Paper: arXiv 2503.01629

Abstract

Traders on financial markets generate non-Markovian effects in various ways, particularly through their competition with one another which can be interpreted as a game between different (types of) traders. To quantify the market mechanisms, we empirically analyze self-response functions for pairs of different stocks and the corresponding trade sign correlators. While the non-Markovian dynamics in the self-responses is liquidity-driven, it is expectation-driven in the cross-responses which is related to the emergence of correlations. We empirically study the non-stationarity of these responses over time. In our previous data analysis, we only investigated the crisis year 2008. We now considerably extend this by also analyzing the years 2007, 2014 and 2021. To improve statistics, we also work out averaged response functions for the different years. We find significant variations over time revealing changes in the traders’ game.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 7.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs advanced mathematical frameworks like response functions and correlators with formal definitions (e.g., Eq. 1-2), while being grounded in heavy empirical analysis of high-frequency TAQ data across multiple years with detailed data processing and statistical reporting.

Research Flowchart

  flowchart TD
  Start["Research Goal:<br>Analyze traders' game dynamics<br>across different time periods"] --> DataInput["Data Input:<br>High-frequency trade data<br>Years: 2007, 2008, 2014, 2021"]
  DataInput --> Methodology["Methodology:<br>Calculate Self- & Cross-Response<br>Functions & Trade Sign Correlators"]
  Methodology --> Computation["Computation:<br>Estimate Non-Markovian Dynamics<br>and Liquidity vs. Expectation Effects"]
  Computation --> Analysis["Analysis:<br>Compare Averaged Responses<br>across different time periods"]
  Analysis --> Findings["Key Findings:<br>1. Significant variation in traders' game over time<br>2. Liquidity-driven (self) vs Expectation-driven (cross) dynamics"]
  Findings --> Outcome["Outcome:<br>Empirical evidence of non-stationary<br>market mechanisms and evolving<br>trader competition strategies"]

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  48. We thank Shanshan Wang for fruitful discussions, we are particularly grateful to Rüdiger Kiesel for helpful remarks on the economics literature

1 of 56 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.