Package 'AFR'

Breusch-Godfrey test [BG test]

Description

BG test is used to test for autocorrelation in the errors of a regression model

Usage

bg(
  model,
  order = 1,
  order.by = NULL,
  type = c("Chisq", "F"),
  data = list(),
  fill = 0
)

Arguments

model	is a (generalized)linear regression model
order	integer. maximal order of serial correlation to be tested.
order.by	Either a vector z or a formula with a single explanatory variable like ~ z
type	the type of test statistic to be returned
data	an optional data frame containing the variables in the model
fill	starting values for the lagged residuals in the auxiliary regression. By default 0 but can also be set to NA.

References

Mitchel, D. and Zeileis, A. Published 2021-11-07. lmtest package

Examples

model <- lm(real_gdp ~ imp + exp + poil + eurkzt + tonia_rate, data = macroKZ)
bg(model)

---

Breusch-Pagan test

Description

Breusch-Pagan test is used to test against heteroskedasticity of a time-series

Usage

bp(model, varformula = NULL, studentize = TRUE, data = list())

Arguments

model	is a (generalized)linear regression model
varformula	a formula describing only the potential explanatory variables for the variance (no dependent variable needed). By default the same explanatory variables are taken as in the main regression model.
studentize	logical. If set to TRUE Koenker's studentized version of the test statistic will be used.
data	an optional data frame containing the variables in the model

References

Torsten, H., Zeileis, A., Farebrother, Richard W., Cummins, C., Millo, G., Mitchell, D., lmtest package Wang, B., 2014, bstats package

Examples

model <- lm(real_gdp ~ imp + exp + poil + eurkzt + tonia_rate, data = macroKZ)
bp(model)

---

All possible regression variable coefficients.

Description

Returns the coefficients for each variable from each model.

Usage

check_betas(object, ...)

Arguments

object	An object of class lm.
...	Other arguments.

Value

check_betas returns a data.frame containing:

x

model

References

Hebbali, Aravind. Published 2020-02-10. olsrr package

Examples

model <- lm(real_gdp~imp+exp+usdkzt+eurkzt, data = macroKZ)
check_betas(model)

---

Preliminary data check for errors

Description

Preliminary check of data frame for missing values, numeric format, outliers.

Missing items: The number of missing values in each column of the dataset. Numeric format: The number of non-numeric variables in each column of the dataset. Outliers: The number of outliers in each column of the dataset.

Usage

checkdata(x)

Arguments

x	is a data frame

Examples

data(macroKZ)
checkdata(macroKZ)

---

Multicollinearity test

Description

multicollinearity is the occurence of high interrelations among two or more independent variables in a multiple regression.

Usage

corsel(x, thrs, num)

Arguments

x	is a numeric vector or matrix
thrs	threshold set to calculate correlation above
num	logical

Examples

data(macroKZ)
corsel(macroKZ,num=FALSE,thrs=0.65)

---

Decomposition plot

Description

The function depicts decomposition of regressors as a stacked barplot

Usage

dec_plot(model, dataset, print_plot = TRUE)

Arguments

model	An object of class lm.
dataset	A dataset based on which model was built
print_plot	logical

Author(s)

The Agency of the Republic of Kazakhstan for Regulation and Development of Financial Market (AFR)

References

Hebbali, Aravind. Published 2020-02-10. olssr package

Examples

data(macroKZ)
model <- lm(real_gdp ~ usdkzt + eurkzt + imp+exp, data = macroKZ)
dec_plot(model, macroKZ)

---

Transforming time-series data to stationary

Description

Difference of logarithms is finding the difference between two consecutive logarithm values of a time-series

Usage

difflog(x, lag = 1, difference = 1)

Arguments

x	time-series vector
lag	lagged period
difference	difference between x items

Examples

data (macroKZ)
new<-pct1(macroKZ)

---

finratKZ dataset

Description

finratKZ dataset

Usage

finratKZ

Format

Dataset of 400 corporate borrowers, i.e. 200 standard (IFRS stage 1) and 200 default ones, characterized by 29 financial ratios.

Default

Dummy variable where 0 - standard(IFRS stage 1) borrower, 1 - default borrower

Rev_gr

Revenue growth rate

EBITDA_gr

EBITDA growth rate

Cap_gr

Capital growth rate

CR

Current ratio

QR

Quick ratio

Cash_ratio

Cash ratio

WC_cycle

Working capital cycle

DTA

Debt-to-assets

DTE

Debt-to-equity

LR

Leverage ratio (Total assets/Total equity)

EBITDA_debt

EBITDA-to-debt

IC

Interest coverage (Income statement)

CTI

Cash-to-income

IC_CF

Interest coverage (Cash flow statement)

DCR

Debt coverage ratio (Cash flow from operations/Total debt)

CFR

Cash flow to revenue

CRA

Cash return on assets (Cash flow from operations/Total assets)

CRE

Cash return on equity (Cash flow from operations/Total equity)

