EPS GrowthA graph to display EPS growth with a trailing simple moving average of the last 4 and 8 periods.
Periods of earnings recessions have a dark red background.
Periods of earnings expansion have a dark green background.
A buy signal/sell signal is generated if the actual period earnings beat the estimates.
Análise Fundamentalista
Upgraded WatermarkThis mimics the built in watermark feature, but adds the ability to change location as well as see an equities sector and industry group.
Bitcoin Economics Adaptive MultipleBEAM (Bitcoin Economics Adaptive Multiple) is an indicator that assesses the valuation of Bitcoin by dividing the current price of Bitcoin by a moving average of past prices. Its purpose is to provide insights into whether Bitcoin is under or overvalued at any given time. The thresholds for the buy and sell zones in BEAM are adjustable, allowing users to customize the indicator based on their preferences and trading strategies.
BEAM categorizes Bitcoin's valuation into two distinct zones: the green buy zone and the red sell zone.
Green Buy Zone:
The green buy zone in BEAM indicates that Bitcoin is potentially undervalued. Traders and investors may interpret this zone as a favorable buying opportunity. The threshold for the buy zone can be adjusted to suit individual preferences or trading strategies.
Red Sell Zone:
The red sell zone in BEAM suggests that Bitcoin is potentially overvalued. Traders and investors may consider selling their Bitcoin holdings during this zone to secure profits or manage risk. The threshold for the sell zone is adjustable, allowing users to adapt the indicator based on their trading preferences.
Methodology:
BEAM calculates the indicator value using the following formula:
beam = math.log(close / ta.sma(close, math.min(count, 1400))) / 2.5
The calculation involves taking the natural logarithm of the ratio between the current price of Bitcoin and a simple moving average of past prices. The moving average period used is a minimum of the specified count or 1400, providing a suitable historical reference for valuation assessment.
The resulting value of BEAM provides a standardized measure that can be compared across different time periods. By adjusting the thresholds for the buy and sell zones, users can customize BEAM to their preferred levels of undervaluation and overvaluation.
Utility:
BEAM serves as a tool for investors in the Bitcoin market, offering insights into Bitcoin's valuation and potential buying or selling opportunities. By monitoring BEAM, market participants can gauge whether Bitcoin is potentially undervalued or overvalued, helping them make informed decisions regarding their Bitcoin positions.
It is important to note that BEAM should be used in conjunction with other technical and fundamental analysis tools to validate signals and avoid relying solely on this indicator for trading decisions. Additionally, traders and investors are encouraged to adjust the threshold values based on their specific trading strategies, risk tolerance, and market conditions.
Credit: The BEAM (Bitcoin Economics Adaptive Multiple) indicator was originally developed by BitcoinEcon
Wyckoff Phases OscillatorThe "Wyckoff Phases Oscillator" is a script designed for the TradingView platform. It's an indicator that provides traders with an oscillator-based visual representation of the Wyckoff Market Cycle. The oscillator doesn't overlay the price chart but instead appears in a separate panel beneath it.
How it works:
The script operates based on two input parameters: length and timeFrame. The length parameter, set by default to 21, determines the period used for various calculations within the script. On the other hand, timeFrame, set by default to "1", specifies the timeframe for which the script will gather and analyze data.
The script requests security information such as closing prices (higherClose), volume (higherVolume), highest prices (higherHigh), and lowest prices (higherLow) from the ticker symbol (syminfo.tickerid) within the defined timeframe.
Two exponential moving averages (ema1 and ema2) are calculated based on the closing prices, with lengths of 5 and 9 respectively.
A Rate of Change (ROC) is calculated based on the closing prices and the defined length.
An average volume (avgVolume) is calculated using a simple moving average (SMA) based on the volume and the defined length.
The script defines conditions for institutional buying and selling.
Institutional buying is determined when the closing price is greater than the lowest price and the volume is greater than the average volume.
