AI Lacks Evidence of Sustained Excess Returns in Virtual Asset Investment

Artificial intelligence (AI) has made advancements in predicting the prices of virtual assets and establishing investment strategies; however, an analysis reveals that there is insufficient evidence to support the claim that it can generate stable excess returns over the long term when considering actual trading costs and risks. According to a paper released on the 4th, the research team reviewed prior studies related to AI investment up to August 31, 2026. While machine learning, time-series-based models, and finance-specific language models have achieved technical advancements, they pointed out that these do not necessarily translate into actual investment returns. It is essential to distinguish between AI's predictive capabilities and actual profitability, as trading fees, spreads, and market shocks can impact profitability. The digital asset market is becoming increasingly complex due to 24-hour trading, the dispersion of exchanges, and changes in supported trading items. The researchers mentioned that AI might quickly capture market conditions; however, they warned that profit opportunities could be compensations for risks such as market crashes, capital constraints, and liquidation risks. The results of backtesting are mixed, with both positive and negative outcomes, leading to the conclusion that it is challenging to prove the existence of AI models that consistently generate net excess returns. The research team suggested that to validate future AI investment performance, it is necessary to use data and models from actual investment points and evaluate trading costs.

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