Cari dalam skrip untuk "momentum"
MomentumMomentum is differences between closing price and closing price on day before n day.
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モメンタムは、n日前の終値と当日終値の差を数値化したものです。
モメンタムの移動平均線も同時に作成します。
Absolute Momentum (Time Series Momentum)Absolute momentum , also known as time series momentum , focuses on the trend of an asset's own past performance to predict its future performance. It involves analyzing an asset's own historical performance, rather than comparing it to other assets.
The strategy determines whether an asset's price is exhibiting an upward (positive momentum) or downward (negative momentum) trend by assessing the asset's return over a given period (standard look-back period: 12 months or approximately 250 trading days). Some studies recommend calculating momentum by deducting the corresponding Treasury bill rate from the measured performance.
Absolute Momentum Indicator
The Absolute Momentum Indicator displays the rolling 12-month performance (measured over 250 trading days) and plots it against a horizontal line representing 0%. If the indicator crosses above this line, it signifies positive absolute momentum, and conversely, crossing below indicates negative momentum. An additional, optional look-back period input field can be accessed through the settings.
Hint: This indicator is a simplified version, as some academic approaches measure absolute momentum by subtracting risk-free rates from the 12-month performance. However, even with higher rates, the values will still remain close to the 0% line.
Benefits of Absolute Momentum
Absolute momentum, which should not be confused with relative momentum or the momentum indicator, serves as a timing instrument for both individual assets and entire markets.
Gary Antonacci , a key contributor to the absolute momentum strategy (find study below), emphasizes its effectiveness in multi-asset portfolios and its importance in long-only investing. This is particularly evident in a) reducing downside volatility and b) mitigating behavioral biases.
Moskowitz, Ooi, and Pedersen document significant 'time series momentum' across various asset classes, including equity index, currency, commodity, and bond futures, in 58 liquid instruments (find study below). There's a notable persistence in returns ranging from one to 12 months, which tends to partially reverse over longer periods. This pattern aligns with sentiment theories suggesting initial under-reaction followed by delayed over-reaction.
Despite its surprising ease of implementation, the academic community has successfully measured the effects of absolute momentum across decades and in every major asset class, including stocks, bonds, commodities, and foreign exchange (FX).
Strategies for Implementing Absolute Momentum:
To Buy a Stock:
Select a Look-Back Period: Choose a historical period to analyze the stock's performance. A common period is 12 months, but this can vary based on your investment strategy.
Calculate Excess Return: Determine the stock's excess return over this period. You can also assume a risk-free rate of "0" to simplify the process.
Evaluate Momentum:
If the excess return is positive, it indicates positive absolute momentum. This suggests the stock is in an upward trend and could be a good buying opportunity.
If the excess return is negative, it suggests negative momentum, and you might want to delay buying.
Consider further conditions: Align your decision with broader market trends, economic indicators, or fundamental analysis, for additional context.
To Sell a Stock You Own:
Regularly Monitor Performance: Use the same look-back period as for buying (e.g., 12 months) to regularly assess the stock's performance.
Check for Negative Momentum: Calculate the excess return for the look-back period. Again, you can assume a risk-free rate of "0" to simplify the process. If the stock shows negative momentum, it might be time to consider selling.
Consider further conditions:Align your decision with broader market trends, economic indicators, or fundamental analysis, for additional context.
Important note: Note: Entering a position (i.e., buying) based on positive absolute momentum doesn't necessarily mean you must sell it if it later exhibits negative absolute momentum. You can initiate a position using positive absolute momentum as an entry indicator and then continue holding it based on other criteria, such as fundamental analysis.
General Tips:
Reassessment Frequency: Decide how often you will reassess the momentum (monthly, quarterly, etc.).
Remember, while absolute momentum provides a systematic approach, it's recommendable to consider it as part of a broader investment strategy that includes diversification, risk management, fundamental analysis, etc.
Relevant Capital Market Studies:
Antonacci, Gary. "Absolute momentum: A simple rule-based strategy and universal trend-following overlay." Available at SSRN 2244633 (2013)
Moskowitz, Tobias J., Yao Hua Ooi, and Lasse Heje Pedersen. "Time series momentum." Journal of financial economics 104.2 (2012): 228-250
New Momentum IndicatorThe Momentum Indicator was created by Darryl W Maddox (Stocks & Commodities V. 9:4 (158-159)) and it is one of the simplest and most powerful indicators out there. Buy when the indicator goes over 0 and sell when it falls below 0
Let me know what other indicators you would like to see me write a script for!
ATR Momentum [QuantVue]ATR Momentum is a dynamic technical analysis tool designed to assess the momentum of a securities price movement. It utilizes the comparison between a faster short-term Average True Range (ATR) and a slower long-term ATR to determine whether momentum is increasing or decreasing.
This indicator visually represents the momentum relationship by plotting both ATR values as lines on a chart and applying color fill between the lines based on if momentum is increasing or decreasing.
When the short-term ATR is greater than the long-term ATR, representing increasing momentum, the area between them is filled with green.
Conversely, when the short-term ATR is less than the long-term ATR line, the area between them is filled with red. This red fill indicates decreasing momentum.
Don't hesitate to reach out with any questions or concerns.
We hope you enjoy!
Cheers.
TS - Momentum OscillatorWhat is it?
RMI & EMA based momentum oscillator to act as a supporting indicator to the rest of the Tradespot indicator suite. Combined trading is made intuitive and accessible to traders of all levels.
Momentum can help you confirm an existing trade, whether to hold position and avoid fakeouts. or it may let you know when the market is losing steam for example and could be a good point to take profit.
Access
This is one of the indicators in our greater trading suite that we offer. Just PM me for access!
Ultimate Momentum"Ultimate Momentum" – Elevating Your Momentum Analysis
Experience a refined approach to momentum analysis with "Ultimate Momentum," a sophisticated indicator seamlessly combining the strengths of RSI and CCI. This tool offers a nuanced understanding of market dynamics with the following features:
1. Harmonious Fusion: Witness the dynamic interplay between RSI and CCI, providing a comprehensive understanding of market nuances.