Institutional selling is determined when the closing price is less than the highest price and the volume is greater than the average volume.
The script also defines conditions for the four phases of the Wyckoff Market Cycle: Accumulation, Markup, Distribution, and Markdown. Each phase has specific conditions based on the closing prices, EMA values, ROC, and institutional buying or selling conditions.
The script then assigns oscillator values based on the Wyckoff phase:
Accumulation is assigned a value of 1
Markup is assigned a value of 2
Distribution is assigned a value of 3
Markdown is assigned a value of 4
These oscillator values are plotted as colored circles, with different colors representing different phases. The color values are specified in RGB format.
Finally, the script plots horizontal lines as references for each of the four phases using the hline function. These lines are labeled and color-coded to match the corresponding oscillator circles. The lines have a linewidth of 1 and are solid in style.
If the oscillator moves from level 1 (Accumulation) to level 2 (Markup), this could indicate a potential bullish trend, as the market moves from a phase of accumulation to a phase of increasing prices.
Conversely, if the oscillator moves from level 3 (Distribution) to level 4 (Markdown), this could signal a potential bearish trend, signaling that the market has moved from a phase of distribution to a phase of declining prices.
While the Wyckoff Phases Oscillator can provide valuable insights on its own, it can also be used in conjunction with other technical analysis tools and indicators. For example, you might use it alongside a volume indicator to confirm signals, or with support and resistance levels to identify potential entry and exit points.
ATR profit and loss linesWhat is ATR?
Taking a candlestick, the following 3 transactions are calculated:
1-The difference between the high of the day and the low of the day
2-The difference between today's high and yesterday's close
3-The difference between today's low and yesterday's close
Atr takes the average of these 14-day candlesticks after making their calculations and it predicts how high or low a candle can go and these give us support and resistance helps with points
If you have noticed a rise in your chart and have no idea how high it will go, you can use Atr profit and loss lines.
The red zone is the stop point, the blue zones are the snow zones.
Must be used with macd. macd is validator.
There is an increase in your chart, you opened the atr profit and loss lines upwards and if macd gives you an increase, it is recommended that you enter the trade at that time. It is recommended to increase your loss line 1 step in the direction of profit every 2 profit breaks on atr profit and loss lines.
ATR Nedir?
Bir mum barı ele alınarak şu 3 işlem hesaplanır:
1-Günün yükseği ile günün düşüğü farkı
2-Günün yükseği ile dünün kapanışının farkı
3-Günün düşüğü ile dünkü kapanışın farkı
ATR ise 14 günlük bu mum barlarının hesaplarını yaptıktan sonra ortalamasını alır ve bir mumum ne kadar yükselip düşebileceği konusunda tahmin verir ve bunlar bize destek ve direnç noktaları konusunda yardımcı olur
Eğer grafiğinizde bir yükseliş farketmişseniz ne kadar yükseleceği konusunda fikriniz yoksa Atr kar zarar çizgilerini kullanabilirsiniz.
Kırmızı bölge durdurma noktası,mavi bölgeler kar bölgeleridir.
Macd ile birlikte kullanılmalıdır.macd doğrulayıcıdır.
Grafiğinizde yükseliş var,atr kar zarar çizgilerini yukarı yönlü açtınız ve macd size yükseliş veriyorsa işte o sırada işleme girmeniz tavsiye edilir.atr kar zarar çizgilerinde her 2 kar kırılımında bir zarar çizginizi kar yönünde 1 kademe arttırmanız önerilir
Bitcoin Limited Growth ModelThe Bitcoin Limeted Growth is a model proposed by QuantMario that offers an alternative approach to estimating Bitcoin's price based on the Stock-to-Flow (S2F) ratio. This model takes into account the limitations of the traditional S2F model and introduces refinements to enhance its analysis.
The S2F model is commonly used to analyze Bitcoin's price by considering the scarcity of the asset, measured by the stock (existing supply) relative to the flow (new supply). However, the LGS-S2F Bitcoin Price Formula recognizes the need for improvements and presents an updated perspective on Bitcoin's price dynamics.
