Behavioral Implications of Knockout for the Dyslexia-Risk Gene Dcdc2 in Mice

Several genetic linkage and epidemiological studies have provided strong evidence that DCDC2 is a candidate gene for developmental dyslexia, a disorder that impairs a person’s reading ability despite adequate intelligence, education, and socio-economic status. Studies investigating embryonic intra-ventricular RNA interference (RNAi) of Dcdc2, a rat homolog of the DCDC2 gene in humans, indicate disruptions in neuronal migration in the rat cortex during development. Interestingly, these anatomical anomalies are consistent with post mortem histological analysis of human dyslexic patients. Other rodent models of cortical developmental disruption have shown impairment in rapid auditory processing and learning maze tasks in affected subjects. The current study investigates the rapid auditory processing abilities of mice heterozygous for Dcdc2 (one functioning Dcdc2 allele) and mice with a homozygous knockout of Dcdc2 (no functioning Dcdc2 allele). It is important to note that this genetic model for behavioral assessment is still in the pilot stage. However, preliminary results suggest that mice with a genetic mutation of Dcdc2 have impaired rapid auditory processing, as well as non-spatial maze learning and memory ability, as compared to wildtypes. By genetically knocking out Dcdc2 in mice, behavioral features associated with Dcdc2 can be characterized, along with other neurological abnormalities that may arise due to the loss of the functioning gene.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.