D-BoT Alpha Volume SpikeHello traders, Let me explain the code and provide an example of how to trade using this indicator.
The code you provided is a Pine Script indicator that combines multiple technical indicators, such as Supertrend, ADX, RSI, and MFI, to generate buy and sell signals. Here's a breakdown of the code:
User Settings:
The user can adjust parameters like overbought_limit, oversold_limit, volume_multiplier, volume_ma_length, volume_spike_multiple, lookback_period, and use_extremities_confirmation according to their preference.
Calculate Supertrend:
The Supertrend indicator is calculated using three different ATR lengths (supertrend_atr_period1, supertrend_atr_period2, supertrend_atr_period3) and corresponding factors (supertrend_factor1, supertrend_factor2, supertrend_factor3).
The supertrend_value1, supertrend_value2, and supertrend_value3 represent the Supertrend values, while trend_direction1, trend_direction2, and trend_direction3 indicate the trend direction (negative for downtrend, positive for uptrend).
Candle calculations:
The high and low values are checked to identify bullish and bearish candles based on specific conditions.
Volume Spikes:
Volume spikes are detected by comparing the current volume with a median volume over a specified lookback period.
If the volume exceeds a certain multiple of the median volume and the DI+ value is greater than the DI- value, an "up" signal is generated. Similarly, if the DI- value is greater than the DI+ value, a "down" signal is generated.
Additional Filters (RSI and MFI):
Relative Strength Index (RSI) and Money Flow Index (MFI) are used as additional filters.
The RSI and MFI parameters can be adjusted according to the user's preference.
The signals generated by the volume spikes are filtered based on RSI and MFI conditions.
Plotting:
The indicator plots shapes (triangles) to represent buy and sell signals.
The Supertrend lines are plotted using different colors and transparency levels based on the distance from the current price.
The "bodyMiddle" plot is used for filling the area between the Supertrend lines.
Example Trade Scenario:
Let's consider an example trade scenario using this indicator:
When the indicator generates an "up" signal (trendBuy = true), indicating a potential bullish trend, and all the confirmation conditions (RSI, MFI, Supertrend) are met, you can consider opening a long position.
Conversely, when the indicator generates a "down" signal (trendSell = true), indicating a potential bearish trend, and all the confirmation conditions are met, you can consider opening a short position.
Remember, this is just an example, and it's crucial to perform thorough analysis and consider other factors before making trading decisions. It's recommended to backtest the strategy, assess risk management, and apply appropriate position sizing techniques.
Please note that the code provided is a simplified version, and there might be additional factors and considerations specific to your trading strategy that are not included in this code. *******"I have also reviewed the following indicators, and the volume calculation approaches of my friends have been very helpful in creating this indicator: "Volume Spikes " © tradeforopp and "Volume Spikes & Growing Volume Signals With Alerts & Scanner" © FriendOfTheTrend."*******
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Enhanced Strategy (Buy/Sell Signals)The provided script is an enhanced strategy that combines multiple indicators to generate buy and sell signals. Here's a breakdown of its features and usage:
Indicators used:
1. Moving Averages (MA): It uses two moving averages, fast and slow, to identify trend direction.
2. Relative Strength Index (RSI): It measures the momentum and overbought/oversold conditions of the asset.
3. Moving Average Convergence Divergence (MACD): It indicates trend direction and potential trend reversals.
4. Stochastic Momentum Index (Stch Mtm): It identifies overbought and oversold conditions and potential reversals.
5. Awesome Oscillator: It helps to gauge the market momentum and potential trend changes.
How to use:
1. The strategy is designed to be used as a study on the TradingView platform.
2. Apply the script to your preferred chart and adjust the input parameters as desired.
3. The buy and sell signals will be plotted as green "Buy" and red "Sell" labels on the chart.
4. You can also observe the plotted indicators to gain insights into the market conditions.
Combination of indicators:
1. Buy Signal: The strategy generates a buy signal when the following conditions are met:
- The fast moving average crosses over the slow moving average (bullish crossover).
- RSI value is above the specified threshold (30 by default), indicating potential oversold conditions.
- MACD line is above the signal line, suggesting a bullish trend.
- Stch Mtm is above 50, indicating bullish momentum.
- The Awesome Oscillator is positive, implying bullish market sentiment.
2. Sell Signal: The strategy generates a sell signal when the following conditions are met:
- The fast moving average crosses under the slow moving average (bearish crossover).
- RSI value is below the specified threshold (100 - RSI threshold), indicating potential overbought conditions.
- MACD line is below the signal line, suggesting a bearish trend.
- Stch Mtm is below 50, indicating bearish momentum.
- The Awesome Oscillator is negative, implying bearish market sentiment.
Market conditions:
- The strategy aims to identify potential entry and exit points based on the combination of indicators.
- It can be used in various market conditions, but it's important to consider the overall market context, news events, and risk management principles.
- It's recommended to use this strategy as a tool for analysis and decision-making, and validate the signals with additional analysis before executing trades.
Please note that the effectiveness and profitability of any trading strategy can vary depending on various factors, including market conditions and individual trading preferences. It's always advisable to conduct thorough backtesting and consider risk management techniques before applying any strategy to live trading.
Volume Tick Analysis and Order Blocks [Tcs] | ALGOThe indicator has been developed to provide the most complete vision possible of liquidity areas, highly traded past price levels, and how volume tick analysis affects price action.
