US Net LiquidityAnalysis of US Net Liquidity: A Comprehensive Overview
Introduction:
The "US Net Liquidity" indicator offers a detailed analysis of liquidity conditions within the United States, drawing insights from critical financial metrics related to the Federal Reserve (FED) and other government accounts. This tool enables economists to assess liquidity dynamics, identify trends, and inform economic decision-making.
Key Metrics and Interpretation:
1. Smoothing Period: This parameter adjusts the level of detail in the analysis by applying a moving average to the liquidity data. A longer smoothing period results in a smoother trend line, useful for identifying broader liquidity patterns over time.
2. Data Source (Timeframe): Specifies the timeframe of the data used for analysis, typically daily (D). Different timeframes can provide varying perspectives on liquidity trends.
3. Data Categories:
- FED Balance Sheet: Represents the assets and liabilities of the Federal Reserve, offering insights into monetary policy and market interventions.
- US Treasury General Account (TGA): Tracks the balance of the US Treasury's general account, reflecting government cash management and financial stability.
- Overnight Reverse Repurchase Agreements (RRP): Highlights short-term borrowing and lending operations between financial institutions and the Federal Reserve, influencing liquidity conditions.
- Earnings Remittances to the Treasury: Indicates revenues transferred to the US Treasury from various sources, impacting government cash flow and liquidity.
4. Moving Average Length: Determines the duration of the moving average applied to the data. A longer moving average length smoothens out short-term fluctuations, emphasizing longer-term liquidity trends.
Variation Lookback Length: Specifies the historical period used to assess changes and variations in liquidity. A longer lookback length captures more extended trends and fluctuations.
Interpretation:
1. Data Retrieval: Real-time data from specified financial instruments (assets) is retrieved to calculate balances for each category (FED, TGA, RRP, Earnings Remittances).
2. Global Balance Calculation: The global liquidity balance is computed by aggregating the balances of individual categories (FED Balance - TGA Balance - RRP Balance - Earnings Remittances Balance). This metric provides a comprehensive view of net liquidity.
3. Smoothed Global Balance (SMA): The Simple Moving Average (SMA) is applied to the global liquidity balance to enhance clarity and identify underlying trends. A rising SMA suggests improving liquidity conditions, while a declining SMA may indicate tightening liquidity.
Insight Generation and Decision-Making:
1. Trend Analysis: By analyzing smoothed liquidity trends over time, economists can identify periods of liquidity surplus or deficit, which can inform monetary policy decisions and market interventions.
2. Forecasting: Understanding liquidity dynamics aids in economic forecasting, particularly in predicting market liquidity, interest rate movements, and financial stability.
3. Policy Implications: Insights derived from this analysis tool can guide policymakers in formulating effective monetary policies, managing government cash flow, and ensuring financial stability.
Conclusion:
The "US Net Liquidity" analysis tool serves as a valuable resource for economists, offering a data-driven approach to understanding liquidity dynamics within the US economy. By interpreting key metrics and trends, economists can make informed decisions and contribute to macroeconomic stability and growth.
Disclaimer: This analysis is based on real-time financial data and should be used for informational purposes only. It is not intended as financial advice or a substitute for professional expertise.
Forecasting
Kaspa Power LawSimple Power Law Indicator for Kaspa with addition of adjustable bands above and below the Power Law Price. Best used on Logarithmic view on Daily Time Frame.
Futures Auto Levels [NariCapitalTrading]Futures Auto Levels Indicator
Introduction
The "Futures Auto Levels" (FAL) indicator shows the previous day's levels, weekly open, high, low, and the Initial Balance Range (IBR).
Indicator Components
The FAL indicator comprises the following components:
Previous Day's Levels: These include the open, high, low, and close of the previous trading day. They are represented on the chart by lines and labels, helping to identify significant price levels from the prior session.
Weekly Open, High, Low: These levels represent the open, high, and low prices of the current trading week.
Initial Balance Range (IBR): The IBR is calculated based on the price range during the first 60 minutes of the trading day. It helps identify initial trading range and potential breakout levels.
How to Use the Indicator
1. Previous Day's Levels:
Monitor the previous day's open, high, low, and close to identify key support and resistance levels.
Use these levels to gauge market sentiment and potential price reversals.
2. Weekly Open, High, Low:
Pay attention to the weekly open, high, and low to understand the market's behavior within the weekly timeframe.
These levels can act as reference points for setting profit targets and stop-loss orders.
3. Initial Balance Range (IBR):
Watch for price movements within the IBR to identify potential trading opportunities.
Breakouts above or below the IBR may signal the beginning of a new trend or continuation of the current trend.
Suggested/Potential Strategies
Reversal Trading: Look for price reversals around previous day's levels, especially when they coincide with other technical indicators or significant support/resistance zones.
Trend Following: Follow the trend by trading breakouts above/below the IBR or weekly high/low levels. Use trailing stops to capture profits while the trend remains intact.
