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Università della Svizzera italiana

Optimal conditionally unbiased bounded-influence inference in dynamic location and scale models

Mancini, Loriano ; Ronchetti, Elvezio ; Trojani, Fabio

In: Journal of the American Statistical Association, 2005, vol. 100, no. 470, p. 628-641

This paper studies the local robustness of estimators and tests for the conditional location and scale parameters in a strictly stationary time series model. We first derive optimal bounded-influence estimators for such settings under a conditionally Gaussian reference model. Based on these results, optimal bounded-influence versions of the classical likelihood-based tests for parametric...

Università della Svizzera italiana

Robust GMM tests for structural breaks

Gagliardini, Patrick ; Trojani, Fabio ; Urga, Giovanni

In: Journal of Econometrics, 2005, vol. 129, no. 1-2, p. 139-182

We propose a class of new robust GMM tests for endogenous structural breaks. The tests are based on supremum, average and exponential functionals derived from robust GMM estimators with bounded influence function. We study the theoretical local robustness properties of the new tests and show that they imply a uniformly bounded asymptotic sensitivity of size and power under general local...

Università della Svizzera italiana

Robustness and ambiguity aversion in general equilibrium

Trojani, Fabio ; Vanini, Paolo

In: Review of Finance, 2004, vol. 8, no. 2, p. 279-324

We analyze the empirical predictions arising from settings of ambiguity aversion in intertemporal heterogenous agents economies. We study equilibria for two tractable wealth-homothetic settings of ambiguity aversion in continuous time. Such settings are motivated by a different robust control optimization problem. We show that ambiguity aversion affects optimal portfolio exposures in a way that...

Università della Svizzera italiana

A note on the three-portfolio matching problem

Trojani, Fabio ; Vanini, Paolo ; Vignola, Luigi

A typical problem arising in the financial planning for private investors consists in the fact that the initial investor’s portfolio, the one determined by the consulting process of the financial institution and the universe of instruments made available to the investor have to be matched/optimized when determining the relevant portfolio choice. We call this problem the three-portfolios...

Università della Svizzera italiana

A review of perturbative approaches for robust optimal portfolio problems

Trojani, Fabio ; Vanini, Paolo

In: Computational methods in decision-making, economics and finance, 2002, p. 109

Only a few intertemporal optimal consumption and portfolio problems in partial and general equilibrium can be solved explicitly. It is illustrated in the paper that perturbation theory is a powerful tool for deriving approximate analytical solutions for the desired optimal policies in problems where general state dynamics are admitted and a preference for robustness is present. Starting from the...

Università della Svizzera italiana

Equilibrium asset pricing with time-varying pessimism

Sbuelz, Alessandro ; Trojani, Fabio

We present a flexible analytical framework that incorporates the equilibrium impact of a (possibly state dependent) sentiment for pessimism in continuous time intertemporal asset pricing. State dependent pessimism comes from a state dependent confidence in the reference belief on equity returns dynamics and implies conservative optimal policies precisely in states where such confidence is low. In...

Università della Svizzera italiana

A geometric approach to multiperiod mean variance optimization of assets and liabilities

Leippold, Markus ; Trojani, Fabio ; Vanini, Paolo

We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplifies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set of basis strategies, each having a clear economic interpretation. This implies that the...