Stonkalysis: Stonk Valuation

#EBITDA = Net income + Tax + Interest + Depreciation & Amortization
#EBIT = Net income + Tax + Interest
#Operating Cash Flow = Net income + Depreciation & Amortization + Non-cash items (Stock-based compensation, unrealized gain/loss, write-downs) - changes in net working capital
#Free Cash Flow = Operating Cash Flow - Capital Expenditures
#Free Cash Flow to Equity = Operating Cash Flow - Capital Expenditures + Net Debt Issued
#Free Cash Flow to Firm = EBIT - Tax + Depreciation & Amortization - Increase in non-working capital - Capex


#Make the equations adjustable in case the data is wrong.

#TODO
#EBITDA
#Cash Flow
#Free Cash Flow
#Free Cash Flow to Equity
#Unleveraged Free CashF low (this is also free cash flow to firm?)
#Leveraged Discounted Cash Flow
#Unleveraged Discounted Cash Flow
#Dividend Discount Model
#Weighted Average Cost of Capital (This is sometimes used as the discount rate?)
#API for ten year yield from teasury 
#API for GDP see WDI


#update per minute while running
#getQuote <- function(ticker) {
#	URL <- paste(quote_call, "&symbol=", ticker, "&apikey=", apikey, sep="")
#	results <- fromJSON(file = URL)
#	return(results)
#}

#calculates the effective tax rates over 5 years
#getEffectiveTax <- function(income) {
#	IBT <- income[[1]]$incomeBeforeTax
#	ITE <- income[[1]]$incomeTaxExpense
#	rates <- ITE / IBT
#	return(rates)
#}

#metrics from profile
#earnings-per-share
#EPS <- function(df) {
#	return(df[[1]]$EPS)
#}

#price-to-earnings
#PE_ratio <- function(df) {
#	return(df[[1]]$PERatio)
#}

#price-earnings-to-growth
#PEG_ratio <- function(df) {
#	return(df[[1]]$PEGRatio)
#}

#Operating Margin TTM
#Operating_Margin <- function(df) {
#	return(df[[1]]$OperatingMarginTTM)
#}

#price-to-sales TTM
#PS_ratio <- function(df) {
#	return(df[[1]]$PriceToSalesRatioTTM)
#}

#price-to-book
#PB_ratio <- function() {
#	return(df[[1]]$PriceToBookRatio)
#}

#beta 
#Beta <- function(df) {
#	return(df[[1]]$Beta)
#}

#EV/EBITDA
#EV_EBITDA <- function(df) {
#	return(df[[1]]$EVToEBITDA)
#}
#metrics from profile

##company to company valuation metrics
#provide correlations between the historical data between two companies



#quote_daily <- getQuote(ticker)

#getEBITDA <- function(df) {
#	nt <- df[[5]][[1]]$netIncome
#	ie <- df[[5]][[1]]$interestExpense
#	it <- df[[5]][[1]]$incomeTaxExpense
#	de <- df[[7]][[1]]$depreciation
#	return(nt + ie + it + de)
#}

#getEBIT <- function(df) {
#	nt <- df[[5]][[1]]$netIncome
#	ie <- df[[5]][[1]]$interestExpense
#	it <- df[[5]][[1]]$incomeTaxExpense
#	return(nt + ie + it)

#}

#totalDebt <- function(df) {
#	df[[5]][[2]]$shortTermDebt
#	df[[5]][[2]]$longTermDebt
#	df[[5]][[2]]$capitalLeaseObligations
	

#	df[[5]]
#}

#getCashFlow <- function(df) {
#	return(df[[7]][[1]]$operatingCashflow)
#}

#getFreeCashFlow <- function(df) {
#	return(getCashFlow(df) - df[[7]][[1]]$cashflowFromInvestment)
#}

#getFreeCashFlowtoEquity <- function(df) {
#	getFreeCashFlow(df) + 
#}

#getUnleveredFreeCashFlow <- function(df) [

#}

#getDCF <- function() {

#}

#getDDM <- function() {

#}

#getWACC <- function() {

#}

#getGDP <- function() {
	#see https://cran.r-project.org/web/packages/WDI/WDI.pdf
#}

#getTenYearYield <- function() {
	#see https://www.business-science.io/finance/2020/02/21/tidy-discounted-cash-flow.html
#}

#price-to-cash-flow
#PtCF_ratio <- function() {

#}

#DtE_ratio <- function() {

#}

#Working_Capital <- function() {

#}

#Inventory_Turnover_ration <- function() {

#}