OHLC ToolOHLC Tool allows you to display Current or Historical OHLC Values as horizontal lines that extend to the right on your chart.
Features
Variable Lookback to display a specific historical bar's values. Default = 1 (Previous Candle)
Customizable Timeframe to view HTF Candle values.
Custom Line Colors, Styles, and Thicknesses.
Price Scale Value Display Capability.
For displaying the line values and labels on the price scale you will need to enable:
"Indicator and financials name labels"
and
"Indicator and financials value labels"
These options are found in the Price Scale Menu under Labels. Price Scale Menu > Labels
When you do this you will notice your other indicator values will also be on the price scale,
if you wish to disable these, go to the indicator settings under the "Style" Tab, Uncheck the "Labels on price scale" box.
Indicator Settings > Style > "Labels on price scale"
Enjoy!
Komut dosyalarını "半导体设备ETF" için ara
Big Poppa Code Strat & Momentum Strategy IndicatorThis indicator is a combination of a few things in order to work with a unique trading style gleaned from Callme100k, jrgreatness, TrustMyLevels , FaithInTheStrat, Rob Smith and Saty Mahajan.
This Indicator is created to help you day trade using, ATR Fibonacci Levels, Price Action and Momentum.
It displays Fibonacci Levels Based on ATR to indicate when a security is 0.236, 0.382 +- the Days Open, +- the Days Open, 0.618 +- the Days Open and 1.0 +- Days Open.
To understand this script you need to understand
Average True Range (ATR)
1 Bar Inside Bar
2 Bar Outside Bar (Break either the top or bottom)
3 Bar Engulfing Bar
Strat Setups - 212, 322, 312
Fibonacci - 0.236, 0.382, 0.618, 1.0
Moving Averages
A Trend is considered bullish when (green)
Current Price is greater than the Fast EMA Value (8)
Fast EMA is greater than PIVOT EMA Value (21)
Pivot EMA is greater than SLOW EMA Value (34)
OR Hull is trending up and the Price is above the Volume Weighted Moving Average and price is above VWAP
A trend is considered Bearish when (red)
Current Price is less than the Fast EMA Value (8)
Fast EMA is less than PIVOT EMA Value (21)
Pivot EMA is less than SLOW EMA Value (34)
OR Hull is trending down and the Price is below the Volume Weighted Moving Average and price is below VWAP
If these conditions are not met then the Momentum is in Conflict (orange)
The Momentum band will match the color of the current trend
The table that is present can be turned off at any time lets you see
1) If Moving Averages are showing bullish, bearish or in conflict
2) If There us Time Frame Continuity, (if 5 min up, are all the other timeframes up also)
3) How much of the ATR have we moved on the day
4) Are we in Call or Put range for the day based on ATR Fib Levels
The Ideal situation for entering a call
1) Momentum is Green
2) FTFC on Green
3) A Strat Actionable Signal is present
4) You are in the call range, 0.236 - 0.618 ATR + the Price
5) The ATR still has room, I.e only 50% of the ATR has been run already
Ideal situation from entering a put
1) Momentum is red
2) FTFC on Red
3) A Strat Actionable Signal is present
4) You are in the put range, 0.236 - 0.618 ATR - the Price
5) The ATR still has room, I.e only 50% of the ATR has been run already
Exit the trade for these reasons you entered (for profit or loss)
1) ATR has no more room
2) FTFC is now in conflict
3) Momentum has shifted
Take Profit when
1) You reach a new ATR Level 0.618, 1.0 , -0.618, -1, etc
Passive Stop Loss
1) Open Price if you are aggressive
2) Next ATR Level Down or Up
Feel free to take profit and leave runners
This script does not give signals, you should do your own research, I am not a financial advisors, I am simply applying principles of seasoned veterans to code. You make all decisions about how you buy, sell and trade. The creator of this script makes no promises and takes no responsibility for your personal trading.
