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- W1796740848 abstract "In this paper, we investigate some predictable patterns in high frequency price jumps using trades, orders and quotes data on the Euronext 100 Index. A fixed volume chart allows us to control for trading volume effects and avoid non trading issues at high frequency aggregation. We detect jumps through four different methods that encompass constant volatility, time-varying volatility and periodicity. Our forecasting model is a logistic model adjusted to rare events. At an average 2-minute trading volume frequency, we find that price jumps are mainly driven by liquidity gaps in the order book. The origin of those gaps is still an open question. They may be due to order cancellations or to a low resiliency of the stock market. Our results suggest that market participants could take advantage of some predictable patterns in price jumps in order to enhance their hedging or investment strategies." @default.
- W1796740848 created "2016-06-24" @default.
- W1796740848 creator A5008507277 @default.
- W1796740848 date "2013-01-01" @default.
- W1796740848 modified "2023-09-27" @default.
- W1796740848 title "Detecting and Forecasting High Frequency Price Jumps in the Stock Market" @default.
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- W1796740848 doi "https://doi.org/10.2139/ssrn.2226455" @default.
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