Pro Momentum CalculatorThe Pro Momentum Calculator Indicator is a tool for traders seeking to gauge market momentum and predict future price movements. It achieves this by counting consecutive candle periods above or below a chosen Simple Moving Average (SMA) and then providing a percentage-based probability for the direction of the next candle.
Here's how this principle works:
1. Counting Consecutive Periods: The indicator continuously tracks whether the closing prices of candles are either above or below the chosen SMA.
- When closing prices are above the SMA, it counts consecutive periods as "green" or indicating potential upward momentum.
- When closing prices are below the SMA, it counts consecutive periods as "red" or suggesting potential downward momentum.
2. Assessing Momentum: By monitoring these consecutive periods, the indicator assesses the strength and duration of the current market trend.
This is important information for traders looking to understand the market's behavior.
3. Predicting the Next Candle: Based on the historical data of consecutive green and red periods, the indicator calculates a percentage probability for the direction of the next candle:
- If there have been more consecutive green periods, it suggests a higher likelihood of the next candle being green (indicating a potential upward movement).
- If there have been more consecutive red periods, it suggests a higher likelihood of the next candle being red (indicating a potential downward movement).
The Pro Momentum Calculator indicator's versatility makes it suitable for a wide range of financial markets, including stocks, Forex, indices, commodities, cryptocurrencies...
Forecasting
[SS] Linear ModelerHello everyone,
This is the linear modeler indicator.
It is a statistical based indicator that provides a likely price target and range based on a linear regression time series analysis.
To represent it visually, all the indicator does is it represents a linear regression channel and actually plots out the range at various points based on the current trend (see the chart below):
The indicator will perform the same assessment, but give you a working range and timeline for targets.
As well, the indicator will back-test the range and variables to see how it is performing and how reliable the results are likely to be.
General Functions:
In the chart above you can see all the various parameters and functions.
The indicator will display the most likely target (MLT) to be expected within the next pre-determined timeframe (by candles).
So for the first target, the indicator is saying within the next 10 candles, BA's MLT is 221.46 and based on BT results the reliability of this assessment is around 46%.
The indicator will also display the anticipated range at each designated timeframe.
In the chart above, we can see that at 20 candles, the likely range that BA should be trading in is 204 and 238 with a reliability of around 62% based on previous performance.
Plot Functions:
As this is performing a linear time series projection, you can have the indicator plot the projected ranges. Simply go to the settings menu and select the desired forecast length:
This will plot out the desired range and result over the specified time period. Here is an example of BA plotted over the next 50 candles on the hourly:
You can technically use this as an SMA/EMA type indicator, just keep in mind it may be a bit slower than a traditional EMA and SMA indicator, as it is processing a lot of data and plotting out forecasted data as opposed to an SMA or EMA.
If you wish to use it as an EMA or SMA, you can unselect the "Display Chart" Function to hide the table, and you can also select the "Plot Label" function. This will display the current projection analytics directly on your plotted line so you don't need to reference the table at all:
Tips on use:
I use this on the larger and smaller timeframes. On all timeframes, I will look to targets that display 90% to 100% in the BT results.
Bear in mind, this does not mean that we will 100% of the time hit this target, these targets can fail, it just means that there is a higher confidence of hitting this target than other, less reliable targets.
I will plot these targets out if they fall within the implied range of the timeframe I am looking at and will act on them according to the price action.
This is a great indicator to use in combination with other range based indicators. If you use the implied range from options to help guide your trading, you can see which targets are likely to be hit based on the current trend that fall within that implied range.
You can also assess the strength of the trends at various points in time and have an actionable range with a reliability reading at various points in time.
That is pretty much the bulk of the indicator.
Hopefully you find it helpful and useful.
As always, leave your questions and suggestions below.
Thanks for reading and checking it out!
Guassian Distribution Forecast [prediction intervals]The Indicator
The Indicator combines volatility and frequency distributions to forecast an area of possible price expansion with an approximate confidence interval / level and level of significance (significance level).
The Script Formula
Additional comments
To alter the models forecasting precision to reflect a given confidence interval, e.g the 90% confidence level (C.L.), use the 1.64 multiplier (toggle value in "Standard normal distribution sd" setting), to use a specific C.L., e.g. the 85th percentile either search for this on google, or calculate it yourself using a Standard Normal Distribution Probability table. Additionaly volatility may be changed by toggling the lookback period setting, this can be thought of as widening the distribution tails.
The look forward parameter is currently fixed at 20, this is because it does not currently work correctly with higher integers, I will try resolve this problem and any other bugs as soon as possible
Value At RiskThe Value at Risk Channel (VaR Channel) is a trading indicator designed to assist traders in managing their risk exposure effectively. By allowing users to select a specific time period and a probability value, this indicator generates upper and lower limits that the price might potentially attain within the chosen timeframe and probability range.
CONCEPTS
This indicator employs the concept of Value at Risk (VaR) calculation, a crucial metric in risk management. VaR quantifies the potential financial loss within a position, portfolio, or company over a defined time period. Financial institutions like banks and investment firms use VaR to estimate the extent and likelihood of potential losses in their portfolios.
The "historical method" is utilized to compute VaR within the indicator. This method analyzes the historical performance of returns and constructs a histogram representing the statistical distribution of past returns. Assuming returns adhere to a normal distribution, probabilities are assigned to different return values based on their position in the distribution percentile.
HOW TO USE
Suppose you wish to plot upper and lower price limits for a 4-hour period with a 5% probability. Access the indicator's Settings tab and set the Timeframe parameter to "4 hours" while configuring the Probability parameter to 5.0.
The indicator serves as a tool to determine appropriate Stop-Loss levels triggering with low probability. Additionally, it helps gauge the likelihood of triggering such levels.
