, Khanh Nguyen [aut]
(2009-2010), Terry Leitch [aut] (since 2016)| Title: | R Interface to the 'QuantLib' Library |
|---|---|
| Description: | The 'RQuantLib' package makes parts of 'QuantLib' accessible from R The 'QuantLib' project aims to provide a comprehensive software framework for quantitative finance. The goal is to provide a standard open source library for quantitative analysis, modeling, trading, and risk management of financial assets. |
| Authors: | Dirk Eddelbuettel [aut, cre]
, Khanh Nguyen [aut]
(2009-2010), Terry Leitch [aut] (since 2016) |
| Maintainer: | Dirk Eddelbuettel <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.4.24 |
| Built: | 2024-10-30 06:50:46 UTC |
| Source: | CRAN |
AffineSwaption prices a swaption with specified
strike and maturity (in years), after calibrating the selected
affine short-rate model to an input swaption volatility matrix. Swaption
maturities are in years down the rows, and swap tenors are in years
along the columns, in the usual fashion. It is assumed that the
swaption is
exercisable at the start of the swap if params$european flag is set to TRUE or
on each reset date (Bermudan) of the underlying swap if params$european flag is
set to FALSE.
AffineSwaption(params, ts, swaptionMaturities, swapTenors, volMatrix,legparams)AffineSwaption(params, ts, swaptionMaturities, swapTenors, volMatrix,legparams)
params |
A list specifying the
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ts |
A term structure built with DiscountCurve is required. See the
help page for |
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swaptionMaturities |
A vector containing the swaption maturities associated with the rows of the swaption volatility matrix. |
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swapTenors |
A vector containing the underlying swap tenors associated with the columns of the swaption volatility matrix. |
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volMatrix |
The swaption volatility matrix. Must be a 2D matrix stored by rows. See the example below. |
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legparams |
A list specifying the |
This function is based on QuantLib Version 0.3.10. It
introduces support for fixed-income instruments in RQuantLib.
At present only a small number of the many parameters that can be set
in QuantLib are exposed by this function. Some of the
hard-coded parameters that apply to the current version include:
day-count conventions, fixing days (2), index (Euribor),
fixed leg frequency (annual), and floating leg frequency
(semi-annual). Also, it is assumed that the swaption
volatility matrix corresponds to expiration dates and tenors that are
measured in years (a 6-month expiration date is not currently
supported, for example).
Given the number of parameters that must be specified and the care with which they must be specified (with no defaults), it is not practical to use this function in the usual interactive fashion.
The simplest approach is simply to save the
example below to a file, edit as desired, and source the result.
Alternatively, the input commands can be kept in a script file
(under Windows) or an Emacs/ESS session (under Linux), and selected
parts of the script can be executed in the usual way.
Fortunately, the C++ exception mechanism seems to work well with the R
interface, and QuantLib exceptions are propagated back to the
R user, usually with a message that indicates what went wrong. (The
first part of the message contains technical information about the
precise location of the problem in the QuantLib code. Scroll to
the end to find information that is meaningful to the R user.)
AffineSwaption returns a list containing calibrated model
paramters (what parameters are returned depends on the model
selected) along with:
NPV |
NPV of swaption in basis points (actual price
equals |
ATMStrike |
At-the-money strike |
params |
Input parameter list |
Terry Leitch
Brigo, D. and Mercurio, F. (2001) Interest Rate Models: Theory and Practice, Springer-Verlag, New York.
For information about QuantLib see https://www.quantlib.org/.
For information about RQuantLib see
http://dirk.eddelbuettel.com/code/rquantlib.html.
if (.Platform$OS.type != "windows" && .Platform$r_arch != "i386") { ## Not run: # This data was generated to match the original quantlib example for Bermudan Swaption params <- list(tradeDate=as.Date('2016-2-15'), settleDate=as.Date('2016-2-17'), startDate=as.Date('2017-2-17'), maturity=as.Date('2022-2-17'), payFixed=TRUE, european=FALSE, dt=.25, strike=.06, method="G2Analytic", interpWhat="discount", interpHow="loglinear") # Market data used to construct the term structure of interest rates tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) # Swaption volatility matrix with corresponding maturities and tenors swaptionMaturities <- c(1,2,3,4,5) swapTenors <- c(1,2,3,4,5) volMatrix <- matrix( c(0.1490, 0.1340, 0.1228, 0.1189, 0.1148, 0.1290, 0.1201, 0.1146, 0.1108, 0.1040, 0.1149, 0.1112, 0.1070, 0.1010, 0.0957, 0.1047, 0.1021, 0.0980, 0.0951, 0.1270, 0.1000, 0.0950, 0.0900, 0.1230, 0.1160), ncol=5, byrow=TRUE) legparams=list(dayCounter="Thirty360", fixFreq="Annual", floatFreq="Semiannual") setEvaluationDate(as.Date("2016-2-16")) times<-times <- seq(0,14.75,.25) dcurve <- DiscountCurve(params, tsQuotes, times=times,legparams) # Price the Bermudan swaption pricing <- AffineSwaption(params, dcurve,swaptionMaturities, swapTenors, volMatrix,legparams) summary(pricing) ## End(Not run) }if (.Platform$OS.type != "windows" && .Platform$r_arch != "i386") { ## Not run: # This data was generated to match the original quantlib example for Bermudan Swaption params <- list(tradeDate=as.Date('2016-2-15'), settleDate=as.Date('2016-2-17'), startDate=as.Date('2017-2-17'), maturity=as.Date('2022-2-17'), payFixed=TRUE, european=FALSE, dt=.25, strike=.06, method="G2Analytic", interpWhat="discount", interpHow="loglinear") # Market data used to construct the term structure of interest rates tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) # Swaption volatility matrix with corresponding maturities and tenors swaptionMaturities <- c(1,2,3,4,5) swapTenors <- c(1,2,3,4,5) volMatrix <- matrix( c(0.1490, 0.1340, 0.1228, 0.1189, 0.1148, 0.1290, 0.1201, 0.1146, 0.1108, 0.1040, 0.1149, 0.1112, 0.1070, 0.1010, 0.0957, 0.1047, 0.1021, 0.0980, 0.0951, 0.1270, 0.1000, 0.0950, 0.0900, 0.1230, 0.1160), ncol=5, byrow=TRUE) legparams=list(dayCounter="Thirty360", fixFreq="Annual", floatFreq="Semiannual") setEvaluationDate(as.Date("2016-2-16")) times<-times <- seq(0,14.75,.25) dcurve <- DiscountCurve(params, tsQuotes, times=times,legparams) # Price the Bermudan swaption pricing <- AffineSwaption(params, dcurve,swaptionMaturities, swapTenors, volMatrix,legparams) summary(pricing) ## End(Not run) }
This function evaluations an American-style option on a common stock using finite differences. The option value as well as the common first derivatives ("Greeks") are returned.
## Default S3 method: AmericanOption(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, timeSteps=150, gridPoints=149, engine="BaroneAdesiWhaley", discreteDividends, discreteDividendsTimeUntil)## Default S3 method: AmericanOption(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, timeSteps=150, gridPoints=149, engine="BaroneAdesiWhaley", discreteDividends, discreteDividendsTimeUntil)
type |
A string with one of the values |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Volatility of the underlying stock |
timeSteps |
Time steps for the “CrankNicolson” finite differences method engine, default value is 150 |
gridPoints |
Grid points for the “CrankNicolson” finite differences method, default value is 149 |
engine |
String selecting pricing engine, currently supported are “BaroneAdesiWhaley” and “CrankNicolson” |
discreteDividends |
Vector of discrete dividends (optional) |
discreteDividendsTimeUntil |
Vector of times to discrete dividends (in fractional years, optional) |
The Finite Differences method is used to value the American Option.
