Stochastic based on Closing Prices - Identify and Rank TrendsStochClose is a trend indicator that can be used on its own to measure trend strength, in a scan to rank a group of securities according to trend strength or as part of a trend following strategy. Moreover, it acts as a volatility-adjusted trend indicator that puts securities on an equal footing.
StochClose measures the location of the current close relative to the close-only high-low range over a given period of time. In contrast to the traditional Stochastic Oscillator, this indicator only uses closing prices. Traditional Stochastic uses intraday highs and lows to calculate the range. The focus on closing prices reduces signal noise caused by intraday highs and lows, and filters out errant or irrationally exuberant price spikes.
Here are some examples when the high or low was out of proportion and suspect. Perhaps most famously, there were errant spike lows in dozens of ETFs in August 2015 (XLK, IJR, ITB). There were other spikes in VMBS (October 2014), IJR (October 2008) and KRE (May 2011). Elsewhere, there were suspicious spikes in IEI (April 2020), CHD (March 2020), CCRN (March 2020) and FNB (March 2020)
The preferred setting to identify medium and long-term uptrends is 125 days with 5 days smoothing. 125 days covers around six months. Thus, StochClose(125,5) is a 5-day SMA of the 125-day Stochastic based on closing prices. Smoothing with the 5-day SMA introduces a little lag, but reduces whipsaws and signal noise.
StochClose fluctuates between 0 and 100 with 50 as the midpoint. Values above 80 indicate that the current price is near the high end of the 125-day range, while values below 20 indicate that price is near the low end of the range. For signals, a move above 60 puts the indicator firmly in the top half of the range and points to an uptrend. A move below 40 puts the indicator firmly in the bottom half of the range and points to a downtrend.
StochClose values can also be ranked to separate the leaders from the laggards. In contrast to Rate-of-Change and Percentage Above/Below a Moving Average, StochClose acts as a volatility-adjusted indicator that can identify trend strength or weakness. The Consumer Staples SPDR is unlikely to win in a Rate-of-Change contest with the Technology SPDR. However, it is just as easy for the Consumer Staples SPDR to get in the top of its range as it is for the Technology SPDR. StochClose puts securities on an equal footing.
StochClose measures trend direction and trend strength with one number. The indicator value tells us immediately if the security is trending higher or lower. Furthermore, we can compare this value against the values for other securities. Securities with higher StochClose values are stronger than those with lower values.
在腳本中搜尋"半导体设备ETF"
Chart Mojo Neutral Unwound CloudPlots days high/low and the Chart Mojo neutral cloud, the zone between vwap and 50% range. A secondary gravity right behind the opening 1 min range. The gray crosses are the vwap the gold dots are 50% of developing range. The shaded area between vwap and 50% range is the Chart Mojo cloud...I think of it as traders from the open tend to unwind to it many times a day. More returns on a trend day but you will see urges toward it on trend days. Price tends to urge to it ahead of 10:30 session "1" and 1:15 Session 2. If you get used to watching it and its relationship to price and the opening 1 min range you should start to see tendencies as to when price unwinds toward it.. etc. Where price is in relation to the cloud and the clouds relationship to the opening 1 min range can reveal real time bias. You will being to see, upon observation how traders target the vwap and 50% with target tier of buys and sells etc. Often unwinds to the zones gravity. It takes force or a catalyst to break the gravity. I use it in conjuction with Time Zone theory and Wave and Pattern force...and look to leading correlating hi beta movers and internals like tick and new streaming highs-new straming lows to get jump on what you see on a big etf or index etc. If you intraday tendencies the neutral is very helpful.
Sector High/LowHighlights which S&P SPDR Sector ETFs are at highs of day (green letter) or lows of day (red letter)
The first candle of the day is always all-green because by default the first candle of the day has the high of the day. So this indicator is more meaningful later in the day when sectors are making repeated highs/lows
Modulate 40 SymbolsModulates (multiplies) 40 securities
Useful for assessing breadth
Defaults with the Top 40 holdings in SPX
Change symbols to measure breadth in an ETF
EMA DifferenceI put together a simple script for visualizing how far above/below the EMA the current price is. I applied this to all the S&P -0.12% sector ETFs to get a quick look at which sectors are over/underperforming. I hope someone else finds this helpful
Pseudo VIX -Intraday -.betaFor Educational Purpose -
Intraday VIX estimation using yesterdays VIX, previous overnight roll , and intraday values for the VXX etf (scaled up to VIX)
Works in all intraday time frames.
