Liquidity Sweep Filter [Magu]SMC The smart money concept in forex trading involves understanding the behavior of institutional players, such as banks and hedge funds, and analyzing supply and demand dynamics, order blocks, and price patterns.
SMC is often seen as a repackaged version of price action trading with a long history of producing positive results in various asset classes
Market liquidity is a fundamental concept in financial markets that significantly impacts trading strategies, asset pricing, and financial stability. The stock market is a prime example of a financial market where liquidity plays a crucial role in determining asset prices and trading strategies. Understanding market liquidity helps investors and traders make informed decisions, especially during times of market volatility. This article explores the key concepts, factors affecting liquidity, and strategies to navigate both liquid and illiquid markets
Ratio
ATH Levels v4# ATH Levels v4
A powerful indicator for tracking All-Time Highs (ATH) and setting customizable price levels based on percentage drops from the ATH. Perfect for cryptocurrency trading, DCA strategies, and risk management.
## Overview
ATH Levels v4 helps traders visualize key support levels calculated as percentage drops from the All-Time High within a configurable lookback period. The indicator also tracks the All-Time Low (ATL) since the last ATH, providing a complete picture of price range dynamics.
## Key Features
### Configurable Percentage Levels
- Define up to 8 custom price levels as percentage drops from ATH
- No longer limited to fixed 10% intervals
- Each level can be set anywhere from 0% to 100% drop
- Default levels: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%
### ATL Tracking (NEW in v4)
- Automatically tracks the All-Time Low since the last ATH was reached
- Displays ATL price and percentage drop from ATH
- Resets when a new ATH is detected
- Can be toggled on/off
### Portfolio Management
- Allocate pot size percentages to each level
- Visualize dollar amounts for each level based on your total pot size
- Plan your DCA (Dollar Cost Averaging) strategy
- Only displays levels with allocated pot percentages
### Flexible Display Options
- Show/hide level lines
- Hide ATH level for zooming into lower levels
- Configurable lookback period (default 365 days)
- Adjustable right margin positioning for labels
- Color-coded labels with transparency gradient
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. Set your total pot size in dollars
3. Configure the percentage drops for each level (where you want to buy/accumulate)
4. Allocate pot size percentages to each level
### Example DCA Strategy
```
Total Pot Size: $10,000
Level 3 (-30%): 10% pot = $1,000
Level 4 (-40%): 20% pot = $2,000
Level 5 (-50%): 25% pot = $2,500
Level 6 (-60%): 30% pot = $3,000
Level 7 (-70%): 10% pot = $1,000
Level 8 (-80%): 5% pot = $500
```
## Settings
### Display Options
- **Show level lines**: Toggle horizontal lines on/off
- **Hide ATH level**: Hide the ATH label for cleaner charts
- **Show ATL since last ATH**: Display/hide the All-Time Low indicator
- **Days to Lookback**: Period for calculating ATH (default: 365)
- **Margin from last bar**: Spacing between chart and labels (default: 10)
### Level Configuration
- **Level 1-8 % drop from ATH**: Set custom percentage drops (0-100%)
- **Level 1-8 pot %**: Allocate your portfolio percentage to each level (0-100%)
**Note**: Levels only display if they have a pot percentage allocated (>0%)
### Pot Size
- **Pot size**: Total amount in dollars available for the strategy
## Version History
### V4 (October 2025)
- Upgraded to PineScript v6
- Configurable percentage drops from ATH (no longer hardcoded)
- ATL tracking and display since last ATH
- Updated syntax and functions for v6 compatibility
### V3 (May 2020)
- Added option to hide ATH level for better chart zoom
### V2
- Hide/show level lines
- Configurable lookback period
- Configurable right margin
- Only shows levels with pot size % set
### V1
- Initial release with 8 fixed levels
## Use Cases
### Cryptocurrency Trading
- Plan accumulation zones during bear markets
- Set alerts at key percentage drops from ATH
- Track historical ATH and ATL ranges
### Risk Management
- Visualize potential support zones
- Plan position sizing at different levels
- Monitor distance from ATH in real-time
### DCA Strategies
- Automate dollar-cost averaging planning
- Allocate budget across multiple price levels
- Track execution of your DCA plan
## Technical Details
- **Version**: PineScript v6
- **Type**: Indicator
- **Overlay**: Yes
- **Default Timeframe**: Works on all timeframes
- **Calculations**: Based on closing prices within lookback period
## Credits
Original concept inspired by daytask. Enhanced and maintained by SilvesterScorpion.com
## License
This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
---
**Tip**: For best results, use on higher timeframes (4H, Daily, Weekly) to identify major support zones. Combine with volume analysis and other indicators for confirmation.
Quarterly EarningsThis Pine script shows quarterly EPS, Sales, and P/E (TTM-based) in a styled table.
PE Rating by The Noiseless TraderPE Rating by The Noiseless Trader
This script analyzes a symbol’s Price-to-Earnings (P/E) ratio, using Diluted EPS (TTM) fundamentals directly from TradingView.