Please see any decent Finance textbook for background reading, and
the QuantLib documentation for details on the QuantLib
implementation.
An object of class AmericanOption (which inherits from class
Option) is returned. It contains a list with the
following components:
value |
Value of option |
delta |
Sensitivity of the option value for a change in the underlying |
gamma |
Sensitivity of the option delta for a change in the underlying |
vega |
Sensitivity of the option value for a change in the underlying's volatility |
theta |
Sensitivity of the option value for a change in t, the remaining time to maturity |
rho |
Sensitivity of the option value for a change in the risk-free interest rate |
dividendRho |
Sensitivity of the option value for a change in the dividend yield |
Note that under the new pricing framework used in QuantLib, pricers do not provide analytics for all 'Greeks'. When “CrankNicolson” is selected, then at least delta, gamma and vega are available. With the default pricing engine of “BaroneAdesiWhaley”, no greeks are returned.
The “CrankNicolson” engine needs to be used when setting discrete dividends.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
# simple call with unnamed parameters AmericanOption("call", 100, 100, 0.02, 0.03, 0.5, 0.4) # simple call with some explicit parameters AmericanOption("put", strike=100, volatility=0.4, 100, 0.02, 0.03, 0.5) # simple call with unnamed parameters, using Crank-Nicolons AmericanOption("put", strike=100, volatility=0.4, 100, 0.02, 0.03, 0.5, engine="CrankNicolson")# simple call with unnamed parameters AmericanOption("call", 100, 100, 0.02, 0.03, 0.5, 0.4) # simple call with some explicit parameters AmericanOption("put", strike=100, volatility=0.4, 100, 0.02, 0.03, 0.5) # simple call with unnamed parameters, using Crank-Nicolons AmericanOption("put", strike=100, volatility=0.4, 100, 0.02, 0.03, 0.5, engine="CrankNicolson")
The AmericanOptionImpliedVolatility function solves for the
(unobservable) implied volatility, given an option price as well as
the other required parameters to value an option.
## Default S3 method: AmericanOptionImpliedVolatility(type, value, underlying, strike,dividendYield, riskFreeRate, maturity, volatility, timeSteps=150, gridPoints=151)## Default S3 method: AmericanOptionImpliedVolatility(type, value, underlying, strike,dividendYield, riskFreeRate, maturity, volatility, timeSteps=150, gridPoints=151)
type |
A string with one of the values |
value |
Value of the option (used only for ImpliedVolatility calculation) |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Initial guess for the volatility of the underlying stock |
timeSteps |
Time steps for the Finite Differences method, default value is 150 |
gridPoints |
Grid points for the Finite Differences method, default value is 151 |
The Finite Differences method is used to value the American Option. Implied volatilities are then calculated numerically.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The AmericanOptionImpliedVolatility function returns an numeric
variable with volatility implied by the given market prices and given parameters.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
EuropeanOption,AmericanOption,BinaryOption
AmericanOptionImpliedVolatility(type="call", value=11.10, underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.5, volatility=0.4)AmericanOptionImpliedVolatility(type="call", value=11.10, underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.5, volatility=0.4)
The AsianOption function evaluates an Asian-style
option on a common stock using an analytic solution for continuous
geometric average price. The option value, the common first
derivatives ("Greeks") as well as the calling parameters are returned.
## Default S3 method: AsianOption(averageType, type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, first=0, length=11.0/12.0, fixings=26)## Default S3 method: AsianOption(averageType, type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, first=0, length=11.0/12.0, fixings=26)
averageType |
Specifiy averaging type, either “geometric” or “arithmetic” |
type |
A string with one of the values |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Volatility of the underlying stock |
first |
(Only for arithmetic averaging) Time step to first average, can be zero |
length |
(Only for arithmetic averaging) Total time length for averaging period |
fixings |
(Only for arithmetic averaging) Total number of averaging fixings |
When "arithmetic" evaluation is used, only the NPV() is returned.
The well-known closed-form solution derived by Black, Scholes and Merton is used for valuation. Implied volatilities are calculated numerically.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The AsianOption function returns an object of class
AsianOption (which inherits from class
Option). It contains a list with the following
components:
value |
Value of option |
delta |
Sensitivity of the option value for a change in the underlying |
gamma |
Sensitivity of the option delta for a change in the underlying |
vega |
Sensitivity of the option value for a change in the underlying's volatility |
theta |
Sensitivity of the option value for a change in t, the remaining time to maturity |
rho |
Sensitivity of the option value for a change in the risk-free interest rate |
dividendRho |
Sensitivity of the option value for a change in the dividend yield |
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
# simple call with some explicit parameters, and slightly increased vol: AsianOption("geometric", "put", underlying=80, strike=85, div=-0.03, riskFree=0.05, maturity=0.25, vol=0.2)# simple call with some explicit parameters, and slightly increased vol: AsianOption("geometric", "put", underlying=80, strike=85, div=-0.03, riskFree=0.05, maturity=0.25, vol=0.2)
This function evaluations an Barrier option on a common stock using a closed-form solution. The option value as well as the common first derivatives ("Greeks") are returned.
## Default S3 method: BarrierOption(barrType, type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, barrier, rebate=0.0)## Default S3 method: BarrierOption(barrType, type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, barrier, rebate=0.0)
barrType |
A string with one of the values |
type |
A string with one of the values |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Volatility of the underlying stock |
barrier |
Option barrier value |
rebate |
Optional option rebate, defaults to 0.0 |
A closed-form solution is used to value the Barrier Option. In the case of Barrier options, the calculations are from Haug's "Option pricing formulas" book (McGraw-Hill).
Please see any decent Finance textbook for background reading, and
the QuantLib documentation for details on the QuantLib
implementation.
An object of class BarrierOption (which inherits from class
Option) is returned. It contains a list with the
following components:
value |
Value of option |
delta |
Sensitivity of the option value for a change in the underlying |
gamma |
Sensitivity of the option delta for a change in the underlying |
vega |
Sensitivity of the option value for a change in the underlying's volatility |
theta |
Sensitivity of the option value for a change in t, the remaining time to maturity |
rho |
Sensitivity of the option value for a change in the risk-free interest rate |
dividendRho |
Sensitivity of the option value for a change in the dividend yield |
.
Note that under the new pricing framework used in QuantLib, binary pricers do not provide analytics for 'Greeks'. This is expected to be addressed in future releases of QuantLib.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
BarrierOption(barrType="downin", type="call", underlying=100, strike=100, dividendYield=0.02, riskFreeRate=0.03, maturity=0.5, volatility=0.4, barrier=90)BarrierOption(barrType="downin", type="call", underlying=100, strike=100, dividendYield=0.02, riskFreeRate=0.03, maturity=0.5, volatility=0.4, barrier=90)
BermudanSwaption prices a Bermudan swaption with specified
strike and maturity (in years), after calibrating the selected
short-rate model to an input swaption volatility matrix. Swaption
maturities are in years down the rows, and swap tenors are in years
along the columns, in the usual fashion. It is assumed that the
Bermudan swaption is
exercisable on each reset date of the underlying swaps.
