---
description: Comprehensive Analysis of Risk Level 1 - Minimal Risk
---

# Simulation Example

Our simulation, conducted over the period from February 13 to November 26, showcases the efficacy of proper asset placement , into the pool with the highest yield rate . This analysis, conducted within the Ethereum network using stablecoins and Ethereum as staking assets, avoids complexities such as asset swapping or bridging, and investments in multi-asset reward pools. The focus is purely on yield optimization through intelligent asset allocation based on APY fluctuations.

For this simulation , we targeted 6 pools , all with a longevity of over 10 months and a minimum TVL of $50M .



<figure><img src="https://3956004477-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGhcGDDb2h8fFpPreXeSt%2Fuploads%2F3zmFhsoL7RtIFC3ERMRs%2FYour%20paragraph%20text.png?alt=media&#x26;token=f0d6e6ee-70ce-48fd-9184-e3e394ee2a92" alt="" width="375"><figcaption></figcaption></figure>

#### First, the Methodology of the Simulation:

* **24-Hour APY Analysis**: The foundation of our simulation was a granular analysis of each pool's 24-hour APY. Although APY is an annualized metric, it's calculated based on a compounding daily rate. By evaluating these daily fluctuations, we could gauge the most opportune moments for asset reallocation.&#x20;
* **Dynamic Asset Allocation Strategy**: The AI Aggregator was programmed to monitor and analyze the daily APY of each pool. It then shifts assets to the pool offering the highest yield at any given time. This strategy is pivotal in our approach, allowing for adaptation to the fluctuating APYs and optimizing the yield potential.

<figure><img src="https://3956004477-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGhcGDDb2h8fFpPreXeSt%2Fuploads%2F0L6XujYzzS1Tz7iU6tHW%2FUntitled.jpg?alt=media&#x26;token=95a37ad1-95cf-4cd8-a403-60beadae31f9" alt=""><figcaption></figcaption></figure>

**Simulation Outcome:** By consistently reallocating assets to the highest-yielding pool based on the 24-hour APY data, fetched from the 6 pools used for this example .Given the average DPR of 0.01879% , our AI Aggregator would have attained an aggregate APY of 7.1%. This represents a notable 42% increase in yield compared to the average yields of the individual pools.

<figure><img src="https://3956004477-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGhcGDDb2h8fFpPreXeSt%2Fuploads%2FU8WeieFEhLuqW9gr84t9%2Farrr.jpg?alt=media&#x26;token=b808ffe5-b44f-4854-8916-d7221efc67e5" alt="" width="329"><figcaption></figcaption></figure>





**It's important to note that this simulation's scope was limited to a conservative investment approach within the Ethereum network, focusing on stablecoins and Ethereum without engaging in asset swapping or bridging and that network fees were not taken into account.**
