We investigate intradaily seasonal patterns on the distribution of high frequency financial returns. Using quantile regression we show the expansions and shrinks of the probability law through the day for three years of 15 minutes sampled stock returns. Returns are more dispersed and less concentrated around the median at the hours near the opening and closing. We provide intradaily value at risk assessments and we show how it adapts to changes of dispersion over the day.high frequency returns, quantile regression, Fourier series, intradaily VaR
In this article we propose a new method for producing semiparametric density forecasts for daily fin...
In this article we propose a new method for producing semiparametric density forecasts for daily fin...
We introduce a model for the analysis of intra-day volatility based on unobserved components. The st...
We model the conditional distribution of high-frequency financial returns by means of a two-componen...
Time series of different nature might be characterised by the presence of deterministic and/or stoch...
Using a reduced rank regression framework as well as information criteria, we investigate the presen...
We develop a nonparametric test for whether return volatility exhibits time-varying intraday periodi...
This thesis is composed of three chapters which propose some novel approaches to model and forecast ...
We provide a new framework for modeling trends and periodic patterns in high-frequency financial dat...
We provide a new framework for modeling trends and periodic patterns in high-frequency financial dat...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
This article provides a comprehensive analysis of the size and statistical significance of the day o...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
The identification and estimation of trends in hydroclimatic time series remains an important task i...
In this paper we propose a new approach to a well-known phenomena of intra-day activity pattern on t...
In this article we propose a new method for producing semiparametric density forecasts for daily fin...
In this article we propose a new method for producing semiparametric density forecasts for daily fin...
We introduce a model for the analysis of intra-day volatility based on unobserved components. The st...
We model the conditional distribution of high-frequency financial returns by means of a two-componen...
Time series of different nature might be characterised by the presence of deterministic and/or stoch...
Using a reduced rank regression framework as well as information criteria, we investigate the presen...
We develop a nonparametric test for whether return volatility exhibits time-varying intraday periodi...
This thesis is composed of three chapters which propose some novel approaches to model and forecast ...
We provide a new framework for modeling trends and periodic patterns in high-frequency financial dat...
We provide a new framework for modeling trends and periodic patterns in high-frequency financial dat...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
This article provides a comprehensive analysis of the size and statistical significance of the day o...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
The identification and estimation of trends in hydroclimatic time series remains an important task i...
In this paper we propose a new approach to a well-known phenomena of intra-day activity pattern on t...
In this article we propose a new method for producing semiparametric density forecasts for daily fin...
In this article we propose a new method for producing semiparametric density forecasts for daily fin...
We introduce a model for the analysis of intra-day volatility based on unobserved components. The st...