Whale Trader Was Down $4.44M On 'Shiba Inu Killer' Dogwifhat—Here's How They Turned It Into A Profit

Zinger Key Points
  • A whale trader converted a Dogwifhat $4.44M trading loss into a $518,000 unrealized profit through trading strategies.
  • A crypto trader predicts a 13% rally from Dogwifhat’s current levels as support levels are retested.

Analytics provider Lookonchain highlighted a whale trader who lost money on Dogwifhat WIF/USD but successfully captured profits trading Popcat POPCAT/USD.

What Happened: The trader initially lost $4.44 million trading WIF twice between April 8 and June 24. The trader withdrew 12,716 Solana SOL/USD, worth $1.94 million, from Binance to buy 1.38 million POPCAT at $1.41. They now hold 2.05 million POPCAT, valued at $2.82 million, with an average buying price of $1.13.

The trader managed to reduce the WIF loss to $2.5 million after purchasing 2.06 million WIF again on June 24 and 25 and holding onto it and currently holds 2.05 million POPCAT, worth $2.8 million, with average buying price of $1.13 and an unrealized profit of $518,000.

Also Read: POPCAT Meme Coin Pops Wallets: These Traders Made Over $8M Profit With Dogecoin, Shiba Inu Kitty Rival

Why It Matters: The whale’s trading strategy demonstrates the high-risk, high-reward nature of cryptocurrency trading. Despite suffering a significant loss, the trader managed to recover by diversifying their portfolio and investing in different cryptocurrencies.

Dogwifhat's 10% gains over the last week added to its 80% rally over the past month. The trader’s decision to hold onto WIF despite the initial loss and invest in POPCAT shows a strategic approach to managing risk and maximizing potential returns.

Rekt Capital marked Dogwifhat successfully retesting the $2.52 level as support for building on its current rally. He added that with this retest, “WIF is now positioned for a move across its red-red range to as high as the $3.22 Range High resistance."

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Image created using artificial intelligence with Midjourney.

This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.

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