Bitget CEO Faces 15.8% Loss in Altcoin Portfolio

Bitget CEO Faces 15.8% Loss in Altcoin Portfolio


The post Bitget CEO Faces 15.8% Loss in Altcoin Portfolio appeared on BitcoinEthereumNews.com.

Gracy Chen, the Chief Executive Officer at the well-known crypto exchange Bitget, has recently discussed the increasing investment losses. Based on her experience throughout the past year, where she incurred a 15.8% loss on altcoins, Gracy Chen pointed out 3 chief reasons responsible for the heightened crypto losses. On her official X account, Chen provided knowledgeable insights for the crypto investors. Today, I analyzed my secondary token investments and learned a lot. Almost a year ago, I bought some secondary market small tokens, including meme, AI, depin and gamefi. A year later, the return of this portfolio is -15.8%. Although the loss is not huge, given this period of time… — Gracy Chen @Bitget (@GracyBitget) January 10, 2025 Gracy Chen of Bitget Faces 15.8% Dip in Return on Small Tokens Gracy Chen pointed out that irrespective of being a veteran crypto professional, she saw a -15.8% return on small tokens. Her small-token portfolio included assets dealing with AI, GameFi, meme, and decentralized physical infrastructure networks. This loss fades in comparison with Bitcoin’s massive rally at the same time as it surged from $40,000+ to above $95,000. While discussing her choices, she indicated that the losses resulted in 3 critical lessons for her. Investing in Small Tokens Results in Losses for Long-Term Investors As per Gracy Chen, one of the prominent reasons behind the losses reportedly accounted for speculation on tokens with small capitalization. She asserted that the long-term investment is not suitable for small-cap, highly speculative tokens. These tokens demand a constant eye on the market. On the other hand, the other tokens such as Bitcoin present a relatively stable position with a low-risk profile. Thus, Chen recommends these assets for long-term investors. Small-Cap Tokens Need Rapid Decision-Making for Effective Gains In addition to this, Chen labeled lack of precise…



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