The script calculates the Price-to-Earnings ratio (P/E) using Diluted EPS (TTM) fundamentals. It then identifies:
PE High → the highest valuation point over a 3-year historical range.
PE Low → the lowest valuation point over a 3-year historical range.
PE Median → the midpoint between the two extremes, offering a fair-value benchmark.
PE (Int) → an additional intermediate low to track more recent undervaluation points. This is calculated based on lowest valuation point over a 1-year historical range
These levels are plotted directly on the chart as horizontal references, with markers showing the exact bars/dates when the extremes occurred. Candles corresponding to those days are also highlighted for context.
Bars corresponding to these extremes are highlighted (red = PE High, green = PE Low).
How it helps
Provides a historical valuation framework that complements technical analysis. We look for long opportunity or base formation near the PE Low and be cautious when stocks tends to trade near High PE.
We do not short the stock at High PE infact be cautious with long trades.
Helps identify whether current price action is happening near overvalued or undervalued zones.
Adds a long-term perspective to support swing trading and investing decisions. If a stock is coming from Low PE to Median PE and along with that if we get entry based on Classical strategies like Darvas Box, or HH-HL based on Dow Theory.
Offers a simple visual map of how far the market has moved from “cheap” to “expensive.”
This tool is best suited for long-term investors and swing traders who want to merge fundamentals with technical setups.
This indicator is designed as an educational tool to illustrate how valuation metrics (like earnings multiples) can be viewed alongside price action, helping traders connect fundamental context with technical execution in real market conditions.
NYSE Advancing Issues & Volume RatiosOverview
This comprehensive market breadth indicator tracks two essential NYSE ratios that provide deep insights into market sentiment and internal strength:
NYSE Advancing Issues Ratio
NYSE Advancing Volume Ratio
Dual Ratio Analysis
Issues Ratio: Measures the percentage of NYSE stocks advancing vs. total issues
Volume Ratio: Measures the percentage of NYSE volume flowing into advancing stocks
Both ratios displayed as easy-to-read percentages (0-100%)
Customizable Display Options
Toggle each ratio on/off independently
Choose from multiple moving average types (SMA, EMA, WMA)
Adjustable moving average periods
Custom color schemes for better visualization
Reference Levels
50% Line: Market neutral point (gray dashed)
10% Line: Extremely bearish breadth (red dotted)
90% Line: Extremely bullish breadth (green dotted)
Optional background highlighting for extreme readings
Smart Alerts
Cross above/below 50% (neutral) for both ratios
Extreme readings: Above 90% (strong bullish) and below 10% (strong bearish)
Real-time notifications for key market breadth shifts
📈 How to Interpret
Bullish Signals
Above 50%: More stocks/volume advancing than declining
Above 90%: Extremely strong market breadth (rare occurrence)
Divergence: Price making new highs while breadth weakens (potential warning)
Market Timing
Extreme readings (10%/90%) often coincide with market turning points
Breadth thrusts from extreme levels can signal powerful moves
Use with other technical indicators for enhanced timing
Forward P/E CalculatorI could not find a forward P/E indicator that gave me proper results. So here is mine.
Metatrader CalculatorThe “ Metatrader Calculator ” indicator calculates the position size, risk, and potential gain of a trade, taking into account the account balance, risk percentage, entry price, stop loss price, and risk/reward ratio. It supports the XAUUSD, XAGUSD, and BTCUSD pairs, automatically calculating the position size (in lots) based on these parameters. The calculation is displayed in a table on the chart, showing the lot size, loss in dollars, and potential gain based on the defined risk.
Put/Call RatioPut/Call Ratio Indicator
This indicator visualizes the Put/Call Ratio for various market symbols, helping traders assess market sentiment and potential reversals. It offers a dropdown menu to select from a range of Put/Call Ratios, including broad equities (CBOE), major indices (SPX, QQQ, IWM, VIX), and individual stocks (TSLA, GOOG, META, AMZN, MSFT, INTC).
The indicator plots the Put/Call Ratio with adjustable moving averages and standard deviation bands to highlight overbought or oversold conditions. A short-term moving average (default: 10 periods) is displayed with trend-based coloring, while longer-term moving averages (defaults: 30 and 200 periods) are calculated but hidden by default. Bands at 1, 1.5, and 2 standard deviations provide context for extreme readings.
Key Overbought/Oversold Signals:
Short-Term Extremes: The 10-day moving average moves beyond 1 standard deviation from the 200-day moving average, signaling potential overbought (above) or oversold (below) conditions. This will be highlighted by red or green background color.
Ratio Extremes: The Put/Call Ratio line itself crosses outside 2 standard deviations from the 200-day moving average, indicating stronger overbought or oversold zones.
Conditional coloring of the ratio line reflects its position relative to the bands, and background shading highlights when the short-term moving average crosses key levels.
Key Features:
Selectable Put/Call Ratio symbols.
Trend-colored moving averages.
