2024 - Median High-Low % Change - Monthly, Weekly, DailyDescription:
This indicator provides a statistical overview of Bitcoin's volatility by displaying the median high-to-low percentage changes for monthly, weekly, and daily timeframes. It allows traders to visualize typical price fluctuations within each period, supporting range and volatility-based trading strategies.
How It Works:
Calculation of High-Low % Change: For each selected timeframe (monthly, weekly, and daily), the script calculates the percentage change from the high to the low price within the period.
Median Calculation: The median of these high-to-low changes is determined for each timeframe, offering a robust central measure that minimizes the impact of extreme price swings.
Table Display: At the end of the chart, the script displays a table in the top-right corner with the median values for each selected timeframe. This table is updated dynamically to show the latest data.
Usage Notes:
This script includes input options to toggle the visibility of each timeframe (monthly, weekly, and daily) in the table.
Designed to be used with Bitcoin on daily and higher timeframes for accurate statistical insights.
Ideal for traders looking to understand Bitcoin's typical volatility and adjust their strategies accordingly.
This indicator does not provide specific buy or sell signals but serves as an analytical tool for understanding volatility patterns.
Bitcoinprediction
Leonid's Bitcoin Sharpe RatioThe Sharpe ratio is an old formula used to value the risk-adjusted return of an asset. It was developed by Nobel Laureate William F. Sharpe. In this case, I have applied it to Bitcoin with an adjustable look-back date.
The Sharpe Ratio shows you the average return earned after subtracting out the risk-free rate per unit of volatility (I've defaulted this to 0.02 ).
Volatility is a measure of the price fluctuations of an asset or portfolio. Subtracting the risk-free rate from the mean return allows you to understand what the extra returns are for taking the risk.
If the indicator is flashing red, Bitcoin is temporarily overbought (expensive).
If the indicator is flashing green, Bitcoin is temporarily oversold (cheap).
The goal of this indicator is to signal out local tops & bottoms. It can be adjusted as far as the lookback time but I have found 25-26 days to be ideal.
E9 PLRRThe E9 PLRR (Power Law Residual Ratio) is a custom-built indicator designed to evaluate the overvaluation or undervaluation of an asset, specifically by utilizing logarithmic price data and a power law-based model. It leverages a dynamic regression technique to assess the deviation of the current price from its expected value, giving insights into how much the price deviates from its long-term trend.
This indicator is primarily used to detect market extremes and cycles, often used in the analysis of long-term price movements in assets like Bitcoin, where cyclical behavior and significant price deviations are common.
This chart is back from 2019 and shows (From left to right) 2018 Bear market bottom at $3.5k (Dark Blue) , following a peak at 12k (dark red) before the Covid crash back down to EUROTLX:4K (Dark blue)
Key Components
Logarithmic Price Data:
The indicator works with logarithmic price data (ohlc4), which represents the average of open, high, low, and close prices. The logarithmic transformation is crucial in financial modeling, especially when analyzing long-term price data, as it normalizes exponential price growth patterns.
Dynamic Exponent 𝑘:
The model calculates a dynamic exponent k using regression, which defines the power law relationship between time and price. This exponent is essential in determining the expected power law price return and how far the current price deviates from that expected trend.
Power Law Price Return:
The power law price return is computed using the dynamic exponent
k over a defined period, such as 365 days (1 year). It represents the theoretical price return based on a power law relationship, which is used to compare against the actual logarithmic price data.
Risk-Free Rate:
The indicator incorporates an adjustable risk-free rate, allowing users to model the opportunity cost of holding an asset compared to risk-free alternatives. By default, the risk-free rate is set to 0%, but this can be modified depending on the user's requirements.
Volatility Adjustment:
A key feature of the PLRR is its ability to adjust for price volatility. The indicator smooths out short-term price fluctuations using a moving average, helping to detect longer-term cycles and trends.
PLRR Calculation:
The core of the indicator is the calculation of the Power Law Residual Ratio (PLRR). This is derived by subtracting the expected power law price return and risk-free rate from the logarithmic price return, then multiplying the result by a user-defined multiplier.
Color Gradient:
The PLRR values are represented visually using a color gradient. This gradient helps the user quickly identify whether the asset is in an undervalued, fair value, or overvalued state:
Dark Blue to Light Blue: Indicates undervaluation, with increasing blue tones representing a higher degree of undervaluation.
Green to Yellow: Represents fair value, where the price is aligned with the expected power law return.
Orange to Dark Red: Indicates overvaluation, with increasing red tones representing a higher degree of overvaluation.
Zero Line:
A zero line is plotted on the indicator chart, serving as a reference point. Values above the zero line suggest potential overvaluation, while values below indicate potential undervaluation.
Dots Visualization:
The PLRR is plotted using dots, with each dot color-coded based on the PLRR value. This dot-based visualization makes it easier to spot significant changes or reversals in market sentiment without overwhelming the user with continuous lines.
