochastic in one_PAYDARDouble Stochastic in one_PAYDAR
Hello dear friends;
Double Stochastic in one_PAYDAR function:
It actually means that I have used two stochastic oscillators in one oscillator with several lines in different degrees,
First Stochastic: or "Fast Stochastic", as its name implies, is a stochastic oscillator with fast parameters and is capable of detecting small oscillations and small trends.
Second Stochastic : or "slow stochastic" means a stochastic oscillator with slow parameters and is capable of detecting slightly larger fluctuations and trends.
(Of course, here I just put parameter D, because I did not want it to be crowded.)
*** This system just Suggests you for points. ***
_____________________________________________________________________________
How to use this system ( just Suggests you) :
Buy: Whenever the first stochastic (fast stochastic ) crosses in the range of 20 or below and moves upwards, and at the same time the second stochastic (slow stochastic ) moves or crosses the green 30 line, a good time To buy or take a long position.
Sell: Whenever the first stochastic (fast stochastic ) crosses in the range of 80 or above and moves down, and at the same time the second stochastic (slow stochastic ) moves or crosses the red 70 line, a good time For sale or short position.
_____________________________________________________________________________
*** This system just Suggests you for points. ***
My suggestion is not to use this system alone and conclude about entry and exit points according to charts, news, market fluctuations and trend direction.
This system was created by Stochastic Oscillator, which is public and open source on the TradingView site.
***I used the Stochastic Oscillator as a public domain and open source on the TradingView site***
In fast stochastics the values of the parameters are set as fast motion and in slow stochastics the values of the parameters are set as slow motion. In fact, these values of the parameters according to the function and price movement in the candles are fast and slow, and I have determined these values at my suggestion, which, of course, I have consulted with several people.
For easier use and personalization for each person, I have left access to the parameters in this system and you can easily change the parameters as you like and use it optimally for yourself.
Of course, my suggestion is to use the numbers and values of the parameters I have written.
I have put different values, which I think will be very useful for trading swings and even below the daily, but you can change the values of different parameters to your liking.
This oscillator is made of a stochastic oscillator that is open source and public on the TradingView site , of course, due to the changes I have made in the parameter values and the inclusion of two stochastics in one oscillator.
*** In this system, the main and basic oscillators is used, It is available as open source and public on the TradingView site ***
Please comment on the use of this oscillator as well as how to use it and your experiences, I will definitely welcome comments and criticisms.
I am very grateful and very loyal to TradingView ,
Be successful and profitable.
Doble stochastic oscillator fast and slowThis is a two stochastic in one indicator :
We have a normal stochastic, and a slower one in order to identify changes in the price movement.
At the same time I added more levels, so its easier visually to identify in each scenario we are.
The slower oscillator, also change color based on direction it has.
Green color = long direction - > buy
Red color = short direction - > sell
[astropark] Volatility IndicatorDear Followers,
today another interesting script: Volatility Indicator .
This indicator measures the volatility of the market you see in the timeframe you see, in a scale between 0 and 1.
It works on cryptocurrencies, commodities, stocks, indexes and forex.
You will see 2 volatility waves:
a black one (with green and blue shadow for increasing and decreasing mode), which is the "faster" one
a red one (with orange and purple shadow for increasing and decreasing mode), which is the "slower" one
The indicator highlights high volatility when it's near the top (1), while low volatility when near the bottom (0).
You can combine this indicator with your own strategy and indicators to validate them :
on low volatility it often happens that a signal fails to be profitable, as it lacks fuel
while it's better if volatility is over low level as price has more room to run while volatility increasing to the top
This indicator also lets you set alerts when volatility exceeds high level or low level.
This is a premium indicator , so send me a private message in order to get access to this script.
Fractal Adaptive Entry IndicatorThis entry indicator was inspired by John Ehle'rs "Fractal Adaptive Moving Average"
It's a very sensitive entry indicator that must be paired with a long-term trend detector in order to filter false positives.
Warning I have not backtested this indicator and will not make any claims to its performance.
Visually, it looks promising, however, backtesting and statistical analysis takes time.
Happy trading
<3
Dow Factor Stoch RSIThe indicator was generated by adding the Dow Factor to the Stochastic Relative Strength Index.( Stoch RSI )
The Dow factor is the effect of the correlation coefficient, which determines the relationship between volume and price, on the existing indicators.