2. Optimized CCI Dynamics: Delve confidently into market intricacies with optimized CCI parameters, enhancing synergy with RSI for a nuanced perspective on trends.
3. Standardized Readings: "Ultimate Momentum" standardizes RSI and CCI, ensuring consistency and reliability in readings for refined signals.
4. Native TradingView Integration: Immerse yourself in the reliability of native TradingView codes for RSI and CCI, ensuring stability and compatibility.
How RSI and CCI Work Together:
RSI (Relative Strength Index): Captures price momentum with precision, measuring the speed and change of price movements.
CCI (Commodity Channel Index): Strategically integrated to complement RSI, offering a unique perspective on price fluctuations and potential trend reversals.
Why "Ultimate Momentum"?
In a crowded landscape, "Ultimate Momentum" stands out, redefining how traders interpret momentum. Gain a profound understanding of market dynamics, spot trend reversals, and make informed decisions.
Your Insights Matter:
Share your suggestions to enhance "Ultimate Momentum" in the comments. Your feedback is crucial as we strive to deliver an unparalleled momentum analysis tool.
Price Weighted MomentumThis indicator is a momentum indicator that is standardized by price. A.K.A (momentum / price)
The purpose of this indicator is to compare momentum between different assets regardless of price.
EX: Bitcoin will always have more momentum than XLE because it's price is $19000 (as of writing this) compared to XLE's price of $40 (as of writing this). But if you divide the momentum by price, you get a standardized value to better compare the 2.
This indicator can be used to compare everything on TradingView.
HOW TO USE/INTERPRET
Positive values denote an uptrend
Negative values denote a downtrend
A value of 0 (or very very close to 0) denotes sideways price action
WHAT'S INCLUDED
Price Weighted Momentum (Unsmoothed by default)
Optional smoothing with either a simple or exponential moving average
Side note: I only added functionality of smoothing for EMA and SMA for my personal uses, but if you want a version of this with another way of smoothing (e.g. HMA, SSMA, etc.) that you would like, the cost of me adding that for you is a follow on Twitter. Just DM me there :)
ADX Momentum Shaded CandlesDescription:
The "ADX Momentum Shaded Candles" indicator (ADXMSC) is an overlay indicator that enhances candlestick charts by adding shading based on the momentum derived from the Average Directional Index (ADX). This indicator provides visual cues about the strength of bullish and bearish momentum by adjusting the transparency of the candlesticks.
How it Works:
The indicator utilizes the ADX indicator to calculate the values of +DI (Directional Indicator Plus) and -DI (Directional Indicator Minus) based on user-defined parameters. It then determines the transparency levels for the bullish and bearish candlesticks based on the calculated values of +DI and -DI. Higher values of +DI or -DI result in lower transparency levels, while lower values increase transparency.
Transparency Calculation:
The transparency of the bullish and bearish candlesticks is adjusted based on the values of +DI and -DI, which reflect the momentum of the price movement. Transparency is inversely proportional to these values, with higher values resulting in lower transparency. To calculate transparency, the indicator uses the formula 100 minus the value of +DI or -DI multiplied by 2. This ensures that higher values of +DI or -DI produce more opaque candlesticks.
Usage:
To effectively use the "ADX Momentum Shaded Candles" indicator (ADXMSC), follow these steps:
1. Apply the indicator to your chart by adding it from the available indicators.
2. Observe the candlesticks on the chart:
- Bullish candlesticks are represented by the original bullish color with adjusted transparency.
- Bearish candlesticks are represented by the original bearish color with adjusted transparency.
3. Analyze the transparency levels of the candlesticks to assess the strength of bullish and bearish momentum. Less transparent candlesticks indicate stronger momentum, while more transparent ones suggest weaker momentum.
4. Combine the visual information from the shaded candlesticks with other technical analysis tools, such as support and resistance levels, trend lines, or oscillators, to confirm potential trade opportunities.
5. Customize the indicator's parameters, such as the ADX length and smoothing, to suit your trading preferences.
6. Implement appropriate risk management strategies, including setting stop-loss orders and position sizing, to manage your trades effectively and protect your capital.
Momentum with ATR and Volatility [ST]Momentum with ATR and Volatility
Description in English:
This indicator combines price momentum with market volatility to identify entry and exit points in trades.
It utilizes the difference in closing prices (momentum) and the Average True Range (ATR) to measure volatility. Buy and sell signals are generated based on the combination of these two components.
Detailed Explanation:
Configuration:
Momentum Length: This input defines the period for calculating the momentum, which is the difference between the closing prices. The default value is 10.
ATR Length: This input defines the period for calculating the Average True Range (ATR), which measures market volatility. The default value is 14.
ATR Threshold: This input defines the threshold multiplier for the ATR to generate buy and sell signals. The default value is 3.5.
Momentum Calculation:
Momentum is calculated as the difference between the current closing price and the closing price momentum_length periods ago.
ATR Calculation:
The ATR is calculated based on the specified length and is used to measure market volatility.
Buy and Sell Signals:
Buy Signal: Generated when momentum is positive, the current close is higher than the previous close, and momentum is greater than ATR * threshold.
Sell Signal: Generated when momentum is negative, the current close is lower than the previous close, and momentum is less than -ATR * threshold.
Plotting:
Buy signals are plotted as green triangles below the bars.
Sell signals are plotted as red triangles above the bars.
Momentum and ATR thresholds are plotted in a separate panel below the main chart.
Momentum is plotted as a blue line.
The ATR threshold lines are plotted as solid orange lines.
Indicator Benefits:
Momentum Measurement: Helps traders gauge the momentum of price movements.
Volatility Measurement: Utilizes ATR to measure market volatility, providing a more comprehensive analysis.
Visual Cues: Provides clear visual signals for buy and sell points, aiding in making informed trading decisions.
Justification of Component Combination:
Combining momentum with ATR provides a more robust measure of potential entry and exit points by considering both price movement and market volatility.
How Components Work Together:
The script calculates momentum and ATR for the specified periods.
It generates buy and sell signals based on the conditions of momentum and ATR.
The signals and values are plotted on the chart to provide a visual representation, helping traders identify potential trading opportunities.