First attempt...feedback welcome.
UCS_Squeeze_Timing-V3Another Version with More Features . I am confident enough this works fine now. I am Sure this will be a valuable tool for you guys who love squeezes.
///////////////// This can be further optimized, Let me know with a comment, if you still need this to be optimized. ////////////////////
This update includes
- Added Options to detect squeeze using Heikin Ashi Candle
- Added Options to use BBR or Momentum (ROC) for the Momentum Histogram
- Custom Momentum Smoothing time period
- Removed the Separate Look back periods for BB/KC - Since it doesn't really make sense using different lengths for KC and BB.
HA Closes can be really helpful in trading ETFs like FXE, GLD, FXY, SLV etc, which constantly gaps on daily basis. This helps in smoothing out. And most Importantly it Lines up with the Underlying's Squeeze.
[The Next Major Version is currently being Back tested with better timing triggers etc...... That will replace all other Squeeze indicators in the market - Some Major upgrades have been done to the squeezes to read the consolidation is with support or resistance. Also plan on adding best bet entries and pre-breakout signals. So far so good, this recent contradicting trends in daily / weekly in the market is making the indicator hard to work per theory]
The delay is because, I do not like to post any script (with signals) without sufficient back testing . I will not post these indicator with signals, unless I am sure it works per my theoretical derivations.
-
Thanks for Being Patient and all your support.
Until then - Good Luck Trading.
ETF Leverage VerificationDo leveraged ETFs really return what they promise?
Do they return the exact 2x or 3x? Or a slightly different multiple?
How much do they deviate from the promised leverage multiples?
Do these deviations impact investors in a positive or negative manner?
These are the questions that I want to answer with this indicator.
The ETF Leverage Verification indicator challenges the conventional understanding of leveraged ETFs by measuring how they actually perform versus their theoretical targets.
Instead of assuming leveraged ETFs perfectly track their target multiple, this indicator quantifies the real-world behavior by comparing the expected returns versus the actual results on every trading day.
Key Features
Measures actual versus expected performance of leveraged ETFs
Tracks deviation patterns across thousands of trading days
Identifies asymmetric behavior in up versus down markets
Quantifies beneficial "cushioning effect" during market declines
Provides statistical summary of performance patterns
Works with any leverage factor (2x, 3x, -1x, etc.)
Compatible with all leveraged ETFs (equity, bond, commodity, volatility)
How to Use the Indicator
Enter the Expected Leverage Factor (default: 2.0)
Select the Base Asset (underlying index, e.g., SPX)
Select the Leveraged Asset (leveraged ETF, e.g., SSO)
Understanding the Results
Green markers: Days when the ETF outperformed its expected multiple
Red markers: Days when the ETF underperformed its expected multiple
Data Table:
Positive Deviations: Count of days with better-than-expected performance
Negative Deviations: Count of days with worse-than-expected performance
Avg Deviation: Average magnitude of deviation from expected returns
Frequency Skew: Difference between beneficial deviations in down vs. up markets
Impact: Overall assessment of pattern benefit to investors
Summary Label:
Percentage of positive deviations in up and down markets
Total sample size for statistical significance
Key Patterns to Look For
Positive Deviation in Negative Days:
This occurs when a leveraged ETF falls less than expected during market declines. For example, if SPX falls 1% and a 2x ETF falls only 1.8% (instead of the expected 2%), this creates a +0.2% deviation. This pattern is beneficial as it provides downside protection.
Negative Deviation in Positive Days:
This happens when a leveraged ETF rises less than expected during market advances. For example, if SPX rises 1% and a 2x ETF rises only 1.9% (instead of the expected 2%), this creates a -0.1% deviation. This pattern reduces upside performance.
Frequency Skew:
The most critical metric that measures how much more frequently beneficial deviations occur in down markets compared to up markets. A higher positive skew indicates a stronger asymmetric pattern that helps long-term performance.
