swami_rsi
Description:
As in the practices, most traders find it hard to set the proper lookback period of the indicator to be used. SwamiCharts offers a comprehensive way to visualize the indicator used over a range of lookback periods. The SwamiCharts of Relative Strength Index (RSI), was developed by Ehlers - see Cycle Analytics for Traders, chapter 16. The indicator was computed over multiple times of the range of lookback period for the Relative Strength Index (RSI), from the deficient period to the relatively high lookback period i.e. 1 to 48, then plotted as one heatmap.
Features:
In this indicator, the improvement is to utilize the color(dot)rgb() function, which finds to giving a relatively lower time to compute, and follows the original color scheme.
The confirmation level, which assumed of 25
Heatmap
Support and Resistance Intensity ZonesSupport and resistance are often drawn using lines. This is too simple and doesn't give a clear idea of the market sentiment at these particular levels. What is strong support and resistance? What is weak support and resistance. How can either be defined by a single price point?
Using a simple, clean and configurable solution, this indicator not only shows these support and resistance levels as zones, it also gives them a colour gradient based on their intensity.
It does this by letting you choose the pivot highs and lows within a chosen range back. Then you choose one of two options to display how these multiple pivots at the same levels look. You can either group these pivots together into 'zones', where grouped pivots are all separated by a chosen price percentage, choosing how many zones to display, the most grouped pivots being the most intense colour.
Alternatively you display the pivots by 'gradient', where the closer the pivots are together in price the more intense the colour. As pivots diverge apart, the colour weakens.
Both of these options have to be seen to realise how much more there is to support and resistance than a single line.
Blockchain Fundamentals: 200 Week MA Heatmap [CR]Blockchain Fundamentals: 200 Week MA Heatmap
This is released as a thank you to all my followers who pushed me over the 600 follower mark on twitter. Thanks to all you Kingz and Queenz out there who made it happen. <3
Indicator Overview
In each of its major market cycles, Bitcoin's price historically bottoms out around the 200 week moving average.
This indicator uses a color heatmap based on the % increases of that 200 week moving average. Depending on the rolling cumulative 4 week percent delta of the 200 week moving average, a color is assigned to the price chart. This method clearly highlights the market cycles of bitcoin and can be extremely helpful to use in your forecasts.
How It Can Be Used
The long term Bitcoin investor can monitor the monthly color changes. Historically, when we see orange and red dots assigned to the price chart, this has been a good time to sell Bitcoin as the market overheats. Periods where the price dots are purple and close to the 200 week MA have historically been good times to buy.
Bitcoin Price Prediction Using This Tool
If you are looking to predict the price of Bitcoin or forecast where it may go in the future, the 200WMA heatmap can be a useful tool as it shows on a historical basis whether the current price is overextending (red dots) and may need to cool down. It can also show when Bitcoin price may be good value on a historical basis. This can be when the dots on the chart are purple or blue.
Over more than ten years, $BTC has spent very little time below the 200 week moving average which is also worth noting when thinking about price predictions for Bitcoin or a Bitcoin price forecast.
Notes
1.) If you do not want to view the legend do the following: Indicator options > Style tab > Uncheck "Tables"
2.) I use my custom function to get around the limited historical data for bitcoin. You can check out the explanation of it here:
swami_money_flow
Description:
Chaikin Money Flow was an indicator that measuring of the volume-weighted average of accumulation and distribution over a specified period (as cited from Fidelity) developed by Marc Chaikin, aim to identify the changes in buying or selling momentum of an asset that leads to the increase or decrease of asset prices. In the original format, the cross above 0 of money flow depicts a buying pressure, while a cross under 0 means a selling pressure. In this indicator, the money flow was displayed in a swami chart, used for detecting a change not only in one specified period but instead in multiple periods at once. Sequencing from the very below, the indicator capture the shift in money flow in shorter lookback periods, going through the very above the indicator capture the change of money flow in greater lookback periods. The color is set to gradient from red as indicating the negative money flow, while green indicates a positive money flow. A smoothing function was given (from Ehlers smoothing function) to reduce noises.
