Paper: arXiv 2504.08611

Abstract

In the theory of financial markets, a stylized fact is a qualitative summary of a pattern in financial market data that is observed across multiple assets, asset classes and time horizons. In this article, we test a set of eleven stylized facts for financial market data. Our main contribution is to consider a broad range of geographical regions across Asia, continental Europe, and the US over a time period of 150 years, as well as two of the most traded cryptocurrencies, thus providing insights into the robustness and generalizability of commonly known stylized facts.

Complexity vs Empirical Score

  • Math Complexity: 4.5/10
  • Empirical Rigor: 9.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper involves moderate mathematical modeling of volatility and statistical testing, but its core focus is on empirical analysis using extensive historical data (150 years) across multiple asset classes and regions, with reproducible code and datasets, making it highly backtest-ready.

Research Flowchart

  flowchart TD
  A["Research Goal<br>Test 11 Stylized Facts"] --> B["Data Collection<br>150 Years: Asia, Europe, US, Crypto"]
  B --> C["Methodology<br>Cross-Asset & Time Horizon Analysis"]
  C --> D["Computational Process<br>Empirical Testing & Validation"]
  D --> E{"Key Outcomes"}
  E --> F["Stylized Facts Robust<br>Across Geographies"]
  E --> G["Time Horizon<br>Dependent Patterns"]
  E --> H["Crypto Markets<br>Exhibit Similar Traits"]

Cited References (72)

  1. Empirical properties of asset returns: stylized facts and statistical issues (2001) — link
  2. Scaling in Stock Market Data: Stable Laws and Beyond (1997)
  3. Long range dependence in financial markets (2005)
  4. Volatility Clustering in Financial Markets: Empirical Facts and Agent-Based Models (2007) — link
  5. Scaling and correlation in financial data (1997) — link
  6. Universal features of price formation in financial markets: perspectives from Deep Learning (2018) — link
  7. Econophysics review: I. Empirical facts (2011) — link
  8. Development of an agent-based speculation game for higher reproducibility of financial stylized facts (2019) — link
and 64 more
  1. Revisiting Stylized Facts for Modern Stock Markets (2023) — link
  2. Stylized Facts of High-Frequency Bitcoin Time Series (2024) — link
  3. The Self-Organized Criticality Paradigm in Economics & Finance (2024) — link
  4. Leverage Effect in Financial Markets: The Retarded Volatility Model (2001) — link
  5. More stylized facts of financial markets: leverage effect and downside correlations (2001) — link
  6. Quadratic Hawkes processes for financial prices (2017) — link
  7. Universality classes for extreme-value statistics (1997) — link
  8. Multivariate Quadratic Hawkes Processes – Part I: Theoretical Analysis (2023) — link
  9. The fine-structure of volatility feedback I: Multi-scale self-reflexivity (2014) — link
  10. Prospect Theory: An Analysis of Decision under Risk (1979)
  11. Volatilities of different time resolutions — Analyzing the dynamics of market components (1997) — link
  12. Heterogeneous volatility cascade in financial markets (2001) — link
  13. ‘Direct’ causal cascade in the stock market from the ‘infrared’ to the ‘ultraviolet’ (1998) — link
  14. A geographical model for the daily and weekly seasonal volatility in the foreign exchange market (1993) — link
  15. Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis (1990) — link
  16. Multi-scaling in finance (2007) — link
  17. Stylised facts for high-frequency cryptocurrency data (2019) — link
  18. Multiresolution methods for financial time series prediction (1995) — link
  19. From the bird’s eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (1997) — link
  20. Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development (2005) — link
  21. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python (2020) — link
  22. Array programming with NumPy (2020) — link
  23. Data structures for statistical computing in python (2010)
  24. statsmodels: Econometric and statistical modeling with python (2010)
  25. Python 3 Reference Manual (2009)
  26. Time series: theory and methods (1986)
  27. Correlations in economic time series (1997) — link
  28. Agent-based modeling in economics and finance: Past, present, and future (2022)
  29. The Extreme Value Method for Estimating the Variance of the Rate of Return (1980)
  30. Estimating Variance From High, Low and Closing Prices (1991)
  31. Intermittency, Long-Memory and Financial Returns (2007) — link
  32. A MODEL OF PACKET TRAFFIC USING A RANDOM WALL MODEL (1999) — link
  33. Self-Similar Network Traffic and Performance Evaluation (2002) — link
  34. Intermittent transition to turbulence in dissipative dynamical systems. Commun. Math. Phys. 74, 189-197 (1980) — link
  35. A probabilistic approach to intermittency (1999)
  36. Turbulent Cascades in Foreign Exchange Markets (1996) — link
  37. A long memory property of stock market returns and a new model (1993) — link
  38. Critical phenomena in natural sciences: chaos, fractals, selforganization and disorder: concepts and tools (2006)
  39. Introduction to Asset Price Dynamics, Volatility, and Prediction (2007)
  40. A Random-Difference Series for Use in the Analysis of Time Series (1934) — link
  41. The Analysis of Economic Time-Series—Part I: Prices (1953) — link
  42. Every minute counts in financial markets (1991) — link
  43. Intraday periodicity and volatility persistence in financial markets (1997) — link
  44. Dedication (2001) — link
  45. High-Frequency Data and Volatility in Foreign-Exchange Rates (1996) — link
  46. Tests of fit for the logistic distribution based on the empirical distribution function (1979) — link
  47. A closed-form solution for options with stochastic volatility with applications to bond and currency options (1993)
  48. A multifractal model of asset returns (1997)
  49. Intermittency of Superpositions of Ornstein–Uhlenbeck Type Processes (2016) — link
  50. Enriching Financial Datasets with Generative Adversarial Networks (2019)
  51. Generative adversarial networks in finance: an overview (2021) — link
  52. The statistics of bitcoin and cryptocurrencies (2016)
  53. Study of Stylized Facts in Stock Market Data (2023) — link
  54. Self-organized criticality: An Explanation of 1/f noise (1987) — link
  55. How nature works (1996) — link
  56. The psycho-biology of language : an introduction to dynamic philology (1935)
  57. Making Sense of Chaos: A Better Economics for a Better World (2024)
  58. Forecasts of Future Prices, Unbiased Markets, and “Martingale” Models (1965) — link
  59. The Levenberg-Marquardt algorithm: Implementation and theory (1978) — link
  60. The effect of intraday periodicity on realized volatility measures (2022) — link
  61. Generalized autoregressive conditional heteroskedasticity (1986) — link
  62. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)
  63. Intermittency and nonextensivity in turbulence and financial markets (1999)
  64. Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979) — link

0 of 72 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.