Standard deviation bands for volatility analysis.
Dynamic line and background coloring for quick insights.
Usage:
Use this indicator to gauge market sentiment—high ratios may suggest bearish sentiment or oversold conditions, while low ratios may indicate bullish sentiment or overbought conditions. Combine with price action or other tools for confirmation.
Sma Indicator with Ratio (pr)SMA Indicator with Ratio (PR) is a technical analysis tool designed to provide insights into the relationship between multiple Simple Moving Averages (SMAs) across different time frames. This indicator combines three key SMAs: the 111-period SMA, 730-period SMA, and 1400-period SMA. Additionally, it introduces a ratio-based approach, where the 730-period SMA is multiplied by factors of 2, 3, 4, and 5, allowing users to analyze potential market trends and price movements in relation to different SMA levels.
What Does This Indicator Do?
The primary function of this indicator is to track the movement of prices in relation to several SMAs with varying periods. By visualizing these SMAs, users can quickly identify:
Short-term trends (111-period SMA)
Medium-term trends (730-period SMA)
Long-term trends (1400-period SMA)
Additionally, the multiplied versions of the 730-period SMA provide deeper insights into potential price reactions at different levels of market volatility.
How Does It Work?
The 111-period SMA tracks the shorter-term price trend and can be used for identifying quick market movements.
The 730-period SMA represents a longer-term trend, helping users gauge overall market sentiment and direction.
The 1400-period SMA acts as a very long-term trend line, giving users a broad perspective on the market’s movement.
The ratio-based SMAs (2x, 3x, 4x, 5x of the 730-period SMA) allow for an enhanced understanding of how the price reacts to higher or lower volatility levels. These ratios are useful for identifying key support and resistance zones in a dynamic market environment.
Why Use This Indicator?
This indicator is useful for traders and analysts who want to track the interaction of price with different moving averages, enabling them to make more informed decisions about potential trend reversals or continuations. The added ratio-based values enhance the ability to predict how the market might react at different levels.
How to Use It?
Trend Confirmation: Traders can use the indicator to confirm the direction of the market. If the price is above the 111, 730, or 1400-period SMA, it may indicate an uptrend, and if below, a downtrend.
Support/Resistance Levels: The multiplied versions of the 730-period SMA (2x, 3x, 4x, 5x) can be used as dynamic support or resistance levels. When the price approaches or crosses these levels, it might indicate a change in the trend.
Volatility Insights: By observing how the price behaves relative to these SMAs, traders can gauge market volatility. Higher multiples of the 730-period SMA can signal more volatile periods where price movements are more pronounced.
Zanger Volume Ratio (ZVR)Zanger Volume Ratio (ZVR)
Credits:
Most of the underlying code and logic in this script have been adapted from the work originally published by The_Peaceful_Lizard
Overview
The Zanger Volume Ratio (ZVR) is a powerful indicator designed to reveal market dynamics by comparing current cumulative volume to an average determined over a historical look-back period. It uses the concept of relative volume to not only highlight unusual volume spikes, but also uses color to illustrate how today's trading compares to typical levels. This unique method of volume analysis was popularized by Dan Zanger - a trader known for turning $10,775 into $18,000,000 in less than two years - by identifying key shifts in market interest and volume behavior.
Key Features
Volume Pacing Analysis:
The script calculates a volume delta by comparing the cumulative volume at any given moment to an average derived over a user-defined lookback period (Default 20-day). The resulting percentage difference offers a clear visualization and insight into unusual volume activity.
Dynamic Visual Representation:
Choose between either “Columns” or “Area” plot styles to display the percent difference. Additionally, you have the option to switch between a standard plot or a background color display, with customizable transparency, ensuring the indicator fits seamlessly with your chart’s aesthetics.
Dashboard Integration:
A simple dashboard table is displayed on the chart, showcasing the current ZVR value in real-time. With user-configurable position, text size, alignment, and color options, this feature ensures that the key metric is always visible and easy to interpret.
Why Use the Zanger Volume Ratio?
The ZVR is more than just a volume indicator. It acts as a window into market sentiment by highlighting days when trading interest intensifies. Many traders believe that an unusually high volume ratio may confirm trend strength or signal a reversal, making the indicator a valuable tool when used in conjunction with other technical analysis methods.
Whether you’re monitoring stocks, commodities, or forex markets, the Zanger Volume Ratio offers an accessible yet sophisticated method to decode volume dynamics. Its practical design and real-time visual feedback provide traders of all experience levels with critical data to spot high-potential setups.
Chart Description
First Pane: normal Volume Indicator on the foreground, ZVR as Background colors
Second Pane: ZVR Indicator with Column Style (default)
First panel: normal volume indicator in foreground, ZVR as background colors
Second panel: ZVR indicator with column style (default)
Note: This indicator is intended for use on intraday charts only!