Likewise, you can assess the probability of your desired Take-Profit level being reached within a specified time frame. For instance, if you anticipate your target to be achieved within a week, set the Timeframe parameter to "1 week" and adjust the Probability parameter to align the VaR channel's limits with your Take-Profit level. The resulting Probability parameter value reflects the likelihood of your target being met within the expected time frame.
This indicator proves valuable for evaluating and managing risk, as well as refining trading strategies. If you discover other applications for this indicator, feel free to share them in the comments!
SETTINGS
Timeframe: Designates the time period within which the price might touch the VaR channel's upper or lower boundary, considering the specified Probability parameter.
Probability: Defines the likelihood of the price reaching the VaR channel's upper or lower limit during the timeframe determined by the Timeframe parameter.
Window: Establishes the historical period (number of past bars) utilized for VaR calculation.
PTS Divergence Finder SellThe PTS Divergence Finder Sell Indicator by Roger Medcalf of Precision Trading Systems.
Bearish - Sell Indications only.
First and foremost, I have been asked many times why I did not provide a sell divergence indicator while happily providing a buy signal divergence finder for many years.
I gave the answer that sell divergences are less reliable than the buy divergences, which is still true.
Some solutions to change this were found, not by giving in to peer pressure or by modification of this indicator which I made more than fifteen years ago, but by changing the default settings to be more strict.
I also noticed that Trading View calculates indicators very fast.
The nature of fear and greed are entirely different as fear is fast and instinct driven at market tops as the opposite emotions of fear and euphoria can instantly lead a human brain into the survival mode of fight or flight.
In the bottoming or oversold conditions in markets greed probogates slowly in buyers as they consider picking up value purchases at market lows with a mindset of having a low expectation of success.
This is what causes the asymmetry in market tops versus bottoms. Therefore the asymmetric settings of the buy and sell versions of this product are now explained for clarity.
I have decided to release the sell divergence indicator with "stricter" default settings.
The Demand Index length used is 55 and the difference it needs to trigger a signal is 12. These of course are user adjustable. The strictness means there are less bad signals.
The results are many tops and intermediate high points defined with pinpoint accuracy. As expected there are some disastrous signals in the midst of violent up trends which a trader can lose on if not using risk management and stops. Likewise it frequently finds the exact top.
How does the PTS Divergence Finder Sell Indicator work?
The PTS Divergence Finder Sell Indicator accurately measures the number of divergences which have occurred in Demand Index, which is a volume based indicator.
This is a histogram style indicator for subgraph two, which plots spikes which appear like stalagmites coming up from the base.
The indicator examines multiple lookback periods of the volume based Demand Index Indicator for the length that you specify. It finds high points in prices where the DI is not making a new "local" high and missing it by the "difference" setting you input.
The Demand Index is called via the library file and the intelligent code sets volume to 1 if no volume is found.
For this reason it will “work” (producing a meaningful plot) on Forex or indices without volume but performance is going to be slightly less than optimal as the valuable dimension of volume is missing.
It is therefore best to focus on instruments like stocks and futures and cryptos that have large volumes and lots of participants.
Liquid markets where many people are “voting” on the market direction give the best results.
A total of twenty look back periods are scanned on every bar and these are hard coded and non adjustable. The length of Demand Index is user adjustable but it is suggested not to wander too far below the default setting of length 55.
The second user adjustable field is “difference” and this represents the difference between Demand Index now and Demand Index “N” bars ago. (N being 20 different look back periods of various periods)
You will understand that a length 18 Demand Index produces a much more volatile plot than a 80 period plot.
For this reason you can find short lengths of “DI” and small “difference” values will produce many more signals of divergences as there is higher volatility in the underlying indicator.
You will observe this when you use it. You can set it to give hundreds of insignificant values but it is best used so you just see the significant ones by following the guidelines below.
Consider this like using a 20 period MA on a 30 second chart compared to a 20 period MA on an hourly chart.
Clearly the hourly MA change of direction is much more meaningful and important.
Suggested settings for various lengths:
Demand Index lengths less than 12 are not generally recommended for finding "good" sell divergences
DI Length 20 = difference of 20 – 35
DI Length 30 = difference of 15 – 33
DI Length 40 = difference of 13 – 31
DI Length 50 = difference of 10 – 19
DI Length 60 = difference of 9 – 15
DI Length 70 = difference of 8 – 14
DI Length 80 = difference of 8 – 13
DI Length 90 = difference of 7 – 12
DI Length 100 = difference of 7 – 11
DI Length 110 to DI Length 200 = difference of 6 – 10
DI Length > 200 = difference of less than 6
You can use decimal places of 0.24 or 0.65 if using lengths > 500
This indicator goes up to length 1000.
As I designed this myself and have been using it for more than fifteen years you can trust me when I suggest to stay reasonably close to the default settings.
Output relevance.
The minimum value is zero which means there are no divergences found, you can then find values from 1 to 20 which is a count of the number of instances found.
Paradoxically it is not so significance if the number is very high or very low as a major top occurring on a multi month high may just show a reading of 1, but some minor mid up trend rally might show a reading of 9.
Be suspicious if you see too many large readings of 12 to 18 reoccurring as it is likely that the indicator is plotted on a market in a very long term and rapid up trend which is dangerous to be shorting.
Execution of trades.
Exercise caution with this product.
Risk control is essential and risking more than 1% to 1.5% of your capital from entry price to stop would not be advised.
As with hunting, firing out lots of small trades in a shot gun approach will lead to better results than gambling all on the first signal you see.
There is much more chance of hitting a bird with a shot gun than a canon and the ammunition is much cheaper.
Always always use a stop loss. Something like 3 to 7 times a fifty period average true range for example.
Whilst it is often possible that a spike appears exactly at the precise high of the week or year and could be the only one you see all year it is risky just to short it or sell it instantly as some markets produce several failed signals which continue to rally higher.
The safest and least risky method is to wait for the trend to begin falling after you see a divergence. This is subjective to your own definition of how to measure the trend as “falling” but I would suggest waiting for a 8-20 period Exponential average to turn down before selling.
