How does $xOPS work?

A high-level explanation of the actors and activities driving flows of $xOPS

ALPHA NOTE: The $xOPS compute credit will not be used by the public until the Beta launch of SimpFi.Ai. As of writing, SimpFi.Ai is currently running an Alpha program which allows us to prepare and stress-test all blockchain protocol / platform infrastructure. Now, without further ado...

$xOPS is an elastic compute credit.

$xOPS is used to pay for services on SimpFi.Ai.

Users must stake xOPS/ETH to mint a membership NFT and access SimpFi.Ai to run workflows (computations).

Workflows carry a base rate to run (billed in $xOPS), which pays for the maintenance cost of keeping the protocol and platform functioning smoothly, as well as a fair markup (just like any other protocol).

Workflow nodes often include paid operations (computations). In this case, $xOPS is converted at runtime into the appropriate billing stream, token, etc. When on-demand conversion is not possible or desirable, users may convert $xOPS into the required allocations at their discretion and these funds are made available during workflow runs (workflow accounts and budgets).

(Note: In the context of paying for services on SimpFi.Ai and in our explainers we sometimes abbreviate $xOPS using the ¤ symbol.)

The total supply and circulating supply of $xOPS therefore represents in-fact the limit of paying the cost of running computations at any given time. This relationship is mathematically represented as such:

where:

• The sum (∑)​ represents the sum of the costs of all computations running simultaneously

• c is the cost of the i-th computation in terms of ¤

• n is the number of computations

This inequality describes the fact that the total cost of all computations running at any given time does not exceed the circulating supply CS(¤).

Users, in order to pay for services, must buy and/or hold $xOPS. On its own, this creates a demand-side pressure, which would normally drive the price up by natural market forces. This is not necessarily ideal to incentivize usage/spending of the credit to run computations and drive growth and adoption of the network.

For this reason, the supply of $xOPS is elastic, a mechanism which helps to keep the price within a more suitable range for everyday usage. Furthermore, to strike a balance and create a system that benefits both long-term and short-term $xOPS users, the mechanism of elasticity is non-diluting.

Let's explore these concepts specifically.

Elasticity means that the total supply of the token may be modified by an oracle. Supply elasticity can help absorb the effects of price volatility, thereby making the price less volatile, and allowing the token to serve as a more suitable unit of account over specific timeframes. Rather than attempting to achieve zero-volatility of price (like a stablecoin), low-variance elastic-supply tokens are more meta-stable without introducing centralization vectors (leading to censorship) or unreliability vectors (leading to flash crashes and shocks) [2]. Centralized elastic compute credits currently power all legacy web2 cloud service providers (such as Amazon Web Services and Google Cloud Platform).

Non-dilutive elastic supply builds on this concept by rebasing accounts to ensure they maintain the same proportion of that supply during an expansion or contraction. This ensures that the supply adjustment itself does not adversely affect the total value of any holdings of any participant in the long run.

Let's look at a hypothetical scenario:

• At time t1, a holder Bob has 10,000¤ of 50,000,000¤ total supply (2 basis points) at a price of 0.0001 ETH for a total value of 1 ETH in Bob's holdings

• At time t2, there is more demand for $xOPS, and the price goes up to 0.00011 ETH

  • Now Bob will have 10,000¤ at a price of 0.00011 ETH for a total value of 1.1 ETH

• To mitigate further price volatility, the oracle triggers a supply adjustment at time t3 to increase the total supply by 10% (in practice the algorithm is more complex, see here: <TODO>)

  • Now, at time t3, Bob has 11,000¤ of 55,000,000¤ total supply (still 2 basis points) at a price of 0.00011 ETH for a total value of 1.21 ETH

  • Although it appears Bob's portfolio has gained value out of thin air, this creates an instantaneous price inefficiency in the market.

  • Since there is now more supply, sophisticated and/or efficient market participants will discount the price at which they will sell or purchase $xOPS, naturally decreasing the demand, and leading the market price to go back down over time.

• At time t4 the price returns to 0.0001 ETH, but now Bob has 11,000¤ at this price, for a total value of 1.1 ETH, meaning Bob will maintain the benefit of the previous demand-driven price increase. Bob and/or the rest of the market will benefit from the price stability of the token, depending on their goals, preferences, and behaviors. Overall volatility has been mitigated.

Utilizing a non-dilutive elastic supply (and therefore implementing a decentralized elastic compute credit) allows $xOPS to absorb and dampen both the real supply-side volatility of the total availability to run computations, as well as the real demand-side volatility of users who would like to run those computations. This creates a more stable pricing mechanism and eases burden on all users for running computations. If the real cost of computations were to deviate significantly, the resulting volatility would be spread out over time. Indeed, this creates a natural market opportunity for short-term traders to take positions in the direction of the stable trendline, which is an additional effect that benefits the stability of the system overall.