MATA GOLD RATIOMata Gold Instrument: User Guide
The Instrument to Gold Oscillator is a technical analysis tool that normalizes the ratio of an instrument's price (e.g., BTC/USD) to the price of gold (XAU/USD) into a 0-100 scale. This provides a clear and intuitive way to evaluate the relative performance of an instrument compared to gold over a specified period.
---
How It Works
1. Calculation of the Ratio:
The ratio is calculated as:
\text{Ratio} = \frac{\text{Instrument Price}}{\text{Gold Price}}
2. Normalization:
The ratio is normalized using the highest and lowest values over a user-defined period (length), typically 14 periods:
\text{Normalized Ratio} = \frac{\text{Ratio} - \text{Min(Ratio)}}{\text{Max(Ratio)} - \text{Min(Ratio)}} \times 100
3. Overbought/Oversold Levels:
Above 80: The instrument is relatively expensive compared to gold (overbought).
Below 20: The instrument is relatively cheap compared to gold (oversold).
---
How to Use the Oscillator
1. Identify Overbought and Oversold Levels:
If the oscillator rises above 80, the instrument may be overvalued relative to gold. This could signal a potential reversal or correction.
If the oscillator falls below 20, the instrument may be undervalued relative to gold. This could signal a buying opportunity.
2. Track Trends:
Rising oscillator values indicate the instrument is gaining value relative to gold.
Falling oscillator values indicate the instrument is losing value relative to gold.
3. Crossing the Midline (50):
When the oscillator crosses above 50, the instrument's value is gaining strength relative to gold.
When it crosses below 50, the instrument is weakening relative to gold.
4. Combine with Other Indicators:
Use this oscillator alongside other technical indicators (e.g., RSI, MACD, STOCH) for more robust decision-making.
Confirm signals from the oscillator with price action or volume analysis.
---
Example Scenarios
1. Trading Cryptocurrencies Against Gold:
If BTC/USD's oscillator value is above 80, Bitcoin may be overvalued relative to gold. Consider reducing exposure or looking for short opportunities.
If BTC/USD's oscillator value is below 20, Bitcoin may be undervalued relative to gold. This could be a good time to accumulate.
2. Commodities vs. Gold:
Analyze the relative strength of commodities (e.g., oil, silver) against gold using the oscillator to identify periods of overperformance or underperformance.
---
Advantages of the Oscillator
Relative Performance Insight: Tracks the performance of an instrument relative to gold, providing a macro perspective.
Clear Visual Representation: The 0-100 scale makes it easy to identify overbought/oversold conditions and trend shifts.
Customizable Periods: The user-defined length allows flexibility in analyzing short- or long-term trends.
---
Limitations
Dependence on Gold: As the oscillator is based on gold prices, any external shocks to gold (e.g., geopolitical events) can influence its signals.
No Absolute Buy/Sell Signals: The oscillator should not be used in isolation but as part of a broader analysis strategy.
---
By using the Instrument to Gold Oscillator effectively, traders and investors can gain valuable insights into the relative valuation and performance of assets compared to gold, enabling more informed trading and investment decisions.
Dynamic Risk-Adjusted Performance Ratios with TableWith this indicator, you have everything you need to monitor and compare the Sharpe ratio, Sortino ratio, and Omega ratio across multiple assets—all in one place. This tool is designed to help save time and improve efficiency by letting you track up to 15 assets simultaneously in a fully customizable table. You can adjust the lookback period to fit your trading strategy and get a clearer picture of how your assets perform over time. Instead of switching between charts, this indicator puts all the critical information you need at your fingertips.
Sharpe Ratio -
Helps evaluate the overall efficiency of investments by comparing the average return to the total risk (measured by the standard deviation of all returns). Essentially, it tells you how much excess return you’re getting for each unit of risk you’re taking. A higher Sharpe ratio means you’re getting better risk-adjusted performance—something you’ll want to aim for in your portfolio.
Sortino Ratio -
Goes a step further by focusing only on downside risk—because let’s face it, no one worries about positive volatility. This ratio is calculated by dividing the average return by the standard deviation of only the negative returns. Perfect for those concerned about avoiding losses rather than chasing extreme gains. It gives you a sharper view of how well your assets are performing relative to the risks you’re trying to avoid.
Omega Ratio -
Offers a unique perspective by comparing the sum of positive returns to the absolute sum of negative returns. It’s a straightforward way to see if your wins outweigh your losses. A higher Omega ratio means your positive returns significantly exceed the downside, which is exactly what you want when building a strong, reliable portfolio.
This indicator is perfect for traders who want to streamline their decision-making process and gain an edge. Bringing together these three critical ratios into a single user-defined table makes it easy to compare and rank assets at a glance. Whether optimizing a portfolio or looking for the best opportunities, this tool helps you stay ahead by focusing on risk-adjusted returns. The customizable lookback period lets you tailor the analysis to fit your unique trading approach, giving you insights that align with your goals. If you’re serious about making data-driven decisions and improving your trading outcomes, this indicator is a game-changer for your toolkit.