Título: Indicador de Momentum com ATR e Volatilidade
Descrição em Português:
Este indicador combina o momentum do preço com a volatilidade do mercado para identificar pontos de entrada e saída em operações.
Utiliza a diferença entre os preços de fechamento (momentum) e o Average True Range (ATR) para medir a volatilidade. Sinais de compra e venda são gerados com base na combinação desses dois componentes.
Explicação Detalhada:
Configuração:
Comprimento do Momentum: Este parâmetro define o período para calcular o momentum, que é a diferença entre os preços de fechamento. O valor padrão é 10.
Comprimento do ATR: Este parâmetro define o período para calcular o Average True Range (ATR), que mede a volatilidade do mercado. O valor padrão é 14.
Limite do ATR: Este parâmetro define o multiplicador de limite para o ATR para gerar sinais de compra e venda. O valor padrão é 3.5.
Cálculo do Momentum:
O momentum é calculado como a diferença entre o preço de fechamento atual e o preço de fechamento momentum_length períodos atrás.
Cálculo do ATR:
O ATR é calculado com base no comprimento especificado e é usado para medir a volatilidade do mercado.
Sinais de Compra e Venda:
Sinal de Compra: Gerado quando o momentum é positivo, o fechamento atual é maior que o fechamento anterior, e o momentum é maior que ATR * threshold.
Sinal de Venda: Gerado quando o momentum é negativo, o fechamento atual é menor que o fechamento anterior, e o momentum é menor que -ATR * threshold.
Plotagem:
Sinais de compra são plotados como triângulos verdes abaixo das barras.
Sinais de venda são plotados como triângulos vermelhos acima das barras.
O momentum e os limites do ATR são plotados em um painel separado abaixo do gráfico principal.
O momentum é plotado como uma linha azul.
As linhas de limite do ATR são plotadas como linhas laranjas sólidas.
Benefícios do Indicador:
Medição do Momentum: Ajuda os traders a avaliar o momentum dos movimentos de preços.
Medição da Volatilidade: Utiliza o ATR para medir a volatilidade do mercado, proporcionando uma análise mais abrangente.
Sinais Visuais: Fornece sinais visuais claros para pontos de compra e venda, auxiliando na tomada de decisões informadas.
Justificação da Combinação de Componentes:
Combinar o momentum com o ATR fornece uma medida mais robusta de potenciais pontos de entrada e saída ao considerar tanto o movimento dos preços quanto a volatilidade do mercado.
Como os Componentes Funcionam Juntos:
O script calcula o momentum e o ATR para os períodos especificados.
Gera sinais de compra e venda com base nas condições de momentum e ATR.
Os sinais e valores são plotados no gráfico para fornecer uma representação visual, ajudando os traders a identificar oportunidades de negociação potenciais.
MLB Momentum IndicatorMLB Momentum Indicator is a no‐lookahead technical indicator designed to signal intraday trend shifts and potential reversal points. It combines several well‐known technical components—Moving Averages, MACD, RSI, and optional ADX & Volume filters—to deliver high‐probability buy/sell signals on your chart.
Below is an overview of how it works and what each part does:
1. Moving Average Trend Filter
The script uses two moving averages (fast and slow) to determine the primary trend:
isUpTrend if Fast MA > Slow MA
isDownTrend if Fast MA < Slow MA
You can select the MA method—SMA, EMA, or WMA—and customize lengths.
Why it matters: The indicator only gives bullish signals if the trend is up, and bearish signals if the trend is down, helping avoid trades that go against the bigger flow.
2. MACD Confirmation (Momentum)
Uses MACD (with user‐defined Fast, Slow, and Signal lengths) to check momentum:
macdBuySignal if the MACD line crosses above its signal line (bullish)
macdSellSignal if the MACD line crosses below its signal line (bearish)
Why it matters: MACD crossovers confirm an emerging momentum shift, aligning signals with actual price acceleration rather than random fluctuation.
3. RSI Overbought/Oversold Filter
RSI (Relative Strength Index) is calculated with a chosen length, plus Overbought & Oversold thresholds:
For long signals: the RSI must be below the Overbought threshold (e.g. 70).
For short signals: the RSI must be above the Oversold threshold (e.g. 30).
Why it matters: Prevents buying when price is already overbought or shorting when price is too oversold, filtering out possible poor‐risk trades.
4. Optional ADX Filter (Trend Strength)
If enabled, ADX must exceed a chosen threshold (e.g., 20) for a signal to be valid:
This ensures you’re only taking trades in markets that have sufficient directional momentum.
Why it matters: It weeds out choppy, sideways conditions where signals are unreliable.
5. Optional Volume Filter (High‐Participation Moves)
If enabled, the indicator checks whether current volume is above a certain multiple of its moving average (e.g., 1.5× average volume).
Why it matters: High volume often indicates stronger institutional interest, validating potential breakouts or reversals.
6. ATR & Chandelier (Visual Reference)
For reference only, the script can display ATR‐based stop levels or a Chandelier Exit line:
ATR (Average True Range) helps gauge volatility and can inform stop‐loss distances.
Chandelier Exit is a trailing stop technique that adjusts automatically as price moves.
Why it matters: Though this version of the script doesn’t execute trades, these lines help you see how far to place stops or how to ride a trend.
7. Final Bullish / Bearish Signal
When all conditions (trend, MACD, RSI, optional ADX, optional Volume) line up for a long, a green “Long” arrow appears.
When all conditions line up for a short, a red “Short” arrow appears.
Why it matters: You get a clear, on‐chart signal for each potential entry, rather than needing to check multiple indicators manually.
8. Session & Date Filtering
The script allows choosing a start/end date and an optional session window (e.g. 09:30–16:00).
Why it matters: Helps limit signals to a specific historical backtest range or trading hours, which can be crucial for day traders (e.g., stock market hours only).
Putting It All Together
Primary Trend → ensures you trade in line with the bigger direction.
MACD & RSI → confirm momentum and avoid overbought/oversold extremes.
ADX & Volume → optional filters for strong trend strength & genuine interest.