Range Trading: Trade within the IBR when the market is consolidating. Buy near the IBR low and sell near the IBR high, with tight stop-loss orders to manage risk.
Conclusion
The Futures Auto Levels indicator is designed to help incorporate levels into trading analysis and trading strategies to improve profitability and consistency.
The Next Pivot (With History) [Mxwll]Introducing "The Next Pivot (With History)"!
With permission from the author @KioseffTrading
The script "The Next Pivot" has been restructured to show historical projections!
Features
Find the most similar price sequence per time frame change.
Forecast almost any public indicator! Not just price!
Forecast any session i.e. 4Hr, 1Hr, 15m, 1D, 1W
Forecast ZigZag for any session
Spearmen
Pearson
Absolute Difference
Cosine Similarity
Mean Squared Error
Kendall
Forecasted linear regression channel
The image above shows/explains some of the indicator's capabilities!
Additionally, you can project almost any indicator!
Should load times permit it, the script can search all bar history for a correlating sequence. This won't always be possible, contingent on the forecast length, correlation length, and the number of bars on the chart.
If a load time error occurs, simple reduce the "Bars Back To Search" parameter!
The script can only draw 500 bars into the future. For whatever time frame you are on and the session you wish to project, ensure it will not exceeded a 500-bar forecast!
Reasonable Assessment
The script uses various similarity measures to find the "most similar" price sequence to what's currently happening. Once found, the subsequent price move (to the most similar sequence) is recorded and projected forward.
So,
1: Script finds most similar price sequence
2: Script takes what happened after and projects forward
While this may be useful, the projection is simply the reaction to a possible one-off "similarity" to what's currently happening. Random fluctuations are likely and, if occurring, similarities between the current price sequence and the "most similar" sequence are plausibly coincidental.
Thanks!
Monte Carlo Shuffled Projection [LuxAlgo]The Monte Carlo Shuffled Projection tool randomly simulates future price points based on historical bar movements made within a user-selected window.
The tool shows potential paths price might take in the future, as well as highlighting potential support/resistance levels.
Note that simulations and their resulting elements are subject to slight changes over time.
🔶 USAGE
By randomly simulating bar movements, a range is developed of potential price action which could be utilized to locate future price development as well as potential support/resistance levels.
Performing a large number of simulations and taking the average at each step will converge toward the result highlighted by the "Average Line", and can point out where the price might develop assuming the trend and amount of volatility persist.
Current closing price + Sum of changes in the calculation window)
This constraint will cause the simulations to always display an endpoint consistent with the current lookback's slope.
While this may be helpful to some traders, this indicator includes an option to produce a less biased range as seen below:
🔶 DETAILS
The Monte Carlo Shuffled Projection tool creates simulations based on the most recent prices within a user-set window. Simulations are done as follows:
Collect each bar's price changes in the user-set window.
Randomize the order of each change in the window.
Project the cumulative sum of the shuffled changes from the current closing price.
Collect data on each point along the way.
This is the process for the Default calculation, for the 'Randomize Direction' calculation, when added onto the front for every other change, the value is inverted, creating the randomized endpoints for each simulation.
The script contains each simulation's data for that bar with a maximum of 1000 simulations.
To get a glimpse behind the scenes each simulation (up to 99) can be viewed using the 'Visualize Simulations' Options as seen below.
Because the script holds the full simulation data, the script can also do calculations on this data, such as calculating standard deviations.
In this script the Standard deviation lines are the average of all standard deviations across the vertical data groups, this provides a singular value that can be displayed a distance away from the simulation center line.
🔶 SETTINGS
Color and Toggle Options are Provided throughout.
Lookback: Sets the number of Bars to include in calculations.
Simulation Count: Sets the number of randomized simulations to calculate. (Max 1000)
Randomize Direction: See Details Above. Creates a more 'Normalized' Distribution
Visualize Simulations: See Details Above. Turns on Visualizations, and colors are randomly generated. Visualized max does not cap the calculated max. If 1000 simulations are used, the data will be from 1000 simulations, however only the last 99 simulations will be visualized.
Standard Deviation Multiplier: Sets the multiplier to use for the Standard Deviation distance away from the center line.
BTC Backwardation SearcherThis Pine Script code is a custom indicator named "BTC Backwardation Searcher" designed for the TradingView platform. The indicator aims to identify and visualize the price difference between two Bitcoin futures contracts: CME:BTC1! and CME:BTC2!.
Here's a breakdown of the code:
1. The script fetches the daily close prices of CME:BTC1! and CME:BTC2! using the security() function.
2. It calculates the percentage price difference between the two contracts using the formula: (btc1Price - btc2Price) / btc2Price * 100.
3. The script also calculates the price difference for the previous two days (2 days ago and 3 days ago) using the same formula.
4. Two conditions are defined:
(1) dailyGreenCondition: If the price difference is greater than or equal to 0.3% for three
consecutive days, including the current day and the previous two days.