Invalidation of the Normal S2F Model:
The normal S2F model has faced criticisms and challenges. One of the limitations is its assumption of a linear relationship between the S2F ratio and Bitcoin's price, overlooking potential nonlinearities and other market dynamics. Additionally, the normal S2F model does not account for external influences, such as market sentiment, regulatory developments, and technological advancements, which can significantly impact Bitcoin's price.
Addressing the Issues:
The LGS-S2F Bitcoin Price Formula introduces refinements to address the limitations of the traditional S2F model. These refinements aim to provide a more comprehensive analysis of Bitcoin's price dynamics:
Nonlinearity: The LGS-S2F model recognizes that the relationship between the S2F ratio and Bitcoin's price may not be linear. It incorporates a logistic growth function that considers the diminishing returns of scarcity and the saturation of market demand.
Data Analysis: The LGS-S2F model employs statistical analysis and data-driven techniques to validate its predictions. It leverages historical data and econometric modeling to support its analysis of Bitcoin's price.
Utility:
The LGS-S2F Bitcoin Price Formula offers insights for traders and investors in the cryptocurrency market. By incorporating a more refined approach to analyzing Bitcoin's price, this model provides an alternative perspective. It allows market participants to consider various factors beyond the S2F ratio alone, potentially aiding in their decision-making processes.
Key Features:
Adjustable Coefficients
Sigma calculation methods: Normal or Stdev
Credit:
The LGS-S2F Bitcoin Price Formula was developed by QuantMario, who has contributed to the field of cryptocurrency analysis through their research and modeling efforts.
TOP 4 STABLECOIN MARKET CAPIn the cryptocurrency market, there is a challenge: understanding the flow of stablecoins during market growth and downturns. It's difficult to grasp whether the market surge is due to a shift in funds from BTC or an influx of USD. Detecting the fluctuation in market capitalization of stablecoins helps investors gain a clearer perspective of market volatility.
Usage:
When there are fluctuations in the market capitalization, it is essential to combine observations of this indicator with other technical indicators.
EFFR Range VisualizerThis script takes the upper and lower target Effective Fed Funds Rate subtracted from 100 to allow the user to quickly visualize how these relate to STIR and Treasury markets.
Real Dominance//Due to incompliance with TV rules, I re-publish this indicator once again. Hope this time it's complaint.
Indicator shows dominance of main coin (BTC by default) after deduction of all stablecoins marketcaps and compares it to dominance that provides TradingView (BTC.D by default). The reason of writing this indicator is to deduct all stablecoins' caps from bitcoin dominance and show dominance without impact of other stablecoins. It means, that if crypto cap equals to, let's say 100, stablecoins' cap will be part of it (something between 10 and 20), but generally stablecoins are not crypto and it's caps are generally not limited, so we can't clearly see what is real dominance of BTC in compare with altcoins.
Notes:
1. dominance for timeframes lower than 1D could be calculated only on tariffs Pro+ or Premium (TV limitation)
2. you may change any and all tickers in indicator's setup menu
3. at the moment of publication (03.06.2023), TV doesn't offer market cap tickers for all stablecoins. Therefore in case it will be added in the future you may add it in the setup menu. There are placeholders for stablecoins that has market cap in amount of more than 5mil USD as of today.
Индикатор показывает доминацию главной монеты (по умолчанию BTC) за вычетом доли всех стейблкоинов в сравнении к доминации, которую показывает TradingView (по умолчанию BTC.D). Причиной написания данного индикатора является необходимость вычесть влияние стейблов на доминацию, так как важно смотреть доминацию именно в сравнении BTC/altcoins, и не учитывать стейблкойны, объем которых по большому счету не ограничен.
Особенности работы:
1. на тарифах кроме Pro+ и Premium, доминация может быть рассчитана только на дневном таймфрейме и выше (ограничения TradingView).
