The traditional principles of supply and demand have always been the foundation for determining an asset’s fair price. However, in the rapidly evolving world of cryptocurrencies, fundamental factors like the assessment of financial health and industry position are less prominent. Instead, market sentiment and emotional reactions often drive price fluctuations and shape investment decisions.
Without established valuation methods, determining an asset’s worth becomes more challenging. However, in recent years, the transformative advancement of large language models (LLMs) has offered a potential solution for the crypto landscape. LLMs could help with sentiment analysis and provide valuable insights that were once insurmountable for traders.
In the past, traders relied on crypto news headlines, Discord chats, and announcements to gauge market sentiment. Systematic traders had to invest considerable effort into developing average-quality sentiment analysis tools, while technology constraints limited the efficiency of processing vast data outputs generated by global media.
The breakthrough in transformers and LLMs allowed sentiment analysis at scale, delivering immense improvements in comparison to traditional methods that heavily relied on manual scoring and Word2Vec models. Numerous competing software-based technology companies are rapidly advancing the development of LLMs. This continuous enhancement of LLM capabilities and size has sparked a debate about whether they are the potential first signs of artificial general intelligence (AGI) or just “mindless parrots.” Regardless of opinions about LLMs, their increasing use in various industries, particularly finance, will undoubtedly accelerate.
One notable example of LLMs is ChatGPT, which provides valuable insights by simulating user interactions. By offering quick and accurate analysis of market sentiment, LLMs like ChatGPT enable traders to capitalize more effectively on market irrationalities. Consequently, the potential revolution in crypto trading brought forth by these innovative technologies could significantly transform the market landscape.
On the other hand, while LLMs appear promising, it’s important to consider that the absence of traditional valuation methods might still hinder the efficiency of fundamental analysis in the ever-volatile crypto space. Furthermore, predominantly relying on technology for trading poses concerns, as emotions and personal judgment can be invaluable when making investment decisions.
To dive deeper into LLMs and their applications, readers may refer to the recent white paper that explores the types, use cases, and performance of these powerful tools. In the end, technology, particularly in the form of LLMs, might offer innovative solutions to evaluating the true value of cryptocurrencies, but the debate on their efficacy and potential remains open.
Source: Coindesk
