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.
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[Comparative CPI SGM]Code Explanation
User Inputs:
len: Defines the period over which CPI changes are calculated, with selectable options of 12, 6, and 3 months.
CP1 and CP2: These are the economic zones whose CPI data are being compared. The options include CPI from various regions like the EU, USA, UK, etc.
Calculating and Comparing Changes:
Calculates the annual change for each CPI and then computes the difference between these two changes.
Trading Utility
In trading, CPI variations are key indicators of inflation within different economic regions. Monetary policy decisions by central banks, heavily influenced by these data, significantly impact financial markets, especially in forex and bond markets.
Monetary Policy Forecasting:
If inflation in one region is significantly higher than in another, the central bank might raise interest rates, potentially strengthening that region's currency.
Currency Trading Strategy:
Traders might use this indicator to speculate on currency pair movements. For example, if US CPI is rising faster than the EU CPI, this might suggest a potential appreciation of the USD against the EUR.
Macroeconomic Analysis:
Understanding where inflation pressures are strongest can guide longer-term investment decisions, such as choosing between emerging and developed markets.
[BT] NedDavis Series: CPI Minus 5-Year Moving Average🟧 GENERAL
The script works on the Monthly Timeframe and has 2 main settings (explained in FEATURES ). It uses the US CPI data, reported by the Bureau of Labour Statistics.
🔹Functionality 1: The main idea is to plot the distance between the CPI line and the 5 year moving average of the CPI line. This technique in mathematics is called "deviation from the moving average". This technique is used to analyse how has CPI previously acted and can give clues at what it might do in the future. Economic historians use such analysis, together with specific period analysis to predict potential risks in the future (see an example of such analysis in HOW TO USE section. The mathematical technique is a simple subtraction between 2 points (CPI - 5yr SMA of CPI).
▶︎Interpretation for deviation from a moving average:
Positive Deviation: When the line is above its moving average, it indicates that the current value is higher than the average, suggesting potential strength or bullish sentiment.
Negative Deviation: Conversely, when the line falls below its moving average, it suggests weakness or bearish sentiment as the current value is lower than the average.
▶︎Applications:
Trend Identification: Deviations from moving averages can help identify trends, with sustained deviations indicating strong trends.
Reversal Signals: Significant deviations from moving averages may signal potential trend reversals, especially when combined with other technical indicators.
Volatility Measurement: Monitoring the magnitude of deviations can provide insights into market volatility and price movements.
Remember the indicator is applying this only for the US CPI - not the ticker you apply the indicator on!
🔹Functionality 2: It plots on a new pane below information about the Consumer Price Index. You can also find the information by plotting the ticker symbol USACPIALLMINMEI on TradingView, which is a Monthly economic data by the OECD for the CPI in the US. The only addition you would get from the indicator is the plot of the 5 year Simple Moving Average.
🔹What is the US Consumer Price Index?
Measures the change in the price of goods and services purchased by consumers;
Traders care about the CPI because consumer prices account for a majority of overall inflation. Inflation is important to currency valuation because rising prices lead the central bank to raise interest rates out of respect for their inflation containment mandate;
It is measured as the average price of various goods and services are sampled and then compared to the previous sampling.
Source: Bureau of Labor Statistics;
FEATURES OF INDICATOR
1) The US Consumer Price Index Minus the Five Year Moving Average of the same.
As shown on the picture above and explained in previous section. Here a more detailed view.
2) The actual US Consumer Price Index (Annual Rate of change) and the Five year average of the US Consumer Price Index. Explained above and shown below:
To activate 2) go into settings and toggle the check box.
HOW TO USE
It can be used for a fundamental analysis on the relationship between the stock market, the economy and the Feds decisions to hike or cut rates, whose main mandate is to control inflation over time.
I have created this indicator to show my analysis in this idea:
What does a First Fed Rate cut really mean?
CREDITS
I have seen such idea in the past posted by the institutional grade research of NedDavis and have recreated it for the TradingView platform, open-source for the community.
HTF Matrix TableThis is a Higher Time Frame Table like the Intra-Day Table that I also have available.
ICT stresses time and liquidity levels in his teachings. This table helps to easily locate these key Time-based price levels. You can use these levels to determine your directional bias and to help generate your narrative for where the market is going.
This indicator creates a table that gives you the price for the following liquidity levels:
*Price* - Current Price
PMH - Previous Month High
PMO - Previous Month Open
PM MT - Previous Month Mean Threshold (Midpoint of candle body)
(Calculated by:
if pmo > pmc
pm_mt := ((pmo-pmc)/2)+pmc
if pmo < pmc
pm_mt := ((pmc-pmo)/2)+pmo)
PMC - Previous Month Close
PML - Previous Month Low
PWH - Previous Week High
PWO - Previous Week Open
PW MT - Previous Week Mean Threshold (Midpoint of candle body)
Calculated by:
if pwo > pwc
pw_mt := ((pwo-pwc)/2)+pwc
if pwo < pwc
pw_mt := ((pwc-pwo)/2)+pwo)
PWC - Previous Week Close
PWL - Previous Week Low
PDO - Previous Day Open
PDH - Previous Day High
PDL - Previous Day Low
PDC - Previous Day Close
PDEQ - Equilibrium of the previous day's range.