Money Flow:
cmf = n-day sum of( (((close - low) - (high - close)) / (high - low)) x volume )/ n-day sum of volume
smoothed = (4*cmf + 3*cmf + 2*cmf + cmf )/10
Notes:
the Darker the color indicates the higher the value e.g. dark red means more selling pressure, and vice versa
if the color is a lineup in a one period, indicates a strong signal (both directions)
very below is for a shorter period, and increasing through to the longest (1 - 30 by default)
Other Example
normalize_heatmap
Description:
This was a simple indicator to indicate the heatmap area of an asset price, in a relative given time period. In default the lookback period was set to 50 bars, indicating the current state of the price within the previous lookback period. The color scheme was using the rainbow palette, which set blue as the cooling-off area, and red as the heating area. The indicator doesn't take into account momentum strategy and thus doesn't consider the future direction of the asset price. Note: cooling-off area, can be considered to entry or adding position as a DCA strategy.
Data Normalize:
norm = (x - min) / (max - min)
Feature:
Heatmap color condition
Weighted Moving average (Additional)
HEX Risk Metric (v0.2)This indicator plots a "risk metric" based on the % increases of the following averages:
ema21, sma50, sma100, sma200, sma300, sma600.
Depending on the rolling 7-day percentage increase of this moving average, a value is assigned to each data point, then normalized to a common range.
This set of metrics attempts to represent data similar to that of a heat map.
Users can adjust filter top, filter bottom, and toggle on/off the different metrics within the set.
HEX Risk Metric (v0.1)This indicator plots a "risk metric" based on the % increases of the following averages:
ema21, sma50, sma100, sma200, sma300, sma600.
Depending on the rolling 7-day percentage increase of this moving average, a value is assigned to each data point, then normalized to a common range.
This set of metrics attempts to represent data similar to that of a heat map.
Users can adjust filter top, filter bottom, and toggle on/off the different metrics within the set.
Morningstar Equity Style Box HeatmapStyle boxes are a classification scheme created by Morningstar. They visually provide a graphical representation of investing categories for equity investments. A style box is a valuable tool for investors to use when determining asset allocation.
There are 9 categories:
Large Value, Large Blend, Large Growth
Medium Value, Medium Blend, Medium Growth
Small Value, Small Blend, Small Growth
The strength of the 9 categories are found by using 9 Vanguard ETF's that follow the respective CRSP index of their category.
Stochastic RSI HeatmapStochastic RSI presented as a heatmap starting from the oversold (20) / overbought (80) levels respectively. The more oversold / overbought the price, the more intense the color (blue / fuchsia).
xBrat BIAS DEPTH HeatmapThis Trading Indicator is the "Go - No Go Gauge" for any trading signals strategy. A Sub-Chart that looks up 6 time frames and gives you real time BIAS. Bullish, Neutral or Bearish on each level. Making decisions, acting on trading signals easier! Only identifying those highest probability trades, no matter what signals trading indicator you are using. Ideal for Forex Trading, Futures Trading, Crypto Trading and Stocks Trading
This BIAS Depth Heatmap includes:
6 Levels of BIAS Depth
Scalping Setting
Day Trading Setting
Swing Trading Setting
And by only concentrating on trading the highest probability trades of any trading strategy, we can block out all the other noise and concentrate on a simple set of rules!
This is why our Founder, Paul Bratby, decided to help filter out all the noise and allow traders to see what's going off on higher timeframes "in depth" to help make those important trade entry decisions. This more global view of the BIAS DEPTH is designed to help traders make decisions faster!
Heatmap WatchlistThis is a Heatmap for custom watchlist tickers. Similar to S&P500 Heatmap .
Add up to 20 tickers.
Check higher timeframe from a lower timeframe.
Check previous candle for any timeframe.
Switch on/off "Price%" and/or "Volume%" heatmap.
S&P500 Heat MapS&P sectors heat map. Follows the timeframe of the active chart.
The following SPDR select sector funds are included
XLB - Materials
XLC - Communication
XLE - Energy
XLF - Financials
XLI - Industrials
XLK - Information technology
XLP - Consumer staples
XLRE - Real estate
XLU - Utilities
XLV - Healthcare
XLY - Consumer discretionary
SPY and current chart ticker will also be included by default, but can be disabled in the settings.