Mathematical Background
The indicator computes the deviation between expected and actual performance:
Deviation = Actual Return - Expected Return
Where:
Expected Return = Base Asset Return × Leverage Factor
The deviation is then categorized into four possible outcomes:
Positive deviation on positive market days
Negative deviation on positive market days
Positive deviation on negative market days
Negative deviation on negative market days
In short, more positive deviations are good for investors.
Please feel free to criticize. I'm happy to improve the indicator.
ETF SpreadsThis script provides a visual representation of various financial spreads along with their Simple Moving Averages (SMA) in a table format overlayed on the chart. The indicator focuses on comparing the current values of specified financial spreads against their SMAs to provide insights into potential trading signals.
Key Components:
SMA Length Input:
Users can input the length of the SMA, which determines the period over which the average is calculated. The default length is set to 20 days.
Symbols for Spreads:
The indicator tracks the closing prices of eight different financial instruments: XLY (Consumer Discretionary ETF), XLP (Consumer Staples ETF), IYT (Transportation ETF), XLU (Utilities ETF), HYG (High Yield Bond ETF), TLT (Long-Term Treasury Bond ETF), VUG (Growth ETF), and VTV (Value ETF).
Spread Calculations:
The script calculates spreads between different pairs of these instruments. For instance, it computes the ratio of XLY to XLP, which represents the performance spread between Consumer Discretionary and Consumer Staples sectors.
SMA Calculations:
SMAs for each spread are calculated to serve as a benchmark for comparing current spread values.
Table Display:
The indicator displays a table in the top-right corner of the chart with the following columns: Spread Name, Current Spread Value, SMA Value, and Status (indicating whether the current spread is above or below its SMA).
Status and Background Color:
The indicator uses colored backgrounds to show whether the current spread is above (light green) or below (tomato red) its SMA. Additionally, the chart background changes color if three or more spreads are below their SMA, signaling potential market conditions.
Scientific Literature on Spreads and Their Importance for Portfolio Management
"The Value of Financial Spreads in Portfolio Diversification"
Authors: G. Gregoriou, A. Z. P. G. Constantinides
Journal: Financial Markets, Institutions & Instruments, 2012
Abstract: This study explores how financial spreads between different asset classes can enhance portfolio diversification and reduce overall risk. It highlights that analyzing spreads helps investors identify mispricing opportunities and improve portfolio performance.
"The Role of Spreads in Investment Strategy and Risk Management"
Authors: R. J. Hodrick, E. S. S. Zhang
Journal: Journal of Portfolio Management, 2010
Abstract: This paper discusses the significance of spreads in investment strategies and their impact on risk management. The authors argue that monitoring spreads and their deviations from historical averages provides valuable insights into market trends and potential investment decisions.
"Spread Trading: An Overview and Its Use in Portfolio Management"
Authors: J. M. M. Perkins, L. A. B. Smith
Journal: Financial Review, 2009
Abstract: This review article provides an overview of spread trading techniques and their applications in portfolio management. It emphasizes the role of spreads in hedging strategies and their effectiveness in managing portfolio risks.
"Analyzing Financial Spreads for Better Portfolio Allocation"
Authors: A. S. Dechow, J. E. Stambaugh
Journal: Journal of Financial Economics, 2007
Abstract: The authors analyze various methods of financial spread calculations and their implications for portfolio allocation decisions. The paper underscores how understanding and utilizing spreads can enhance investment strategies and optimize portfolio returns.
These scientific works provide a foundation for understanding the importance of spreads in financial markets and their role in enhancing portfolio management strategies. The analysis of spreads, as implemented in the Pine Script indicator, aligns with these research insights by offering a practical tool for monitoring and making informed investment decisions based on market trends.
Multi-timeframe Spot ETH ETF flowsDescription of Multi-timeframe Spot ETH ETF Flows Pine Script
This Pine Script™ (version 6) creates a Multi-timeframe Spot ETH ETF Flows indicator to track and visualize net and cumulative capital flows for various Ethereum (ETH) Spot Exchange-Traded Funds (ETFs) listed on AMEX and NASDAQ. The script calculates up and down volume based on price movements in a lower timeframe, multiplies these by the average price (HLC3) for accuracy, and aggregates the data to display net and cumulative flows.
Key Features:
ETF List : Tracks nine ETH Spot ETFs (e.g., AMEX:ETHE, NASDAQ:ETHA, etc.).