Once the trade is entered you can implement a trailing stop to allow maximum potential gains and if your style is one of wanting to take quick profits then it is wise to take only some partial profits and give the sell off a chance to go lower and exit the remainder when the trend changes. If the move was picked up near the absolute top it could be a very large collapse in the downtrend.
Sometimes you might wait up to twenty five bars after the divergence is seen before the trend begins falling. Much longer than this an it gradually negates the signal as it shows the buyers have become stronger and the safest decision is to stay out of the market.
It is not unusual for the divergences to mark the exact high of a market and this high can lead to a large move down.
There are however frequent “failed divergences” and these can be treated in the same technical analysis manner as a failed head and shoulders or failed double top where the failure to fall indicates a likelihood of a continuation higher, meaning it is time to cut a loss.
This indicator only gives sell signals. Every single signal will be given in some degree or another in an up trend at the highest high price.
Market selection is important.
Avoid markets in an endless up trend. Look for ebbs and flows in a major down trend.
Best results are on liquid markets in a good long term down trend that has frequent rallies, you can observe the past signals and often history repeats with the good previous signals tending to indicate that future signals may also be good. (This is not certain of course)
This is also true of a market showing several historically bad divergence signals leading to more bad signals.
If the past performance of this indicator is poor on the market you are viewing, then move to another market until one is found where the readings show good price dips after the signals in historical data.
Time frames.
This product can be applied to any time frame of market but be aware as is stated above, the slower time frames yield more valid signals and shorter time frames lead to more randomness and noise ridden plots of lower significance.
That said, it provides a valid reason to enter a trade and can give good results providing good stops and risk control are used. I have seen plenty of valid signals on 30 second charts right up to weekly charts.
Idiosyncrasies.
It can often be seen that multiple divergences occur over a range of ten to thirty or so bars during a very gentle spiky kind of rally.
This can be treated in the same way as above - waiting for the trend to fall after the last divergence occurs is the way to play it.
Groups of divergences can indicate some patient insider selling patterns in anticipation of some bad news they might know.
Thanks for reading this and please read it a few more times to fully understand the points mentioned.
After that please spend some time changing settings and markets to fully appreciate how it operates.
Roger Medcalf - Precision Trading Systems
Custom SMA Plot It creates a custom indicator named "Custom SMA Plot (CSP)" that overlays on a price chart. The indicator fetches the closing prices and calculates a 14-period simple moving average (SMA) of these prices. This SMA is then visually represented as a blue line, which starts from the SMA value of the bar 100 candles ago and extends to the current bar's SMA value. The line has a thickness of 1 unit.
When price breaks over wave go long.
When price breaks below wave go short.
Gaussian Detrended ReversionThis strategy, titled "Gaussian Detrended Reversion Strategy," aims to identify potential price reversals using the customized Gaussian Detrended Price Oscillator (GDPO) in combination with smoothed price cycles.
Key Elements of the Strategy:
GDPO Calculation: The strategy first calculates the Detrended Price Oscillator (DPO) by comparing the close price to an Exponential Moving Average (EMA) of a specified period. This calculation helps identify short-term price cycles by detrending the price data.
Gaussian Smoothing: The DPO values are then smoothed using the Arnaud Legoux Moving Average (ALMA), applying a Gaussian smoothing technique. This smoothed version of the DPO is intended to filter out noise and provide a clearer picture of price trends.
Entry and Exit Conditions: The strategy defines conditions for both long and short entry points as well as exit points. It looks for specific crossover events between the smoothed GDPO and its lagged version. The strategy enters a long position when the smoothed GDPO crosses above the lag and is negative, and exits the long position when the smoothed GDPO crosses below the lag or the zero line. Similarly, the strategy enters a short position when the smoothed GDPO crosses below the lag and is positive, and exits the short position when the smoothed GDPO crosses above the lag or the zero line.
Visualization: The smoothed GDPO and its lag are plotted on the chart using distinct colors. The zero line is also displayed as a reference point. Additionally, the chart background changes color when the strategy enters a long or short position. Cross markers are also plotted at the crossover points as exit cues.
Overall, this strategy aims to capture potential price reversals using the GDPO and Gaussian smoothing, with specific entry and exit conditions to guide trading decisions.
Market Sessions and TPO (+Forecast)This indicator "Market Sessions and TPO (+Forecast)" shows various market sessions alongside a TPO profile (presented as the traditional lettering system or as bars) and price forecast for the duration of the session.
Additionally, numerous statistics for the session are shown.
Features
Session open and close times presented in boxes
Session pre market and post market shown
TPO profile generated for each session (normal market hours only)
A forecast for the remained of the session is projected forward
Forecast can be augmented by ATR
Naked POCs remain on the chart until violated
Volume delta for the session shown
OI Change for the session shown (Binance sourced)
Total volume for the session shown
Price range for the session shown
The image above shows processes of the indicator.
Volume delta, OI change, total volume and session range are calculated and presented for each session.
Additionally, a TPO profile for the most recent session is shown, and a forecast for the remainder of the active session is shown.
The image above shows an alternative display method for the session forecast and TPO profile!
Additionally, the pre-market and post-market times are denoted by dashed boxes.
The image above exemplifies additional capabilities.
That's all for now; further updates to come and thank you for checking this out!
And a special thank you to @TradingView of course, for making all of this possible!
Daily Network Value to Transactions Signal (NVTS)
Quote of GlassNode ...
The NVT Signal (NVTS) is a modified version of the original NVT Ratio.
It uses a 90 day moving average of the daily transaction volume in the denominator instead of the raw daily transaction volume.
This moving average improves the ratio to better function as a leading indicator.
The Network Value to Transactions (NVT) Ratio is calculated by dividing the market cap by the transferred on-chain volume measured in USD.
GlassNode says the NVT Ratio was created by Willy Woo.
I have peaked into Glassnode and took their idea.
