The economic benefit of applying the Fourier covariance estimation methodology over other estimators in the presence of market microstructure noise is studied from the perspective of an asset-allocation decision problem. We find that using Fourier methodology yields statistically significant gains

We analyze the effects of market microstructure noise on the Fourier estimator of multivariate volatilities. We prove that the estimator is consistent in the case of asynchronous data and robust in the presence of microstructure noise. This result is obtained through an analytical computation of...

Financial crises prediction is an essential topic in finance. Designing an efficient Early Warning System (EWS) can help prevent catastrophic losses resulting from financial crises. We propose an EWS for predicting potential market instability conditions under which perturbations in the price...

We define a new consistent estimator of the integrated volatility of volatility based only on a pre-estimation of the Fourier coefficients of the volatility process. We investigate the finite sample properties of the estimator in the presence of noise contamination by computing the bias of the...

We discuss the impact of volatility estimates from high frequency data on derivative pricing. The principal purpose is to estimate the diffusion coefficient of an Itô process using a nonparametric Nadaraya–Watson kernel approach based on selective estimators of spot volatility proposed in the...