Trust Model

TradeAlgoAVS ensures that Operators:

• Execute trades correctly according to the strategy logic.

• Do not have custody of user funds.

• Keep strategy logic confidential.

• Distribute fees based on the agreed subscription model.

• Operators are slashed if:

  • They deviate significantly from the expected strategy performance.

  • They execute trades incorrectly or inefficiently.

  • They engage in front-running or exploitative behavior.

TradeAlgoAVS employs an M-of-N aggregation model where multiple Operators (quorum) execute the same strategy, and their performance statistics are compared.

The assumption is that:

1. The same trading strategy, under identical market conditions, should yield statistically similar results within an expected standard deviation.

2. Investors (strategy users) do not care about the individual order-level execution but rather the final performance metrics (profit, ROI, drawdown, Sharpe ratio, etc.).

Validation Workflow

Summary

1. Multiple Operators execute the strategy independently.

2. Their trade performance metrics are compared:

   • ROI

   • Profit percentage

   • Execution slippage

   • Risk scores (e.g Sharpe ratio)

3. Final aggregated results are submitted on chain.

4. If an Operator's results deviate significantly from the expected statistical range, they are:

   • Flagged for fraud.

   • Slashed if proven malicious.

Details

$N$ Operators independently execute the strategy, and their performance metrics are compared. Let $X_i$ be the performance metric of Operator $i$. The mean of all Operator performances is defined as:

$$\mu = \frac{1}{N} \sum_{i=1}^{N} X_i$$

The standard deviation:

$$\sigma = \sqrt{\frac{1}{N} \sum_{i=1}^{N} (X_i - \mu)^2}$$

It follows that the decision rule for rewards and penalties is:

$$S_i = \begin{cases} \text{Reward}, & \text{if } |X_i - \mu| \leq \sigma \\ \text{Slash}, & \text{if } |X_i - \mu| > \sigma \end{cases}$$

After removing outliers, the remaining valid Operator results are aggregated as:

$$X_{\text{final}} = \frac{1}{M} \sum_{i=1}^{M} X_i, \quad X_i \text{ within } \sigma \text{ range}$$

where $M$ is the number of non-outlier Operators that will get rewarded for honest and efficient task completion. $M - N$ is the number of Operators that will get slashed.

Goal

The TradeAlgoAVS trust model is designed to ensure that:

• Investors get what they subscribed for (verifiable performance).

• Strategy providers can’t falsify results or steal funds.

• Operators are incentivized to act honestly under a strong slashing mechanism.

This hybrid on-chain/off-chain design brings together the best of web3 security and traditional finance execution while preserving privacy, transparency, and accountability.