This case study covers an investment usage scenario of Nyctale's Software Suite. In the following example, we present how our analytics tools can be used as an investment and trading decision-aiding tool.

We are analyzing the activity on the Chainlink network (LINK token) during Q2 and Q3 2020 (from early April to late September).

If you are not familiar with our approach, please consult our Analytic methodology.

In the considered period, the LINK price went from $2.25 to $9.35, with a peak of around $20. The main speculative period has occurred from late July to early October.

Figure 1: Price evolution of the LINK token from April to October, 2020

In the following, we explain how our tools enable our users to gain insights and possibly generate investment performance by better understanding this price evolution pattern. It'll give you insight into how the LINK community behaved during this period.

Macro-view on investor activity

Thanks to our behavioral modeling engine, we could observe the activity of the Chainlink investor community during this "up and down" pattern. These types of patterns are characterized by a growing transaction activity until the token reached a local price maximum, with different types of behaviors appearing before and after the peak.

Figure 2: Number of wallets per behavioral category for LINK token

Let's focus on the main speculative period, from July 29th to October 5th.

Before the local price maximum (from July 29th to August 16th - from $7 to $20):

  • We observed a decrease in the number of Holders.
  • We observed a rise in the number of Incoming Investors and Speculators.
  • We observed a stronger rise in the number of Outgoing Investors, which began to sharply decrease on August 15th, 1 day before the price maximum was reached.
Figure 3: Number of wallets labeled as Holders
Figure 4: Number of wallets labeled as Incoming Investors
Figure 5: Number of wallets labeled as Speculators
Figure 6: Number of wallets labeled as Outgoing Investors

After the local price maximum (from August 16th to October 5th - from $20 to $9.35):

  • The number of Holders started increasing again during the price dump (Figure 3).
  • The drop in price translated in a decreasing number of active investors (Incoming and Outgoing) and Speculators (Figures 4, 5, and 6), with several variations to be screened.

Going deeper in the analysis to gain qualitative insights

Now, let's deep-dive into the evolution of the price decrease to see how our behavioral personas reacted during different sub-phases defined as:

1- August 16th to August 21st

2- August 21st to August 30th

3- August 30th to September 6th

4- September 6th to September 13th

5- September 13th to September 23rd

6- September 23rd to early October

Figure 7: Price evolution of the LINK token from August to October, 2020

Before the local maximum (August 16th), we saw that the Incoming Investor persona was positively correlated with the price: there was a continuous increase of Incoming Investors' wallets while the price was reaching a new maximum.

After the price decrease until early October, the correlation/trend is mostly inversed except for sub-phase 1. For all other sub-phases, Incoming Investors were attracted by the downward pressure on price (sub-phase 3 and 5), while their number was decreasing in price recovery phases (sub-phase 2, 4, and 6).

Figure 8: Number of wallets labeled as Incoming Investors

With regards to Outgoing Investors, it's worth analyzing the correlation with the different sub-groups, which represents the order of magnitude of associated portfolios (range of their decreased balance):

10 LINK < Micro < 1k LINK < Little < 10k LINK < Medium < 100k LINK < Big

The Micro Outgoing Investor category has surprisingly reacted ahead of the downward trend on the price. Around 5k wallets of this sub-group seemed to have well anticipated the price fall, having cashed out just before the price started to decrease in sub-phase 1.

This might have been fueled by informed and smart retail investors, or by wealthy investors who dissimulate their selling pressure in managing hundreds or thousands of wallets. That's why monitoring small investor categories is essential to anticipate price evolution.

Their number progressively decreased until sub-phase 4 with its price bounce. An increasing number of outgoing wallets here translates to a pessimistic expectation of future price evolution.

Figure 9: Number of wallets labeled as Micro Outgoing Investors

The Little and Medium Outgoing Investor categories mainly fueled the first phase of the price decrease. During the price increase in period 4, their number has also risen which, again, could be interpreted as an early warning sign of a further price decrease, which happened in period 5.

Together with the decreasing number of Incoming Investors in period 4, the trend tends to show a pessimistic market sentiment at that time.

Figure 10: Number of wallets labeled as Little and Medium Outgoing Investors

The Big Outgoing Investor category is monitoring wealthy investors having millions of dollars in value in their wallets. Sub-phases 3 (from $17.5 to $9.75) and 5 (from $13 to $7.5) are the two periods where the decrease in price was the most significant. They are also the two periods in which Big Outgoing Investors' numbers have been significantly growing.

Figure 11: Number of wallets labeled as Big Outgoing Investors

Additional indicators to look out for

The wealth concentration indicator (Figure 12) highlights the outcome for wealthy investors who have consolidated their position during the overall period. This indicator could be used to identify the drivers of price fluctuation:

  • With such a centralization trend for network wealth, it means big investors are consolidating their position.
  • A decentralization trend would highlight a wealth transfer from significant investors to retail ones. This may be a healthy sign regarding the true decentralization of a network, but with too much wealth spread across retail investors, it could also mean that big investors are not confident enough to invest.
Figure 12: 90% wealth concentration indicator

Concluding insights

Looking at the evolution of these different personas and their respective sub-groups, we can see that each price action can be better understood by the analysis of the above indicators. However, beware that their correlation with price might change depending on market cycles and sentiments.

The main conclusions at this stage are the following:

Benchmark each category of outgoing investors to anticipate a downward trend on the price. Small investors' behaviors might be very useful as an early-warning sign during a speculative period.

The correlation of different indicators can be used to analyze the rationality of a given period.

For instance in period 4 of our analyzed timeframe, it might have been possible to anticipate future downward trends by looking at the current price increase compared to the decrease of Incoming Investors and the increase of Outgoing Investors. This mix of trends from different personas doesn't seem sustainable in the long run, possibly pointing to a soon-to-come correction.

Expect significant price movements when major stakeholders/whales are making moves. They have the ability to change the overall market dynamic quite quickly and substantially.

Anticipating price movement isn't an easy task. There is no right or wrong answer, but looking at the on-chain behavior of all stakeholders, not only big investors, when prices begin to move significantly helps in understanding the drivers and potential outcomes of these speculative periods. It's important to closely monitor the activity of significant investors while keeping an eye on retail trends.

Some macro-indicators are fueling our global understanding of price patterns, and more detailed analysis is giving us insights on how retail and big investors are behaving. With these elements at hand, looking at other investors' behaviors, it's possible to become a smarter investor.

Check out for further analysis and insights.

DISCLAIMER: This report does not provide any investment advice. All data is provided for information and/or educational purposes. All investment decisions based on the information provided here are your own responsibility. You can consult our Terms & Conditions here.