What separates crypto from traditional stocks and derivatives is that all transactions, data and information is immutable on the block chain, to be gathered and seen by any. By using a simple data tool, Omniscope, and the raw data gathered directly from the bitcoin block chain we can produce graphs and set conditions for relatively accurate buys and sells. This article explores on-chain metrics, market sentiment, block chain address activity and several supply and profit metrics. 

Supply in Profit

To start with we take a look at the supply in profit metric. This indicator is shown as a percentage with a lower band at >50% and upper band at <95%. In general when taking a macro view of the market, it is important that not too many investors are sitting on profit if you want the asset to climb in price. As more market participants become profitable, there is a higher likelihood of them selling. When the supply in profit reaches 95% or above, the market is due for a correction. As seen in the view below, the last times this occurred was during the latest price peak in November 2021 and the top of the previous leg back in April 2021. December 2018 was the last time that the % supply in profit dipped below 50%, and was indeed the best buying opportunity in the last 5 years.

% of inactive supply

The chart below shows the % of total supply inactive for 1 year or more. More bitcoins remaining inactive means that they are being held instead of traded, and indeed leads to higher prices being found shortly after. More specifically, if we were to take a look at each time the % of supply inactive reaches new all time highs after finding a macro bottom, we would see that it represents a shift in sentiment and price action. Historically each time a new high is made with this metric, it acts as a leading indicator for future bullish price action. First seen half way through 2012, a new high of 35% of all bitcoins remaining inactive for over a year signaled the macro bottom of that bearish period, and those prices were never seen again. Similarly in January of 2015, bitcoin supply inactive reached a new high of 55%, only a month shy of the macro bottom for that specific bearish period. The last time a high was formed was in July of 2020, preceding the recent run up to $64k. This metric is an excellent indicator for long term macro trend shifts, and should be on  every trader’s radar as a gauge of upcoming momentum shifts and large price moves. Currently this metric reads 62.5%, a level to keep an eye on as we head close to previous highs. 

Net Unrealized Profit/Loss

Next we take a look at NUPL, one of the more popular macro indicators for determining market sentiment. It calculates the total amount of profit or loss in the market. The NUPL value oscillates between 1 and -1.5, and contains bands within each representing market sentiment at that point. The market is in a state of euphoria when the NUPL value is above 0.75 and is shown by the colour blue. Green stands for belief, orange hope and red capitulation. Below is a view of the NUPL plotted with price after bitcoins second halving. Note the capitulation values shown by the NUPL metric are at the exact bottoms of price during the 5 year period. Furthermore, the cycle top of 2018 could have been predicted by the <0.75 reading on the NUPL, turning the bar blue. Selling at euphoria and buying at capitulation seems to be a solid macro strategy. 

As seen from the view, euphoria states are almost never reached, with the last time being in December of 2017, at the peak of the previous bull market. Previously euphoria was reached in 2013 and 2014, both occurring at the absolute top price points of their periods. The last 2 capitulation periods found in the data were the march 2020 crash and the 2018 bear market trough. These were the best buying opportunities for bitcoin in the last 5 years. 

Fear and Greed

Finally, we explore the fear and greed index. The cryptocurrency market is very emotional, consisting largely of retail investors easily spooked by negative price action. Since the asset class could still be considered in its infancy, the lack of liquidity on the order books leads to massive sell-offs in times of crisis or extreme fear. The retail reaction to fear is to sell and “take what you can while you still can”. Similarly a rising market brings strong emotions of greed and FOMO, oftentimes leading investors to overexpose themselves to risk through leverage and derivatives. During these times, the market is usually due for a correction. 

Since the market fluctuates between fear and greed, never staying at one end of the spectrum for too long, we can map the data and extrapolate the best course of action based on the values of this index. Data is gathered from five sources (volatility, market momentum, social media, dominance, trends) and combined to give a fear and greed value between 0 and 100. 

On the view above, the fear and greed values are shown by their marker colour, red indicating a fearful value and green a greedy value. It is clear to see when mapped onto price, that periods of fear are often good buying opportunities. This view shows price action between 2020 until current day. It seems that a cluster of 2 or 3 fearful bars are often followed by a mark up phase in price. Select fearful markers followed by the next greedy ones to see the % change in price had you bought at fear and sold in greed.

Here is the interactive report: Crypto Report

… and the video explainer

Enjoy!

N.B. This article does not constitute financial advice

The post Investing in Crypto – insights for a beginner trader with Omniscope appeared first on Visokio.

The first step in the process is thinking about meaningful questions, so a report can be developed to deliver relevant answers.

With the world’s attention span getting shorter, the analyst will also want to deliver these with a minimal number of charts. This is where the data artisan skills become useful…

Open data sources are everywhere and, in many cases, they come in a format that is not accessible to all potential users (xml, JSON, not just Excel), which means that only patient/ data literate users can interrogate the information and extract meaningful insights.

Curious? This tutorial will show you how to build the interactive dashboard presented below. Read more…

Feel free to play with the charts and filters to see the effects!

The post How to build a live data transaction report appeared first on Visokio.

Are you only as good as your last performance?  Analysis of the water quality in Europe in the year 2020 looks impressive – an assessment of coastline, lakes and transitional waters rated the majority of locations as “excellent”.  Star country Cyprus achieved a 100% rating, while only two countries recorded less than impressive results.

