Efficient Market Dynamics: Unraveling Informational Efficiency in UK Horse Racing Betting Markets Through Betfair’s Time Series Analysis
Narayan Tondapu
Narayan Tondapu, Microsoft, Redmond (Washington), USA.
Manuscript received on 23 February 2024 | First Revised Manuscript received on 04 March 2024 | Second Revised Manuscript received on 26 February 2025 | Manuscript Accepted on 15 March 2025 | Manuscript published on 30 March 2025 | PP: 39-49 | Volume-4 Issue-3, March 2025 | Retrieval Number: 100.1/ijssl.C111603030324 | DOI: 10.54105/ijssl.C1116.04030325
Open Access | Ethics and Policies | Cite | Zenodo | OJS | Indexing and Abstracting
© The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Using Betfair’s time series data, an analysis of the United Kingdom (UK) horse racing market reveals an interesting paradox: a market with short tails, rapidly decaying autocorrelations, and no long-term memory. There seems to be a remarkably high level of informational efficiency in betting exchange returns, in contrast to financial assets that are characterized by heavy tails and volatility clustering. The generalized Gaussian unconditional distribution with a light tail points to a market where knowledge is quickly assimilated and reflected in prices. This is further supported by the extremely quick fading of autocorrelations and the absence of gain- loss asymmetry. Therefore, in addition to measuring long-range memory, the Hurst exponent also shows mean reversion, a sign that markets respond quickly to fresh information.
Keywords: Betfair, Financial Assets, Horse Racing Market, United Kingdom.
Scope of the Article: Economics