(Calculated by math.abs(((pdh-pdl)/2)+pdl))
PDH2 - Two Days Back High
PDL2 - Two Days Back Low
PDH3 - Three Days Back High
PDL3 - Three Days Back Low
Gives you the opening price for the following times:
Midnight Open
NY Open
Lets you set the time for the Asia and London sessions and will give the high and low for those two sessions.
Asia High
Asia Low
London High
London Low
Ability to hide either the table or lines.
The levels are sorted descending in price in the table, with the background colored based on their relation to price. The prices are also plotted on the chart based on the range you specify in relation to the current price. These lines are also colored based on their relation to price.
This indicator does not give you anything but the price at a specific time, you must determine your own bias and narrative based on the levels that are given.
The indicator runs on the seconds chart.
Smart Money Liquidity Heatmap [AlgoAlpha]🌟📈 Introducing the Smart Money Liquidity Heatmap by AlgoAlpha! 🗺️🚀
Dive into the depths of market liquidity with our innovative Pine Script™ indicator designed to illuminate the trading actions of smart money! This meticulously crafted tool provides an enhanced visualization of liquidity flow, highlighting the dynamics between smart and retail investors directly on your chart! 🌐🔍
🙌 Key Features of the Smart Money Liquidity Heatmap:
🖼️ Visual Clarity: Uses vibrant heatmap colors to represent liquidity concentrations, making it easier to spot significant trading zones.
🔧 Customizable Settings: Adjust index periods, volume flow periods, and more to tailor the heatmap to your trading strategy.
📊 Dynamic Ratios: Computes the ratio of smart money to retail trading activity, providing insights into who is driving market movements.
👓 Transparency Options: Modify color intensity for better visibility against various chart backgrounds.
🛠 How to Use the Smart Money Liquidity Heatmap:
1️⃣ Add the Indicator:
Add the indicator to favourites. Customize settings to align with your trading preferences, including periods for index calculation and volume flow.
2️⃣ Market Analysis:
Monitor the heatmap for high liquidity zones signalled by the heatmap. These are potential areas where smart money is actively engaging, providing crucial insights into market dynamics.
Basic Logic Behind the Indicator:
The Smart Money Liquidity Heatmap utilizes the Smart Money Interest Index Indicator and operates by differentiating between the trading behaviors of informed (smart money) and less-informed (retail) traders. It calculates the differences between specific volume indices—Positive Volume Index (PVI) for retail investors and Negative Volume Index (NVI) for institutional players—and their respective moving averages, highlighting these differences using the Relative Strength Index (RSI) over user-specified periods. This calculation generates a ratio that is then normalized and compared against a threshold to identify areas of high institutional trading interest, visually representing these zones on your chart as vibrant heatmaps. This enables traders to visually identify where significant trading activities among smart money are occurring, potentially signalling important buying or selling opportunities.
🎉 Elevate your trading experience with precision, insight, and clarity by integrating the Smart Money Liquidity Heatmap into your toolkit today!
[Global Contraction Expansion Index SGM]Script Features
Dynamic Period Choice: The user can adjust the calculation period (period) for relative performance, allowing flexibility according to specific market analysis needs.
Sector Selection: The script takes into account different economic sectors through well-known ETFs like QQQ (technology), XLF (financial), XLY (consumer discretionary), XLV (healthcare), XLI (industrial) and XLE (energy). This diversification helps gain a general overview of economic health across different market segments.
Relative Performance Calculation: For each sector, the script calculates the relative performance using a simple moving average (SMA) of the price change over the specified period. This helps identify price trends adjusted for normal market fluctuations.
GCEI Index: The GCEI Index is calculated as the average of the relative performance of all sectors, multiplied by 100 to express it as a percentage. This provides an overall indicator of sectoral economic performance.
Crossover Signals: The script detects and marks points where the overall index (GCEI) crosses its own exponential moving average (emaGCEI), indicating potential changes in the overall trend of market performance.
Visualization: Results are visualized through graphs, where positive and negative regions are colored differently. Fills between the zero line and the index curves make it easy to see periods of contraction or expansion
When this index diverges from the SP500, it may be a sign that the technology sector is outperforming other sectors.
[Forex Fondamental Overview SGM]Fundamental analysis tool designed for currency trading in financial markets. The script generates a dashboard that displays key economic indicators for two selected currencies. Here is what makes this script particularly interesting for a trader:
1. Direct comparison between two currencies: The script allows you to choose two currencies (from a predefined list) and directly compare their key economic indicators such as interest rate, GDP growth, debt-to-GDP ratio, unemployment rate, inflation (CPI and PPI), and the services and manufacturing PMI indices. This gives you immediate insight into the economic strengths and weaknesses of each currency, which is crucial for making informed trading decisions.
