Asymmetric Smiles, Leverage Effects and Structural Parameters.

In this paper, we characterize the asymmetries of the smile through multiple leverage effects in a stochastic dynamic asset pricing framework. The dependence between price movements and future volatility is introduced through a set of latent state variables. These latent variables can capture not only the volatility risk and the interest rate risk which potentially affect option prices, but also any kind of correlation risk and jump risk. The standard financial leverage effect is produced by a cross-correlation effect between the state variables which enter into the stochastic volatility process of the stock price and the stock price process itself. However, we provide a more general framework where asymmetric implied volatility curves result from any source of instantaneous correlation between the state variables and either the return on the stock or the stochastic discount factor. In order to draw the shapes of the implied volatility curves generated by a model with latent variables, we specify an equilibrium-based stochastic discount factor with time non-separable preferences. When we calibrate this model to empirically reasonable values of the parameters, we are able to reproduce the various types of implied volatility curves inferred from option market data.

GLS Detrending, Efficient Unit Root Tests and Structural Change

We extend the class of M-tests for a unit root analyzed by Perron and Ng (1996) and Ng and Perron (1997) to the case where a change in the trend function is allowed to occur at an unknown time. These tests M(GLS) adopt the GLS detrending approach of Dufour and King (1991) and Elliott, Rothenberg and Stock (1996) (ERS). Following Perron (1989), we consider two models : one allowing for a change in slope and the other for both a change in intercept and slope. We derive the asymptotic distribution of the tests as well as that of the feasible point optimal tests PT(GLS) suggested by ERS. The asymptotic critical values of the tests are tabulated. Also, we compute the non-centrality parameter used for the local GLS detrending that permits the tests to have 50% asymptotic power at that value. We show that the M(GLS) and PT(GLS) tests have an asymptotic power function close to the power envelope. An extensive simulation study analyzes the size and power in finite samples under various methods to select the truncation lag for the autoregressive spectral density estimator. An empirical application is also provided.

The role of porcine reproductive and respiratory syndrome (PRRS) virus structural and non-structural proteins in virus pathogenesis.

Porcine reproductive and respiratory syndrome (PRRS) is an economically devastating viral disease affecting the swine industry worldwide. The etiological agent, PRRS virus (PRRSV), possesses a RNA viral genome with nine open reading frames (ORFs). The ORF1a and ORF1b replicase-associated genes encode the polyproteins pp1a and pp1ab, respectively. The pp1a is processed in nine non-structural proteins (nsps): nsp1a, nsp1b, and nsp2 to nsp8. Proteolytic cleavage of pp1ab generates products nsp9 to nsp12. The proteolytic pp1a cleavage products process and cleave pp1a and pp1ab into nsp products. The nsp9 to nsp12 are involved in virus genome transcription and replication. The 30 end of the viral genome encodes four minor and three major structural proteins. The GP2a, GP3 and GP4 (encoded by ORF2a, 3 and 4), are glycosylated membrane associated minor structural proteins. The fourth minor structural protein, the E protein (encoded by ORF2b), is an unglycosylated membrane associated protein. The viral envelope contains two major structural proteins: a glycosylated major envelope protein GP5 (encoded by ORF5) and an unglycosylated membrane M protein (encoded by ORF6). The third major structural protein is the nucleocapsid N protein (encoded by ORF7). All PRRSV non-structural and structural proteins are essential for virus replication, and PRRSV infectivity is relatively intolerant to subtle changes within the structural proteins. PRRSV virulence is multigenic and resides in both the non-structural and structural viral proteins. This review discusses the molecular characteristics, biological and immunological functions of the PRRSV structural and nsps and their involvement in the virus pathogenesis.