BermudanSwaption(params, ts, swaptionMaturities, swapTenors, volMatrix)BermudanSwaption(params, ts, swaptionMaturities, swapTenors, volMatrix)
params |
A list specifying the
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ts |
A term structure built with DiscounCurve or market observables
needed to construct the spot term
structure of interest rates. A list of name/value pairs. See the
help page for |
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swaptionMaturities |
A vector containing the swaption maturities associated with the rows of the swaption volatility matrix. |
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swapTenors |
A vector containing the underlying swap tenors associated with the columns of the swaption volatility matrix. |
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volMatrix |
The swaption volatility matrix. Must be a 2D matrix stored by rows. See the example below. |
This function was update for QuantLib Version 1.7.1 or later. It
introduces support for fixed-income instruments in RQuantLib. It implements the
full function and should work in most cases as long as there are suuficient swaption vol
data points to fit the affine model. At least 5 unique points are required. The data point
search attempts to find 5 or more points with one being the closet match in terms in of
expiration and maturity.
See the SabrSwaption function for an alternative.
BermudanSwaption , if there are sufficient swaption vols to fit an affine model,
returns a list containing calibrated model
paramters (what parameters are returned depends on the model
selected) along with:
price |
Price of swaption in basis points (actual price
equals |
ATMStrike |
At-the-money strike |
params |
Input parameter list |
If there are insufficient swaption vols to calibrate it throws a warning and returns NULL
Dominick Samperi
Brigo, D. and Mercurio, F. (2001) Interest Rate Models: Theory and Practice, Springer-Verlag, New York.
For information about QuantLib see https://www.quantlib.org/.
For information about RQuantLib see
http://dirk.eddelbuettel.com/code/rquantlib.html.
## Not run: # This data replicates sample code shipped with QuantLib 0.3.10 results params <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-19'), startDate=as.Date('2003-2-19'), maturity=as.Date('2008-2-19'), dt=.25, payFixed=TRUE, strike=.05, method="G2Analytic", interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date('2002-2-15')) # Market data used to construct the term structure of interest rates tsQuotes <- list(d1w =0.05, # d1m =0.0372, # fut1=96.2875, # fut2=96.7875, # fut3=96.9875, # fut4=96.6875, # fut5=96.4875, # fut6=96.3875, # fut7=96.2875, # fut8=96.0875, s3y =0.05, s5y =0.05, s10y =0.05, s15y =0.05) times=seq(0,14.75,.25) swcurve=DiscountCurve(params,tsQuotes,times) # Use this to compare with the Bermudan swaption example from QuantLib #tsQuotes <- list(flat=0.04875825) # Swaption volatility matrix with corresponding maturities and tenors swaptionMaturities <- c(1,2,3,4,5) swapTenors <- c(1,2,3,4,5) volMatrix <- matrix( c(0.1490, 0.1340, 0.1228, 0.1189, 0.1148, 0.1290, 0.1201, 0.1146, 0.1108, 0.1040, 0.1149, 0.1112, 0.1070, 0.1010, 0.0957, 0.1047, 0.1021, 0.0980, 0.0951, 0.1270, 0.1000, 0.0950, 0.0900, 0.1230, 0.1160), ncol=5, byrow=TRUE) volMatrix <- matrix( c(rep(.20,25)), ncol=5, byrow=TRUE) # Price the Bermudan swaption pricing <- BermudanSwaption(params, ts=.05, swaptionMaturities, swapTenors, volMatrix) summary(pricing) ## End(Not run)## Not run: # This data replicates sample code shipped with QuantLib 0.3.10 results params <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-19'), startDate=as.Date('2003-2-19'), maturity=as.Date('2008-2-19'), dt=.25, payFixed=TRUE, strike=.05, method="G2Analytic", interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date('2002-2-15')) # Market data used to construct the term structure of interest rates tsQuotes <- list(d1w =0.05, # d1m =0.0372, # fut1=96.2875, # fut2=96.7875, # fut3=96.9875, # fut4=96.6875, # fut5=96.4875, # fut6=96.3875, # fut7=96.2875, # fut8=96.0875, s3y =0.05, s5y =0.05, s10y =0.05, s15y =0.05) times=seq(0,14.75,.25) swcurve=DiscountCurve(params,tsQuotes,times) # Use this to compare with the Bermudan swaption example from QuantLib #tsQuotes <- list(flat=0.04875825) # Swaption volatility matrix with corresponding maturities and tenors swaptionMaturities <- c(1,2,3,4,5) swapTenors <- c(1,2,3,4,5) volMatrix <- matrix( c(0.1490, 0.1340, 0.1228, 0.1189, 0.1148, 0.1290, 0.1201, 0.1146, 0.1108, 0.1040, 0.1149, 0.1112, 0.1070, 0.1010, 0.0957, 0.1047, 0.1021, 0.0980, 0.0951, 0.1270, 0.1000, 0.0950, 0.0900, 0.1230, 0.1160), ncol=5, byrow=TRUE) volMatrix <- matrix( c(rep(.20,25)), ncol=5, byrow=TRUE) # Price the Bermudan swaption pricing <- BermudanSwaption(params, ts=.05, swaptionMaturities, swapTenors, volMatrix) summary(pricing) ## End(Not run)
This function evaluations an Binary option on a common stock using a closed-form solution. The option value as well as the common first derivatives ("Greeks") are returned.
## Default S3 method: BinaryOption(binType, type, excType, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, cashPayoff)## Default S3 method: BinaryOption(binType, type, excType, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, cashPayoff)
binType |
A string with one of the values |
type |
A string with one of the values |
excType |
A string with one of the values |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Volatility of the underlying stock |
cashPayoff |
Payout amount |
A closed-form solution is used to value the Binary Option.
Please see any decent Finance textbook for background reading, and
the QuantLib documentation for details on the QuantLib
implementation.
An object of class BinaryOption (which inherits from class
Option) is returned. It contains a list with the
following components:
value |
Value of option |
delta |
Sensitivity of the option value for a change in the underlying |
gamma |
Sensitivity of the option delta for a change in the underlying |
vega |
Sensitivity of the option value for a change in the underlying's volatility |
theta |
Sensitivity of the option value for a change in t, the remaining time to maturity |
rho |
Sensitivity of the option value for a change in the risk-free interest rate |
dividendRho |
Sensitivity of the option value for a change in the dividend yield |
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
BinaryOption(binType="asset", type="call", excType="european", underlying=100, strike=100, dividendYield=0.02, riskFreeRate=0.03, maturity=0.5, volatility=0.4, cashPayoff=10)BinaryOption(binType="asset", type="call", excType="european", underlying=100, strike=100, dividendYield=0.02, riskFreeRate=0.03, maturity=0.5, volatility=0.4, cashPayoff=10)
The BinaryOptionImpliedVolatility function solves for the
(unobservable) implied volatility, given an option price as well as
the other required parameters to value an option.