2. все тикеры, включая главную и сравниваемую монеты можно менять по желанию в настройках. Стиль линий настраивается на соответствующей вкладке в настройках.
3. к сожалению, на момент публикации индикатора (03.06.2023), TradingView предоставляет данные капитализации для ограниченного количества стейблкойнов. В настройки добавлены заглушки для последующего добавления других стейблкойнов. В список внесены монеты, капитализация которых на момент публикации индикатора составляла более 5 млн долларов.
Liquidity Proxy : ChinaThis is based on the 'Global Liquidity Proxy' as defined by Darius Dale.
GLP is comprised of:
* Central bank balance sheet
* Narrow money supply
* Foreign exchange reserves minus gold
This is an approximation based on the description above.
This indicator shows the global liquidity proxy for China.
The model, in terms of TradingView symbols is:
YoY change % of
CNCBBS + CNM1 + CNFER - CNGRES
The chart doesn't exactly match what Darius shows so his model is likely somewhat different.
RED : China liquidity index
GREEN : SSE composite index YoY change %
Altcoin ComparatorUse this indicator to compare an altcoin's ratio compared to Bitcoin (orange), the general altcoin market (blue), and the entire cryptocurrency market cap (yellow).
Bright colors indicate the altcoin is outperforming the crypto market while dull colors in imply it is under-performing.
Likewise, staying in the green implies sustained outperformance while staying in the red implies sustained under-perfrmance.
Oversold values imply the altcoin is expensive while overbought imply it is cheap.
Be sure to use market caps: ETH, SOL, ADA, etc. not ETHUSD, SOLUSDT, etc.
Sector/IndustryThis is a simple script that displays a symbol's sector and industry in a table at bottom right area of the chart.
Central Bank LiquidityCentral Bank Liquidity = Total value of the assets of all Federal Reserve Banks - Overnight Reverse Repurchase Agreements (RRP) - The Treasury General Account (TGA)
TradingView ticker arithmetic: FRED:WALCL-FRED:WTREGEN-FRED:RRPONTSYD
Valuation Metrics Table (P/S, P/E, etc.)This table gives the user a very easy way of seeing many valuation metrics. I also included the 5 year median of the price to sales and price to earnings ratios. Then I calculated the percent difference between the median and the current ratio. This gives a sense of whether or not a stock is over valued or under valued based on historical data. The other ratios are well known and don't require any explanation. You can turn off the ones you don't want in the settings of the indicator. Another thing to mention is that diluted EPS is used in calculations
US Market SentimentThe "US Market Sentiment" indicator is designed to provide insights into the sentiment of the US market. It is based on the calculation of an oscillator using data from the High Yield Ratio. This indicator can be helpful in assessing the overall sentiment and potential market trends.
Key Features:
Trend Direction: The indicator helps identify the general trend direction of market sentiment. Positive values indicate a bullish sentiment, while negative values indicate a bearish sentiment. Traders and investors can use this information to understand the prevailing market sentiment.
Overbought and Oversold Levels: The indicator can highlight overbought and oversold conditions in the market. When the oscillator reaches high positive levels, it suggests excessive optimism and a potential downside correction. Conversely, high negative levels indicate excessive pessimism and the possibility of an upside rebound.
Divergence Analysis: The indicator can reveal divergences between the sentiment oscillator and price movements. Divergences occur when the price reaches new highs or lows, but the sentiment oscillator fails to confirm the move. This can signal a potential trend reversal or weakening of the current trend.
Confirmation of Trading Signals: The "US Market Sentiment" indicator can be used to confirm other trading signals or indicators. For instance, if a momentum indicator generates a bullish signal, a positive reversal in the sentiment oscillator can provide additional confirmation for the trade.
Usage and Interpretation:
Positive values of the "US Market Sentiment" indicate a bullish sentiment, suggesting potential buying opportunities.
