Bandwidth Volatility - Silverman Rule of thumb EstimatorOverview
This indicator calculates volatility using the Rule of Thumb bandwidth estimator and incorporating the standard deviations of returns to get historical volatility. There are two options: one for the original rule of thumb bandwidth estimator, and another for the modified rule of thumb estimator. This indicator comes with the bandwidth , which is shown with the color gradient columns, which are colored by a percentile of the bandwidth, and the moving average of the bandwidth, which is the dark shaded area.
The rule of thumb bandwidth estimator is a simple and quick method for estimating the bandwidth parameter in kernel density estimation (KSE) or kernel regression. It provides a rough approximation of the bandwidth without requiring extensive computation resources or fine-tuning. One common rule of thumb estimator is Silverman rule, which is given by
h = 1.06*σ*n^(-1/5)
where
h is the bandwidth
σ is the standard deviation of the data
n is the number of data points
This rule of thumb is based on assuming a Gaussian kernel and aims to strike a balance between over-smoothing and under-smoothing the data. It is simple to implement and usually provides reasonable bandwidth estimates for a wide range of datasets. However , it is important to note that this rule of thumb may not always have optimal results, especially for non-Gaussian or multimodal distributions. In such cases, a modified bandwidth selection, such as cross-validation or even applying a log transformation (if the data is right-skewed), may be preferable.
How it works:
This indicator computes the bandwidth volatility using returns, which are used in the standard deviation calculation. It then estimates the bandwidth based on either the Silverman rule of thumb or a modified version considering the interquartile range. The percentile ranks of the bandwidth estimate are then used to visualize the volatility levels, identify high and low volatility periods, and show them with colors.
Modified Rule of thumb Bandwidth:
The modified rule of thumb bandwidth formula combines elements of standard deviations and interquartile ranges, scaled by a multiplier of 0.9 and inversely with a number of periods. This modification aims to provide a more robust and adaptable bandwidth estimation method, particularly suitable for financial time series data with potentially skewed or heavy-tailed data.
Formula for Modified Rule of Thumb Bandwidth:
h = 0.9 * min(σ, (IQR/1.34))*n^(-1/5)
This modification introduces the use of the IQR divided by 1.34 as an alternative to the standard deviation. It aims to improve the estimation, mainly when the underlying distribution deviates from a perfect Gaussian distribution.
Analysis
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Modelling Requirements
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Pros of Bandwidth as a volatility measure
Robust to Data Distribution: Bandwidth volatility, especially when estimated using robust methods like Silverman's rule of thumb or its modifications, can be less sensitive to outliers and non-normal distributions compared to some other measures of volatility
Flexibility: It can be applied to a wide range of data types and can adapt to different underlying data distributions, making it versatile for various analytical tasks.
How can traders use this indicator?
In finance, volatility is thought to be a mean-reverting process. So when volatility is at an extreme low, it is expected that a volatility expansion happens, which comes with bigger movements in price, and when volatility is at an extreme high, it is expected for volatility to eventually decrease, leading to smaller price moves, and many traders view this as an area to take profit in.
In the context of this indicator, low volatility is thought of as having the green color, which indicates a low percentile value, and also being below the moving average. High volatility is thought of as having the yellow color and possibly being above the moving average, showing that you can eventually expect volatility to decrease.
Analysis
Weekend Analysis
There are always discussions about how the weekend affects Crypto-Coins.
It seems that on Monday, the price usually returns to Friday's level.
To make a qualified statement, I wrote this script that tests exactly that
and provides an evaluation.
It displays a candle for Saturday and Sunday.
Either green or red, but also blue if there was hardly any movement.
This threshold is set at 2%, but can be changed in the settings.
If the relative distance from Saturday's open to Friday's close is less than this value,
it counts as the same.
The timeframe should be between day and hour so that Tradingview goes back far enough in the past.
The output (here for BTC)
Total: 477
Lower: 20%
Equal: 55%
Higher: 25%
is displayed in the chart, but also output via the log function.
Awesome Oscillator + Bars count lines + EMA LineThe indicator includes an Awesome Oscillator with 2 vertical lines at a distance of 100 and 140 bars from the last bar to determine the third Elliott wave by the maximum peak of AO in the interval from 100 to 140 bars according to Bill Williams' Profitunity strategy. Additionally, a faster EMA line is displayed that calculates the difference between 5 Period and 34 Period Exponential Moving Averages (EMA 5 - EMA 34) based on the midpoints of the bars, just like AO calculates the difference between Simple Moving Averages (SMA 5 - SMA 34).
