MACD + SMA 200 Strategy (by ChartArt)Here is a combination of the classic MACD (moving average convergence divergence indicator) with the classic slow moving average SMA with period 200 together as a strategy.
This strategy goes long if the MACD histogram and the MACD momentum are both above zero and the fast MACD moving average is above the slow MACD moving average. As additional long filter the recent price has to be above the SMA 200. If the inverse logic is true, the strategy goes short. For the worst case there is a max intraday equity loss of 50% filter.
Save another $999 bucks with my free strategy.
This strategy works in the backtest on the daily chart of Bitcoin, as well as on the S&P 500 and the Dow Jones Industrial Average daily charts. Current performance as of November 30, 2015 on the SPX500 CFD daily is percent profitable: 68% since the year 1970 with a profit factor of 6.4. Current performance as of November 30, 2015 on the DOWI index daily is percent profitable: 51% since the year 1915 with a profit factor of 10.8.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
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Stock Market Trend Analysis Trading System 101 (by ChartArt)This is a very simple trading system which is measuring the core of uptrends and downtrends using three basic elements: Close price, HL2 price, Pivot price.
Depending if the uptrend or downtrend is strong, the buy/sell signals are shown in different colors. The stronger trends are in brighter colors (lime and fuchsia). If the trend just fully changed direction from uptrend to downtrend (or vice versa), there is a background color highlight in the color of the new trend direction.
The trend detection should work best on monthly charts. I have created this in under an hour. My goal was to use the least amount of rules possible, therefore there are many false signals and the code is quite lazy.
You can lose all your money if you rely on these buy/sell signals!
MACD Color Trawler (by ChartArt)This version of the MACD indicator is 'trawling' (checking) if the MACD histogram and the zero line crossing with the MACD line are both positive or negative. The idea behind this is to show areas with higher or lower risk.
Features:
1. Enable the bar color
2. Enable the background color
3. Change zero line value
FYI:
"The MACD-Histogram is an indicator of an indicator. In fact, MACD is also an indicator of an indicator. This means that the MACD-Histogram is the fourth derivative of price."
First derivative: 12-day EMA and 26-day EMA
Second derivative: MACD (12-day EMA less the 26-day EMA)
Third derivative: MACD signal line (9-day EMA of MACD)
Fourth derivative: MACD-Histogram (MACD less MACD signal line)
Source: stockcharts.com
High-Low Cloud Trend [ChartPrime]The High-Low Cloud Trend - ChartPrime indicator, combines the concepts of trend following and mean reversion into a dynamic cloud representation. This indicator constructs high and low bands based on lookback periods, which adjust dynamically to reflect market conditions. By highlighting the upper and lower extremes, it provides a visual gauge for potential reversals and continuation points.
◆ KEY FEATURES
Dynamic Cloud Bands : Uses high and low derived from user-defined lookback periods to create reactive bands that illustrate trend strength and potential reversal zones.
Color-coded Visualization : Applies distinct colors to the bands based on the trend direction, improving readability and decision-making speed.
Mean Reversion Detection : Identifies points where price extremes may revert to a mean, signaling potential entry or exit opportunities based on deviation from expected values.
Flexible Visualization : Offers options to display volume or price-based metrics within labels, enhancing analytical depth.
◆ FUNCTIONALITY DETAILS
Band Formation : Calculates two sets of bands; one based on a primary lookback period and another for a shorter period to capture mean reversion points.
◆ USAGE
Trend Confirmation : Use the main bands to confirm the prevailing market trend, with the cloud filling acting as a visual guide.
Breakout Identification : Monitor for price breaks through the cloud to identify strong momentum that may suggest a viable breakout.
Risk Management : Adjust positions based on the proximity of price to either band, using these as potential support or resistance areas.
Mean Reversion Strategies : Apply mean reversion techniques when price touches or crosses the bands, indicating a possible return to a central value.
⯁ USER INPUTS
Lookback Period : Sets the primary period for calculating high and low bands.
Mean Reversion Points : Toggles the identification of mean reversion opportunities within the bands.
Volume/Price Display : Chooses between displaying volume or price information in the indicator's labels for enhanced detail.
The High-Low Cloud Trend indicator is a versatile and powerful tool for traders who engage in both trend following and mean reversion strategies. It provides a clear visual representation of market dynamics, helping traders to make informed decisions based on established and emerging patterns. This indicator's dual approach ensures that it is suitable for various trading styles and market conditions.