2. Automatic data updating: Indicator values are updated automatically using security requests (request.security) that pull the most recent data available. This means you don't need to manually update data or check multiple sources; the script takes care of that for you.
3. Currency Relative Strength Calculation: The script calculates a strength index for each currency based on its economic indicators, and then it determines a relative strength index for the currency pair. This allows you to quickly see which currency is currently strongest, providing a basis for "buy strength, sell weakness" trading strategies.
4. Intuitive visualization: Results are presented in clear tables with colored indicators, making the information quickly digestible. For example, the background color changes depending on the relative strength of the currency pair, giving you an immediate visual signal of the overall trend.
5. Adaptability to different trading strategies: Whether you are a swing trader, a day trader, or a scalper, understanding the economic state of currencies can help you align your trading positions with underlying macroeconomic trends. This script gives you this information without requiring detailed economic analysis on your part.
In short, this script is a powerful tool for any Forex trader who wants to integrate fundamental analysis into their trading routine without bothering with the complexity of tracking and analyzing a multitude of economic indicators manually.
PPN - Token compare to USDT/BTCThis simple indicator allows you to easily view the price of a selected cryptocurrency token in either USDT or BTC on TradingView charts. By adding this indicator to your chart, you can quickly compare the price of the token to either USDT (Tether) or BTC (Bitcoin).
**Features:**
- Choose between displaying the token price in USDT or BTC.
- Automatically detects the current trading pair and adjusts the display accordingly.
- Uses data from the BINANCE exchange to fetch real-time prices.
**How to Use:**
1. Add the indicator to your TradingView chart.
2. Select the desired ticker ending (USDT or BTC) in the indicator settings.
3. Pin the indicator to a new scale (More -> Pin to Scale -> New scale or no scale (fullscreen).
**Note:** This indicator is intended for informational purposes only and should not be used as the sole basis for making trading decisions. Always conduct your own research and consult with a financial advisor before making any investment decisions.
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Feel free to use and modify! <3
Message me on TradingView if you have any suggestions!
[SGM Forex Interest Rate]
Through an analysis of the interest rates of selected currencies, this indicator calculates the difference between these rates to provide an indication of the relative strength between the two currencies. This relative strength is graphically represented as an area with a specific color for better visualization.
The curves represent the values of the two selected currencies, while the colored area between them highlights the difference in strength. A horizontal line is also drawn at the zero level to help identify turning points or divergence points.
Interest rates play a crucial role in forex trading for several reasons:
Impact on capital flows: Interest rates affect international capital flows. Investors are attracted to currencies offering higher yields, which can lead to currency appreciation with higher interest rates.
Influence on monetary policy decisions: Central banks often adjust interest rates to achieve macroeconomic goals such as price stability, economic growth, and full employment. Announcements of interest rate changes or hints about the future direction of rates can have a significant impact on the foreign exchange market.
Determination of financing costs: Interest rates affect the financing costs of transactions in the foreign exchange market. Traders often borrow low-interest currencies to purchase higher-yielding currencies, which can lead to large movements in the market.
Economic Indicators: Interest rates are also key economic indicators. Changes in interest rates may reflect overall economic conditions and be interpreted as signs of economic growth or contraction.
Risk and volatility factors: Interest rate differences between two countries can create arbitrage opportunities, but also risks. Unexpected changes in interest rates or market expectations may result in increased volatility in the foreign exchange market.
In sum, interest rates are a fundamental part of the global financial landscape and are therefore crucial for forex traders, as they provide indications of economic trends, capital flows and trading opportunities.
Financials ScoreThe Pine Script you've provided is designed to compute and display a "Financials Score" for a security based on several key financial metrics. This script is structured to run as an independent indicator on the TradingView platform, appearing in a separate pane rather than overlaying on the main price chart. Here's a breakdown of the script's components and functionality:
User Inputs
- **Period Selection**: Users can choose between 'FQ' (Financial Quarter) and 'FY' (Financial Year) to specify the period for which financial data should be considered.
- **Display Settings**: Allows customization of the table's appearance with inputs for text size, text color, data text color, and panel background color. These inputs help tailor the visual representation to the user's preferences.
- **Table Position**: Users can choose where to position any table within the indicator pane from several options like top left, top center, top right, etc.
- **Show Status Column**: A boolean input to decide whether to show an additional status column in any table outputs.