I also added a few more Moving Averages to select from, and the length can also be changed.
This script does not depend on Glassnode alone, instead I pulls data of several services...
CoinMarketCap
CoinMetrics
GlassNode
IntoTheBlock
Therefor we have more Tokens to select from.
I have also blocked some faulty data of each service.
If you get a study error of any kind then there is no data available,
or you on a wrong timeframe.
Best to use this script in a daily chart.
And keep in mind it pulls data of yesterday.
Therefor the plot is offset by 1 to the left.
The script will check each service if the data for the chart is available.
Market Cap is taken in the following order ...
CainMarketCap
GlassNode
CoinMetrics
Transaction volume as USD is taken in the following order ...
IntoTheBlock
CoinMetrics
GlassNode
Happy Trading!
Feigenbaum ProjectionsThe theory of price delivery per Feigenbaum projections is credited to TRSTNGLRD, this indicator aims to aid traders from all backgrounds to utilize projections for determination of potential future price moves.
What follows is the simplest description of where to anchor the projection:
As price delivers and clears higher high (buy side liquidity) then reverses to clear most recent low (sell side liquidity), this becomes the anchorage point for the Feigenbaum projection and is referred to as perturbation. The start and end points for the projection should be only those candle bodies that wholly exist within the range within the high and low that were cleared by the perturbation, this range of candle bodies is to be considered the "initial condition". Structure that appears as a broadening formation is one such price delivery occurrence that can be utilized with these projections.
The projected zones are all pre-configured by TRSTNs specifications per Feigenbaum but can be adjusted if the need arises.
Price is expected to expand beyond the initial condition and into the negative and positive target zones, accuracy diminishes with further expansion and reevaluation should occur when a new perturbation is discovered.
It's recommended to explore various timeframes to find a perturbation by which to anchor the next Feigenbaum projection.
I'll do my best to update this description with time as more discoveries are made and TRSTNGLRD provides more guidance and feedback on this indicator.
MAD Volatility PercentileMean Absolute Deviation (MAD) is a statistical measure that tells you how spread out or variable a set of data points is. It calculates the average distance of each data point from the mean (average) of the data set. MAD helps you understand how much individual values differ from the average value. It's a way to measure the overall "average distance" of the data points from the center point.
Indicator Overview:
This indicator measures market volatility using Mean Absolute Deviation of returns. The MAD Volatility Percentile Indicator calculates and represents market volatility as a percentile. The lower the percentile, the lower the volatility, and the higher the percentile value is, the higher the volatility is.
Understanding Volatility:
Lower percentiles signify a lower volatility market environment, reflecting reduced volatility, while higher percentiles indicate increased volatility and significant price movements. The indicator also comes with an SMA to see when the burst of higher volatility occur. You can also change the sample length on the indicators option. You can consider a big move occurring when the percentile value is above the SMA.
Application
Generally when the Mean Absolute Deviation Volatility Percentile is low, then this means that the volatility is low and a expansion could happen soon, which means a big move will occur soon. This indicator can also protect you from entering a trade that will not have any significant moves for a while.
This indicator is not a directional indicator but it can be applied with directional indicators, and is extremely versatile. For example you can use it with momentum indicators and if there is low volatility and bullish momentum then this can be a signal to potentially place a long position.
Features:
The percentile length sets the lookback of the percentile which calculates the percentile of the Mean Absolute Deviation of returns.
Sample length: Gets the volatility sample (returns)
SMA Length: The SMA of the percentile. Used to find when a move can be considered as an "expansion"
Alerts: You can also enable color alerts that flash when the volatility is at extremely low levels which can signify that a big move could happen soon.
This is an example of the alerts that the indicator comes with.
AI Trend Navigator [K-Neighbor]█ Overview
In the evolving landscape of trading and investment, the demand for sophisticated and reliable tools is ever-growing. The AI Trend Navigator is an indicator designed to meet this demand, providing valuable insights into market trends and potential future price movements. The AI Trend Navigator indicator is designed to predict market trends using the k-Nearest Neighbors (KNN) classifier.
By intelligently analyzing recent price actions and emphasizing similar values, it helps traders to navigate complex market conditions with confidence. It provides an advanced way to analyze trends, offering potentially more accurate predictions compared to simpler trend-following methods.
█ Calculations
KNN Moving Average Calculation: The core of the algorithm is a KNN Moving Average that computes the mean of the 'k' closest values to a target within a specified window size. It does this by iterating through the window, calculating the absolute differences between the target and each value, and then finding the mean of the closest values. The target and value are selected based on user preferences (e.g., using the VWAP or Volatility as a target).
KNN Classifier Function: This function applies the k-nearest neighbor algorithm to classify the price action into positive, negative, or neutral trends. It looks at the nearest 'k' bars, calculates the Euclidean distance between them, and categorizes them based on the relative movement. It then returns the prediction based on the highest count of positive, negative, or neutral categories.
█ How to use
Traders can use this indicator to identify potential trend directions in different markets.
Spotting Trends: Traders can use the KNN Moving Average to identify the underlying trend of an asset. By focusing on the k closest values, this component of the indicator offers a clearer view of the trend direction, filtering out market noise.
Trend Confirmation: The KNN Classifier component can confirm existing trends by predicting the future price direction. By aligning predictions with current trends, traders can gain more confidence in their trading decisions.
█ Settings
PriceValue: This determines the type of price input used for distance calculation in the KNN algorithm.
hl2: Uses the average of the high and low prices.
VWAP: Uses the Volume Weighted Average Price.
VWAP: Uses the Volume Weighted Average Price.
Effect: Changing this input will modify the reference values used in the KNN classification, potentially altering the predictions.
TargetValue: This sets the target variable that the KNN classification will attempt to predict.
Price Action: Uses the moving average of the closing price.
VWAP: Uses the Volume Weighted Average Price.
Volatility: Uses the Average True Range (ATR).
