Valuing crypto-assets with “Behaviour Elephant Analysis”

Disclaimer: I am NOT a financial advisor, and nothing below should be taken as investment advice. It might be I’m just a lucky guy who gets it right from time to time.

This article started as a small one with the intention to share some exciting visual insights into the crypto world. Yet, as time went on (I’ve spent three days on this article) — I had to cover more and more topics to make it sound reasonable, fluid and understandable for anyone reading it.

The text below might read sometimes like “too much financial and speculative info” or “too technical and only for IT geeks” or even “it is only for those crazy people who believe they can change the way valuable information is created and distributed”.

So, keep this in mind while reading:

If you’re a talented blockchain data scientist and get bored at the beginning, the deeper and further we go, the more interesting it might become for you.

If you’re a pragmatic crypto currency investor and get excited in the beginning but become tempted to stop reading the later part — do your best to get through it. Try to understand why the data, and the way we (crypto participants) have to deal with it, is so important.

Crypto is a social (r)evolution. Profits are just one of the measurements. Not always the best one, but often good enough to make us work together.

The Challenge Ahead

Valuing cryptocurrency assets is a challenging task. You need to constantly decide if the value of the crypto market in general, or a specific asset, is too high, too low, or more or less “ok”.

Why does this become “obsessive” behaviour? Well, the answer is simple — because the potential profits of making the right decisions are pretty insane. But so are the risks of making the wrong ones.

To be clear — no one can eliminate the risks completely. No one can make “right” decision in financial markets all the time. But it’s possible to address the risks as they come.

Based on the experience we’ve collected over the last few years, we want to kick-off a dialog, to share our practical approach to generating insights into the cryptomarket, and to scale up this approach once the framework we’re building for it gets real traction.

A few words about why we want to “scale it up”:

The crypto space is plagued with dozens of problems. Scams, pump-&-dumps, lack of transparency… the list goes on. Though we love self-regulation (even co-founded “Project Transparency” back in September 2017), we also believe there is another sustainable and profitable way toward risk management.

It starts on a personal level, and it’s P2P. If you know how to avoid “buying the tops” and “selling the bottoms”… and you teach someone else so that he also knows… and so on… more people will become informed on what makes projects “overvalued” (or “undervalued”), and the more efficient and faster price discovery will become.

To be clear — not everyone will be able to measure crypto assets properly. Only those with skills, dedication, and the right effort based on the proper approach can learn how to see through the noise.

Sound ambitious? Yes, it may be. But we’ve been following small steps for more than two years now and seeing where it goes.

In this article we will talk about:

  1. An introduction to “Behaviour elephant analysis”
  2. A look into on-chain data, giving 4 recent examples
  3. Conclusion & invitation to participate/collaborate

Let’s go. We know, time is precious. Even more so in crypto.

1. What the heck is “behaviour elephant” analysis?

Well, call it “quant analysis for the blockchain era” if you wish, though we personally believe this name is boring and smells like Wall Street.

Therefore we will keep calling it — “behaviour elephant analysis”.

It is a practical method of analyzing the crypto market. Seeing through noise. Getting insight. How do we do it?

Let’s break it down:

Behaviour: We start with this term because price discovery is heavily based on how humans behave when they interact with money or things of value. Cryptocurrencies, blockchains… let’s keep it simple. It’s all about value. “Internet of value” is being built right now, with some specific side-effects.

One of the side-effects is that the things have changed from how they were 5 years ago. 70-80% of crypto market participants are here today solely to make money. Once institutional investors are allowed to participate, we will have 95% in it just for the money.

And once value/money is involved we (humans) behave as we always do. We are greedy (want to get more) or filled with fear (of missing out or losing it). Rarely (almost never) do we land in the middle and act rationally.

When the price or value is increasing, we feel good. The more it goes up, the better we feel. It goes so far, that these emotions almost completely take control over the mind. The same goes when the price starts declining. The name of the emotion is different, but the result is the same. The stronger the emotion gets, the less reasonable we become.

