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2 results

  • 5 - Infill Asymptotic Theory and Applications in Financial Econometrics

  • from Part II - Continuous-Time Models and High-Frequency Financial Econometrics
  • Edited by Shuping Shi, Macquarie University, Sydney, Xiaohu Wang, Fudan University, Shanghai, Tao Zeng, Zhejiang University, China
  • Book:
    Financial Econometrics
    Published online:
    20 February 2025
    Print publication:
    27 February 2025, pp 132-158

  • Summary

    Recent years have seen a surge of econometric development of infill asymptotic theory. Unlike the traditional large-sample theory which assumes that an increasing sample size is due to an increasing time span (denoted as the long-span asymptotic theory in this chapter), infill asymptotic theory assumes that the sample size increases because the sampling frequency shrinks toward zero. The limit of the infill asymptotics of the estimators are those based on a continuous record. Not surprisingly, a development of infill asymptotic theory is closely linked to the increased popularity of continuous time models in applied economics and finance. This chapter reviews the literature on the infill asymptotic theory and applications in financial econometrics, such as unit root testing, bootstrap, and structural break models. In many applications, nonstandard limiting distribution arises. In some cases, the initial condition shows up in the limiting distributions. Monte Carlo studies are carried out to check the performance of the infill asymptotic theory relative to the long-span asymptotic theory.

Financial Econometrics
  • Theory and Applications
  • Edited by Shuping Shi, Xiaohu Wang, Tao Zeng
  • Published online:
    20 February 2025
    Print publication:
    27 February 2025
  • Financial Econometrics is a contribution to modern financial econometrics, overviewing both theory and application. It covers, in detail, three important topics in the field that have recently drawn the attention of the academic community and practitioners, with low-frequency data (trend determination, bubble detection, and factor-augmented regressions) and examines various topics in high-frequency financial econometrics with continuous time models and discretized data. Also included are the estimation of stochastic volatility models, posterior-based hypothesis testing, and posterior-based model selection. Exploring topics at the forefront of research in the field of financial econometrics, this book offers an accessible introduction to the research and provides the groundwork for the development of new econometric techniques.