We propose localized spectral estimators for the quadratic covariation and the spot covolatility of diffusion processes which are observed discretely with additive observation noise. The eligibility of this approach to lead to an appropriate estimation for time-varying volatilities stems from an...

We propose a new methodology based on Fourier analysis to estimate the fourth power of the volatility function (spot quarticity) and, as a byproduct, the integrated function. We prove the consistency of the proposed estimator of the integrated quarticity. Further, we analyse its efficiency in...

We investigate the dynamics of the relationship between returns and extreme downside risk in different states of the market by combining the framework of Bali, Demirtas, and Levy (2009) with a Markov switching mechanism. We show that the risk-return relationship identified by Bali, Demirtas, and...

Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools. Although machine learning algorithms can uncover subtle, contextual and non-linear relationships,...

In this paper we prove a central limit theorem for the Fourier quarticity estimator proposed in Mancino and Sanfelici (2012). In particular, we obtain a new consistency result and we show that the estimator reaches the parametric rate ρ(n)1/2, where ρ(n), is the discretization mesh and n the...

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based...

Measuring comovements across international financial markets is important for policy purposes and portfolio management. We develop a new approach to analyse such comovements in relation to key state variables, such as equity market volatility and short-term interest rates. These state variables...

There are different approaches for the detection of market phase changes in stock markets. Most of them utilize various assumptions and constraints which makes these methods somewhat arbitrary. This paper develops an algorithm which identifies bull and bear markets retrospectively in a very...

The paper studies the statistical properties of the evolution of the USD/HKD exchange rate during the period after the separation of strong and weak side convertibility undertakings, when the rate is confined to a specified corridor. We suggest a discrete time Markov model for the exchange rate...