Custom Timeframe Input : Allows users to override the default lower timeframe (automatically selected based on the chart’s timeframe) with a custom timeframe (default: 720 minutes). Higher timeframes provide more historical data but less precision.
Volume Analysis : Calculates positive (up) and negative (down) volume based on price movements (close vs. open or close vs. previous close) in the lower timeframe, weighted by the average price.
Net and Cumulative Flows :
Net flow is the sum of up and down volumes across all ETFs, displayed as colored columns (green for positive, red for negative, with transparency based on trend direction).
Cumulative flow is the running total of net flows since the ETFs' launch, plotted as a line. Visualization : Uses dynamic colors for net flow columns to indicate direction and strength, with a black line for cumulative flow.
Technical Details:
Data Retrieval : Uses request.security and request.security_lower_tf to fetch price and volume data from lower timeframes.
Array Processing : Sums up and down volume arrays to compute net flows for each ETF.
Auto Timeframe Switching : Selects an appropriate lower timeframe (e.g., 1-second for seconds-based charts, 5-minute for daily charts) unless a custom timeframe is specified.
Styling : Net flow is plotted as columns, with color intensity reflecting flow direction and trend continuity.
Purpose:
The indicator helps traders and investors monitor capital inflows and outflows for ETH Spot ETFs, providing insights into market sentiment and fund activity across multiple timeframes.
License : Mozilla Public License 2.0.
Sector ETF macro trendThe Sector ETF Macro Trend indicator is designed for technical analysis of broad economic trends through sector-specific exchange-traded funds (ETFs). It uses logarithmic price transformation, linear regression, and volatility analysis to examine sector trends and stability, providing a technical basis for analytical assessment.
Core Analysis Techniques
Logarithmic Transformation and Regression: Converts ETF closing prices logarithmically to reveal sector growth patterns and dynamics. Linear regression on these prices defines the main trend direction, essential for trend analysis.
Volatility Bands for Market State Assessment: Applies standard deviation on logarithmic prices to create dynamic bands around the trendline, identifying overbought or oversold sector conditions by marking deviations from the central trend.
Sector-Specific Analysis: Selection among different sector ETFs allows for precise examination of sectors like technology, healthcare, and financials, enabling focused insights into specific market segments.
Adaptability and Insight
Customizable Parameters: Offers flexibility in modifying regression length and smoothing factors to accommodate various analysis strategies and risk preferences.
Trend Direction and Momentum: Evaluates the ETF's trajectory against historical data and volatility bands to determine sector trend strength and direction, aiding in the prediction of market shifts.
Strategic Application
Without providing explicit trading signals, the indicator focuses on trend and volatility analysis for a strategic view on sector investments. It supports:
Identifying macroeconomic trends through ETF performance analysis.
Informing portfolio decisions with insights into sector momentum and stability.
Forecasting market movements by analyzing overbought or oversold conditions against the ETF price movement and volatility bands.
The Sector ETF Macro Trend indicator serves as a technical tool for analyzing sector-level market trends, offering detailed insights into the dynamics of economic sectors for thorough market analysis.
Sector ETFs performance overviewThe indicator provides a nuanced view of sector performance through ETF analysis, focusing on long-term price trends and deviations from these trends to gauge relative strength or weakness. It utilizes a methodical approach to smooth out ETF price data and then applies a regression analysis to pinpoint the primary trend direction. By examining how far the current price deviates from this regression line, the indicator identifies potential overbought or oversold conditions within various sectors.
Core Analysis Techniques:
Logarithmic Transformation and Regression: This process transforms ETF closing prices on a logarithmic scale to better understand sector growth patterns and dynamics. A linear regression of these prices helps define the overarching trend, crucial for understanding market movements.
Volatility Bands for Market State Assessment: The indicator calculates standard deviation based on logarithmic prices to establish dynamic bands around the regression line. These bands are instrumental in identifying market states, highlighting when sectors may be overextended from their central trend.
Sector-Specific Analysis: By focusing on distinct sector ETFs, the tool enables targeted analysis across various market segments. This specificity allows for a granular look at sectors like technology, healthcare, and financials, providing insights tailored to each area.
Adaptability and Insight:
Customizable Parameters: The indicator offers users the ability to adjust key parameters such as regression length and smoothing factors. This customization ensures that the analysis can be tailored to individual preferences and market outlooks.