Quick scan for signal🙏🏻 Hey TV, this is QSFS, following:
^^ Quick scan for drift (QSFD)
^^ Quick scan for cycles (QSFC)
As mentioned before, ML trading is all about spotting any kind of non-randomness, and this metric (along with 2 previously posted) gonna help ya'll do it fast. This one will show you whether your time series possibly exhibits mean-reverting / consistent / noisy behavior, that can be later confirmed or denied by more sophisticated tools. This metric is O(n) in windowed mode and O(1) if calculated incrementally on each data update, so you can scan Ks of datasets w/o worrying about melting da ice.
^^ windowed mode
Now the post will be divided into several sections, and a couple of things I guess you’ve never seen or thought about in your life:
1) About Efficiency Ratios posted there on TV;
Some of you might say this is the Efficiency Ratio you’ve seen in Perry's book. Firstly, I can assure you that neither me nor Perry, just as X amount of quants all over the world and who knows who else, would say smth like, "I invented it," lol. This is just a thing you R&D when you need it. Secondly, I invite you (and mods & admin as well) to take a lil glimpse at the following screenshot:
^^ not cool...
So basically, all the Efficiency Ratios that were copypasted to our platform suffer the same bug: dudes don’t know how indexing works in Pine Script. I mean, it’s ok, I been doing the same mistakes as well, but loxx, cmon bro, you... If you guys ever read it, the lines 20 and 22 in da code are dedicated to you xD
2) About the metric;
This supports both moving window mode when Length > 0 and all-data expanding window mode when Length < 1, calculating incrementally from the very first data point in the series: O(n) on history, O(1) on live updates.
Now, why do I SQRT transform the result? This is a natural action since the metric (being a ratio in essence) is bounded between 0 and 1, so it can be modeled with a beta distribution. When you SQRT transform it, it still stays beta (think what happens when you apply a square root to 0.01 or 0.99), but it becomes symmetric around its typical value and starts to follow a bell-shaped curve. This can be easily checked with a normality test or by applying a set of percentiles and seeing the distances between them are almost equal.
Then I noticed that on different moving window sizes, the typical value of the metric seems to slide: higher window sizes lead to lower typical values across the moving windows. Turned out this can be modeled the same way confidence intervals are made. Lines 34 and 35 explain it all, I guess. You can see smth alike on an autocorrelogram. These two match the mean & mean + 1 stdev applied to the metric. This way, we’ve just magically received data to estimate alpha and beta parameters of the beta distribution using the method of moments. Having alpha and beta, we can now estimate everything further. Btw, there’s an alternative parameterization for beta distributions based on data length.
Now what you’ll see next is... u guys actually have no idea how deep and unrealistically minimalistic the underlying math principles are here.
I’m sure I’m not the only one in the universe who figured it out, but the thing is, it’s nowhere online or offline. By calculating higher-order moments & combining them, you can find natural adaptive thresholds that can later be used for anomaly detection/control applications for any data. No hardcoded thresholds, purely data-driven. Imma come back to this in one of the next drops, but the truest ones can already see it in this code. This way we get dem thresholds.
Your main thresholds are: basis, upper, and lower deviations. You can follow the common logic I’ve described in my previous scripts on how to use them. You just register an event when the metric goes higher/lower than a certain threshold based on what you’re looking for. Then you take the time series and confirm a certain behavior you were looking for by using an appropriate stat test. Or just run a certain strategy.
To avoid numerous triggers when the metric jitters around a threshold, you can follow this logic: forget about one threshold if touched, until another threshold is touched.
In general, when the metric gets higher than certain thresholds, like upper deviation, it means the signal is stronger than noise. You confirm it with a more sophisticated tool & run momentum strategies if drift is in place, or volatility strategies if there’s no drift in place. Otherwise, you confirm & run ~ mean-reverting strategies, regardless of whether there’s drift or not. Just don’t operate against the trend—hedge otherwise.
3) Flex;
Extension and limit thresholds based on distribution moments gonna be discussed properly later, but now you can see this:
^^ magic
Look at the thresholds—adaptive and dynamic. Do you see any optimizations? No ML, no DL, closed-form solution, but how? Just a formula based on a couple of variables? Maybe it’s just how the Universe works, but how can you know if you don’t understand how fundamentally numbers 3 and 15 are related to the normal distribution? Hm, why do they always say 3 sigmas but can’t say why? Maybe you can be different and say why?
This is the primordial power of statistical modeling.
4) Thanks;
I really wanna dedicate this to Charlotte de Witte & Marion Di Napoli, and their new track "Sanctum." It really gets you connected to the Source—I had it in my soul when I was doing all this ∞
Daily Ratio OCHL Averager by Munif ShaikhThe "Daily Ratio OCHL Averager" indicator, is designed for use in financial charts. It calculates an average value based on the daily open, close, high, and low prices, and visualizes this average on the chart.
Ratio Calculation:
The script calculates a ratio representing the normalized difference as a percentage. This ratio helps determine if the current price is above or below the calculated average.