### Financial Metrics
The script retrieves various financial data points using the `request.financial` function. The data retrieved includes:
- **Operating Margin** (`opmar`)
- **Earnings Per Share (Basic)** (`eps`)
- **Price to Earnings Ratio** (`pe_ratio`)
- **Price to Book Ratio** (`pb_ratio`)
- **Debt to Equity Ratio** (`de_ratio`)
- **Return on Equity Adjusted to Book Value** (`roe_pb`)
- **Piotroski F-Score** (`fscore`)
### Scoring Logic
A scoring system is implemented where each financial metric contributes points to a total score based on specified conditions:
- **Operating Margin**: +20 points if greater than 20%.
- **EPS**: +20 points if greater than 0.
- **P/E Ratio**: +10 points if between 0 and 20.
- **P/B Ratio**: +10 points if less than 3.
- **D/E Ratio**: +10 points if less than 0.8.
- **ROE/PB Ratio**: +20 points if greater than 5.
- **F-Score**: +10 points if greater than 5.
The script uses ternary operators to conditionally add points to the `total_score` variable based on these criteria.
### Output
- **`plot` function**: The total score is plotted as a line graph in the indicator pane, allowing users to visually track the financial health score over time.
### Overall Functionality
This script is valuable for investors or traders who want to quickly assess the financial health of a company using key metrics and visualize this assessment directly within the TradingView interface. The score provides a simplified aggregate view that can aid in making investment decisions based on financial fundamentals.
Yield Curve SpaghettiDisplays the difference in yield between multiple bond pairs for a given country.
Currently supports US, DE, and GB bonds
Smart Money Interest Index [AlgoAlpha]🌟 Smart Money Interest Index by AlgoAlpha 🌟
Welcome to the innovative Smart Money Interest Index indicator, designed meticulously by AlgoAlpha to revolutionize the way you trade! 📈🧠 This indicator is engineered to decipher the activities of smart money investors relative to the less informed (dumb money) and dynamically display their dominance in the trading landscape through a sophisticated visual index. 🚀💹
🔑 Key Features:
- Smart vs. Dumb Money Analysis: Tracks and compares the movements of smart money (informed investors) and dumb money (general public) within the market to identify potential investment signals.
- Relative Strength Index (RSI) Based Ratios: Utilizes RSI for both smart and dumb money to create a ratio that indicates buying or selling pressures.
- Dynamic Normalization: Employs a long-term peak normalization over a customizable period to ensure the index remains relevant regardless of market conditions.
- Visual Thresholds and Signals: Highlights significant shifts in market dynamics with color-coded thresholds, making it easier to spot changes at a glance.
🛠 How to Use the Smart Money Interest Index:
🔹 🚀 Step 1: Adding the Indicator
- Add the indicator to your favourites.
- Customize the settings according to your analysis needs:
- `Index Period`, `Volume Flow Period`, `Normalization Period`, `High Interest Threshold`
🔹 📊 Step 2: Interpretation of the Index
- Monitor the index plot; a rising index suggests increasing smart money interest, potentially indicating a buying opportunity.
- A value above the high interest threshold (in yellow) highlights significant interest by smart money, suggesting a good time to buy.
🔹 🔔 Step 3: Setting Alerts
- Configure alerts to notify you when the index crosses above the set threshold, enabling you to capitalize on trading opportunities timely and efficiently.
📐 Basic Logic Overview:
The Smart Money Interest Index by AlgoAlpha provides a unique metric that contrasts the investment behaviors of informed (smart money) and general (dumb money) investors. Utilizing the Relative Strength Index (RSI), this indicator evaluates the trading pressure exerted by both groups over specified periods, then forms a ratio of these activities to identify dominance in buying or selling trends. For example, when we see dumb money selling and smart buying, this suggests that the conditions for buying the asset is optimal as smart money is willing to buy the dip. The outputs are normalized against the highest values observed in a user-defined term to maintain consistency through varying market conditions. When the index exceeds a certain threshold, it suggests that smart money presence is particularly strong, possibly indicating that smart money is looking to enter positions on the asset. This tool serves as a sophisticated visual guide to understanding market dynamics and making well-informed trading decisions based on the activities of market-savvy investors. Smart money activity is identified during areas of low volume and the opposite for dumb money, the indicator uses the NVI and PVI metrics as its foundation for smart and dumb money analysis.
📊 Enhance Your Trading Strategy:
Leverage the Smart Money Interest Index to gain deeper insights into market dynamics and enhance your decision-making process with a powerful, data-driven approach. Whether you're looking to identify entry points or set strategic exits, this tool is designed to provide you with the competitive edge you need in the fast-paced world of trading. 🌐✨
Transform your trading with the power of smart money analysis—start using the Smart Money Interest Index today! 🚀🔔
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.
Index Generator [By MUQWISHI]▋ INTRODUCTION :
The “Index Generator” simplifies the process of building a custom market index, allowing investors to enter a list of preferred holdings from global securities. It aims to serve as an approach for tracking performance, conducting research, and analyzing specific aspects of the global market. The output will include an index value, a table of holdings, and chart plotting, providing a deeper understanding of historical movement.
