Groundhog Day is a folkloric method used by farmers, especially in the United States and Canada, to predict the arrival of winter, based on the behaviour of the animal when it survives the winter on 2 February.

According to the belief, if you do not see the groundhog's shadow when it comes out of the ground, because the day is dark, this means that winter will be over soon. If, on the other hand, it is a sunny day and you see the groundhog's shadow, it means that winter will last longer [1].

In any case, this does not serve to speculate on certain things, such as, for example, that the market will end or at what point this crypto-market may end. It has been a tough winter months in the cryptocurrency market, with token prices dropping sharply and once stable companies and organisations downsizing or even disappearing overnight.

With that in mind, the aim of this dashboard is to try to predict whether the crypto-winter will last much longer or, on the contrary, it looks like it is coming to an end. To do so, we will use on-chain data from Flipside Crypto to support the arguments.

Then, we will try to identify some of the major reasons why market will continute going down or in contrary, will revert the situation. To do that, I have compared several metrics between BTC (the mother of crypto) and the major altcoins (chosen as average crypto market) like ETH, BNB, MATIC and OP. The metrics studied have been:

• Prices trends over the past year
• Daily changes over the past year
• Relationship between BTC changes and cryptomarket changes
• Some causes for cryptomarket struggle.
• Study of any potential causes or any indicators that could help us predict whether/when it could recover?

BTC price vs ETH price (major altcoin)

As seen, from the past year, a total of 35 times the BTC price down more than 1%. Take into account that we have considered cryptomarket as average metrics of ETH, MATIC, BNB, and OP tokens because in my opinion they are representative tokens of global altcoins. During these bad days when BTC down, the average changed in prices were --3.5%. However, in the case of BTC price, the average percentage change during those days were around -2.5. In fact, if we take into account how many times average market price decreased when BTC falls more than 1% were 33. Then, in only 2 times when the BTC goes down more than 1%, cryptomarket stayed safe.

Finally, I have computed how many times average cryptomarket prices outperformed the BTC price when it went down. From the 33 times, 11 days cryptomarket price outperformed BTC, being 31% of times when cryptomarket price had a better performance than BTC.

To conclude this first approach, I have compared the evolution of BTC price against the whole cryptomarket in order to see if it follows similar trends or at some points the cryptomarket price developed different sideways. In the first two images, we can see the BTC price changes over the past month and year (left and right) in comparison to the other top crypto tokens such as ETH, BNB, OP and MATIC. As it can be seen, when the BTC price goes up or down, the whole cryptomarket price do the same but in a more pronounced manner. It is a clear positive correlation between the price change of the whole cryptomarket and the BTC price.

If we take a look at the second two images, we can see how there is a strong positive correlation between the BTC price and the average cryptomarket price in terms of daily changes. It can be clearly seen that when the percentage is negative, the average market change is negative as well. On the other hand, when the BTC price change is positive the average whole cryptomarket goes up as well. In both cases, when the percentage is higher, the same occurs for the whole cryptomarket.

Indicator 1: swapping activity

The first possible indicator selected is the swaps. When the price of an asset change, it is the major of the times related to its netflow on swaps. For this reason, I have selected this first indicator.

If we take a look at the first chart, it can be seen how the netflow of swaps accross the major chains has been negative on the major of the days over the past months. If we take this trend and compare it against the average cryptomarket price, we can see how they are not correlated due to follows different trends. However, it can be seen how when the volume increase negatively (more outs than ins) the price tends to drop faster. In contrary, when the volume is strongly positive, the price tends to go up faster.

Indicator 2: transfer’s activity

The second possible indicator selected is the transfers. When the price of an asset change, it is commonly realted to transfers activity. For this reason, I have selected this indicator.

If we take a look at the first chart, it can be seen how the volume of tokens in transfers accross all chains has fluctuated a lot over the past weeks and months, reaching the highest numbers on September 15th when the Ethereum marge took place. However, it was not relevant for the crypto prices. If we take this trend and compare it against the whole cryptomarket price movements, we can see how they are moderatly positive correlated due to follows similar trends.

