search for: riskfreerate

...ing on here , what i can do to fix this.. do i need to smooth each expiration's line then interpolate.... ?? library(RQuantLib) library(quantmod) library(rgl) library(akima) library(ggplot2) library(plyr) GetIV <- function(type, value, underlying, strike,dividendYield, riskFreeRate, maturity, volatility, timeSteps=150, gridPoints=151) { AmericanOptionImpliedVolatility(type, value, underlying, strike,dividendYield, riskFreeRate, maturity, volatility, timeSteps=150, gridPoints=151)$im...

...ssumed that all input parameters are independent of ageing : ######################################################### InputDim <-20 # Max number of ageings in the inputs CPIRate <- rep(0.02 , InputDim ) # CPI inflation rate LossInflaRate <- rep(0.02 , InputDim) # inflation rate of losses RiskFreeRate <- rep(0.04, InputDim ) # vector of risk free rate RiskRate <- rep(0.06, InputDim ) # vector of risk free rate ################   lapse param begin : LapseType <- rep("linear" , InputDim ) # type of the function used to calculate lapse rate= "power", "logistic&quot...

...try and run the EuropeanOption example using atm.work$For_Price as my array of underlying prices and the other inputs from row 9 of atm.work. i<-9; x<-EuropeanOption(type = "put", underlying = atm.work$For_Price, strike = atm.work$K[i], dividendYield = atm.work$BEY[i], riskFreeRate = atm.work$BEY[i], maturity = atm.work$t_exp[i], volatility = atm.work$sigma[i]) x$parameters has the array of underlying prices but the results is only a single vector using the first row of atm.work$For_Price. Is this because I am pulling the inputs from data.frame not arrays? A...

...t;SOCK") registerDoSNOW(cl.tmp) optData.df <- head(pristine,100000) system.time( optData.df$impliedVol <- foreach(i=1:NROW(optData.df),.packages="RQuantLib") %dopar% with(optData.df[i,], tryCatch({EuropeanOptionImpliedVolatility(type,value,underlying, strike, dividendYield, riskFreeRate, maturity, volatility)$impliedVol}, error = function (ex){0})) ) This works fine! PROBLEM: However, when I do the same but with optData.df <- pristine ... which has about 3.8 million options data ... the cores do not seem to be fully utilized (they seem to run at 25%). I noticed some slight...

...function name tailRisk = list() a list params = list(alpha=0.05, a=1, ...) a list portfolio slot a list weights = NULL a numeric vector targetReturn = NULL a numeric value targetRisk = NULL a numeric value riskFreeRate = 0 a numeric value nFrontierPoints = 50 an integer value status = NA) a integer value optim slot a list solver = "solveRquadprog" a function names objective = NULL function names options = list()...

Hello. I don't understand a particular output of portfolio.optim (tseries). I have 4 assets and the portfolio.optim returns an asset with weight equals to zero. If I do a portfolio.optim with 3 assets, without the asset with weight equals to zero, it returns a completely different result. That's I would expected the same weights as the run with 4 assets. Below the code. Thanks in