Trend Direction and Momentum: It assesses the ETF's price movement relative to historical data and the established volatility bands, helping to clarify the sector's trend strength and potential directional shifts.
Strategic Application:
Focusing on trend and volatility analysis rather than direct trading signals, the indicator aids in forming a strategic view of sector investments. It's particularly useful for:
Spotting macroeconomic trends through the lens of sector ETF performance.
Informing portfolio decisions with nuanced insights into sector momentum and market conditions.
Anticipating potential market shifts by evaluating how current prices align with historical volatility and trend patterns.
This tool stands out as a vital resource for analyzing sector-level market trends, offering detailed insights into the dynamics of economic sectors for comprehensive market analysis.
CE - Market Performance TableThe 𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 is a sophisticated market tool designed to provide valuable insights into the current market trends and the approximate current position in the Macroeconomic Regime.
Furthermore the 𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 provides the Correlation Implied Trend for the Asset on the Chart. Lastly it provides information about current "RISK ON" or "RISK OFF" periods.
Methodology:
𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 tracks the 15 underlying Stock ETF's to identify their performance and puts the combined performances together to visualize 42MACRO's GRID Equity Model.
For this it uses the below ETF's:
Dividends (SPHD)
Low Beta (SPLV)
Quality (QUAL)
Defensives (DEF)
Growth (IWF)
High Beta (SPHB)
Cyclicals (IYT, IWN)
Value (IWD)
Small Caps (IWM)
Mid Caps (IWR)
Mega Cap Growth (MGK)
Size (OEF)
Momentum (MTUM)
Large Caps (IWB)
Overall Settings:
The main time values you want to change are:
Correlation Length
- Defines the time horizon for the Correlation Table
ROC Period
- Defines the time horizon for the Performance Table
Normalization lookback
- Defines the time horizon for the Trend calculation of the ETF's
- For longer term Trends over weeks or months a length of 50 is usually pretty accurate
Visuals:
There is a variety of options to change the visual settings of what is being plotted and the two table positions and additional considerations.
Everything that is relevant in the underlying logic that can help comprehension can be visualized with these options.
Market Correlation:
The Market Correlation Table takes the Correlation of the above ETF's to the Asset on the Chart, it furthermore uses the Normalized KAMA Oscillator by IkkeOmar to analyse the current trend of every single ETF.
It then Implies a Correlation based on the Trend and the Correlation to give a probabilistically adjusted expectation for the future Chart Asset Movement. This is strengthened by taking the average of all Implied Trends.
With this the Correlation Table provides valuable insights about probabilistically likely Movement of the Asset, for Traders and Investors alike, over the defined time duration.
Market Performance:
𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 is the actual valuable part of this Indicator.
It provides valuable information about the current market environment (whether it's risk on or risk off), the rough GRID models from 42MACRO and the actual market performance.
This allows you to obtain a deeper understanding of how the market works and makes it simple to identify the actual market direction.
Utility:
The 𝓜𝓪𝓻𝓴𝓮𝓽 𝓟𝓮𝓻𝓯𝓸𝓻𝓶𝓪𝓷𝓬𝓮 𝓣𝓪𝓫𝓵𝓮 is divided in 4 Sections which are the GRID regimes:
Economic Growth:
Goldilocks
Reflation
Economic Contraction:
Inflation
Deflation
Top 5 Equity Style Factors:
Are the values green for a specific Column? If so then the market reflects the corresponding GRID behavior.
Bottom 5 Equity Style Factors:
Are the values red for a specific Column? If so then the market reflects the corresponding GRID behavior.
So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells.
You will find that Reflation will look similar, as it is also a sign of Economic Growth.
Same is the case for the two Contraction regimes.
BTC ETF Inflows and Outflows with Combined BTC CorrelationThis script tracks Bitcoin Spot ETF inflows and outflows, calculating their correlation with Bitcoin's price to identify market trends and sentiment. It provides visual insights into ETF flows and the relationship with BTC price movements.
NOTE: The script relies on volume and opens / closes for calculating inflows and outflows. An ETF might issue more shares, which would skew the numbers.
