Classical quantitative finance models such as the Geometric Brownian Motion or its later extensions such as local or stochastic volatility models do not make sense when seen from a physics-based perspective, as they are all equivalent to a negative mass oscillator with a noise. This paper...

We compare the performance of popular covariance forecasting models in the context of a portfolio of major European equity indices. We find that models based on high-frequency data offer a clear advantage in terms of statistical accuracy. They also yield more theoretically consistent predictions...

This paper tests a traditional model of asset pricing, the CCAPM (Consumption Capital Asset Pricing Model), using data from the Spanish stock market. A generalized calibration method is used to test this model. This method allows us to judge the degree of correspondance between the population...

Implications of factor-based asset pricing models for estimation of expected returns and for portfolio selection are investigated. In the presence of model mispricing due to a missing risk factor, the mispricing and the residual covariance matrix are linked together. Imposing a strong form of...

This paper presents an equilibrium asset pricing model with incomplete information on returns and agents' utility. Only some moments of the returns distributions are observable, and investors associate a return's riskness to the time required for its mean to converge around its expectation,...

This paper deals with applying GIS and spatial statistics to hedonic modeling. More precisely, it looks at spatial autocorrelation and trend surface analysis (TSA) as devices that can be used to improve model performances. Empirical analysis is performed on the Charlesbourg 1986-87 bungalow...

This paper discusses how central banking is evolving in light of recent experience, with particular emphasis on the incorporation of uncertainty into policy decision-making. The sort of post-crisis uncertainty that central banks are dealing with today is more profound than that which is...

In this paper, we focus on the trade and quote data for the IBM stock traded at the NYSE. We present two different framworks for analyzing this dataset. First, using regularly sampled observations, we characterize the intraday volatility of the mid-point of the bid-ask quotes by estimating GARCH...