Negative Aura price

24hr trending on @mobyagent Smash the like button if you hold any of these ♥️

so which of these memes will go to $5B first? 🐶 1. $MOG 2. #USELESS 3. $AURA 4. $SPX 5. #KEYCAT 6. $NEIRO 7. $NPC 8. $DOG 9. $SKI 10. $UFD

Update this table from yesterday. House, titcoin, USEFUL, poop, and sendit have been added. Today's MVPs are LuckyCoin, USEFUL, and poop (yellow background mark). This form is intended to be updated for a long time, and any coins I suggest I add can be placed in the comment area 😎

my top memecoins $FARTCOIN $CryBB $ETH $SOL $BONK $WIF $AURA $MOODENG what else should I buy? send everything higher ☝🏻

Playing on-chain Meme, I personally think there are two main methodologies, one is narrative trading, and the other is address mining, the former focuses on the smell and sensitivity of the market, and the latter focuses on careful study and analysis of data. Not only do they not conflict, but they often need to be used in combination. They also correspond to the two driving forces required for the rise of tokens, namely the joint force of the market and retail investors, and the pull of bookmakers and whales. Narrative trading, the focus is on what kind of story the token tells, whether it can resonate with the market, and how far a token can go based on the background of the event, innovation, popularity, etc. For example, $Ani and $Gork are narratives spawned by Musk's new products, which are both influential and interesting, and are easy to spread; $Trump, $Pnut, are contributed by major political-related events; Last year's AI hackathon market paid attention to Dev resume and industry status; $Neiro, $Pochita is a derivative of the Dogecoin concept; $Fartcoin, $Useless emphasizes crypto nihilism. When the market sentiment is good, retail investors are highly motivated, and there is a lot of liquidity, the narrative itself can give birth to Meme coins with a market value of tens of M or even higher, and when the market is bad, it is necessary to rely on the market maker to control the market and attract attention through the increase, typical of which is the recent $Aura, which has been pulled from a state of almost zero to 230M in a few days. To catch this type of banker, the most suitable way is to dig the address, analyze whether there are clusters of pull addresses and their intentions, or find clues through the previously accumulated address library. The disadvantage of this method is that it is very time-consuming, because the pull address is often changed frequently, and the second is that even if traces are seen, once the bottom chips are not firmly controlled, the dealer can choose to abandon the market, and the initiative is completely in the hands of others. Whether it is a big KOL on Twitter or a car on the chain, most of them are mainly narrative transactions, this is not because the address mining is not good, in the final analysis, it is because it is reflexive, once a certain pull address is shared, and more and more people know, it means that the resistance to pull is getting bigger and bigger, resulting in abandonment or changing addresses. In contrast, address mining is a technical activity that is only suitable for small-scale sharing, while narrative transactions need to reach as many people as possible, after all, consensus is the core of the narrative.