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.

The Effect of Deleting Anchor on the Classification of Examinees

The presence of outlying anchor items is an issue faced by many testing agencies. This study examines the effect of removing or retaining one aberrant anchor item. The degree of aberrancy was manipulated as well as the ability distribution of examinees, and four IRT scaling methods were investigated (Mean-sigma, mean-mean, Stocking & Lord, and Haebara). The results indicate that the percent of correctly classified students was not affected by either retaining or removing the aberrant item, although the over- and under- classification of examinees was. There was no difference among the methods.

The Effect of Broadleaf Canopies on Survey-grade Horizontal GPS/GLONASS Measurements

A study was conducted to empirically determine the degradation of survey-grade GPS horizontal position measurements due to the effects of broadleaf forest canopies. The measurements were taken using GPS/GLONASS-capable receivers measuring C/A and P-codes, and carrier phase. Fourteen survey markers were chosen in central Connecticut to serve as reference markers for the study. These markers had varying degrees of sky obstruction due to overhanging tree canopies. Sky obstruction was measured by photographing the sky with a 35mm reflex camera fitted with a hemispherical lens. The negative was scanned and the image mapped using an equal- area projection to remove the distortion caused by the lens. The resulting digital image was thresholded to produce a black-and-white image in which a count of the black pixels is a measure of sky-area obstruction. The locations of the markers were determined independently before the study. During the study, each marker was occupied for four 20-minute sessions over the period of one week in mid-July, 1999. The location of the study markers produced relatively long baselines, as compared with similar studies. We compared the accuracy of GPS-only vs. GPS&GLONASS as a function of sky obstruction. Based on our results, GLONASS observations did not improve or degrade the accuracy of the position measurements. There is a loss of 2mm of accuracy per percent of sky obstruction for both GPS only and GPS&GLONASS.