And once we have a group of “unaware of what is going on” people who are just following their emotions, we enter the next stage — crowd behaviour. We can be easily manipulated. Or we unintentionally manipulate others, trying to persuade someone to buy our “bag”. Just look at the time after the January 2018 decline. Ever since the top there is an abundance of “hopium”. The crypto space has been filled with positive news, like this or that coin is going to be the best performer in 2018 (how do they know?). Yet prices keep going down for all crypto assets and uneducated people keep losing (be it money or their psychic health). This is typical crowd behaviour. It often leads into buying the tops and selling the bottoms. Over and over again. Completely unaware of the underlying mechanics and unable to make efficient decisions.

Therefore studying the “behaviour” aspect of market dynamics is key to understanding how the crypto markets are functioning.

Crypto Elephant, as it is. At times cute, but mostly wild.

Elephant: In order to get the data for behaviour analysis, we need to tap into different areas of data. Its like trying to figure out the shape of an elephant in the dark. If you touch just one area, you don’t get the whole picture.

So which areas do we need to understand and analyze? At least three:

  1. Pure crowd sentiment data (texts). This is subtle — much deeper and more complicated (and at times irrational) than is lately propagated in the crypto space. A separate article is coming just on this topic alone.
  2. On-chain data. The main topic of this article. Examples below.
  3. Price/volume data TA (technical analysis). We used it, for instance, to predict this current “burst” back in 2017, before it happened.

These areas seem to be of different natures, right? Yet, they represent the same animal, just observed from different perspectives. By understanding the connection between all the different pieces of data, educating yourself on “mass psychology”, and studying human behaviour — you might see the elephant more clearly and closer to his real shape.

2. On-chain (blockchain) data

Usage of this type of data is growing in popularity. Yet, since its a pretty new area of analysis, there is no “proven” way of generating timely insights. The most established metric — NVT (Network Value to Transaction Ratio) — is an interesting attempt at “analyzing the elephant”. Yet, taken alone it has some problems (as correctly pointed out in this article). We believe that an attempt (also made in the linked article) to adjust some settings in the formula to make it a “crystal ball” won’t help.

The reason is simple. First, there is no crystal ball. Second, NVT is a valuable piece of data, but only one piece. Its like touching the leg of the elephant and thinking “I know what this is — stable, heavy, with some coarse hair, a slowly moving leg”. But its not. There’s also a trunk. Ignore it and some pretty painful experiences will enter your life.

So, do we have other on-chain metrics? Oh yes, we do! Since this is a practical discussion, let’s take something directly from life.

Recently I was sitting in my bungalow on a beautiful island in Thailand (Koh Phangan), drilling down through our (Santiment’s) fast growing on-chain data collection. The whole team met here for a couple of weeks, we’ve been working hard on many topics, and blockchain data was one of the most important points of focus. I was excited and at the same time a bit worried. Would I be able to generate some insights using our data and platform?

To test it out, I picked four ERC-20 projects: ENG, KNC, BAT, DNT

Looking carefully into the data we gathered… my mind generated a few insights, which I shared immediately with our community.

You can read the whole story on our Discord server. Here is the short version.

First, I shared the following charts with our community (no worries, I will post the same charts with explanations right below):

KNC (Kyber Network)
ENG (Enigma)

Looks interesting but what the heck do these lines mean, right?

As promised, the same charts, but with some explanations:

KNC, on-chain insight

The top chart (exchange flow) shows how many tokens are flowing to and from the exchanges. Why is this important? Well, you never move big amounts of tokens to an exchange without a good reason. Behaviour, remember? If you do — there’s a good chance you’re doing it for selling.

You don’t store a big amount of tokens on an exchange either. It’s pretty risky. Big players know this. Unless you’re planning to dump it shortly after you bought it, you will send it to a cold/hardware wallet. On the other hand, small players (or sometimes the exchange itself) might decide to keep tokens on the exchange. This gives an even deeper insight into behaviour. You start understanding not only why but probably who is taking the actions.

Check the exchange flow for ENG, for instance:

ENG, on-chain insights, explained

It’s a pretty different picture from KNC. Let’s follow the numbers on the chart.