(2) dailyRedCondition(commented): If the price difference is less than or equal to -1% for three consecutive days, including the current day and the previous two days.
(I commented it out because I don't think it's useful.)
5. The plotshape() function is used to display green triangles on the chart when the dailyGreenCondition is met, and red triangles when the dailyRedCondition is met. These triangles are displayed on the daily, weekly, and monthly timeframes.
The purpose of this indicator is to help traders identify potential trading opportunities based on the price difference between the two Bitcoin futures contracts. The green triangles suggest a bullish scenario where CME:BTC1! is significantly higher than CME:BTC2!, while the red triangles indicate a bearish scenario where CME:BTC2! is significantly lower than CME:BTC1!.
However, it's important to note that this indicator should be used in conjunction with other technical analysis tools and fundamental analysis. Traders should also consider their risk tolerance, investment goals, and market conditions before making any trading decisions based on this indicator.
FVG Breakaway/3rd Candle (Arjo) [MK]Simple script to identify FVGs (Fair Value Gaps) on the current chart timeframe. The script differs from other FVG indicators on the Tradingview platform by using Arjos 3rd candle rule to identify which gaps are 'Breakway Gaps' and which Gaps are likely to be returned to.
NOTE: As with all 'trading rules' this theory is not 100% accurate.
default settings:
Breakaway Gaps = YELLOW
Gaps that price may return to = GREEN
Mitigated Gaps = 100% TRANSPARENT
What is a FVG:
A FVG is a price area defined by a 3 candle pattern. For a bullish FVG, the low of the 3rd candle must be higher than the high of the 1st candle. This then leaves an area that is drawn as in the example below:
A bearish FVG is defined by the high of the 3rd candle being lower than the low of the 1st candle, as shown in the example below:
FVGs can act like magnets where price will either retrace to or reach for, therefore they can be used as entry points and also for take profit target levels.
If for example, a trader would like to use an FVG for an entry, it would be useful to know which FVGs are more likely for price to re-enter and which FVG will be left un-touched. FVGs that are likely to be left un-touched by price are called 'Breakaway Gaps'.
How do we define a 'Breakaway Gap':
First we identify FVGs using the rules stated above, then we look to see where the 3rd candle closed in relation to the 2nd candle. For a bullish 'Breakaway Gap' we want to see the 3rd candle close above the high of the 2nd candle. An example of a bullish Breakaway Gap is shown in the example below:
A bearish 'Breakaway Gap' is defined by the close of the 3rd candle being lower than the low of the 2nd candle. An example is shown below:
How do we define an FVG that price may return to:
Any gap that does not meet the above rules for a 'Breakway Gap' is therefore considered an FVG that price may return to. So for a bullish FVG that price may return to we would look to see if the close of the 3rd candle is above the high of the 2nd candle. If it is not above the high of the 2nd candle then it more likely that price will retrace into the FVG before continuing higher. An example is shown below:
A bearish gap that price may return to is defined by the close of the 3rd candle not being lower than the low of the 2nd candle. An example is shown below:
The indicator is based on the teachings of 'Arjo'. Note: breakaway gaps will only remain 'breakaway' until a liquidity level is reached. Breakaways therefore do not remain 'breakaway' forever. Users of the indicators must fully comprehend this theory before using the indicator with live markets.
Users of the script should be fully aware of this concept and also have conducted thorough backtesting using a large data set before using this indicator with live accounts.
Uptrick: Trend Analysis 1 Trend Identification:
• The indicator primarily aims to identify trends in the market. It does this by computing two EMAs (fast and slow) and deriving the MACD line, which is the difference between these two EMAs. The MACD line is a momentum indicator that shows the relationship between two moving averages. When the MACD line is above the signal line, it suggests bullish momentum, while below indicates bearish momentum.
2 Entry and Exit Signals:
• The indicator generates potential entry and exit signals based on several conditions:
• Price vs. 20-period EMA: It checks whether the price is above or below the 20-period Exponential Moving Average. This is a common technique used to determine the overall direction of the trend. If the price is above the 20-period EMA, it suggests a bullish trend, and if it's below, it indicates a bearish trend.
• MACD Slope: It calculates the slope of the MACD line over a specified number of bars. A positive slope suggests increasing bullish momentum, while a negative slope indicates increasing bearish momentum.
• Signal Line Crossings: Traders often look for crossovers between the MACD line and the signal line as potential buy or sell signals. When the MACD line crosses above the signal line, it's considered a bullish signal (buy), and when it crosses below, it's seen as a bearish signal (sell).
3 Visual Representation:
• The indicator provides a visual representation of these conditions by plotting the MACD line with different colors depending on the market conditions (bullish, bearish, or neutral). Additionally, it draws vertical lines at the start of negative MACD slopes to highlight potential shifts in momentum.
