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Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenon

Published 17 Apr 2024 in q-fin.TR and q-fin.RM | (2404.11722v2)

Abstract: This research extends the conventional concepts of the bid--ask spread (BAS) and mid-price to include the total market order book bid--ask spread (TMOBBAS) and the global mid-price (GMP). Using high-frequency trading data, we investigate these new constructs, finding that they have heavy tails and significant deviations from normality in the distributions of their log returns, which are confirmed by three different methods. We shift from a static to a dynamic analysis, employing the ARMA(1,1)-GARCH(1,1) model to capture the temporal dependencies in the return time-series, with the normal inverse Gaussian distribution used to capture the heavy tails of the returns. We apply an option pricing model to address the risks associated with the low liquidity indicated by the TMOBBAS and GMP. Additionally, we employ the Rachev ratio to evaluate the risk--return performance at various depths of the limit order book and examine tail risk interdependencies across spread levels. This study provides insights into the dynamics of financial markets, offering tools for trading strategies and systemic risk management.

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References (45)
  1. Limit Order Books. Cambridge University Press.
  2. Residual life time at great age. The Annals of Probability, 2(5):792–804.
  3. Different approaches to risk estimation in portfolio theory. The Journal of Portfolio Management, 31(1):103–112.
  4. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3):307–327.
  5. High-frequency trading and price discovery. The Review of Financial Studies, 27(8):2267–2306.
  6. Option valuation using the fast Fourier transform. Journal of Computational Finance, 2:61–73.
  7. Clark, P. (1973). A subordinated stochastic process model with fixed variance for speculative prices. Econometrica, 41:135–156.
  8. Cont, R. (2001). Empirical properties of asset returns: Stylized facts and statistical issues. Quantitative Finance, 1(2):223.
  9. Davison, A. C. (1984). Modelling excesses over high thresholds, with an application. In Statistical Extremes and Applications, pages 461–482. Springer-Verlag.
  10. Comparison of tail index estimators. Statistica Neerlandica, 52(1):60–70.
  11. Duffie, D. (2010). Dynamic Asset Pricing Theory. Princeton University Press.
  12. Eagle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation. Econometrica, 50(4):987–1007.
  13. Modelling Extremal Events: For Insurance and Finance. Springer-Verlag.
  14. Stochastic Finance: An Introduction in Discrete Time. Walter de Gruyter.
  15. Limit order books. Quantitative Finance, 13(11):1709–1742.
  16. Grimshaw, S. D. (1993). Computing maximum likelihood estimates for the generalized Pareto distribution. Technometrics, 35(2):185–191.
  17. Assessing confidence intervals for the tail index by Edgeworth expansions for the Hill estimator.
  18. Hill, B. M. (1975). A simple general approach to inference about the tail of a distribution. The Annals of Statistics, pages 1163–1174.
  19. Hogg, R. V. (1972). More light on the kurtosis and related statistics. Journal of the American Statistical Association, 67(338):422–424.
  20. Hogg, R. V. (1974). Adaptive robust procedures: A partial review and some suggestions for future applications and theory. Journal of the American Statistical Association, 69(348):909–923.
  21. Parameter and quantile estimation for the generalized Pareto distribution. Technometrics, 29(3):339–349.
  22. LOBSTER: Limit Order Book Rreconstruction System. Available at SSRN 1977207.
  23. Risk premia: Exact solutions vs. log-linear approximations. Journal of Banking & Finance, 37:4256–4264.
  24. Lux, T. (2009). Stochastic behavioral asset-pricing models and the stylized facts. In Handbook of Financial Markets: Dynamics and Evolution, pages 161–215. Elsevier.
  25. On the distribution of stock price differences. Journal of Operations Research, 15:1057–1062.
  26. Quantitative Risk Management: Concepts, Techniques and Tools—Revised Edition. Princeton University Press.
  27. O’Hara, M. (1998). Market Microstructure Theory. Wiley.
  28. The estimation of the parameters of the stable laws. Biometrika, 62:163–170.
  29. Pickands III, J. (1975). Statistical inference using extreme order statistics. the Annals of Statistics, pages 119–131.
  30. Stable Paretian Models in Finance. Wiley.
  31. An asset return model capturing stylized facts. Mathematics and Financial Economics, 5(2):101–119.
  32. Sato, K.-I. (1999). Lévy Processes and Infinitely Divisible Distributions. Cambridge University Press.
  33. Schoutens, W. (2003). Lévy Processes in Finance: Pricing Financial Derivatives. Wiley, Hoboken, NJ.
  34. Sharpe, W. F. (1966). Mutual fund performance. The Journal of Business, 39(1):119–138.
  35. An agent-based approach to financial stylized facts. Physica A: Statistical Mechanics and its Applications, 379(1):207–225.
  36. Bitcoin volatility and intrinsic time using double subordinated levy processes.
  37. Multiple subordinated modeling of asset returns: Implications for option pricing. Econometric Reviews, 40(3):290–319.
  38. Equity premium puzzle or faulty economic modelling? Review of Quantitative Finance and Accounting, 56:1329–1342.
  39. Shreve, S. E. (2004). Stochastic Calculus for Finance II: Continuous-Time Models. Springer-Verlag.
  40. Smith, R. L. (1985). Maximum likelihood estimation in a class of nonregular cases. Biometrika, 72(1):67–90.
  41. Smith, R. L. (1987). Estimating tails of probability distributions. The Annals of Statistics, pages 1174–1207.
  42. Performance measurement in a downside risk framework. The Journal of Investing, 3(3):59–64.
  43. Tsay, R. S. (2005). Analysis of Financial Time Series. Wiley.
  44. A note on the mean correcting martingale measure for geometric Lévy processes. Applied Mathematics Letters, 24(5):593–597.
  45. Yu, J. (2003). Empirical characteristic function estimation and its applications. Econometric Reviews, 23:93–123.

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