It helps to draw on all the areas that generate a price move, or market inefficiency.
The indicator has different features:
- ORDER BLOCKS : The indicator draws different kinds of order blocks on the chart.
• Real valuable order blocks - where the price reaction is more probable. It's define by a calculation of the quantity tick volume exchanged between bulls and bears on a price level, which can create a candle event, such as engulfing candles. For this motivation the order blocks plotted will be a real valuable area.
The threshold can be adjusted based on the strategy's needs, in particular this set up has been added to adapt the strategy on different kind of asset. For Cryptocurrency for example the best threshold are between 0.5 and 1. The lower the value, the fewer order blocks will be plotted, but they will be more valuable. It's possible to show the volume exchanged, the percentage, and who controlled the valuable area, bulls or bears, on these order blocks.
For a better visualization, the order block will change color (more transparent) after it will be violated for the first time, and it will be deleted once the price will break trough it.
All order blocks can be extend
GENERAL OB VISUALIZATION
EXAMPLE OF TRADES ON OB
It's also possible to plot the footprint of past and invalidated order blocks on the chart, which can help to draw lines for future valuable areas.
• Secondary order blocks are less valuable order blocks where the probability of a price reaction is less. Usually, they work for small retracements and are more useful for scalpers. the concept is the same as Primary order blocks but without a too restricted calculation of tick volume exchanged
• LIQUIDITY GRABS: Liquidity grabs are plotted on candles that try to invalidate an order block, but high volumes move them to the opposite direction. They happen when opposite players try to move the market in the opposite direction. They are calculated only on primary order blocks.
A good entry usually is when a liquidity grab appear, the price come in the liquidity grab area to fry liquidity and price close again in the liquidity grab area.
• VOLUME VSA: All candles with high and above-average volume are plotted on the chart for both bull and bear volume. It highlights more than average volume, high volume, and extreme volume with different colors. This can help to spot good entries or detect beginning/end of a trend. For example abnormal high volume at the end of a big price movement, in the same direction, can define the end of a trend. If same situation of abnormal high volume, but in the opposite direction of the trend, could define the beginning of a market inversion.
• FAIR VALUE GAPS: It highlights all the inefficiencies of market moves, which can be used as retracement or price return areas. Here, they can be adjusted based on how effective they are adjusting the volume threshold. Bulls and bears FVG are defined in different colors. More effective FVG are plotted in less transparent colors, and you will find three levels of effectiveness.
Both OB and FVG will change color once the price retraces on them, and they will be removed when they are invalidated.
Please note that this indicator is for educational purposes only and should not be used for trading without further testing and analysis.
Intraday Mean Reversion MainThe Intraday Mean Reversion Indicator works well on certain stocks. It should be used for day trading stocks but need to be applied on the Day to Day timeframe.
The logic behind the indicator is that stocks that opens substantially lower than yesterdays close, very often bounces back during the day and closes higher than the open price, thus the name Intraday Mean reversal. The stock so to speak, reverses to the mean.
The indicator has 7 levels to choose from:
0.5 * standard deviation
0.6 * standard deviation
0.7 * standard deviation
0.8 * standard deviation
0.9 * standard deviation
1.0 * standard deviation
1.1 * standard deviation
The script can easily be modified to test other levels as well, but according to my experience these levels work the best.
The info box shows the performance of one of these levels, chosen by the user.
Every Yellow bar in the graph shows a buy signal. That is: The stocks open is substantially lower (0.5 - 1.1 standard deviations) than yesterdays close. This means we have a buy signal.
The Multiplier shows which multiplier is chosen, the sum shows the profit following the strategy if ONE stock is bought on every buy signal. The Ratio shows the ratio between winning and losing trades if we followed the strategy historically.
We want to find stocks that have a high ratio and a positive sum. That is More Ups than downs. A ratio over 0.5 is good, but of course we want a margin of safety so, 0.75 is a better choice but harder to find.
If we find a stock that meets our criteria then the strategy will be to buy as early as possible on the open, and sell as close as possible on the close!
Supertrend - Optimised Exit We created a small script that will allow you to have a quick look into static SL/PT to choose from. This might save you time, replacing the manual search for optimal SL/PT.
We're checking signals of the strategy and computing its performance with a grid of SL/PT selected.
We used SuperTrend signals in this example, but it will be straightforward to integrate your signals.
In addition to total Return, we compute MAX Dd and Profit Factor. Other metrics can be implemented as well.
Thanks to @MUQWISHI for helping code it.
Disclaimer
Please remember that past performance may not indicate future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
MESThe Double Bollinger Bands strategy is a trend-following strategy that aims to identify high-probability trading opportunities in trending markets. The strategy involves using two sets of Bollinger Bands with different standard deviation values to identify potential entry and exit points.
Bollinger Bands are a technical analysis tool that consists of three lines plotted on a price chart: a simple moving average (SMA) in the middle, and an upper and lower band that are each a certain number of standard deviations away from the SMA. The standard deviation value determines the width of the bands, with a larger deviation resulting in wider bands.
In this indicator, the first set of Bollinger Bands is calculated using a length of 20 bars and a standard deviation of 2, while the second set uses a length of 20 bars and a standard deviation of 3. The bands are plotted on the price chart along with the SMA for each set.
The buy signal is generated when the price falls below the lower band of the second set of Bollinger Bands (the 3-standard deviation band) and then rises above the lower band of the first set (the 2-standard deviation band). This is interpreted as a potential reversal point in a downtrend and a signal to enter a long position.