ROA

Return on assets

ROE

Return on equity

NPM

Net profit margin

GPM

Gross profit margin

OPM

Operating profit margin

RecT

Receivables turnover

InvT

Inventory turnover

PayT

Payables turnover

TA

Total assets turnover

FA

Fixed assets turnover

WC

Working capital turnover

References

The Agency of the Republic of Kazakhstan for Regulation and Development of Financial Market

---

Godfrey-Quandt test

Description

Godfrey-Quandt test is used to test against heteroskedasticity of a time-series

Usage

gq(
  model,
  point = 0.5,
  fraction = 0,
  alternative = c("greater", "two.sided", "less"),
  order.by = NULL,
  data = list()
)

Arguments

model	is a (generalized)linear regression model
point	numerical. If point is smaller than 1 it is interpreted as percentages of data
fraction	numerical. The number of central observations to be omitted.
alternative	a character string specifying the alternative hypothesis.
order.by	Either a vector z or a formula with a single explanatory variable like ~ z
data	an optional data frame containing the variables in the model.

References

Torsten, H., Zeileis, A., Farebrother, Richard W., Cummins, C., Millo, G., Mitchell, D., lmtest package Wang, B., 2014, bstats package

Examples

model <- lm(real_gdp ~ imp + exp + poil + eurkzt + tonia_rate, data = macroKZ)
gq(model)

---

Hodrick-Prescott filter for time series data

Description

Hodrick-Prescott filter is a data smoothing technique that removes trending in time series data frame

Usage

HP(x, freq = NULL, type = c("lambda", "frequency"), drift = FALSE)

Arguments

x	time-series vector
freq	integer
type	character, indicating the filter type
drift	logical

Examples

data(macroKZ)
HP(macroKZ[,2])

---

macroKZ dataset

Description

macroKZ dataset

Usage

macroKZ

Format

A time series data frame of 57 quarterly observations of 50 macroeconomic and 10 financial parameters for 2010-2024 period.

real_gdp

Real GDP

GDD_Agr_R

Real gross value added Agriculture

GDD_Min_R

Real gross value added Mining

GDD_Min_R

Real gross value added Mining

GDD_Man_R

Real gross value added Manufacture

GDD_Elc_R

Real gross value added Electricity

GDD_Con_R

Real gross value added Construction

GDD_Trd_R

Real gross value added Trade

GDD_Trn_R

Real gross value added Transportation

GDD_Inf_R

Real gross value added Information

GDD_R

Real gross value added

GDP_DEF

GDP deflator

Rincpop_q

Real population average monthly income

Rexppop_q

Real population average monthly expenses

Rwage_q

Real population average monthly wage

imp

Import

exp

Export

cpi

Inflation

realest_resed_prim

Real price for estate in primary market

realest_resed_sec

Real price for estate in secondary market

realest_comm

Real price for commercial estate

index_stock_weighted

Change in stock value for traded companies

ntrade_Agr

Change in stock value for non-traded companies Agriculture

ntrade_Min

Change in stock value for non-traded companies Mining

ntrade_Man

Change in stock value for non-traded companies Manufacture

ntrade_Elc

Change in stock value for non-traded companies Electricity

ntrade_Con

Change in stock value for non-traded companies Construction

ntrade_Trd

Change in stock value for non-traded companies Trade

ntrade_Trn

Change in stock value for non-traded companies Transportation

ntrade_Inf

Change in stock value for non-traded companies Information

fed_fund_rate

Federal Funds Rate

govsec_rate_kzt_3m

Return on government securities in KZT, 3 m

govsec_rate_kzt_1y

Return on government securities in KZT, 1 year

govsec_rate_kzt_7y

Return on government securities in KZT, 7 years

govsec_rate_kzt_10y

Return on government securities in KZT, 10 years

tonia_rate

TONIA

rate_kzt_mort_0y_1y

Weighted average mortgage lending rate for new loans, less than a year

rate_kzt_mort_1y_iy

Weighted average mortgage lending rate for new loans, more than a year

rate_kzt_corp_0y_1y

Weighted average mortgage lending rate for new loans to non-financial organizations in KZT, less than a year

rate_usd_corp_0y_1y

Weighted average mortgage lending rate for new loans to non-financial organizations in CKB, less than a year

rate_kzt_corp_1y_iy

Weighted average mortgage lending rate for new loans to non-financial organizations in KZT, more than a year

rate_usd_corp_1y_iy

Weighted average mortgage lending rate for new loans to non-financial organizations in CKB, more than a year

rate_kzt_indv_0y_1y

Weighted average mortgage lending rate for consumer loans in KZT, less than a year

rate_kzt_indv_1y_iy

Weighted average mortgage lending rate for consumer loans in KZT, less than a year

usdkzt

USD KZT exchange rate

eurkzt

EUR KZT exchange rate

rurkzt

RUB KZT exchange rate

poil

Price for Brent

realest_resed_prim_rus

Real price for estate in primary market in Russia

realest_resed_sec_rus

Real price for estate in secondary market in Russia

cred_portfolio

credit portfolio

coef_liq_k4

k4 prudential coefficient

coef_k1

k1 prudential coefficient

coef_k3

k3 prudential coefficient

provisions

provisions

percent_margin

percent margin

com_inc

commissionary income

com_exp

commissionary expenses

oper_inc

operational income

oth_inc

other income

DR

default rate

Source

Bureau of National statistics, Agency for Strategic planning and reforms of the Republic of Kazakhstan

References

The Agency of the Republic of Kazakhstan for Regulation and Development of Financial Market

---

Test for normality Test for detecting violation of normality assumption.

