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Interpreting Price Data: Magnitude and Velocity
When monitoring price action, and using it to find and filter trades, understanding magnitude and velocity will likely have a great impact on your trading success (or failure if you don’t understand these concepts). These terms are simply used to refer to how far the price has run in a particular direction–magnitude–and how fast it covered that distance–velocity. By monitoring both these factors, you’ll likely enhance your performance by finding high probability trades when certain conditions materialize, seeing when trends turn on strong moves, and avoiding times of choppy low magnitude and velocity price action.
Magnitude is simply how far a price run is. A long run, where the price moves relentlessly in one direction for a long period of time has a strong magnitude, and is what we want to see during trending waves.
Magnitude can also be used to interpret small waves. Price waves of small magnitude show that the price isn’t moving strongly in that direction, and therefore we want to see price waves of small magnitude on pullbacks.
There is no set magnitude reading which will indicate a strong buy or sell reading. Rather it is always relative to prior waves. There are multiple ways to use magnitude for interpreting price action.
- Waves of large magnitude in the direction of the trend confirm that trend.
- Waves of large magnitude against the trend direction indicate a potential reversal, or at least a significant pullback, is underway.
- Waves of small magnitude in the trending direction indicate the trend may be losing steam, since the trend can no longer produce waves of large magnitude.
- Waves of small magnitude on pullbacks (against the trend) indicate a healthy trend and the trend is likely to continue after the pullback completes.
Think of magnitude in degrees. A very strong wave carries more weight than a strong move. A very small wave shows an even greater lack of conviction than a small wave.
Figure 1 shows a downtrend in the GBPJPY on a 1 minute chart. Notice how the trend can be confirmed simply by looking at the magnitude of the price moves. Throughout the move lower the waves down were of greater magnitude than the waves higher, indicating the trend was likely to continue.
Figure 1. Using Magnitude in Downtrend: GBPJPY 1 Minute Chart
Velocity also helps us assess price action, and is used in conjunction with magnitude.
Velocity is simply how fast the price covers distance. A very fast move shows more conviction than a very slow move.
Looking at the same downtrend, we can include velocity to confirm our expectations that the downtrend will continue. Moves down are not only larger, but they occur faster–taking less time to cover more distance. Having both magnitude and velocity occurring primarily in one direction is a powerful combination.
Figure 2. Using Velocity (and magnitude) in Downtrend: GBPJPY 1 Minute Chart
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This provides compelling evidence that the downtrend will continue, until there is either a move higher that has greater magnitude than the major down waves, or a wave higher occurs with significant velocity (and respectable magnitude) that indicates buyers are once again entering the market with conviction.
Magnitude and velocity are arguably two of the most important factors when assessing price action. Even so, it doesn’t mean you won’t have losing trades. It is simply evidence to help find and filter trades. Prices can always do erratic things, causing losses despite the evidence that is gathered. Always keep an open mind when trading, absorbing new evidence and monitoring the magnitude and velocity of new price waves as they form.
Improve Your Price Action Trading with Velocity and Magnitude
Improve your trading by analyzing price action, especially velocity and magnitude. As a price action trader, these concepts are crucial for analyzing and making profitable trading decisions in stock, forex or futures markets (or any other market).
Price is the ultimate indicator, it tells the real story. While other technical indicators may help summarize price data, price movement is the basis from which (most of) those indicators are derived. It follows that having advanced price-action-analysis skills will aid your trading. Price action trading is making trading decisions based on price movement itself, without the aid of other technical indicators (although trendlines, marking up your charts and using Fibonacci retracements levels are common among price action traders).
The Importance of Velocity and Magnitude When Analyzing Price Action
Every price wave within a trend can be judged based on velocity and magnitude. Therefore, at every stage of the trend assessments can be made about the probability of trades in regards to that trend.
