Threshold bipower variation and the impact of jumps on volatility forecasting
This study reconsiders the role of jumps for volatility forecasting by showing that jumps have
a positive and mostly significant impact on future volatility. This result becomes apparent …
a positive and mostly significant impact on future volatility. This result becomes apparent …
[كتاب][B] Handbook of volatility models and their applications
A complete guide to the theory and practice of volatility models in financial engineering
Volatility has become a hot topic in this era of instant communications, spawning a great …
Volatility has become a hot topic in this era of instant communications, spawning a great …
[PDF][PDF] HAR modeling for realized volatility forecasting
The importance of financial market volatility has generated a very large literature 5 in which
volatility dynamics has been modelled in order to take into account its 6 most salient …
volatility dynamics has been modelled in order to take into account its 6 most salient …
Nonparametric tests for pathwise properties of semimartingales
We propose two nonparametric tests for investigating the pathwise properties of a signal
modeled as the sum of a Lévy process and a Brownian semimartingale. Using a …
modeled as the sum of a Lévy process and a Brownian semimartingale. Using a …
Outlyingness weighted covariation
Quadratic covariation is a popular descriptive measure for the volatility of a multivariate price
process. It is consistently estimated by the sum of outer products of high-frequency returns …
process. It is consistently estimated by the sum of outer products of high-frequency returns …
Nonparametric stochastic volatility
We provide nonparametric methods for stochastic volatility modeling. Our methods allow for
the joint evaluation of return and volatility dynamics with nonlinear drift and diffusion …
the joint evaluation of return and volatility dynamics with nonlinear drift and diffusion …
Spot volatility estimation using delta sequences
We introduce a unifying class of nonparametric spot volatility estimators based on delta
sequences and conceived to include many of the existing estimators in the field as special …
sequences and conceived to include many of the existing estimators in the field as special …
Jump robust two time scale covariance estimation and realized volatility budgets
We estimate the daily integrated variance and covariance of stock returns using high-
frequency data in the presence of jumps, market microstructure noise and non-synchronous …
frequency data in the presence of jumps, market microstructure noise and non-synchronous …
Optimum thresholding using mean and conditional mean squared error
We consider a univariate semimartingale model for (the logarithm of) an asset price,
containing jumps having possibly infinite activity. The nonparametric threshold estimator IV …
containing jumps having possibly infinite activity. The nonparametric threshold estimator IV …
Stock volatility, return jumps and uncertainty shocks during the Great Depression
There are a multitude of explanations for the depth and length of the Great Depression, of
which uncertainty has been proposed as one possible explanation (Romer 1990). The …
which uncertainty has been proposed as one possible explanation (Romer 1990). The …