Publication
Intraday volatility forecasting in high-frequency data using order book information
| Summary: | This research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future considering a multiplicative component GARCH framework, where the conditional volatility of high-frequency returns is decomposed into a daily, diurnal and stochastic intraday component. In contrast to extant research, in this work project a relatively long period of 423 trading days is covered corresponding to about 345.000 1-minute observations. To opt for a more practitioner-oriented approach we perform fixed window as well as rolling window forecasts. There is evidence that incorporating Limit Order Book information into the return series leads to superior forecasting results compared to the usage of simple trade returns. Nonetheless, the forecasting performance is time-varying and is often deteriorated by the seasonality of liquidity provision |
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| Main Authors: | Grübe, Maximilian |
| Subject: | Garch Volatility forecasting High-frequency data Limit order book |
| Year: | 2019 |
| Country: | Portugal |
| Document type: | master thesis |
| Access type: | open access |
| Associated institution: | Universidade Nova de Lisboa |
| Language: | English |
| Origin: | Repositório Institucional da UNL |
| Summary: | This research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future considering a multiplicative component GARCH framework, where the conditional volatility of high-frequency returns is decomposed into a daily, diurnal and stochastic intraday component. In contrast to extant research, in this work project a relatively long period of 423 trading days is covered corresponding to about 345.000 1-minute observations. To opt for a more practitioner-oriented approach we perform fixed window as well as rolling window forecasts. There is evidence that incorporating Limit Order Book information into the return series leads to superior forecasting results compared to the usage of simple trade returns. Nonetheless, the forecasting performance is time-varying and is often deteriorated by the seasonality of liquidity provision |
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