In the indicator settings, you can change the number of bars for vertical lines and any parameters for AO and EMA - method (SMA, Smoothed SMA, EMA and others), length, source (open, high, low, close, hl2 and others).
***
Индикатор включает Awesome Oscillator с 2 вертикальными линиями на расстоянии 100 и 140 баров от последнего бара, чтобы определить третью волну Эллиота по максимальному пику AO в интервале от 100 до 140 баров по стратегии Profitunity Билла Вильямса. Дополнительно отображается более быстрая линия EMA, которая вычисляет разницу между 5 Периодной и 34 Периодной Экспоненциальными Скользящими Средними (EMA 5 - EMA 34) по средним точкам баров (hl2), точно так же, как AO вычисляет разницу между Простыми Скользящими Средними (SMA 5 - SMA 34).
В настройках индикатора вы можете изменить количество баров для вертикальных линий и любые параметры для AO и EMA – метод (SMA, Smoothed SMA, EMA и другие), длину, источник (open, high, low, close, hl2 и другие).
Visible bars count on chart + highest/lowest bars, max/min AOThe indicator displays the number of visible bars on the screen (in the upper right corner), including the prices of the highest and lowest bars, the maximum or minimum value of the Awesome Oscillator (similar to MACD 5-34-5) for identify the 3-wave Elliott peak in the interval of 100 to 140 bars according to the Profitunity strategy of Bill Williams. The values change dynamically when scrolling or changing the scale of the graph.
In the indicator settings, you can hide labels, lines and change any parameters for the AO indicator - method (SMA, Smoothed SMA, EMA and others), length, source (open, high, low, close, hl2 and others).
‼️ The values are updated within 2-3 seconds after changing the number of visible bars on the screen.
***
Индикатор отображает количество видимых баров на экране (в правом верхнем углу), в том числе цены самого высокого и самого низкого баров, максимальное или минимальное значение Awesome Oscillator (аналогично MACD 5-34-5), чтобы определить пик 3-волны Эллиота в интервале от 100 до 140 баров по стратегии Profitunity Билла Вильямса. Значения меняются динамически при скроллинге или изменении масштаба графика.
В настройках индикатора вы можете скрыть метки, линии и изменить любые параметры для индикатора AO – метод (SMA, Smoothed SMA, EMA и другие), длину, источник (open, high, low, close, hl2 и другие).
‼️ Значения обновляются в течении 2-3 секунд после изменения количества видимых баров на экране.
Economic Growth Index (XLY/XLP)Keeping an eye on the macroeconomic environment is an essential part of a successful investing and trading strategy. Piecing together and analysing its complex patterns are important to detect probable changing trends. This may seem complicated, or even better left to experts and gurus, but it’s made a whole lot easier by this indicator, the Economic Growth Index (EGI).
Common sense shows that in an expanding economy, consumers have access to cash and credit in the form of disposable income, and spend it on all sorts of goods, but mainly crap they don’t need (consumer discretionary items). Companies making these goods do well in this phase of the economy, and can charge well for their products.
Conversely, in a contracting economy, disposable income and credit dry up, so demand for consumer discretionary products slows, because people have no choice but to spend what they have on essential goods. Now, companies making staple goods do well, and keep their pricing power.
These dynamics are represented in EGI, which plots the Rate of Change of the Consumer Discretionary ETF (XLY) in relation to the Consumer Staples ETF (XLP). Put simply, green is an expanding phase of the economy, and red shrinking. The signal line is the market, a smoothed RSI of the S&P500. Run this on a Daily timeframe or higher. Check it occasionally to see where the smart money is heading.
TimeSeriesRecurrencePlotLibrary "TimeSeriesRecurrencePlot"
In descriptive statistics and chaos theory, a recurrence plot (RP) is a plot showing, for each moment i i in time, the times at which the state of a dynamical system returns to the previous state at `i`, i.e., when the phase space trajectory visits roughly the same area in the phase space as at time `j`.
```
A recurrence plot (RP) is a graphical representation used in the analysis of time series data and dynamical systems. It visualizes recurring states or events over time by transforming the original time series into a binary matrix, where each element represents whether two consecutive points are above or below a specified threshold. The resulting Recurrence Plot Matrix reveals patterns, structures, and correlations within the data while providing insights into underlying mechanisms of complex systems.
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~starling7b
___
Reference:
en.wikipedia.org
github.com
github.com
github.com
github.com
juliadynamics.github.io
distance_matrix(series1, series2, max_freq, norm)
Generate distance matrix between two series.