To research the methods described above look up
Rob Smith : The Strat
Saty Mahajan : ATR Levels
Fibonacci
Using the HULL Moving Average
Exponential Moving Averages
VWAP
VWMA
Remaining ATR [vnhilton]ATR levels can be used on a trading day to look for overextensions beyond the average, where you can look to take profits. Remaining ATR is calculated as the current day range subtracted by the previous day ATR. RATR is then plotted away from the high & low lines. All lines (except for the day open) are dynamic, so RATR lines will move according to how much RATR remains.
Note: This indicator only works on intraday timeframes
(FEATURES)
- Works on either RTH or ETH sessions
- Select Day ATR period, & 3 multipliers that will be applied to RATR values away from respective intraday high & low
- Extend current lines to the right
- Show recent lines only
- Change line style, colours within & out the intraday range, & thickness
- Change label offset, size, & colours within & out the intraday range
- Hide RATR lines & labels when within intraday range
- Plot fill between lines (note: RATR plot fills are from their lines to the intraday high & low, so there'll be overlapping)
To show more lines in the past, go to higher intraday timeframes.
Same chart & timeframe as above but on RTH session only.
Simple Momentum and Trend, Fixed PnL Strategy for SPY 1D [SR]This strategy uses an ATR rule to assess momentum and a TSI rule to assess bullish or bearishness
It has a fixed stop at 50 points, and fixed take profit at 300 pips
It provides a very satisfyingly smooth equity line with a max drawdown below 5% and realized profit over 200%
This is the initial version as I work out optimizations and add plots to the chart based on the strategy's actions.
I would love to get the community's feedback and help as I'm new. Not sure how to limit the date range of the backtest to make it more realistic. I'm also not certain how to plot it best.
Z-Score Buy and Sell SignalsHello everyone!
Happy Holidays, Merry/Happy Christmas!
Here is my Christmas gift to you to show my appreciation of your support and engagement over the past year!
This is the Z-Score Buy and Sell Signal indicator!
How it works:
It works by looking at the Z-Score of an equities close price and looking for previous areas over reversals over the defined period of time.
It also looks at areas that are overbought or oversold (manifested by Z-Scores greater than or less than 2 Standard Deviations away) and displays them as bar colour changes.
Historic reversals are signaled with buy and/or sell signals.
Oversold is signaled with a green bar colour change (colour can be customaized).
Overbought is signaled with an orange bar colour change.
How to use it:
You can use it with support resistance or other indicators. You can use this on both the larger and small timeframes, depending on the style of trader you are.
You can modify the input length to look back on shorter or longer periods.
As a general rule from my experience using it, if you are using the shorter timeframes (i.e. 1 minute tfs), its best to look back between 50 and 75 candles for most equities.
If you are looking at the larger timeframes (i.e. Daily, 1 to 2 hour, etc.) its best to set the input value to between 500 to 800.
But, as always, you should check to ensure the indicator is providing correct signals by reviewing the previous signals to ensure that they adequate identified reversals.
It is also best not to use this alone as your sole indicator. It is meant to be supplementary to other indicators/support resistance/chart patterns you are using to guide your trades. This will not replace good TA and a good understand of the stock and its likely trajectory.
As always, please feel free to share your comments/feedback/questions and recommendations below.
As always, I do customary tutorial videos for my indicators, so please see below for an in-depth video tutorial should you want to see it in action:
Otherwise, happy holidays everyone! And all of the best over this Christmas weekend to you and your loved ones!
Moving Average Support and ResistanceThis indicator takes a moving average, creates an envelope, and analyzes how frequently the moving average and its deviations act as areas of support or resistance. Using this information, you can determine how strong the moving average is as a support or resistance. For example, if the 200 SMA with a 5% range and 1% buffer has an S/R ratio of 1:1.5, then the 200 SMA is acting as resistance more frequently than support. This indicator uses the "buffer" as an envelope extension. The best way to think of this buffer is to envision areas where false breakouts and stop runs may occur. Use this indicator to experiment with different moving averages, ranges, and buffers to find the best combination for your trading style.
