Spot Forecasting in DeFi

Spot forecasting involves attempting to anticipate future prices or returns on a spot asset, including leveraging machine learning and AI models. The forecast may be in the realm of milliseconds, or up to months and possibly even years.

The most apparent is implementing a manual or algorithmic trading strategy based on anticipated price movement, which in practice has mixed results depending on the performance of the forecasting model and the strategy. Further a portfolio might make use of spot forecasting in hedging or risk management using forecasts and statistics around forecasts.

The team has created multiple spot forecasting models that we've uploaded onto our AI Model Hub (https://t.co/ovVaIz8fTn) and we're working with many DeFi teams to productionalize features and applications leveraging these powerful models.

Use-cases in DeFi include:
✅ Vaults implementing spot forecasting can utilize more sophisticated and dynamic porfolio strategies. A vault agent or algorithm that anticipates potential future price movements can reduce risk by reducing exposure to volatile assets ahead of anticipated downturn, or increase exposure when a comparative increase in value is expected in certain assets.
✅ Yield Aggregators aim to produce regular income or value increase using staking or other lock-up methods. Spot forecasts enable the aggregator to compare the relative expected value of staking in one protocol or asset versus another.
✅ Modern Portfolio Theory techniques for portfolio optimization can utilize spot returns forecasts as inputs for mean-variance optimization. These forecasts, which typically represent expectations for asset returns over a specific investment horizon, are combined with historical or implied covariance matrices to generate efficient portfolios that maximize expected return for a given level of risk.

OpenGradient's advanced infrastructure, models, and research will redefine DeFi, enabling more intelligent features and optimized protocols that can improve user experience and profitability.

We're excited to be working with many protocol partners and clients on integrating AI and ML workflows like these into their applications to provide secure and seamless intelligence.

SUI/USDT spot forecasting model on OpenGradient's AI model hub 🔗: https://t.co/I2sU13EWXP