4 Volume Analysis:
• It incorporates volume analysis by coloring the volume histogram differently based on whether the price is above or below the 20-period EMA. This can provide additional confirmation of trend strength. Higher volumes during price movements above the EMA may confirm bullish trends, while higher volumes during price movements below the EMA may confirm bearish trends.
5 Customization:
• Traders can customize the input parameters such as the fast and slow EMA periods according to their trading strategies and the specific market they're analyzing.
VWAP RollingThis indicator, referred to here as "VWAP Rolling," is a technical tool designed to provide insight into the average price at which an asset has traded over a specified rolling period, along with bands that can indicate potential overbought or oversold conditions based on standard deviations from this rolling VWAP.
Purpose and Utility:
The indicator's primary purpose is to track the volume-weighted average price (VWAP) over a specified period, typically 20 bars in this script. The VWAP Rolling is particularly useful in assessing the average price level at which a security has been traded over the recent history, incorporating both price and volume data. This can help traders understand the prevailing market price in relation to trading volume.
Advantages:
1. Dynamic Average: Unlike fixed VWAP indicators that calculate over a specific session, the rolling VWAP adapts to recent price and volume changes, offering a more responsive and dynamic average.
2. Volume Sensitivity: By weighting prices by volume, the rolling VWAP gives more importance to periods with higher trading activity, providing a clearer picture of where significant trading has occurred.
3. Standard Deviation Bands: The inclusion of standard deviation bands (configurable as 1x and 2x deviations in this script) around the rolling VWAP adds a layer of analytical depth. These bands can serve as potential areas of support and resistance, highlighting deviations from the mean price.
Singularization and Interpretation:
The VWAP Rolling indicator is singularized by its ability to adapt to changing market conditions, offering a dynamic representation of the average price level influenced by volume. To use and interpret this indicator effectively:
• Rolling VWAP Line: The main line represents the rolling VWAP. When this line trends upwards, it suggests that recent trading has been occurring at higher prices weighted by volume, indicating potential bullish sentiment. Conversely, a downtrend in the rolling VWAP may indicate bearish sentiment.
• Standard Deviation Bands: The upper and lower bands (configurable as 1x and 2x standard deviations from the rolling VWAP) are used to identify potential overbought or oversold conditions. A price crossing above the upper band may indicate overbought conditions, signaling a potential reversal or correction downwards. Conversely, a price crossing below the lower band may suggest oversold conditions, potentially signaling a bounce or reversal upwards.
• Band Interaction: Watch for interactions between price and these bands. Repeated touches or breaches of the bands can provide clues about the strength of the prevailing trend or potential reversals.
Interpretative Insights:
• Trend Confirmation: The direction of the rolling VWAP can confirm or contradict the prevailing price trend. If the price is above the rolling VWAP and the VWAP is rising, it suggests a strong bullish sentiment. Conversely, a falling rolling VWAP with prices below might indicate a bearish trend.
• ean Reversion Signals: Extreme moves beyond the standard deviation bands may signal potential mean reversion. Traders can look for price to revert back towards the rolling VWAP after such deviations.
In summary, the VWAP Rolling indicator offers traders a flexible tool to gauge average price levels and potential deviations, incorporating both price and volume dynamics. Its adaptability and standard deviation bands provide valuable insights into market sentiment and potential trading opportunities.
Sector Rotation Hedging With Volatility Index [TradeDots]The "Sector Rotation Hedging Strategy With Volatility Index" is a comprehensive trading indicator developed to optimally leverage the S&P500 volatility index. It is designed to switch between distinct ETF sectors, strategically hedging to moderate risk exposure during harsh market volatility.
HOW DOES IT WORK
The core of this indicator is grounded on the S&P500 volatility index (VIX) close price and its 60-day moving average. This serves to determine whether the prevailing market volatility is above or below the quarterly average.
In periods of elevated market volatility, risk exposure escalates significantly. Traders retaining stocks in sectors with disproportionately high volatility face increased vulnerability to negative returns. To tackle this, our indicator employs a two-pronged approach utilizing two sequential candlestick close prices to confirm if volatility surpasses the average value.
Upon confirming above-average volatility, a hedging table is deployed to spotlight ETFs with low volatility, such as the Utilities Select Sector SPDR Fund (XLU), to derisk the overall portfolio.
Conversely, in low-volatility conditions, sectors yielding higher returns like the Technology Select Sector SPDR Fund (XLK) are preferred. The hedging table is utilized to earmark high-return sector ETFs.
Thus, during highly volatile market periods, the strategy recommends enhancing portfolio allocation to low-volatility ETFs. During low-volatility windows, the portfolio is calibrated towards high-volatility ETFs for heightened returns.
IMPORTANT CONSIDERATION
In real trading, additional considerations encompassing trading commissions, management fees, and ancillary rotation costs should be factored in. False signals may arise, potentially leading to losses from these fees.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Fair ValueThis indicator is designed to provide a valuation perspective based on a specified length and deviations from a base value. This code calculates fair value levels relative to a chosen source (typically closing prices) using simple moving averages (SMA) or exponential moving averages (EMA). Please note that this is purely educational and should not be considered financial advice.