If a trend is strong based on velocity and magnitude we know that we want to take the next valid trade signal (based on our trading plan) that will get us into that trend. If velocity and magnitude are significantly weakening then the trend may be ending and therefore the next trade signal may be filtered out (not taken), or our expectation/target for the trade lowered. For example, in the latter case, if we are day trading and our target is typically $0.15 away from our entry, but velocity and magnitude are slowing
Price Action Trading: The Magnitude of Price Waves
Magnitude, in regards to analyzing price action, refers to the length of price waves, relative to other price waves of consequence. If the price runs for a long way in one direction without a significant pullback, then that run has strong or large magnitude. During a trend we want to see the impulse waves (waves in the direction of the trend) have large magnitude than pullbacks.
Short or small price waves have little or weak magnitude. The price is not moving aggressively in one direction. During a trend, pullbacks should have weak magnitude relative to the impulse waves of the trend.
Figure 1. Analyzing Price Action using Magnitude: GBPYJPY 1 Minute Chart
Magnitude is not measured in absolutes; it is always relative to other price waves. Waves are measured against recent waves, as well as the overall outlook (looking at the bigger picture). In figure 1 the trend is down because the impulse waves are larger than the smaller pullbacks. Toward the middle of the chart there are some stronger pullbacks, relative to recent down waves. While this may deter us from taking a short position for a period of time, looking at the overall outlook the pullback is not big enough to rival the major down waves.
Here are some basic guidelines for analyzing price action with magnitude:
- The trend is confirmed by waves of large magnitude in the trending direction.
- A reversal has begun, or deeper pullback is underway, when a wave of large magnitude (relative) occurs against the prior trend.
- A trend may be losing momentum if small waves start to occur in the trending direction. The trend isn’t over yet, it is just potentially weakening (it’s possible to have several slow waves in the direction of the trend, only to be followed by another strong wave renewing the strength of the trend–this is why we don’t assume the trend is over just because there are small waves in the trending direction).
- Pullbacks of small magnitude, relative to the impulse waves of the trend, confirm the trend.
Compare a pullback to other pullbacks, impulse waves and the overall trend. Do the same for impulse waves; comparing them to other recent impulse waves, recent pullbacks and the overall trend.
It can also help to view another time frame as well. If trading off a 1-minute chart, (like above), it may help to view a 5-minute chart as well. This will provide a slightly broader perspective, and you may notice some relative strengths or weaknesses in waves that you hadn’t noticed on the shorter time frame chart.
Price Action Trading: The Velocity of Price Waves
Velocity is how fast price covers distance, and is used in conjunction with magnitude.
A very fast price move which covers a significant distance (relative) shows greater conviction than a wave that moves very slowly.
Figure 2 shows the same chart as above, yet we can also use velocity to analyze this chart, in conjunction with magnitude. Moves down are not only larger than pullbacks, but they occur faster than the pullbacks–the impulse waves down cover more distance in a quicker amount of time.
Having magnitude and velocity on the side of the market you are trading is ideal (for example, taking short positions when strong velocity and magnitude are to the downside).
Figure 2. Analyzing Price Action using Magnitude and Velocity: GBPYJPY 1 Minute Chart
Velocity is most applicable when combined with magnitude. A short burst of velocity isn’t particularly important, since it could just be one or two big orders being filled in the market. A move of large magnitude which also has velocity shows a lot of power and conviction, and may either confirm the trend (if in the trending direction) or indicate a reversal (if moving against the trend).
Extremely large moves with substantial velocity (both relative to recent price action) usually indicate some sort of news announcement or some unusual event. Even in extreme cases such as these, velocity and magnitude play a role. Watching the size of the waves, and how fast they move (relative to each other) can provide insight into where the price is most likely to go next.
How to Use This Information When Trading Based on Price Action
Analyzing price action is a constant task. Being able to adjust to new information is critical. This cannot only be down in hindsight, it must be done in real-time. As waves are unfolding talk to yourself, assessing the wave’s velocity and magnitude in this moment. If you only react to it in hindsight, you will always be entering/exiting trades late.
