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  • What is ethere.al
  • What is ISA
  • Mintable Assets
    • Direction - Bullish
      • DeFi Growth Market | DGM
      • eITY | Inverse 3x, 5x, 10x Leveraged US Ten Year Yield Hedge
      • Financial Innovation Market | FIM
      • Indirect Crypto Exposure | ICE
      • Synthetic Economies
      • Traditional Finance to Decentralized Finance Interpolation | TDI
      • Transversal Unemployment Market | TUM
    • Direction - Bearish
      • Consumer Price Index DeFi Hedged | CPIDH
      • Consumer Price Index TradFi Hedged | CPITH
      • DeFi Capital Inflow | DCI
      • DeFi Capital Outflow | DCO
      • Distributive Debt Cycle | DDC
      • eTY | 3x, 5x, 10x Leveraged US Ten Year Yield Hedge
      • eBTC - eETH | Inverse Large Cap Assets
      • Synthetic Recession Probability - usRP
      • Traditional Capital Inflow | TCI
      • Traditional Capital Outflow | TCO
    • Direction - Neutral
      • Delta DeFi Sentiments | DDS
      • DeFi Gamma Expansion | DGE
      • Delta Global Energy Sentiments | DGES
      • Delta Global Technology Sentiments | DGTS
      • Delta Neutral Indirect to Direct Crypto Exposure | DNIDCE
      • DeFi Volatility Index | DVIX
      • Global Energy Sentiment | GES
      • Global Technology Sentiment | GTS
      • Machine Generated Market Sentiment | MGMS
      • Rapid Extrinsic Value Decay AVAX | REVDA
      • Rapid Extrinsic Value Decay BTC | REVDB
      • Rapid Extrinsic Value Decay ETH | REVDE
      • Volumetric DeFi Exposure | VDE
    • Example Portfolios
    • Non-Traditional Hedges
    • Pricing Model
  • Mintable Dynamic Products | Options
    • Rho - Dynamic Fixed Yield Product
    • DTV Sync Options
  • Economics
    • Swap and Mint Fees
  • Roadmap
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    • Product Vision
    • Additional Asset Mints
    • Tokenized Algorithms
    • Deep Option Liquidity
    • Lending Partnership
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  1. Mintable Assets

Pricing Model

PreviousNon-Traditional HedgesNextRho - Dynamic Fixed Yield Product

Last updated 2 years ago

Synthetic portfolio theory assets (SPTA) are priced using a primary data feed that pulls relevant information. For example, a volume-specific product utilizes volume data as a core starting point. The data is then manipulated to smooth curves, normalize volatility spikes within a trailing period range, and then fed to an oracle for pricing the asset. These calculations occur on a compute server, similar to how our option chain execution begins. We are working to decentralize and verify compute accuracy for further transparency in our asset pricing.

Depending on what the underlying asset is designed to hedge, multiple data streams could be used to pull specific pre-compute variables to model more nuanced products. However, in either case, the goal is to minimize volatility over longer durations for our hedge-oriented products. This also makes them less susceptible to manipulation because all of our assets are aggregated calculations; therefore, for manipulation to occur in the SPTA, sustained manipulation in each of the underlying base feeds would need to occur for a longer duration than our built-in smoothing windows. In some cases, this results in sustained manipulation attacks for more than 1 quarter.

Our trade-oriented asset list reduces this timeline of smoothing to allow for more significant intra-day moves. While more volatile, these specific assets are protected similarly by introducing random sampling into their windows that are pair matched to prior periods. In addition, just like our lower volatility products, SPTAs do not track singular entities but aggregated market pockets. Therefore, the capital required to manipulate even shorter windowed products would be larger than the profit that could be gained due to our mint limits.

Mint rates across our entire platform are scaled based on several key features, including supply/demand for the asset, the realized volatility of the asset class, and the available liquid POL on the platform under which redemptions would be fulfilled.