Market liquidity is a latent and dynamic variable. Building on Cont et al. (2014), we propose a dynamical price impact model at high-frequency, in which price impact is a product of daily, diurnal, and autoregressive stochastic intraday com- ponents. The model is estimated using a Kalman filter...

Asset transaction prices sampled at high frequency are much staler than one might expect in the sense that they frequently lack new updates showing zero returns. In this paper, we propose a theoretical framework for formalizing this phenomenon. It hinges on the existence of a latent...

In all investment decisions it is important to determine the degree of uncertainty associated with the valuation of a company. We propose an original and robust methodology to company valuation which replaces the traditional point estimate of the conventional Discounted Cash Flow (DCF) with a...

This paper presents two stocks recommendation systems based on a stochastic characterization of firm present value that extends the conventional discounted cash flow analysis. In the Single-Stock Quantile recommendation system, the market price of a company's stocks is compared with the...

In the context of high-frequency financial data it is often assumed that sampling times are exogenous. This entails that financial asset prices, sampled on a grid of trade instants, are independent from the sampling times. We derive statistical tests capable of determining whether or not, and to...

We propose a novel algorithm which allows to sample paths from an underlying price process in a local volatility model and to achieve a substantial variance reduction when pricing exotic options. The new algorithm relies on the construction of a discrete multinomial tree. The crucial feature of...

It has been recently shown that spot volatilities can be very well modeled by rough stochastic volatility type dynamics. In such models, the log-volatility follows a fractional Brownian motion with Hurst parameter smaller than 1/2. This result has been established using high frequency volatility...

We present an augmented stochastic version of the Solow neoclassical growth model to examine whether financial factors -- expressed as deviations from their trend -- represent important business cycle drivers.Our novel framework is used to study the dynamics of the US growth over the period...

Based on the fact that realized measures of volatility are affected by measurement errors, we introduce a new family of discrete-time stochastic volatility models having two measurement equations relating both observed returns and realized measures to the latent conditional variance. A...

In this study we provide an analytical characterization of the impact of zero returns on the popular realized covariance estimator of Barndorff-Nielsen and Shephard (2004). In our framework, efficient price processes evolve as a semimartingale with some likelihood of repeated prices. We show...