Vitalik: Building Index Tracking Assets Based on Options Rather Than Debt

Original article by Ethereum founderVitalik Buterin

Translation by Qin Xiaofeng, Odaily Planet Daily (@QinXiaofeng 888 )

Special thanks to Vladimir Novakovski, Curve developers, and others who provided feedback and review for this article.

Suppose you have a price index T, denominated in ETH. For example, T could be the USD/ETH price (i.e., the reciprocal of ETH/USD), CPI/ETH (i.e., CPI/USD * USD/ETH), or any other commodity price index, or even more exotic indices (like the average rent in a certain city). You want to allow users to gain exposure to T.

In simple terms, your goal is to create a synthetic asset tracking T within an ecosystem where ETH is the only "trustless" asset (or could be extended to other trustless assets), without relying on a centralized issuer. The only trust dependency is the oracle, which can be trust-minimized, unlike an issuer.

If T is considered the USD/ETH price, this problem is essentially the same as an "algorithmic stablecoin." In reality, it is a perpetual future.

All methods attempting to provide this functionality must face a fundamental problem: the entire system can only hold ETH, and its assets and liabilities denominated in T must net to zero. Therefore, for every user holding a positive position in T, there must be another user holding an equal negative position in T. What happens if T rises too high, causing the negative-T holder to go "bankrupt"?

In traditional algorithmic stablecoins, this problem is solved through forced liquidation.

For example, suppose the ETH price is $2500, and a user holds a position (1 ETH, -$2000). If the ETH price drops to $2000 (in practice, triggered at a slightly higher price for a safety margin), the system must be able to "force liquidate" the user: allow any other person to put in $2000 and collect the underlying 1 ETH, so the entire system is not burdened by an under-collateralized $2000 debt.

The problem with relying on liquidation is that liquidation depends on a real-time oracle. You need an oracle that can provide a binding ETH/USD price value and do so instantly.

Real-time oracles are difficult to secure. You have to rely on a limited number of participants who observe real-time signals in an automated manner. You cannot use any mechanism with recourse. You also cannot use the most effective technology currently available for building secure and cheap oracles: placing a prediction market in front of a secure but expensive oracle, and only using the expensive oracle in case of significant disagreement.

This article proposes a paradigm shift that can allow synthetic assets to rely only on "slow" oracles: we completely remove the concept of liquidation, transforming the system's "basic building block" from debt to options. On this basis, you can choose to build an index-tracking asset as a higher-layer structure, or not build one at all and let users rebalance themselves. Decoupling these two mechanisms brings greater stability and flexibility.

Synthetic Options

We define two assets: P and N.

Parameters include: (i) Index T, (ii) Strike price S, (iii) Maturity date M.

At any time, a pair (P, N) can be generated by splitting 1 ETH. Similarly, you can merge P and N at any time to redeem 1 ETH.

At time M, the oracle is called to determine the value of T. Let this value be x. After the oracle is determined:

• P receives min(1, S / x) ETH
• N receives max(0, 1 - S / x) ETH

Note: P + N = 1. Therefore, there is no possibility of liquidation.

Additionally, for easier understanding, here is the same chart denominated in USD:

An interesting feature of this design is that it is "essentially" a prediction market, and such prediction markets have already existed and been traded for years. See: Scalar Markets (Scalar Markets | Seer).

This means the design can share the same oracle with the prediction market system, thereby improving security.

How to Use Synthetic Options

Suppose the current price is 2500, and as a user you want to build a portfolio with some USD exposure. You buy some (P 1500), an asset with a strike price of 1500, well below the current price of 2500. Is this sufficient?

Not entirely. Although the current price is far above 1500, it could still fall below 1500 by the maturity date. The greater this risk, the more the USD-denominated value of (P 1500) deviates from its maximum. In fact, it begins to deviate quadratically from $1. The chart below illustrates this:

Note that this is just a smoothed version of the curve above. The degree of smoothing depends both on the gap between the current price and 1500, and on the market's expectations for future price volatility.