Parameters:
series1 (float) : Source series 1.
series2 (float) : Source series 2.
max_freq (int) : Maximum frequency to inpect or the size of the generated matrix.
norm (string) : Norm of the distance metric, default=`euclidean`, options=`euclidean`, `manhattan`, `max`.
Returns: Matrix with distance values.
method normalize_distance(M)
Normalizes a matrix within its Min-Max range.
Namespace types: matrix
Parameters:
M (matrix) : Source matrix.
Returns: Normalized matrix.
method threshold(M, threshold)
Updates the matrix with the condition `M(i,j) > threshold ? 1 : 0`.
Namespace types: matrix
Parameters:
M (matrix) : Source matrix.
threshold (float)
Returns: Cross matrix.
rolling_window(a, b, sample_size)
An experimental alternative method to plot a recurrence_plot.
Parameters:
a (array) : Array with data.
b (array) : Array with data.
sample_size (int)
Returns: Recurrence_plot matrix.
Test - Most correlated assetThis is a simple test to find the most and least correlated assets in a list.
Advanced Engulfing CandlesThere are a plenty of Engulfing candle detecting indicators but every single of them detect engulfing candles engulfed by only single candle but sometime it take more then one candle to engulf the previous opposite candle, which is also considered as engulfing candle.
So this script show both type of candles.
Type of Engulfing Candles
Normal Engulfing Candles
Candle engulfed by more then one continuous candle
I hope you will like it.
If you find any bugs or have any suggestions for any possible addition feel free to comment or DM me.
BTC Supply in Profits and Losses (BTCSPL) [AlgoAlpha]Description:
🚨The BTC Supply in Profits and Losses (BTCSPL) indicator, developed by AlgoAlpha, offers traders insights into the distribution of INDEX:BTCUSD addresses between profits and losses based on INDEX:BTCUSD on-chain data.
Features:
🔶Alpha Decay Adjustment: The indicator provides the option to adjust the data against Alpha Decay, this compensates for the reduction in clarity of the signal over time.
🔶Rolling Change Display: The indicator enables the display of the rolling change in the distribution of Bitcoin addresses between profits and losses, aiding in identifying shifts in market sentiment.
🔶BTCSPL Value Score: The indicator optionally displays a value score ranging from -1 to 1, traders can use this to carry out strategic dollar cost averaging and reverse dollar cost averaging based on the implied value of bitcoin.
🔶Reversal Signals: The indicator gives long-term reversal signals denoted as "▲" and "▼" for the price of bitcoin based on oversold and overbought conditions of the BTCSPL.
🔶Moving Average Visualization: Traders can choose to display a moving average line, allowing for better trend identification.
How to Use ☝️ (summary):
Alpha Decay Adjustment: Toggle this option to enable or disable Alpha Decay adjustment for a normalized representation of the data.
Moving Average: Toggle this option to show or hide the moving average line, helping traders identify trends.
Short-Term Trend: Enable this option to display the short-term trend based on the Aroon indicator.
Rolling Change: Choose this option to visualize the rolling change in the distribution between profits and losses.
BTCSPL Value Score: Activate this option to show the BTCSPL value score, ranging from -1 to 1, 1 implies that bitcoin is extremely cheap(buy) and -1 implies bitcoin is extremely expensive(sell).
Reversal Signals: Gives binary buy and sell signals for the long term
Altcoin ManagerThe Altcoin Manager is a comprehensive script for identifying the current altcoin narrative by tracking and analyzing of a wide array of altcoins across various blockchain layers and categories, such as DeFi, GameFi, AI, and Meme coins. Ideal for traders looking to get a broad yet detailed view of the altcoin market, covering various sectors and chains.
The Key Features:
Versatile Asset Tracking:
Tracks 40 different cryptocurrencies (as of publishing) across different categories, allowing for a diversified and detailed analysis of the altcoin market.
Customizable Assets and Category Analysis:
Select 20 of your own coins across 4 different categories such as DeFi, GameFi, AI, and Meme coins as well as specifying their individual chains.
Dynamic Layer and Chain Analysis:
Includes options to plot and analyze specific blockchain layers and chains such as Ethereum Chain, Solana Chain, BNB Smart Chain, Arbitrum Chain, and Polygon Chain. The script associates various assets with specific blockchains, providing a clearer picture of how different segments of the altcoin market are performing.