Arrows → each potential buy (Long) or sell (Short) signal is clearly shown on your chart.
Use Cases
5‐Minute Scalping: Shorter RSI/MACD lengths to catch small, frequent intraday moves.
Swing Trading: Larger MAs, bigger RSI thresholds, and using ADX to filter only major trends.
Cautious Approach: Enable volume & ADX filters to reduce false signals in choppy markets.
Benefits & Limitations
Benefits:
Consolidates multiple indicators into one overlay.
Clear buy/sell signals with optional dynamic volatility references.
Flexible user inputs adapt to different trading styles/timeframes.
Limitations:
Like all technical indicators, it can produce false signals in sideways or news‐driven markets.
Success depends heavily on user settings and the particular market’s behavior.
Summary
The MLB Momentum Indicator combines a trend filter (MAs), momentum check (MACD), overbought/oversold gating (RSI), and optional ADX/Volume filters to create clear buy/sell arrows on your chart. This approach encourages trading in sync with both trend and momentum, and helps avoid suboptimal entries when volume or trend strength is lacking. It can be tailored to scalp micro‐moves on lower timeframes or used for higher‐timeframe swing trading by adjusting the input settings.
ATR + Momentum Shifts w/Take ProfitThis script is a technical analysis indicator designed to assist in identifying potential entry points and setting take profit levels in trading. It combines the Average True Range (ATR) indicator, momentum shifts, and customizable take profit levels to provide insights into potential market movements.
Differences from Currently Published Ones:
This script is unique due to its use of a combination of elements:
ATR and Momentum: The script combines the ATR indicator to provide dynamic support and resistance levels with the momentum indicator to identify shifts in the underlying momentum.
Customizable Take Profit Levels: It offers the ability to set take profit levels based on customizable multipliers of the ATR, helping traders manage potential profits.
How to Use:
ATR Bands: The script plots upper and lower ATR bands as potential dynamic support and resistance levels.
Shift Arrows: Arrows are plotted below bars for potential long entry opportunities (green triangle) and above bars for potential short entry opportunities (yellow triangle).
Take Profit Levels: The script also plots take profit levels both above and below the source price based on the ATR multipliers set in the inputs.
Markets and Conditions:
This script can be used across various financial markets, including stocks, forex, commodities, and cryptocurrencies. It's most effective in trending markets where momentum shifts can signal potential reversals or continuation of trends. Traders should consider the following conditions:
Trend Confirmation: Look for momentum shifts in the direction of the prevailing trend for higher probability setups.
Volatility: Higher volatility can amplify ATR movements and subsequently affect the placement of ATR bands and take profit levels.
Risk Management: Always implement proper risk management strategies to protect your capital.
Additional Considerations:
Customization: Traders can adjust input parameters like ATR length, momentum length, and take profit multipliers to match their trading style and market conditions.
Combining with Other Indicators: Consider using this indicator in conjunction with other technical indicators or chart patterns for confirmation.
Simple Volatility MomentumOverview:
The Simple Volatility Momentum indicator calculates the mean and standard deviation of the changes of price (returns) using various types of moving averages (Incremental, Rolling, and Exponential). With quantifying the dispersion of price data around the mean, statistical insights are provided on the volatility and the movements of price and returns. The indicator also ranks the mean absolute value of the changes of price over a specified time period which helps you assess the strength of the "trend" and "momentum" regardless of the direction of returns.
Simple Volatility Momentum
This indicator can be used for mean reversion strategies and "momentum" or trend based strategies.
The indicator calculates the average return as the momentum metric and then gets the moving average of the average return and standard deviations from average return average. On the options you can determine if you want to use 1 or 2 standard deviation bands or have both of them enabled.
Settings:
Source: By default it's at close.
M Length: This is the length of the "momentum".
Rank Length: This is the length of the rank calculation of absolute value of the average return
MA Type: This is the different type of calculations for the mean and standard deviation. By default its at incremental.
Smoothing factor: (Only used if you choose the exponential MA type.)
The absolute value of the average return helps you see the strength of the "momentum" and trend. If there is a low ranking of the absolute value of the average return then you can eventually expect it to increase which means that the average return is trending, leading to trending price moves. If the Mean ABS rank value is at or near the maximum value 100 and the average return is at -2 standard deviation from the mean, you can see it as the negative momentum or trend being "finished". Similarly, if the Mean ABS value is near or at the maximum value 100 and the average return is at +2 standard deviation from the mean, you can view the uptrend, as "finished" and the Mean ABS rank can't really go higher than 100.
Moving Average Calculations type:
Incremental: Incremental moving averages use an incremental approach to update the moving average by adding the newest data point and subtracting the oldest one.
Exponential: The exponential moving average gives more weight to recent data points while still considering older ones. This is achieved by applying a smooth factor to the previous EMA value and the current data point. EMA's react more quickly to recent changes in the data compared to simple moving averages, making them useful for short term trends and momentum in financial markets.
Rolling: The moving average is calculated by taking the average of a fixed number of data points within a defined window. As new data becomes available, the window moves forward and the average is recalculated. Rolling Moving Averages are useful for smoothing out short-fluctuations and identifying trends over time.
Important thing to note about indicators involving bands and "momentum" or "trend" or prices:
For the explanation we will assume that stock returns follow a normal distribution and price follows a log normal distribution. Please note that in the live market this assumption isn't always true. Many people incorrectly use standard deviations on prices and trade them as mean reversion strategies or overbought or oversold levels which is not what standard deviations are meant for. Assuming you have applied the log transformation on the standard deviation bands (if your input is raw price then you should use a log transformation to remove the skewness of price), and you have a range of 2 standard deviations from the mean, under the empirical rule with enough occurrences 95% of the values will be within the 2 standard deviation range. This doesn't mean that if price falls to the bottom of the 2 standard deviation bound, there is a 95% chance it will revert back to mean, this is incorrect and not how standard deviations or mean reversion works.
"MOMENTUM"
In finance "momentum" refers to the rate of change of a time series data point. It shows the persistence or tendency for a data series to continue moving in its current direction. In finance, "momentum" based strategies capitalize on the observed tendency of assets that have performed well (or poorly) in the recent past to continue performing well (or poorly) in the near future. This persistence is often observed in various financial instruments including stocks, currencies and commodities.