Looking at the relationship between volume transferred and price movements, we can see a moderate positive correlation, saying as that when the volume transferred is positively higher, the pricce movements seems to go up, and on the other way around.

Key insights

• It can be seen how the average cryptomarket and BTC price followed similar trends but in different price change ranges.
• During these bad days when market down, the average changed in prices were -3.5%. However, in the case of BTC price, the average percentage change during those days were -2.5. The percentage are similar when BTC goes up, being 3.5% for the whole market and 2.72 in the case of BTC.
• If we take into account how many times BTC price decreased when cryptomarket falls more than 1% were 35. In only 2 times when the BTC goes down more than 1%, cryptomarket price stayed safe. From the 29 times when BTC was positive, cryptomarket price goes up 28 times while only 1 time cryptomarket prices stayed unsafe.
• From the 35 bad times, 11 days cryptomarket price outperformed BTC, being 35% of times when cryptomarket price had a better performance than BTC. From the 29 good times, the whole cryptomarket outperforms BTC 19 times, representing 65.5% of the times.
• There is a strong positive correlation between the whole cryptomarket price and the BTC cryptomarket price in terms of daily changes. It can be clearly seen that when the percentage is negative, the average market change is negative as well and on the other way around, suggesting that the cryptomarket could revert the situation when BTC start to go up.
• The netflow of swaps for crosschain ecosystem has been so steady over the past weeks and months, but in some specific days the amount was so positive. If we take this trend and compare it against the average cryptomarket price, it can be seen how when the volume increase negatively (more outs than ins) the price tends to drop faster. In contrary, when the volume is strongly positive, the price tends to go up faster, suggesting that a positive increase of volume of swaps on the entire crosschain ecosystem could lead to a market recovery.
• The volume of tokens in transfers accross all chains has fluctuated a lot over the past weeks and months, reaching the highest numbers on September 15th when the Ethereum marge took place. If we take this trend and compare it against the whole cryptomarket price movements, we can see how they are moderatly positive correlated due to follows similar trends, suggesting that if the volume of transfers accross chains continues to go up, the cryptomarket price could start to recover.
• Looking at the relationship between active users and price movements, we can see a moderate positive correlation, saying as that when the active users increase, the price movements seems to be positive, and on the other way around. When the daily amount of active users is lower, the price change tends to be negative.

As a result, here we can see the difference between BTC price performance and ETH price performance over the past year. It can be seen how the ETH and BTC prices followed similar trends. However, it seems that when BTC goes up, ETH do it in a higher range. As well, when BTC goes down, ETH do it in higher ranges too.

The second chart represents the daily change in price of ETH price against BTC price. When BTC decreases the ETH prices decreased in a higher % and on the other way around.

Regarding positive days, a total of 29 times the BTC price up more than 1%. Again, taking into account that we have considered cryptomarket as average metrics of ETH, MATIC, BNB, and OP tokens because in my opinion they are representative tokens of altcoins. During these good days when BTC up, the average changed in prices were 3.34%. Again, the BTC price seems less volatile, which was 2.72. In fact, if we take into account how many times cryptomarket price increased when BTC goes up more than 1% were 28. Then, in only 1 time, the cryptomarket goes down even BTC price goes up and the cryptomarket stayed unsafe.

Finally, I have computed how many times cryptomarket prices outperformed the BTC when it went up. From the 29 times, 19 days the global cryptomarket price outperformed BTC, being 65.5% of times when cryptomarket had a better performance than BTC.

Indicator 3: active users’ activity

Overview

Methodology

BTC performance vs Global Market performance

The third possible indicator selected is the active users. When the price of an asset change, it is commonly realted to mass adoption and it is to say, the amount of users interested on it. For this reason, I have selected this indicator.

If we take a look at the first chart, it can be seen how the number of active users accross all chains has increased from September to December 2022. However, since the start of the year, it seems that the active users have been decreasing slowly. However, it was not relevant for the crypto prices.

Looking at the relationship between active users and price movements, we can see a moderate positive correlation, saying as that when the active users increase, the price movements seems to be positive, and on the other way around. When the daily amount of active users is lower, the price change tends to be negative.