Conversely, the sell signal is generated when the price rises above the upper band of the second set of Bollinger Bands and then falls below the upper band of the first set. This is interpreted as a potential reversal point in an uptrend and a signal to enter a short position.
To make it easier to identify buy and sell signals on the price chart, the indicator plots triangles above the bars for sell signals and below the bars for buy signals.
Overall, the Double Bollinger Bands strategy can be a useful tool for traders who want to follow trends and identify potential entry and exit points. However, as with any trading strategy, it is important to backtest and thoroughly evaluate its performance before using it in live trading.
Weis Wave-Wave TypesWeis Wave - Waves Types indicator
The Concept
This indicator has been created based on David's Weis theory of cumulative volume histograms but this indicator has been enhanced with additional wave types to be able to identify the following:
Visually identify the Effort vs Result concept (too much volume but small pip move or small volume too large pip move). Imbalance of Supply and Demand.
Be able to monitor how volume progresses within the wave, if it is increasing, decreasing or staying steady.
Identify easily the large volume waves using the emphasized volume algorithm to analyze the price reaction afterwards following the theory that Institutions participate on large volumes
What it does
This indicator draws cumulative histograms of 5 different wave types. Up swing histogram is when price goes up and down swing histogram is when price goes down. It adds the volume of each bar within the wave swing, it adds the pips of each bar within the wave swing , it adds the time of each bar within the wave swing, it measures if the volume rate is increasing or decreasing within the wave swing and emphasizes on larger volume volume waves by increasing their size for visual purposes.
How it does it
The length of each cumulative histogram is equal to each wave price swing. The price wave sensitivity can be adjusted by AutoSensitivity parameter (min value =2 and max value=11). The larger the number the more sensitive it is, which means more wave swings will be created. The selectable values for the wave type are: Volume, Pips, Time, Progressive Volume Rate or Emphasized Volume. Furthermore the width of the cumulative histogram bars can be adjusted as well as the color of the up and the down swings. Finally divider input values are available for volume and pip to decrease large numbers on the y-axis of the histograms.
Wave Type Detailed Explanation
Volume: the indicator adds the volume of each bar within the price wave swing and creates a cumulative histogram
Pips: the indicator adds the bar distance from open to close and creates a cumulative histogram of the net pip movement of the price swing
Time: adds the time of each bar within the price wave swing and creates a cumulative histogram
Progressive Volume Rate (PVR): measures the volume rate within each wave (if volume is increasing or decreasing or staying steady as the wave progresses)
Emphasized Volume: the indicator adds the volume of each bar within the price wave swing and creates a cumulative histogram but contains an algorithm that emphasizes the large waves.
How to Use
Draw Support/Resistance and Fib - Monitor carefully the cumulative histograms at these levels. Usually supply and demand imbalance happens at this level.
First and most important of all adjust AutoSesnsitivity to get your swings correct. Getting the correct swings means waves are catching the tops and bottoms of each price wave swings.
Then identify potential trades by:
1. Comparison of cumulative Volume histogram vs Pip histogram which makes the concept of Wyckoff "Effort versus Result" identifiable, lot's of volume with small pip move = lot's of effort vs with small result. Supply and Demand imbalance.
2. Monitor Progressive Volume Rate histogram which measures if the volume rate is increasing, decreasing or remains steady within the price wave swing. This histogram indicates more or less participation as price increases or decreases within the specific wave. For example increase of volume rate as price goes up could mean more participation which could mean that sellers might be entering. Also the opposite is valid increasing volume rate as price goes down could mean that buyers are entering.
3. Emphasized Volume waves, provide a visual emphases on large volume waves only, useful for traders that like to trade with high volume trends and for traders that believe that in large volume waves large institutes participate. Trade with price trend but also with the volume trend concept.
What makes it unique
This indicator is an advance cumulative wave histogram because apart the regular volume histogram and apart form using each wave type individually to make a decision it provides more confidence and becomes more powerful when confluence is used combining the other wave types and by using the strategies mentioned above to a higher probability trade. Some examples are shown below
Example of Effort vs. Result Concept
Example of Progressive Volume Rate
Example of Emphasized Volume
Net Unrealized Profit/Loss (NUPL)Indicator Overview
This indicator is derived from Market Value and Realized Value, which can be defined as:
Market Value: The current price of Bitcoin multiplied by the number of coins in circulation. This is like market cap in traditional markets i.e. share price multiplied by number of shares.
Realized Value: Rather than taking the current price of Bitcoin, Realized Value takes the price of each Bitcoin when it was last moved i.e. the last time it was sent from one wallet to another wallet. It then adds up all those individual prices and takes an average of them. It then multiplies that average price by the total number of coins in circulation.
By subtracting Realized Value from Market Value we calculate Unrealized Profit/Loss.
Unrealized Profit/Loss estimates the total paper profits/losses in Bitcoin held by investors. This is interesting to know but of greater value is identifying how this changes relatively over time.
To do this we can divide Unrealized Profit/Loss by Market Cap. This creates Net Unrealized Profit/Loss, sometimes referred to as NUPL, which is very useful to track investor sentiment over time for Bitcoin.
Relative Unrealised Profit/Loss is another name used for this analysis.
How To View The Chart
The key principle of this tool is in the ratio between market cap and Bitcoin investors taking profit.