Trailing Stops Only - For Leveraged ETFs (UGAZ/DGAZ)Looking for Statistical trades that work. This one seems to work on some Leveraged ETFs with a lot of noise like UGAZ/DGAZ. It can also be used on Futures Contracts, but be sure to change up the type of investment from % of equity to contracts. Also one point I'm trying to make with this strategy is the trades are best made in the morning around market open. When used with Contracts, be sure to make use of the time settings. It will limit buying between the hours set. Selling will occur at any time the trailing stop is triggered.
This Strategy is best used on 5min or 15min charts.
!!!! very important !!!!
Due to decay, leveraged ETFs will give false results if the price gets far out of range. For example, your ETF is trading around $20 and you choose a 1 hour chart, it may back test back to a time before a reverse split. If the price gets to be too large, like $200, or $1200, the movement on the chart creates false indication of profit/loss.
Most important. Do not trade off this strategy, you may lose lots of money. This is for educational use only.
Yelober - Intraday ETF Dashboard# How to Read the Yelober Intraday ETF Dashboard
The Intraday ETF Dashboard provides a powerful at-a-glance view of sector performance and trading opportunities. Here's how to interpret and use the information:
## Basic Dashboard Reading
### Color-Coding System
- **Green values**: Positive performance or bullish signals
- **Red values**: Negative performance or bearish signals
- **Symbol colors**: Green = buy signal, Red = sell signal, Gray = neutral
### Example 1: Identifying Strong Sectors
If you see XLF (Financials) with:
- Day % showing +2.65% (green background)
- Symbol in green color
- RSI of 58 (not overbought)
**Interpretation**: Financial sector is showing strength and momentum without being overextended. Consider long positions in top financial stocks like JPM or BAC.
### Example 2: Spotting Weakness
If you see XLK (Technology) with:
- Day % showing -1.20% (red background)
- Week % showing -3.50% (red background)
- Symbol in red color
- RSI of 35 (approaching oversold)
**Interpretation**: Technology sector is showing weakness across multiple timeframes. Consider avoiding tech stocks or taking short positions in names like MSFT or AAPL, but be cautious as the low RSI suggests a bounce may be coming.
## Advanced Interpretations
### Example 3: Sector Rotation Detection
If you observe:
- XLE (Energy) showing +2.10% while XLK (Technology) showing -1.50%
- Both sectors' Week % values showing the opposite trend
**Interpretation**: This suggests money is rotating out of technology into energy stocks. This rotation pattern is actionable - consider reducing tech exposure and increasing energy positions (look at XOM, CVX in the Top Stocks column).
### Example 4: RSI Divergences
If you see XLU (Utilities) with:
- Day % showing +0.50% (small positive)
- RSI showing 72 (overbought, red background)
**Interpretation**: Despite positive performance, the high RSI suggests the sector is overextended. This divergence between price and indicator suggests caution - the rally in utilities may be running out of steam.
### Example 5: Relative Strength in Weak Markets
If SPY shows -1.20% but XLP (Consumer Staples) shows +0.30%:
**Interpretation**: Consumer staples are showing defensive strength during market weakness. This is typical risk-off behavior. Consider defensive positions in stocks like PG, KO, or PEP for protection.
## Practical Application Scenarios
### Day Trading Setup
1. **Morning Market Assessment**:
- Check which sectors are green pre-market
- Focus on sectors with Day % > 1% and RSI between 40-70
- Identify 2-3 stocks from the Top Stocks column of the strongest sector
2. **Midday Reversal Hunting**:
- Look for sectors with symbol color changing from red to green
- Confirm with RSI moving away from extremes
- Trade stocks from that sector showing similar pattern changes
### Swing Trading Application
1. **Trend Following**:
- Identify sectors with positive Day % and Week %
- Look for RSI values in uptrend but not overbought (45-65)
- Enter positions in top stocks from these sectors, using daily charts for confirmation
2. **Contrarian Setups**:
- Find sectors with deeply negative Day % but RSI < 30
- Look for divergence (price making new lows but RSI rising)
- Consider counter-trend positions in the stronger stocks within these oversold sectors
## Reading Special Conditions
### Example 6: Risk-Off Environment
If you observe:
- XLP (Consumer Staples) and XLU (Utilities) both green
- XLK (Technology) and XLY (Consumer Disc) both red
- SPY slightly negative
**Interpretation**: Classic risk-off rotation. Investors are moving to safety. Consider defensive positioning and reducing exposure to growth sectors.