Multiple Non-Linear Regression [ChartPrime]This indicator is designed to perform multiple non-linear regression analysis using four independent variables: close, open, high, and low prices. Here's a breakdown of its components and functionalities:
Inputs:
Users can adjust several parameters:
Normalization Data Length: Length of data used for normalization.
Learning Rate: Rate at which the algorithm learns from errors.
Smooth?: Option to smooth the output.
Smooth Length: Length of smoothing if enabled.
Define start coefficients: Initial coefficients for the regression equation.
Data Normalization:
The script normalizes input data to a range between 0 and 1 using the highest and lowest values within a specified length.
Non-linear Regression:
It calculates the regression equation using the input coefficients and normalized data. The equation used is a weighted sum of the independent variables, with coefficients adjusted iteratively using gradient descent to minimize errors.
Error Calculation:
The script computes the error between the actual and predicted values.
Gradient Descent: The coefficients are updated iteratively using gradient descent to minimize the error.
// Compute the predicted values using the non-linear regression function
predictedValues = nonLinearRegression(x_1, x_2, x_3, x_4, b1, b2, b3, b4)
// Compute the error
error = errorModule(initial_val, predictedValues)
// Update the coefficients using gradient descent
b1 := b1 - (learningRate * (error * x_1))
b2 := b2 - (learningRate * (error * x_2))
b3 := b3 - (learningRate * (error * x_3))
b4 := b4 - (learningRate * (error * x_4))
Visualization:
Plotting of normalized input data (close, open, high, low).
The indicator provides visualization of normalized data values (close, open, high, low) in the form of circular markers on the chart, allowing users to easily observe the relative positions of these values in relation to each other and the regression line.
Plotting of the regression line.
Color gradient on the regression line based on its value and bar colors.
Display of normalized input data and predicted value in a table.
Signals for crossovers with a midline (0.5).
Interpretation:
Users can interpret the regression line and its crossovers with the midline (0.5) as signals for potential buy or sell opportunities.
This indicator helps users analyze the relationship between multiple variables and make trading decisions based on the regression analysis. Adjusting the coefficients and parameters can fine-tune the model's performance according to specific market conditions.
Multi Asset Histogram [ChartPrime]Multi Asset Histogram Indicator
Overview:
The "Multi Asset Histogram" indicator provides a comprehensive visualization of the performance of multiple assets relative to each other. By calculating a score for each asset and displaying it in a histogram format, this indicator helps traders quickly identify the trends, dominant asset and the average performance of the assets in the selected group.
Key Features:
◆ Multi-Asset Score Calculation:
The indicator calculates a trend score for each selected asset based on the price source (e.g., hl2).
The trend score is determined by comparing the current price to the prices over the past bars back defined by user, adding or subtracting points based on whether the current price is higher or lower than previous prices.
// Score Function
trscore(src) =>
total = 0.0
for i = 1 to 50
total += (src >= nz(src ) ? 1 : -1)
total
◆ Flexible Symbol Input:
Traders can input up to 10 different symbols (e.g., BTCUSD, ETHUSD, etc.) to be included in the histogram analysis.
◆ Dynamic Visualization:
A histogram is plotted for each asset, with bars colored based on the score, providing a clear visual representation of the relative performance.
Color gradients from red to aqua indicate the performance, with red representing negative scores and aqua representing positive scores.
◆ Adaptive Histogram Lines:
The width and placement of histogram lines adapt based on the calculated scores, ensuring clear visualization regardless of the values.
Dashed lines represent the mean score of all assets, helping traders identify the overall market trend.
◆Detailed Labels and Values:
Labels are placed on the histogram to display the exact score for each asset.
Mean value and zero line labels provide additional context for the overall performance.
◆ Visual Scaling Lines:
Zero line and mean line are clearly marked, helping traders understand the distribution and scale of scores.
Scales on the left and right of the histogram indicate the performance range.
◆ Informative Table:
A table is displayed on the chart, showing the dominant asset (the one with the highest score) and the mean score of all assets.
The table updates dynamically to reflect real-time changes in asset performance.
◆ Settings:
Length: The value of number bars back is greater or less than the current value of the source
Source: The price source to be used for score calculation (e.g., hl2).
Symbols: Up to 10 different asset symbols can be input for analysis.
Usage Notes:
This indicator is useful for traders who monitor multiple assets simultaneously and need a quick visual reference to identify the strongest and weakest performers.
The color coding and dynamic labels make it easy to interpret the relative performance and make informed trading decisions.
This indicator is designed to enhance multi-asset analysis by providing a clear, visual representation of each asset's performance relative to the others, making it easier to identify trends and dominant assets in the market.
Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator
Overview:
The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making.