When market cap rises much faster than profit taking we see that the market is overheating, one could say due to investor greed (red band). For the strategic investor such times have historically been favourable to take profit.
We can break down different percentages of Bitcoin Relative Unrealized Profit/Loss to determine what stage of the market we are in. This can be advantageous for the long term strategic investor.
Created By
Tamas Blummer, Tuur Demeester and Michiel Lescrauwaet
Joel Greenblatt Magic FormulaJoel Greenblatt Magic Formula. I always wanted to make this.
The Indicator shows 3 values.
ROC,EY,SUM.
ROC= Return On Capital.
EY=Earnings Yield
SUM= Addition of Two.
Formula:
ROC=EBIT / (Net Working Capital + Net Fixed Assets).
EY = EBIT / Enterprise value
Enterprise Value=(Market value of equity + Net Interest-bearing debt)
To implement the strategy, investors start by identifying a universe of stocks, typically large-cap or mid-cap companies that trade on a major stock exchange. Next, they rank the stocks based on their ROC and EY. The companies with the best combination of these two metrics are considered the best investments (based on this ranking).
For example, a stock that ranks 10th on EY and 99th on ROIC gets a value of 109. The two ranks are simply added together and all stocks are ranked on the sum of the two ranks. The stocks with the lowest values are best.
All credits to "The Little Book That Beats The Market" by Joel Greenblatt
The Magic Formula strategy is a stock selection method popularized by Joel Greenblatt’s book The Little Book That Beats the Market.
It involves ranking companies based on Two factors:
A high return on capital and A high Earnings Yield.
The companies with the best combination of these two metrics are considered the best investments. The strategy aims to find undervalued companies with strong financials that have the potential for high returns over the long term.
Multi-Time Period Chart[1] 3 overlays w/ Halfbacks These are 3 High-Low ranges that uses the code of TradingView's built-in Multi-Time Period Chart indicator as well as adds on optional midpoint (or "halfback") to the overlays. Finally, there are labels offset on the right margin that indicate the open price for each of those timeframes. One thing I adjusted is that range of each timeframe is omitted. This is because the original TV indicator's boxes have their right edge completely covering the wicks (Thus, the title for this indicator). This script has plenty of utility, but it designed specifically with the STRAT (Rob Smith) methodology in mind.
CPR with inside candle, Pivot Points and 4EMA The CPR trading strategy is a technical analysis approach that combines multiple indicators to determine potential price levels and trading opportunities. The strategy uses three main components: Inside Candles, Pivot Points, and the 4EMA.
Inside Candles: The Inside Candle pattern is a candlestick pattern where the current candle has a lower high and a higher low than the previous candle. This pattern can indicate a period of consolidation or indecision in the market and can signal a potential reversal or continuation of the trend.
Pivot Points: Pivot Points are technical indicators that use the previous day's price data to calculate key levels of support and resistance for the current trading day. These levels can act as potential areas of buying or selling pressure and can help traders identify potential entry and exit points.
4EMA: The 4EMA is a short-term Exponential Moving Average that tracks the average price of an asset over the previous four periods. This indicator is used to help identify short-term trends in the market and can signal potential buying or selling opportunities.
To apply the CPR strategy, traders first look for Inside Candles on their chart, indicating a period of consolidation or indecision in the market. Next, they identify the Pivot Points for the current trading day, which can act as potential areas of support or resistance. Finally, traders use the 4EMA to confirm the direction of the trend and potential entry or exit points.
For example, if an Inside Candle forms at a Pivot Point level and the 4EMA is indicating an uptrend, this could be a potential buying opportunity. Conversely, if an Inside Candle forms at a Pivot Point level and the 4EMA is indicating a downtrend, this could be a potential selling opportunity.
CPR Weekly Variable Weekday SellerGood afternoon traders,
This is a script I built for option selling, in attempt to have a high success rate. This is pretty much the same as my other one titled "CPR Option Selling Strategy." The difference is this one is strictly for Weeklies, with a variable weekday to expiry. I've had many requests to have a weekly that would end on Thursday, so here it is. Just select the date for expiry of the option, then it will calculate a "weekly" option set, using the the same set up as the traditional M-F weekly CPR information, except for offset for the weekday in question.
So for expiry dates for options on Thursday, you would choose "Thursday" in the parameters and it will calculate using Fri through Thu data for the pivot timeframes.
The rest is like this...
The gist of how it works:
It uses the opening or close of the current chart's timeframe opening bar when referenced against a "weekly" timeframe determined by the week ending weekday chosen for the central pivot range ( CPR ).
Using that comparison, this script calculates an option to sell: put, call, or iron condor. It will calculate a call value using an average of the CPR central pivot and the max value of the prior higher timeframe's high or R1 (whichever is higher.)
It does the same for the put side, but uses the higher timeframe's low or S1 (whichever is lower.)
It will use the option on the other side of the source (open or close) of the CPR as the "option in play."
Settings:
There are many settings, most are simply "viewable" settings, and probably self explanatory, others, not so much:
"Source for Trigger" - this is the value used on the "opening bar," such as the close. This value is the one compared to the Central Pivot Range in determining whether to sell a call (if the source is lower,) sell a put (if the source is higher,) or an iron condor if it's in the CPR .
"Show Historical Win/Loss Percentages" - this shows a table in the bottom right of the W/L percentages for the current ticker and settings. Used for a quick glance at historical success rates.
