different institutional environments. Using a Panel Data version of the Vector Auto Regressive (VAR) methodology, we test for …

This paper presents a scoring model that predicts the risk of drop-out for borrowers at a microfinance lender in … Bolivia. Drop-out risk was greater for women, manufacturers, newer borrowers, and those with more arrears. Out-of-sample tests …) who are at-risk of drop-out. …

Value-at-Risk (VaR) determines the probability of a portfolio of assets losing a certain amount in a given time period … due to adverse market conditions with a particular level of confidence. Value-at-Risk has received considerable attention … from financial economists and financial practitioners for its use in risk reporting, in particular the risks of derivatives …

We measure the loss potential of Hedge Funds by combining three market risk measures: VaR, Draw-Down and Time Under … considering Non-Normality, neglect to model time- dependence. Moreover, VaR is an incomplete measure of market risk whenever the … results clearly state that market risk may be substantially underestimated by those models which assume Normality or, even …

This paper deals with the issue of calculating daily Value-at-Risk (VaR) measures within an environment of thin trading … VaR measures difficult to calculate. We propose and implement a methodology to calculate VaR measures with an incomplete …-structure dynamic model of interest rates. Phase II, calculates portfolio VaR measures with several alternative methods using the …

We propose a fast algorithm for computing the economic capital, Value at Risk and Greeks in the Gaussian factor model …