Università della Svizzera italiana

Robust subsampling

Camponovo, Lorenzo ; Scaillet, Olivier ; Trojani, Fabio

In: Journal of econometrics, 2012, vol. 167, no. 1, p. 197-210

We characterize the robustness of subsampling procedures by deriving a formula for the breakdown point of subsampling quantiles. This breakdown point can be very low for moderate subsampling block sizes, which implies the fragility of subsampling procedures, even when they are applied to robust statistics. This instability arises also for data driven block size selection procedures minimizing ...

Università della Svizzera italiana

Robust value at risk prediction

Mancini, Loriano ; Trojani, Fabio

In: Journal of financial econometrics, 2011, vol. 9, no. 2, p. 281-313

This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that controls bootstrap instability due to outlying observations. A Monte Carlo simulation shows that our robust method provides more accurate VaR...

Università della Svizzera italiana

Limits of learning about a categorical latent variable under prior near-ignorance

Piatti, Alberto ; Zaffalon, Marco ; Trojani, Fabio ; Hutter, Marcus

In: International journal of approximate reasoning, 2009, vol. 50, no. 4, p. 597-611

In this paper, we consider the coherent theory of (epistemic) uncertainty of Walley, in which beliefs are represented through sets of probability distributions, and we focus on the problem of modeling prior ignorance about a categorical random variable. In this setting, it is a known result that a state of prior ignorance is not compatible with learning. To overcome this problem, another...

Università della Svizzera italiana

A general multivariate threshold GARCH model with dynamic conditional correlations

Audrino, Francesco ; Trojani, Fabio

In: Journal of business & economic statistics, 2011, vol. 29, no. 1, p. 138-149

We introduce a new multivariate GARCH model with multivariate thresholds in conditional correlations and develop a two-step estimation procedure that is feasible in large dimensional applications. Optimal threshold functions are estimated endogenously from the data, and the model conditional covariance matrix is ensured to be positive definite. We study the empirical performance of our model in...

Università della Svizzera italiana

Infinitesimal robustness for diffusions

La Vecchia, Davide ; Trojani, Fabio

In: Journal of the american statistical association, 2010, vol. 105, no. 490, p. 703–712

We develop infinitesimally robust statistical procedures for the general diffusion processes. We first prove the existence and uniqueness of the times-series influence function of conditionally unbiased M-estimators for ergodic and stationary diffusions, under weak conditions on the (martingale) estimating function used. We then characterize the robustness of M-estimators for diffusions and...

Università della Svizzera italiana

Correlation risk and optimal portfolio choice

Buraschi, Andrea ; Porchia, Paolo ; Trojani, Fabio

In: The journal of finance, 2010, vol. 65, no. 1, p. 393-420

We develop a new framework for multivariate intertemporal portfolio choice that allows us to derive optimal portfolio implications for economies in which the degree of correlation across industries, countries, or asset classes is stochastic. Optimal portfolios include distinct hedging components against both stochastic volatility and correlation risk. We find that the hedging demand is...

Università della Svizzera italiana

Ambiguity aversion and the term structure of interest

Gagliardini, Patrick ; Porchia, Paolo ; Trojani, Fabio

In: The review of financial studies, 2009, vol. 22, no. 10, p. 4157-4188

This paper studies the term structure implications of a simple structural model in which the representative agent displays ambiguity aversion, modeled by Multiple Priors Recursive Utility. Bond excess returns reflect a premium for ambiguity, which is observationally distinct from the risk premium of affine yield curve models. The ambiguity premium can be large even in the simplest log-utility...

Università della Svizzera italiana

Accurate short-term yield curve forecasting using functional gradient descent

Audrino, Francesco ; Trojani, Fabio

In: Journal of financial econometrics, 2007, vol. 5, no. 4, p. 591–623

We propose a multivariate nonparametric technique for generating reliable shortterm historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest rate series. It is computationally feasible in large dimensions and it can account for non- linearities...