Paper: arXiv 2408.03594

Abstract

Market information events are generated intermittently and disseminated at high speeds in real-time. Market participants consume this high-frequency data to build limit order books, representing the current bids and offers for a given asset. The arrival processes, or the order flow of bid and offer events, are asymmetric and possibly dependent on each other. The quantum and direction of this asymmetry are often associated with the direction of the traded price movement. The Order Flow Imbalance (OFI) is an indicator commonly used to estimate this asymmetry. This paper uses Hawkes processes to estimate the OFI while accounting for the lagged dependence in the order flow between bids and offers. Secondly, we develop a method to forecast the near-term distribution of the OFI, which can then be used to compare models for forecasting OFI. Thirdly, we propose a method to compare the forecasts of OFI for an arbitrarily large number of models. We apply the approach developed to tick data from the National Stock Exchange and observe that the Hawkes process modeled with a Sum of Exponential’s kernel gives the best forecast among all competing models.

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs advanced mathematical modeling with Hawkes processes and detailed kernel specifications, while demonstrating high empirical rigor through application to high-frequency tick data, model comparison, and specific forecasting results on the National Stock Exchange.

Research Flowchart

  flowchart TD
  A["Research Goal:<br>Forecast High-Frequency OFI<br>using Hawkes Processes"] --> B["Data Input:<br>Tick Data from<br>National Stock Exchange"]
  B --> C["Methodology 1:<br>Estimate OFI using<br>Hawkes Process with<br>Sum of Exponentials Kernel"]
  C --> D["Methodology 2:<br>Forecast Near-Term<br>OFI Distribution"]
  D --> E["Methodology 3:<br>Compare Forecasts<br>across Multiple Models"]
  E --> F["Key Findings:<br>Hawkes Process with<br>Sum of Exponentials Kernel<br>provides best forecast"]

Cited References (34)

  1. GRASP with path-relinking for the three-index assignment problem (2000)
  2. Probability distribution of solution time in GRASP: an experimental investigation (2003)
  3. Parallel GRASP with path-relinking for job shop scheduling (1984)
  4. Title of a Book in Another Language (Quoted in that Language) (1988)
  5. Multi-start and strategic oscillation methods – principles to exploit adaptive memory (2000)
  6. Bubbles in Japan’s stock markets: a macroeconomic analysis (1995)
  7. The resurgent Japanese economy and a Japan–United States free trade agreement (1997)
  8. Efficient algorithms for layer assignment problems (1996)
and 26 more
  1. Gravitation (1973)
  2. Parallel GRASP with path-relinking for job shop scheduling (1983)
  3. Title of Book (2002)
  4. A study on Algorithmic Trading / High Frequency Trading In The Indian Capital Market (2017)
  5. Does Algorithmic Trading Improve Liquidity? (2011)
  6. The cost of algorithmic trading: A first look at comparative performance (2005)
  7. The price impact of order book events (2014)
  8. Flow toxicity and liquidity in a high-frequency world (2012)
  9. Point spectra of some mutually exciting point processes (1971)
  10. Price formation and liquidity in the U.S. Treasury market: The response to public information (1999)
  11. Order imbalances and stock price movements on October 19 and 20, 1987 (1993)
  12. Stock market crashes and the performance of circuit breakers: Empirical evidence (1993)
  13. Order imbalance, liquidity, and market returns (2002)
  14. Futures volatility forecasting based on big data analytics with incorporating an order imbalance effect (2022)
  15. High-frequency quoting: Short-term volatility in bids and offers (2018)
  16. Hawkes processes in finance (2015)
  17. Non-parametric estimation of quadratic Hawkes processes for order book events (2022)
  18. A reality check for data snooping (2000)
  19. A test for superior predictive ability (2005)
  20. Second order statistics characterization of Hawkes processes and non-parametric estimation (2014) — link
  21. Inferring trade direction from intraday data (1991)
  22. On Lewis’ simulation method for point processes (1981)
  23. A non-parametric EM algorithm for multiscale Hawkes processes (2011)
  24. The diversity of high-frequency traders (2013)
  25. Liquidity, Information, and Infrequently Traded Stocks (1996)
  26. The Economic Role of the CBOE’s Short-Term Volatility Index Futures (1992)

0 of 34 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.