FAQ

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EWAVES Live currently covers a selection of Commodities, Crypto, Forex, US Stock & Bond Indices, US ETFs and US Stocks. For a full list of covered assets or if you wish for additional coverage, please email us at info@ewaves.com.

We are currently partnered with Trade Navigator.

EWAVES Live starts updating its charts (using the latest end-of-day daily bar data) every night at 8 PM EST. It takes some time for processing, so the updates will likely not be available until about 15 minutes thereafter.

If you are logged in during the update process, you will need to refresh your browser window to view the latest charts.

We plan to make intraday updates available in a future edition of the program.

The labels mostly use the labeling convention described in Frost & Prechter’s book Elliott Wave Principle. Impulses and diagonals use 1-2-3-4-5, zigzags and flats use A-B-C, and complex corrections use W-X-Y.

The only slightly unusual labeling are triangles, which are lowercase a-b-c-d-e. This distinction is important for two reasons:

(1) The internals of triangle waves “a” and “b” resemble the internals of flat waves “A” and “B”, so we require different labels for disambiguation. No other pattern has this issue.

(2) Sometimes, in the WaveFinder (an Elliott wave search engine; see “WaveFinder” section below for details), you may want to specify “the last wave of a correction,” which would be “C” for a zigzag or flat, but “e” for a triangle.

EWAVES’ wave counts will not necessarily align with any particular analyst’s market opinion. Users may review its analysis in isolation or seek to incorporate it with other sources or tools.

The reflection of social mood in freely traded markets is imperfect. Therefore, it is generally not possible to label Elliott waves without incorporating some subwaves that do not subdivide cleanly, or that appear to subdivide in ways which do not match their context.

Additionally, all market data formats contain artifacts, making the internal wave structure impossible to discern over short-term intervals. For example, a beautiful five-wave structure on an hourly chart may appear as a three-wave structure when looking at the corresponding daily bars.

To allow EWAVES to count real world data, it is allowed to “squint” over data segments in much the same way that human practitioners do. The resulting waves simply have no internal structure, i.e., they are of an “unknown” type. Their meaning comes from the larger context in which they occur.

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Elliotticity is the degree to which a data segment adheres to the Elliott Wave Principle. It varies from 0% to 100%. Each individual Elliott wave spans a data segment with an elliotticity rating corresponding to the quality of its internal structure.

Additionally, to ensure each wave’s elliotticity has a strong meaning, each wave’s elliotticity also includes a modest amount of extra context, i.e. it mixes in some of the elliotticity of other surrounding waves. This makes perfect sense when you consider a wave that has just begun: obviously, the elliotticity of the preceding wave is what you should focus on, because the new wave has virtually no discernible structure yet, and thus no meaningful elliotticity without incorporating some context. At this time, the precise extra context included is: (1) the preceding waves of the same degree (i.e. for a wave 3, wave 2 and wave 1 are also included for context) and (2) the preceding wave of one degree higher (i.e. for a wave 3 of a wave C, wave B would also be included for context).

A perhaps unexpected aspect of how EWAVES implements elliotticity is that it is scale invariant. The recent daily picture is given as much consideration as the recent weekly picture, which is given as much consideration as the recent monthly picture, and so on. In this way, elliotticity is as equally sensitive to short-term market activity as it is to long-term market activity. In other words, a wave with high elliotticity counts well at all degrees of scale, from the past to the present.

In past newsletters, we have referred to the elliotticity of the largest wave in a market as the market’s total elliotticity. As a result of time frame invariance, total elliotticity is perhaps the most generally useful single numerical value for ranking markets against one another in terms of Elliott wave conformance. If a market has high total elliotticity, then you should be able zoom all the way in, or all the way out, and the market should adhere well to the Elliott wave model at all timescales.

Total elliotticity is the default ranking method used (if sorting markets by elliotticity) when the WaveFinder is inactive. When using the WaveFinder, the elliotticity value will correspond to each wave that you find. That gives you the option to focus on shorter-term elliotticity rather than total, which can be more useful when the highest-degree waves are unimportant (which is generally the case, since for example you usually do not care about the multi-century picture).

Elliotticity values are not percentiles (i.e. a relative rank of wave conformance), but are absolute percentages from 0% to 100% determining how conformant individual waves are to the Elliott Wave Principle. The higher the value, the better.