Slope Normalized (SN)Introduction:
The Normalized Slope script is a technical indicator that aims to measure the strength and direction of a trend in a financial market. It does this by calculating the slope of the source data series, which can be any type of data (such as price, volume, or an oscillator) over a specified length of time. The slope is then normalized, meaning it is transformed to a scale between -1 and 1, with 0 representing a flat trend.
Methodology:
The Normalized Slope script uses an exponential smoothing function to smooth the source data series. The smoothing factor, or alpha, can be adjusted by the user through the input parameter "Pre Smoothing".
Next, the script calculates the slope of the smoothed data series by finding the average difference between the current value and the values of the previous "Length" periods. This slope is then normalized using a function that scales the data to a range of -1 to 1, with 0 representing a flat trend. The normalization function takes the minimum and maximum values of the slope, calculates the difference between them, and then scales the data to the range of -1 to 1.
The normalized slope is then smoothed again using another exponential smoothing function with a user-adjustable smoothing factor (the "Post Smoothing" input parameter). A center line representing a flat trend can also be plotted on the chart by enabling the "Center Line" input parameter. Additionally, the user can choose to display bounds at the -1 and 1 levels by enabling the "Bounds" input parameter.
Conclusion:
The Normalized Slope script provides traders with a visual representation of the strength and direction of a trend in a financial market. It can be used as a standalone indicator or in combination with other technical analysis tools to help traders make informed trading decisions.
Root Mean Square (RMS)The Root Mean Square (RMS) is a statistical measure of the magnitude of a set of numbers. It is a type of mean, or average, that is calculated by taking the square root of the sum of the squares of a set of numbers, divided by the number of items in the set. The RMS is often used to measure the magnitude of a time-varying signal, such as a waveform or a time series data.
The indicator takes in two input parameters: the source data and the length of the RMS window. The source data can be any time series data, such as the closing price of a security, and the length parameter determines the number of data points used in the RMS calculation.
The script begins by declaring the RMS indicator function and specifying that it should be plotted as an overlay on the chart. The function takes in two parameters: source and length. The source parameter is the time series data that will be used in the RMS calculation, and the length parameter determines the number of data points to include in the calculation.
Next, the script defines the RMS function using a single line of code. The function calculates the RMS by taking the square root of the sum of the squares of the source data, divided by the length. This is done using the built-in math.sqrt, math.sum, and math.pow functions, which respectively calculate the square root, sum, and power of a set of numbers.
Finally, the script defines the source and length input parameters using the input.source and input.int functions. The source parameter is defined as the closing price of the security, and the length parameter is defined as an integer with a default value of 20.
The RMS indicator implemented in this script can be used to measure the magnitude of a time-varying signal. By adjusting the length parameter, users can control the number of data points included in the RMS calculation and fine-tune the indicator to their specific needs.
Imbalance Detector [LuxAlgo]This indicator detects and highlights market imbalances alongside a dashboard returning information about their frequency of occurrence and their fill percentage. Imbalances included in this script are Fair Value Gaps (FVG), Opening Gaps (OG) and Volume Imbalances (VI).
Alerts are available for the occurrences of all market imbalances.
Settings
Imbalances
Each imbalance has the same settings layout:
Imbalance: Enable/disable the detection of the specific imbalance.
Min Width: If enabled, requires the imbalance area width to be greater than the specified value. This minimum width can be expressed in points, percentages or ATR multiples.
Extend: Extend imbalances by a specified number of bars.
Dashboard
Show Dashboard: Enable/disable the dashboard on the chart.
Dashboard Location: Location of the dashboard on the chart.
Dashboard Size: Size of the dashboard.
Usage
Market imbalances are part of the many concepts available to price action traders and highlight areas where there is a disparity between supply and demand.
It is common to see price come back to these areas and traders often use them as supports and resistances but also as targets.
Details
The script can detect three distinct types of imbalances described below.
Fair Value Gaps
Fair Value Gaps (FVG) are three candle formations characterized by a gap between the wicks of the non-adjacent candles in the formation.
A bullish FVG is characterized by a gap between the current price low and the 2 bars anterior price high, and a bearish FVG is characterized by a gap between the current price high and the 2 bars anterior price low.
