Machine learning and market dynamics
With markets moving lower over the past few weeks, two questions are on many investors’ minds: What’s behind the move, and when might markets change course? We tackle both of those thorny questions in our latest batch of insights.
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Understanding all of the factors that drive crypto prices can be a challenge. To help make sense of market moves, we applied two machine-learning algorithms, linear regression and random forest, to determine which factors were most important in the first half of the year. The results show that the key return drivers for BTC, ETH, and SOL were predominantly token-specific metrics, but macro factors also played a role. Going forward, the models suggest that fundamentals like network activity and user adoption are likely to remain dominant forces in the second half of 2024.
In this week’s Market Call, we break down some of the reasons for the recent market downtrend. From ETH ETFs to FTX claims to interest rate cuts, there might be a number of potential positive catalysts on the horizon to shift this narrative.