Key Features:
◆ Customizable Look-Back Period:
Input: Length
Default: 20
Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier.
◆ Overbought and Oversold Thresholds:
Inputs: Upper Threshold and Lower Threshold
Default: 1.5 and -1.5 respectively
Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals.
◆ Candlestick Color Plotting:
Input: Plot Bar Color
Default: false
Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative.
◆ Mean Reversion and Trend Signals:
Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points.
◆ Invalidation Levels:
Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated.
◆ Gradient Color Coding:
Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions.
◆ Usage Notes:
Setting the Look-Back Period:
Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading.
Interpreting Thresholds:
Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability.
Candlestick Coloring:
Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets.
Mean Reversion and Trend Signals:
Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points.
Invalidation Levels:
Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid.
This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
Kalman Volume Filter [ChartPrime]The "Kalman Volume Filter" , aims to provide insights into market volume dynamics by filtering out noise and identifying potential overbought or oversold conditions. Let's break down its components and functionality:
Settings:
Users can adjust various parameters to customize the indicator according to their preferences:
Volume Length: Defines the length of the volume period used in calculations.
Stabilization Coefficient (k): Determines the level of noise reduction in the signals.
Signal Line Length: Sets the length of the signal line used for identifying trends.
Overbought & Oversold Zone Level: Specifies the threshold levels for identifying overbought and oversold conditions.
Source: Allows users to select the price source for volume calculations.
Volume Zone Oscillator (VZO):
Calculates a volume-based oscillator indicating the direction and intensity of volume movements.
Utilizes a volume direction measurement over a specified period to compute the oscillator value.
Normalizes the oscillator value to improve comparability across different securities or timeframes.
// VOLUME ZONE OSCILLATOR
VZO(get_src, length) =>
Volume_Direction = get_src > get_src ? volume : -volume
VZO_volume = ta.hma(Volume_Direction, length)
Total_volume = ta.hma(volume, length)
VZO = VZO_volume / (Total_volume)
VZO := (VZO - 0) / ta.stdev(VZO, 200)
VZO
Kalman Filter:
Applies a Kalman filter to smooth out the VZO values and reduce noise.
Utilizes a stabilization coefficient (k) to control the degree of smoothing.
Generates a filtered output representing the underlying volume trend.
// KALMAN FILTER
series float M_n = 0.0 // - the resulting value of the current calculation
series float A_n = VZO // - the initial value of the current measurement
series float M_n_1 = nz(M_n ) // - the resulting value of the previous calculation
float k = input.float(0.06) // - stabilization coefficient
// Kalman Filter Formula
kalm(k)=>
k * A_n + (1 - k) * M_n_1
Volume Visualization:
Displays the volume histogram, with color intensity indicating the strength of volume movements.
Adjusts bar colors based on volume bursts to highlight significant changes in volume.
Overbought and Oversold Zones:
Marks overbought and oversold levels on the chart to assist in identifying potential reversal points.
Plotting:
Plots the Kalman Volume Filter line and a signal line for visual analysis.
Utilizes different colors and fills to distinguish between rising and falling trends.
Highlights specific events such as local buy or sell signals, as well as overbought or oversold conditions.
This indicator provides traders with a comprehensive view of volume dynamics, trend direction, and potential market turning points, aiding in informed decision-making during trading activities.
Momentum Ghost Machine [ChartPrime]Momentum Ghost Machine (ChartPrime) is designed to be the next generation in momentum/rate of change analysis. This indicator utilizes the properties of one of our favorite filters to create a more accurate and stable momentum oscillator by using a high quality filtered delayed signal to do the momentum comparison.
Traditional momentum/roc uses the raw price data to compare current price to previous price to generate a directional oscillator. This leaves the oscillator prone to false readings and noisy outputs that leave traders unsure of the real likelihood of a future movement. One way to mitigate this issue would be to use some sort of moving average. Unfortunately, this can only go so far because simple moving average algorithms result in a poor reconstruction of the actual shape of the underlying signal.
The windowed sinc low pass filter is a linear phase filter, meaning that it doesn't change the shape or size of the original signal when applied. This results in a faithful reconstruction of the original signal, but without the "high frequency noise". Just like any filter, the process of applying it requires that we have "future" samples resulting in a time delay for real time applications. Fortunately this is a great thing in the context of a momentum oscillator because we need some representation of past price data to compare the current price data to. By using an ideal low pass filter to generate this delayed signal we can super charge the momentum oscillator and fix the majority of issues its predecessors had.