_______________________
▋ OVERVIEW:
The image can be taken as an example of building a custom index. I created this index and named it “My Oil & Gas Index”. The index comprises several global energy companies. Essentially, the indicator weights each company by collecting the number of shares and then computes the market capitalization before sorting them as seen in the table.
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▋ OUTPUTS:
The output can be divided into 3 sections:
1. Index Title (Name & Value).
2. Index Holdings.
3. Index Chart.
1. Index Title , displays the index name at the top, and at the bottom, it shows the index value, along with the daily change in points and percentage.
2. Index Holdings , displays list the holding securities inside a table that contains the ticker, price, daily change %, market cap, and weight %. Additionally, a tooltip appears when the user passes the cursor over a ticker's cell, showing brief information about the company, such as the company's name, exchange market, country, sector, and industry.
3. Index Chart , display a plot of the historical movement of the index in the form of a bar, candle, or line chart.
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▋ INDICATOR SETTINGS:
(1) Naming the index.
(2) Entering a currency. To unite all securities in one currency.
(3) Table location on the chart.
(4) Table’s cells size.
(5) Table’s colors.
(6) Sorting table. By securities’ (Market Cap, Change%, Price, or Ticker Alphabetical) order.
(7) Plotting formation (Candle, Bar, or Line)
(8) To show/hide any indicator’s components.
(9) There are 34 fields where user can fill them with symbols.
Please let me know if you have any questions.
ITG Scalper with Early SignalsThe TEMA-MACD Fusion Indicator combines the Triple Exponential Moving Average (TEMA) and Moving Average Convergence Divergence (MACD) to provide traders with a comprehensive insight into market momentum and trend direction.
TEMA is a powerful smoothing indicator that reduces lag and provides a clearer representation of price trends. By applying TEMA to MACD, this fusion indicator enhances the traditional MACD signals, offering more accurate and timely indications of trend changes and potential entry/exit points.
Key Features:
TEMA: The Triple Exponential Moving Average offers a unique perspective on price movements by providing a triple-smoothed average. It adapts more swiftly to changes in price compared to traditional moving averages, making it well-suited for capturing short to medium-term trends.
MACD: The Moving Average Convergence Divergence is a versatile momentum oscillator that depicts the relationship between two moving averages of an asset's price. It is widely used to identify trend direction, momentum strength, and potential reversal points.
Enhanced Signals: By integrating TEMA with MACD, this indicator generates enhanced signals that filter out noise and provide a clearer picture of market dynamics. It helps traders to identify trend reversals, confirm trend strength, and pinpoint potential entry and exit points with greater precision.
Customizable Parameters: Traders can customize the indicator's parameters according to their trading style and preferences, allowing for flexibility in signal generation and adaptability to various market conditions.
User-Friendly Interface: The indicator is designed with a user-friendly interface, making it accessible to traders of all levels of experience. Clear visual representations of signals and trend dynamics facilitate easy interpretation and decision-making.
Multi-Timeframe Compatibility: The TEMA-MACD Fusion Indicator is compatible with multiple timeframes, enabling traders to analyze trends and signals across different time horizons, from intraday to long-term perspectives.
Incorporate the TEMA-MACD Fusion Indicator into your trading strategy to gain deeper insights into market trends and make informed trading decisions with greater confidence.
True stock performance based on EY Bar divergenceI created this indicator to be used in conjunction with my other indicator "True stock performance based on Earnings Yield". I've detailed in that description how true performance is calculated. In short it measures how much EY is moving in relation to the stock price. The theory is that if stock price is moving heavily while EY isn't you have a sentiment driven trend and the stock isn't traded on fundamentals.
This indicators marks bars when stock performance divergences from true performance.
Green upward triangle = The true performance closes lower than previous while stock price is closing higher. This indicates a optimistic sentiment as stock price is pushed up even though price based on EY is moving down.
Red downward triangle = The true performance closes higher than previous while stock price closing lower. This indicates a negative sentiment as stock price is pushed down even though price based on EY is moving up.
How do I use it?
I use it to confirm when sentiment has taken taken over a stock. If you have a fair uptrend (when both stock performance and true performance are doing higher highs), optimistic divergencies are welcome. I've used NVIDIA from 2017 to 2019 to demonstrate.
But if true performance starts to make lower highs while stock performance keeps going up and you see optimistic divergencies, you can tell that the market is getting overoptimistic.
When the stock had crashed it eventually bottomed and started to make higher lows together with an uptrend of true performance, which I count as a fair uptrend. Regardless of that you start to see some negative divergencies indicating that people are scared that the stock will drop again and oversell. These opportunities can be good places to buy more.
But i don't care about earnings, I'm a technical trader. Do i have any use for it?