## Default S3 method: BinaryOptionImpliedVolatility(type, value, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, cashPayoff=1)## Default S3 method: BinaryOptionImpliedVolatility(type, value, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, cashPayoff=1)
type |
A string with one of the values |
value |
Value of the option (used only for ImpliedVolatility calculation) |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Initial guess for the volatility of the underlying stock |
cashPayoff |
Binary payout if options is exercised, default is 1 |
The Finite Differences method is used to value the Binary Option. Implied volatilities are then calculated numerically.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The BinaryOptionImpliedVolatility function returns an numeric
variable with volatility implied by the given market prices.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
EuropeanOption,AmericanOption,BinaryOption
BinaryOptionImpliedVolatility("call", value=4.50, strike=100, 100, 0.02, 0.03, 0.5, 0.4, 10)BinaryOptionImpliedVolatility("call", value=4.50, strike=100, 100, 0.02, 0.03, 0.5, 0.4, 10)
This class forms the basis from which the more specific classes are derived.
## S3 method for class 'Bond' print(x, digits=5, ...) ## S3 method for class 'FixedRateBond' print(x, digits=5, ...) ## S3 method for class 'Bond' plot(x, ...) ## S3 method for class 'Bond' summary(object, digits=5, ...)## S3 method for class 'Bond' print(x, digits=5, ...) ## S3 method for class 'FixedRateBond' print(x, digits=5, ...) ## S3 method for class 'Bond' plot(x, ...) ## S3 method for class 'Bond' summary(object, digits=5, ...)
x |
Any Bond object derived from this base class |
object |
Any Bond object derived from this base class |
digits |
Number of digits of precision shown |
... |
Further arguments |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
None, but side effects of displaying content.
The interface might change in future release as QuantLib
stabilises its own API.
Khanh Nguyen [email protected]; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
## Not run: ## This data is taken from sample code shipped with QuantLib 0.9.7 ## from the file Examples/Swap/swapvaluation params <- list(tradeDate=as.Date('2004-09-20'), settleDate=as.Date('2004-09-22'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-09-20")) ## We got numerical issues for the spline interpolation if we add ## any on of these three extra futures, at least with QuantLib 0.9.7 ## The curve data comes from QuantLib's Examples/Swap/swapvaluation.cpp ## Removing s2y helps, as kindly pointed out by Luigi Ballabio tsQuotes <- list(d1w = 0.0382, d1m = 0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, # s2y = 0.037125, ## s2y perturbs s3y = 0.0398, s5y = 0.0443, s10y = 0.05165, s15y = 0.055175) times <- seq(0,10,.1) setEvaluationDate(params$tradeDate) discountCurve <- DiscountCurve(params, tsQuotes, times) # price a zero coupon bond bondparams <- list(faceAmount=100, issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100 ) dateparams <-list(settlementDays=1, calendar="UnitedStates/GovernmentBond", businessDayConvention=4) ZeroCouponBond(bondparams, discountCurve, dateparams) # price a fixed rate coupon bond bond <- list(settlementDays=1, issueDate=as.Date("2004-11-30"), faceAmount=100, dayCounter='Thirty360', paymentConvention='Unadjusted') schedule <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), period='Semiannual', calendar='UnitedStates/GovernmentBond', businessDayConvention='Unadjusted', terminationDateConvention='Unadjusted', dateGeneration='Forward', endOfMonth=1) calc=list(dayCounter='Actual360', compounding='Compounded', freq='Annual', durationType='Modified') rates <- c(0.02875) FixedRateBond(bond, rates, schedule, calc, discountCurve=discountCurve) # price a fixed rate coupon bond from yield yield <- 0.050517 FixedRateBond(bond, rates, schedule, calc, yield=yield) # calculate the same bond from the clean price price <- 92.167 FixedRateBond(bond, rates, schedule, calc, price=price) # price a floating rate bond bondparams <- list(faceAmount=100, issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100, effectiveDate=as.Date("2004-12-01")) dateparams <- list(settlementDays=1, calendar="UnitedStates/GovernmentBond", dayCounter = 1, period=3, businessDayConvention = 1, terminationDateConvention=1, dateGeneration=0, endOfMonth=0, fixingDays = 1) gearings <- spreads <- caps <- floors <- vector() iborCurve <- DiscountCurve(params,list(flat=0.05), times) ibor <- list(type="USDLibor", length=6, inTermOf="Month", term=iborCurve) FloatingRateBond(bondparams, gearings, spreads, caps, floors, ibor, discountCurve, dateparams) ## End(Not run)## Not run: ## This data is taken from sample code shipped with QuantLib 0.9.7 ## from the file Examples/Swap/swapvaluation params <- list(tradeDate=as.Date('2004-09-20'), settleDate=as.Date('2004-09-22'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-09-20")) ## We got numerical issues for the spline interpolation if we add ## any on of these three extra futures, at least with QuantLib 0.9.7 ## The curve data comes from QuantLib's Examples/Swap/swapvaluation.cpp ## Removing s2y helps, as kindly pointed out by Luigi Ballabio tsQuotes <- list(d1w = 0.0382, d1m = 0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, # s2y = 0.037125, ## s2y perturbs s3y = 0.0398, s5y = 0.0443, s10y = 0.05165, s15y = 0.055175) times <- seq(0,10,.1) setEvaluationDate(params$tradeDate) discountCurve <- DiscountCurve(params, tsQuotes, times) # price a zero coupon bond bondparams <- list(faceAmount=100, issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100 ) dateparams <-list(settlementDays=1, calendar="UnitedStates/GovernmentBond", businessDayConvention=4) ZeroCouponBond(bondparams, discountCurve, dateparams) # price a fixed rate coupon bond bond <- list(settlementDays=1, issueDate=as.Date("2004-11-30"), faceAmount=100, dayCounter='Thirty360', paymentConvention='Unadjusted') schedule <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), period='Semiannual', calendar='UnitedStates/GovernmentBond', businessDayConvention='Unadjusted', terminationDateConvention='Unadjusted', dateGeneration='Forward', endOfMonth=1) calc=list(dayCounter='Actual360', compounding='Compounded', freq='Annual', durationType='Modified') rates <- c(0.02875) FixedRateBond(bond, rates, schedule, calc, discountCurve=discountCurve) # price a fixed rate coupon bond from yield yield <- 0.050517 FixedRateBond(bond, rates, schedule, calc, yield=yield) # calculate the same bond from the clean price price <- 92.167 FixedRateBond(bond, rates, schedule, calc, price=price) # price a floating rate bond bondparams <- list(faceAmount=100, issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100, effectiveDate=as.Date("2004-12-01")) dateparams <- list(settlementDays=1, calendar="UnitedStates/GovernmentBond", dayCounter = 1, period=3, businessDayConvention = 1, terminationDateConvention=1, dateGeneration=0, endOfMonth=0, fixingDays = 1) gearings <- spreads <- caps <- floors <- vector() iborCurve <- DiscountCurve(params,list(flat=0.05), times) ibor <- list(type="USDLibor", length=6, inTermOf="Month", term=iborCurve) FloatingRateBond(bondparams, gearings, spreads, caps, floors, ibor, discountCurve, dateparams) ## End(Not run)
These functions are using internally to convert from the characters at
the R level to the enum types used at the C++ level. They are
documented here mostly to provide a means to look up some of the
possible values—the user is not expected to call these functions directly..