Description

Test for normality Test for detecting violation of normality assumption.

Usage

ols_test_normality(model, ...)

Arguments

model	an object of class lm.
...	Other arguments.

Value

ols_test_normality is a list containing the following components:

kolmogorv	kolmogorov smirnov statistic
shapiro	shapiro wilk statistic
cramer	cramer von mises statistic
anderson	anderson darling statistic

Examples

data(macroKZ)
model <- lm(real_gdp ~ imp + exp + usdkzt + poil, data = macroKZ)
ols_test_normality(model)

---

Necessary size of the time-series dataset

Description

Estimates number of models generated from given number of regressors X

Usage

opt_size(model)

Arguments

model

is a linear regression model a class lm.

Examples

data(macroKZ)
model <- lm(real_gdp ~ imp + exp + poil + eurkzt + tonia_rate, data = macroKZ)
opt_size(model)

---

Transforming time-series data to stationary

Description

Percent change is a change between two consecutive terms,

Usage

pct1(x)

Arguments

x	time-series vector(s)

Examples

data (macroKZ)
new<-pct1(macroKZ)

---

Transforming time-series data to stationary

Description

Percent change is a change between a term and its lagged value for prior period,

Usage

pct4(x)

Arguments

x	time-series vector(s)

Examples

data (macroKZ)
new<-pct4(macroKZ)

---

Pluto-Tasche method for multi-year probability of default (PD) analysis

Description

Calculates the variation inflation factors of all predictors in regression models

Usage

pt_multi(pf, num_def, conf_level, num_years)

Arguments

pf	unconditional portfolio distribution from the worst to the best credit quality
num_def	number of defaults in a given rating class
conf_level	confidence interval of PD estimates
num_years	number of periods used in the PD estimation

Examples

pf <- c(10,20,30,40)
num_def <- c(1,2,3,4)
conf_level = 0.99
num_years = 3
pt_multi(pf, num_def, conf_level, num_years)

---

Pluto-Tasche method for one-year probability of default (PD) analysis

Description

Calculates probability of default according to One-period Pluto and Tasche model

Usage

pt_one(pf, num_def, ci = 0.9)

Arguments

pf	unconditional portfolio distribution from the worst to the best credit quality
num_def	number of defaults in a given rating class
ci	condifence interval of PD estimates

References

Surzhko, Denis. Published 2015-05-21. LDPD package. Archived on 2022-06-20.

Examples

pf <- c(10,20,30,40)
num_def <- c(1,2,3,4)
pt_one(pf, num_def, ci= 0.9)

---

Regression forecast plot

Description

The function depicts forecast and actual data.

Usage

reg_plot(model, dataset)

Arguments

model	An object of class lm.
dataset	A dataset based on which model was built.

Author(s)

The Agency of the Republic of Kazakhstan for Regulation and Development of Financial Market (AFR)

Examples

data(macroKZ)
model <- lm(real_gdp ~ usdkzt + eurkzt + imp + exp, data = macroKZ)
reg_plot(model, macroKZ)

---

Test for detecting violation of Gauss-Markov assumptions.

Description

Test for detecting violation of Gauss-Markov assumptions.

Usage

reg_test(y)

Arguments

y	A numeric vector or an object of class lm.

Value

reg_test returns an object of class "reg_test". An object of class "reg_test" is a list containing the following components:

bp	Breusch-Pagan statistic
bg	Breusch-Godfrey statistic
dw	Durbin-Watson statistic
gq	Godfrey-Quandt statistic

Examples

data(macroKZ)
model <- lm(real_gdp~ imp + exp + poil + eurkzt + usdkzt, macroKZ)
reg_test(model)

---

Regressors selection

Description

The function allows to choose regressors based on multiple criteria as AIC, RMSE etc

Usage

regsel_f(
  model,
  pval = 0.3,
  metric = "adjr" & "aic",
  progress = FALSE,
  details = FALSE,
  ...
)

Arguments

model	is a linear regression model
pval	p value; variables with p value less than pval will enter into the model
metric	statistical metrics used to estimate the best model
progress	Logical; if TRUE, will display variable selection progress.
details	Logical; if TRUE, will print the regression result at each step.
...	other arguments

References

Hebbali, Aravind. Published 2020-02-10. olssr package

Examples

data(macroKZ)
model <- lm(real_gdp ~ imp + exp + poil + eurkzt + tonia_rate, data = macroKZ)
regsel_f(model)

---

VIF by variable

Description

Calculates the variation inflation factors of all predictors in regression models

Usage

vif_reg(model)

Arguments

model

is a linear regression model

References

Petrie, Adam. Published 2020-02-21. regclass package

Examples

data(macroKZ)
model <- lm(real_gdp ~ imp + exp + poil + eurkzt + tonia_rate, data = macroKZ)
vif_reg(model)

---