We live in a financial world where, if it takes you more than a few moments to discover a 300-page document in Mandarin from a People’s Bank of China website, translate it, understand its impact on the market, and deliver this actionable intelligence to your trading engine, you are already behind. The amount of data coming online is overwhelming current analytical tools that were built for the walled gardens of uniformly structured data.
To address this problem, Yupana employes various machine learning and data refinement techniques to inform its agent based modeling structure. By utilizing its network properties, it synthesizes otherwise uncorrelated information to derive meaningful insight. In this way, Yupana strives to provide a more comprehensive representation of a given system and scale to the needs of that system.
Yupana will initially be developed and refined by addressing the particularly well suited use case of crypto-financial analysis. That said, Yupana will later become an independent community-driven project. As data continues to open across industries, only through a decentralized and cross-disciplinary approach can Yupana scale successfully. The roadmap below lays out Yupana’s development with this in mind:
|3-6 months||1-2 years||3-5 years|
|Preparing historical data to train models||Fully integrating Yupana with Nakamoto Terminal Content Delivery Chain production environment||Handing over project control to the open-source community|
|Prototyping all components within Splunk framework||Open-sourcing all components and portions of the data||Spinning up Yupana modules as independent open projects|
|Testing the network using easily verifiable assumptions||Presenting Yupana at scientific conferences|
|Getting feedback on the concept from other industries and scientific community||Expanding beyond cryptofinance, involving companies and industries|
At the moment, Yupana’s development is being supported by Inca Digital Securities’ research division, IDS Labs, as well as a number of scientists and volunteers. We would like to extend an invitation to all parties interested in contributing to the development of this technology and using it to power real-world use cases. All research materials and prototypes can be found at https://gitlab.com/IncaSec/Labs/yupana/.
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