Cumulative and Per-Candle Change:
Switch between viewing the total cumulative change since a set start date or the per-candle change, offering flexibility in analyzing price movements over different timeframes.
Denomination Adjustment:
Includes a functionality to denominate asset prices in other currencies or crypto such as BTC, allowing for a more tailored financial analysis according to your preference.
Moving Averages for Categories and Chains:
Calculates and plots moving averages for each category and chain, aiding in the identification of trends over the selected moving average length.
How do I use it?
This script is not used with any particular chart. Instead, assign it it's own tab and layout.
For a clearer analysis, use multiple different panels to track Categories and Chains separately, both Cumulative for a longer term analysis and Per-Candle to find ongoing breakouts and changes in trend.
You can either use the pre-selected altcoins to represent the market, or you can select your own.
The Layer 1 and Layer 2 are not customizable but consists of 15 popular Layer 1 incl Bitcoin, Ethereum, Solana etc. Layer 2 consists of 5 popular Layer 2.
Trailing Candle CounterThis script is for users who like to monitor and/or analyze a specified number of candles within the time the last candle closed. Al Brooks fans may enjoy this indicator.
While searching for an indicator that already had this functionality I found a script by @Steversteves which counted the candles/percentage within a set period of time. This let me know it could be done. In honor of Steversteves I kept the table the same colors - although, I added code to allow the table to be modified.
When opening the script the user will need to set a begin/end time to analyze – don't worry as you can set anything you want and it can be altered after the script is running.
This image shows the settings for a user to be able to set a begin time and have the indicator count all the candles from that time through to the current time and update at each candle close. The user can move the beginning time as needed. This is useful if the user is monitoring the length of a trend, wedge, channel, etc.:
If the indicator is in view and the beginning time is on the chart the user can select the table to view/select/change the beginning time.
This image shows the settings for a user to monitor the last set of candles since the last candle closed. This is useful if the user expects a pullback after a set number of candles or expects some alteration in a trend within a set number of candles. In this case the user setting is to watch five candles:
This setting is the reason for my creation of this indicator. This image shows the settings for a user to monitor two sets of candles. In this case an additional set of five candles has been added to the original set of five candles:
If one is watching for movements to last a certain number of bars when the first bar of the movement is exiting the background color the user can expect a change in the price momentum.
This image shows the same functionality as in Steversteves original script (although, I used almost none of his original code). The user can set a begin time and end time to analyze the number or red/green candles and the percentage of each within that time period.
If the indicator is in view and the beginning and end times are on the chart the user can select the table to view/select/change the times.
I hope you find this useful and if you have any questions/comments/suggestions for improvement please comment below.
Rainbow Fibonacci Momentum - SuperTrend🌈 "Rainbow Fibonacci Momentum - SuperTrend" Indicator 🌈
IMPORTANT: as this is a complex and elaborate TREND ANALYSIS on the graph, ALL INDICATORS REPAINT.
Experience the brilliance of "Rainbow Fibonacci Momentum - SuperTrend" for your technical analysis on TradingView! This versatile indicator allows you to visualize various types of Moving Averages, including Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), and Volume Weighted Moving Averages (VWMA).
Each MA displayed in a unique color to create a stunning rainbow effect. This makes it easier for you to identify trends and potential trading opportunities.
Key Features:
📊 Multiple Moving Average Types - Choose from a range of moving average types to suit your analysis.
🎨 Stunning Color Gradient - Each moving average type is displayed in a unique color, creating a beautiful rainbow effect.
📉 Overlay Compatible - Use it as an overlay on your price chart for clear trend insights.
With the "Rainbow Fibonacci Momentum - SuperTrend" indicator, you'll add a burst of color to your trading routine and gain a deeper understanding of market trends.
HOW IT WORKS
MA Lines:
MA - 5: purple lines
MA - 8: blue lines
MA - 13: green lines
MA - 21: yellow lines
MA - 34: orange lines
MA - 55: red line
Header Color Indicators:
Purple: MA-5 is in uptrend on the chart
Blue: MA-5 and MA-8 are in the uptrend on the chart
Green: MA-5, MA-8 and MA-13 are in the uptrend on the chart
Yellow: MA-5, MA-8, MA-13 and MA-21 are in the uptrend on the chart
Orange: MA-5, MA-8, MA-13, MA-21 and MA-34 are in the uptrend on the chart
Red: MA-5, MA-8, MA-13, MA-21, MA-34 and MA-55 are in the uptrend on the chart
Red + White Arrow: All MAs are correctly aligned in the uptrend on the chart
Footer Color Indicators:
Purple: MA-5 is in downtrend on the chart
Blue: MA-5 and MA-8 are in the downtrend on the chart
Green: MA-5, MA-8 and MA-13 are in the downtrend on the chart
Yellow: MA-5, MA-8, MA-13 and MA-21 are in the downtrend on the chart
Orange: MA-5, MA-8, MA-13, MA-21 and MA-34 are in the downtrend on the chart
Red: MA-5, MA-8, MA-13, MA-21, MA-34 and MA-55 are in the downtrend on the chart
Red + White Arrow: All MAs are correctly aligned in the downtrend on the chart
Background Colors:
Light Red: All MAs are on the rise!