Key Features:
1. Valuation Calculation: The indicator computes a base value using either SMA or EMA, providing a reference point for fair value.
2. Deviation Levels: Additional levels of valuation are defined as deviations from the base value, indicating potential overvalued or undervalued conditions.
3. Currency-Specific Display: It displays valuation levels in different currency symbols based on the asset's trading currency.
4. Visual Representation: The indicator plots fair value lines and shades areas to highlight potential deviations.
5. Line Projection: A projection line shows potential future movement based on the calculated slope. This feature forecasts future price movement using a linear regression line's slope, dynamically projecting the trend forward. It provides traders with valuable insight into potential future price behavior. The implementation involves complex mathematical computations to determine the slope and iterative drawing of projected segments.
Educational Purpose: This indicator is for educational purposes only. It does not guarantee accuracy or suitability for trading decisions.
Please use caution and consider consulting a financial professional before making any investment decisions based on this indicator. Keep in mind that market conditions can change rapidly, and historical performance may not predict future results.
Price Prediction With Rolling Volatility [TradeDots]The "Price Prediction With Rolling Volatility" is a trading indicator that estimates future price ranges based on the volatility of price movements within a user-defined rolling window.
HOW DOES IT WORK
This indicator utilizes 3 types of user-provided data to conduct its calculations: the length of the rolling window, the number of bars projecting into the future, and a maximum of three sets of standard deviations.
Firstly, the rolling window. The algorithm amasses close prices from the number of bars determined by the value in the rolling window, aggregating them into an array. It then calculates their standard deviations in order to forecast the prospective minimum and maximum price values.
Subsequently, a loop is initiated running into the number of bars into the future, as dictated by the second parameter, to calculate the maximum price change in both the positive and negative direction.
The third parameter introduces a series of standard deviation values into the forecasting model, enabling users to dictate the volatility or confidence level of the results. A larger standard deviation correlates with a wider predicted range, thereby enhancing the probability factor.
APPLICATION
The purpose of the indicator is to provide traders with an understanding of the potential future movement of the price, demarcating maximum and minimum expected outcomes. For instance, if an asset demonstrates a substantial spike beyond the forecasted range, there's a significantly high probability of that price being rejected and reversed.
However, this indicator should not be the sole basis for your trading decisions. The range merely reflects the volatility within the rolling window and may overlook significant historical price movements. As with any trading strategies, synergize this with other indicators for a more comprehensive and reliable analysis.
Note: In instances where the number of predicted bars is exceedingly high, the lines may become scattered, presumably due to inherent limitations on the TradingView platform. Consequently, when applying three SD in your indicator, it is advised to limit the predicted bars to fewer than 80.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Fibonacci Trend Reversal StrategyIntroduction
This publication introduces the " Fibonacci Retracement Trend Reversal Strategy, " tailored for traders aiming to leverage shifts in market momentum through advanced trend analysis and risk management techniques. This strategy is designed to pinpoint potential reversal points, optimizing trading opportunities.
Overview
The strategy leverages Fibonacci retracement levels derived from @IMBA_TRADER's lance Algo to identify potential trend reversals. It's further enhanced by a method called " Trend Strength Over Time " (TSOT) (by @federalTacos5392b), which utilizes percentile rankings of price action to measure trend strength. This also has implemented Dynamic SL finder by utilizing @veryfid's ATR Stoploss Finder which works pretty well
Indicators:
Fibonacci Retracement Levels : Identifies critical reversal zones at 23.6%, 50%, and 78.6% levels.
TSOT (Trend Strength Over Time) : Employs percentile rankings across various timeframes to gauge the strength and direction of trends, aiding in the confirmation of Fibonacci-based signals.
ATR (Average True Range) : Implements dynamic stop-loss settings for both long and short positions, enhancing trade security.
Strategy Settings :
- Sensitivity: Set default at 18, adjustable for more frequent or sparse signals based on market volatility.
- ATR Stop Loss Finder: Multiplier set at 3.5, applying the ATR value to determine stop losses dynamically.
- ATR Length: Default set to 14 with RMA smoothing.
- TSOT Settings: Hard-coded to identify percentile ranks, with no user-adjustable inputs due to its intrinsic calculation method.
Trade Direction Options : Configurable to support long, short, or both directions, adaptable to the trader's market assessment.
Entry Conditions :
- Long Entry: Triggered when the price surpasses the mid Fibonacci level (50%) with a bullish TSOT signal.
- Short Entry: Activated when the price falls below the mid Fibonacci level with a bearish TSOT indication.
Exit Conditions :
- Employs ATR-based dynamic stop losses, calibrated according to current market volatility, ensuring effective risk management.
Strategy Execution :
- Risk Management: Features adjustable risk-reward settings and enables partial take profits by default to systematically secure gains.
