Search Results for author: Giacomo Toscano

Found 4 papers, 0 papers with code

Bias optimal vol-of-vol estimation: the role of window overlapping

no code implementations8 Apr 2020 Giacomo Toscano, Maria Cristina Recchioni

We derive a feasible criterion for the bias-optimal selection of the tuning parameters involved in estimating the integrated volatility of the spot volatility via the simple realized estimator by Barndorff-Nielsen and Veraart (2009).

From Zero-Intelligence to Queue-Reactive: Limit Order Book modeling for high-frequency volatility estimation and optimal execution

no code implementations24 Feb 2022 Tommaso Mariotti, Fabrizio Lillo, Giacomo Toscano

Building on this approach, in this paper we introduce three main innovations: (i) we use as data-generating process the Queue-Reactive model of the limit order book (Huang et al. (2015)), which - compared to the Zero-Intelligence model - generates more realistic microstructure dynamics, as shown here by using an Hausman test; (ii) we consider not only estimators of the integrated volatility but also of the spot volatility; (iii) we show the relevance of the estimator in the prediction of the variance of the cost of a simulated VWAP execution.

Asymptotic Normality for the Fourier spot volatility estimator in the presence of microstructure noise

no code implementations19 Sep 2022 Maria Elvira Mancino, Tommaso Mariotti, Giacomo Toscano

Moreover, we complete the asymptotic theory for the Fourier spot volatility estimator in the absence of noise, originally presented in [Mancino and Recchioni, 2015], by deriving a Central Limit Theorem with the optimal convergence rate $n^{1/4}$.

SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks

no code implementations11 Jan 2024 Alessio Brini, Giacomo Toscano

The results we obtain suggest that SpotV2Net shows improved accuracy, compared to alternative econometric and machine-learning-based models.

Graph Attention

Cannot find the paper you are looking for? You can Submit a new open access paper.