Red: All MAs are align correctly on the rise!
Light Green: All MAs are in freefall!
Green: All MAs are align correctly in freefall!
Tiny Arrows Indicators/Alerts:
Down Arrow: All MAs are in freefall!
Up Arrow: All MAs are on the rise!
Big Arrows Indicators/Alerts:
Down Arrow: All MAs are align correctly in freefall!
Up Arrow: All MAs are align correctly on the rise!
Blockunity Stablecoin Liquidity (BSL)Monitor the liquidity of the crypto market by tracking the capitalizations of the major Stablecoins.
Stablecoin Liquidity (BSL) is an ideal tool for visualizing data on major Stablecoins. The number of Stablecoins in circulation is one of the best indices of liquidity within the crypto market. It’s an important metric to keep an eye on, as an increase in the number of Stablecoins in circulation offers a great opportunity to see cryptoasset prices rise. The tool’s multiple on-board display modes enable analysis of its data in the best possible conditions.
The Idea
The goal is to provide the community with the ideal tool to visualize the liquidity of the crypto market, via the state of the market capitalizations of the major Stablecoins.
How to Use
The tool is very easy to use and interpret. First of all, let's distinguish two main elements:
The chart as 3 distinct display modes to let you observe data in the best possible conditions.
There is a panel that summarizes the market capitalizations of the main Stablecoins.
Display Mode: Cumulative
In Cumulative mode (default), the different capitalizations are displayed one on top of the other with colored bands.
You can see that when the number of Stablecoins in circulation increases, crypto asset prices enter an uptrend. And if the liquidity of Stablecoins dries up, the trend will become bearish.
Display Mode: Aggregated
Aggregated mode displays a single line, which is the sum of the different capitalizations, varying between green and red depending on the state of this data according to its moving average declared in the 'Aggregated MA Lengh' field.
You can thus easily see trend changes and therefore opportunities to enter or exit the crypto market.
Display Mode: Independent
The Independent mode also displays the different capitalizations, but detached from each other with labels.
This display mode is particularly interesting for studying transfers from one Stablecoin to another, as can be seen below.
Other Settings
You can choose whether or not to include each of the Stablecoins data, and configure their display color. Note that in 'Cumulative' display mode, the data is taken into account even if the box is unchecked.
How it Works
The tool works in a simple way: We take the market capitalization data of the Stablecoins that interest us, then we process them according to the different display modes.
Let us know if you would like other ways of visualizing this data!
FCF / FFO / CFOA and dividends per shareThe indicator shows the Free Cashflow, Funds From Operations or Cash From Operating Activities per share and you can compare it to the dividends per share. You can see at a glance whether the dividends could be paid by one of this KPI. Please use the 12M time unit for the best result.
Blockchain FundamentalThis indicator is made for traders to harness fundamental blockchain data for better decision-making. Unlike traditional tools, this indicator doesn't depend on standard technical indicators. It offers a novel perspective by focusing on core blockchain metrics like capitalization, miner activity, and other intrinsic data elements. I've designed a distinct scoring logic, exclusive to BF, ensuring it's user-friendly and provides actionable insights for traders at all levels.
Mainly created for Bitcoin , but can be applied to any other crypto assets in cost of losing some metrics in the analysis.
Ethereum chart:
Features:
Customizable Moving Averages:
Choose from an array of moving averages, with the flexibility to adjust the length for a tailored analysis, aiding in pinpointing asset trends.
Blockchain Metrics Integration:
Incorporates a range of blockchain metrics such as Market Cap to Realised Cap ratio, Spent Output Profit Ratio, ATH Drawdown, and more.
Blockchain Metrics Evaluation:
Each metric can be toggled on/off to customize the analysis. Using default settings, traders can use all of the metrics combined.