  1. A huge amount of tokens have been moved to an exchange. This alone in a bear market (where we’ve been for more than a month) might indicate “capitulation” behaviour. This often happens shortly before “the bottom”. The bottom indeed came few days later.
  2. A big amount of ENG was moved to an exchange again after the price had started to grow. More than 50% of these tokens, however, were bought and moved out of the exchange. A healthy sign for continuing the rise.
  3. Even more ENGs are moved to the exchange again. This wasn’t good sign. Typical behaviour after a long bear market is to “sell at the first sign of problems”. In other words, participants are still nervous and ready to dump at any time. Seeing such huge speculative pressure added to the exchange wallets was a bit scary.

So, now you will understand a bit more why we said the following to our community:

KNC: People are buying KNC tokens in order to actually use them. And, in fact, they did use them. That is, honestly, pretty huge for the crypto space. The token is easily “pumpable” (if the KNC team or their token holders would like to do it). And it’s generally a good fundamental sign of network adoption.

ENG: People are accumulating ENG purely for speculation purposes, which in the current market stage (shortly after bottoming) is kind of shaky and dangerous. It’s very easy to scare people and freak out. The dump might happen at any time, especially if you see some “good news” (This last observation isn’t based on on-chain data, but rather on our “crowd sentiment” approach to seeing the market. Our community knows what good news might mean under some conditions — run away as fast as you can. For the astute reader here though, it might be enough to recall the popular phrase, “buy the rumour, sell the news”).

We shared two more examples (BAT and DNT) on the same date. Interestingly enough, one of them (BAT) experienced a strong increase over the next few days after we shared the insight, whereas the other (DNT) crashed. We will provide the same charts here (without additional marks) and the conclusions we gave back on Sunday, March 25.

As an experiment, try to interpret the charts first, and only then read what we said about them.

BAT, on-chain data
DNT, on-chain data

..and here is what we said:

BAT

a) This is the only project we’ve seen so far where, after the tokens were moved to the exchange:

  1. They were completely bought out very quickly
  2. Then they were moved out of the exchange

b) The correlation between the price (USD) and “daily active addresses” is pretty amazing.

DNT

This one is really special. As you know, it has recently pumped like there’s no tomorrow. Good news: there is indeed some small spike in activity (bottom chart). Not so good news: there has been a huge (really huge) inflow of tokens to the exchange. Whoever bought it, is still holding it there.

Conclusion: These tokens are “hot money” and aren’t being used for anything but speculation. They will very likely crash the market once the “crowd mood peak” is reached.

The rest is history. BAT pumped, DNT crashed.

One important addition: We’ve made our conclusions regarding DNT not only based on the blockchain data. As you might recall from the beginning of the article, we consider at least three areas:

  1. Pure crowd sentiment data (texts)
  2. On-chain data
  3. Price/volume data

We always try to use as much data as we get access to from each of the above domains. Sometimes the crowd mood is very strong and clear. Sometimes the on-chain data is very insightful. And the last but not least — sometimes just looking at the price charts is insightful enough.

Whatever you are looking at, there is an elephant behind the different pieces of data. If we try to keep the whole picture in mind and don’t lose ourselves in the details — there is a good chance this wild animal won’t hurt us.

3. Conclusion

Data is power. We showed it in this article but we also know it based on many events in the world around us. This power becomes even stronger when you know how to apply it (as we did with our analysis).

We are opening our growing set of data for similar-minded cryptocurrency researchers. The examples in this article do not show everything we have. Just our on-chain data alone includes TBR (token burn rate — an amazing proxy for seeing behaviour of “whales” and early investors/insiders), Transaction Volume, and more in-depth analyses of activity across crypto exchanges.

Are you interested in learning together how to practically value crypto assets? Would you like to collaborate on expanding the data, cleaning it up and bringing more clarity and insights into the crypto world (be it for the benefit of the community or your own profit)? Are you one who knows that problems are best solved when you apply your own mindful effort?

Finally, do you also feel like this is the time to form an open-sourced movement for more efficient analyses and usage of the vast amount of the data in the crypto space?

If yes — get in touch, we would love hearing from you. Join our Discord channel. Either contact me under “@balance#4827” or any of our team members there.

Santiment is a crypto market intelligence platform, building smart tools and a vibrant community aimed at bringing clarity to crypto trading and investing. To learn more, visit our website at https://santiment.net, sign up for our newsletter at http://eepurl.com/cfgl3n, and join the conversation on our Discord channels.