Bar Coloring:
The chart’s bars are colored in accordance with the PLRR value at each point in time, making it visually clear when an asset is potentially overvalued or undervalued.
Indicator Functionality
Cycle Identification : The E9 PLRR is especially useful for identifying cyclical market behavior. In assets like Bitcoin, which are known for their boom-bust cycles, the PLRR can help pinpoint when the market is likely entering a peak (overvaluation) or a trough (undervaluation).
Overvaluation and Undervaluation Detection: By comparing the current price to its expected power law return, the PLRR helps traders assess whether an asset is trading above or below its fair value. This is critical for long-term investors seeking to enter the market at undervalued levels and exit during periods of overvaluation.
Trend Following: The indicator helps users identify the broader trend by smoothing out short-term volatility. This makes it useful for both momentum traders looking to ride trends and contrarian traders seeking to capitalize on market extremes.
Customization
The E9 PLRR allows users to fine-tune several parameters based on their preferences or specific market conditions:
Lookback Period:
The user can adjust the lookback period (default: 100) to modify how the moving average and regression are calculated.
Risk-Free Rate:
Adjusting the risk-free rate allows for more realistic modeling of the opportunity cost of holding the asset.
Multiplier:
The multiplier (default: 5.688) amplifies the sensitivity of the PLRR, allowing users to adjust how aggressively the indicator responds to price movements.
This indicator was inspired by the works of Ashwin & PlanG and their work around powerLaw. Thank you. I hall be working on the calculation of this indicator moving forward to make improvements and optomisations.
Relative volume zone + Smart Order Flow Dynamic S/ROverview:
The Relative Volume Zone + Smart Order Flow with Dynamic S/R indicator is designed to help traders identify key trading opportunities by combining multiple technical components. This script integrates relative volume analysis, order flow detection, VWAP, RSI filtering, and dynamic support and resistance levels to offer a comprehensive view of the market conditions. It is particularly effective on shorter timeframes (M5, M15), making it suitable for scalping and day trading strategies.
Key Components:
1. Relative Volume Zones:
• The script calculates the relative volume by comparing the current volume with the average volume over a defined lookback period (volLookback). When the relative volume exceeds a specified multiplier (volMultiplier), it indicates a high volume zone, signaling potential accumulation or distribution areas.
• Purpose: Identifies high-volume trading zones that may act as significant support or resistance, indicating possible entry or exit points.
2. Smart Order Flow Analysis:
• The indicator uses Volume Delta (the difference between buying and selling volume) and a Cumulative Delta to detect order imbalances in the market.
• Order Imbalance is identified using a moving average of the Volume Delta (orderImbalance), which helps highlight hidden buying or selling pressure.
• Purpose: Reveals market sentiment by showing whether buyers or sellers dominate the market, aiding in the identification of trend reversals or continuations.
3. VWAP (Volume Weighted Average Price):
• VWAP is calculated over a default daily length (vwapLength) to show the average price a security has traded at throughout the day, based on both volume and price.
• Purpose: Provides insight into the fair value of the asset, indicating whether the market is in an accumulation or distribution phase.
4. RSI (Relative Strength Index) Filter:
• RSI is used to filter buy and sell signals, preventing trades in overbought or oversold conditions. It is calculated using a specified period (rsiPeriod).
• Purpose: Reduces false signals and improves trade accuracy by only allowing trades when RSI conditions align with volume and order flow signals.
5. Dynamic Support and Resistance Levels:
• The script dynamically plots support and resistance levels based on recent swing highs and lows (swingLookback).
• Purpose: Identifies potential reversal zones where price action may change direction, allowing for more precise entry and exit points.
How It Works:
• Buy Signal:
A buy signal is generated when:
• The price enters a high-volume zone.
• The price crosses above a 5-period moving average.
• The cumulative delta shows more buying pressure (cumulativeDelta > SMA of cumulativeDelta).
• The RSI is below 70 (not in overbought conditions).
• Sell Signal:
A sell signal is generated when:
• The price enters a high-volume zone.
• The price crosses below a 5-period moving average.
• The cumulative delta shows more selling pressure (cumulativeDelta < SMA of cumulativeDelta).
• The RSI is above 30 (not in oversold conditions).
• Dynamic Support and Resistance Lines:
Drawn based on recent swing highs and lows, these lines provide context for potential price reversals or breakouts.
• VWAP and Order Imbalance Lines:
Plotted to show the average traded price and highlight order flow shifts, helping to validate buy/sell signals.
How to Use:
1. Apply the Indicator:
Add the script to your chart and adjust the settings to match your trading style and preferred timeframe (optimized for M5/M15).
2. Interpret the Signals:
Use the buy and sell signals in conjunction with dynamic support/resistance, VWAP, and order imbalance lines to identify high-probability trade setups.
3. Monitor Alerts:
Set alerts for significant order flow events to receive notifications when there is a positive or negative order imbalance, indicating potential market shifts.