Optional:
There's a switch in setting "Data from previous bar" - if selected, the change percent will be from the previous candle. For example, if the chart timeframe is daily with this option selected, data will be from previous day. Similar situation with all timeframes. Also, when this option is active, the text "Previous Bar" will be printed in red color on the top right corner to avoid any confusion.
Williams Alligator Trend Filter HeatmapHello I've decided that the alligator lines can be used to find a trend. This script expands on that and checks 10 different multipliers to see trend over the long term and have 10 values. Those 10 values each give a color to one of the 10 lines in turn giving this Fire like plotting. I personaly use this to see if there is fear (red) in the markets or greed (blue), plotted 9 different crypto coins on the chart and have 4 columns in my setup to see the values on different timeframes. In the chart preview this is 1H,30M,10M,1M to see current environment. The colors use alot of data to generate especialy the bottom part, that colors based on a very long time zone.
Relative Strength Screener V2 - Top 100 volume leadersNew and improved strength heatmap for the top 100 volume leaders in the S&P. Coded in a workaround to the 40 request.security limitation that currently exists in Pine. Added the ability to input the number of columns (time frames) you wish to display.
For 3 time frame analysis, add the indicator to your chart 3 times. Change the number of columns to 3 for each of these indicators. Specify the column and time frame for each one (example, 5 minute for column 1, 1 hour for column 2 and Daily chart for column 3). It will automatically resize the columns/tables to properly display the output. This provides a sort of "Strength Heatmap" for the top 100 stocks in the S&P. To achieve this, make a copy of the indicator and substitute lines 68-105 with the following premade watchlists :
Make a copy 1 - FIrst 38 volume leaders in the S&P
s01 = input.symbol('AAPL', group = 'Symbols', inline = 's01')
s02 = input.symbol('ABBV', group = 'Symbols', inline = 's02')
s03 = input.symbol('ABT', group = 'Symbols', inline = 's03')
s04 = input.symbol('ACN', group = 'Symbols', inline = 's04')
s05 = input.symbol('AEP', group = 'Symbols', inline = 's05')
s06 = input.symbol('AIG', group = 'Symbols', inline = 's06')
s07 = input.symbol('AMAT', group = 'Symbols', inline = 's07')
s08 = input.symbol('AMD', group = 'Symbols', inline = 's08')
s09 = input.symbol('APA', group = 'Symbols', inline = 's09')
s10 = input.symbol('ATVI', group = 'Symbols', inline = 's10')
s11 = input.symbol('AXP', group = 'Symbols', inline = 's11')
s12 = input.symbol('BA', group = 'Symbols', inline = 's12')
s13 = input.symbol('BBWI', group = 'Symbols', inline = 's13')
s14 = input.symbol('BBY', group = 'Symbols', inline = 's14')
s15 = input.symbol('BK', group = 'Symbols', inline = 's15')
s16 = input.symbol('BMY', group = 'Symbols', inline = 's16')
s17 = input.symbol('BRK.B', group = 'Symbols', inline = 's17')
s18 = input.symbol('C', group = 'Symbols', inline = 's18')
s19 = input.symbol('CAT', group = 'Symbols', inline = 's19')
s20 = input.symbol('CCL', group = 'Symbols', inline = 's20')
s21 = input.symbol('CFG', group = 'Symbols', inline = 's21')
s22 = input.symbol('CL', group = 'Symbols', inline = 's22')
s23 = input.symbol('CNC', group = 'Symbols', inline = 's23')
s24 = input.symbol('COF', group = 'Symbols', inline = 's24')
s25 = input.symbol('COP', group = 'Symbols', inline = 's25')
s26 = input.symbol('COST', group = 'Symbols', inline = 's26')
s27 = input.symbol('CRM', group = 'Symbols', inline = 's27')
s28 = input.symbol('CVS', group = 'Symbols', inline = 's28')
s29 = input.symbol('CVX', group = 'Symbols', inline = 's29')
s30 = input.symbol('DAL', group = 'Symbols', inline = 's30')