Opening Gaps
Opening Gaps (OG) are imbalances characterized by non-existent activity within a specific price range.
A bullish OG occurs when the current price low is greater than the previous high, a bearish OG occurs when price high is lower than the previous price low.
Opening Gaps primarily occur in closing markets, as such they are less common in the cryptocurrency market.
Most of the time an Opening Gap will also be accompanied by a Fair Value Gap, in order to avoid clutter the indicator will not detect Fair Value Gaps if Opening Gaps are enabled and if an Opening Gap has been detected
Volume Imbalances
Volume Imbalances (VI) are characterized by a price discontinuity between the opening price and previous close, but unlike Opening Gaps we do not see nonexistent activity within a certain price range.
A bullish VI occur when both the opening and closing prices are superior to the previous closing price, with the current price low overlapping the previous price high. A bearish VI occur when both the opening and closing prices are inferior to the previous closing price, with the current price high overlapping the previous price low.
Because Volume Imbalances can occur excessively on markets with frequent gaps, we make use of an additional condition for filtering out less significant imbalances. Bullish VI's will require the previous price high to be lower than the opening price, while bullish VI's will require the previous price low to be higher than the opening price.
Welford Bollinger Bands (WBB)The Welford method is an algorithm for calculating the running average and variance of a series of numbers in a single pass, without the need to store all the previous values. It works by maintaining an ongoing running average and variance, updating them with each new value in the series. The running average is updated using a simple formula that adds the new value to the previous average, weighed by the number of values that have been processed so far. The variance is updated using a similar formula that takes into account the deviation of the new value from the running average.
The Welford method has several advantages that make it a good fit for use in calculating Bollinger Bands. First, it is more numerically stable than other methods, as it avoids accumulating round-off errors and can handle large numbers of data points without overflow or underflow. This is important when working with financial data, which can contain large price movements and wide ranges of values.
Second, the Welford method is well-suited for use in real-time or streaming data scenarios where all the data may not be available upfront. This is useful in the context of Bollinger Bands, which are often used to identify trend changes and trading opportunities in real-time, as the bands are updated with each new data point.
Finally, the Welford method is simple and efficient, making it easy to implement and fast to compute. This is important when creating technical indicators and trading strategies, as performance is often a critical factor.
Overall, the Welford method is a reliable and efficient way to calculate the running average and variance of a series of numbers, making it a good fit for use in calculating Bollinger Bands and other technical indicators.
Modified TradingView's Up/Down Volume [vnhilton]
When plotting columns, histograms, etc. You'll notice that the indicator does not stick to the bottom of the pane. To fix this, you need another indicator (we'll call this 'placeholder') in the same pane as this indicator. Pin the placeholder indicator to the left scale, & pin the main indicator to the left scale. Then, pin the placeholder indicator to scale A, & finally the main indictor to the right scale.
Note: On the daily timeframes & higher, the up/down volume isn't accurate. Therefore, I've added a feature where you can toggle on the main indicator to disappear & only show ordinary total volume similar to the TradingView volume indicator.
The original code belongs to TradingView. This is a modified indicator that displays the down volume above the up volume similar to the volume profile. Also includes a moving average using the total volume, & a feature to display ordinary volume to solve the up/down inaccuracies on the daily timeframe & higher.
Noise GateThis Pine Script code defines an indicator called "Noise Gate" which filters out "noise" from a given signal. The indicator takes four input parameters: source, length, ratio, and level. The source parameter specifies the source data for the indicator (e.g., close prices), the length parameter specifies the length of a moving average, the ratio parameter specifies the attenuation ratio, and the level parameter specifies the threshold for attenuating the signal.
The core of the indicator is the noise_gate function, which takes three input parameters: signal, ratio, and level. The signal parameter represents the input signal that needs to be filtered. The ratio parameter specifies the amount by which the signal will be attenuated (reduced in amplitude) if it falls below the level parameter. The level parameter is a threshold that determines whether the signal will be attenuated or not.