- Position Reversal: Includes an option to reverse positions based on new TSOT signals, improving the strategy's responsiveness to evolving market conditions.
The strategy is optimized for the BYBIT:WIFUSDT.P market on a scalping (5-minute) timeframe, using the default settings outlined above.
I spent a lot of time creating the dynamic exit strategies for partially taking profits and reversing positions so please make use of those and feel free to adjust the settings, tool tips are also provided.
For Developers: this is published as open-sourced code so that developers can learn something especially on dynamic exits and partial take profits!
Good Luck!
Disclaimer
This strategy is shared for educational purposes and must be thoroughly tested under diverse market conditions. Past performance does not guarantee future results. Traders are advised to integrate this strategy with other analytical tools and tailor it to specific market scenarios. I was only sharing what I've crafted while strategizing over a Solana Meme Coin.
Symbol CorrelationThe "Symbol Correlation" indicator calculates and displays the correlation between the chosen symbol's price and another selected source over a specified period. It also includes a moving average (SMA) of this correlation to provide a smoothed view of the relationship.
Why SMA and Table Display ?
The inclusion of SMA (Simple Moving Average) with adjustable length (SMA Length) enhances the indicator's utility by smoothing out short-term fluctuations in correlation, allowing for clearer trend identification. The SMA helps to visualize the underlying trend in correlation, making it easier to spot changes and patterns over time.
The table display of the correlation SMA value offers a concise summary of this trend. By showcasing the current correlation SMA alongside its historical values, traders can quickly gauge the relationship's strength relative to previous periods.
Interpreting the Indicator:
1. Correlation Values: The primary plot shows the raw correlation values between the symbol's price and the specified source. A value of 1 indicates a perfect positive correlation, -1 signifies a perfect negative correlation, and 0 suggests no linear relationship.
2. Correlation SMA: The SMA line represents the average correlation over a defined period (SMA Length). Rising SMA values indicate strengthening correlation trends, while declining values suggest weakening correlations.
3. Choosing SMA Length: Traders can adjust the SMA Length parameter to tailor the moving average to their specific analysis horizon. Shorter SMA lengths react quickly to price changes but may be more volatile, while longer SMA lengths smooth out noise but respond slower to recent changes.
In summary, the "Symbol Correlation" indicator is a valuable tool for assessing the evolving relationship between a symbol's price and an external source. Its use of SMA and tabular presentation facilitates a nuanced understanding of correlation trends, aiding traders in making informed decisions based on market dynamics.
Previous Candle + Inside/OutsideThe script uses the previous candle of the current timeframe to assess the state of the current candle.
1. Previous candle high/low and midpoint are displayed
2. Highlights current bar if INSIDE previous candle
3. Highlights current bar if POTENTIAL OUTSIDE bar. This condition uses the logic that if the previous high/low has been swept and price then reaches previous bar 50%, then an OUTSIDE bar is possible.
4. If current candle breaks previous high/low, a label is added to identify.
5. If above condition is true and current candle color is opposite of previous, then label is highlighted to show possible bull/bear condition.
6. If current candle live price is below previous midpoint, a BEAR label is shown
7. If current candle live price is above previous midpoint, a BULL label is shown
I personally use the indicator on Daily/Weekly/Monthly charts to help with my overall market assessment. However users may find their own use for the indicator...or modify it to their own preferences.
As ever, the indicator should only be used with live trading accounts after thorough backtesting using a large data range.
London Killzone + Deviations[MK]For traders that use the London Killzone session high/low to project possible take profit targets.
The indicator will determine the current day London killzone high and low range and draw a range box to the right of the last candle on the chart. Drawing to the right of the chart keeps the workspace cleaner.
The high/low range is then used to project Standard Deviation levels above and below the London range.
Levels projected are +/- 1, 2, 2.5, 3, 4.
Users of the script should conduct proper backtesting using a large data range before applying to live accounts.
[Sharpe projection SGM]Dynamic Support and Resistance: Traces adjustable support and resistance lines based on historical prices, signaling new market barriers.
Price Projections and Volatility: Calculates future price projections using moving averages and plots annualized standard deviation-based volatility bands to anticipate price dispersion.
Intuitive Coloring: Colors between support and resistance lines show up or down trends, making it easy to analyze quickly.
Analytics Dashboard: Displays key metrics such as the Sharpe Ratio, which measures average ROI adjusted for asset volatility
Volatility Management for Options Trading: The script helps evaluate strike prices and strategies for options, based on support and resistance levels and projected volatility.
Importance of Diversification: It is necessary to diversify investments to reduce risks and stabilize returns.
Disclaimer on Past Performance: Past performance does not guarantee future results, projections should be supplemented with other analyses.
The script settings can be adjusted according to the specific needs of each user.
