## Abstract Recent research investigating the properties of high‐frequency financial data has suggested that the stochastic nonlinearity widely present in such data may be characterized by heterogeneous components in conditional volatility, and nonlinear dependence of threshold autoregressive form
Dynamics of intraday serial correlation in the Italian futures market
✍ Scribed by Simone Bianco; Roberto Renò
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 263 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0270-7314
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✦ Synopsis
Abstract
The serial correlation of high‐frequency intraday returns on the Italian stock index futures (FIB30) in the period 2000–2002 is studied. It is found that intraday autocorrelation is mostly negative for time scales lower than 20 minutes, mainly due to the bid–ask bounce effect. Although this supports the efficiency of the Italian futures market, evidence that intraday serial correlation becomes positive in high‐volatility regimes is also provided. Moreover, it is found that it is mainly unexpected volatility that makes serial correlation rise, and not its predictable part. The results are supportive of the K. Chan (1993) model. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:61–84, 2006
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