Negative values suggest a bearish sentiment, indicating potential selling or shorting opportunities.
Extreme positive or negative values may signal overbought or oversold conditions, respectively, and could precede a market reversal.
Divergences between the sentiment oscillator and price trends may suggest a potential change in the current market direction.
Traders and investors can combine the "US Market Sentiment" indicator with other technical analysis tools to enhance their decision-making process and gain deeper insights into the US market sentiment.
Rolling Risk-Adjusted Performance RatiosThis simple indicator calculates and provides insights into different performance metrics of an asset - Sharpe, Sortino and Omega Ratios in particular. It allows users to customize the lookback period and select their preferred data source for evaluation of an asset.
Sharpe Ratio:
The Sharpe Ratio measures the risk-adjusted return of an asset by considering both the average return and the volatility or riskiness of the investment. A higher Sharpe Ratio indicates better risk-adjusted performance. It allows investors to compare different assets or portfolios and assess whether the returns adequately compensate for the associated risks. A higher Sharpe Ratio implies that the asset generates more return per unit of risk taken.
Sortino Ratio:
The Sortino Ratio is a variation of the Sharpe Ratio that focuses specifically on the downside risk or volatility of an asset. It takes into account only the negative deviations from the average return (downside deviation). By considering downside risk, the Sortino Ratio provides a more refined measure of risk-adjusted performance, particularly for investors who are more concerned with minimizing losses. A higher Sortino Ratio suggests that the asset has superior risk-adjusted returns when considering downside volatility.
Omega Ratio:
The Omega Ratio measures the probability-weighted ratio of gains to losses beyond a certain threshold or target return. It assesses the skewed nature of an asset's returns by differentiating between positive and negative returns and assigning more weight to extreme gains or losses. The Omega Ratio provides insights into the potential asymmetry of returns, highlighting the potential for significant positive or negative outliers. A higher Omega Ratio indicates a higher probability of achieving large positive returns compared to large negative returns.
Utility:
Performance Evaluation: Provides assessment of an asset's performance, considering both returns and risk factors.
Risk Comparison: Allows for comparing the risk-adjusted returns of different assets or portfolios. Helps identify investments with better risk-reward trade-offs.
Risk Management: Assists in managing risk exposure by evaluating downside risks and volatility.
[TTI] Fed Net Liquidity Indicator📜 ––––HISTORY & CREDITS
The Fed Net Liquidity Indicator is a tool developed after reading Max Anderson's twitter thread. This indicator is based on the calculation of the Fed's balance sheet, the Treasury General checking account, and what banks are parking at the overnight repo window at the Fed. The net of these three components gives us the net liquidity available to the markets, which is considered the fuel behind market moves.
🎯 ––––WHAT IT DOES
The Fed Net Liquidity Indicator provides a visual representation of the net liquidity levels in the market. It plots the SPX along with blue shading that represents the net liquidity levels. It also includes risk on/risk off signals and a fair value line that measures whether the market is overbought or oversold compared to the net liquidity readings.
The indicator also includes two levels for overbought and oversold conditions. The "short/hedge" level indicates that the market is becoming overbought and it's time to reduce risk-on positions. The "euphoric" level indicates extreme overbought conditions and it's time to actively short the market or exit. On the other side, the "bounce" line indicates oversold conditions and a potential short-term pop, while the "capitulation" level indicates extreme oversold conditions and a potential for a significant bounce.
🛠️ ––––HOW TO USE IT
To use the Fed Net Liquidity Indicator, you first need to set it up on your chart. Once set up, you can use it to guide your trading decisions based on the net liquidity levels, risk on/risk off signals, and the fair value line.
👉Follow the net liquidity levels: The market generally follows the net liquidity. If the liquidity is increasing, the market tends to go up, and if the liquidity is decreasing, the market tends to go down.