Every metric is essentially evaluated on a scale from -100 to 100 and then combined with others. If any metric is uncertain about its direction (equals to 0), then the score of it is not accounted in a final calculation.
Kalman Filter:
This indicator offers the option to apply a Kalman filter to the signals, enhancing the smoothness and accuracy of the indicator’s output. This is my approach to mitigate the noise in the final output.
Signal Oscillator:
Displays the aggregated score of all selected blockchain metrics.
Offers visual signals with adjustable upper and lower bounds for easy interpretation based on particular asset observation.
Visual Elements:
Signal Oscillator:
A visual representation of the aggregated blockchain fundamental score.
(White line for a raw calculation, orange line for kalman-filtered one)
Signal Counter:
Displays the count of metrics currently being considered in the fundamental score calculation. (grey line at the middle of an indicator)
Buy/Sell Signal Coloring:
The background color changes to indicate potential buying or selling opportunities based on user-defined bounds.
Usage:
Analysis:
Use the signal oscillator to identify potential market tops and bottoms based on blockchain fundamental data.
Adjust the bounds to customize the sensitivity of buy/sell signals.
Customization:
Enable/disable specific blockchain metrics to tailor the indicator to your analytical needs.
Adjust the moving average type and length for better analysis.
Integration:
Combine with other technical indicators to create a comprehensive trading strategy.
Utilize in conjunction with volume and price action analysis for enhanced decision-making. Every output could be used in traders custom strategies and indicators.
BearMetricsLooking at the financial health of a company is a critical aspect of stock analysis because it provides essential insights into the company's ability to generate profits, meet its financial obligations, and sustain its operations over the long term. Here are several reasons why assessing a company's financial health is important when evaluating a stock:
1. **Profitability and Earnings Growth**: A company's financial statements, particularly the income statement, provide information about its profitability. Analyzing earnings and revenue trends over time can help you assess whether the company is growing or declining. Investors generally prefer companies that show consistent earnings growth.
2. **Risk Assessment**: Financial statements, including the balance sheet and income statement, offer a comprehensive view of a company's assets, liabilities, and equity. By evaluating these components, you can gauge the level of financial risk associated with the stock. A healthy balance sheet typically includes a manageable debt load and strong equity.
3. **Cash Flow Analysis**: Cash flow statements reveal how effectively a company manages its cash, which is crucial for day-to-day operations, debt servicing, and future investments. Positive cash flow is essential for a company's stability and growth prospects.
4. **Debt Levels**: Examining a company's debt levels and debt-to-equity ratio can help you determine its leverage. High debt levels can be a cause for concern, as they may indicate that the company is at risk of financial distress, especially if it struggles to meet interest payments.
5. **Liquidity**: Liquidity is vital for a company's short-term survival. By assessing a company's current assets and current liabilities, you can gauge its ability to meet its short-term obligations. Companies with low liquidity may face difficulties during economic downturns or unexpected financial challenges.
6. **Dividend Sustainability**: If you're an income-oriented investor interested in dividend-paying stocks, you'll want to ensure that the company can sustain its dividend payments. A healthy balance sheet and consistent cash flow can provide confidence in dividend sustainability.
7. **Investment Confidence**: A company with a strong financial position is more likely to attract investor confidence and positive sentiment. This can lead to higher stock prices and a lower cost of capital for the company, which can be beneficial for its growth initiatives.
8. **Risk Mitigation**: By assessing a company's financial health, you can mitigate investment risk. Understanding a company's financial position allows you to make more informed decisions about the level of risk you are comfortable with and whether a particular stock aligns with your risk tolerance.
9. **Long-Term Viability**: Ultimately, investors are interested in companies that have the potential for long-term success. A company with a healthy financial foundation is more likely to weather economic downturns, adapt to industry changes, and thrive over the years.
In summary, examining a company's financial health is a fundamental aspect of stock analysis because it provides a comprehensive picture of the company's current state and its ability to navigate future challenges and capitalize on opportunities. It helps investors make informed decisions and assess the long-term prospects of a stock in their portfolio.
TradersCheckListThe Traders Check List is a unique and innovative tool designed to assist traders in their decision-making process. Unlike traditional indicators that provide signals or visual representations of market data, the Traders Check List offers a structured and customizable checklist that traders can use to ensure they're adhering to their trading plan and strategy.
While there are countless indicators available for trend detection, momentum, volatility, and other market aspects, very few tools focus on the trader's process. The Traders Check List fills this gap by providing a visual reminder of key trading considerations directly on the chart.