Plotting the Average Line:
The average value (dDaily) is plotted on the chart with a dynamic color indicating whether the current price is above (green) or below (red) the average.
Traders can use this indicator to visually analyze how the current price compares to the daily average. The color-coded average line helps quickly identify bullish or bearish conditions. The ratio percentage provides an additional quantitative measure of this relationship.
This indicator can be particularly useful in identifying trends and potential reversal points by showing how prices behave relative to their daily average, aiding in making informed trading decisions.
Ratio Chart with GMMA■About this indicator
This indicator divides the selected stocks by any stocks you specify and plots the result in a new pane.
At the same time, it plots the GMMA against the result of the division.
This allows you to see the relative chart and trend of the selected stock and the arbitrary stock.
Quote Symbol: Specify the denominator of the division. The default is TOPIX. Feel free to change it.
EMA Days: 5 to 30 days are indicated in green, and 75 to 200 days in red. Change the number of days and color freely.
Explanation of Effective Usage
It is recommended to enter an index for stocks specified in the Quote Symbol.
By entering the index, you can check the superiority of the selected issue and the index at a glance.
Example: By dividing AAPL by SP500, you can see on the chart whether AAPL is stronger or weaker relative to SP500.
(Similar concept to the Relative Strength Comparison RSC.)
At the same time, by plotting GMMA, you can confirm the trend of strength or weakness of the selected issue divided by the index. This is useful for swing trading and mid- to long-term trading.
The greater the distance between the short-term and long-term EMAs of the GMMA, the more the selected stocks outperform the index, and when the short-term and long-term EMAs cross, the trend ends and the stock underperforms the index.
■About the Chart
The screen below shows a chart plotted using this indicator.
For comparison with the regular chart, the upper screen shows only the GMMA plotted for the selected stocks.
From the red circle in the lower screen, a trend begins where the selected stocks outperform the index, and the trend ends at the blue circle.
When the trend ends, the selected stocks will underperform the index and it can be determined that it is more efficient to invest in another stock.
■このインジケーターについて
このインジケーターは選択している銘柄を、指定した任意の銘柄で割り算し、その結果を新規ペインにプロットします。
同時に、割り算の結果に対してGMMAをプロットします。
これにより選択した銘柄と、任意の銘柄の相対チャートとトレンドを把握することが出来ます。
Quote Symbol：割り算の分母を指定します。デフォルトはTOPIXです。自由に変更して下さい。
EMA日数：5～30日が緑、75～200日を赤で表記しています。日数と色は自由に変更して下さい。
■有効な使い方の説明
Quote Symbolで指定する銘柄は、指数を入力することを推奨します。
指数を入力することによって、選択した銘柄と指数の優位性を一目で確認出来ます。
例）AAPLをSP500で割ることで、SP500に比べてAAPLが相対的に強いのか、弱いのかをチャートで把握できます。
（相対力比較RSCと似たような考え方です。）
同時にGMMAをプロットすることで、選択した銘柄÷指数の強弱のトレンドを確認できます。これはスイングトレードや中長期トレードに役立ちます。
GMMAの短期EMAと長期EMAの距離が開いていくほど、指数より選択した銘柄がアウトパフォームしていると考えられ、短期EMAと長期EMAが交わるとトレンドは終了し、指数をアンダーパフォームします。
■チャートについて
下の画面がこのインジケーターを使用してプロットしたチャートです。
通常のチャートとの比較のため、上画面には選択した銘柄にGMMAだけをプロットしたものを表示しています。
下の画面の赤い丸から、選択した銘柄が指数をアウトパフォームするトレンドが始まり、青い〇でトレンドは終了します。
トレンドが終了した場合、選択した銘柄は指数をアンダーパフォームするので、別の銘柄に投資する方が効率的と判断できます。
Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
Dividend-to-ROE RatioDividend-to-ROE Ratio Indicator
The Dividend-to-ROE Ratio indicator offers valuable insights into a company's dividend distribution relative to its profitability, specifically comparing the Dividend Payout Ratio (proportion of earnings as dividends) to the Return on Equity (ROE), a measure of profitability from shareholder equity.
Interpretation:
1. Higher Ratio: A higher Dividend-to-ROE Ratio suggests a stable dividend policy, where a significant portion of earnings is returned to shareholders. This can indicate consistent dividend payments, often appealing to income-seeking investors.
2. Lower Ratio: Conversely, a lower ratio implies that the company retains more earnings for growth, potentially signaling a focus on reinvestment for future expansion rather than immediate dividend payouts.
3. Excessively High Ratio: An exceptionally high ratio may raise concerns. While it could reflect a generous dividend policy, excessively high ratios might indicate that a company is distributing more earnings than it can sustainably afford. This could potentially hinder the company's ability to reinvest in its operations, research, or navigate economic downturns effectively.
Utility and Applications:
The Dividend-to-ROE Ratio can be particularly useful in the following scenarios:
1. Income-Oriented Investors: For investors seeking consistent dividend income, a higher ratio signifies a company's commitment to distributing profits to shareholders, potentially aligning with income-oriented investment strategies.
