6 resultados para Model risk
em University of Connecticut - USA
Resumo:
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.
Resumo:
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.
Resumo:
The effects of exchange rate risk have interested researchers, since the collapse of fixed exchange rates. Little consensus exists, however, regarding its effect on exports. Previous studies implicitly assume symmetry. This paper tests the hypothesis of asymmetric effects of exchange rate risk with a dynamic conditional correlation bivariate GARCH(1,1)-M model. The asymmetry means that exchange rate risk (volatility) affects exports differently during appreciations and depreciations of the exchange rate. The data include bilateral exports from eight Asian countries to the US. The empirical results show that real exchange rate risk significantly affects exports for all countries, negative or positive, in periods of depreciation or appreciation. For five of the eight countries, the effects of exchange risk are asymmetric. Thus, policy makers can consider the stability of the exchange rate in addition to its depreciation as a method of stimulating export growth.
Resumo:
The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.
Resumo:
This paper develops a reduced form three-factor model which includes a liquidity proxy of market conditions which is then used to provide implicit prices. The model prices are then compared with observed market prices of credit default swaps to determine if swap rates adequately reflect market risks. The findings of the analysis illustrate the importance of liquidity in the valuation process. Moreover, market liquidity, a measure of investors. willingness to commit resources in the credit default swap (CDS) market, was also found to improve the valuation of investors. autonomous credit risk. Thus a failure to include a liquidity proxy could underestimate the implied autonomous credit risk. Autonomous credit risk is defined as the fractional credit risk which does not vary with changes in market risk and liquidity conditions.
Resumo:
Credit-rationing model similar to Stiglitz and Weiss [1981] is combined with the information externality model of Lang and Nakamura [1993] to examine the properties of mortgage markets characterized by both adverse selection and information externalities. In a credit-rationing model, additional information increases lenders ability to distinguish risks, which leads to increased supply of credit. According to Lang and Nakamura, larger supply of credit leads to additional market activities and therefore, greater information. The combination of these two propositions leads to a general equilibrium model. This paper describes properties of this general equilibrium model. The paper provides another sufficient condition in which credit rationing falls with information. In that, external information improves the accuracy of equity-risk assessments of properties, which reduces credit rationing. Contrary to intuition, this increased accuracy raises the mortgage interest rate. This allows clarifying the trade offs associated with reduced credit rationing and the quality of applicant pool.