MFI + RSI + MOM With Bull & Bear Trend LabelMOMENTUM + MONEY FLOW INDEX + RELATIVE STRENGTH INDEX WITH BULL & BEAR LABELS
This is a combination of 3 popular indicators. Momentum(MOM), Money Flow Index(MFI) and Relative Strength Index(RSI) along with color changing labels that tell you each indicator's current trend.
The middle white line shows the level that each indicator needs to stay above to be bullish and below for bearish. Watch for all three indicators to cross and hold above or below the mid line for big moves.
It is important to note that these indicators do not need to be going up to be bullish or down to be bearish. They just need to hold above or below the mid line to understand the overall trend.
The momentum indicator is the most relevant in my opinion. If it is holding above the mid line steadily, usually the overall trend will continue upwards so look to buy the dips if the momentum cloud is staying above the white line and vice versa.
It is also important to note that the default settings for this indicator are the 100 period as I find it to be super relevant across most charts but these numbers can be changed in the indicator settings.
Since momentum swings wildly past the normal 0-100 range, it is important to note that the momentum line has been “normalized” to stay within this same range as the rsi and mfi. So if you look at a normal momentum indicator side by side with this indicator it will not look the same however, I find it to be a very good indicator of overall direction so I know the current market sentiment even when price is diverging from the indicator directions.
All of the colors, sources and lengths can be easily customized in the indicator settings input tab.
***HOW TO USE***
When Momentum is above the mid line, it is bullish. When Momentum is below the mid line, it is bearish.
A label on the right side will update in real time to tell you if momentum is Bullish or Bearish for faster recognition of the trend.
When RSI is above the mid line, it is bullish. When Momentum is below the mid line it is bearish.
A label on the right side will update in real time to tell you if RSI is Bullish or Bearish for faster recognition of the trend.
When MFI is above the mid line, it is bullish. When MFI is below the mid line it is bearish.
A label on the right side will update in real time to tell you if MFI is Bullish or Bearish for faster recognition of the trend.
This indicator was built to help you quickly identify the Bullish or Bearish nature of the current trend with a live color changing label so you can glance at the label and understand it's direction without analyzing the indicator data.
***MARKETS***
This indicator can be used as a signal on all markets, including stocks, crypto, futures and forex.
***TIMEFRAMES***
This mom + mfi + rsi indicator can be used on all timeframes.
***TIPS***
Try using numerous indicators of ours on your chart so you can instantly see the bullish or bearish trend of multiple indicators in real time without having to analyze the data. Some of our favorites are our Auto Fibonacci, Directional Movement Index, Volume Profile, Auto Support And Resistance and Money Flow Index in combination with this indicator. They all have real time Bullish and Bearish labels as well so you can immediately understand each indicator's trend.
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Adaptive Oscillator constructor [lastguru]Adaptive Oscillators use the same principle as Adaptive Moving Averages. This is an experiment to separate length generation from oscillators, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. Note that all Oscillators here are normalized to -1..1 range. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource , so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Oscillators.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers , but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power ( exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Oscillators section offer you a choice of Oscillator algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
CMO - Chande Momentum Oscillator
RSI - Relative Strength Index
Volume-scaled RSI - my own version of RSI. It scales price movements by the proportion of RMS of volume
Momentum RSI - RSI of price momentum
Rocket RSI - inspired by RocketRSI by John F. Ehlers (not an exact implementation)
MFI - Money Flow Index
LRSI - Laguerre RSI by John F. Ehlers
LRSI with Fractal Energy - a combo oscillator that uses Fractal Energy to tune LRSI gamma
Fractal Energy - Fractal Energy or Choppiness Index by E. W. Dreiss
Efficiency ratio - based on Kaufman Adaptive Moving Average calculation
DMI - Directional Movement Index (only ADX is drawn)
Fast DMI - same as DMI, but without secondary smoothing
If no Adaptation is selected (None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set.
Before an Oscillator, a High Pass filter may be executed to remove cyclic components longer than the provided Highpass Length (no High Pass filter, if Highpass Length = 0). Both before and after the Oscillator a Moving Average can be applied. The following Moving Averages are included: SMA, RMA, EMA, HMA , VWMA, 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. For more details on these Moving Averages, you can check my other Adaptive Constructor indicator:
The Oscillator output may be renormalized and postprocessed with the following Normalization algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
Inverse Fisher Transform - Inverse Fisher Transform
Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers
Except for Inverse Fisher Transform, all Normalization algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Oscillator length is used.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other PulseWire community members (they are also mentioned in the library code) without whom this script would not have been possible. Indicator
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Measure Volume, Momentum, Trend, VolatilityThis script displays the following indicators in one pane to quickly determine several important factors regarding price action. It allows the user to quickly see all of most important factors surrounding price action in one pane with one quick glance. This should be incredibly helpful and allow things like double divergence and trend confirmation to be spotted much more quickly. I personally use the data in this indicator to replace four separate indicators and it has brought my win rate and profit factor significantly higher. I hadn't seen any place where all of the best J. Welles Wilder indicators such as RSI, Parabolic SAR, and DMI/ADX were brought into one easy to use interface. This is my attempt at fixing that gap. For a much deeper understanding of how to use these indicators, I recommend reading New Concepts in Technical Trading Systems written by J. Welles Wilder.
Momentum via RSI (Relative Strength Index)
Volume via MFI (Money Flow Index)
Volatility via DMI/ADX (Direction Movement Index/Average Directional Index)
Trend via Parabolic SAR (Parabolic Stop and Reverse)
It is worth noting that DMI/ADX and Parabolic SAR can both help determine trend strength and volatility.