matchBDC(bdc = c("Following", "ModifiedFollowing", "Preceding", "ModifiedPreceding", "Unadjusted", "HalfMonthModifiedFollowing", "Nearest")) matchCompounding(cp = c("Simple", "Compounded", "Continuous", "SimpleThenCompounded")) matchDayCounter(daycounter = c("Actual360", "ActualFixed", "ActualActual", "Business252", "OneDayCounter", "SimpleDayCounter", "Thirty360", "Actual365NoLeap", "ActualActual.ISMA", "ActualActual.Bond", "ActualActual.ISDA", "ActualActual.Historical", "ActualActual.AFB", "ActualActual.Euro")) matchDateGen(dg = c("Backward", "Forward", "Zero", "ThirdWednesday", "Twentieth", "TwentiethIMM", "OldCDS", "CDS")) matchFrequency(freq = c("NoFrequency","Once", "Annual", "Semiannual", "EveryFourthMonth", "Quarterly", "Bimonthly", "Monthly", "EveryFourthWeek", "Biweekly", "Weekly", "Daily")) matchParams(params)matchBDC(bdc = c("Following", "ModifiedFollowing", "Preceding", "ModifiedPreceding", "Unadjusted", "HalfMonthModifiedFollowing", "Nearest")) matchCompounding(cp = c("Simple", "Compounded", "Continuous", "SimpleThenCompounded")) matchDayCounter(daycounter = c("Actual360", "ActualFixed", "ActualActual", "Business252", "OneDayCounter", "SimpleDayCounter", "Thirty360", "Actual365NoLeap", "ActualActual.ISMA", "ActualActual.Bond", "ActualActual.ISDA", "ActualActual.Historical", "ActualActual.AFB", "ActualActual.Euro")) matchDateGen(dg = c("Backward", "Forward", "Zero", "ThirdWednesday", "Twentieth", "TwentiethIMM", "OldCDS", "CDS")) matchFrequency(freq = c("NoFrequency","Once", "Annual", "Semiannual", "EveryFourthMonth", "Quarterly", "Bimonthly", "Monthly", "EveryFourthWeek", "Biweekly", "Weekly", "Daily")) matchParams(params)
bdc |
A string identifying one of the possible business day convention values. |
cp |
A string identifying one of the possible compounding frequency values. |
daycounter |
A string identifying one of the possible day counter scheme values. |
dg |
A string identifying one of the possible date generation scheme values. |
freq |
A string identifying one of the possible (dividend) frequency values. |
params |
A named vector containing the other parameters as components. |
The QuantLib documentation should be consulted for details.
Note that Actual365NoLeap is soft deprecated as of QuantLib 1.11 and hard deprecated as of
QuantLib 1.16. For users on QuantLib 1.16 or later, use of the RQuantLib daycounter enum with a
value of severn will result in Actual365Fixed(Actual365Fixed::NoLeap) which is functionally
equivalent to Actual365NoLeap. Previously RQuantLib allowed users to retain
Actual365NoLeap via defining RQUANTLIB_USE_ACTUAL365NOLEAP, but this is no longer
required.
Also note that ActualActual without explicit convention specification is hard deprecated
as of QuantLib 1.23. This is only soft-deprecated in RQuantLib by explicitly passing in the same
default convention. Previously RQuantLib allowed users to define
RQUANTLIB_USE_ACTUALACTUAL, but this is no longer required.
Each function converts the given character value into a corresponding
numeric entry. For matchParams, an named vector of strings is
converted into a named vector of numerics..
The interface might change in future release as QuantLib
stabilises its own API.
Khanh Nguyen [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
The isBusinessDay function evaluates the given dates in the context
of the given calendar, and returns a vector of booleans indicating
business day status. BusinessDay is also
recognised (but may be deprecated one day).
The isHoliday function evaluates the given dates in the context
of the given calendar, and returns a vector of booleans indicating
holiday day status.
The isWeekend function evaluates the given dates in the context
of the given calendar, and returns a vector of booleans indicating
weekend status.
The isEndOfMonth function evaluates the given dates in the context
of the given calendar, and returns a vector of booleans indicating
end of month status.
The getEndOfMonth function evaluates the given dates in the context
of the given calendar, and returns a vector that corresponds to the end
of month. endOfMonth is a deprecated form for this function.
The getHolidayList function returns the holidays between the
given dates, with an option to exclude weekends. holidayList is
a deprecated form for this function. Similarly,
getBusinessDayList and, for symmetry, businessDayList
return the list of business days; this always excludes weekends.
The adjust function evaluates the given dates in the context
of the given calendar, and returns a vector that adjusts each input
dates to the appropriate near business day with respect to the given convention.
The advance function evaluates the given dates in the context
of the given calendar, and returns a vector that advances the given
dates of the given number of business days and returns the result.
This functions gets called either with both argument n and
timeUnit, or with argument period.
The businessDaysBetween function evaluates two given dates in the context
of the given calendar, and returns a vector that gives the number of
business day between.
The dayCount function returns the number of day between two dates
given a day counter, see Enum.
The yearFraction function returns year fraction between two dates
given a day counter, see Enum.
The setCalendarContext function sets three values to a singleton
instance at the C++ layer.
The setEvaluationDate function sets the evaluation date used by
the QuantLib pricing engines.
The advanceDate function advances the given date by the given
number of days in the current calendar instance.
The addHolidays and removeHolidays add (and remove)
holidays to (from) the given calendar. Note that this change is
transitory and does not persist the session as all actual calendar
information comes from the QuantLib library that this package is linked
against.
The calendars vector contains all calendar identifiers.
isBusinessDay(calendar, dates) businessDay(calendar="TARGET", dates=Sys.Date()) # deprecated form isHoliday(calendar, dates) isWeekend(calendar, dates) isEndOfMonth(calendar, dates) getEndOfMonth(calendar, dates) endOfMonth(calendar="TARGET", dates=Sys.Date()) getHolidayList(calendar, from, to, includeWeekends=FALSE) holidayList(calendar="TARGET", from=Sys.Date(), to = Sys.Date() + 5, includeWeekends=FALSE) getBusinessDayList(calendar, from, to) businessDayList(calendar="TARGET", from=Sys.Date(), to = Sys.Date() + 5) adjust(calendar, dates, bdc = 0L) advance(calendar="TARGET", dates=Sys.Date(), n, timeUnit, period, bdc = 0, emr =0) businessDaysBetween(calendar, from, to, includeFirst = TRUE, includeLast = FALSE) dayCount(startDates, endDates, dayCounters) yearFraction(startDates, endDates, dayCounters) setCalendarContext(calendar, fixingDays, settleDate) setEvaluationDate(evalDate) addHolidays(calendar, dates) removeHolidays(calendar, dates)isBusinessDay(calendar, dates) businessDay(calendar="TARGET", dates=Sys.Date()) # deprecated form isHoliday(calendar, dates) isWeekend(calendar, dates) isEndOfMonth(calendar, dates) getEndOfMonth(calendar, dates) endOfMonth(calendar="TARGET", dates=Sys.Date()) getHolidayList(calendar, from, to, includeWeekends=FALSE) holidayList(calendar="TARGET", from=Sys.Date(), to = Sys.Date() + 5, includeWeekends=FALSE) getBusinessDayList(calendar, from, to) businessDayList(calendar="TARGET", from=Sys.Date(), to = Sys.Date() + 5) adjust(calendar, dates, bdc = 0L) advance(calendar="TARGET", dates=Sys.Date(), n, timeUnit, period, bdc = 0, emr =0) businessDaysBetween(calendar, from, to, includeFirst = TRUE, includeLast = FALSE) dayCount(startDates, endDates, dayCounters) yearFraction(startDates, endDates, dayCounters) setCalendarContext(calendar, fixingDays, settleDate) setEvaluationDate(evalDate) addHolidays(calendar, dates) removeHolidays(calendar, dates)
calendar |
A string identifying one of the supported QuantLib calendars, see Details for more |
dates |
A vector (or scalar) of |
from |
A vector (or scalar) of |
to |
A vector (or scalar) of |
includeWeekends |
boolean that indicates whether the calculation should include the weekends. Default = false |
fixingDays |
An integer for the fixing day period, defaults to 2. |
settleDate |
A date on which trades settles, defaults to two days after the current day. |
n |
an integer number |
timeUnit |
A value of 0,1,2,3 that corresponds to Days, Weeks, Months, and Year; for more detail, see the QuantLib documentation at https://www.quantlib.org//reference/group__datetime.html |
period |
See Enum |
bdc |
Business day convention. By default, this value is 0 and correspond to Following convention |
emr |
End Of Month rule, default is false |
includeFirst |
boolean that indicates whether the calculation should include the first day. Default = true |
includeLast |
Default = false |
startDates |
A vector of |
endDates |
A vector of |
dayCounters |
A vector of numeric type. See Enum |
evalDate |
A single date used for the pricing valuations. |
The calendars are coming from QuantLib, and the QuantLib documentation should be consulted for details.