👉Pay attention to risk on/risk off signals: These signals can help you understand the market environment and adjust your positions accordingly. A risk-on signal indicates a good time to expose yourself to the market and go long on risk assets like stocks and crypto. A risk-off signal indicates that it's time to exit the market, hedge your positions, or go short.
👉Use the fair value line: This line can help you determine whether the market is overbought or oversold compared to the net liquidity readings. If the market is rising steeply but the liquidity is not confirming that, it could indicate overbought conditions. Conversely, if the market is falling but the liquidity is not confirming that, it could indicate oversold conditions.
👉Consider the overbought and oversold levels: These levels can help you identify potential tops and bottoms in the market. If the market reaches the short/hedge level, it's time to reduce risk-on positions. If it reaches the euphoric level, it's time to actively short the market or exit. On the other side, if the market reaches the bounce line, it could indicate a potential short-term pop. If it reaches the capitulation level, it could indicate a potential for a significant bounce.
TTP NVT StudioNVT Studio is an indicator that aims to find areas of reversal of the Bitcoin price based on the extreme areas of Network Value Transaction.
Instructions:
- We recommend using it on INDEX:BTCUSD
- Use the daily or weekly timeframe
The indicator works as an oscillator and offers to visualisation modes.
1) Showing the short term oscillations of NVT showing signals in potential areas of reversal.
2) The actual value of NVT displayed. When in green is an area of value and in red when its overextended.
This indicator can be used based on the signals or based on breakouts of trend lines drawn in the oscillator mode.
Red/green dots: signal type 1 - extremes with confirmation, these might trigger late
Yellow/Orange: signal type 2 - extremes without confirmation, might trigger too soon
P/E RatioPlots the P/E Ratio with highest, lowest and average, as well as two ranges, 25-20 & 20-0 considered as the regular P/E Range
Range BreakerStrategy Description: Range Breaker
The Range Breaker strategy is a breakout trading strategy that aims to capture profits when the price of a financial instrument moves out of a defined range. The strategy identifies swing highs and swing lows over a specified lookback period and enters long or short positions when the price breaks above the swing high or below the swing low, respectively. It also employs stop targets based on a percentage to manage risk and protect profits.
Beginner's Guide:
Understand the concepts:
a. Swing High: A swing high is a local peak in price where the price is higher than the surrounding prices.
b. Swing Low: A swing low is a local trough in price where the price is lower than the surrounding prices.
c. Lookback Period: The number of bars or periods the strategy analyzes to determine swing highs and swing lows.
d. Stop Target: A predetermined price level at which the strategy will exit the position to manage risk and protect profits.
Configure the strategy:
a. Set the initial capital, order size, commission, and pyramiding as needed for your specific trading account.
b. Choose the desired lookback period to identify the swing highs and lows.
c. Set the stop target multiplier and stop target percentage as desired to manage risk and protect profits.
Backtest the strategy:
a. Set the backtest start date to analyze the strategy's historical performance.
b. Observe the backtesting results to evaluate the strategy's effectiveness and adjust the parameters if necessary.
Implement the strategy:
a. Apply the strategy to your preferred financial instrument on the TradingView platform.
b. Monitor the strategy's performance and adjust the parameters as needed to optimize its effectiveness.
Risk management:
a. Always use a stop target to protect your trading capital and manage risk.
b. Don't risk more than a small percentage of your trading capital on a single trade.
c. Be prepared to adjust the strategy or stop trading it if the market conditions change significantly.
Adjusting the Lookback Period and Timeframes for Optimal Strategy Performance
The Range Breaker strategy uses a lookback period to identify swing highs and lows, which serve as the basis for determining entry and exit points for long and short positions. By adjusting the lookback period and analyzing different timeframes, you can potentially find the best strategy configuration for each specific asset.
Adjusting the lookback period:
The lookback period is a critical parameter that affects the sensitivity of the strategy to price movements. A shorter lookback period will make the strategy more sensitive to smaller price fluctuations, resulting in more frequent trading signals. On the other hand, a longer lookback period will make the strategy less sensitive, generating fewer signals but potentially capturing larger price movements.