2. Financial Health Assessment: Analysts and stakeholders can use this ratio to gauge a company's financial health and dividend sustainability. It provides insights into management's capital allocation decisions and strategic focus.
3. Comparative Analysis: When comparing companies within the same industry, this ratio helps in benchmarking dividend policies and identifying outliers with unusually high or low ratios.
Considerations:
1. Contextual Analysis: Interpretation should be contextualized within industry standards and the company's financial history. Comparing the ratio with peers in the same sector can provide meaningful insights.
2. Financial Health: It's crucial to evaluate this indicator alongside other financial metrics (like cash flow, debt levels, and profit margins) to grasp the company's overall financial health and sustainability of its dividend policy.
Disclaimer: This indicator is for informational purposes only and does not constitute financial advice. Investors should conduct thorough research and consult with financial professionals before making investment decisions based on this ratio.
CAPEX RatioUnderstanding the CAPEX Ratio: An Essential Financial Metric
Introduction
In the world of finance, understanding how companies allocate their resources and reinvest their earnings is crucial for investors and analysts. One fundamental metric used to assess a company's investment behavior is the CAPEX Ratio. This article delves into what the CAPEX Ratio signifies, its advantages, and how to interpret its implications.
What is the CAPEX Ratio?
The CAPEX Ratio, short for Capital Expenditure Ratio, is a financial indicator that measures the proportion of a company's capital expenditures (CAPEX) relative to various financial metrics such as revenue, free cash flow, net income, or total assets. CAPEX represents investments made by a company to acquire or maintain its physical assets.
Interpreting the Results
Each variant of the CAPEX Ratio provides unique insights into a company's financial strategy:
• CAPEX to Revenue Ratio: This ratio shows what portion of a company's revenue is being reinvested into capital investments. A higher ratio might indicate aggressive expansion plans or a need for infrastructure upgrades.
• CAPEX to Free Cash Flow Ratio: By comparing CAPEX with free cash flow, this ratio reveals how much of a company's available cash is dedicated to capital investments. It helps assess financial health and sustainability.
• CAPEX to Net Income Ratio: This ratio measures how much of a company's net income is being channeled back into capital expenditures. A high ratio relative to net income could signal a company's commitment to growth and development.
• CAPEX to Total Assets Ratio: This metric assesses the proportion of total assets being allocated towards capital expenditures. It provides a perspective on the company's investment intensity relative to its overall asset base.
Advantages of Using CAPEX Ratios
• Insight into Investment Strategy: Helps investors understand where a company is directing its resources.
• Evaluation of Financial Health: Indicates how efficiently a company is reinvesting profits or available cash.
• Comparative Analysis: Enables comparisons across companies or industries to gauge investment priorities.
How to Use the CAPEX Ratio
• Comparative Analysis: Compare the CAPEX Ratios over time or against industry peers to spot trends or outliers.
• Investment Decision-Making: Consider CAPEX Ratios alongside other financial metrics when making investment decisions.
Conclusion
In conclusion, the CAPEX Ratio is a valuable financial metric that offers deep insights into a company's investment behavior and financial health. By analyzing different variants of this ratio, investors and analysts can make informed decisions about a company's growth prospects and financial stability.
Support and Resistance: Triangles [YinYangAlgorithms]Overview:
Triangles have always been known to be the strongest shape. Well, why wouldn’t that likewise apply to trading? This Indicator will create Upwards and Downwards Triangles which in turn create Support and Resistance locations. For example, we find 2 highs that meet the criteria (within deviation %, Minimum Distance and Lookback Distance). We calculate the distance between these two and create an Equilateral Triangle Downwards (You can adjust the % if you want more of an Isosceles Triangle). The midpoint (tip) of this triangle is the Support and the bottom (base) of it is the Resistance. The exact opposite applies for an Upwards Triangle.
The reason why Triangles may make for good Support and Resistance locations is the % 's used, much like the fibonacci, use ratios relevant in nature and everywhere in the world around us, so why not for trading too?
Tutorial:
If you look at the locations we’ve circled above, all of them exhibit strong rejections are predictive Support and Resistance locations plotted by the triangles created. There can only ever be 1 Upward and 1 Downward Triangle at a time, so when a new one is created, the Support and Resistance locations are moved.
If you scroll back far enough you’ll notice the Triangles disappear but their Support and Resistance locations are still plotted. This has to do with the fact you are allowed only so many Lines plotted and when a new Triangle is created, an old one will be removed. The Support and Resistance locations however will stay.
If we look at the example above, you can see the Support and Resistance locations the Triangles made here may have helped predict where the price would struggle to surpass.
By default the Look Back Distance is set to 50 and the Min Distance is 10 (settings used in all previous examples). However, you can modify these to make Triangles more ‘Rare’ and therefore the Support and Resistance locations change less. In the example above for Instance we left Look Back Distance to 50 but changed Min Distance from 10 to 25. This results in Support and Resistance locations that may hold better in the long term.
