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Financial Modelling - Essay Example

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Probability of default Name: Institution: Probability of default Banks consider credit risks, a dominant source of risk and hence the banks subject it to strict oversight. Additionally, credit risks remain one of the central topics in financial policy debates…
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Financial Modelling
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This paper models an approach for estimation of the probability of default (PD) using publicly available information. It borrows from past research to develop an analytical approach and explore the provided data sample. Regulators are conventionally not the single constituency of individuals interested in PD estimate properties. Typically, PDs are products of credit asset pricings, from bonds, loans, as well as sophisticated instruments including credit derivatives. These are often needed for successful risk management.

According to (DDDDD), default is however considered a rare event, more particularly, for high credit quality firms which constitute a bulk of huge corporate segment in any of the big banks. However, PDs can systematically vary with business cycle and hence unlike to remain stable over time. In this report, a number of factors are identified, factor which shape or rather act as determinants of probability of default. These include price to book ratio, age of firm, region where firm is located, firm’s sector, debt ratio, and size of the firms.

According to Freedman (2005) regression analysis includes modeling and analysis of variables, with special focus on the relationship between a dependent variable and a set of independent variables. Its helps a researcher establish how the dependent variable is alters when one or more of the dependent variable is varied. . ed in various firm metrics for the period following on the period for which default risk (probability of default) is calculated, and if the Fama and French risk factors, size and price to book ratio, are proxies for default effect.

Vassalou & Xing (2004) looked for an effect of default risk on equity returns, and besides that, tested if the Fama and French factors size and book to market ratio, explain equity returns because they capture a default effect. Their findings reported that the size of a firm and its price to book ratio do not explain equity returns cross-section due to the fact that they contain information that is related to default risk. Additionally, the researchers conclude that high default risk can only be compensated by higher returns in small organizations which have a high price to book ratio.

Population and Sample Selection While a number of factors have been used in the past to evaluate the default risk by firms, the reports limits itself to the probability of default as a measure of risk. Only a few major predictor variables were chosen for these studies investigations. The performance and various growth related indicators of probability of default were compared against each other. The data obtained was drawn from a large base of firms, each of whose the probability of default was related against the selected variables and a pattern proposed.

It is important to emphasize that no causal relationship is assumed but rather the variables are merely used as predictors. The study sample comprised of data from 300 firms, each with known probability of default and a multiple other variables. Sample Selection Given the large number of corporations across the globe, the data obtained was limited to only 300 firms whose full range of data as per the

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