Paper: arXiv 2501.06032

Abstract

We introduce a novel framework for developing fully-automated trading model algorithms. Unlike the traditional approach, which is grounded in analytical complexity favored by most quantitative analysts, we propose a paradigm shift that embraces real-world complexity. This approach leverages key concepts relating to self-organization, emergence, complex systems theory, scaling laws, and utilizes an event-based reframing of time. In closing, we describe an example algorithm that incorporates the outlined elements, called the Delta Engine.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 2.0/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper employs advanced mathematical concepts like scaling laws, intrinsic time, and complex systems theory, but lacks any concrete backtest results, statistical metrics, or implementation details (e.g., code, data, performance tables).

Research Flowchart

  flowchart TD
  A["Research Goal: Develop automated trading framework embracing real-world complexity"]
  
  B["Key Methodology<br>Complex Systems Theory<br>Self-organization & Emergence"]
  
  C["Data/Inputs<br>High-frequency financial data streams<br>Event-based temporal markers"]
  
  D["Computational Process<br>Event-based reframing of time<br>Delta Engine algorithm"]
  
  E["Key Outcomes<br>Novel paradigm shift from analytical complexity<br>Scalable trading framework"]
  
  A --> B
  B --> C
  C --> D
  D --> E

Cited References (17)

  1. Multi-scale representation of high frequency market liquidity (2016)
  2. Patterns in high-frequency FX data: discovery of 12 empirical scaling laws (2011)
  3. The Alpha Engine: Designing an Automated Trading Algorithm (2018)
  4. The unreasonable effectiveness of mathematics in the natural Sciences (1960)
  5. More Is Different: B roken symmetry and the nature of the hierarchical structure of science. (1972)
  6. Complexity: A very short introduction (2014)
  7. Applied Complexity: F inance and Economics in a New Light (2019)
  8. A new kind of science (2002)
and 9 more
  1. A project to find the fundamental theory of physics (2020)
  2. Power laws, P areto distributions and Z ipf’s law (2005)
  3. The theory of intrinsic time: A primer — → 2406.07354
  4. Changing time scale for short-term forecasting in financial markets (1996)
  5. The Sapient Cosmos: What a modern-day synthesis of science and philosophy teaches usaAbout the emergence of information, consciousness, and meaning (2025)
  6. R&D strategy document (2010) — link
  7. From the bird’s eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (1997)
  8. Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time (2019)
  9. Bridging the gap: Decoding the intrinsic nature of time in market data (2022) — link

1 of 17 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.