This indicator has a few extra features that other momentum/roc indicators dont have. One major yet simple improvement is the inclusion of a moving average to help gauge the rate of change of this indicator. Since we included a moving average, we thought it would only be appropriate to add a histogram to help visualize the relationship between the signal and its average. To go further with this we have also included linear extrapolation to further help you predict the momentum and direction of this oscillator. Included with this extrapolation we have also added the histogram in the extrapolation to further enhance its visual interpretation. Finally, the inclusion of a candle coloring feature really drives how the utility of the Momentum Machine .
There are three distinct options when using the candle coloring feature: Direct, MA, and Both. With direct the candles will be colored based on the indicators direction and polarity. When it is above zero and moving up, it displays a green color. When it is above zero and moving down it will display a light green color. Conversely, when the indicator is below zero and moving down it displays a red color, and when it it moving up and below zero it will display a light red color. MA coloring will color the candles just like a MACD. If the signal is above its MA and moving up it will display a green color, and when it is above its MA and moving down it will display a light green color.
When the signal is below its MA and moving down it will display a red color, and when its below its ma and moving up it will display a light red color. Both combines the two into a single color scheme providing you with the best of both worlds. If the indicator is above zero it will display the MA colors with a slight twist. When the indicator is moving down and is below its MA it will display a lighter color than before, and when it is below zero and is above its MA it will display a darker color color.
Length of 50 with a smoothing of 100
Length of 50 with a smoothing of 25
By default, the indicator is set to a momentum length of 50, with a post smoothing of 2. We have chosen the longer period for the momentum length to highlight the performance of this indicator compared to its ancestors. A major point to consider with this indicator is that you can only achieve so much smoothing for a chosen delay. This is because more data is required to produce a smoother signal at a specified length. Once you have selected your desired momentum length you can then select your desired momentum smoothing . This is made possible by the use of the windowed sinc low pass algorithm because it includes a frequency cutoff argument. This means that you can have as little or as much smoothing as you please without impacting the period of the indicator. In the provided examples above this paragraph is a visual representation of what is going on under the hood of this indicator. The blue line is the filtered signal being compared to the current closing price. As you can see, the filtered signal is very smooth and accurately represents the underlying price action without noise.
We hope that users can find the same utility as we did in this indicator and that it levels up your analysis utilizing the momentum oscillator or rate of change.
Enjoy
PhiSmoother Moving Average Ribbon [ChartPrime]DSP FILTRATION PRIMER:
DSP (Digital Signal Processing) filtration plays a critical role with financial indication analysis, involving the application of digital filters to extract actionable insights from data. Its primary trading purpose is to distinguish and isolate relevant signals separate from market noise, allowing traders to enhance focus on underlying trends and patterns. By smoothing out price data, DSP filters aid with trend detection, facilitating the formulation of more effective trading techniques.
Additionally, DSP filtration can play an impactful role with detecting support and resistance levels within financial movements. By filtering out noise and emphasizing significant price movements, identifying key levels for entry and exit points become more apparent. Furthermore, DSP methods are instrumental in measuring market volatility, enabling traders to assess volatility levels with improved accuracy.
In summary, DSP filtration techniques are versatile tools for traders and analysts, enhancing decision-making processes in financial markets. By mitigating noise and highlighting relevant signals, DSP filtration improves the overall quality of trading analysis, ultimately leading to better conclusions for market participants.
APPLYING FIR FILTERS:
FIR (Finite Impulse Response) filters are indispensable tools in the realm of financial analysis, particularly for trend identification and characterization within market data. These filters effectively smooth out price fluctuations and noise, enabling traders to discern underlying trends with greater fidelity. By applying FIR filters to price data, robust trading strategies can be developed with grounded trend-following principles, enhancing their ability to capitalize on market movements.
Moreover, FIR filter applications extend into wide-ranging utility within various fields, one being vital for informed decision-making in analysis. These filters help identify critical price levels where assets may tend to stall or reverse direction, providing traders with valuable insights to aid with identification of optimal entry and exit points within their indicator arsenal. FIRs are undoubtedly a cornerstone to modern trading innovation.
Additionally, FIR filters aid in volatility measurement and analysis, allowing traders to gauge market volatility accurately and adjust their risk management approaches accordingly. By incorporating FIR filters into their analytical arsenal, traders can improve the quality of their decision-making processes and achieve better trading outcomes when contending with highly dynamic market conditions.
INTRODUCTORY DEBUT:
ChartPrime's " PhiSmoother Moving Average Ribbon " indicator aims to mark a significant advancement in technical analysis methodology by removing unwanted fluctuations and disturbances while minimizing phase disturbance and lag. This indicator introduces PhiSmoother, a powerful FIR filter in it's own right comparable to Ehlers' SuperSmoother.