s31 = input.symbol('DIS', group = 'Symbols', inline = 's31')
s32 = input.symbol('DISCA', group = 'Symbols', inline = 's32')
s33 = input.symbol('DISCK', group = 'Symbols', inline = 's33')
s34 = input.symbol('DISH', group = 'Symbols', inline = 's34')
s35 = input.symbol('DLTR', group = 'Symbols', inline = 's35')
s36 = input.symbol('DOW', group = 'Symbols', inline = 's36')
s37 = input.symbol('DVN', group = 'Symbols', inline = 's37')
s38 = input.symbol('EBAY', group = 'Symbols', inline = 's38')
Make a copy 2 - Tickers 39 to 76
s01 = input.symbol('EOG', group = 'Symbols', inline = 's01')
s02 = input.symbol('F', group = 'Symbols', inline = 's02')
s03 = input.symbol('FB', group = 'Symbols', inline = 's03')
s04 = input.symbol('FCX', group = 'Symbols', inline = 's04')
s05 = input.symbol('FIS', group = 'Symbols', inline = 's05')
s06 = input.symbol('GE', group = 'Symbols', inline = 's06')
s07 = input.symbol('GIS', group = 'Symbols', inline = 's07')
s08 = input.symbol('GM', group = 'Symbols', inline = 's08')
s09 = input.symbol('GS', group = 'Symbols', inline = 's09')
s10 = input.symbol('HD', group = 'Symbols', inline = 's10')
s11 = input.symbol('IBM', group = 'Symbols', inline = 's11')
s12 = input.symbol('INTC', group = 'Symbols', inline = 's12')
s13 = input.symbol('JNJ', group = 'Symbols', inline = 's13')
s14 = input.symbol('JPM', group = 'Symbols', inline = 's14')
s15 = input.symbol('KR', group = 'Symbols', inline = 's15')
s16 = input.symbol('LUV', group = 'Symbols', inline = 's16')
s17 = input.symbol('LVS', group = 'Symbols', inline = 's17')
s18 = input.symbol('MA', group = 'Symbols', inline = 's18')
s19 = input.symbol('MCD', group = 'Symbols', inline = 's19')
s20 = input.symbol('MCHP', group = 'Symbols', inline = 's20')
s21 = input.symbol('MDT', group = 'Symbols', inline = 's21')
s22 = input.symbol('MET', group = 'Symbols', inline = 's22')
s23 = input.symbol('MGM', group = 'Symbols', inline = 's23')
s24 = input.symbol('MOS', group = 'Symbols', inline = 's24')
s25 = input.symbol('MPC', group = 'Symbols', inline = 's25')
s26 = input.symbol('MRK', group = 'Symbols', inline = 's26')
s27 = input.symbol('MRNA', group = 'Symbols', inline = 's27')
s28 = input.symbol('MS', group = 'Symbols', inline = 's28')
s29 = input.symbol('MSFT', group = 'Symbols', inline = 's29')
s30 = input.symbol('MU', group = 'Symbols', inline = 's30')
s31 = input.symbol('NCLH', group = 'Symbols', inline = 's31')
s32 = input.symbol('NEE', group = 'Symbols', inline = 's32')
s33 = input.symbol('NEM', group = 'Symbols', inline = 's33')
s34 = input.symbol('NFLX', group = 'Symbols', inline = 's34')
s35 = input.symbol('NKE', group = 'Symbols', inline = 's35')
s36 = input.symbol('NVDA', group = 'Symbols', inline = 's36')
s37 = input.symbol('ORCL', group = 'Symbols', inline = 's37')
s38 = input.symbol('OXY', group = 'Symbols', inline = 's38')
Make a copy 3 - tickers 77 to 114
s01 = input.symbol('PENN', group = 'Symbols', inline = 's01')
s02 = input.symbol('PEP', group = 'Symbols', inline = 's02')
s03 = input.symbol('PFE', group = 'Symbols', inline = 's03')
s04 = input.symbol('PG', group = 'Symbols', inline = 's04')
s05 = input.symbol('PM', group = 'Symbols', inline = 's05')
s06 = input.symbol('PYPL', group = 'Symbols', inline = 's06')
s07 = input.symbol('QCOM', group = 'Symbols', inline = 's07')
s08 = input.symbol('RTX', group = 'Symbols', inline = 's08')
s09 = input.symbol('SBUX', group = 'Symbols', inline = 's09')
s10 = input.symbol('SCHW', group = 'Symbols', inline = 's10')
s11 = input.symbol('SLB', group = 'Symbols', inline = 's11')
s12 = input.symbol('SYF', group = 'Symbols', inline = 's12')
s13 = input.symbol('T', group = 'Symbols', inline = 's13')
s14 = input.symbol('TFC', group = 'Symbols', inline = 's14')
s15 = input.symbol('TGT', group = 'Symbols', inline = 's15')