As of the most recent version of the EWAVES engine, you’ll find that waves with elliotticities at or above 50% are high quality, with 55% and higher absolutely the best-in-class. Below around 38% is where waves start exhibiting potentially problematic issues, including but not limited to (1) unlabeled/unknown substructure (2) contextual waves are poor quality (3) extrapolation of existing structure is highly probable to break Elliott wave rules. Therefore, when using the WaveFinder, a minimum elliotticity of around 38% is a good choice.

In theory, Elliotticity could be as high as 100%, but that is only practically possible when using data that is artificially constructed to conform to idealized Elliott waves. Real world data rarely gets much beyond 50% conformance.

EWAVES Live has a built-in WaveFinder, which is the world’s first Elliott wave search engine. It is a query system for quickly finding and sorting through thousands of real time Elliott waves based on precise criteria.

For example, you could build a query to find unfolding 5th waves that follow a triangle and are less than 20% complete.

By far the best way to learn is to watch the EWAVES Live tutorial video.

There are multiple types of context waves. The context wave called simply “wave” is the actual wave you’re searching for. It is the wave that will be highlighted by the WaveFinder. Many search queries only involve looking for a “wave” with particular attributes (see section “What are the Wave Attributes?” below for details). For example, to find an impulse wave, you would search for a wave with the attribute “type” set to “impulse.”

There other context waves provide the environment (aka “context”) for “wave”. You may, for example, specify attributes for the “prior” context wave. This is the wave structure that precedes the wave you’re searching for. For example, to find waves that follow triangles, you would add the context wave “prior”, and then require that “prior” have the attribute “type” set to “triangle.”

Another context wave is “parent,” which is the larger wave of which “wave” is a component. For example, if you want “wave” to occur in the context of a larger 3rd wave, you would add the context wave “parent” and then require its attribute “label” to be “3.”

The “child” context wave is the last component wave of “wave.” For example, if you were looking for an impulse wave where its 5th wave was in progress, you would add context wave “child” and set its “label” attribute to “5.”

If you wish to specify attributes for a wave larger than “parent”, the grandparent is called “parent(+1)”, the great-grandparent is “parent(+2)”, and so on. Similarly, there is “child(-1)”, “child(-2)”, and so on.

• Type: The pattern formed by a wave’s internal structure. For example, “impulse” for an impulse wave.

You may specify multiple patterns for a wave. For example, if you’re interested in motive waves, you can specify that a wave be either “impulse” or “diagonal”.

• Label: The position of a wave in a larger pattern. These should be self-explanatory, because they’re mostly identical to classical Elliott wave labels. The one exception is triangles, which use lowercase a-b-c-d-e instead of uppercase. Doing so allows the expression of “the final wave of a pattern” which would require a difference between “c” (part of a triangle) and “C” (the final wave of a zigzag or flat).

You may specify multiple labels for a wave. For example, if you’re interested in motive waves in the final position of a structure, you can specify that a wave be either “5” or “C”.

• Elliotticity: This is a percentage measure (0% to 100%) describing how strongly a wave’s internal structure, plus a certain amount of its context, conforms to the Elliott Wave Principle. For details see the earlier FAQ question “What is Elliotticity?”. Elliotticity is helpful in identifying high quality waves.

• Linearity: This is a percentage measure (0% to 100%) describing how line-like a wave is. 100% would be a perfectly straight line, whereas 0% would entail a sideways, 2-dimensional structure. A triangle would be expected to have low linearity, while an impulse wave would be expected to have high linearity. This measure is akin to the concept of fractal dimension. Linearity is helpful in identifying strongly trending waves.

• Complete: This is a percentage measure (0% to 100%) describing an estimate of how close a wave is to completion, in terms of both price and time. For example, an impulse wave that is currently in its 5th wave is likely more complete than an impulse wave that is currently in its 2nd wave.

Completeness is useful to anticipate turning points, such as starting waves (those that are 0 to 5% complete), or ending waves (those that are 95% to 100% complete). It is also a useful measure that allows you to base your search on the distance a wave has already traveled. For example, you may want to identify 5th waves, but only those that are not already more than 50% complete.

• Duration: How long a wave has taken to unfold thus far, in days. Note that this measure does not involve any extrapolation, so it may be much less than the eventual ultimate duration of a wave.