Effect: Selecting different targets will affect what the KNN is trying to predict, altering the nature and intent of the predictions.
Number of Closest Values: Defines how many closest values will be considered when calculating the mean for the KNN Moving Average.
Effect: Increasing this value makes the algorithm consider more nearest neighbors, smoothing the indicator and potentially making it less reactive. Decreasing this value may make the indicator more sensitive but possibly more prone to noise.
Neighbors: This sets the number of neighbors that will be considered for the KNN Classifier part of the algorithm.
Effect: Adjusting the number of neighbors affects the sensitivity and smoothness of the KNN classifier.
Smoothing Period: Defines the smoothing period for the moving average used in the KNN classifier.
Effect: Increasing this value would make the KNN Moving Average smoother, potentially reducing noise. Decreasing it would make the indicator more reactive but possibly more prone to false signals.
█ What is K-Nearest Neighbors (K-NN) algorithm?
At its core, the K-NN algorithm recognizes patterns within market data and analyzes the relationships and similarities between data points. By considering the 'K' most similar instances (or neighbors) within a dataset, it predicts future price movements based on historical trends. The K-Nearest Neighbors (K-NN) algorithm is a type of instance-based or non-generalizing learning. While K-NN is considered a relatively simple machine-learning technique, it falls under the AI umbrella.
We can classify the K-Nearest Neighbors (K-NN) algorithm as a form of artificial intelligence (AI), and here's why:
Machine Learning Component: K-NN is a type of machine learning algorithm, and machine learning is a subset of AI. Machine learning is about building algorithms that allow computers to learn from and make predictions or decisions based on data. Since K-NN falls under this category, it is aligned with the principles of AI.
Instance-Based Learning: K-NN is an instance-based learning algorithm. This means that it makes decisions based on the entire training dataset rather than deriving a discriminative function from the dataset. It looks at the 'K' most similar instances (neighbors) when making a prediction, hence adapting to new information if the dataset changes. This adaptability is a hallmark of intelligent systems.
Pattern Recognition: The core of K-NN's functionality is recognizing patterns within data. It identifies relationships and similarities between data points, something akin to human pattern recognition, a key aspect of intelligence.
Classification and Regression: K-NN can be used for both classification and regression tasks, two fundamental problems in machine learning and AI. The indicator code is used for trend classification, a predictive task that aligns with the goals of AI.
Simplicity Doesn't Exclude AI: While K-NN is often considered a simpler algorithm compared to deep learning models, simplicity does not exclude something from being AI. Many AI systems are built on simple rules and can be combined or scaled to create complex behavior.
No Explicit Model Building: Unlike traditional statistical methods, K-NN does not build an explicit model during training. Instead, it waits until a prediction is required and then looks at the 'K' nearest neighbors from the training data to make that prediction. This lazy learning approach is another aspect of machine learning, part of the broader AI field.
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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!
US Recession IndicatorThe US Recession Indicator is designed to identify recessions as they happen, using two reputable indicators that have accurately foreseen all past recessions since 1969. Unlike the National Bureau of Economic Research (NBER) which determines recession dates after the fact, this indicator seeks to spot recessions in real-time. When both of these distinct metrics meet certain criteria, the chart's background becomes shaded, signifying a strong likelihood that the economy is in a recession. Furthermore, a built-in alert system keeps users updated without constant monitoring.
The first metric is the Smoothed Recession Probabilities developed by Marcelle Chauvet. It is based on a dynamic-factor markov-switching model that assesses four monthly coincident variables: non-farm payroll employment, the index of industrial production, real personal income excluding transfer payments and real manufacturing and trade sales. It offers a mathematical analysis of how recessions deviate from expansions. In essence, this index mirrors the probability of the prevailing true economic situation being a recession, grounded on the current GDP data.
The second metric is the Sahm Rule Recession Indicator developed by Claudia Sahm. It operates on the principle that changes in the unemployment rate can be used to identify the onset of a recession. According to this rule, if the three-month moving average of the unemployment rate rises by 0.5 percentage points or more above its lowest point from the preceding year, it flags a potential recession.
For this combined indicator, the thresholds are intentionally set lower than when each metric is used individually. Both metrics must simultaneously suggest a potential recession in order to send a signal. This stems from the realisation that neither metric is infallible and has, on occasion, sent false signals in the past. By requiring both to align, the likelihood of a false positive is reduced. However, it's crucial to understand that past performance does not guarantee future results, leaving the door open for potential false alerts which may not be confirmed by the NBER.
ICT Daily Bias Finder [DTCC]What is This?
The ICT Daily Bias Finder uses a method called "DTCC" to identify the London and New York session's bias, bullish or bearish. This indicator should only be relied on for 5 minute, and not other timeframes.
How do I use it?
Look at the previous days two boxes (labeled DTCC Bear/DTCC Bull), if both are bullish or both are bearish it is NOT recommended to rely on DTCC for that day. If the first one is bullish and second one is bearish, the DTCC for the next day says that London session will turn ABOVE midnight opening price, while New York will turn UNDER midnight opening price (longs in London, shorts in New York). If the second one is bearish and the first is bullish, the DTCC for the next day says that London session will turn UNDER midnight opening price, while New York will turn ABOVE midnight opening price (shorts in London, longs in New York)
Emoji guide to DTCC indicator:
🟢🟢: Don't trust DTCC for that day
🔴🔴: Don't trust DTCC for that day
🟢🔴: Longs in London above Midnight Opening Price, Shorts in New York under Midnight Opening Price
🔴🟢: Shorts in London under Midnight Opening Price, Longs in New York under Midnight Opening Price
Reminder: NEVER rely solely on DTCC, DTCC can be wrong and is not right 100% of times.