"Momentum" is commonly calculated with the average return, and relies on the assumption that assets with positive "momentum" or a positive average return will likely continue to perform well in the short to medium term, while assets with a negative average return are expected to continue underperforming. This average return or expected value is derived from historical observations and statistical analysis of previous price movements. However, real markets are subject to levels of efficiencies, market fluctuations, randomness, and may not always produce consistent returns over time involving momentum based strategies.
Mean Reversion:
In finance, the average return is an important parameter in mean reversion strategies. Using statistical methodologies, mean reversion strategies aim to exploit the deviations from the historical average return by identifying instances where current prices and their changes diverge from their expected levels based on past performance. This approach involves statistical analysis and predictive modelling techniques to check where and when the average rate of change is likely to revert towards the mean. It's important to know that mean reversion is a temporary state and will not always be present in a specific timeseries.
Using the average return over price offers several advantages in finance and trading since it is less sensitive to extreme price movements or outliers compared to raw price data. Price itself contains a distribution that is usually positively-skewed and has no upper bound. Mean reversion typically occurs in distributions where extreme values are followed by a tendency for the variable to return towards its mean over time, however the probability distribution of price has no tendency for values to revert towards any specific level. Instead, values may continue to increase without a bound. Returns themself contain more stationary behavior than price levels. Mean reversion strategies rely on the assumption that deviations from the mean will eventually revert back to the mean. Returns, being more likely to exhibit stationary, are better suited for mean reversion based strategies.
The distribution of returns are often more symmetrically distributed around their mean compared to price distributions. This symmetry makes it easier to identify deviations from the mean and assess the likelihood of mean reversion occurrence. Returns are also less sensitive to trends and long-term price movements compared to price levels. Mean reversion strategies aim to exploit deviations from mean, which can be obscured when analyzing raw price data since raw price is almost always trending. Returns can filter out the trend component of price movements, making it easier to identify opportunities.
Stationary Process: Implication that properties like mean and variance remain relatively constant over time.
Machine Learning Momentum Index (MLMI) [Zeiierman]█ Overview
The Machine Learning Momentum Index (MLMI) represents the next step in oscillator trading. By blending traditional momentum analysis with machine learning, MLMI delivers a potent and dynamic tool that aligns with the complexities of modern financial landscapes. Offering traders an adaptive way to understand and act on market momentum and trends, this oscillator provides real-time insights into market momentum and prevailing trends.
█ How It Works:
Momentum Analysis: MLMI employs a dual-layer analysis, utilizing quick and slow weighted moving averages (WMA) of the Relative Strength Index (RSI) to gauge the market's momentum and direction.
Machine Learning Integration: Through the k-Nearest Neighbors (k-NN) algorithm, MLMI intelligently examines historical data to make more accurate momentum predictions, adapting to the intricate patterns of the market.
MLMI's precise calculation involves:
Weighted Moving Averages: Calculations of quick (5-period) and slow (20-period) WMAs of the RSI to track short-term and long-term momentum.
k-Nearest Neighbors Algorithm: Distances between current parameters and previous data are measured, and the nearest neighbors are used for predictive modeling.
Trend Analysis: Recognition of prevailing trends through the relationship between quick and slow-moving averages.
█ How to use
The Machine Learning Momentum Index (MLMI) can be utilized in much the same way as traditional trend and momentum oscillators, providing key insights into market direction and strength. What sets MLMI apart is its integration of artificial intelligence, allowing it to adapt dynamically to market changes and offer a more nuanced and responsive analysis.
Identifying Trend Direction and Strength: The MLMI serves as a tool to recognize market trends, signaling whether the momentum is upward or downward. It also provides insights into the intensity of the momentum, helping traders understand both the direction and strength of prevailing market trends.
Identifying Consolidation Areas: When the MLMI Prediction line and the WMA of the MLMI Prediction line become flat/oscillate around the mid-level, it's a strong sign that the market is in a consolidation phase. This insight from the MLMI allows traders to recognize periods of market indecision.
Recognizing Overbought or Oversold Conditions: By identifying levels where the market may be overbought or oversold, MLMI offers insights into potential price corrections or reversals.
█ Settings
Prediction Data (k)
This parameter controls the number of neighbors to consider while making a prediction using the k-Nearest Neighbors (k-NN) algorithm. By modifying the value of k, you can change how sensitive the prediction is to local fluctuations in the data.
A smaller value of k will make the prediction more sensitive to local variations and can lead to a more erratic prediction line.
A larger value of k will consider more neighbors, thus making the prediction more stable but potentially less responsive to sudden changes.
Trend length
This parameter controls the length of the trend used in computing the momentum. This length refers to the number of periods over which the momentum is calculated, affecting how quickly the indicator reacts to changes in the underlying price movements.
A shorter trend length (smaller momentumWindow) will make the indicator more responsive to short-term price changes, potentially generating more signals but at the risk of more false alarms.
A longer trend length (larger momentumWindow) will make the indicator smoother and less responsive to short-term noise, but it may lag in reacting to significant price changes.
Please note that the Machine Learning Momentum Index (MLMI) might not be effective on higher timeframes, such as daily or above. This limitation arises because there may not be enough data at these timeframes to provide accurate momentum and trend analysis. To overcome this challenge and make the most of what MLMI has to offer, it's recommended to use the indicator on lower timeframes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
TEWY - Magic Momentum IndicatorMy goal is to equip every trader and investor with the essential tools necessary to confidently navigate the complexities of the financial markets, enabling them to consistently identify opportunities and maintain a position of strength on the winning side of their trades. This indicator stands as a potent tool, offering the capability to effectively assess longer-term momentum trends.
Allow me to provide some context regarding the genesis of this indicator. By keenly observing the pattern of momentum loss preceding each trend reversal, coupled with the notable decrease in the rate of price change, I've formulated this indicator. This design is rooted in the understanding that these dynamics hold key insights into the market's shifting trends.