PhiSmoother leverages a custom tailored FIR filter to smooth out price fluctuations by mitigating aliasing noise problematic to identification of underlying trends with accuracy. With adjustable parameters such as phase control, traders can fine-tune the indicator to suit their specific analytical needs, providing a flexible and customizable solution.
Mathemagically, PhiSmoother incorporates various color coding preferences, enabling traders to visualize trends more effectively on a volatile landscape. Whether utilizing progression, chameleon, or binary color schemes, you can more fluidly interpret market dynamics and make informed visual decisions regarding entry and exit points based on color-coded plotting.
The indicator's alert system further enhances its utility by providing notifications of specifically chosen filter crossings. Traders can customize alert modes and messages while ensuring they stay informed about potential opportunities aligned with their trading style.
Overall, the "PhiSmoother Moving Average Ribbon" visually stands out as a revolutionary mechanism for technical analysis, offering traders a comprehensive solution for trend identification, visualization, and alerting within financial markets to achieve advantageous outcomes.
NOTEWORTHY SETTINGS FEATURES:
Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options.
Phase Control Parameter - One of the notable standout features of this indicator is the phase control parameter. Traders can fine-tune the phase or lag of the indicator to adapt it to different market conditions or timeframes. This feature enables optimization of the indicator's responsiveness to price movements and align it with their specific trading tactics.
Coloring Preferences - Another magical setting is the coloring features, one being "Chameleon Color Magic". Traders can customize the color scheme of the indicator based on their visual preferences or to improve interpretation. The indicator offers options such as progression, chameleon, or binary color schemes, all having versatility to dynamically visualize market trends and patterns. Two colors may be specifically chosen to reduce overlay indicator interference while also contrasting for your visual acuity.
Alert Controls - The indicator provides diverse alert controls to manage alerts for specific market events, depending on their trading preferences.
Alertable Crossings: Receive an alert based on selectable predefined crossovers between moving average neighbors
Customizable Alert Messages: Traders can personalize alert messages with preferred information details
Alert Frequency Control: The frequency of alerts is adjustable for maximum control of timely notifications
Ranges With Targets [ChartPrime]The Ranges With Targets indicator is a tool designed to assist traders in identifying potential trading opportunities on a chart derived from breakout trading. It dynamically outlines ranges with boxes in real-time, providing a visual representation of price movements. When a breakout occurs from a range, the indicator will begin coloring the candles. A green candle signals a long breakout, suggesting a potential upward movement, while a red candle indicates a short breakout, suggesting a potential downward movement. Grey candles indicate periods with no active trade. Ranges are derived from daily changes in price action.
This indicator builds upon the common breakout theory in trading whereby when price breaks out of a range; it may indicate continuation in a trend.
Additionally, users have the ability to customize their risk-reward settings through a multiplier referred to as the Target input. This allows traders to set their Take Profit (TP) and Stop Loss (SL) levels according to their specific risk tolerance and trading strategy.
Furthermore, the indicator offers an optional stop loss setting that can automatically exit losing trades, providing an additional layer of risk management for users who choose to utilize this feature.
A dashboard is provided in the top right showing the statistics and performance of the indicator; winning trades; losing trades, gross profit and loss and PNL. This can be useful when analyzing the success of breakout trading on a particular asset or timeframe.
Risk Reward Optimiser [ChartPrime]█ CONCEPTS
In modern day strategy optimization there are few options when it comes to optimizing a risk reward ratio. Users frequently need to experiment and go through countless permutations in order to tweak, adjust and find optimal in their data.
Therefore we have created the Risk Reward Optimizer.
The Risk Reward Optimizer is a technical tool designed to provide traders with comprehensive insights into their trading strategies.
It offers a range of features and functionalities aimed at enhancing traders' decision-making process.
With a focus on comprehensive data, it is there to help traders quickly and efficiently locate Risk Reward optimums for inbuilt of custom strategies.
█ Internal and external Signals:
The script can optimize risk to reward ratio for any type of signals
You can utilize the following :
🔸Internal signals ➞ We have included a number of common indicators into the optimizer such as:
▫️ Aroon
▫️ AO (Awesome Oscillator)
▫️ RSI (Relative Strength Index)
▫️ MACD (Moving Average Convergence Divergence)
▫️ SuperTrend
▫️ Stochastic RSI
▫️ Stochastic
▫️ Moving averages
All these indicators have 3 conditions to generate signals :
Crossover
High Than
Less Than
🔸External signal
▫️ by incorporating your own indicators into the analysis. This flexibility enables you to tailor your strategy to your preferences.