How can you use this in real-time? Here is a trade that I take regularly, and it is almost entirely based on velocity and magnitude. Assume the trend is down, and the last wave down was 20 pips (day trading forex). The price starts to rebound, quickly, and rallies 25 pips before starting to drop again. The rally had bigger magnitude than the last down wave (and possibly more velocity as well). That tells me the price has reversed to the upside (not longer a downtrend). But I don’t do anything yet. I am now biased to buy, but I wait to see how the price reacts when it starts to drop. Assuming the pullback has less velocity than the rally, I will enter a trade on that pullback, expecting upward momentum to eventually kick in again, taking the price higher. Basically, I am taking the information I have and making assessments on whether I believe the current pullback (which is where I typically take trades, in the direction of the trend) will be of smaller magnitude than the last impulse wave, based on the velocity and magnitude of prior waves and the velocity and magnitude of the price right now. While this strategy is based largely on velocity and magnitude, the method still requires a trade trigger, stop loss and profit target, so you need to incorporate a few more elements to make velocity and magnitude a complete strategy.
Velocity and magnitude are also incorporated into almost every other strategy I use. For example, if the price has plummeted a long way, and then forms a double bottom chart pattern composed of small waves (compared to the drop), I am not likely to use that double bottom pattern as a buy signal. The selling momentum was too strong, and I don’t want to buy into that. BUT, if the price plummets, rebounds, has a small wave to the downside, and then forms a double bottom pattern, that is more enticing as a buy signal. Before the double bottom even occurred the price was already showing signs that the selling momentum was slowing (smaller wave before the double bottom). The same concepts apply to most chart patterns, trend trading, range trading as well as front-running (predicting chart pattern breakout direction).
Traders may wish to develop some guidelines or rules about velocity or magnitude in their trading plan. While these concepts are relatively simple to understand in theory, I consider them advanced trading techniques because they have the potential to turn a rule-based system (which most new traders use) into a hybrid trading system. A hybrid system is one which has rule-based elements incorporated with more subjective elements such as interpreting velocity and magnitude.
You’ll need to hone your price analysis skills in a demo account, and only when you see–over many trades–that using this information provides you with an edge should you attempt to implement this knowledge using real money.
Agreeing that something works or can aid your trading is very different than actually being able to do it, and using that knowledge in real time trading. Therefore, practice, practice, practice. It is always easier to do this in hindsight, and that will be the starting point as you begin to practice using these concepts. Go through historical charts, analyze velocity and magnitude and how it impacted the trend, as well as potential trades you may have taken. Then proceed to trade using this information in a demo account, marking up charts in real-time, noting changes in velocity and magnitude, and how those changes affect the price waves that follow (see 5 Step Plan for Forex Trading Success).
Realize that velocity and magnitude are constantly in flux. We must look at an overall picture of what is occurring as well as note details about each wave. This is the study of current price waves relative to recent price waves. There is still an element of uncertainty. Everything can look great and we will still lose trades. By analyzing price action based velocity and magnitude–and being able to effectively act on the information we interpret and alter our expectations/targets–those losing trades will hopefully happen less often for you.
By Cory Mitchell, CMT Follow me on Twitter @corymitc and check out our Facebook page.
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MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains seasonal (winter) ice sheet-wide velocity maps for Greenland. The maps are derived from Interferometric Synthetic Aperture Radar (InSAR) data obtained by the Canadian Space Agency’s (CSA) RADARSAT-1, the Japan Aerospace Exploration Agency’s (JAXA) Advanced Land Observation Satellite (ALOS), and the German Aerospace Center’s (DLR) TerraSAR-X/TanDEM-X (TSX/TDX) satellites, as well as from the European Space Agency’s (ESA) C-band Synthetic Aperture Radar data from Copernicus Sentinel-1A and -1B.
This is the most recent version of these data.
For Version 2, all velocity maps underwent quality control screening to remove erroneous data points. In addition, the following measures were performed:
- Added new map for 2009/2020.
- Added ALOS fine-beam data to improve coverage in 2006/2007, 2007/2008, and 2008/2009.
- Corrected a substantial error on Rink glacier where the time interval was off by a factor of 2.
- Improved baseline fits for consistency in the interior of the ice sheet.
- Updated error estimates to better represent the average behavior of the data.
- Added/updated shapefiles of satellite tracks for 2020 to 2020 winters.
- Added browse files for 2020 to 2020 winters.