Example use (OLD EXAMPLE):
An example use (which I completed last week) on the chart referenced in this share: I sold a put-spread for $0.90, selling a 590 and buying a 570 strike in the middle of the week. I was looking at an hourly timeframe chart with a weekly pivot timeframe for the strategy.
Obviously, making only $0.90 on a $20 spread, there is a lot more to lose than to make, but I did some other analysis to go with it, so I felt safe, and I had a stop set for $1.50. So it worked, along with 3 other plays I did, very similar, and if that "Historical Win/Loss Percentage" is accurate, which I am fairly certain it is, I felt good about it.
The key all comes down to what you sell it for, right? That piece only you can determine. :)
Happy trading and enjoy,
Deuce
WillyCycle Oscillator&DoubleMa/ErkOzi/"This code creates a technical analysis indicator used to calculate and visualize the WillyCycle oscillator and double moving average indicators on the price of a financial asset. The functionality can be summarized as follows:
*Calculate the WillyCycle oscillator: The WillyCycle is an oscillator calculated based on the highest and lowest values of an asset. This oscillator is used to measure overbought or oversold conditions of the asset.
*Calculate the double moving average: The double moving average helps determine trends by calculating the short-term and long-term moving averages of asset prices.
*Use the WillyCycle oscillator and double moving average indicators together: The WillyCycle oscillator is combined with the double moving averages to provide a clearer indication of overbought and oversold conditions.
*Visualize the indicator with color coding: The indicator is color-coded to show overbought and oversold conditions. Additionally, line and background colors are changed to make the indicator more readable.
Many parameters can be adjusted on the indicator: The indicator can be customized and modified by the user. For example, the period of the WillyCycle oscillator and the lengths of the double moving averages can be adjusted."
The strategy is based on two indicators - the WillyCycle oscillator and the double moving average. The WillyCycle oscillator measures overbought and oversold conditions of the asset based on its highest and lowest values. The double moving average calculates short-term and long-term moving averages of the asset's price, which can help identify trends.
The WillyCycle oscillator and the double moving average are combined in this strategy to provide a clearer indication of overbought and oversold conditions. When the WillyCycle oscillator indicates that the asset is oversold and the short-term moving average crosses above the long-term moving average, it may signal a buy opportunity. Conversely, when the WillyCycle oscillator indicates that the asset is overbought and the short-term moving average crosses below the long-term moving average, it may signal a sell opportunity.
To make it easier for traders to read and interpret the indicator, color-coding is used to indicate overbought and oversold conditions. The user can also customize the indicator by adjusting parameters such as the period of the WillyCycle oscillator and the lengths of the double moving averages.
*ıt provides successful buy and sell signals for price reversals.
*You can open counter trades in overbought and oversold areas by following the averages.
Mason’s Line IndicatorThe Macon Strategy is an idea conceived by Didier Darcet , co-founder of Gavekal Intelligence Software. Inspired by the Water Level, an instrument used by masons to check the horizontality or verticality of a wall. This method aims to measure the psychology of financial markets and determine if the market is balanced or tilting towards an unfavorable side, focusing on the behavioral risk of markets rather than economic or political factors.
The strategy examines the satisfaction and frustration of investors based on the distance between the low and high points of the market over a period of one year. Investor satisfaction is influenced by the current price of the index and the path taken to reach that price. The distance to the low point provides satisfaction, while the distance to the high point generates frustration. The balance between the two dictates investors’ desire to hold or sell their positions.
To refine the strategy, it is important to consider the opinion of a group of investors rather than just one individual. The members of a hypothetical investor club invest successively throughout the past year. The overall satisfaction of the market on a given day is a democratic expression of all participants.
If the overall satisfaction is below 50%, investors are frustrated and sell their positions. If it is above, they are satisfied and hold their positions. The position of the group of investors relative to the high and low points represents the position of the air bubble in the water level. Market performance is measured day by day based on participant satisfaction or dissatisfaction.
In conclusion, memory, emotions, and decision-making ability are closely linked, and their interaction influences investment decisions. The Macon Strategy highlights the importance of the behavioral dimension in understanding financial market dynamics. By studying investor behavior through this strategy, it is possible to better anticipate market trends and make more informed investment decisions.
Presentation of the Mason’s Line Indicator:
The main strategy of this indicator is to measure the average satisfaction of investors based on the position of an imaginary air bubble in a tube delimited by the market’s highs and lows over a given period. After calculating the satisfaction level, it is then normalized between 0 and 1, and a moving average can be used to visualize trends.
Key features:
Calculation of highs and lows over a user-defined period.
Determination of the position of the air bubble in the tube based on the closing price.
Calculation of the average satisfaction of investors over a selected period.
Normalization of the average satisfaction between 0 and 1.
Visualization of normalized or non-normalized average satisfaction levels, as well as their corresponding moving averages.
User parameters:
Period for min and max (days) : Sets the period over which highs and lows will be calculated (1 to 365 days).
Period for average satisfaction (days) : Determines the period over which the average satisfaction of investors will be calculated (1 to 365 days).
Period for SMA : Sets the period of the simple moving average used to smooth the data (1 to 1000 days).
Bubble_value : Adjustment of the air bubble value, ranging from 0 to 1, in increments of 0.025.
Normalized average satisfaction : Option to choose whether to display the normalized or non-normalized average satisfaction.