The noise_gate function first calculates the absolute value of the signal using the math.abs() function. This is done because the filtering only applies to the magnitude of the signal, not its sign (positive or negative value).
The function then checks if the absolute value of the signal is above the level threshold using an if statement. If it is, the signal is returned as is. If the absolute value of the signal is below the level threshold, the function calculates a value called soft_knee_ratio using the formula 1 - (level - abs_signal) / level. This value represents the amount by which the signal will be attenuated. The signal is then reduced in amplitude by this soft_knee_ratio and the resulting value is returned as the output of the function.
The noise_gate function applies the transformation symmetrically to both positive and negative values of the signal parameter. This is because the transformation only depends on the absolute value of the signal, not its sign. The transformation first calculates the absolute value of the signal using the math.abs() function and then applies the filtering based on the magnitude of the signal. The sign of the signal is not taken into account in this process. As a result, the transformation is applied symmetrically to both positive and negative values of the signal.
The noise_gate function can be a valuable tool for anyone looking to filter out noise or unwanted variations from a signal. It is flexible and easy to use, and can be applied to a wide range of situations where signal noise reduction is needed. For example, it can be used to smooth out financial time series data or to remove background noise from an audio recording.
The noise_gate function in this code has been modified to include an additional input parameter called knee_type, which allows the user to specify whether to use a hard knee or a soft knee. A hard knee means that the compressor triggers simply at the threshold, whereas a soft knee means that the compressor triggers smoothly, gradually increasing the attenuation as the signal falls further below the threshold.
To use a hard knee, the user can set the knee_type parameter to "hard". To use a soft knee, the user can set the knee_type parameter to "soft". The default value for the knee_type parameter is "soft", so if the user does not specify a value for knee_type, the noise_gate function will use a soft knee by default.
The noise_gate function includes a check for the value of the knee_type parameter and applies the appropriate knee type. If the knee_type parameter is set to "hard", the function applies a hard knee by simply triggering at the threshold and dividing the input by the ratio if the signal falls below the threshold. If the knee_type parameter is set to "soft" (or if it is not specified and the default value is used), the function applies a soft knee by gradually increasing the attenuation of the signal as it falls further below the threshold.
The noise_gate function can be a valuable tool for anyone looking to filter out noise or unwanted variations from a signal. It is flexible and easy to use, and can be applied to a wide range of situations where signal noise reduction is needed. For example, it can be used to smooth out financial time series data or to remove background noise from an audio recording.
Ratio_between_two_symbolsThis script plots the ratio of two symbols to show the relative strength between in order to determine which is the stronger security
Volatility Adjusted EMA (VAEMA) The pine script shown in the code is an indicator that calculates the volatility-adjusted exponential moving average (VAEMA) of a given data series. The VAEMA indicator uses a variable alpha value in the EMA calculation, with the alpha value being inversely proportional to the volatility of the data. This allows the VAEMA indicator to provide a more accurate representation of the data's trend. The user can specify the length of the data series, the alpha value, and whether to invert the proportionality of the alpha value in the calculation. The resulting VAEMA line is plotted on the chart.
inverted alpha proportions
long lookback regular
long lookback inverted
Buyer to Seller Volume (BSV) Indicator As promised, here is the buyer to seller volume indicator!
About it/How it works:
The indicator tracks buying and selling volume. It does it simplistically but effectively simply by looking at red vs green candles and averaging out the volume of each respective candle.
It uses the SMA of buying/selling and overall volume to track buyers to sellers and also display the average volume traded over a designated period of time.
Legend:
Green lines = buying volume
Red lines = selling volume
Yellow lines = SMA over designated period of time (user input defined, default is 14 candles).
Buyers are shown in green and sellers are shown in red:
How to Use it:
Default, the indicator goes to 1 Day, 14 candle period.
My preference personally is to use to have it go to "chart" but you can view any time period on the chart that you want and designate the time period of volume you want to view independently.