Extreme Fundamental PricesExtreme Fundamental Prices is developed for Stock Markets to see the optimum, estimated and extreme estimated prices of any stocks on any markets. It works globally. Every country has different inflation, interest and deposit interest rates. The indicator consider these difference and it adopts itself automatically for chosen stock. Only the "Deposit Interest Rate" is manual because tradingview does not support this value for every country or value is wrong. If you know the deposit interest rate of your country enter the value manually. This is priority. Otherwise switch to "Interest Rate" on the menu. However the Optimum P/E line is not developed to work perfectly with this option. The Extreme Fundamental Prices indicator consists three lines which are,
-Optimum P/E
-Estimated 1Y Price
-Extreme Estimated 1Y Price
Optimum P/E line consists the financial data of chosen stock and economic data of country; which are financials of the stocks, inflation rate, deposit interest rate and interest rate(if "Interest Rate" option chosen).
Estimated 1Y Price line consists the financial data of chosen stock.
Extreme Estimated 1Y Price line consists the financial data of chosen stock.
This indicator does not tell you to buy or sell the stock. If stock price above these lines, the stock is fundamentally overpriced. If stock price below these lines, the stock is not fundamentally overpriced. Logically, price can tend to meet these lines.
For Instance, default value 33.00 is the current Deposit Interest Rate of Turkey. I am using this rate to look stocks on BIST. If you are looking on NASDAQ, just simply enter the deposit interest rate value of USA, looking for DAX enter the Euro Zone deposit interest rate.
Crude Oil Top and Bottoms -by Trevor GeallDiscover the Crude Oil Tops and Bottoms Predictor Indicator: Your Key to Market Precision!
How to Use:
Ideal for the daily chart. Wait for the colored background to form.
Confirm signals by waiting for the first candle to close after the background disappears. That would be your sign to go long (if the line is crossing up) or short (if line is crossing dow).
Combine with other indicators for enhanced insights.
Unveil Market Secrets:
Identifies potential tops and bottoms in crude oil.
Empowers strategic trading decisions.
Advanced divergence detection and price channel analysis.
Note: While powerful, no indicator guarantees perfect predictions. Use it alongside comprehensive analysis and risk management. Elevate your crude oil trading now!
PS If I get enough positive feedback on my indicators ill release some of the better ones.
DCA Liquidation Calculation [ChartPrime]The DCA Liquidation Calculator is a powerful table indicator designed for both manual and bot-assisted traders who practice Dollar Cost Averaging (DCA). Its primary objective is to help traders avoid getting liquidated and make informed decisions when managing their positions. This comprehensive table indicator provides essential information to DCA traders, enabling them to plan their trades effectively and mitigate potential risks of liquidation.
Key Features:
Liquidation Price Awareness: The DCA Liquidation Calculator calculates and displays the liquidation price for each trade within your position. This critical information empowers traders to set appropriate stop-loss levels and avoid being liquidated in adverse market conditions, especially in leveraged trading scenarios.
DCA Recommendations: Whether you are executing DCA manually or using a trading bot, the DCA Liquidation Calculator offers valuable guidance. It suggests optimal entry prices and provides insights into the percentage deviation from the current market price, helping traders make well-timed and well-informed DCA decisions.
Position Sizing: Proper position sizing is essential for risk management. The DCA Liquidation Calculator helps traders determine the percentage of capital to allocate to each trade based on the provided insights. By using the recommended position sizing, traders can protect their capital and potentially maximize profits.
Profit and Loss Visualization: Gain real-time visibility into your Profit and Loss (PnL) with the DCA Liquidation Calculator. This feature allows you to monitor your trades' performance, enabling you to adapt your strategies as needed and make data-driven decisions.
Margin Call Indicators: Anticipating potential margin calls is crucial for maintaining a healthy trading account. The DCA Liquidation Calculator's smart analysis helps you identify and manage potential margin call situations, reducing the risk of account liquidation.
Capital Requirements: Before entering a trade, it's vital to know the required capital. The DCA Liquidation Calculator provides you with this information, ensuring you are adequately prepared to execute your trades without overextending your resources.
Maximum Trade Limit: Considering your available capital, the DCA Liquidation Calculator helps you determine the maximum number of trades you can enter. This feature ensures you maintain a disciplined and sustainable trading approach aligned with your financial capabilities.
Color-Coded Risk Indicators:
Green Liquidation Price Cell: Indicates that the position is considered safe from liquidation at the given parameters.
Yellow Liquidation Price Cell: Warns traders of potential liquidation risk. Exercise caution and monitor the trade closely to avoid undesirable outcomes.
Purple Liquidation Price Cell: Shows the liquidation price, but it does not necessarily indicate an imminent liquidation. Use this information to make prudent risk management decisions.
Red Row: Signals that the trade cannot be executed due to insufficient capital. Consider alternative strategies or ensure adequate capitalization before proceeding.
Settings explained:
In conclusion, the DCA Liquidation Calculator equips traders with essential tools to make well-calculated decisions, minimize liquidation risks, and optimize their Dollar Cost Averaging strategy. By offering comprehensive insights into your trading position, this indicator empowers you to navigate the markets with confidence and increase your potential for successful and sustainable trading.
Oil Price Prediction (Highly Accurate)It's a little-known fact that gold prices move preceded oil prices by 20 months.
If you don't believe me here is a short video from Tom McClellan discussing this www.cnbc.com
This gives us one of the best and highly accurate indicators of what oil will do in the months to come.
HOW TO USE.
When adding the script to your charts it's important to make a couple of adjustments.
Click the triple dots (...), scroll down to pin to scale, and click pin to new scale.
Rght-click the new scale and click auto (fits data to screen)
Go into the indicator settings and turn off the red line.
What you'll be left with is a price projection on where oil prices will go. This becomes your 30,000-foot view. It is important for traders to know if they're coming into a bullish, bearish or consolidating market and this indicator does that.
Its important to mention this is for Monthly charts.
Happy Trading
Extrapolated Previous Trend [LuxAlgo]The Extrapolated Previous Trend indicator extrapolates the estimated linear trend of the prices within a previous interval to the current interval. Intervals can be user-defined.
