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 fore...
This research investigates the role of high-frequency data in volatility forecasting of the China st...
This paper analyses the forecastability of the EuroStoxx 50 monthly returns volatil- ity. We conside...
2015 - 2016Aim of this thesis is to propose and discuss novel model specifications for predicting fi...
This research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future cons...
This research conducts high-frequency intraday volatility estimations on the Euro Stoxx 50 Future u...
This paper proposes a new way of modeling and forecasting intraday returns. We decompose the volatil...
The increased availability of high frequency data sets have led to important new insights in underst...
The increasing availability of financial market data at intraday frequencies has not only led to the...
The vast amount of information characterizing nowadays’s high-frequency financial datasets poses bot...
This paper investigates the role of intraday prices and volume to generate daily volatility forecast...
<p>The idea that integrates parts of this dissertation is that high-frequency data allow for more pr...
The flow of information in financial markets is covered in two parts. An high-order estimator ...
In this paper, we develop modeling tools to forecast Value-at-Risk and volatility with investment ho...
Purpose – Algorithmic trading attempts to reduce trading costs by se...
While much research related to forecasting return volatility does so in a univariate setting, this p...
This research investigates the role of high-frequency data in volatility forecasting of the China st...
This paper analyses the forecastability of the EuroStoxx 50 monthly returns volatil- ity. We conside...
2015 - 2016Aim of this thesis is to propose and discuss novel model specifications for predicting fi...
This research conducts high-frequency intraday volatility forecasts on the Euro Stoxx 50 Future cons...
This research conducts high-frequency intraday volatility estimations on the Euro Stoxx 50 Future u...
This paper proposes a new way of modeling and forecasting intraday returns. We decompose the volatil...
The increased availability of high frequency data sets have led to important new insights in underst...
The increasing availability of financial market data at intraday frequencies has not only led to the...
The vast amount of information characterizing nowadays’s high-frequency financial datasets poses bot...
This paper investigates the role of intraday prices and volume to generate daily volatility forecast...
<p>The idea that integrates parts of this dissertation is that high-frequency data allow for more pr...
The flow of information in financial markets is covered in two parts. An high-order estimator ...
In this paper, we develop modeling tools to forecast Value-at-Risk and volatility with investment ho...
Purpose – Algorithmic trading attempts to reduce trading costs by se...
While much research related to forecasting return volatility does so in a univariate setting, this p...
This research investigates the role of high-frequency data in volatility forecasting of the China st...
This paper analyses the forecastability of the EuroStoxx 50 monthly returns volatil- ity. We conside...
2015 - 2016Aim of this thesis is to propose and discuss novel model specifications for predicting fi...