###############################################################################
## TESTING OF THE FUNDAMENTAL-BASED VIEW OF SOVEREIGN DEFAULT RISK ##
## ##
## TEST SPECIFICATIONS OF THE FORM: ##
## ##
## delta(y,{t,t+2}) ~ delta(x, {t-1,t}) | z, year ##
## ##
## - y = {rating, cds, spread}, ##
## ##
## - x={revenue, unanticipated expenditure, financial sector health score, ##
## non-financial sector health score}. ##
## ##
## - z = {debt, rating, income classification, geographical classification} ##
###############################################################################
bench <- getSovBenchmarks()
crisis1 <- loadCrisisDB()
crisis2 <- alternativeCrisisDB()
alt <- getAltmanZscore()
pd <- getAggregatedBankscopePDs()
macro <- createQueriedMacroDataset(test = FALSE)
dt <-
list(
bench,
crisis1,
crisis2,
alt,
pd,
copy(macro)
) %>>% joinDatasetList
dt1[iso3 == 'GRC']
dt2[iso3 == 'GRC'] %>>% (df~qplot(data = df, x=date,y =C_ratingnum_D,geom = 'line'))
## COMPUTE PAIRWISE CORRELATIONS BY DECILES OF Z
undebug(tabulateCorrelationsByGroup)
tabulateCorrelationsByGroup(
data = dt,
group = 'spread',
xvar = c('zscorepd75','SC_CLOSURE_ALL.Q3.'),
xvarConvert = 'shift(lag = +1, dif = TRUE);`*`(-1)',
benchVars = c('cds','ratingnum','spread'),
benchConvert = 'shift(lag = +1, dif = TRUE);`*`(-1)',
method = 'spearman'
)
tabulateCorrelationsByGroup(
data = dt,
group = 'ratingnum',
xvar = c('zscorepd75','SC_CLOSURE_ALL.Q3.'),
xvarConvert = 'shift(lag = -1, dif = TRUE)',
benchVars = c('ratingnum','spread','cds'),
benchConvert = 'shift(lag = +1, dif = TRUE);`*`(-1)',
method = 'pearson'
)
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