The mean and standard deviation are two fundamental statistical concepts often represented in a Gaussian curve, or normal distribution. Here's a quick little lesson on these concepts:
Average
The mean (or arithmetic mean) is the result of the sum of all values in a data set divided by the total number of values. In a data distribution, it represents the center of gravity of the data points.
Standard Deviation
The standard deviation measures the dispersion of the data relative to its mean. A low standard deviation indicates that the data is clustered near the mean, while a high standard deviation shows that it is more spread out.
Gaussian curve
The Gaussian curve or normal distribution is a graphical representation showing the probability of distribution of data. It has the shape of a symmetrical bell centered on the middle. The width of the curve is determined by the standard deviation.
68-95-99.7 rule (rule of thumb): Approximately 68% of the data is within one standard deviation of the mean, 95% is within two standard deviations, and 99.7% is within three standard deviations.
In statistics, understanding the mean and standard deviation allows you to infer a lot about the nature of the data and its trends, and the Gaussian curve provides an intuitive visualization of this information.
In finance, it is crucial to remember that data dispersion can be more random and unpredictable than traditional statistical models like the normal distribution suggest. Financial markets are often affected by unforeseen events or changes in investor behavior, which can result in return distributions with wider standard deviations or non-symmetrical distributions.
Tweet/X Post Timestamp - By LeviathanThis script allows you to generate visual timestamps of X/Twitter posts directly on your chart, highlighting the precise moment an X post/tweet was made. All you have to do is copy and paste the post URL.
◽️ Use Cases:
- News Trading: Traders can use this indicator to visually align market price actions with news or announcements made on X (formerly Twitter), aiding in the analysis of news impact on market volatility.
- Behavioral Analysis: Traders studying the influence of social media on price can use the timestamps to track correlations between specific posts and market reactions.
- Proof of Predictions: Traders can use this indicator to timestamp their market forecasts shared on X (formerly Twitter), providing a visual record of their predictions relative to actual market movements. This feature allows for transparent verification of the timing and accuracy of their analyses
◽️ Process of Timestamp Calculation
The calculation of the timestamp from a tweet ID involves the following steps:
Extracting the Post ID:
The script first parses the input URL provided by the user to extract the unique ID of the tweet or X post. This ID is embedded in the URL and is crucial for determining the exact posting time.
Calculating the Timestamp:
The post ID undergoes a mathematical transformation known as a right shift by 22 bits. This operation aligns the ID's timestamp to a base reference time used by the platform.
Adding Base Offset:
The result from the right shift is then added to a base offset timestamp (1288834974657 ms, the epoch used by Twitter/X). This converts the processed ID into a UNIX timestamp reflecting the exact moment the post was made.
Date-Time Conversion:
The UNIX timestamp is further broken down into conventional date and time components (year, month, day, hour, minute, second) using calculations that account for leap years and varying days per month.
Label Placement:
Based on user settings, labels displaying the timestamp, username, and other optional information such as price changes or pivot points are dynamically placed on the chart at the bar corresponding to the timestamp.
Yield Curve SpaghettiDisplays the difference in yield between multiple bond pairs for a given country.
Currently supports US, DE, and GB bonds
Nadaraya-Watson Probability [Yosiet]The script calculates and displays probability bands around price movements, offering insights into potential market trends.
Setting Up the Script
Window Size: Determines the length of the window for the Nadaraya-Watson estimation. A larger window smooths the data more but might lag current market conditions.
Bandwidth: Controls the bandwidth for the kernel regression, affecting the smoothness of the probability bands.
Reading the Data Table
The script dynamically updates a table positioned at the bottom right of your chart, providing real-time insights into market probabilities. Here's how to interpret the table:
Table Columns: The table is organized into three columns:
Up: Indicates the probability or relative change percentage for the upper band.
Down: Indicates the probability or relative change percentage for the lower band.
Table Rows: There are two main rows of interest:
P%: Shows the price change percentage difference between the bands and the closing price. A positive value in the "Up" column suggests the upper band is above the current close, indicating potential upward momentum. Conversely, a negative value in the "Down" column suggests downward momentum.
R%: Displays the relative inner change percentage difference between the bands, offering a measure of the market's volatility or stability within the bands.
Utilizing the Insights
Market Trends: A widening gap between the "Up" and "Down" percentages in the "P%" row might indicate increasing market volatility. Traders can use this information to adjust their risk management strategies accordingly.
Entry and Exit Points: The "R%" row provides insights into the relative position of the current price within the probability bands. Traders might consider positions closer to the lower band as potential entry points and positions near the upper band as exit points or take-profit levels.
Conclusion
The Nadaraya-Watson Probability script offers a sophisticated tool for traders looking to incorporate statistical analysis into their trading strategy. By understanding and utilizing the data presented in the script's table, traders can gain insights into market trends and volatility, aiding in decision-making processes. Remember, no indicator is foolproof; always consider multiple data sources and analyses when making trading decisions.