This can be used for:
1. Identify trends: When buying or selling volume is above selling volume and above the SMA, you know that this persuasively supports a bullish trend. Inverse for the opposite (see below):
2. To identify fakeouts and whether there is volume backing a move:
3. To identify potential changes in trends via a cross:
Its also a great reference when you are unsure of a move. This indicator literally just saved me from wrongfully shorting the FOMC bear flag today:
Probably many other uses you can find, but these are the things I like to use it for!
As always, I have posted a tutorial video for your reference:
As always though, if you have any questions, comments or suggestions for the indicator, please share them below!
Safe trades and best of luck to all!
Triple Exponential Hull Moving Average THMAThis pine script calculates the triple exponential Hull moving average (THMA) of a given data series. The THMA is a type of moving average that is calculated using the exponential moving average (EMA) of the data. In this script, the ema() function is used to calculate the EMA of the data three times, with different lengths for each calculation. The resulting value is the THMA of the data. The script also plots the THMA on a chart, using a green color for upward trends and a red color for downward trends. The length of the moving average and the alpha parameter used in the EMA calculation can be specified by the user as input parameters.
A trader may use this pine script to help identify trends in the stock market. By plotting the triple exponential Hull moving average (THMA) of the data on a chart, the trader can quickly see whether the market is trending up or down, and how strong the trend is. This can help the trader make informed decisions about when to buy and sell stocks. Additionally, the script allows the user to customize the length of the moving average and the alpha parameter used in the EMA calculation, which can be useful for analyzing different time frames and making more accurate predictions.
Vector MagnitudeThe pine indicator is a script for technical analysis of stock market data. It calculates the direction and magnitude of a moving average, and plots the result on a chart. The length of the moving average is specified by the user as an input parameter. The script uses the simple moving average (SMA) function from the TA-Lib library to calculate the average of the data. It then determines the direction of the vector by comparing the current value to the average. If the current value is greater than the average, the direction is set to 1. If it is less than the average, the direction is set to -1. Otherwise, the direction is set to 0. The magnitude of the vector is calculated using the Pythagorean theorem. The output is the magnitude of the vector, with the sign indicating the direction.
A trader may use this pine script to help identify trends in the stock market. By plotting the direction and magnitude of the moving average on a chart, the trader can quickly see whether the market is trending up or down, and how strong the trend is. This can help the trader make informed decisions about when to buy and sell stocks. Additionally, the script allows the user to customize the length of the moving average, which can be useful for analyzing different time frames and making more accurate predictions.
Daily Reset CWEMA/CWTEMAThis Pine Script code defines an indicator called "Daily Reset CWEMA" that plots a custom weighted moving average on a chart. The indicator takes three inputs: a source series (usually the close price of a security), a length parameter that specifies the number of periods over which the moving average is calculated, and a style parameter that specifies the type of moving average to use (either a custom weighted exponential moving average (CWEMA) or a custom weighted triple exponential moving average (CWTEMA)).
The code first checks the current time frame and adjusts the length parameter accordingly. If the time frame is daily, weekly, or monthly, the length parameter is used as-is. Otherwise, the length is set to the number of bars since the last day change, unless this value is less than the length parameter, in which case the length is set to the number of bars since the last day change.
The ema(), tema(), wma(), cwema(), and cwtema() functions are then defined. The ema() function calculates the exponential moving average of the source data using the number of bars since the last day change as the length. The tema() function calculates the triple exponential moving average of the source data using the number of bars since the last day change as the length. The wma() function calculates the weighted moving average of the source data using the given weights and the number of bars since the last day change as the length. The cwema() and cwtema() functions are similar to the wma() function, but use the ema() and tema() functions to calculate the moving average values instead of the source data directly.
Finally, the ma() function is defined, which takes the source data, length, and style as inputs and calls the appropriate moving average function based on the style parameter. The result of this function is then plotted on the chart.
Suggested by: @hjsjshs
Cumulative Weighted Triple Exponential Moving Average (CWTEMA)This Pine Script code defines an indicator called "CWTEMA" that plots a custom weighted triple exponential moving average (TEMA) on a chart. The indicator takes two inputs: a source series (usually the close price of a security) and a length parameter that specifies the number of periods over which the moving average is calculated.