Beneficiaries:

• Long-term holders of $xOPS benefit by owning a non-dilutive elastic compute credit, analogous to having a transferable/saleable Amazon credit that allows usage of a fixed portion of the total capabilities of Amazon Web Services (another analogy could be an energy credit for a burgeoning energy grid)

• Short-term traders may take $xOPS positions in-between supply adjustments, allowing them to benefit from the price returning to the stable trendline, and helping reinforce price stability

• Liquidity providers will benefit by collecting fees on every purchase of $xOPS used to run workflows, as well as every conversion of $xOPS to another unit or currency used to run operations (just like Uniswap)

• Liquidity providers can participate in $xOPS incentive programs to boost rewards up to 500% by locking their liquidity over a certain time frame

• Finally, users of SimpFi.Ai benefit from $xOPS as a more convenient unit of account for their cross-platform operations and to pay for valuable computations (automations) for their personal and business use cases

To summarize, we can consider the following alternatives to a decentralized elastic compute credit:

• Censorable fiat currencies

• Volatile cryptocurrencies (BTC, ETH, etc.)

• Centralized collateralized stablecoins (USDT, USDC)

• Algorithmic stablecoins (UST i.e. TerraUSD)

• Decentralized crypto-collateralized stablecoins (DAI)

• Fractional algorithmic stablecoin (FRAX)

• Centralized elastic compute credits (AWS credits, only AWS and their customers benefit, scalability limited by bureaucracy)

• Non-dilutive elastic cryptocurrency (AMPL)

• Non-dilutive elastic compute credit ($xOPS)

We believe the $xOPS decentralized elastic compute credit offers the best overall benefits for the participants in the SimpFi.Ai ecosystem.

Addendum A: Short-Term Fluctuations (Surges)

• Description: Real supply shocks (e.g., sudden increase or decrease in network computational power) or demand shocks (e.g., spikes in demand for computational resources) could cause the price to spike, similar to surge pricing in ride-sharing services.

• Mitigation Mechanisms:

  • Gradual Rebase Intervals: The protocol can implement more frequent but smaller supply adjustments to smooth out fluctuations.

  • Dynamic Rebase Caps: Setting maximum limits on how much supply can change in a single adjustment period can help prevent extreme volatility.

  • Buffer Pools: Maintaining a reserve or buffer pool can help absorb sudden supply or demand shocks and release or absorb credits as needed to stabilize the market.

  • Dynamic Adjustment Mechanisms: Use adaptive algorithms that change supply adjustment frequency and magnitude based on market conditions.

Addendum B: Market Manipulation and Anti-Whale Mechanisms

• Description: Large actors or groups might perform arbitrage or execute large transactions at a significant scale to manipulate the market, creating artificial price movements and exploiting opportunities repeatedly. Large actors could significantly influence the market if they can buy, sell, or mint large amounts of credits in a short period.

• Mitigation Mechanisms:

  • Arbitrage Limits: Implement caps on the amount of credits that can be minted or redeemed in a single transaction or within a specific timeframe to ensure price corrections happen gradually and stably.

  • Penalties for Excessive Trading: Introduce fees or penalties for excessive trading activity within short periods to discourage manipulative behavior.

  • Real-Time Data Feeds: Utilize decentralized oracles and real-time data feeds to ensure supply adjustments are as accurate and timely as possible.

  • Transaction Caps: Set limits on the amount of credits that can be bought, sold, or minted in a single transaction or over a specific period.

  • Slippage Controls: Implement slippage protection to prevent large transactions from causing significant price swings. (i.e. limit orders, TWAP, market depth, dynamic spread)

  • Accumulation / Distribution: Use time-weighted average price (TWAP) mechanisms for large orders to distribute their impact over time.

  • Emergency Protocols: Develop emergency protocols that can be triggered to temporarily stabilize the system during a supply / demand shock or a manipulation attack, such as pausing supply changes or freezing certain operations.

Addendum C: Risk Management and Hedging

• Description: The system should employ risk management strategies to hedge against large-scale attacks and stabilize the market.

• Mitigation Mechanisms:

  • Insurance Pools: Establish insurance funds to cover losses from attacks and stabilize the market.

  • Hedging Instruments: Use financial instruments to hedge against significant market movements and reduce exposure to sudden price changes.

  • Continuous Monitoring: Implement tools to continuously monitor activity and detect unusual patterns that might indicate manipulation.

Footnotes:

1. TODO

2. TODO