s16 = input.symbol('TJX', group = 'Symbols', inline = 's16')
s17 = input.symbol('TMUS', group = 'Symbols', inline = 's17')
s18 = input.symbol('TSLA', group = 'Symbols', inline = 's18')
s19 = input.symbol('TWTR', group = 'Symbols', inline = 's19')
s20 = input.symbol('TXN', group = 'Symbols', inline = 's20')
s21 = input.symbol('UAL', group = 'Symbols', inline = 's21')
s22 = input.symbol('UNH', group = 'Symbols', inline = 's22')
s23 = input.symbol('V', group = 'Symbols', inline = 's23')
s24 = input.symbol('VIAC', group = 'Symbols', inline = 's24')
s25 = input.symbol('WBA', group = 'Symbols', inline = 's25')
s26 = input.symbol('WFC', group = 'Symbols', inline = 's26')
s27 = input.symbol('WMT', group = 'Symbols', inline = 's27')
s28 = input.symbol('WYNN', group = 'Symbols', inline = 's28')
s29 = input.symbol('XOM', group = 'Symbols', inline = 's29')
s30 = input.symbol('SPY', group = 'Symbols', inline = 's30')
s31 = input.symbol('SPY', group = 'Symbols', inline = 's31')
s32 = input.symbol('SPY', group = 'Symbols', inline = 's32')
s33 = input.symbol('SPY', group = 'Symbols', inline = 's33')
s34 = input.symbol('SPY', group = 'Symbols', inline = 's34')
s35 = input.symbol('SPY', group = 'Symbols', inline = 's35')
s36 = input.symbol('SPY', group = 'Symbols', inline = 's36')
s37 = input.symbol('SPY', group = 'Symbols', inline = 's37')
s38 = input.symbol('SPY', group = 'Symbols', inline = 's38')
Weekly Volume HeatmapThis tool is designed to visualize how the trading volume of each asset changes during the week.
How to use
This tool can help us better understand the market and answer many questions, such as:
◽ How to avoid getting stop hunted?
Typically, trading volume decreases at certain times of the week, which is the best time for large holders to manipulate the market. Low volume means there is less liquidity in the market. Large transactions in an illiquid market can cause large price changes.
Large holders (whales) have enough capital to push the price in the desired direction to trigger a cascade of stop-loss orders which can move the price further.
After a stop hunt, the market typically reverses, leaving stop hunted traders behind.
It is best to avoid using stop-loss orders and leveraged trading during these hours of the week.
◽ When’s the best time to make decisions
During some hours of the week the trading volume usually decreases; at these times, most traders are inactive and do not participate in transactions.
Therefore, the price changes that occur during these times lack conviction.
It is better to make decisions when there are more active traders in the market. At these periods, a relatively high trading volume is usually observed.
How it works
First, it calculates the average traded volume of each period (for example Monday 9:00 AM) from the first bar to the last bar. It then calculates the ratio of the average traded volume in each period to the average traded volume per week. Finally, the result is displayed as a percentage in each cell.
Different values are distinguished by different background colors. Light colors are used for low values and dark colors are used for high values.
Limits
It only works in the 1 hour time frame.
Samples
Stock => AAPL
Futures => ES1!
Forex => EURUSD
Litt Heat MapThe Litt Heap Map uses the MA Line (Moving Average Line) from Litt Pro Indicators. The Heat Map tells the trader the trend direction based on MA 1 and MA 2.
If the value of MA 1 is greater than the value of MA 2 then the MA Line is colored Bull.
If the value of MA 1 is less than the value of MA 2 then the MA Line is colored Bear.
The Litt Heat Map allows you to see the MA Line for multiple symbols on 1 chart! You can use the Heat Map as a scanner to see when trend has changed, or as a trend confirmation tool when multiple symbols are aligning.