So, I've developed this indicator with the purpose of granting you the ability to select and construct optional combinations of up to two comparable symbols. Through this, you gain a comprehensive and insightful perspective on the ever-evolving dynamics of the market.
This indicator acts like an oscillator and momentum line serves as a key determinant. When the line is positioned above 0, it signifies a positive momentum; conversely, if it rests below 0, it indicates a sideways to negative trend. This mechanism offers a clear and intuitive means of gauging prevailing market conditions.
Should you have any inquiries or require further clarification regarding this indicator, please do not hesitate to reach out to me via direct message. I am here to provide you with the necessary guidance and support to ensure your experience with this tool is both seamless and enriching. Your understanding and satisfaction remain my utmost priority.
By TEWY - Trade Easy With Yogesh
I am Yogesh
Ultimate Momentum OscillatorThe Ultimate Momentum Oscillator is a tool designed to help traders identify the current trend direction and the momentum of the prices.
This oscillator is composed of one histogram and one line, paired with the two overbought and the two oversold levels.
The histogram is a trend-based algorithm that allows the user to read the market bias with multiple trend lengths combined.
The line is a momentum-based formula that allows traders to identify potential reversal and the speed of the price.
This tool can be used to:
- Identify the current trend direction
- Identify the momentum of the price
- Identify oversold and overbought levels
Stochastic Momentum Channel with Volume Filter [IkkeOmar]A stochastic version of my momentum channel volume filter
The "Stochastic Momentum" indicator combines the concepts of Stochastic and Bollinger Bands to provide insights into price momentum and potential trend reversals. It can be used to identify overbought and oversold conditions, as well as potential bullish and bearish signals.
The indicator calculates a Stochastic RSI using the RSI (Relative Strength Index) of a given price source. It applies smoothing to the Stochastic RSI values using moving averages to generate two lines: the %K line and the %D line. The %K line represents the current momentum, while the %D line represents a filtered version of the momentum.
Additionally, the indicator plots Bollinger Bands around the moving average of the Stochastic RSI. The upper and lower bands represent levels where the price is considered relatively high or low compared to its recent volatility. The distance between the bands reflects the current market volatility.
Here's how the indicator can be interpreted:
Stochastic Momentum (%K and %D lines):
When the %K line crosses above the %D line, it suggests a potential upward move or bullish momentum.
When the %K line crosses below the %D line, it indicates a potential downward move or bearish momentum.
The color of the plot changes based on the relationship between the %K and %D lines. Green indicates %K > %D, while red indicates %K < %D.
Bollinger Bands (Upper and Lower Bands):
When the price crosses above the upper band, it suggests an overbought condition, indicating a potential reversal or pullback.
When the price crosses below the lower band, it suggests an oversold condition, indicating a potential reversal or bounce.
To identify potential upward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses above the lower band, it may signal a potential upward move or bounce.
If the %K line crosses above the %D line while the %K line is below the upper band, it may indicate a potential upward move.
To identify potential downward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses below the upper band, it may signal a potential downward move or pullback.
If the %K line crosses below the %D line while the %K line is above the lower band, it may indicate a potential downward move.
Code explanation
Input Variables:
The input function is used to create customizable input variables that can be adjusted by the user.
smoothK and smoothD are inputs for the smoothing periods of the %K and %D lines, respectively.
lengthRSI represents the length of the RSI calculation.
lengthStoch is the length parameter for the stochastic calculation.
volumeFilterLength determines the length of the volume filter used to filter the RSI.
Source Definition:
The src variable is an input that defines the price source used for the calculations.
By default, the close price is used, but the user can choose a different price source.
RSI Calculation:
The rsi1 variable calculates the RSI using the ta.rsi function.
The RSI is a popular oscillator that measures the strength and speed of price movements.
It is calculated based on the average gain and average loss over a specified period.
In this case, the RSI is calculated using the src price source and the lengthRSI parameter.
Volume Filter:
The code calculates a volume filter to filter the RSI values based on the average volume.
The volumeAvg variable calculates the simple moving average of the volume over a specified period (volumeFilterLength).
The filteredRsi variable stores the RSI values that meet the condition of having a volume greater than or equal to the average volume (volume >= volumeAvg).
Stochastic Calculation:
The k variable calculates the %K line of the Stochastic RSI using the ta.stoch function.
The ta.stoch function takes the filtered RSI values (filteredRsi) as inputs and calculates the %K line based on the length parameter (lengthStoch).
The smoothK parameter is used to smooth the %K line by applying a moving average.
The d variable represents the %D line, which is a smoothed version of the %K line obtained by applying another moving average with a period defined by smoothD.
Momentum Calculation:
The kd variable calculates the average of the %K and %D lines, representing the momentum of the Stochastic RSI.
Bollinger Bands Calculation:
The ma variable calculates the moving average of the momentum values (kd) using the ta.sma function with a period defined by bandLength.
The offs variable calculates the offset by multiplying the standard deviation of the momentum values with a factor of 1.6185.
The up and dn variables represent the upper and lower bands, respectively, by adding and subtracting the offset from the moving average.
The Bollinger Bands provide a measure of volatility and can indicate potential overbought and oversold conditions.
Color Assignments:
The colors for the plot and Bollinger Bands are assigned based on certain conditions.
If the %K line is greater than the %D line, the plotCol variable is set to green. Otherwise, it is set to red.
The upCol and dnCol variables are set to different colors based on whether the fast moving average (fastMA) is above or below the upper and lower bands, respectively.
Plotting:
The Stochastic Momentum (%K) is plotted using the plot function with the assigned color (plotCol).
The upper and lower Bollinger Bands are plotted using the plot function with the respective colors (upCol and dnCol).
The fast moving average (fastMA) is plotted in black color to distinguish it from the bands.
The hline function is used to plot horizontal lines representing the upper and lower bands of the Stochastic Momentum.
The code combines the Stochastic RSI, Bollinger Bands, and color logic to provide visual representations of momentum and potential trend reversals. It allows traders to observe the interaction between the Stochastic Momentum lines, the Bollinger Bands, and price movements, enabling them to make informed trading decisions.