If we scroll back a bit, we can see the settings ‘Look Back Distance’ 50 and ‘Minimum Distance’ 25 had done a decent job at predicting the ATH resistance and many Support and Resistance locations around it. Keep in mind, previous results don’t mean future results, but Triangles may create ratios which apply well to trading.
We will conclude our Tutorial here. Hopefully you can see the benefit to the ratio Triangles make when predicting Support and Resistance locations.
Settings:
Show Triangles: If all you want to know is the Support and Resistance locations, there’s no need to draw the Triangles.
Triangle Zones: What types of triangles should we create our zones for? Options are Upward, Downward, Both, None.
Max Deviation Allowed: Maximum Deviation up or down from the last bars High/Low for potential to create a Triangle.
Lookback Distance: How far back we look to see for potential of a High/Low within Deviation range.
Min Distance: This is so triangles are spaced properly and not from 2 bars beside each other. Min distance allocated between 2 points to create a Triangle.
Bar Percent Increase: How much % multiplier do we apply for each bar spacing of the triangle. 0.005 creates a close to Equilateral Triangle, but other values like 0.004 and 0.006 seem to work well too.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Realized Profit & Loss [BigBeluga]The Realized Loss & Profit indicator aims to find potential dips and tops in price by utilizing the security function syminfo.basecurrency + "_LOSSESADDRESSES".
The primary objective of this indicator is to present an average, favorable buying/selling opportunity based on the number of people currently in profit or loss.
The script takes into consideration the syminfo.basecurrency, so it should automatically adapt to the current coin.
🔶 USAGE
Users have the option to enable the display of either Loss or Profit, depending on their preferred visualization.
Examples of displaying Losses:
Example of displaying Profits:
🔶 CONCEPTS
The concept aims to assign a score to the data in the ticker representing the realized losses. This score will provide users with an average of buying/selling points that are better to the typical investor.
🔶 SETTINGS
Users have complete control over the script settings.
🔹 Calculation
• Profit: Display people in profit on an average of the selected length.
• Loss: Display people in loss on an average of the selected length.
🔹 Candle coloring
• True: Color the candle when data is above the threshold.
• False: Do not color the candle.
🔹 Levels
- Set the level of a specific threshold.
• Low: Low losses (green).
• Normal: Low normal (yellow).
• Medium: Low medium (orange).
• High: Low high (red).
🔹 Z-score Length: Length of the z-score moving window.
🔹 Threshold: Filter out non-significant values.
🔹 Histogram width: Width of the histogram.
🔹 Colors: Modify the colors of the displayed data.
🔶 LIMITATIONS
• Since the ticker from which we obtain data works only on the daily timeframe, we are
restricted to displaying data solely from the 1D timeframe.
• If the coin does not have any realized loss data, we can't use this script.
The Strat with Continuity [starlord_xrp]This indicator shows entry and exit points for The Strat as well as potential setups. It also has full time frame continuity detection.
Ratio To Average - The Quant ScienceRatio To Average - The Quant Science is a quantitative indicator that calculates the percentage ratio of the market price in relation to a reference average. The indicator allows the calculation of the ratio using four different types of averages: SMA, EMA, WMA, and HMA. The ratio is represented by a series of histograms that highlight periods when the ratio is positive (in green) and periods when the ratio is negative (in red).
What is the Ratio to Average?
The Ratio to Average is a measure that tracks the price movements with one of its averages, calculating how much the price is above or below its own average, in percentage terms.
USER INTERFACE
Lenght: it adjusts the number of bars to include in the calculation of the average.
Moving Average: it allows you to choose the type of average to use.
Color Up/Color Down : it allows you to choose the color of the indicator for positive and negative ratios.
TTP OI + LS signal filterThis oscillator helps filtering specific conditions in the market based on open interest (OI) and the ratio of longs and shorts (LS) for crypto assets.
Currently it works with BINANCE:BTCUSDT.P but soon I'll be adding support for more assets.
It flags areas of interest like:
- Too many longs, too many shorts in the market
- Open interest too high or too low
It accepts an external signal as a source in which case filters can be applied to the original signal. For example the external signal might trigger and plot a 1 when RSI break below 70. By connecting such signal with this oscillator you'll be able to only pass-through the ones that occur when any of the areas of interest mentioned above are also valid.
If both filter are applied it acts as an OR. For example, if too many longs and too many shorts are active, it will pass through the signal in either condition.
The results of the original signal filtered is printed to be able to later use it in any external backtester strategy that accepts external sources too.
If external source signal is disabled it will trigger any time the combined filters are returning true.
Open interest and the ratio of longs/shorts is considered too high whenever the stochastic RSI calculation of the OI or ratio LS reaches a level above 80 and too low when below 20
The ratio of long/shorts is calculated by dividing the ratio of longs vs shorts from BITFINEX:BTCUSDLONGS and BITFINEX:BTCUSDSHORTS