To understand the principle, suppose M is two weeks away, and the current price is 1499. How much is (P 1500) worth? It represents the probability that "the ETH/USD price will be above 1500 two weeks from now." Since ETH can be highly volatile, this value could be high or low, perhaps $50. If the current price drops to 1399? The price of P would fall, but not to zero, because the price could still recover above 1500 by time M.

When ETH/USD is far below 1500, the value of N approaches zero. When ETH/USD is far above 1500, the value of N approaches price - 1500. In the intermediate region, it is a smooth curve transitioning from one mode to another.

The Black-Scholes model is one formulaic method for estimating the fair price of (P 1500) (at least for indices T representing a price, rather than more exotic underlyings like weather). However, since 2008, the Black-Scholes model has become synonymous with the catastrophic fragility that can result from over-reliance on mathematical models—and not without reason. Therefore, we should not place excessive faith in the precise details of the curve, not least because we do not want to introduce another oracle needed to measure expected volatility, skewness, or kurtosis.

Instead, we should keep the following chart in mind, which is the derivative of the previous one. It tells you: at the current price level, how much ETH exposure does one unit of (P 1500) correspond to?

Remember, as a holder of (P 1500), your goal is to "hold" USD with no ETH exposure. The strategy this chart suggests is: the safe approach is to hold deep "in-the-money" options, and then roll them into options with a lower strike price once the price approaches the strike.

For example, you could follow an algorithm: if the current price is X, buy an option P with strike price S < X/2 and a maturity 1-2 months in the future. If the price drops below S * 1.5, roll into an option P' with a new strike price S' < X/4. Do not hold until expiry, because you would be exposed to ETH risk at the time the oracle determines the price.

Let speculators and market makers hold N and provide you with liquidity.

We can compare the properties of liquidation-based synthetic assets and option-based synthetic assets as follows:

In both systems, action must be taken in response to significant price movements: in one system, the protocol performs liquidation; in the other, the user conducts rebalancing. The key difference with option-based synthetic assets is that the user can choose how to execute this action.

Rebalancing could be done by a fully automated on-chain DAO (Note: fully automated. All rules are set by the DAO, no voting or AI required). Such a DAO would be a "wrapper" for the options system and would provide a "stablecoin." Alternatively, users can choose to rebalance locally, using a daemon on their own device.

By transferring the decision point of "when to {liquidate/rebalance}" from on-chain tools to users, we gain two advantages:

1. Reduced MEV risk for users, as transactions are not pre-visible.
2. Elimination of reliance on a global canonical oracle. Users still need an oracle that responds faster than (e.g.) two weeks, but users can hide which oracle they use (e.g., a locally running agent queries dozens of financial news websites, no one knows which ones, and takes the median). This helps protect the system from oracle attacks.

The user's main choices are timing and thresholds. If users rebalance frequently, they are more susceptible to short-term price fluctuations from counterparties. If users rebalance conservatively, they bear more quadratic drift.

I believe that accepting moderate quadratic drift (e.g., an annualized standard deviation of about 1-4%) is an underappreciated strategy. This cost is indeed significant, and it is counterintuitive, making this design unsuitable as an "accounting stablecoin" (i.e., it cannot allow recipients and senders or capital gains tax authorities to "pretend it's USD").

However, it becomes much more reasonable if you approach it not from the perspective of "I want to simulate USD," but from the perspective of "I want price stability" (i.e., being able to pay a known future expense). The annualized volatility between fiat currencies far exceeds 1-4%. The annualized volatility of any individual's or business's expected future expenses denominated in their local fiat currency also far exceeds 1-4%. Additionally, the equilibrium annualized return of algorithmic stablecoins like RAI often fluctuates by a roughly comparable magnitude.

An important decision to make is: What market mechanism governs rebalancing, even when done conservatively? It is very easy to lose 2% or more per year across multiple rounds of slippage, and this is the biggest risk that the entire scheme might lose its competitiveness.

Fortunately, users' time preference is almost always very low. Users don't care whether they rebalance today, tomorrow, or in three days. We should leverage this to design an ideal market structure with far lower slippage than traditional automated market makers. Rebalancing would be more like single-sided market making than an immediate sale.