Price & Momentum Reversal Indicator [TradeDots]Price & Momentum Divergence Indicator is a variant of the Chande Momentum Oscillator (CMO), designed to identify reversal patterns in overvalued and undervalued markets. This indicator aims to mitigate the common problem of all oscillating indicators: false buy/sell signals during prolonged market trends, by incorporating a volume-weighted approach and momentum analysis.
📝 HOW IT WORKS
Price Extremeness Calculation
The indicator evaluates the extremeness of the current price by analyzing price changes over a fixed window of candlesticks.
It separates the price changes into positive and negative changes, then multiplies them by the bar volume to obtain volume-weighted values, giving higher significance to bars with larger volumes.
Extremeness Ratio
The ratio is calculated by taking the difference between the total positive changes and total negative changes, and then dividing this result by the sum of the total positive and negative changes.
The result is then smoothed to reduce market noise and rescaled to a range between -100 to 100, where 100 indicates all price changes within the window are positive.
Momentum Analysis
Momentum is calculated by measuring the rate of change of the smoothed extremeness ratio, indicating whether market extremeness is slowing and showing signs of reversion.
Reversal Signal Confirmation
For an asset to be considered a reversal, it has to be in the overvalued or undervalued zone (exceeding the overvalued & undervalued threshold). It must then show a slowed momentum change and a price reversion.
Lastly, candlestick analysis is used to confirm the reversal signal, ensuring there is no room for further breakout price movement.
🛠️ HOW TO USE
Candlestick Visualization
Candlestick bodies are painted with gradient colors representing the smoothed price extremeness (OBOS Index), ranging from -100 (solid red) to 100 (solid green). The exact value is displayed in a table at the bottom right corner.
Slowing price momentum is indicated with blue (bearish) and purple (bullish) colors, showing market pressure from the opposite side.
Reversal Confirmation
A decrease in price momentum combined with a price reversal triggers a signal label on the candlestick, indicating a potential pullback or reversal. This can serve as a reference for better entry and exit points.
⭐️ Premium Features
Higher Timeframe (HTF) Analysis
The indicator includes a feature to apply the same algorithm to a selected higher timeframe, ensuring trend alignment across multiple timeframes.
Alert Functions
Real-time notifications for overvalued and undervalued conditions, allowing traders to monitor trades and reversal signals anywhere and anytime.
❗️LIMITATIONS
Accuracy decreases in volatile and noisy markets.
Extended bullish or bearish market conditions may affect performance.
See Author's instructions below to get instant access to this indicator.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Alpha Momentum Trade - AMT (QUAD Financial)The "Alpha Momentum Trend" indicator was conceived by Tiago Friedrich and programmed by Conrado Villaça.
The indicator description applies to the daily chart. When used on other timeframes, the indicator also changes its signals based on the timeframe used.
It has five fields, from top to bottom:
1. "ATR Multiple MA" greater than multiple: shows how many candles the asset stayed 7 times the ATR (average true range) above the 50-period simple moving average (SMA) in the last 126 candles. The purpose is to identify the strength of the asset because the more times it stayed at this distance from the SMA 50, the greater the acceleration of its prices tends to be, indicating a high momentum asset. You can change the period of the SMA in the indicator settings.
2. ATR% Multiple from MA: shows the multiple of ATR that the asset is from the same SMA as in the upper field. The default is the SMA 50, and the indicator helps identify interesting regions to take profits from long positions. When the asset is more than 7 ATRs above the SMA 50, the asset is considered "stretched," and a correction or price consolidation becomes likely. For high beta assets with a very strong trend, you can use a multiple of 10 ATRs for this purpose.
3. ATR% Multiple from 52w Low: shows the multiple of ATR that the asset is in relation to the 52-week low price. The higher the number, the more the asset has risen relative to its volatility standards, indicating a stronger trend. For momentum traders, it's ideal for the asset to be at least 15 ATRs above the minimum for this period to ensure that it's in a strong uptrend and far from the lows.
4. Longest streak above SMA: within the last 126 candles, it shows the longest streak of days when the asset didn't close below a specific simple moving average. The default definition is with the 10-day SMA, but you can change it in the indicator settings. The more consecutive days the asset can stay above the SMA10, the sign that its trend is consistent and not very volatile, which is desirable. Ideally, an asset should have previously formed an uptrend by staying at least 20 consecutive days above the SMA10.
5. Longest streak above EMA: within the last 126 candles, it shows the longest streak of days when the asset didn't close below a specific exponential moving average. The default definition is with the 21-day EMA, but you can change it in the indicator settings. The more consecutive days the asset can stay above the EMA21, the sign that its trend is consistent and not very volatile, which is desirable. Ideally, an asset should have previously formed an uptrend by staying at least 35 consecutive days above the EMA21.
It's also possible to visualize on the chart the moving averages used for the calculation of the "ATR Multiple MA," "Longest streak above SMA," and "Longest streak above EMA". In the default configuration, this results in a simple 50-day moving average, a simple 10-day moving average, and an exponential 21-day moving average being displayed on the chart, respectively.
GKD-C Smoother Momentum MACD w/ dual DSL [Loxx]Giga Kaleidoscope GKD-C Smoother Momentum MACD w/ dual DSL is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Smoother Momentum MACD w/ dual DSL
What is Smoother Momentum?
Smoother Momentum is a technical indicator used to evaluate the momentum of financial assets over a specific period. It is a popular tool among traders and analysts as it helps filter out noise from the price data and provides a clearer understanding of the underlying trend. The code snippet provided is a function, smmom(), that calculates the Smoother Momentum using a combination of Exponential Moving Averages (EMAs). In the following, we will delve into the concept of Smoother Momentum, its formulation, and the rationale behind the calculations.