Currently, the following strings are recognised: TARGET (a default calendar), Argentina, Australia, Brazil, Canada and Canada/Settlement, Canada/TSX, China, CzechRepublic, Denmark, Finland, Germany and Germany/FrankfurtStockExchange, Germany/Settlement, Germany/Xetra, Germany/Eurex, HongKong, Hungary, Iceland, India, Indonesia, Italy and Italy/Settlement, Italy/Exchange, Japan, Mexico, NewZealand, Norway, Poland, Russia, SaudiArabia, Singapore, Slovakia, SouthAfrica, SouthKorea, SouthKorea/KRX, Sweden, Switzerland, Taiwan, Turkey, Ukraine, UnitedKingdom and UnitedKingdom/Settlement, UnitedKingdom/Exchange, UnitedKingdom/Metals, UnitedStates and UnitedStates/Settlement, UnitedStates/NYSE, UnitedStates/GovernmentBond, UnitedStates/NERC and WeekendsOnly.
(In case of multiples entries per country, the country default is listed right after the country itself. Using the shorter form is equivalent.)
A named vector of booleans each of which is true if the corresponding date is a business day (or holiday or weekend) in the given calendar. The element names are the dates (formatted as text in yyyy-mm-dd format).
For setCalendarContext, a boolean or NULL in case of error.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
dates <- seq(from=as.Date("2009-04-07"), to=as.Date("2009-04-14"), by=1) isBusinessDay("UnitedStates", dates) isBusinessDay("UnitedStates/Settlement", dates) ## same as previous isBusinessDay("UnitedStates/NYSE", dates) ## stocks isBusinessDay("UnitedStates/GovernmentBond", dates) ## bonds isBusinessDay("UnitedStates/NERC", dates) ## energy isHoliday("UnitedStates", dates) isHoliday("UnitedStates/Settlement", dates) ## same as previous isHoliday("UnitedStates/NYSE", dates) ## stocks isHoliday("UnitedStates/GovernmentBond", dates) ## bonds isHoliday("UnitedStates/NERC", dates) ## energy isWeekend("UnitedStates", dates) isWeekend("UnitedStates/Settlement", dates) ## same as previous isWeekend("UnitedStates/NYSE", dates) ## stocks isWeekend("UnitedStates/GovernmentBond", dates) ## bonds isWeekend("UnitedStates/NERC", dates) ## energy isEndOfMonth("UnitedStates", dates) isEndOfMonth("UnitedStates/Settlement", dates) ## same as previous isEndOfMonth("UnitedStates/NYSE", dates) ## stocks isEndOfMonth("UnitedStates/GovernmentBond", dates) ## bonds isEndOfMonth("UnitedStates/NERC", dates) ## energy getEndOfMonth("UnitedStates", dates) getEndOfMonth("UnitedStates/Settlement", dates) ## same as previous getEndOfMonth("UnitedStates/NYSE", dates) ## stocks getEndOfMonth("UnitedStates/GovernmentBond", dates) ## bonds getEndOfMonth("UnitedStates/NERC", dates) ## energy from <- as.Date("2009-04-07") to<-as.Date("2009-04-14") getHolidayList("UnitedStates", from, to) to <- as.Date("2009-10-7") getHolidayList("UnitedStates", from, to) dates <- seq(from=as.Date("2009-04-07"), to=as.Date("2009-04-14"), by=1) adjust("UnitedStates", dates) adjust("UnitedStates/Settlement", dates) ## same as previous adjust("UnitedStates/NYSE", dates) ## stocks adjust("UnitedStates/GovernmentBond", dates) ## bonds adjust("UnitedStates/NERC", dates) ## energy advance("UnitedStates", dates, 10, 0) advance("UnitedStates/Settlement", dates, 10, 1) ## same as previous advance("UnitedStates/NYSE", dates, 10, 2) ## stocks advance("UnitedStates/GovernmentBond", dates, 10, 3) ## bonds advance("UnitedStates/NERC", dates, period = 3) ## energy from <- as.Date("2009-04-07") to<-as.Date("2009-04-14") businessDaysBetween("UnitedStates", from, to) startDates <- seq(from=as.Date("2009-04-07"), to=as.Date("2009-04-14"),by=1) endDates <- seq(from=as.Date("2009-11-07"), to=as.Date("2009-11-14"), by=1) dayCounters <- c(0,1,2,3,4,5,6,1) dayCount(startDates, endDates, dayCounters) yearFraction(startDates, endDates, dayCounters) head(calendars, 10)dates <- seq(from=as.Date("2009-04-07"), to=as.Date("2009-04-14"), by=1) isBusinessDay("UnitedStates", dates) isBusinessDay("UnitedStates/Settlement", dates) ## same as previous isBusinessDay("UnitedStates/NYSE", dates) ## stocks isBusinessDay("UnitedStates/GovernmentBond", dates) ## bonds isBusinessDay("UnitedStates/NERC", dates) ## energy isHoliday("UnitedStates", dates) isHoliday("UnitedStates/Settlement", dates) ## same as previous isHoliday("UnitedStates/NYSE", dates) ## stocks isHoliday("UnitedStates/GovernmentBond", dates) ## bonds isHoliday("UnitedStates/NERC", dates) ## energy isWeekend("UnitedStates", dates) isWeekend("UnitedStates/Settlement", dates) ## same as previous isWeekend("UnitedStates/NYSE", dates) ## stocks isWeekend("UnitedStates/GovernmentBond", dates) ## bonds isWeekend("UnitedStates/NERC", dates) ## energy isEndOfMonth("UnitedStates", dates) isEndOfMonth("UnitedStates/Settlement", dates) ## same as previous isEndOfMonth("UnitedStates/NYSE", dates) ## stocks isEndOfMonth("UnitedStates/GovernmentBond", dates) ## bonds isEndOfMonth("UnitedStates/NERC", dates) ## energy getEndOfMonth("UnitedStates", dates) getEndOfMonth("UnitedStates/Settlement", dates) ## same as previous getEndOfMonth("UnitedStates/NYSE", dates) ## stocks getEndOfMonth("UnitedStates/GovernmentBond", dates) ## bonds getEndOfMonth("UnitedStates/NERC", dates) ## energy from <- as.Date("2009-04-07") to<-as.Date("2009-04-14") getHolidayList("UnitedStates", from, to) to <- as.Date("2009-10-7") getHolidayList("UnitedStates", from, to) dates <- seq(from=as.Date("2009-04-07"), to=as.Date("2009-04-14"), by=1) adjust("UnitedStates", dates) adjust("UnitedStates/Settlement", dates) ## same as previous adjust("UnitedStates/NYSE", dates) ## stocks adjust("UnitedStates/GovernmentBond", dates) ## bonds adjust("UnitedStates/NERC", dates) ## energy advance("UnitedStates", dates, 10, 0) advance("UnitedStates/Settlement", dates, 10, 1) ## same as previous advance("UnitedStates/NYSE", dates, 10, 2) ## stocks advance("UnitedStates/GovernmentBond", dates, 10, 3) ## bonds advance("UnitedStates/NERC", dates, period = 3) ## energy from <- as.Date("2009-04-07") to<-as.Date("2009-04-14") businessDaysBetween("UnitedStates", from, to) startDates <- seq(from=as.Date("2009-04-07"), to=as.Date("2009-04-14"),by=1) endDates <- seq(from=as.Date("2009-11-07"), to=as.Date("2009-11-14"), by=1) dayCounters <- c(0,1,2,3,4,5,6,1) dayCount(startDates, endDates, dayCounters) yearFraction(startDates, endDates, dayCounters) head(calendars, 10)
