# Architecture of Automated Crypto-Finance Agent

arXiv: https://arxiv.org/abs/2107.07769 · HTML: https://mlsanity.com/paper/2107.07769/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 10 references that are in the map.
- First posted on arXiv 16 Jul 2021.

## Builds on (most cited first, 3 of 3)

- [Reinforcement Learning for Market Making in a Multi-agent Dealer Market](https://mlsanity.com/paper/1911.05892/) (2019)
- [Using Deep Learning for price prediction by exploiting stationary limit order book features](https://mlsanity.com/paper/1810.09965/) (2018)
- [A zero-sum monetary system, interest rates, and implications](https://mlsanity.com/paper/1506.08231/) (2015)

## Built on by (most cited first, 3 of 3)

- [Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models](https://mlsanity.com/paper/2211.08281/) (2022)
- [Causal Analysis of Generic Time Series Data Applied for Market Prediction](https://mlsanity.com/paper/2204.12928/) (2022)
- [SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergence](https://mlsanity.com/paper/2605.10515/) (2026)

## Abstract (arXiv)

We present the cognitive architecture of an autonomous agent for active portfolio management in decentralized finance, involving activities such as asset selection, portfolio balancing, liquidity provision, and trading. Partial implementation of the architecture is provided and supplied with preliminary results and conclusions.