Smoother Momentum Formula:
The Smoother Momentum calculation involves three EMAs with different smoothing factors. The function smmom() takes two input parameters: src, which represents the source data (such as price), and per, which represents the period for smoothing.
smmom(float src, float per)=>
float alphareg = 2.0 / (1.0 + per)
float alphadbl = 2.0 / (1.0 + math.sqrt(per))
float ema = src
float ema21 = src
float ema22 = src
if bar_index > 0
ema := nz(ema ) + alphareg * (src - nz(ema ))
ema21 := nz(ema21 ) + alphadbl * (src - nz(ema21 ))
ema22 := nz(ema22 ) + alphadbl * (ema21 - nz(ema22 ))
float out = (ema22 - ema)
out
The smoothing factors for the three EMAs are as follows:
alphareg = 2.0 / (1.0 + per)
alphadbl = 2.0 / (1.0 + sqrt(per))
These factors determine the degree of smoothing applied to the input data. The alphareg factor provides regular smoothing, while the alphadbl factor introduces a double smoothing effect.
The three EMAs are calculated as follows:
ema = src
ema21 = src
ema22 = src
For each bar index greater than zero, the EMAs are updated using the following formulas:
ema := nz(ema ) + alphareg * (src - nz(ema ))
ema21 := nz(ema21 ) + alphadbl * (src - nz(ema21 ))
ema22 := nz(ema22 ) + alphadbl * (ema21 - nz(ema22 ))
The Smoother Momentum (out) is then calculated as the difference between ema22 and ema:
out = (ema22 - ema)
Rationale Behind Smoother Momentum:
The Smoother Momentum indicator is designed to provide a refined view of an asset's momentum by employing multiple levels of smoothing. By incorporating the regular EMA (ema) and the double smoothed EMAs (ema21 and ema22), the indicator minimizes the impact of price fluctuations, resulting in a smoother momentum line.
The use of different smoothing factors allows the indicator to capture both short-term and long-term price movements, making it a valuable tool for various trading strategies. The Smoother Momentum provides traders with a better understanding of the underlying trend and helps them identify potential entry and exit points.
Smoother Momentum is a powerful technical indicator that offers valuable insights into an asset's momentum by leveraging a combination of Exponential Moving Averages with different smoothing factors. The smmom() function is an efficient implementation of the Smoother Momentum indicator, providing traders and analysts with a clear and concise view of the asset's underlying trend. By incorporating this indicator into their trading strategies, market participants can make more informed decisions and improve their overall performance.
What is the Moving Average Convergence Divergence (MACD)?
The Moving Average Convergence Divergence (MACD) is a widely-used technical indicator that measures the relationship between two Exponential Moving Averages (EMAs) of an asset's price. Developed by Gerald Appel in the 1970s, the MACD is employed by traders and analysts to identify trend reversals, bullish or bearish momentum, and potential entry or exit points in the market. This following will provide an in-depth understanding of the MACD, its formulation, and the rationale behind its calculations.
MACD Formula:
The MACD is derived from two Exponential Moving Averages of different periods, usually 12 and 26. The MACD line is calculated as the difference between the short-term (12-period) EMA and the long-term (26-period) EMA. Alongside the MACD line, a signal line, typically a 9-period EMA of the MACD line, is calculated. The interaction between the MACD line and the signal line forms the basis for generating trading signals.
Here are the formulas for calculating the MACD components:
1. Short-term EMA (12-period): EMA_short = EMA(price, 12)
2. Long-term EMA (26-period): EMA_long = EMA(price, 26)
3. MACD Line: MACD = EMA_short - EMA_long
4. Signal Line (9-period EMA of MACD): Signal = EMA(MACD, 9)
5. Additionally, the MACD Histogram represents the difference between the MACD line and the signal line, visualizing the degree of separation between the two lines.
MACD Histogram: Histogram = MACD - Signal
Rationale Behind MACD:
The MACD indicator is based on the principle that moving averages can provide insights into an asset's trend and momentum. By calculating the difference between two EMAs of different periods, the MACD line oscillates around the zero line, capturing the underlying trend and momentum of the asset. When the short-term EMA is above the long-term EMA, the MACD line is positive, indicating bullish momentum. Conversely, when the short-term EMA is below the long-term EMA, the MACD line is negative, signifying bearish momentum.
The signal line, a 9-period EMA of the MACD line, serves as a smoothing factor and a trigger for trading signals. When the MACD line crosses above the signal line, it generates a bullish signal, suggesting a potential buying opportunity. On the other hand, when the MACD line crosses below the signal line, it produces a bearish signal, indicating a possible selling opportunity.
The MACD Histogram visualizes the divergence between the MACD line and the signal line, helping traders assess the strength of the trend and the momentum. A widening histogram signifies an increasing divergence between the two lines, indicating stronger momentum, while a narrowing histogram denotes decreasing divergence, suggesting weakening momentum.
The Moving Average Convergence Divergence (MACD) is a powerful and versatile technical indicator that offers valuable insights into an asset's trend and momentum. By examining the interactions between the MACD line, the signal line, and the MACD Histogram, traders can identify potential trend reversals, bullish or bearish momentum, and entry or exit points in the market. The MACD's effectiveness in various market conditions and its compatibility with different trading strategies make it an indispensable tool for market participants seeking to make well-informed decisions and enhance their overall performance.
What is a Discontinued Signal Line (DSL)?
Many indicators employ signal lines to more easily identify trends or desired states of the indicator. The concept of a signal line is straightforward: by comparing a value to its smoothed, slightly lagging state, one can determine the current momentum or state.
The Discontinued Signal Line builds on this fundamental idea by extending it: rather than having a single signal line, multiple lines are used based on the indicator's current value.
The "signal" line is calculated as follows:
When a specific level is crossed in the desired direction, the EMA of that value is calculated for the intended signal line.
When that level is crossed in the opposite direction, the previous "signal" line value is "inherited," becoming a sort of level.
This approach combines signal lines and levels, aiming to integrate the advantages of both methods.
In essence, DSL enhances the signal line concept by inheriting the previous signal line's value and converting it into a level.
You can select between anchored and unanchored DSL, as well as utilize zero-line crosses without DSL.
What is the Smoother Momentum MACD w/ dual DSL?
This indicator uses the Smoother Momentum algorithm to calculate a MACD. Signals are created by middle crosses, signal crosses, or DSL crosses.
█ 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
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, the Average Directional Index (ADX), and the Chandelier Exit.
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.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 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)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
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: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Smoother Momentum MACD w/ dual DSL as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