You possibly could, yes. If you want to follow the crowd, optimistic divergencies confirms that the market is still interested in the stock and may keep pushing the price up. But be careful. Negative divergencies almost never marks any tops, it often confirms downtrends and may indicate bottoms. Often the optimistic divergencies marks the top so don't buy more blindly using this indicator.
True stock performance based on Earnings YieldThe whole basis of the stock market is that you invest your money into a business that can use that money to increase it's earnings and pay you back for that investment with dividends and increased stock value. But because we are human the market often overbuy stocks that cant keep up their earnings with the current inflow of investments. We can also oversell a stock that is keeping up with earnings in regards to the stock price but we don't care because of the sentiment we have.
Earnings Yield is simply the percentage of Earnings Per Share in relation to the stock price. Alone, it's a great fundamental indicator to analyze a company. But I wanted to use it in another way and got tired of using the calculator all the time so that's why I made this indicator.
The goal is to see if the STOCK price is moving accordingly to the BUSINESS earnings. It works by calculating the difference of EY (TTM) previous close (1 bar) to the close thereafter. It then calculates the stock performance of the latest bar and divides that to get decimal form instead of percent. Then it divides the stock performance in decimal form with the difference of EY calculated before. The result shows how much the stock prices moves in relation to how much EY is moving. The theory is that if EY barely moves but the stock price moves heavily, you have a sentiment driven trend.
Example: Week 1 EY = 1.201. Week 2 EY = 1.105.
1.201 - 1.105 = 0.096
Week 2 performed a 11,2% increase in stock price. = 0.112 in decimal form.
0.112 / 0.096 = 1.67
1.67 is the multiple that plots this indicator.
Here is an good example of a stock that's currently in a highly sentiment driven trend, NVIDIA! (Posted 2024-03-30)
Here is an example of a Swedish stock that retail investors flocked to that have been blowned out completely.
When do I buy and sell?
This indicator is not meant to give exact entries or exits. The purpose is to scout the current and past sentiment, possible divergencies and see if a stock is over or under valued. I did add a 50 EMA to get some form of mean plotted. One could buy when true performance is low and sell when true performance drops below the 50 EMA. You could also just sell a part of your position and set a trailing exit with a ordinary 50 EMA or something like that. Often the sentiment will keep driving the price up. But if it last for 1 month or 1 year is impossible to tell.
Try it out and learn how it works and use it as you like. Cheers!
NVT Z-ScoreNVT Z-Score Script:
Data Source and Calculation: This script calculates the NVT ratio by dividing the market cap (assumed from QUANDL data) by a 90-day MA of the transaction volume (also from QUANDL), similar to the NVTS calculation. However, the adaptation lies in further analyzing the NVT ratio through a Z-score approach, not explicitly described in the original NVTS methodology.
Z-Score Analysis: The script calculates the mean and standard deviation of the NVT ratio over a user-defined period (daysForMean, defaulting to 180 days) and then computes the Z-score of the current NVT ratio relative to this historical data. This Z-score analysis introduces a standardized way of understanding the NVT ratio's deviation from its historical average, offering a nuanced view of market valuation states.
Visualization and Dynamic Zones: The visualization emphasizes Z-score-based dynamic zones (green, yellow, and red), determined by the stdDevMultiplier. These zones are plotted and filled on the chart, providing visual cues for interpreting the NVT ratio's current state in relation to its historical norm. This aspect significantly differs from the traditional NVTS approach by directly incorporating the concept of standard deviation and Z-scores into the analysis.
Inflation CorrelationHeyo fellas,
In today’s dynamic economic landscape, understanding the relationship of market prices to other economical factors like inflation rate is crucial. The Inflation Correlation Indicator is designed to provide traders with a clear visualization of this relationship. By correlating average inflation rates from selected countries with market closing prices, this indicator offers a unique perspective on potential market movements influenced by inflationary trends.
Features:
Country Selection: Choose from the European Union (EU), Germany (DE), or the United States (US) to tailor the correlation analysis to your specific market interest.
Correlation Length Customization: Adjust the correlation length to refine the sensitivity of the indicator to recent inflation data.
Visual Clarity: The correlation histogram changes color based on the direction of the correlation, providing an intuitive understanding of the inflation correlation.
Whether you’re a fundamental analyst seeking to incorporate macroeconomic indicators into your strategy or a trader looking for an edge in inflation-sensitive markets, the Inflation Correlation Indicator is an indispensable tool in your TradingView arsenal.
Thanks for checking this out!
Best regards,
simwai
NSE Option Straddle Candle Chart
'NSE Option Straddle Candle Chart' plot a straddle chart of the mentioned strike.
Straddle means combine price of a call price and a put price.
User has 4 inputs :
1 : Spot Symbol
2 : Expiry date
3 : Straddle Strikes
4 : Ema Length
5 : Supertrend Inputs
How to use :
1 : Trade need to know first what is a straddle. If ATM straddle price is 405, than it means market is likely to close within 405 points up or down at the expiry.