Focusing on Poland’s performance we see that only 22% of the sampling locations are rated “excellent”, also that 401 data points out of 602 never submitted a measurement. With these records filtered out, the situation has changed: 66% of the submitted results are rated “excellent”, which is in line with the country’s results in the last 10 years. It is worth noting that Poland recorded dramatic improvement in 2011, jumping from just 24% to 67%. So – Poland’s result can be attributed to the data recording method, rather than an actual poor performance.

(Link to the interactive report)

On the other hand – the UK has shown notably poor records against the European neighbours in the last 10 years and the country has managed to record a performance over 80% only in 2013.

According to the Guardian “All English rivers have failed to meet quality tests for pollution amid concerns over the scale of sewage discharges and agricultural and industrial chemicals entering the water system.” Also that “water companies had poured raw sewage into rivers on more than 20,000 occasions in 2019, and dumped thousands of tonnes of raw sewage on beaches.”

Similarly to Poland, only a subset of the 640 registered measuring locations reported results in 2020 (183). When only those results are taken into account, the rating is 60%, which still leaves the UK at the bottom of the league.

The post How to Visualise Geographic Time Data – Analysis of the Water Quality in Europe appeared first on Visokio.

As an example, in this particular video, we show you how you can set “project parameters” used in workflow configurations and trigger a data execution from a Report.
A way to allow your end users to refresh dashboards and complex workflows simply by tweaking some preconfigured params.

Enjoy
Feedback is always welcomed

The post How to set parameters and trigger workflow execution from a Report appeared first on Visokio.

Take a look at these new features – they should bring a smile to your face.

Data editing

Data Table block in the workflow, linked to the improved Table View in the Report, empowers project editors and report viewers to snapshot, query and edit data, to amend mistakes or add comments and push the edited data ‘upstream’ into the workflow. Read more

Data validation

Validate data block can automate multiple data quality scans, such as data schema and values. Create alerts should something fail the criteria or add an output with diagnostics report, telling you about everything that failed, so you can quickly identify the problems. More..

Data alerts

Email block makes communication an integral part of the data management process: notify the report viewer that their report is ready, or let the analyst know they need to fix something, by sending them those validation diagnostics.

Before you ask – email output is integrated with the Batch output block, so you can use it in the multi-user publishing scenarios. More…

Block bookmarks

Bookmark frequently used workflow blocks to avoid having to configure them repeatedly – works for the multi-tab Reports and coding blocks too!
Find more here

Salesforce integration

The Salesforce connector is now added to Evo, making it easy to integrate SF API with data coming from other sources to create a complete overview of your business, edit the CRM data, even publish it back to Salesforce, should you wish to.  Read more

Finally – we’ve added some features to make the report formatting easier.

As usual, make sure to check our changelog to see features making their way daily.

Stay tuned, stay safe and let us know if you have any feedback

#TeamVisokio

The post Rocking after Rock – new Omniscope features appeared first on Visokio.

Editing + Workflow Execution

Attached here you’ll find a IOZ file to import the project locally to play with 2 interesting features:

1. 1. Edit data from a Report using the “Editable Table” view.  When connected to a Text Input or Data Table block the view allows you to perform data edits as if it was a simple spreadsheet app.
   2. Execute specific blocks of a Workflow through a Custom view in the Report app which uses the Workflow REST API

A simple custom view to control Workflow Execution from the Report has been added to our GitHub repo, you’ll find it in your Omniscope Evo by clicking on the Add View menu (alt+A) -> and selecting or typing “Workflow Execution”

A video which describes the project is available here. Enjoy.

The post How to Edit data and Execute Workflow from Report appeared first on Visokio.

Considering the context of a web based report, the only chance to embed a web page is by using a <iframe>.
To achieve that we have developed a simple Custom view, (code available on our GitHub repo https://github.com/visokio/omniscope-custom-views/tree/master/web ) which you can install on any Omniscope Evo versions directly from the “Add View” menu.

The view navigates to a URL link according to the current selection / filter state. If multiple records with multiple URLs are selected the view won’t show any content. You can play with the URL setting in the view options to control this behaviour (e.g. by changing which function to apply on the field), by default a “singleton” function is used on a text field.
N.B. some pages might not load when loading content in a iframe is not permitted by their server.

Here is how it looks, select a Url in the report below and try it yourself.
P.S. Pardon the matryoshka effect of embedding an Evo report in a web page, which contains a web page with a Evo report, which contains a web page…

Report

No Description

The post How to Show dynamic web content in a dashboard appeared first on Visokio.

At the top a simple pivot view shows all the evaluated weekly correlations for each cryptocurrency, coloured by range and sortable.

The bar / line charts show the average Volume as bars, the close average price and the correlation average in that split interval.

Finally filters on the right allow you to drill down and explore data over time.

Tap on the image to open the interactive report

Needless to say… we haven’t found a pattern which can predict price movement with absolute certainty… but we are looking into it, for instance we tried to predict the Bitcoin price for the next few months by doing Time series forecast using Holt-Winters method. Here’s the results:

Tap on the image to open the report

And here using ARIMA model to forecast Bitcoin future value:

Tap on the image to open the report

If you are curious to see how we implemented the data workflow and the dashboards you can check the project here : Prices trend
We will refresh the data from time to time to keep the experiment live.
Comments are always welcomed.

The post CryptoCurrency Volume / Price correlation analysis – Is there any pattern? appeared first on Visokio.