Abstract
The analysis of financial data on the lowest aggregation level is an ongoing topic in the recent financial econometrics literature. The availability of financial transaction databases has created a new exciting field in econometrics and empirical finance which allows us to look at old puzzles in finance from a new perspective and to address a variety of new issues. Transaction data - sometimes refereed to as ultra-high-frequency data - can be seen as the informational limiting case where all transactions are recorded and information with respect to the complete transaction and order flow on a financial market is collected. The main property of transaction data is the irregular spacing in time. For this reason, they have to be considered as marked point processes. Since the seminal work of Engle and Russell (1998), much research effort has been devoted to the specification and application of financial point process models.
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