One of the immediate goals of the Yupana project is to go beyond an academic exercise and prove the conceptual viability of Agent Based Modeling approach in a real-world market simulation and predictions application. The crypto-asset ecosystem, and Nakamoto Terminal platform, specifically, provide a perfect testbed thanks to a vast amount of time-stamped data, an active developer community, and a scalable infrastructure with access to multiple 3rd party services.
Predictive Modeling In CryptoFinance
With the publishing of Satoshi Nakamoto’s white paper, “Bitcoin: A peer-to-peer electronic cash system” (2008) based on Adam Back’s Proof-of-Work System, and the subsequent open-source software release of Bitcoin in 2009, the door to distributed ledger technology was opened. Bitcoin paved the way for new cryptographic systems to be created at will through forking or development of a new project. Today, these systems proliferate faster than one can keep up with. Some projects are…
Agent Based Modeling Framework for Cryptofinance
As stated in the previous post, Yupana - Global Vision, conventional modeling techniques for simulating complex environments have relied on a set of fixed rules to govern how the model is to function. Agent based models (ABM) have been used for this purpose, to represent complex systems such as those in evolutionary biology or economics. While methods of ABM have been effective for specific use-cases, they fail to be generalizable and scalable over multiple systems. Popular heuristics such as…
Introduction to Yupana: A Flexible Agent Based Modeling Framework
Complex systems like those in biology, economics, or ecology are difficult to represent and properly understand. Complex interactions, emergent properties, and high dimensionality make it difficult to disentangle the governing rules and systemic properties when trying to model a given environment. We often depend on external tools to help us see particular patterns that are otherwise non-salient. These tools help us to better understand narrow relationships, aggregate and filter large sets of…
Agent Based Modeling Framework for Cryptofinance
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.