- Essays on high frequency financial econometrics
- Award date
- 16 June 2015
- Number of pages
- Amsterdam: Tinbergen Institute
- Document type
- PhD thesis
- Faculty of Economics and Business (FEB)
- Amsterdam School of Economics Research Institute (ASE-RI)
It has long been demonstrated that continuous-time methods are powerful tools in financial modeling. Yet only in recent years, their counterparts in empirical analysis—high frequency econometrics—began to emerge with the availability of intra-day data and relevant statistical tools. This dissertation contributes to the development of this emerging area in two directions.
On the one hand, it develops new econometric tools to identify different types of interdependence structure among asset state processes. Chapter 2 examines the co-movement of asset price and its volatility, known as leverage effect. Different from previous work, this chapter allows price and volatility processes to have both continuous and discontinuous stochastic components that may contribute to the overall leverage effect. The second type is about the interdependence between price process and its jump intensity, known as self-excitation. Chapter 3 extends the definition of self-excitation in jumps accordingly, proposes statistical tests to detect its presence in a discretely observed path at high frequency, and derives the tests’ asymptotic properties.
On the other hand, Finance theory implies a set of constraints on the dynamics of an option price process and that of its underlying processes. Yet empirical option pricing models may either implicitly ignore some theoretical constraints or impose a possibly misspecified parametric structure on it. Chapter 4 fill this gap, by proposing a statistical procedure that utilizes information from the time series of the underlying processes to test the specification of a given option pricing model.
- Research conducted at: Universiteit van Amsterdam
Series: Tinbergen Institute research series 611
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