Mag7 IndexThis is an indicator index based on cumulative market value of the Magnificent 7 (AAPL, MSFT, NVDA, TSLA, META, AMZN, GOOG). Such an indicator for the famous Mag 7, against which your main security can be benchmarked, was missing from the TradingView user library.
The index bar values are calculated by taking the weighted average of the 7 stocks, relative to their market cap. Explicitly, we are multiplying each bar period's total outstanding stock amount by the OHLC of that period for each stock and dividing that value by the combined sum of outstanding stock for the 7 corporations. OHLC is taken for the extended trading session.
The index dynamically adjusts with respect to the chosen main security and the bars/line visible in the chart window; that is, the first close value is normalized to the main security's first close value. It provides recalculation of the performance in that chart window as you scroll (this isn't apparent in the demo chart above this description).
It can be useful for checking market breadth, or benchmarking price performance of the individual stock components that comprise the Magnificent 7. I prefer comparing the indicator to the Nasdaq Composite Index (IXIC) or S&P500 (SPX), but of course you can make comparisons to any security or commodity.
Settings Input Options:
1) Bar vs. Line - view as OHLC colored bars or line chart. Line chart color based on close above or below the previous period close as green or red line respectively.
2) % vs Regular - the final value for the window period as % return for that window or index value
3) Turn on/off - bottom right tile displaying window-period performance
Inspired by the simpler NQ 7 Index script by @RaenonX but with normalization to main security at start of window and additional settings input options.
Please provide feedback for additional features, e.g., if a regular/extended session option is useful.
US CPIIntroducing "US CPI" Indicator
The "US CPI" indicator, based on the Consumer Price Index (CPI) of the United States, is a valuable tool for analyzing inflation trends in the U.S. economy. This indicator is derived from official data provided by the U.S. Bureau of Labor Statistics (BLS) and is widely recognized as a key measure of inflationary pressures.
What is CPI?
The Consumer Price Index (CPI) is a measure that examines the average change in prices paid by consumers for a basket of goods and services over time. It is an essential economic indicator used to gauge inflationary trends and assess changes in the cost of living.
How is "US CPI" Calculated?
The "US CPI" indicator in this script retrieves CPI data from the Federal Reserve Economic Data (FRED) using the FRED:CPIAUCSL symbol. It calculates the rate of change in CPI over a specified period (typically 12 months) and applies technical analysis tools like moving averages (SMA and EMA) for trend analysis and smoothing.
Why Use "US CPI" Indicator?
1. Inflation Analysis: Monitoring CPI trends provides insights into the rate of inflation, which is crucial for understanding the overall economic health and potential impact on monetary policy.
2. Policy Implications: Changes in CPI influence decisions by policymakers, central banks, and investors regarding interest rates, fiscal policies, and asset allocation.
3. Market Sentiment: CPI data often impacts market sentiment, influencing trading strategies across various asset classes including currencies, bonds, and equities.
Key Features:
1. Customizable Smoothing: The indicator allows users to apply exponential moving average (EMA) smoothing to CPI data for clearer trend identification.
2. Visual Representation: The plotted line visually represents the inflation rate based on CPI data, helping traders and analysts assess inflationary pressures at a glance.
Sources and Data Integrity:
The CPI data used in this indicator is sourced directly from FRED, ensuring reliability and accuracy. The script incorporates robust security protocols to handle data requests and maintain data integrity in a trading environment.
In conclusion, the "US CPI" indicator offers a comprehensive view of inflation dynamics in the U.S. economy, providing traders, economists, and policymakers with valuable insights for informed decision-making and risk management.
Disclaimer: This indicator and accompanying analysis are for informational purposes only and should not be construed as financial advice. Users are encouraged to conduct their own research and consult with professional advisors before making investment decisions.
Evolving RThe "Evolving R" script is a script that allows to calculate a dynamic reward-to-risk ratio at any given point of time during the trade. Its fundamentals are based on Tom Dante's concept of an evolving reward-to-risk. The script requires a user to input their preferred stop loss price and the target price for a specific asset, and calculates the ratio between two differences: (a) the absolute difference between the target price and the current price and (b) the absolute difference between the stop loss price and the current price.
The output of the script displays the ratio discussed as a value called "Evolving R" in the table. In order to use it successfully, the user of the script has to input:
(a) Stop loss price for the asset
(b) Target price for the asset
Theoretically, as long as the evolving R value holds above or equal to 0.25, the trade is worth holding. However, if the evolving R value drops below 0.25, the table turns red and signifies that such a trade possesses more risk than there is a reward remaining: this alerts the user to possibly take profits prematurely without risking their unrealized gains for a minor amount of additional gain.
The graphics of the script are represented by green and red areas: the green area indicates the area between the current price and the target price, while the red area shows the distance between the current price and the stop loss price. This visual representation allows users to understand the relative reward-to-risk ratio graphically in addition to the given evolving R value output.
The script is used for any type of trading: whether trend-trading or in a ranging market, it doesn't suggest a user which market conditions they should use.