- Updated the velocity magnitude (vv) file name.
- Changed the missing data value for the velocity magnitude (vv) files to -1 and set it as the attribute in all files.
COMPREHENSIVE Level of Service
Data: Data integrity and usability verified; data customization services available for select data
Documentation: Key metadata and comprehensive user guide available
User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services
Other Access Options
Once you have logged in, you will be able to click and download files via a Web browser. There are also options for downloading via a command line or client. For more detailed instructions, please see Options Available for Bulk Downloading Data from HTTPS with Earthdata Login.
Earthdata Search: This application allows you to search, visualize, and access data across thousands of Earth science data sets. Additional customization services are available for select data sets, including subsetting, reformatting, and reprojection.
Worldview: This application allows you to interactively browse global satellite imagery within hours of it being acquired. You can also save it, share it, and download the underlying data.
As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.
Joughin, I., B. Smith, I. Howat, and T. Scambos. 2020 , updated 2020. MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/OC7B04ZM9G6Q. [Date Accessed].
As a condition of using these data, we request that you acknowledge the author(s) of this data set by referencing the following peer-reviewed publication.
Joughin, I., B. Smith, I. Howat, T. Scambos, and T. Moon. 2020. Greenland Flow Variability from Ice-Sheet-Wide Velocity Mapping, Journal of Glaciology. 56. 415-430.
Detailed Data Description
This data set contains eleven winter Greenland ice sheet-wide mosaicked velocity maps derived from SAR data. Depending on the year, different platforms and sensors were used to produce these data (see Table 3). For each winter, a shapefile is included to indicate the source satellite image pairs that were processed to produce the mosaic. Since speckle tracking may fail to produce results at some points within a SAR image pair, the swaths listed in the shapefile only indicate which data could have contributed to a particular point (i.e., some data from that swath were used in the mosaic, but at any particular point, there may not have been a valid result from that swath).
For maps of glacier outlet areas, some of which demonstrate profound velocity changes during the observation period, see the related data set MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from InSAR.
Data are available in GeoTIFF ( .tif ) format. Five GeoTIFF files are available for each winter product: a velocity magnitude map ( vv ), separate x- and y-component velocities ( vx , vy ), and separate x- and y-component error estimates ( ex , ey ). For the years 2020 to 2020, a shapefile ( .shp ) with the source satellite information as well as a browse ( .jpg ) image of the velocity magnitude with a color log scale saturating at 3000 m/year are provided.
The file naming convention used for this data set is:
greenland_vel_mosaic_2020_2020_ v02.1 .shp
The following table describes the individual components used in the file names.
The total GeoTIFF volume is approximately 12 GB and the total JPG volume is approximately 418 MB. The total shapefile ( .shp, .dbf, .shx, .prj ) volume is approximately 3 MB.
The entire data volume is 13.3 GB.
This data set covers Greenland.
Southernmost latitude: 60° N
Note: Prior to 2020, the data are provided only at 500 m resolution.
Data are provided in a WGS 84 polar stereographic grid with a standard latitude of 70° N and rotation angle of -45° E (sometimes specified as a longitude of 45° W). With this convention, the y-axis extends south from the North Pole along the 45° W meridian.
The following table provides information for geolocating this data set.
This data set provides velocity data for the winters listed in Table 3. The data sources and their agencies are:
(*) Note: For the 2020/2020 winter, the first track starts on 03 March 2020. There is a temporal gap between that date and the rest of the data, which continue on 10 November 2020. The later date was chosen as the directory name for that winter (i.e., /2020.11.10/ ).
Velocities are reported in meters per year. The velocity magnitude is reported in the vv files. The vx and vy files contain the velocity components in the x- and y-directions, defined by the polar stereographic grid. These velocities are true values and not subject to the distance distortions present in a polar stereographic grid. Small spatial gaps were filled via interpolation in some areas. Interpolated values are identifiable as locations with velocity data but no error estimates. Radar-derived velocities are determined using a combination of conventional InSAR and speckle tracking techniques (Joughin et al., 2002).