The CallableBond function sets up and evaluates a callable fixed rate bond using Hull-White model
and a TreeCallableFixedBondEngine pricing engine. For more detail, see the source codes in quantlib's example folder, Examples/CallableBond/CallableBond.cpp
## Default S3 method: CallableBond(bondparams, hullWhite, coupon, dateparams)## Default S3 method: CallableBond(bondparams, hullWhite, coupon, dateparams)
bondparams |
a named list whose elements are:
|
|||||||||||||||||||||||||||||||||||||
hullWhite |
a named list whose elements are parameters needed to set up a HullWhite pricing engine in QuantLib:
Currently, the codes only support a flat rate yield term structure. For more detail, see QuantLib's doc on HullWhite and TreeCallableFixedBondEngine. |
|||||||||||||||||||||||||||||||||||||
coupon |
a numeric vector of coupon rates |
|||||||||||||||||||||||||||||||||||||
dateparams |
(Optional) a named list, QuantLib's date parameters of the bond.
See example below. |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The CallableBond function returns an object of class
CallableBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
price price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
cashFlows |
cash flows of the bond |
The interface might change in future release as QuantLib
stabilises its own API.
Khanh Nguyen [email protected] for the inplementation; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
if (interactive()) { # the example is too computationally expensive for normal checks #set-up a HullWhite according to example from QuantLib HullWhite <- list(term = 0.055, alpha = 0.03, sigma = 0.01, gridIntervals = 40) #callability schedule dataframe Price <- rep(as.double(100),24) Type <- rep(as.character("C"), 24) Date <- seq(as.Date("2006-09-15"), by = '3 months', length = 24) callSch <- data.frame(Price, Type, Date) callSch$Type <- as.character(callSch$Type) bondparams <- list(faceAmount=100, issueDate = as.Date("2004-09-16"), maturityDate=as.Date("2012-09-16"), redemption=100, callSch = callSch) dateparams <- list(settlementDays=3, calendar="UnitedStates/GovernmentBond", dayCounter = "ActualActual", period="Quarterly", businessDayConvention = "Unadjusted", terminationDateConvention= "Unadjusted") coupon <- c(0.0465) setEvaluationDate(as.Date("2004-11-22")) CallableBond(bondparams, HullWhite, coupon, dateparams) #examples using default values CallableBond(bondparams, HullWhite, coupon) dateparams <- list(period="Quarterly", businessDayConvention = "Unadjusted", terminationDateConvention= "Unadjusted") CallableBond(bondparams, HullWhite, coupon, dateparams) bondparams <- list(issueDate = as.Date("2004-09-16"), maturityDate=as.Date("2012-09-16")) CallableBond(bondparams, HullWhite, coupon, dateparams) }if (interactive()) { # the example is too computationally expensive for normal checks #set-up a HullWhite according to example from QuantLib HullWhite <- list(term = 0.055, alpha = 0.03, sigma = 0.01, gridIntervals = 40) #callability schedule dataframe Price <- rep(as.double(100),24) Type <- rep(as.character("C"), 24) Date <- seq(as.Date("2006-09-15"), by = '3 months', length = 24) callSch <- data.frame(Price, Type, Date) callSch$Type <- as.character(callSch$Type) bondparams <- list(faceAmount=100, issueDate = as.Date("2004-09-16"), maturityDate=as.Date("2012-09-16"), redemption=100, callSch = callSch) dateparams <- list(settlementDays=3, calendar="UnitedStates/GovernmentBond", dayCounter = "ActualActual", period="Quarterly", businessDayConvention = "Unadjusted", terminationDateConvention= "Unadjusted") coupon <- c(0.0465) setEvaluationDate(as.Date("2004-11-22")) CallableBond(bondparams, HullWhite, coupon, dateparams) #examples using default values CallableBond(bondparams, HullWhite, coupon) dateparams <- list(period="Quarterly", businessDayConvention = "Unadjusted", terminationDateConvention= "Unadjusted") CallableBond(bondparams, HullWhite, coupon, dateparams) bondparams <- list(issueDate = as.Date("2004-09-16"), maturityDate=as.Date("2012-09-16")) CallableBond(bondparams, HullWhite, coupon, dateparams) }
The ConvertibleFixedCouponBond function setups and evaluates a
ConvertibleFixedCouponBond using QuantLib's BinomialConvertibleEngine
and BlackScholesMertonProcess
The NPV, clean price, dirty price, accrued interest, yield and cash flows of
the bond is returned. For detail, see test-suite/convertiblebond.cpp
The ConvertibleFloatingCouponBond function setups and evaluates a
ConvertibleFixedCouponBond using QuantLib's BinomialConvertibleEngine
and BlackScholesMertonProcess
The NPV, clean price, dirty price, accrued interest, yield and cash flows of
the bond is returned. For detail, see test-suite/convertiblebond.cpp
The ConvertibleZeroCouponBond function setups and evaluates a
ConvertibleFixedCouponBond using QuantLib's BinomialConvertibleEngine
and BlackScholesMertonProcess
The NPV, clean price, dirty price, accrued interest, yield and cash flows of
the bond is returned. For detail, see test-suite/convertiblebond.cpp.
## Default S3 method: ConvertibleFloatingCouponBond(bondparams, iborindex, spread, process, dateparams) ## Default S3 method: ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) ## Default S3 method: ConvertibleZeroCouponBond(bondparams, process, dateparams)## Default S3 method: ConvertibleFloatingCouponBond(bondparams, iborindex, spread, process, dateparams) ## Default S3 method: ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) ## Default S3 method: ConvertibleZeroCouponBond(bondparams, process, dateparams)
bondparams |
bond parameters, a named list whose elements are:
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iborindex |
a DiscountCurve object, represents an IborIndex |
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spread |
a double vector, represents paramter 'spreads' in ConvertibleFloatingBond's constructor. |
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coupon |
a double vector of coupon rate |
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process |
arguments to construct a BlackScholes process and set up the binomial pricing engine for this bond.