🔶 USAGE
Returned lines can be used to provide a forecast of trends, assuming trends are persistent in sign and slope.
Using them as support/resistance can also be an effecting usage in case the trend in a new interval does not follow the characteristic of the trend in the previous interval.
The indicator includes a dashboard showing the degree of persistence between segmented trends for uptrends and downtrends. A higher value is indicative of more persistent trend signs.
A lower value could hint at an anti-persistent behavior, with uptrends over an interval often being followed by a down-trend and vice versa. We can invert candle colors to determine future trend direction in this case.
🔶 DETAILS
This indicator can be thought of as a segmented linear model ( a(n)t + b(n) ), where n is the specific interval index. Unlike a regular segmented linear regression model, this indicator is not subject to lookahead bias, coefficients of the model are obtained on previous intervals.
The quality of the fit of the model is dependent on the variability of its coefficients a(n) and b(n) . Coefficients being less subject to change over time are more indicative of trend persistence.
🔶 SETTINGS
Timeframe: Determine the frequency at which new trends are estimated.
TradeMaster SignalsTrading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. To address this, we present a powerful indicator package designed to assist traders on their journey to success.
The TradeMaster indicator package encompasses a variety of trading strategies, including the SMC (Supply, Demand, and Price Action) approach, along with many other techniques. By leveraging concepts such as price action trading, support and resistance analysis, supply and demand dynamics, these indicators can empower traders to analyze entry and exit positions with precision. Unlike other forms of technical analysis that produce values or plots based on historical price data, Price Action brings you the facts straight from the source - the current price movements.
The indicator package consists of three powerful indicators that can be used individually or together to maximize trading effectiveness.
⭐ About the Signals Indicator
This indicator offers a unique opportunity for traders to design their own personalized trading strategy. It has a built-in backtesting system, which allows you to thoroughly analyze the performance of your strategy before implementing it in live trading. With the ability to customize and test your strategy using historical data, the Signals indicator empowers you to make data-driven decisions and refine your trading approach.
👉 How does it work?
The Signals indicator provides users with the ability to select trigger conditions and further narrow them down using confirmations.
Conditions are quantitative factors that influence the generation of signals on the chart and in the backtest table. You can enable multiple conditions to create a comprehensive set of criteria for signal generation.
Confirmations, on the other hand, are qualitative factors that selectively filter out conditions based on their alignment with the chosen confirmations. This helps refine the signals and provide more targeted trading opportunities. Multiple confirmations can be enabled to further enhance the precision of the signals.
A well-balanced strategy in the Signals indicator involves carefully selecting a combination of conditions and confirmations to generate accurate trading signals. Finding the right balance between them is crucial for consistent and profitable trading.
To offer even more flexibility, the Signals indicator includes two powerful main functions:
Target Placement System: This feature allows you to set up to 6 targets with a stop loss level and partial exit percentages. You can choose between automatic target creation or manual customization, giving you control over your profit targets.
Exit Strategy: With this feature, you can define your preferred trailing stop strategy, allowing you to implement a systematic approach to exiting trades. By setting appropriate trailing stop levels, you can limit potential losses, while the system secures profits by automatically closing positions partially when certain price targets are reached. This may help you to maintain discipline in your trading and optimize your risk-reward ratio.
With over 30 unique conditions, 10 confirmations, and the deep Target Placement and Exit Strategy systems, the Signals indicator offers a vast array of possibilities. In fact, there are potentially millions of different strategy outputs available for each ticker. Despite its complexity, the script remains lightweight and fast, ensuring smooth performance.
The Signals Backtest table provides a comprehensive overview of your strategy's performance. You can track your current position with all the necessary details, allowing you to monitor your trades effectively and make informed decisions based on the backtest results.
⚠️ WARNING!
Backtest results do not guarantee future performance. Strategies tested on synthetic data may not accurately represent real-world results. Testing should be conducted on charts that reflect actual closing prices.
The indicator displays buy/sell signals intended to support traders' analysis. There are numerous possibilities and combinations available to create your own unique strategies, whether trading with or against the trend or capturing oversold bounces. These are just a few of the many options! Our indicator can easily be tailored to fit your trading strategy.
The settings that influence the signal-generating algorithm play a crucial role in effectively utilizing the signals. We provide users with the flexibility to modify the settings to align with their trading style, while also offering simple adjustment methods using various techniques.
Each method for modifying the signal settings has been designed to meet specific user needs. It is important to understand that one method is not necessarily more accurate than another.
It is essential to understand that signal indications generally serve as trend confirmations, rather than direct entry and exit points. Focusing on the easy use of signal settings and utilizing other functionalities in our toolkit will likely be a better decision than attempting to find the "holy grail" of optimized signal settings and solely relying on following the signals.
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. Our aim is to offer useful features that meet the needs of the 21st century and that we actually use.
🛑 Risk Notice:
Everything provided by trademasterindicator – from scripts, tools, and articles to educational materials – is intended solely for educational and informational purposes. Past performance does not assure future returns.
Quarterly Version: Sustainable Growth Rate+ (SGR+)The Sustainable Growth Rate+ (SGR+) is an advanced financial indicator designed to estimate the sustainable growth rate of a company in a more comprehensive manner than the traditional Sustainable Growth Rate (SGR). This indicator has been created to overcome certain limitations of the traditional SGR, especially its reliance on Return on Equity (ROE), which does not take into account the impact of debt on a company's growth.
Calculation:
The SGR+ is calculated using the following formula:
(Net Income - Dividends - Depreciation & Amortization) / (Shareholders' Equity + Long-Term Debt)
This formula essentially adjusts the net income by subtracting dividends and depreciation & amortization expenses. The result is then divided by the sum of shareholders' equity and long-term debt. By including long-term debt in the denominator, SGR+ accounts for the role of debt in a company's capital structure, providing a more realistic picture of its potential growth.