What Makes It Unique:
This script is unique because it combines multiple market analysis tools — relative volume zones, smart order flow, VWAP, RSI filtering, and dynamic support/resistance — to provide a well-rounded, multi-dimensional view of the market. This integration allows traders to make more informed decisions by validating signals across various indicators, enhancing overall trading accuracy and effectiveness.
Bitcoin wave modelBitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log (BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in prices ranging between 200,000 and 240,000 USD.
Enjoy the mathematical insights!
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
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.
MA Multiplier with FibonacciThis implementation of the "2-Year MA Multiplier" gives you some control over the indicator, you can change the multiplier from it's default of 5, you can change the lookback from it's default of 730 days and I've also added three fibonacci traces between the moving average and it's multiple that you can play with. Oh and you can also choose the data source ('close' or 'hl2' make most sense).
The formula for this indicator was created by Philip Swift.
Thanks to @Pladizow for pointing me to this indicator.
BTC Fibonacci DMA350 TrendlinesAdapted from Tim Graham's Code.
See Original Inspiring Article from Phillip Swift at: @positivecrypto
When looking into BITSTAMP:BTCUSD 1D data in spreadsheet. Historically, BTC Highs Hit (Simple Daily Moving Average 350 Days) DMA350 in reverse Fibonacci Sequence Order
2013 Hit DMA350*8 before All Time High (ATH)
2017 Hit DMA350*5 before ATH
I expect 2021 to hit DMA350*3 ATH. When BTC hits DMA350*3 ATH, I suggest selling!
Ori Bitcoin Mining ProfitabilityThis indicator shows Mining Profitability USD/Day for 1 THash/s. Have options to toggle line/trend view, log on/off and smoothing for line view.
🔗Blockchain Fundamentals - Bitcoin Post Halving Price Model🔗Blockchain Fundamentals - Bitcoin SFR / Halving Price Prediction Model
Description
This price model is based upon the work of PlanB (@100trillionUSD) which can be seen here: medium.com
He states "We can also model bitcoin price directly with Stock to Flow. The formula of course has different parameters, but the result is the same, 95% R2 and a predicted bitcoin price of $55,000 with SF 50 after May 2020 halving."
He was using monthly data on a weekly timeframe. I converted to a daily timeframe, and add in future price prediction by projecting the average number of blocks mined. You can use this along with the Stock to Flow Ratio indicator here .
Post halving price prediction currently stands at ~$62k based on this model.
👍 Enjoying this indicator or find it useful? Please give me a like and follow! I post crypto analysis, price action strategies and free indicators regularly.
💬 Questions? Comments? Want to get access to an entire suite of proven trading indicators? Come visit us on telegram and chat, or just soak up some knowledge. We make timely posts about the market, news, and strategy everyday. Our community isn't open only to subscribers - everyone is welcome to join.
For Trialers & Chat: t.me
🔗Blockchain Fundamentals - Bitcoin Velocity by Cryptorhythms🔗Blockchain Fundamentals - Bitcoin Velocity by Cryptorhythms
Description
The velocity of money is the rate at which money is exchanged in an economy. It is the number of times that money moves from one transaction to another. It also refers to how much a unit of currency is used in a given period of time. Simply put, it's the rate at which people spend currency. The velocity of money is usually measured as a ratio of gross national product (GNP) to a country's total supply of money, in traditional markets.
Here is the formula proposed by twitter user PositiveCrypto, implemented for you here on tradingview.
How does it relate to Bitcoin?
Is bitcoin trending towards savings or payments? This can help you decide. It is similar to Bitcoin Network Momentum, except this takes into account bitcoins increasing supply.
Low velocity implies HODLing and Speculation on future value. People looking at bitcoin as a longer term investment.
Higher velocity indicates currency changing hands faster. Perhaps as an indication of adoption pushing bitcoin towards a payment/transaction usage.
Opinions and Hypothesis
In the midst of the last bear market we saw velocity spike, perhaps as people gave up on investments and starting using it for payments.
As the 2017 bull run sucked in more buyers at higher and higher retail prices, velocity decreased, perhaps as those people did not want to sell at a loss.
As we entered the big dip in Nov 2018 velocity began increasing, as some capitulated and others were drawn into the market by lower prices.
Extras
I added in additional functionality so you can change the moving average from SMA to a few other choices (more MA's to choose from coming soon in future update). I also added a variable to change the length of said MA to your desired value so you may experiment. You can also chose to display as a line or area plot depending on preference.
👍 Enjoying this indicator or find it useful? Please give me a like and follow! I post crypto analysis, price action strategies and free indicators regularly.
💬 Questions? Comments? Want to get access to an entire suite of proven trading indicators? Come visit us on telegram and chat, or just soak up some knowledge. We make timely posts about the market, news, and strategy everyday. Our community isn't open only to subscribers - everyone is welcome to join.
For Trialers & Chat: t.me