Currency Strength DashboardDrawing Currency Strength (consists of: USD, EUR, JPY, GBP, AUD, CHF, CAD, NZD) historical plots in parallel with currency strength heat map and dynamic legend, which makes this script unique as Dashboard.
Calculation criteria is based on user's input: Session, by which you can recalculate based on D, W, M.
ADX Heatmap & Di's + Fib Referencial by [JohnnySnow]For quicker and easier interpretation, ADX line is displayed in a heatmap style. The more absolute difference between both DIs, the more intense the color.
Because some people use 20 ADX reference and others use 25 ADX reference to confirm the trend, I just add both as reference lines in a 'golden box'
Additionally, reference lines were added with default values set to Fib levels
BEST Algo HeatmapHello traders
How to access?
Offered to all the current customers
To be used alongside the BTI Algo Global script.
Heatmap
This heatmap screens the BTI Algo Global signals across different timeframes.
The screened timeframes are for now: m1/m2/m5/m15/m30/H1/H2/H4/H8/Daily
The trends are based on the triangle primary signals
Limitations
- I could only access the last 20K loaded candles, then you might see a blank case for the screened high timeframes when you're loading the screener on a low timeframe chart.
Example: a 1-minute chart with the screener might struggle sometimes to display the 4H/8H/Daily data
- What to do then?
I found a hack.
Just load the chart on a much higher timeframe and you should be able to see the latest timeframes from the heatmap
If any questions, please let me know
Dave
Volume Profile HeatmapA variation of a Volume Profile based on code originally by LuxAlgo. () The traditional bar chart is replaced with full-width bars that are brighter for high volume price levels.
Like a traditional VP, its purpose is to visualize how volume corresponds to specific price levels, allowing you to get a quick idea of where the most activity is occurring, and where it hasn't been. This information may provide clues as to where price action may return, areas of support and resistance , and regions where price may move quickly. The basic concepts behind any Volume Profile (or Price by Volume Chart) should apply here as well. (investopedia article)
Inputs are set up such that you can customize the lookback period, number of rows, and width of rows for most major timeframes individually. Timeframes between those available will use the next lower timeframe settings (e.g., 2m chart will use the 1m settings.)
This indicator is experimental and is likely to receive further updates.
Volume Zones Multi-Timeframe OverlayAt its core, this indicator is a variation of my other indicator, Welkin Advanced Volume Overlay (for VSA )
This version is based on the power of multi-timeframe analysis. The basic functionality is simple: Plot lines from the high and low of candles formed during periods of high volume and fill the space between them. The volume levels for deciding what counts as "high volume" are based on standard deviations of the volume's SMA , and the higher the volume , the brighter the zone. i.e., a volume zone set by a volume level that is 4 standard deviations higher than average will be more "filled in" and less transparent than a volume zone from a 2 standard deviation candle.
These zones tend to act as areas of congestion, and the "ceilings" and "floors" of the zones as support and resistance . Overlapping zones tend to indicate strength and are likely to require more effort to get through. The more timeframes that agree with each other, the stronger the zone, ceiling, or floor.
By default, these zones are drawn based on the chart's timeframe and 1 timeframe higher, automatically set based on some "standard" values:
1m -> 5m
5m -> 15m
10m -> 30m
15m -> 60m
30m -> 60m
60m -> 1d
1d -> 1w
Finally, both the base timeframe and the higher timeframe are customizable; this is intended to make it easy to "double" up copies of the indicator to fit even more timeframes on the chart, creating a sort of heatmap for volume price analysis.
An example of three copies of the indicator, showing volume zones from 6 different timeframes.
Intraday Volume Spikes HeatmapA tool to identify and visualize abnormal volume clusters. Intended for intraday charts with volume data available. Works out of the box without a need for setting up 100500 parameters.
Features:
Customizable table
4 modes
17 color palettes including Viridis, Inferno, Magma and Plasma available
Example: Viridis palette
Example: Inferno palette
Heat Map Template [DM]Greetings colleges
Today I share a simple template to make your composite heat map
Remember that they can overlap, although here you can only alternate
The source for heat map is an RSI of various lengths which are described in the footer of the script
Enjoy”