◽️ How to link your signal with the optimizer:
In order to be able to analysis your signal we need to read it and to do so we would need to PLOT your signal with a defined value
plot( YOUR LONG Condition ? 100 : 0 , display = display.data_window)
█ Customizable Risk to Reward Ratios:
This tool allows you to test seven different customizable risk to reward ratios , helping you determine the most suitable risk-reward balance for your trading strategy. This data-driven approach takes the guesswork out of setting stop-loss and take-profit levels.
█ Comprehensive Data Analysis:
The tool provides a table displaying key metrics, including:
Total trades
Wins
Losses
Profit factor
Win rate
Profit and loss (PNL)
This data is essential for refining your trading strategy.
🔸 It includes a tooltip for each risk to reward ratio which gives data for the:
Most Profitable Trade USD value
Most Profitable Trade % value
Most Profitable Trade Bar Index
Most Profitable Trade Time (When it occurred)
Position and size is adjustable
█ Visual insights with histograms:
Visualize your trading performance with histograms displaying each risk to reward ratio trade space, showing total trades, wins, losses, and the ratio of profitable trades.
This visual representation helps you understand the strengths and weaknesses of your strategy.
It offers tooltips for each RR ratio with the average win and loss percentages for further analysis.
█ Dynamic Highlighting:
A drop-down menu allows you to highlight the maximum values of critical metrics such as:
Profit factor
Win rate
PNL
for quick identification of successful setups.
█ Stop Loss Flexibility:
You can adjust stop-loss levels using three different calculation methods:
ATR
Pivot
VWAP
This allows you to align risk-reward ratios with your preferred risk tolerance.
█ Chart Integration:
Visualize your trades directly on your price chart, with each trade displayed in a distinct color for easy tracking.
When your take-profit (TP) level is reached , the tool labels the corresponding risk-reward ratio for that specific TP, simplifying trade management.
█ Detailed Tooltips:
Tooltips provide deeper insights into your trading performance. They include information about the most profitable trade, such as the time it occurred, the bar index, and the percentage gain. Histogram tooltips also offer average win and loss percentages for further analysis.
█ Settings:
█ Code:
In summary, the Risk Reward Optimizer is a data-driven tool that offers traders the ability to optimize their risk-reward ratios, refine their strategies, and gain a deeper understanding of their trading performance. Whether you're a day trader, swing trader, or investor, this tool can help you make informed decisions and improve your trading outcomes.
MACD Normalized [ChartPrime]Overview of MACD Normalized Indicator
The MACD Normalized indicator, serves as an asset for traders seeking to harness the power of the moving average convergence divergence (MACD) combined with the advantages of the stochastic oscillator. This novel indicator introduces a normalized MACD, offering a potentially enhanced flexibility and adaptability to numerous market conditions and trading techniques.
This indicator stands out by normalizing the MACD to its average high and average low, also factoring in the deviation of the high-low position from the mean. This approach incorporates the high and low in the calculations, providing the benefits of stochastic without its common drawbacks, such as clipping problems. As a result, the indicator becomes exceptionally versatile and suitable for various trading strategies, including both faster and slower settings.
The MACD Normalized Indicator boasts a variety of options and settings. The features include:
Enable Ribbon: Toggle the display of the ribbon accompanying the MACD Normalized, as desired.
Fast Length: Determine the movement speed of the fast line to receive advance notice of potential market opportunities.
Slow Length: Control the movement pace of the slow line for smoother signals and a comprehensive outlook on market trends.
Average Length: Specify the length used to calculate the high and low averages, providing greater control over the indicator's granularity.
Upper Deviation: Establish the extent to which the high and low values deviate from the mean, ensuring adaptability to diverse market situations.
Inner Band (Middle Deviation): Adjust the balance between the high and low deviations to create an inner band signal, giving traders a secondary level of market analysis and decision-making support.
Enable Candle Color: Enable the coloring of candles based on the MACD Normalized value for effortless visualization of trading potential.
Use Cases for the MACD Normalized Indicator
In addition to analyzing market trends and identifying potential trading opportunities, ChartPrime's MACD Normalized Indicator offers a range of applications for traders. These use cases encompass distinct trading scenarios and strategies:
Overbought and Oversold Regions
One of the key applications of the MACD Normalized Indicator is identifying overbought and oversold regions. Overbought refers to a situation where an asset's price has risen significantly and is expected to face a downturn, while oversold indicates a price drop that may subsequently lead to a reversal.