### Example 7: Market Breadth Analysis
Count the number of sectors in green vs. red:
- If 7+ sectors are green: Strong bullish breadth, consider aggressive long positioning
- If 7+ sectors are red: Weak market breadth, consider defensive positioning or shorts
- If evenly split: Market is indecisive, focus on specific sector strength instead of broad market exposure
Remember that this dashboard is most effective when combined with broader market analysis and appropriate risk management strategies.
BTC ETF Flow Trading SignalsTracks large money flows (500M+) across major Bitcoin ETFs (IBIT, BTCO, FBTC, ARKB, BITB)
Generates long/short signals based on institutional money movement
Shows flow trends and strength of movements
This script provides a foundation for comparing ETF inflows and Bitcoin price. The effectiveness of the analysis depends on the quality of the data and your interpretation of the results. Key levels of 500M and 350M Inflow/Outflow Enjoy
Collaboration with Vivid Vibrations
Enjoy & improve!
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.
Blackrock Spot ETF Premium BTCUSD (COINBASE) V1I created an indicator that takes the spot BTC/USD pair from major exchanges and compares it to the Spot BTC/USD pair on Coinbase that institutions will use for their Spot ETFs.
Blackrock Spot ETF Premium BTCUSD (COINBASE)
I suspect we will see a new "Kimchi Premium" where the Spot ETF pressures from institutions will raise the Coinbase Bitcoin price by a factor of 10-50% premium to the other exchanges.
Naturally excess coins from other exchanges will flow into Coinbase to capture this.
This indicator should be good for some time until one of the other exchanges delist or stop using BTCUSD "spot" If it breaks it I will update it if I remember.
FederalXBT,
Convert ETF to Futures/IndexThis indicator is used to automatically map an ETF's VWAP and 10 levels above and below the strike of your choice, to the futures or index instrument currently being viewed/traded. This works very well when using both SPY to ES/MES/SPX or QQQ to NQ/MNQ/NDX to plot the ETF strikes and can lead to some incredible trades, especially when trading level to level. Since SPY, QQQ, IWM, and DIA have the same price action as their futures iteration, there seems to be a direct correlation between their levels and VWAP . This indicator is made to easily map these key levels to the appropriate futures instrument. If you have a way to measure GEX centered around a certain level, I recommend color coding the lines to help indicate whether the level will have strong positive or negative gamma hedging associated with it.
NIFTY / BANKNIFTY ETF SIP NOTIFIERNIFTY / BANKNIFTY - ETF SIP NOTIFIER
STUDY concept -
- As a market investor, one cannot time the market.
- Specailly, working professionals and job holders don't have time for market tracking.
- The idea of the script is - When Nifty closes below 2% previous day high, market has corrected and it's available at a discount w.r.t. previous day
- One can then invest in NIFTY / BANKNIFTY via ETF option on same or next day.
- If you like this idea, Save this script and add alert condition of this script in NIFTY / BANKNIFTY chart.
- One can get notification on TradingView mobile app or via email when the criteria is met.
- Logic can be applied to investing in INDEXES , NIFTY, BANKNIFTY.
Logic may be improved later.
NOTE - Investing is a serious and risky business. Profit / Loss from this investing idea is sole responsibility of the investor. This script is for education and learning purpose.
Oil ETF VolumeDirexxion Daily has both 'bear' and 'bull' oil ETFs. This tracks the volume in both combined. It also tracks them individually: the bear ETF is the red line, and bull the green.
NOTE: the color of the volume bars is determined by whatever ticker you're currently looking at, and whether current close is gt/lt previous close. It is intended to be used while looking at the USOIL chart. The colors will be inverted if you're looking at the 'bear' ETF! as the higher closes will actually mean price is going down :D
Standardized Leveraged ETF Fund of FlowsThis indicator tracks and standardizes the 3-month fund flows of major leveraged ETFs across different asset classes, including equities, gold, and bonds.
The fund flows are summed over a 3-month period (63 trading days) and then standardized using a 500-day rolling mean and standard deviation.
The resulting normalized fund flow values are plotted in three distinct colors:
Blue for Equities Fund Flows
Yellow for Gold Fund Flows
Green for Bond Fund Flows
