Auto-Rebalance

What is rebalance?

Example

Taking the SOL-USDC pool as an example:

Initial State (3X Neutral)

Figure 1

Price changes result in exposure, and the position deviates from Delta, no longer Neutral. For example, when the price of SOL drops, there will be a part of USDC and a part of SOL in the Equity.

Figure 2

The essence of Auto-Rebalance: Management of Delta, keeping it in a reasonable range.

Let’s continue the example above.

When Delta = +4%, rebalance is triggered. Francium’s bot🤖️ rebalances the assets in Vault: return to the state where exposure = 0, i.e. Delta → 0, while the total value remains unchanged.

The position returns again to the state of Figure 1, i.e., no more exposure on SOL.

When & Why Auto-Rebalance?

Check out Francium's previous article, which described in detail the mechanism of Rebalance and the performance of backtesting:

Why and when rebalancing to Pseudo-Delta Neutral strategy?Medium

Here we define Delta: The parameters used to determine the triggering of Rebalance in Francium's Auto Rebalance Vault.

• Delta

  Delta is the ratio used to measure the long-short ratio in your leveraged position. Delta-zero means your position doesn't have to suffer any impermanent loss. If delta is far from zero, whether positive or negative, your position suffers a high-impermanent loss.

  Delta = (Current no. of non-stable coin in position - Current no. of borrowed non-stable coin)/Current no. of borrowed non-stable coin

Next, let’s take a look at how the delta value of the initial neutral position and the position equity change as the price changes.

Initial Parameters:

• Deposit 500 USDC

• Open a 2X SOL-USDC Neutral Position, (Borrow 10 SOL, given SOL price is $50)

• Without regard to the profit, borrowing interest, etc.

It can be seen that the divergence loss of the position equity will be multiplied and nonlinearly amplified with the offset of the Delta value. Therefore, it is necessary to keep Delta within a reasonable range.

Figure: How Delta Varies with Price Fluctuations

However, it should be realized that although Rebalance can avoid further divergence loss, each Rebalance is essentially a settlement of losses. Meanwhile, Rebalancing will also cause a certain degree of value friction due to trading fees, trading slippage, and other factors. Over-frequent Rebalances will continuously reduce the position equity.

In essence, we need to design an effective rebalance strategy: Balance the pros & cons of Rebalance. Combined with backtesting data, a set of parameters of the best return expectation is obtained. After extensive backtesting, we present the existing Auto-Rebalance Vault product functionality.