To optimize the lookback period for a specific asset, you can test different lookback values and compare their performance in terms of risk-adjusted returns, win rate, and other relevant metrics. Keep in mind that using an overly short lookback period may lead to overtrading and increased transaction costs, while an overly long lookback period may cause the strategy to miss profitable trading opportunities.
Analyzing different timeframes:
Timeframes refer to the duration of each bar or candlestick on the chart. Shorter timeframes (e.g., 5-minute, 15-minute, or 30-minute) focus on intraday price movements, while longer timeframes (e.g., daily, weekly, or monthly) capture longer-term trends. The choice of timeframe affects the number of trading signals generated by the strategy and the length of time each position is held.
To find the best strategy for each asset, you can test the Range Breaker strategy on different timeframes and analyze its performance. Keep in mind that shorter timeframes may require more active monitoring and management due to the increased frequency of trading signals. Longer timeframes, on the other hand, may require more patience as positions are held for extended periods.
Finding the best strategy for each asset:
Every asset has unique price characteristics that may affect the performance of a trading strategy. To find the best strategy for each asset, you should:
a. Test various lookback periods and timeframes, observing the strategy's performance in terms of profitability, risk-adjusted returns, and win rate.
b. Consider the asset's historical price behavior, such as its volatility, liquidity, and trend-following or mean-reverting tendencies.
c. Evaluate the strategy's performance during different market conditions, such as bullish, bearish, or sideways markets, to ensure its robustness.
d. Keep in mind that each asset may require a unique set of strategy parameters for optimal performance, and there may be no one-size-fits-all solution.
By experimenting with different lookback periods and timeframes, you can fine-tune the Range Breaker strategy for each specific asset, potentially improving its overall performance and adaptability to changing market conditions. Always practice proper risk management and be prepared to make adjustments as needed.
Remember that trading strategies carry inherent risk, and past performance is not indicative of future results. Always practice proper risk management and consider your own risk tolerance before trading with real money.
Fierytrading: Volatility DepthDear Tradingview community,
I'd like to share one of my staple indicators with you. The volatility depth indicator calculates the volatility over a 7-day period and plots it on your chart.
This indicator only works for the DAILY chart on BTC/USD.
Colors
I've color coded the indicator as follows:
- Red: Extreme Volatility
- Orange: High Volatility
- Yellow: Normal Volatility
- Green: Low Volatility
Red: extreme changes in price. Often during local tops and bottoms.
Orange: higher than average moves in price. Often before or after a "red" period. Often seen in the middle of bear or bull markets.
Yellow: normal price action. Often seen during early stage bull-markets and late stage bear-markets.
Green: very low price movement. Often during times of indecision. Once this indicator becomes green, you can expect a big move in either direction. Low volatility is always followed by high volatility.
In a long-term uptrend, a green period often signals a bullish break out. In a long-term downtrend it often signals a bearish break out.
How to use
Save the indicator and apply it to your chart. You can change the length in the settings, but it's optimized for 7 days, so no need to change it.
I've build in alerts for all 4 different volatility periods. In most cases, the low volatility alert is enough.
Good luck!
Rule of 40The rule of 40 is a popular metric for measuring the quality of SaaS companies. It measures growth and profitability. Companies are considered good if this sum is above 40.
It is the sum of the year over year sales growth and profit margin.
Rule of 40 = YoY sales growth + profit margin
Cobra's CryptoMarket VisualizerCobra's Crypto Market Screener is designed to provide a comprehensive overview of the top 40 marketcap cryptocurrencies in a table\heatmap format. This indicator incorporates essential metrics such as Beta, Alpha, Sharpe Ratio, Sortino Ratio, Omega Ratio, Z-Score, and Average Daily Range (ADR). The table utilizes cell coloring resembling a heatmap, allowing for quick visual analysis and comparison of multiple cryptocurrencies.