2 : Straddle is traded on pairs only
3 : If trader sells a straddle than , straddle price should move down. For there reference supertrend and moving average is plotted on chart
4 : Both this indicators helps trade to identify the trend , hence predict market.
5 : Options are dying assite , so is straddle , so prefer selling straddle instead of buying.
Buffett IndicatorThis is an open-source version of the Buffett indicator. The old version was code-protected and broken, so I created another version.
It's computed simply as the entire SPX 500 capitalization divided by the US GDP. Since TradingView does not have data for the SPX 500 capitalization, I used quarterly values of SPX devisors as a proxy.
I tried to create another version of the Buffett indicator for other countries/indexes, but I can't find the data. If you can help me find data for index divisors, I can add more choices to this indicator.
It's interesting to see how this indicator's behavior has changed in the last few years. Levels that looked crazy are not so crazy anymore.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
NSE Option Chain
This Indicator show Options Data on signal dashboard , that help trader to analyse the market.
Options data consist of two things , Call and Put.
Every Strike has its Call and Put price.
So if user Opens any chart which is traded in options , dashboard will show total 16 Call and 16 Put strikes
8 Above from ATM and 8 Below from ATM.
On left hand side of dashboard there is Call data and on right side there is Put data.
Call side datas are , Call LTP which is latest price of that call strike , Call Chg which is change in points from previous day close and third is Call % which is % change from previous day close.
Same is on put side.
Color code is done based on positive or negative of data. If change or % is negative then color is red else green.
ATM strike data is plotted in bold
Inputs :
Spot Symbol Input for Option dashboard
Expiry date of that option contract
Strike interval between 2 strikes
Reference ATM strike ( user should keep this input as current ATM strike )
How to Use :
If dashboard shows call side is negative and put side is positive then that means market Bearish , because falling market leads to falling price of call and increase in price of Put.
Similarly if put is negative and call is positive then market is bullish.
This dashboard give trend conformation , trader should take other conformation also before taking trade.
Statistics • Chi Square • P-value • SignificanceThe Statistics • Chi Square • P-value • Significance publication aims to provide a tool for combining different conditions and checking whether the outcome is significant using the Chi-Square Test and P-value.
🔶 USAGE
The basic principle is to compare two or more groups and check the results of a query test, such as asking men and women whether they want to see a romantic or non-romantic movie.
–––––––––––––––––––––––––––––––––––––––––––––
| | ROMANTIC | NON-ROMANTIC | ⬅︎ MOVIE |
–––––––––––––––––––––––––––––––––––––––––––––
| MEN | 2 | 8 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
| WOMEN | 7 | 3 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
|⬆︎ SEX | 10 | 10 | 20 |
–––––––––––––––––––––––––––––––––––––––––––––
We calculate the Chi-Square Formula, which is:
Χ² = Σ ( (Observed Value − Expected Value)² / Expected Value )
In this publication, this is:
chiSquare = 0.
for i = 0 to rows -1
for j = 0 to colums -1
observedValue = aBin.get(i).aFloat.get(j)
expectedValue = math.max(1e-12, aBin.get(i).aFloat.get(colums) * aBin.get(rows).aFloat.get(j) / sumT) //Division by 0 protection
chiSquare += math.pow(observedValue - expectedValue, 2) / expectedValue
Together with the 'Degree of Freedom', which is (rows − 1) × (columns − 1) , the P-value can be calculated.
In this case it is P-value: 0.02462
A P-value lower than 0.05 is considered to be significant. Statistically, women tend to choose a romantic movie more, while men prefer a non-romantic one.
Users have the option to choose a P-value, calculated from a standard table or through a math.ucla.edu - Javascript-based function (see references below).
Note that the population (10 men + 10 women = 20) is small, something to consider.
Either way, this principle is applied in the script, where conditions can be chosen like rsi, close, high, ...
🔹 CONDITION
Conditions are added to the left column ('CONDITION')
For example, previous rsi values (rsi ) between 0-100, divided in separate groups
🔹 CLOSE
Then, the movement of the last close is evaluated
UP when close is higher then previous close (close )
DOWN when close is lower then previous close
EQUAL when close is equal then previous close
It is also possible to use only 2 columns by adding EQUAL to UP or DOWN
UP
DOWN/EQUAL
or
UP/EQUAL
DOWN
In other words, when previous rsi value was between 80 and 90, this resulted in:
19 times a current close higher than previous close
14 times a current close lower than previous close
0 times a current close equal than previous close
However, the P-value tells us it is not statistical significant.
NOTE: Always keep in mind that past behaviour gives no certainty about future behaviour.
A vertical line is drawn at the beginning of the chosen population (max 4990)
Here, the results seem significant.
🔹 GROUPS
It is important to ensure that the groups are formed correctly. All possibilities should be present, and conditions should only be part of 1 group.