By adjusting the indicator's parameters, such as the upper and inner deviation levels, traders can set precise boundaries to determine overbought and oversold areas. When the MACD moves into the upper region, it may signal that the asset is overbought and due for a price correction. Conversely, if the MACD enters the lower region, it possibly indicates an oversold condition with the potential for a price rebound.
Signal Line Crossovers
The MACD Normalized Indicator displays two lines: the fast line and the slow line (inner band). A common trading strategy involves observing the intersection of these two lines, known as a crossover. When the fast line crosses above the slow line, it may signify a bullish trend or a potential buying opportunity. Conversely, a crossover with the fast line moving below the slow line typically indicates a bearish trend or a selling opportunity.
Divergence and Convergence
Divergence occurs when the price movement of an asset does not align with the corresponding MACD values. If the price establishes a new high while the MACD fails to do the same, a bearish divergence emerges, suggesting a potential downtrend. Similarly, a bullish divergence takes place when the price forms a new low but the MACD does not follow suit, hinting at an upcoming uptrend.
Convergence, on the other hand, is represented by the MACD lines moving closer together. This movement signifies a potential change in the trend, providing traders with a timely opportunity to enter or exit the market.
Bar Magnified Volume Profile/Fixed Range [ChartPrime]This indicator draws a volume profile by utilizing data from the lower timeframe to get a more accurate representation of where volume occurred on a bar to bar basis. The indicator creates a price range, and then splits that price range into 100 grids by default. The indicator then drops down to the lower timeframe, approximately 16 times lower than the current timeframe being viewed on the chart, and then parses through all of the lower timeframe bars, and attributes the lower timeframe bar volume to all grids that it is touching. The volume is dispersed proportionally to the grids which it is touching by whatever percent of the candle is inside each grid. For example, if one of the lower timeframe bars is interacting with "2" of the grids in the profile, and 60% of the candle is inside of the top grid, 60% of the volume from said candle will be attributed to the grid.
To make all of this magic happen, this script utilizes a quadratic time complexity algorithm while parsing and attributing the volume to all of the grids. Due to this type of algorithm being used in the script, many of the user inputs have been limited to allow for simplicity, but also to prevent possible errors when executing loops. For the most part, all of the settings have been thoroughly tested and configured with the right amount of limitations to prevent these errors, but also still give the user a broad range of flexibility to adjust the script to their liking.
📗 SETTINGS
Lookback Period: The lookback period determines how many bars back the script will search for the "highest high" and the "lowest low" which will then be used to generate the grids in-between
Number Of Levels: This setting determines how many grids there will be within the volume profile/fixed range. This is personal preference, however it is capped at 100 to prevent time complexity issues
Profile Length: This setting allows you to stretch or thin the volume profile. A higher number will stretch it more, vise versa a smaller number will thin it further. This does not change the volume profiles results or values, only its visual appearance.
Profile Offset: This setting allows you to offset the profile to the left or right, in the event the user does not appreciate the positioning of the default location of the profile. A higher number will shift it to the right, vise versa a lower number will shift it to the left. This is personal preference and does not affect the results or values of the profile.
🧰 UTILITY
The volume profile/fixed range can be used in many ways. One of the most popular methods is to identify high volume areas on the chart to be used as trade entries or exits in the event of the price revisiting the high volume areas. Take this picture as an example. The image clearly demonstrates how the 2 highest areas of volume within this magnified volume profile also line up to great areas of support and resistance in the market.
Here are some other useful methods of using the volume profile/fixed range
Identify Key Support and Resistance Levels for Setups
Determine Logical Take Profits and Stop Losses
Calculate Initial R Multiplier
Identify Balanced vs Imbalanced Markets
Determine Strength of Trends
Bollinger + RSI, Double Strategy Long-Only (by ChartArt) v1.2This strategy uses the RSI indicator together with the Bollinger Bands to go long when the price is below the lower Bollinger Band (and to close the long trade when this value is above the upper Bollinger band).
This simple strategy only places a long, when both the RSI and the Bollinger Bands indicators are at the same time in a oversold condition.
In this new version 1.2 the strategy was simplified even more than before by going long-only, which made the strategy more successful in backtesting than the previous version (that older version also opened short trades).
This strategy does not repaint and was updated to PineScript version 3.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
P.S. For advanced users: If you want also be able to short with the same strategy approach, then please use my older version 1.1:
Action Section, Volatility Choppiness Indicator (by ChartArt)Here is a solution to find entry points to trade. This indicator highlights price sections with low choppiness, where both the ADX (Average Directional Index) indicator shows strong movement (up or down!) in the price and a customized Money Flow indicator (which uses only the change of the volume not the change of the price, hence a Volume Flow indicator), also shows volatility is present. Using higher filter values than the default setting of "30" reduces the noise, but also shows less 'action sections'. Vice versa using values lower than "30" increases the amount and duration of action sections which are shown.
