A heuristic approach to assessing default risk in debt repayment of retail exposures is a rather straightforward debt sustainability ratio. Read on as a HTML independent file.
Rodolfo Vanzini
Making sense of economics
Blog Archives
Gauging credit losses
Loss rates on loans are explained by a number of drivers that for a single loan can be summarized as read it as an independent html file (with R code).
Gambling on bad loans
View it as an independent HTML file with R code. Quotes in gambling are driven by the probability of an outcome to occur and in a football match like Premier League’s Arsenal vs. Chelsea on Saturday, January 19th 2019 —at the time of writing this short essay about gambling on bad loans—
Assorbimenti patrimoniali e peggioramento delle condizioni economiche nel credito
L’aumento degli assorbimenti patrimoniali in uno scenario di peggioramento delle condizioni economiche Rodolfo Vanzini 1 giugno 2018 La regolamentazione sul rischio di credito richiede che le banche nel cosiddetto approccio standard detengano patrimonio di vigilanza in ragione della quantità e della qualità del credito erogato associando ogni esposizione creditizia ad
Credit selection with FFTrees in R
Alberi decisionali fast-and-frugal e credit selection con il modello Unico (draft version) Rodolfo Vanzini 4 febbraio 2018 Introduzione La selezione delle imprese a cui riconoscere affidabilità creditizia, da parte di un intermediario finanziario come una banca, è essenzialmente riconducibile – dal punto di vista metodologico – ad un esercizio di
Predicting duration before credit default of borrowers based on loan-installment-to-income ratio
This post is a short demonstration of a simple regression analysis based on a mock data set (dat) that consists of loan-installment-to-income ratios of 28 borrowers (LIIR) and the number of months before default (Months). I want to revise the basic steps for regression analysis in R and would like to show practitioners
16 years of volatility on the S&P 500
Lately, I was wondering how serious volatility has gotten so far and so decided to update my hall of volatility on the S&P 500. Check the following chart (drawn along a GARCH-estimated-1-day-99% VaR) In case you wonder, at 99% probability only 1% “exceedance” is theoretically expected (using the normal distribution
R code risk classification procedures: a tutorial
Fans of risk classification procedures will find this draft containing a basic – though A-to-Z complete – tutorial on how to use R for credit management useful at worst. This preliminary version of a fully fledged publication (article or book is still to be determined) contains all the relevant R