The code first defines a tema() function, which calculates the TEMA for a given series of data and a given length. The function uses the ta.ema() function from the ta library to compute the exponential moving average of the source data, and then applies the triple exponential moving average formula to calculate the TEMA.
The wma() function is then defined, which calculates the weighted moving average of a given series of data using a set of weights. This function computes the weighted sum of the source data using the given weights, then divides this sum by the sum of the weights to calculate the weighted moving average.
Finally, the cweema() function is defined, which calculates the custom weighted TEMA. This function first computes the weights for each value in the moving average using the given length parameter, then calls the wma() and tema() functions to calculate the weighted moving average using the TEMA values. The cweema() function is then plotted on the chart.
Gann Spiral / Square of 9The Gann Spiral, more commonly known as the Square of 9 is one of the most well known tools that Gann used. Today, it is most commonly used to find possible support and resistance levels, and possible reversals in time.
This indicator is a more flexible version of the traditional Gann Spiral / Square. This is achieved by allowing you to change:
Price and Time direction
The timeframe
How often to draw lines based on degrees
Toggles for Price and Time
Price and Time line customization
How to use:
1 - Select your desired starting value of Price and Time.
2 - Choose the direction of Price and Time.
3 - Choose the amount of lines to display.
4 - Choose how often for lines to be drawn (Rotation Degree Value).
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Side Note:
This uses a more proper and more accurate formula to "navigate the square". (Sqr x + 2)^2 is not the formula used, but rather (Sqr x + 1)^2.
If you wish to use the formula you're used to, change Full Revolution Value to 180.
The reasoning behind this formula change is because I re-created the square in the form of an actual spiral. The issue with such a conversion is that the formula used to construct it uses one Pi. If you understand circles, you should know that we're off by 180 degrees. A full rotation is 360, not 180.
Correcting for this error requires a slight but important change in the formula, that being +1 instead of +2. This not only corrects it to fit for a proper spiral, but also makes it easier to use fractions. 1/360 results in 1 degree. This slight formula change makes it incompatible when used on the actual Square of 9, however it is technically the more accurate formula.
Session High and Low IndicatorThis script is meant for stocks that have a pre-market session. It is meant to be used on the 1 min time frame. This script will draw a green line at the high of pre-market, and a red line at the low of pre-market and extend these lines across the regular session day
This makes it easy to see if price action during regular market has broken above pre-market high or broken below pre-market low.
The high/low skips any quick spikes in price action (similar to what happens at 8:30 am every day).
BugiCoThis indicator is designed for shorter time frames - specifically 15 minutes to 1 minute.
It is scalping tool that users William Bollinger setup on various time frames.
This indicator will give you an edge and a way of thinking that you NEVER THOUGHT before because it has a story.
This indicator isolates between 0 and 100. Below around 20 is a buy, above 80 is a sell.
In these locations, try to formulate a scalping strategy with stop loss and risk management. If you don't do that, you will go broke quick in any indicator setup anyways. Be smart...
Story Of This Indicator
~ Took me a while to understand Bollinger Bands and i knew a ton about Fibonacci indicators. So decided to combine fibonacci and bollinger together across different time frames, which is the key. Use as small of a time frame as possible and use it all across the board. The game is designed to rob you either way BUT at least you will have a chance to see what your masters are already taking a look at. There are more complicated tools than this but understand this simple thing "Only way to win in this market to is to do the opposite of the crowd and steal as much money as possible". Create tools that can show you this to "WIN"...
I have a ton of other tools that can change everything for your trading/investing. Reach out to me if you have any questions.
Best wishes
~Megalodon
HLC3_ZThis indicator uses a single price point for each session (HLC3 by default) to draw waves.
This helps to filter out small or high frequency fluctuation in the price, and focus on the trend.
There are also options to display cumulative volume for each wave, or to overlay the price source to draw the wave on the chart.
I find using this indicator helps with finding the wave structures or the head or bottom structures such as head-and-shoulder.
