This article analyses two sudden depreciations of the Canadian dollar in the 1990s: July/August 1998 and November/December 1994. It is found that a nonparametric exchange rate model based on a combination of fundamental and microstructure (order flow) variables can be used not only to explain,...

This paper concentrates on quantifying the behavioral aspects of systemic risk by using a novel approach based on entropy. More specifically, we study aggregate market expectations and the predictability of the systemic risk before and during the financial crisis in 2008. Two underlying signals...

This paper builds a novel multi-criteria, non-parametric classification framework in order to improve the accuracy of pricing European options. The proposed approach is based on classifying financial options according to their implied volatility, time to maturity and moneyness. Using a recent...

We study the risk of informed trading in an electronic foreign exchange market and test whether informed trading is driven by marketwide private information. Our framework is based on a structural microstructure trade model that measures the market makers' beliefs directly. Evidence of high...

This paper tests the theoretical assumption of the foreign exchange market microstructure that dealers and non-dealer customers interact over discrete trading rounds. An exhaustive frequency-domain analysis reveals that the interaction is limited and mainly due to the instability of financial...

We explore the relationship between disaggregated order flow, the Canada/U.S. dollar (CAD/USD) market and U.S. macroeconomic announcements. Three types of CAD order flow and the CAD/USD are cointegrated. Financial order flow appears to contemporaneously drive the CAD/USD while commercial order...

This paper investigates a non-parametric modular neural network (MNN) model to price the S&P-500 European call options. The modules are based on time to maturity and moneyness of the options. The option price function of interest is homogenous of degree one with respect to the underlying index...

This paper develops a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require instruments and yields...

We develop a dynamic framework to identify aggregate market fears ahead of a major market crash through the skewness premium of European options. Our methodology is based on measuring the distribution of a skewness premium through a q-Gaussian density and a maximum entropy principle. Our...