Please note that the Mason’s Line Indicator is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Correlation prix [SP500, TESLA, BTCBefore you see this post I want to thank all the TradingView team. Every day that passes I learn better and better to use Pine script and I owe this to all those who publish and to the philosophy of TradingView. Thanks from Amos
This trading indicator compares the prices of the S&P 500 Index (SP500), Tesla (TSLA), and Bitcoin (BTC) to find correlations between them. To make the prices of SP500 and Tesla comparable to the price of Bitcoin, the indicator multiplies the closing price of Tesla by 114 and the closing price of the S&P 500 Index by 5.6.
In this way we can superimpose the prices on the BTC chart and see what happens.
Average BTC price/ tesla price = 114, so if we multiply the tesla price by 114 times we can superimpose it on the BTC price
At average BTC/SPX price = 5.6, also in this case we multiply the price of SPX by 5.6 to overlay the graph and see any correlations.
The indicator then calculates the average price between SP500 and Tesla, using the formula (SP500 + Tesla) / 2. This calculation creates a new line on the chart that represents the average price between these two assets.
The BTC_SP_TE variable is then calculated as the average of the closing price of Bitcoin and the previously calculated average price of SP500 and Tesla, using the formula (Btc + SP_TE) / 2. This calculation creates another line on the chart that represents the average price between Bitcoin and the previously calculated average between SP500 and Tesla.
The idea behind calculating these averages is to find correlations and patterns between the prices of these assets, which can help identify potential trading opportunities. By comparing the average prices of different assets, the trader can look for trends and patterns that might not be apparent when looking at each asset individually.
The indicator plots these prices on a chart and fills the area between them with either green or fuchsia, depending on which one is higher. The strategy suggests buying Bitcoin when the average price of SP500 and Tesla is higher than the current price of Bitcoin, and selling when it is lower.
To add visual cues to the trading strategy, the indicator uses the plotchar function to display a small triangle below the chart when it detects a potential buying opportunity. This is done with the following parameters:
Value: BTC_SP_TE < Btc and Btc > Btc1 and Btc1 > Btc , which is a logical expression that checks whether the average price of SP500 and Tesla is less than the current price of Bitcoin (BTC_SP_TE < Btc), and whether the current price of Bitcoin is higher than the price 10 bars ago (Btc > Btc1 ) and higher than the price on the previous bar (Btc1 > Btc ).
Text: "Moyen BTC_SP_Te", which is the text to display inside the marker.
Symbol: "▲", which is the symbol to use for the marker. In this case, it is a small triangle pointing upwards.
Location: location.belowbar, which specifies that the marker should be placed below the bar.
I hope this is an example of how to create an indicator on TradingView, remember that correlations do not always last, it is possible that when you see the graph this correspondence no longer exists, do your studies and get inspired.
Economic Data Trading alerts - CPI, Interest rate, PPI, etcDescription:
This indicator is designed to alert based on user-selected economic data for Europe, the US, and Japan. It allows users to define their preferred economic data points and trade direction based on the change in the economic data compared to the previous value.
you can use the strategy to automate economic data trading.
Key Features:
Choose from various economic data points for Europe, the US, and Japan.
Customize trade direction based on whether the economic data is above or below the previous value.
Define entry conditions based on user preferences.
Visualize trade entries on the chart.
Display a table showing the results of executed trades.
Please note that this strategy is provided for educational purposes only and should not be considered as financial advice. Always do your own research and use proper risk management when trading.
The indicator is BETA please make sure to test it before using it.
IMPORTANT: you need to be aware of the fundmentals because the regime changes and markets react to every release of data differently.
NewCopter📊 Indicator overview!
The indicator's strategy is based on calculations that are displayed on the chart based on price or volume.
Indicator uses a customizable volume threshold to filter out low volume candle and only display those with significant volume.
The algorithm analyzes market data and sets an entry/exit signal.
The key point of the indicator is reverse trades.
After the algorithm analyzes the current characteristics of the market, an entry signal is placed on the chart.
So whether you're a novice or experienced trader, indicator can help you stay ahead of the game and make more informed trading decisions.
As a result, the trader can be sure that the signal is based on data analysis.
A long or short position can be stopped either at a profit or at a small
loss without compromising the potential profit.
Signals without redrawing
📌Management of risks.
The market is unstable, and it is impossible to know what the future holds for it.
The only way to manage risk. You can limit the loss by setting a stop loss of 1% from the entry point.
Take profit is recommended to set with a ratio of 1:1, 1:2,1:3, with partial fixation of 40%, 30%, 30%!
We recommend fixing positions in parts. The signal in the opposite direction will be when the volume exits.
❕ To match the risk per trade, we recommend not entering with high leverage.
Trade only the amount you are willing to lose.
With increased volatility in the market and flat movement , the indicator can give many signals.
After a strong fall or rise, we recommend not to open positions, because.
high probability of flat movement.
✅Recommendations for the indicator!
Reverse transactions, the indicator shows where to buy-sell, sell-buy.
Entry / exit is carried out on the next candle after the candle with a signal (buy / sell)
Timeframes up to 1 hour (inclusive) are used, you can also use a higher timeframe.
Main trading pairs BTC BNB BIT
You can also trade other pairs, but you NECESSERY do a back test of the indicator.
⚙️!Technical part
The indicator is based on the EMA 20 and EMA 200 moving averages.