The "action section" indicator does not show the direction if the price is going up or down. It shows if there is enough action worthy the time to trade (lower odds of a neutral sideways trend). Therefore in addition a Heikin-Ashi based price change indicator can optionally be plotted, which shows the actual direction of the price.
Action Section, High Volume Volatility & Low Price Choppiness Indicator
This indicator works only on charts which have volume data.
Narrow Range + Inside Day, Short Only Strategy (by ChartArt)This short only strategy determines when there is both a NR7 (narrow range 7, a trading day in which the range is narrower than any of the previous six days), plus a inside day (high of the current day is lower than the high of the previous day and the low of the current day is higher than the low of the previous day) both on the same trading day and enters a short trade when the close is lower than the open and the slope of the simple moving average is downwards, too.
The strategy closes the short trade next time the daily close is lower than the open in any of the next trading days. In addition the NR7ID can be colored (the color is red when the close is lower that day than the open, else the color is green) and the SMA can be drawn with a color based on the direction of the SMA slope. To fine-tune the strategy it is highly recommended to change the period length of the SMA, which determines if the measured SMA slope is downwards or not. In this version 1.1 I made a small change to long only version. By default only the bearish NR7ID days are colored.
Inspiration:
How to trade NR7 and Inside Day Pattern
paststat.com
Code credit:
NR7 indicator script from Tradingview user Lazybear:
pastebin.com
P.S. You can find the 'long only' version of this trading strategy here:
Golden Cross, SMA 200 Moving Average Strategy (by ChartArt)This famous moving average strategy is very easy to follow to decide when to buy (go long) and when to take profit.
The strategy goes long when the faster SMA 50 (the simple moving average of the last 50 bars) crosses above the slower SMA 200. Orders are closed when the SMA 50 crosses below the SMA 200. This simple strategy does not have any other stop loss or take profit money management logic. The strategy does not short and goes long only!
Here is an article explaining the "golden cross" strategy in more detail:
www.stockopedia.com
On the S&P 500 index (symbol "SPX") this strategy worked on the daily chart 81% since price data is available since 1982. And on the DOW Jones Industrial Average (symbol "DOWI") this strategy worked on the daily chart 55% since price data is available since 1916. The low number of trades is in both cases not statistically significant though.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
MACD trend heatmap (by ChartArt)This is an overlay indicator which uses the classic period settings and signals from the MACD (Moving Average Convergence/Divergence) indicator to overlay a heatmap using all the information the MACD generates with its three periods (12,26,9).
The first two moving averages which the MACD uses (12 and 26) can be plotted on the chart like usual EMAs.
In addition to the background color function (the heatmap) and the EMAs, there is an optional bar color alert when the uptrend or the downtrend as measured by the MACD appears to be very strong.
Stochastic + RSI, Double Strategy (by ChartArt)This strategy combines the classic RSI strategy to sell when the RSI increases over 70 (or to buy when it falls below 30), with the classic Stochastic Slow strategy to sell when the Stochastic oscillator exceeds the value of 80 (and to buy when this value is below 20).
This simple strategy only triggers when both the RSI and the Stochastic are together in a overbought or oversold condition. The one hour chart of the S&P 500 worked quite well recently with this double strategy.
By the way this strategy should not be confused with the 'Stochastic RSI', which measures the RSI only.
All trading involves high risk; past performance is not necessarily indicative of future results.
Trend Trading With Moving Averages (by ChartArt)This indicator is measuring if three different moving average calculations (EMA,WMA,SMA) with the same period length are aligned in an uptrend. If this is the case then the bar is colored in green. If only one or two of the three moving averages signals an uptrend then the bar is colored in blue. This can mean that the trend is changing.
Save another $999 bucks with this free indicator.
This is the ChartArt optimized version. Original idea: Steve Primo's Robbery Indicator (PET-D).
coded by UCSgears:
Stocks Box (by ChartArt)Get a multi-time frame (MTF) view of the price!
You can select to see either close price (default), or HL2 price, or HLC3 price, or OHLC4 price of all time-frames.And you change the smoothing method (and smoothing period) of the daily price, which is shown as a blue line, with period 10 WMA smoothing as default.
P:S. I had the drawings on the chart hidden, because they have nothing to do with the indicator, but with publishing the script they showed up again :(