With these codes we are able to integrate them numerically into the indicators.
For more information on the Dow factor, please see my indicator:
This code is open source under the MIT license. ( github.com )
My dow factor updates will continue.We adapted the indicators and saw successful results, now it is time to examine and develop the factor itself.
Stay tuned , best regards.
Turbo Scaler - The Art Of Being (too) EarlyIntroduction
Fast smooth indicators that produce early signals can sound utopic but mathematically its not a huge deal, the effect of early outputs based on smooth inputs can be seen on differentiators crosses, this is why i propose this indicator that aim to return extra fast signals based on a slightly modified max-min normalization method. The indicator introduce inherent smoothing without having an huge impact on the indicator reactivity.
The Indicator
The indicator is based on max-min normalization (like the stochastic oscillator) however instead of using the highest/lowest of the input we use the highest and lowest of the moving average of the input. This process using as input the closing price and the moving average closing price will return two lines, and because of the nature of max-min normalization we can see that the trigger line (in orange) produce earlier crosses. length control the highest/lowest period while smooth control the output lines smoothness (50 by default).
alpha control the scaling amount, with higher values of alpha creating more constrained scale, when alpha = 1 the scale is in a range of (0,1) while lower values of alpha can make the output move more freely.
alpha = 0.25
alpha = 1
Higher values of alpha create earlier signals.
Downsides Of Early Crosses
Of course such indicator make us exposed to the trend as seen below.
We can nonetheless protect ourselves against such cases scenarios by lowering alpha.
lowering alpha allow to catch movements of the trend without loosing much reactivity at the cost of an increased umber of trades.
Possible Uses
The proposed indicator allow for an high number of uses because of its scale, reactive nature...etc. A method that allow us to go with the main trend is by taking into account the crosses between the lines and the sign of the lines, for example :
The first signal (green) happen when the main line (in blue) crossover the trigger (orange) while both are > 0, the same happen with the second signal however both lines are < 0. This method can use certain levels instead of the sign (main line crossover trigger while both > 0.7...etc).
This method is great for the indicator because such cases scenarios does not happen a lot with ranging markets, we can clearly that when trending the trigger can have the tendency to be flat and higher than 0 thus allowing for the main line to produce those signals.
Conclusion
I have presented a super reactive crosses indicator based on max-min normalization with the ability to both be smooth and produce early entries/exits signals, different methods have been presented in order to allow for different setups using this indicator.
The introduction of the alpha parameter allow for more control which is what those kind of indicators needs. I hope you find an use to it :)
Support Me
Making indicators sure is hard, it takes time and it can be quite lonely to, so i would love talking with you guys while making them :) There isn't better support than the one provided by your friends so drop me a message.
Adaptive StochasticAdapt To The Right Situation
There are already some Adaptive Stochastic scripts out there, but i didn't see the concept of using different periods highest/lowest for their calculations. What we want
for such oscillator is to be active when price is trending and silent during range periods. Like that the information we will see will be clear and easy to use.
Switching between a long term highest/lowest during range periods and a short term highest/lowest during trending periods is what will create the adaptive stochastic.
The switching is made thanks to the Efficiency Ratio , the period of the efficiency ratio is determined by the length parameter.
The period of the highest and lowest will depend on the slow and fast parameters, if our efficiency ratio is close to one (trending market) then the indicator will use highest and lowest of period fast , making the indicator more reactive, if our efficiency ratio is low (ranging market) then the indicator will use highest and lowest of period slow , making the indicator less reactive.
The source of the indicator is a running line ( lsma ) of period slow-fast .
it is also possible to switch the parameters values, making the indicator reactive during ranging market and less reactive during trending ones.
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
Mean Reversion Short / Long Oscillating strategy that does pretty well on 1M forex markets and gets you a lot of signals. Better to use after an exhaustive move or in a consolidation phase.
[RS][JR]RSI Ribbon + CandleRSI Ribbon + Candle
By Ricardo Santos and JR
In this chart rendering we are combining RSI and Moving Averages. For an added features we included colors to the candles and ribbons. Lime and green displays a strong bullish trend, yellow is caution or no trade, red and maroon are bearish trends. You can also find divergences using the ribbon.
Divergence
