I think many people misunderstand USDf / sUSDf, which is related to our past habits of looking at yield stablecoins: everyone wants a definite annualized number, preferably one that can be guaranteed for the next three months. But when the market cools down, you will find that a more important question is actually another one—what are the 'legs' supporting this yield, which leg is most afraid of cooling down, and which leg is more like the chassis.
Mechanically, the yield of sUSDf comes from a set of strategy combinations. The official documentation clearly mentions the positive and negative interest rate differentials and the sources of strategies including some token staking. In other words, what you get is not a 'single interest', but a basket of yield factors that perform differently under different market conditions. This structure itself implies a reality: when sentiment shifts from exuberance to caution, yield changes will not be 'overall dropping together', but more likely 'returning to normal in sequence'.
If we break down the returns from this basket into a language closer to risk managers, it can generally be understood as three sources with different climate sensitivities: derivative-related basis / funding returns, arbitrage-related returns from price differences and execution, and staking returns that are closer to 'on-chain base returns'. Falcon provided a slice of the return composition at that time in a progress disclosure in July 2025: basis, arbitrage, and staking each accounted for different weights (this is a snapshot from a specific period, not a permanent ratio). I see it as a model for understanding rather than a fixed answer for the future.
Based on this model, you can more easily understand 'who changes first when the market cools down'. When volatility contracts, the enthusiasm for contract trading decreases, and cross-platform price differences tend to converge, the first to be compressed are often the two return legs that are more sensitive to market sentiment and liquidity - the basis / funding-related opportunities, and the arbitrage legs that rely on active price differences. I am not saying they will disappear, but that they will return more quickly from 'high positions during favorable conditions' back to 'more normal ranges'. This is an inference based on return structure: the same strategy will naturally produce different results in high-volatility and low-volatility environments.
Relatively speaking, staking or more fundamental sources of returns may feel more like the chassis in terms of 'short-term sensation', but it is not a perpetual motion machine and will still be influenced by token economics, on-chain activities, and risk control rhythms. It is precisely because of this that I have always felt the correct way to approach USDf / sUSDf is not to 'bet on an unchanging number', but to place it within your own return layering system, allowing it to bear that part of the stable color that you can explain, review, and hold long-term.
This is actually a very obvious change in mental rules. Previously, when we judged returns in dollars, we liked to ask 'what is the current APY'; now a more mature question should be 'what makes up this APY, and how will it change in different market climates'. When you start thinking with 'the stress ranking of return sources', your expectations for USDf will be closer to the asset management logic of the real world, rather than being led by short-term numbers.
Azu gives you the simplest and most lifesaving action advice: write your return expectations as a range, rather than a single point. For example, you can set a more honest version for yourself - I am willing to accept reasonable fluctuations in this base return across different market stages, and my position size should be based on the premise of 'even if it returns to the lower end of the range, I won’t panic'. As long as you do this, when the market cools, you will be steadier than most people because you have already written 'it will change' into your strategy statement.
