Framework
Ÿ Team - March 2024 - Founding Paper
Last updated
Ÿ Team - March 2024 - Founding Paper
Last updated
Anyone with the slightest background in finance or economics has likely heard of the Efficient Market Hypothesis. This theory posits that financial markets are informationally efficient, suggesting that outperforming the market would be impossible.
Decades of debate have challenged the Efficient Market Hypothesis, with critics pointing out the flaws and limitations of the framework and others adding nuances to it. For which the outcome can be summarized as follows: Markets are only as efficient as the supply and demand providers making the market.
Therefore, less efficient markets exist, and it is possible to predict these markets with a certain degree of confidence by processing the available data quicker and more efficiently than other market participants. Nevertheless, doing that efficiently in practice is still a big challenge.
Acknowledging the evolving nature of financial markets, Ÿ strategically chose to focus on the cryptocurrency market. Its dynamic nature, relative newness, and potential inefficiencies create fertile ground for analysis and prediction, making it ideal for our proprietary tools.
A key advantage crypto market offers is a vast trove of readily available data. However, effectively managing, organizing, analyzing, and interpreting this massive dataset presents a significant challenge. Recent advancements in artificial intelligence have made it possible to tackle this complexity.
Despite this progress, no one has yet fully succeeded in aggregating data from the diverse array of reliable sources within this space. Moreover, extracting actionable insights requires deep experience and the ability to make use of existing data correctly. This complexity hinders the creation of a single, user-friendly model capable of generating insightful and profitable predictions.
Ÿ is building an AI real-time market prediction suite of services. We harness AI to deliver unprecedented insights into market sentiment and trends. Our proprietary Oracle offer an unmatched advantage, empowering you with an unbeatable suite of prediction solutions for data centered decision-making.
Ÿ Oracle
The Oracle is the collective output of the multiple, integrated sub-process structures that collaborate to deliver optimal precision. Ÿ Oracle employs two model types to transform data into predictions:
Data Agents: analyze, refine, and stores diverse data sources.
Oracle Agents: leverage this processed data to forecast future outcomes.
Data Agents
The Oracle employs data agents to relentlessly monitor diverse information sources 24/7: news, market prices, liquidity, on-chain and off-chain activity, and upcoming market events. This rich, self-updating historical database combined with real-time self-browsing capabilities ensures our models remain aligned with rapidly evolving markets.
Oracle Agents
Upon receiving observed events, our models analyze, label, and score incoming data. Oracle Agents seek current and past patterns, identify repetitions, draw historical parallels, and factor in context and sentiment. This analysis is then delivered to the appropriate output channels.
Database
The Oracle's predictive performance and power hinges on its expanding database. This repository encompasses data from the CEX market, on-chain data, ETF data, Sentiment Data, Traditional Finance Data, Orderbooks data and more – essentially, every conceivable source of crypto-relevant information. As well as real-time updates ensuring the database constantly reflects the market's pulse.
Output Channels
The Oracle is designed for seamless integration across multiple output channels. Starting with a real-time updates and reports via the Ÿ Web Dashboard for in-depth analysis, the Oracle bot, the telegram mini app and future plans include developer-centric APIs and WebSockets. This flexibility empowers users to interact with the Oracle in the way that best suits their needs.
Ÿ Agents serve as the initial building blocks for creating the unified Oracle. Each of our 10 Agents acts as a dedicated data hub, focusing on a specific market data observer. All of these 10 agents are then unified in our Ÿ Oracle.
Here is a one-sentence explainer for all current active agents
With a goal of providing full-market coverage, the Ÿ Framework is forever evolving. Now the latest is the V4 Framework Upgrade focus on expansion of market coverage, multi-time frames and personalized strategy generation.
More control for our users
Clear Multi-Time Frame Trading Signals & Market Insights
10 Tracked symbols $BTC, $ETH, $SOL, $BNB, $WIF, $LINK, $ADA, $DOT, $XRP & $DOGE
New Comprehensive Recent History Output
Generate Personalized Trading Strategies
Strategy performance heatmap
Ÿ Stables
Insights into stablecoins state & their effects on crypto assets.
Ÿ CEX
Daily analysis of centralized exchange market activity & its potential impact on crypto assets.
Ÿ Balance
The balances of different crypto assets on exchanges and their correlation with Bitcoin valuation.
Ÿ Orderbook
Orderbook imbalances (Bid & Ask side) for crypto assets on different exchanges (Spot & Futures).
Ÿ Option
Option's volume & open interest for different CEX's.
Ÿ Rates
On-chain Borrow & Deposit rates.
Ÿ Yields
Examines the size and rewards of various crypto assets onchain.
Ÿ X
Analyzes crypto asset tweets for Sentiment, Readability, Polarity, Reach, & Interactions.
Ÿ TradFi
Tracks the dollar index, major US benchmarks (S&P 500, Nasdaq), key tech stocks (Google, Apple), and crypto-related stocks (Bitcoin miners, MicroStrategy, Coinbase).
Ÿ News
Analyzes crypto asset news using features from the title and text. Key features include sentiment, readability, text complexity, and polarity.