One use of duration is to specify the size of existing wave structure. For example, you may wish to look at impulse waves that are just starting their internal 5^th waves, and you want to specify a duration for waves 1 through 4. An impulse 1-2-3-4 structure spanning between 150 and 250 days provides a context that indicates a potential for a sizable 5th wave to follow.

Another use of duration is to compare trends. For example, you may wish to find waves with a duration of around 100 days, and then sort those waves by their slopes. Doing so emulates a classic momentum model, yet it uses only Elliott waves. Momentum considerations can then be combined with wave structure considerations.

• Duration (Expected): The expected total number of days a wave will have lasted at completion, derived by extrapolating the current wave structure.

The expected duration is one way to measure the overall size of a wave, regardless of if it’s a brand-new wave that is only one-day into its development, or if it’s a more mature wave. If you wish to “anticipate all advances or declines of a particular total duration”, then expected duration is a great way to do that.

Expected duration combines well with restrictions on labels and wave types. For example, you may want to look for “all 3rd of a 3rd waves with an expected duration between 100 and 200 days”, which is easy to achieve by adding a label requirement of “3”, adding a context wave “parent” also with a label requirement of “3”, and setting Duration (Expected) to 100-200 days.

• Duration (Remaining): The expected number of days between now and the completion of the wave, derived by extrapolating the current wave structure.

A common usage of a wave’s remaining duration is to limit the expected amount of time that a move is going to take. For example, you may wish to look for 5th waves that have a remaining magnitude of 20% (see below section on “Magnitude (Remaining)”), but you don’t want to wait around forever for the 20% move to happen, so you may choose to further filter your results by only looking at those with a remaining duration less than 100 days.

• Magnitude (Expected): The expected percentage move of a wave from start to end, derived by extrapolating the current wave structure.

Expected magnitude can be used similarly to expected duration, in that it is a measure of the overall expected size of a wave. For example, rather than using expected duration to find waves, it may be preferable to use expected magnitude. After all, the 1987 crash was a zigzag pattern with a large magnitude, but a short duration.

Note that magnitude is not the same concept as the height of a wave (the distance from its lowest to its highest price). A sideways pattern, such as a triangle or flat, may have a large height but a small magnitude. If you’re interested in searching for triangles or flats, duration is a better measure of size than magnitude is.

Magnitude is asymmetric because a 100% increase is the same log distance as a 50% decrease. We could have made it symmetric by changing the units to log-returns, but (1) that is less intuitive for most people and (2) the natural asymmetry of percentage changes is often desirable when considering stocks and ETFs.

• Magnitude (Remaining): The expected percentage a wave must travel from today’s price to reach its completion. This is derived by extrapolating the current wave structure.

Remaining magnitude is useful to filter waves based on the expected percentage change from current prices. For example, you may wish to look for C waves of flats that have a remaining magnitude of at least 30%, and a remaining duration of less than 90 days.

Note that the remaining magnitude of a wave increases when a counter-trend move occurs, reflecting the fact that there is now a greater distance between the current price and the wave’s expected target.

• Retrace: The retracement of a wave thus far, relative to the wave that precedes it. For example, a 2nd wave that falls by 70% relative to the preceding 1st wave would have a retrace value of 70%. A 5th wave that exceeds the high of wave 4 would have a retrace value exceeding 100%.

Retrace is useful for finding waves which have made new extremes. For example, requiring a 3rd wave to have a retrace value over 100% implies that wave 3 has broken out relative to waves 1 and 2. Such a breakout is the minimal structural definition of a trend.

Retrace is also useful for the opposite purpose: finding waves which have not made new extremes. For example, requiring a 5th wave to have a retrace value under 30% implies that wave 5 still has the potential for plenty of net travel relative to wave 4.

• Slope: The slope of a wave thus far, measured in %-per-year from the start of the wave to the current price. Like magnitude, this value is asymmetric, since a 100% increase-per-year is the same log size as a 50% decrease-per-year.

Slope is a useful mechanism for finding high-momentum trends, regardless of where they are within the wave structure. Since it does not perform any extrapolation, this is a more classic definition of momentum than the expected slope or remaining slope attributes.

One caveat with slope is that short-term waves are much steeper than long-term waves. (This is the case because the component waves of a parent wave are each partially retraced, so they must be collectively steeper than the parent wave.) For a slope comparison to be meaningful, compare waves within the same asset class and ensure that the waves are of comparable duration.