Which determine the current trend and the trend on higher timeframes.
the basic idea is that when we combine both we can see trend of the current and the past linear when they cross each other and from this we can make signals
Assuming that past shorter trend has the value of resistance or threshold values, so cross of current linear of those points can show if the trend is to buy or to sell by signals seen in the arrows .
So past and present mix and give us the future.
need to solve issue when market goes sideways but it easy to see how the trend look by the signals
It is also based on the open and close of past days, weeks, months.
The pivot high function calculates the pivot high, which is an important step in detecting bullish structures in the market.
The function also determines the swing state (high or low) of the current candle and returns the calculated swing values.
RSI are used.
RSI is a classic oscillator built on the basis of calculating the relative rate of change in asset prices
over a given period.
Additional tools: volume and volatility .
🗯Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
And remember that past results in no way guarantee future results.
✔️If you already have your own strategy, you can use it along with the indicator.
Enjoy trading with our indicator.
MFE & MAE ToolThis is a simple implementation of the MFE/MAE Tool for TradingView.
It's a quite powerful tool and pretty useful in systematic trading, but I don't see many trader using it these days.
It's created for EMA cross, but you can easily change it to use your own signals.
What is MAE/MFE Tool
MAE stands for Maximum Adverse Excursion - Worst P&L during the trade
MFE stands for Maximum Favorable Excursion - Best P&L during the trade
The idea is pretty simple. We take only signals without any position management or exits and measure the best/worst P&L for the next X bars after the signal was.
The primary use case for it is to understand how good your signals are .
If you'll add complicated money management tools, exits, and SL/PT to your strategy, it brings quite a lot of noise. After that, it's pretty tricky to understand if your signals bring much information about future price movements. In other words, bad money management can ruin good signals, and you might discard the entire strategy without knowing that. So this is why I think it's important to check the quality of your signals separately.
Another simple way to use it is to estimate where to put SL/PT
In this example, we're computing MAE/MFE in percent. We're plotting it both on the chart and computing some statistics based on it. This is why it's pretty easy to get a quick understanding of what is your SL/PT should be.
MAE/MFE tool consists of a:
Chart - it displays a point for every signal. Long/Short trades can have different colors. On hover you'll see details for this signal.
Table with stats - we're computing basic metrics for these Signals like average/min/median/max MAE/MFE, number of trades, and how many trades hit selected SL and PT. Stats are also separated by the side so you can see performance separately for longs and shorts.
The indicator is highly customizable, you can configure:
Bars you want to use to compute MAE/MFE
Side selection
SL and R:R
Styling of the chart
Position and style of the table
Parameters for the EMA
EMA cross and its parameter were selected randomly, so don't estimate to see a great performance here.
MFE/MAE tool is a pretty powerful concept. At some point, I'll create an entire article in my blog with more examples and descriptions.
Thanks to @MUQWISHI for helping code it.
Disclaimer
Please remember that past performance may not indicate future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Grenblatt Magic FormulaThe magic formula is an investing strategy created by Joel Greenblatt that focuses on finding the best price to buy certain companies in order to maximize returns. When Greenblatt coined the term magic formula investing, his portfolio had a return of 24% from 1998 to 2009.
This means that $10,000 invested at 24% for the period would have turned into just over $1 million. A fund based on the S&P 500 index for the same period would have turned that $10,000 into just under $75,000.1
Note
Bigger returns matter, especially over long periods, due to the power of compounding.
Others who ran their own experiments were not able to duplicate Greenblatt's high returns but still yielded positive results. As a result, investing experts agree that the strategy of magic formula investing outperforms the indexes. In most cases, though, it doesn't seem to beat indexes by as much as Greenblatt indicated when he introduced the concept in his book, The Little Book That Beats the Market.
There are two ratios in the magic formula. The first is the earnings yield: EBIT /EV. This is earnings before interest and taxes divided by enterprise value.A simpler and more common version of this ratio is earnings /price. Greenblatt prefers EBIT over earnings , because EBIT more accurately compares companies with different tax rates. EV is preferred to share price because EV also factors in the company's debt. Therefore, EBIT /EV provides a better picture of overall earnings than earnings /price.
The second ratio is return on capital, which is EBIT /(Net Fixed Assets + Working Capital)
The first ratio looks at earnings before interest and taxes compared to enterprise value. The second ratio focuses on the earnings relative to tangible assets. Many assets listed on the balance sheet depreciate over time as their usefulness is used up. These types of assets are called "fixed assets."
Net fixed assets are fixed assets minus all the accumulated depreciation and any liabilities associated with the asset. This gives a more accurate sense of the real value of a company's assets, compared to just looking at the total asset number on the balance sheet . Working capital is also part of this ratio and is current assets minus current liabilities. This gives a picture of whether the company is likely able to continue operations in the short term.
While the two ratios in the magic formula look small, they actually are computing a lot of data about the inner workings of a company, including:
Earnings
Interest
Tax rates
Equity price
Debt
Depreciation of assets
Current assets
Current liabilities
Broadening Formations [TFO]This indicator highlights deviations from broadening formations (or megaphone patterns). Deviations from broadening ranges can often foreshadow reversals, especially in consolidation phases. These deviations are highlighted via trendlines that change color when tested, and also have the option to be alerted.
These broadening formations are heavily used with "The Strat" and can add confluence when looking for reversals within higher timeframe points of interest.