Error estimates are provided for all non-interpolated, radar-derived velocity vectors in separate GeoTIFF files appended with _ex.tif and _ey.tif . These estimates include the statistical uncertainty associated with the phase and speckle tracking error. Formal errors agree reasonably well with errors determined by comparison with GPS data (Joughin et al., 2002). The values, however, underestimate the true uncertainty in several ways, and should be used as an indication of relative quality rather than absolute error. Refer to the Error Sources section for more details.
The missing data value for the velocity magnitude ( vv ) files is -1 and is set as the attribute in all files. The missing data value for the velocity component ( vx , vy ) and error estimate ( ex , ey ) files is -2e+9.
Software and Tools
GeoTIFF files and shapefiles can be viewed with a variety of Geographical Information System (GIS) software packages including QGIS and ArcGIS. JPG files can be viewed within any browser.
Data Acquisition and Processing
The velocity maps in this data set were created by mosaicking multiple strips of InSAR-derived data. The methods include a combination of speckle tracking and conventional interferometry. Individual images were selected based on two criteria: images should be taken from the same winter; and the time span between images from any given winter should be as short as possible. For more detail, refer to Joughin et al. (2002).
Annual mosaics were created using data collected during each Greenland winter. Spatial gaps exist either because no data were available or because interferometric correlation was insufficient to produce an estimate in those regions. The latter is most often the case in regions with high snow accumulation. In regions with sufficient data, the averages are based on up to three measurements. Typically, more data are available in regions of swath overlap, especially at higher latitudes.
The data are gridded at 0.5 km resolution, but the true resolution varies between 0.5 and 1 km. Many small glaciers are resolved outside the main ice sheet; however, for glaciers that are narrower than 1 km, the velocity represents an average of both moving ice and stationary rock. So, while a narrow glacier may be visible on the map, its speed is likely underestimated. Furthermore, interpolation produces artifacts where the interpolated value is derived from nearby rock, causing apparent stationary regions in the middle of otherwise active flow. In such instances, the data should be interpreted with care.
The following sections briefly describe how the mosaics were generated for each winter.
In late 2000 and early 2001, during the RADARSAT-1 Modified Antarctic Mapping Mission, CSA acquired nearly complete coverage of Greenland with multiple passes suitable for InSAR (03 September 2000 to 24 January 2001). All of the available data for Greenland were used to produce the 2000/2001 mosaic. In cases where the data quality was too poor, some products were discarded. All source data were obtained from the Alaska Satellite Facility (ASF).
In 2005 and 2006, RADARSAT-1 imaged most of Greenland on four consecutive missions, producing three InSAR pairs. Once all of the data were processed, poor coherence passes were screened out and the remaining data were used to assemble the 2005/2006 mosaic.
The 2006/2007 mosaic was produced with RADARSAT-1 fine-beam data. Coverage is substantially improved by including ascending JAXA ALOS quad-pol data, including coverage in the southeast of Greenland. The ionospheric errors are often large (>20 m/year) in the ALOS data; therefore, points were manually removed where errors were excessive. This approach was chosen in order to balance maximal coverage with minimal error. Nevertheless, these data should be interpreted with care, particularly in the southeast region.
The 2007/2008 mosaic was produced with RADARSAT-1 fine-beam data in the same manner as the 2006/2007 mosaic, including the use of a substantial volume of ALOS fine-beam data, largely along the northwest coast.
The 2008/2009 mosaic utilizes data from CSA’s RADARSAT-1, the DLR’s TSX, and JAXA’s ALOS satellites.
The 2009/2020 mosaic consists almost entirely of ALOS SAR data collected in Fine-Beam, Single-Polarization (FBS) mode. Because L-band is more subject to ionospheric distortion of speckle-tracked azimuth offsets, streak errors for some areas are large (>10 m/year), often exceeding the magnitude of the accompanying error estimates. In other areas, these errors are barely perceptible. Some of the worst streaks were edited out. However, a number of lesser streaks were left in place to preserve coverage and illustrate the magnitude of these errors with obvious examples. Despite being more susceptible to ionospheric distortion, L-band data correlate well in areas with high accumulation. As a result, this map has better coverage in the southeast than many of the maps from other winters.