In the example above, the two top situations are acceptable; close against close can only be higher, lower or equal.
The two examples at the bottom, however, are very poorly constructed.
Several conditions can be placed in more than 1 group, and some conditions are not integrated into a group. Even if the results are significant, they are useless because of the group formation.
A population count is added as an aid to spot errors in group formation.
In this example, there is a discrepancy between the population and total count due to the absence of a condition.
The results when rsi was between 5-25 are not included, resulting in unreliable results.
🔹 PRACTICAL EXAMPLES
In this example, we have specific groups where the condition only applies to that group.
For example, the condition rsi > 55 and rsi <= 65 isn't true in another group.
Also, every possible rsi value (0 - 100) is present in 1 of the groups.
rsi > 15 and rsi <= 25 28 times UP, 19 times DOWN and 2 times EQUAL. P-value: 0.01171
When looking in detail and examining the area 15-25 RSI, we see this:
The population is now not representative (only checking for RSI between 15-25; all other RSI values are not included), so we can ignore the P-value in this case. It is merely to check in detail. In this case, the RSI values 23 and 24 seem promising.
NOTE: We should check what the close price did without any condition.
If, for example, the close price had risen 100 times out of 100, this would make things very relative.
In this case (at least two conditions need to be present), we set 1 condition at 'always true' and another at 'always false' so we'll get only the close values without any condition:
Changing the population or the conditions will change the P-value.
In the following example, the outcome is evaluated when:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is lower/equal than the close value from 2 bars back
Or:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is equal than the close value from 2 bars back
close value from 1 bar back is lower than the close value from 2 bars back
In both examples, all possibilities of close against close are included in the calculations. close can only by higher, equal or lower than close
Both examples have the results without a condition included (5 = 5 and 5 < 5) so one can compare the direction of current close.
🔶 NOTES
• Always keep in mind that:
Past behaviour gives no certainty about future behaviour.
Everything depends on time, cycles, events, fundamentals, technicals, ...
• This test only works for categorical data (data in categories), such as Gender {Men, Women} or color {Red, Yellow, Green, Blue} etc., but not numerical data such as height or weight. One might argue that such tests shouldn't use rsi, close, ... values.
• Consider what you're measuring
For example rsi of the current bar will always lead to a close higher than the previous close, since this is inherent to the rsi calculations.
• Be careful; often, there are na -values at the beginning of the series, which are not included in the calculations!
• Always keep in mind considering what the close price did without any condition
• The numbers must be large enough. Each entry must be five or more. In other words, it is vital to make the 'population' large enough.
• The code can be developed further, for example, by splitting UP, DOWN in close UP 1-2%, close UP 2-3%, close UP 3-4%, ...
• rsi can be supplemented with stochRSI, MFI, sma, ema, ...
🔶 SETTINGS
🔹 Population
• Choose the population size; in other words, how many bars you want to go back to. If fewer bars are available than set, this will be automatically adjusted.
🔹 Inputs
At least two conditions need to be chosen.
• Users can add up to 11 conditions, where each condition can contain two different conditions.
🔹 RSI
• Length
🔹 Levels
• Set the used levels as desired.
🔹 Levels
• P-value: P-value retrieved using a standard table method or a function.
• Used function, derived from Chi-Square Distribution Function; JavaScript
LogGamma(Z) =>
S = 1
+ 76.18009173 / Z
- 86.50532033 / (Z+1)
+ 24.01409822 / (Z+2)
- 1.231739516 / (Z+3)
+ 0.00120858003 / (Z+4)
- 0.00000536382 / (Z+5)
(Z-.5) * math.log(Z+4.5) - (Z+4.5) + math.log(S * 2.50662827465)
Gcf(float X, A) => // Good for X > A +1
A0=0., B0=1., A1=1., B1=X, AOLD=0., N=0
while (math.abs((A1-AOLD)/A1) > .00001)
AOLD := A1
N += 1
A0 := A1+(N-A)*A0
B0 := B1+(N-A)*B0
A1 := X*A0+N*A1
B1 := X*B0+N*B1
A0 := A0/B1
B0 := B0/B1
A1 := A1/B1
B1 := 1
Prob = math.exp(A * math.log(X) - X - LogGamma(A)) * A1
1 - Prob
Gser(X, A) => // Good for X < A +1
T9 = 1. / A
G = T9
I = 1
while (T9 > G* 0.00001)
T9 := T9 * X / (A + I)
G := G + T9
I += 1
G *= math.exp(A * math.log(X) - X - LogGamma(A))
Gammacdf(x, a) =>
GI = 0.
if (x<=0)
GI := 0
else if (x
Chisqcdf = Gammacdf(Z/2, DF/2)
Chisqcdf := math.round(Chisqcdf * 100000) / 100000
pValue = 1 - Chisqcdf
🔶 REFERENCES
mathsisfun.com, Chi-Square Test
Chi-Square Distribution Function