• Slope (Expected): The expected slope of a wave at completion, derived by extrapolating the current wave structure.

The expected slope is useful for finding high-momentum waves, even if their observed near-term momentum has waned. For example, wave 1 may be high momentum, but may be being partially retraced by a wave 2. While the retracement reduces the slope of the larger impulse wave of which waves 1 and 2 are a component, the retracement does not reduce the expected slope of the larger impulse wave.

Expected slope is more powerful than traditional momentum measures since it anticipates future slope rather than just measuring current slope.

Slope (Remaining): The expected remaining slope of a wave to completion, derived by extrapolating the current wave structure.

The remaining slope is useful to rank waves based on the expected move-per-unit-time from current prices. For example, you may wish to look for 3^rd waves with an expected duration around 200 days and then sort them by their remaining slope. Unlike expected slope, waves with high remaining slope will sometimes be within deep corrective structures, because this fact increases their remaining potential. This means that some waves that rank highly in terms of remaining slope will have a completely different look than those that rank highly via traditional momentum measurement methods.

Please contact us with a detailed description of the wave attribute that you care about, and we’ll consider it for addition into the WaveFinder.

EWAVES Live itself has two main data files that drive the WaveFinder. The easiest way to download these files is by logging into EWAVES Live and downloading them from there.

• markets.json defines the markets for EWAVES Live, with their attendant metadata. It has no dependencies on any other files.

• waves.bin is a supplementary file (which depends on markets.json for market definitions) that is required for the WaveFinder. It defines attributes for every currently unfolding wave in every market.

Please note that the formats for these files are subject to change any time EWAVES Live is upgraded. Therefore, if you wish to take a long-term, hard dependency on EWAVES’ data output, you should probably contact us.

markets.json is a JSON text file. It is so simple and self-documenting that the best way to understand it is to download the current file and simply take a look.

waves.bin is a binary file, composed of a contiguous linear array of waves, representing the set of unfolding waves across all markets. Each wave is a simple POD (plain old data) structure.

The waves are ordered thusly:

• Each wave has a market ID, which links it to a market in markets.json. The waves in waves.bin are written primarily in the order of their market IDs.

• Each wave also has a degree, with the largest degree wave being degree 0, the next-largest being 1, and so on. The waves are written secondarily in the order of their degrees.

• Finally, every single unfolding wave has a matching prior wave (for example, an unfolding wave 5 has a prior wave 4). So, waves are written in pairs, with the prior wave first, and then the actual unfolding wave after.

For example, the set of waves looks something like this:

[market 0, degree 0, prior wave]
[market 0, degree 0, wave]
[market 0, degree 1, prior wave]
[market 0, degree 1, wave]
…
[market 1, degree 0, prior wave]
[market 1, degree 0, wave]
…

The wave structure itself is best represented by the following Rust code snippet:

// Represents the pattern formed by a wave's internal structure
enum WaveType {
    Impulse,
    Diagonal,
    Zigzag,
    Flat,
    Triangle,
    DoubleZig,
    Unknown
}

// Represents the position of a wave in a larger pattern
enum WaveLabel {
    _1, _2, _3, _4, _5, // position in impulse/diagonal
     A,  B,  C,         // position in zigzag/flat
     W,  X,  Y,         // position in double-zig
     a,  b,  c,  d,  e  // position in triangle
}

// wave structure (18 bytes)
#[repr( C, packed )] #[derive( Copy, Clone, Debug )] pub struct Wave {
    market: u16, // which market this wave is a member of
    degree: u8, // largest wave is degree 0, next-largest is 1, etc.
    zoom: u8, // the smallest zoom level that can view this entire wave
    type_label: u8, // type (4-bits) | label (4-bits)
    elliotticity: u8, // % elliotticity, from 0 (0%) to 200 (100%)
    linearity: u8, // % linearity, from 0 (0%) to 200 (100%)
    complete: u8, // % complete, from 0 (0%) to 200 (100%)
    duration: f16, // years (365.2425 days) from start to now
    duration_remaining: f16, // expected years from now to end
    magnitude: f16, // 100x-log-return from start to now
    magnitude_remaining: f16, // expected 100x-log-return from now to end
    retrace: f16, // % retracement thus far relative to prior wave
}