Logic:
The logic behind the SGR+ is to factor in both the role of debt and the recurring costs of asset maintenance/replacement (approximated by Depreciation & Amortization expenses) into the growth estimation.
By incorporating debt, we capture a company's total capital employed (equity + debt) rather than just equity, thus considering the full range of financing options used to fuel growth.
Depreciation & Amortization expenses are subtracted from net income to better reflect the amount of earnings that can be retained for growth, as these expenses indicate the necessary reinvestment for maintaining the operational efficiency of a company's assets.
History:
The original SGR was based on the Dupont Analysis developed by the Dupont Corporation in the 1920s. While it provided a useful estimate of a company's potential growth, many analysts felt that it did not fully capture the realities of modern business finance, particularly the significant role of debt and recurring asset costs. This led to the development of the SGR+, which factors in these important elements to provide a more comprehensive and realistic measure of a company's sustainable growth rate.
Usage:
While SGR+ provides a more nuanced estimate of a company's potential growth, it should not be used in isolation. It is most effective when used alongside other financial indicators, including historical growth rates, ROE, and analyst forecasts. It also requires a careful evaluation of a company's earnings consistency and volatility.
Remember, the SGR+ is still an estimation based on various assumptions, and should be used with a sufficient margin of safety. Regularly comparing the SGR+ over multiple years can provide insight into the stability or volatility of a company's growth rate, contributing to a more accurate growth prediction.
Nadaraya-Watson Envelope Strategy (Non-Repainting) Log ScaleIn the diverse world of trading strategies, the Nadaraya-Watson Envelope Strategy offers a different approach. Grounded in mathematical analysis, this strategy utilizes the Nadaraya-Watson kernel regression, a method traditionally employed for interpreting complex data patterns.
At the core of this strategy lies the concept of 'envelopes', which are essentially dynamic volatility bands formed around the price based on a custom Average True Range (ATR). These envelopes help provide guidance on potential market entry and exit points. The strategy suggests considering a buy when the price crosses the lower envelope and a sell when it crosses the upper envelope.
One distinctive characteristic of the Nadaraya-Watson Envelope Strategy is its use of a logarithmic scale, as opposed to a linear scale. The logarithmic scale can be advantageous when dealing with larger timeframes and assets with wide-ranging price movements.
The strategy is implemented using Pine Script v5, and includes several adjustable parameters such as the lookback window, relative weighting, and the regression start point, providing a level of flexibility.
However, it's important to maintain a balanced view. While the use of mathematical models like the Nadaraya-Watson kernel regression may provide insightful data analysis, no strategy can guarantee success. Thorough backtesting, understanding the mathematical principles involved, and sound risk management are always essential when applying any trading strategy.
The Nadaraya-Watson Envelope Strategy thus offers another tool for traders to consider. As with all strategies, its effectiveness will largely depend on the trader's understanding, application, and the specific market conditions.
Adaptive Price Channel (log scale)The field of technical analysis is consistently expanding, with numerous indicators used for market forecasting. Amongst them, a novel indicator dubbed the Adaptive Price Channel (log scale), inspired by the renowned Nadaraya-Watson Envelope (LuxAlgo) from LuxAlgo, is gaining traction for its distinctive features and versatility. Unlike its predecessor, the Adaptive Price Channel (log scale) is applicable on a logarithmic scale, thereby allowing it to be utilized on both smaller and larger timeframes.
1. Key Features
The Adaptive Price Channel (log scale) is founded on the trading view Pinescript language, version 5, with its primary aim to maximize the versatility and scalability of trading indicators. It allows traders to adapt it according to their preferred timeframe, thereby making it applicable for a wide range of trading strategies.
Its bandwidth can be adjusted through the input parameters, offering traders the flexibility to manipulate the indicator according to their strategic requirements. Furthermore, it provides an option for repainting smoothing. This option enables users to control the repainting effect in which the historical output of the indicator may change over time. When disabled, the indicator provides the endpoints of the calculations, ensuring consistency in historical values.
Moreover, the Adaptive Price Channel (log scale) allows for color customization, thereby improving visibility and user-friendliness. The colors of the indicator's upward and downward directions can be changed according to the user's preference.
2. Working Mechanism
The Adaptive Price Channel (log scale) uses the logarithm of the source, which is typically the closing price of a trading instrument. It leverages a Gaussian function that exponentially decreases the further the price moves away from the mean, accounting for both positive and negative values. The bandwidth of the Gaussian function can be adjusted to adapt to different market conditions.
Additionally, the Adaptive Price Channel (log scale) features an array of 500 lines for each bar, which helps in defining the boundaries or envelope for price movements. The calculations are executed using the Nadaraya-Watson estimator, which uses kernel regression for non-parametric analysis.
The calculated values for the upper and lower bounds of the envelope are then converted back from the logarithmic scale using the exponential function. This calculation process continues for each bar until the last bar in the data set.
To ensure optimal performance, the Adaptive Price Channel (log scale) uses dynamic repainting. If the repainting mode is enabled, it adjusts the smoothing of the indicator for the entire historical data, making the results more accurate.
3. Visualization and Alerts
The Adaptive Price Channel (log scale) offers an array of visual aids, including labels and plots. The upper and lower bounds of the envelope are plotted, and the indicator triggers labels at points where the closing price crosses these boundaries. These labels serve as alerts for potential trading opportunities.
4. Conclusion
The Adaptive Price Channel (log scale) is an innovative and adaptable trading indicator, drawing inspiration from its predecessor but introducing unique features to increase its versatility. By providing a repainting option, it ensures consistent historical values, thereby enhancing the reliability of the indicator. Furthermore, the capability to operate on a logarithmic scale broadens its usability for different timeframes. The Adaptive Price Channel (log scale) is a powerful tool for any trader, facilitating a better understanding of market dynamics, and enabling more informed decision-making.