Moon Phases + Daily, Weekly, Monthly, Quarterly & Yearly Breaks█ Moon Phases
From LuxAlgo description.
Trading moon phases has become quite popular among traders, believing that there exists a relationship between moon phases and market movements.
This strategy is based on an estimate of moon phases with the possibility to use different methods to determine long/short positions based on moon phases.
Note that we assume moon phases are perfectly periodic with a cycle of 29.530588853 days (which is not realistically the case), as such there exists a difference between the detected moon phases by the strategy and the ones you would see. This difference becomes less important when using higher timeframes.
█ Daily, Weekly, Monthly, Quarterly & Yearly Breaks
This indicator marks the start of the selected periods with a vertical line that help with identifying cycles.
It allows to enable or disable independently the daily, weekly, monthly, quarterly and yearly session breaks.
This script is based on LuxAlgo and kaushi / icostan scripts.
Moon Phases Strategy
Year/Quarter/Month/Week/Day breaks
Month/week breaks
Market Interest ZoneGeneral description
The Market Interest Zone (MI Zone) indicator is designed to facilitate market analysis and meet the needs of most traders by building zones that can act as support or resistance.
The logic of each MI Zone is based on the culminating increase in volume (the analysis of such volume is done by comparing the volume of each candle with the SMA plotted for a certain period with the input volume data). This logic is not very useful in the middle of a pulse, so by comparing the OHLC of candles, the indicator builds such zones only on local pulse extremes. The indicator also has a built-in super trend indicator that acts as a trend filter. We have compared many technical indicators that can help filter zones, but in our opinion, super trend shows the best results due to more flexible settings compared to moving average. Each drawn Japanese candlestick is an independent zone from which you can open a position with a limit order and close a position, depending on the trader's usual risk management.
In this version of the indicator, only the D1 timeframe is available, but it is enough for long-term trades
The indicator has two modes:
Trend/Reversal - in which absolutely all zones are displayed;
Trend - which displays only those zones that have passed the filter in the direction of the current trend;
Opening a position with a market order when a zone of interest appears is not part of the strategy's logic, as it increases the commission and limits the trading potential. However, if you understand the market context, then such an entry with a market order can be realized.
In cases when the candle that formed the zone is quite volatile and has a large spread, it is permissible to place a limit order for 50% of this zone.
Examples of using a trading strategy
As we wrote earlier, each Japanese candlestick drawn is an independent zone that can be worked with without additional conditions and understanding of the context. The MI Zone appears under certain conditions, when the second candlestick closes after the zone itself. After that, you can place a limit order at the high/low of this zone (depending on the direction) + a protective stop order on the opposite side of the zone.
Simple Limit Entry in Trend/Reverse Mode:
Simple Limit Entry in Trend Mode:
Retest Limit Entry in Trend/Reverse Mode:
Mirror Retest Limit Entry in Trend/Reverse Mode:
Risk management strategy
Fixing positions is recommended when the RR reaches 1:3 to 1:5. It is also possible to split a position, the second part of which will be fixed at more global levels.
In the above examples, position fixation is shown exclusively at global levels. In real trading, we recommend closing part of the position when local levels are reached.
Also, when RR 1:1 is reached, it is recommended to move the stop loss to breakeven.
Conclusion
It is important to understand that this logic can have different meanings depending on the financial instrument used. Therefore, we recommend performing a basic backtest of the methods of use and risk management parameters before using the indicator directly.
Flying Dragon Trend IndicatorFlying Dragon Trend Indicator can be used to indicate the trend on all timeframes by finetuning the input settings.
The Flying Dragon Trend family includes both the strategy and the indicator, where the strategy supports of selecting the optimal set of inputs for the indicator in each scenario. Highly recommended to get familiar with the strategy first to get the best out of the indicator.
Flying Dragon Trend plots the trend bands into the ribbon, where the colours indicate the trend of each band. The plotting of the bands can be turned off in the input settings. Based on the user selectable Risk Level the trend pivot indicator is shown for the possible trend pivot when the price crosses the certain moving average line, or at the Lowest risk level all the bands have the same colour. The trend pivot indicator is not shown on the Lowest risk level, but the colour of the trend bands is the indicator instead .
The main idea is to combine two different moving averages to cross each other at the possible trend pivot point, but trying to avoid any short term bounces to affect the trend indication. The ingenuity resides in the combination of selected moving average types, lengths and especially the offsets. The trend bands give visual hint for the user while observing the price interaction with the bands, one could say that when "the Dragon swallows the candles the jaws wide open", then there is high possibility for the pivot. The leading moving average should be fast while the lagging moving average should be, well, lagging behind the leading one. There is Offset selections for each moving average, three for leading one and one for the lagging one, those are where the magic happens. After user has selected preferred moving average types and lengths, by tuning each offset the optimal sweet spot for each timeframe and equity will be found. The default values are good enough starting points for longer (4h and up) timeframes, but shorter timeframes (minutes to hours) require different combination of settings, some hints are provided in tooltips. Basically the slower the "leading" moving average (like HMA75 or HMA115) and quicker the "lagging" moving average (like SMA12 or SMA5) become, the better performance at the Lowest risk level on minute scales. This "reversed" approach at the minute scales is shown also as reversed colour for the "lagging" moving average trend band, which seems to make it work surprisingly well.
The Flying Dragon Trend does not necessarily work well on zig zag and range bounce scenarios without additional finetuning of the input settings to fit the current condition.