The Volatility mechanism is measured by DMI and ADX and displayed at the top of the pane using circles. The top, tiny circles reflect if show if positive DI or negative DI has a higher value. The small circles directly underneath indicate whether or not the ADX is above 20 (configurable, some may choose to increase this to 25 or even 30).
The Momentum mechanism is shown as standard RSI with the default being a white line and default period of 14, which is all configurable.
The Volume mechanism is shown as standard MFI with the default being a fuchsia line and default period of 14, which is also configurable.
The momentum and volume oscillators should be used in conjunction to help spot whether the trend is strong or weak using divergences and the middle, overbought, and oversold levels. These levels are also configurable.
The Trend mechanism is measured by Parabolic SAR and displayed at the bottom of the pane using diamonds. The default is red diamonds when in a bear trend, green when in an uptrend which is configurable. When price is above the Parabolic SAR, it is considered to be an uptrend. When price is below the Parabolic SAR, it is considered to be a downtrend. The way price is measured is also configurable (i.e. open, close, ohlc4, hlc3, etc.). When price crossed above or below the Parabolic SAR, the diamonds will change colors.
All the indicators displayed should be used in a well rounded strategy. For instance, I only trade when ADX is above 20 and rarely trade against the trend shown via PSAR. When trend shifts and divergences helped indicate a trend shift would occur using the RSI and MFI, it can be a great spot to take an entry. RSI/MFI can also confirm the trend is strong when they are not showing divergences and inline with price action. All of this data should be used in conjunction with good fundamental data and technical levels. Divergences with RSI and MFI on double tops or bottoms can also be incredibly powerful. There is no right or wrong way to use all the data displayed in this indicator, however using all four pillars of trading (Momentum, Volume, Trend, Volatility) will help ensure only the best trades are taken. Indicator
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Williams %R & RSI with Multiple PeriodsDESCRIPTION
1. Calculates %R and RSI with multiple period lengths.
1 period length value is defined by User.
8 period length values follow User's selection of classic number sequences, e.g. Fibonacci, Leonardo, Lucas, Narayana, etc.
2. User selects which indicator and periods to display or hide.
DEFAULTS
%R default custom period: 10.
RSI default custom period: 14.
%R & RSI default number sequence periods: Lucas numbers 11, 18, 29, 47, 76, 123, 199, 322.
CALCULATIONS
%R = (period high - most recent period's close price)/(period high - period low)
RSI = 100 - 1 / (100 + RS), where RS = SMMA(up, period) / SMMA(down, period)
PURPOSE
1. Identify price trends.
CREDITS
1. Williams %R technical analysis momentum oscillator by Larry Williams.
2. Wilder's Relative Strength Index technical analysis momentum oscillator by J. Welles Wilder.
3. "Solarized" color scheme by Ethan Schoonover. Indicator
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Kifier's MFI/STOCH Hidden Divergence/Trend BeaterMFI/STOCH Hidden Divergence/Trend Beater
General Idea:
My premise around this strategy was to make a general strategy for crypto that would help out with finding entry positions for when you’re bullish on a crypto and want to hold on for a while, and at the same time avoiding massive drops. Essentially a way to mix long term/ swing trading; I somewhat achieved my goal however it still requires a lot of logic tuning of the trend averages.
I’m a huge proponent of volume indicators and coupled with average closing price, I think this gives a really good idea of what is happening with the market. It gives an idea on the market and retail investor sentiment. This generally gives you logical entry positions (Although I don’t know how amazing that will work with all cryptos, there’s a fine line between a good strategy and one that just rides bubble market conditions, some would argue that’s still a success and others not)
How it works:
There are many components to the strategy that try to do different things:
First of all there are two types of entries, a MFI hidden divergence with a STOCH check, essentially it will only fire when a divergence is detected while STOCH is above 50%, however this might be changed in the future as due to the volatile nature of cryptos, the STOCH is not too effective. The second entry is a simple MFI/STOCH trend, if STOCH is above 50% and the trend is detected to be in a trending long, once a MFI crossover over the 50% line is detected an entry is placed, this is designed to get out profit where the divergence would otherwise be less accurate during strongly trending conditions.
-MFI is a great indicator, as a volume weighted momentum indicator I find it the most accurate of all, the STOCH however is a great indicator to get a general picture of simple market conditions and can filter out the emotional noise of retail investors.
-VWMA and an SMA (The bottom oscillator) gives an idea of the trend tacking into account of the volume, this serves as a more short term filter of the trend for filters.
-OBV checks are done between the OBV and an EMA of the OBV, to get the idea of a volume weighted long trend, which is important for crypto as there are massive rallies to go up due to retail greed, it’s great to jump onto it at the beginning, and get off before the stack of cards fall apart.
-ATR is used to detect when the market is relatively just ranging or moving sideways, which is where the hidden divergence entries are done, during predictable and profitable market conditions.
- Stop loss is based on the closest support of the entry, this is a nice medium of room to breath but also an actual stop loss.
Future plans and improvements:
Currently there’s a lot I want to improve, mostly the divergence detection and the overall sharpe ratio could be much better, but the current value of 0.5 gives me hope that the strategy is onto something. I also want to change TP from a percentage stop to something more dynamic but that might be too optimistic. The current plan is to paper trade test this either by manual or by a python bot, to see how it performs with some user input as well.
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