Twenty coastal sites in this mosaic utilize 30 km x 50 km TSX scenes. These X-band data greatly improve the results for many of the fast-moving outlet glaciers.
The data for the 2020/2020 mosaic were collected from January 2020 to March 2020, which corresponds to the last months during which RADARSAT-1 was active. These data were combined with TSX winter data from November 2020 to March 2020.
General Information for 2020 to 2020
The 2020 to 2020 mosaics were produced mostly with ESA’s Copernicus Sentinel-1A/1B data and supplemented by DLR’s TSX/TDX data for coastal outlets. The data for the 2020 to 2020 mosaics were acquired in either 12-day (through 16 September) or 6-day repeat cycles (16 October forward). In cases of missing acquisitions, the repeat periods may be longer (i.e., integer multiples of 6 or 12 days) for some of the image pairs.
Unlike earlier SAR acquisitions, Sentinel-1A/1B provides crossing ascending and descending orbit data over much of the ice sheet. In areas where data from crossing orbits were available, an error-weight range-offset-only solution was included in the velocity product, eliminating azimuth offsets and reducing the error from ionospheric streaking in the azimuth offsets.
To take advantage of the year-round Sentinel coastal coverage, data are collected during Greenland winter periods with little or no melt. This definition might produce small seasonal differences compared to mosaics from other years in which narrower acquisition periods were used. However, such differences are generally small relative to inter-annual variability and to the noise reduction accomplished by averaging a greater volume of data acquired over a longer time period.
Due to the reduction in the resolution of Sentinel-1A/1B SAR data, some systematic differences between the mosaics produced by RADARSAT, ALOS, and TSX/TDX data may exist, especially in regions with sharp gradients or strong curvatures. Smoothing earlier velocity results to approximately 1.5 km resolution (i.e., to roughly the resolution of Sentinel-1) should improve agreement among data sets. In producing the mosaics, higher resolution TSX/TDX data are given more weight, hence the loss in resolution should be smaller in these areas. These mosaics are posted at both 0.2 km and 0.5 km spacing. For work requiring a finer resolution, see Version 1 of the MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from InSAR data set.
As a result of the large volume of data used, the overall quality of the data is good. Compared to earlier products, the coverage in the southeast is generally improved, particularly for 2020/17; however, high accumulation in the southeast reduces image-to-image correlation, resulting in higher noise. Additionally, there may be coherent displacement signals in these regions that are not associated with horizontal ice motion. If such displacement occurs with characteristics other than those assumed in the solution (e.g., predominantly vertical instead of horizontal displacement), then the result will be incorrectly mapped to horizontal motion, contributing to the overall level of noise.
The 2020/2020 mosaic was largely produced from TSX data, with the addition of Sentinel-1A data. As Sentinel-1 data acquisition began during this winter period, there are almost no Sentinel-1 data prior to January 2020, with the exception of the region around the Jakobshavn glacier. As a result of the limited satellite coverage, the 2020/2020 mosaic contains more noise and less spatial coverage than the 2020/2020 and 2020/2020 mosaics.
The 2020/2020 mosaic was largely produced from Sentinel-1A data. The six tracks that covered nearly the entire coast were collected at almost every 12-day interval. In the interior, typically four images (i.e., three pairs) were collected with better coverage and fewer errors than the 2020/2020 mosaic.
The 2020/2020 mosaic was largely produced from Sentinel-1A/1B data. In October 2020, Sentinel-1B started acquiring data over Greenland in an orbit that lags behind Sentinel-1A by six days. As a result, Sentinel-1A/1B pairs are often separated by only six days, providing better correlation and coverage, particularly in the southeast of Greenland. Thus, the mosaic for this winter provides almost complete spatial coverage relative to all prior winter velocity products.
The 2020/2020 mosaic was largely produced from 6-day repeat cycles from Sentinel-1A/1B. In general, more data were collected in the ice sheet interior during this winter mapping campaign. As a result, this mosaic should have a lower level of noise in the data relative to prior winter velocity products. The 6-day sampling also provides better coverage because the image-to-image correlation is improved with shorter time intervals.
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