Functionality:
Upon applying the Traders Check List to a chart, users will see a table displayed, typically in the top right corner. This table contains rows that represent different trading considerations, such as trend direction, risk management, and psychological factors. Each row can be customized by the user to fit their specific trading plan.
For instance, a trader might have a row labeled "Trending Lower" with a corresponding "Yes/No" column to confirm if the current instrument is indeed trending downward.
Underlying Concepts:
The Traders Check List is based on the principle that successful trading is not just about market analysis but also about discipline and consistency. By having a visual checklist on the chart, traders are constantly reminded of their strategy's key components, reducing the likelihood of impulsive or emotional decisions.
How to Use:
Apply the Traders Check List to your desired chart.
Customize the rows based on your trading strategy's key considerations.
As you analyze the market, update the checklist to reflect the current conditions and your analysis.
Before entering a trade, review the checklist to ensure all criteria are met.
Hybrid EMA AlgoLearner⭕️Innovative trading indicator that utilizes a k-NN-inspired algorithmic approach alongside traditional Exponential Moving Averages (EMAs) for more nuanced analysis. While the algorithm doesn't actually employ machine learning techniques, it mimics the logic of the k-Nearest Neighbors (k-NN) methodology. The script takes into account the closest 'k' distances between a short-term and long-term EMA to create a weighted short-term EMA. This combination of rule-based logic and EMA technicals offers traders a more sophisticated tool for market analysis.
⭕️Foundational EMAs: The script kicks off by generating a 50-period short-term EMA and a 200-period long-term EMA. These EMAs serve a dual purpose: they provide the basic trend-following capability familiar to most traders, akin to the classic EMA 50 and EMA 200, and set the stage for more intricate calculations to follow.
⭕️k-NN Integration: The indicator distinguishes itself by introducing k-NN (k-Nearest Neighbors) logic into the mix. This machine learning technique scans prior market data to find the closest 'neighbors' or distances between the two EMAs. The 'k' closest distances are then picked for further analysis, thus imbuing the indicator with an added layer of data-driven context.
⭕️Algorithmic Weighting: After the k closest distances are identified, they are utilized to compute a weighted EMA. Each of the k closest short-term EMA values is weighted by its associated distance. These weighted values are summed up and normalized by the sum of all chosen distances. The result is a weighted short-term EMA that packs more nuanced information than a simple EMA would.
OrderBlock [kyleAlgo]The principle of this indicator
ATR (Average True Range) Setting: The code uses ATR to help calculate the Supertrend indicator.
Supertrend Trend Direction: Identify bullish and bearish trends with the Supertrend method.
Order Block Recognition: This part of the code recognizes and creates order blocks, visualizing them as boxes on the chart. If the number of blocks exceeds the maximum limit, old blocks will be deleted.
Function to prevent overlapping: check whether the new order block overlaps with the existing order block through the isOverlapping function.
Order block color setting: The code sets the color according to whether the block is bullish or bearish, and whether it breaks above or below. Afterwards the color of the existing order blocks will be updated.
Sensitivity settings: Through the input settings of factor and atrPeriod, the sensitivity of Supertrend and the detection of order blocks can be affected.
Visualization: Use TradingView's box.new function to draw and visualize order blocks on the chart.
Practicality:
Support and Resistance Levels: Order blocks may represent areas of support and resistance in the market. By visualizing these areas, traders can better understand when price reversals are likely to occur.
Trading Signals: Traders may be able to identify trading signals based on the color changes of blocks and price breakouts. For example, if the price breaks above a bullish block, this could be a signal to buy.
Risk Management: By using ATR to adjust the sensitivity of Supertrend, the symbol helps traders to adjust their strategies according to market volatility. This can be used as a risk management tool to help identify stop loss and take profit points.
Multi-timeframe analysis: Although the code itself does not implement multi-timeframe analysis directly, it can be done by applying this indicator on different timeframes. This helps to analyze the market from different angles.
Flexibility and Customization: Through sensitivity settings, traders can customize the indicator according to their needs and trading style.
Reduced screen clutter: By removing overlapping order blocks and limiting the maximum number of order blocks, this code helps reduce clutter on charts, allowing traders to analyze the market more clearly.
Overall, this "Pine Script" can be a powerful analytical tool for trend traders and those looking to improve their trading decisions by visualizing key market areas. It can be used alone or combined with other indicators and trading systems for enhanced functionality.
