High-frequency Financial Market Data (Risk Technology by Owain ap Gwilym, Charles Sutcliffe

By Owain ap Gwilym, Charles Sutcliffe

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They found for their sample that shorter time gaps were associated with both faster and larger quote changes. Hausman et al (1992) made allowance for clock-time effects in order to examine whether trade-to-trade prices are stable in transaction time versus clock time. Engle and Russell (1997) proposed a new way of modelling the time gaps between irregularly spaced events such as trades or quote revisions, termed the Autoregressive Conditional Duration (ACD) model. Engle and Russell (1998) found evidence of duration clustering for trades in IBM shares during 1990-91, ie short time gaps between trades tend to cluster together.

Heteroscedasticity and Time Deformation If short-interval returns are independently and identically distributed, there is a simple relationship between the differencing interval and return variance. The variance of returns over long periods (comprising T short periods) is equal to T times the variance over a single short period. However, when using high-frequency data, returns are unlikely to be independently and identically distributed, therefore this relationship will not hold. For example, Müller et al (1995) showed that the volatility of foreign exchange returns does not increase in the predicted manner as the differencing interval is lengthened, and concluded that forex data are not self-similar fractals, ie the distribution of exchange rates is not invariant to changes in the differencing interval.

However, the full set of trade or quote data provides a larger dataset than one that has been compressed by discarding intervening observations. Trade data represents the most fundamental level of data on the trading process. However, researchers may seek data on additional variables related to the trading process, eg the internal aggregation of orders into one large trade, the internal crossing of trades, the process of deciding when to trade (the trading strategy), the portfolio positions of traders at the time they decide to trade, the motives for trading, etc.

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