Moralis Magazine #3 – Automated Whale Watching

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Every week, we like to deep-dive into blockchain programming. From performing experiments, to fixing blockchain data access problems (and everything in between) – we’ll show you how Moralis makes solving these issues simple. This week, we’ll dive into automated whale watching.

Moralis is here to support you, and eager to be your “wingman” as we build the future of finance together.

If you missed our first two issues, it’s not too late to check them out! 

Issue 1: IPFS; Issue 2: CORS Errors

Up This Week: Automated Whale Watching

It is no secret that crypto-whales (holders of millions of dollars in crypto assets) are able to move and directly influence markets when opening and closing large positions. 

By watching the moves of these big players, it is possible to make informed market decisions. These decisions can then form the basis for profitable trading strategies. 

How to Whale Watch…

In its most basic form, crypto-whale watching may be as simple as monitoring a single address that holds a large quantity of assets. The problem with this method is, how does the user know whether the particular whale that they are watching is actually a good indicator of market movements?

To shortcut the whale selection and monitoring process, many users choose to monitor a public source of crypto whale movement information. Examples include: Whale Alert on Twitter, or Crypto Quant Alert on Telegram. 

https://twitter.com/whale_alert (Twitter)

https://t.me/s/cryptoquant_alert (Telegram)

The advantage of whale alert providers like these, is that the published information is typically well researched and reliable. 

However, since everyone is receiving the information at the same time, the ability to “act first” on the signals is heavily demissed, and often impossible. For this reason, expert users search for more exclusive alert channels.

Rather than taking these alerts at face value, we can use them as the basis for deeper research in order to extract more actionable information.

CryptoQuant’s expanded resources (tier-based and require a fee) offers a ring-fencing algorithm. The metrics provided can be used to predict a market move e.g. ‘Coinbase Pro Outflow’ has a big spike on recent block timeframe (beginning August 27th):

Another common practice is to use the timestamps of the alerts, as a basis for manually searching the blockchain. Searching this way often involves interacting with multiple block explorers, including: https://blockchair.com (for time filtering); https://bitinfocharts.com/ and https://oxt.me/ (for their labelling data to compare with others). 

Once an address is identified, the next step is to attempt to determine the type of address; by studying the transactions of the address we can tell whether it is used to hold assets long term ( likely cold storage) or short term (a hot wallet).

Lastly, with this prerequisite knowledge we can build our own alerts around addresses, and even establish triggers when a certain type of address receives or sends funds.

Automating this process is a daunting task. Thankfully, Moralis is the perfect catch-all solution.

Moralis provides the ability to build your own alerts, while avoiding vanity/erroneous labels. This allows Moralis users to better adhere to a core blockchain principle: don’t trust, verify.

Join us now as we explore using Moralis to construct a whale watching powerhouse, and how we can expand upon what’s already possible. 

With that, we’re proud to introduce the first part of ‘Whale Watching with Moralis’, a multi-part video series. 

This video is the first step in the process of drafting a bespoke wallet monitoring system, superior in function to either of the whale watching examples presented above…

September 3, 2021
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