External Indicator Analysis Overlay | Buy/Sell | HTF Heikin-AshiThis chart overlay offers multiple candlestick display options. The Regular (Japanese) and the Heikin-Ashi candles are well known. The Mari-Ashi (or Renko) option is something special as it should be timeframe independent, so that sideways action should be represented in one candle. That is difficult to realize as an overlay on the normal candlestick structure, but perhaps the chosen implementation is useful nonetheless. The Velocity option is experimental and is designed to show if the price has accelerated too much in a trend direction. In this case, the highs and lows do not reflect the actual highs and lows, but indicate the overshooting velocity. The opening of the candle also depends on the inherent velocity, but the close of the candle is always the actual close. Anyway, it doesn't look very useful, but the option is there.
All options can be applied to higher timeframes. A usable setting is obtained by disabling only the body of the TradingView candles in regular mode and enabling this overlay.
A large part of this overlay consists of buy/sell indication settings. For activation it is necessary to select an external source. For example the “Relative Bi-Directional Volatility Range”, specifically the Trend Shift Signal (TSS). This signal switches from 0 to 1, if the trend becomes bullish or from 0 to -1, if the trend becomes bearish. It will be automatically detected without specifying the Indication Type. Alternatively, the Volatility Moving Average (VMA) would meet the requirements for the Indication Type “Buy = positive | Sell = negative”. The Moving Average Convergence Divergence (MACD) also fulfills these conditions. Another example is to use any Moving Average with the Indication Type “Buy = rising | Sell = falling”. In the chart above the Hull Moving Average (HMA) is used. In addition, it is possible to reverse the signal, so that positive signals become negative and vice versa. The signals will be labeled as Buy or Sell on the chart.
The user can analyze whether the provided signals are good or bad indications for going long or short or simply for rebalancing a portfolio. Therefore, it is possible to set a starting point for the analysis and choose a weighting for the investments from 0% to 100% of the portfolio. To avoid sleepless nights, a very reliable (and conservative) setting seems to be Rebalancing with 50% (very similar to the well-known 60/40 portfolio). The calculation results are shown in a table.
As a small addition there is the possibility to label the peaks by setting the distance between the highs/lows. This will make the quality of the buy and sell signals even more clear.
Price by Volume ColumnsThis indicator allows you to identify how price changes for a given time period are sensitive to the volume. You will identify these changes as bars in the bottom of the chart. You may see the changes in bars for better understanding of price movements, identify trends. Please take trades at your own risk and discretion
Bitcoin Limited Growth ModelThe Bitcoin Limeted Growth is a model proposed by QuantMario that offers an alternative approach to estimating Bitcoin's price based on the Stock-to-Flow (S2F) ratio. This model takes into account the limitations of the traditional S2F model and introduces refinements to enhance its analysis.
The S2F model is commonly used to analyze Bitcoin's price by considering the scarcity of the asset, measured by the stock (existing supply) relative to the flow (new supply). However, the LGS-S2F Bitcoin Price Formula recognizes the need for improvements and presents an updated perspective on Bitcoin's price dynamics.
Invalidation of the Normal S2F Model:
The normal S2F model has faced criticisms and challenges. One of the limitations is its assumption of a linear relationship between the S2F ratio and Bitcoin's price, overlooking potential nonlinearities and other market dynamics. Additionally, the normal S2F model does not account for external influences, such as market sentiment, regulatory developments, and technological advancements, which can significantly impact Bitcoin's price.
Addressing the Issues:
The LGS-S2F Bitcoin Price Formula introduces refinements to address the limitations of the traditional S2F model. These refinements aim to provide a more comprehensive analysis of Bitcoin's price dynamics:
Nonlinearity: The LGS-S2F model recognizes that the relationship between the S2F ratio and Bitcoin's price may not be linear. It incorporates a logistic growth function that considers the diminishing returns of scarcity and the saturation of market demand.
Data Analysis: The LGS-S2F model employs statistical analysis and data-driven techniques to validate its predictions. It leverages historical data and econometric modeling to support its analysis of Bitcoin's price.
Utility:
The LGS-S2F Bitcoin Price Formula offers insights for traders and investors in the cryptocurrency market. By incorporating a more refined approach to analyzing Bitcoin's price, this model provides an alternative perspective. It allows market participants to consider various factors beyond the S2F ratio alone, potentially aiding in their decision-making processes.
Key Features:
Adjustable Coefficients
Sigma calculation methods: Normal or Stdev
Credit:
The LGS-S2F Bitcoin Price Formula was developed by QuantMario, who has contributed to the field of cryptocurrency analysis through their research and modeling efforts.
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