The indicator also includes a shortened explanation tooltip of each metric when hovering over it's respected cell. I shall elaborate on each here for anyone interested.
Metric Descriptions:
1. Beta: measures the sensitivity of an asset's returns to the overall market returns. It indicates how much the asset's price is likely to move in relation to a benchmark index. A beta of 1 suggests the asset moves in line with the market, while a beta greater than 1 implies the asset is more volatile, and a beta less than 1 suggests lower volatility.
2. Alpha: is a measure of the excess return generated by an investment compared to its expected return, given its risk (as indicated by its beta). It assesses the performance of an investment after adjusting for market risk. Positive alpha indicates outperformance, while negative alpha suggests underperformance.
3. Sharpe Ratio: measures the risk-adjusted return of an investment or portfolio. It evaluates the excess return earned per unit of risk taken. A higher Sharpe ratio indicates better risk-adjusted performance, as it reflects a higher return for each unit of volatility or risk.
4. Sortino Ratio: is a risk-adjusted measure similar to the Sharpe ratio but focuses only on downside risk. It considers the excess return per unit of downside volatility. The Sortino ratio emphasizes the risk associated with below-target returns and is particularly useful for assessing investments with asymmetric risk profiles.
5. Omega Ratio: measures the ratio of the cumulative average positive returns to the cumulative average negative returns. It assesses the reward-to-risk ratio by considering both upside and downside performance. A higher Omega ratio indicates a higher reward relative to the risk taken.
6. Z-Score: is a statistical measure that represents the number of standard deviations a data point is from the mean of a dataset. In finance, the Z-score is commonly used to assess the financial health or risk of a company. It quantifies the distance of a company's financial ratios from the average and provides insight into its relative position.
7. Average Daily Range: ADR represents the average range of price movement of an asset during a trading day. It measures the average difference between the high and low prices over a specific period. Traders use ADR to gauge the potential price range within which an asset might fluctuate during a typical trading session.
Utility:
Comprehensive Overview: The indicator allows for monitoring up to 40 cryptocurrencies simultaneously, providing a consolidated view of essential metrics in a single table.
Efficient Comparison: The heatmap-like coloring of the cells enables easy visual comparison of different cryptocurrencies, helping identify relative strengths and weaknesses.
Risk Assessment: Metrics such as Beta, Alpha, Sharpe Ratio, Sortino Ratio, and Omega Ratio offer insights into the risk associated with each cryptocurrency, aiding risk assessment and portfolio management decisions.
Performance Evaluation: The Alpha, Sharpe Ratio, and Sortino Ratio provide measures of a cryptocurrency's performance adjusted for risk. This helps assess investment performance over time and across different assets.
Market Analysis: By considering the Z-Score and Average Daily Range (ADR), traders can evaluate the financial health and potential price volatility of cryptocurrencies, aiding in trade selection and risk management.
Features:
Reference period optimization, alpha and ADR in particular
Source calculation
Table sizing and positioning options to fit the user's screen size.
Tooltips
Important Notes -
1. The Sharpe, Sortino and Omega ratios cell coloring threshold might be subjective, I did the best I can to gauge the median value of each to provide more accurate coloring sentiment, it may change in the future.
The median values are : Sharpe -1, Sortino - 1.5, Omega - 20.
2. Limitations - Some cryptos have a Z-Score value of NaN due to their short lifetime, I tried to overcome this issue as with the rest of the metrics as best I can. Moreover, it limits the time horizon for replay mode to somewhere around Q3 of 2021 and that's with using the split option of the top half, to remain with the older cryptos.
3. For the beginner Pine enthusiasts, I recommend scimming through the script as it serves as a prime example of using key features, to name a few : Arrays, User Defined Functions, User Defined Types, For loops, Switches and Tables.
4. Beta and Alpha's benchmark instrument is BTC, due to cryptos volatility I saw no reason to use SPY or any other asset for that matter.