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dateparams |
(Optional) a named list, QuantLib's date parameters of the bond.
See the examples below. |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The ConvertibleFloatingCouponBond function returns an object of class
ConvertibleFloatingCouponBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
price price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
cashFlows |
cash flows of the bond |
The ConvertibleFixedCouponBond function returns an object of class
ConvertibleFixedCouponBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
price price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
cashFlows |
cash flows of the bond |
The ConvertibleZeroCouponBond function returns an object of class
ConvertibleZeroCouponBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
price price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
cashFlows |
cash flows of the bond |
Khanh Nguyen [email protected] for the inplementation; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
# commented-out as it runs longer than CRAN likes ## Not run: #this follow an example in test-suite/convertiblebond.cpp params <- list(tradeDate=Sys.Date()-2, settleDate=Sys.Date(), dt=.25, interpWhat="discount", interpHow="loglinear") dividendYield <- DiscountCurve(params, list(flat=0.02)) riskFreeRate <- DiscountCurve(params, list(flat=0.05)) dividendSchedule <- data.frame(Type=character(0), Amount=numeric(0), Rate = numeric(0), Date = as.Date(character(0))) callabilitySchedule <- data.frame(Price = numeric(0), Type=character(0), Date = as.Date(character(0))) process <- list(underlying=50, divYield = dividendYield, rff = riskFreeRate, volatility=0.15) today <- Sys.Date() bondparams <- list(exercise="am", faceAmount=100, divSch = dividendSchedule, callSch = callabilitySchedule, redemption=100, creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter="ActualActual", period = "Semiannual", calendar = "UnitedStates/GovernmentBond", businessDayConvention="Following") lengths <- c(2,4,6,8,10,12,14,16,18,20,22,24,26,28,30) coupons <- c( 0.0200, 0.0225, 0.0250, 0.0275, 0.0300, 0.0325, 0.0350, 0.0375, 0.0400, 0.0425, 0.0450, 0.0475, 0.0500, 0.0525, 0.0550 ) marketQuotes <- rep(100, length(lengths)) curvedateparams <- list(settlementDays=0, period="Annual", dayCounter="ActualActual", businessDayConvention ="Unadjusted") curveparams <- list(method="ExponentialSplinesFitting", origDate = Sys.Date()) curve <- FittedBondCurve(curveparams, lengths, coupons, marketQuotes, curvedateparams) iborindex <- list(type="USDLibor", length=6, inTermOf="Month", term=curve) spreads <- c() #ConvertibleFloatingCouponBond(bondparams, iborindex, spreads, process, dateparams) #example using default values #ConvertibleFloatingCouponBond(bondparams, iborindex,spreads, process) dateparams <- list(settlementDays=3, period = "Semiannual", businessDayConvention="Unadjusted") bondparams <- list( creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) #ConvertibleFloatingCouponBond(bondparams, iborindex, #spreads, process, dateparams) #this follow an example in test-suite/convertiblebond.cpp #for ConvertibleFixedCouponBond #set up arguments to build a pricing engine. params <- list(tradeDate=Sys.Date()-2, settleDate=Sys.Date(), dt=.25, interpWhat="discount", interpHow="loglinear") times <- seq(0,10,.1) dividendYield <- DiscountCurve(params, list(flat=0.02), times) riskFreeRate <- DiscountCurve(params, list(flat=0.05), times) dividendSchedule <- data.frame(Type=character(0), Amount=numeric(0), Rate = numeric(0), Date = as.Date(character(0))) callabilitySchedule <- data.frame(Price = numeric(0), Type=character(0), Date = as.Date(character(0))) process <- list(underlying=50, divYield = dividendYield, rff = riskFreeRate, volatility=0.15) today <- Sys.Date() bondparams <- list(exercise="am", faceAmount=100, divSch = dividendSchedule, callSch = callabilitySchedule, redemption=100, creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter="Actual360", period = "Once", calendar = "UnitedStates/GovernmentBond", businessDayConvention="Following" ) coupon <- c(0.05) ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) #example with default value ConvertibleFixedCouponBond(bondparams, coupon, process) dateparams <- list(settlementDays=3, dayCounter="Actual360") ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) bondparams <- list(creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) #this follow an example in test-suite/convertiblebond.cpp params <- list(tradeDate=Sys.Date()-2, settleDate=Sys.Date(), dt=.25, interpWhat="discount", interpHow="loglinear") times <- seq(0,10,.1) dividendYield <- DiscountCurve(params, list(flat=0.02), times) riskFreeRate <- DiscountCurve(params, list(flat=0.05), times) dividendSchedule <- data.frame(Type=character(0), Amount=numeric(0), Rate = numeric(0), Date = as.Date(character(0))) callabilitySchedule <- data.frame(Price = numeric(0), Type=character(0), Date = as.Date(character(0))) process <- list(underlying=50, divYield = dividendYield, rff = riskFreeRate, volatility=0.15) today <- Sys.Date() bondparams <- list(exercise="am", faceAmount=100, divSch = dividendSchedule, callSch = callabilitySchedule, redemption=100, creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter="Actual360", period = "Once", calendar = "UnitedStates/GovernmentBond", businessDayConvention="Following" ) ConvertibleZeroCouponBond(bondparams, process, dateparams) #example with default values ConvertibleZeroCouponBond(bondparams, process) bondparams <- list(creditSpread=0.005, conversionRatio=0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter='Actual360') ConvertibleZeroCouponBond(bondparams, process, dateparams) ConvertibleZeroCouponBond(bondparams, process) ## End(Not run)# commented-out as it runs longer than CRAN likes ## Not run: #this follow an example in test-suite/convertiblebond.cpp params <- list(tradeDate=Sys.Date()-2, settleDate=Sys.Date(), dt=.25, interpWhat="discount", interpHow="loglinear") dividendYield <- DiscountCurve(params, list(flat=0.02)) riskFreeRate <- DiscountCurve(params, list(flat=0.05)) dividendSchedule <- data.frame(Type=character(0), Amount=numeric(0), Rate = numeric(0), Date = as.Date(character(0))) callabilitySchedule <- data.frame(Price = numeric(0), Type=character(0), Date = as.Date(character(0))) process <- list(underlying=50, divYield = dividendYield, rff = riskFreeRate, volatility=0.15) today <- Sys.Date() bondparams <- list(exercise="am", faceAmount=100, divSch = dividendSchedule, callSch = callabilitySchedule, redemption=100, creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter="ActualActual", period = "Semiannual", calendar = "UnitedStates/GovernmentBond", businessDayConvention="Following") lengths <- c(2,4,6,8,10,12,14,16,18,20,22,24,26,28,30) coupons <- c( 0.0200, 0.0225, 0.0250, 0.0275, 0.0300, 0.0325, 0.0350, 0.0375, 0.0400, 0.0425, 0.0450, 0.0475, 0.0500, 0.0525, 0.0550 ) marketQuotes <- rep(100, length(lengths)) curvedateparams <- list(settlementDays=0, period="Annual", dayCounter="ActualActual", businessDayConvention ="Unadjusted") curveparams <- list(method="ExponentialSplinesFitting", origDate = Sys.Date()) curve <- FittedBondCurve(curveparams, lengths, coupons, marketQuotes, curvedateparams) iborindex <- list(type="USDLibor", length=6, inTermOf="Month", term=curve) spreads <- c() #ConvertibleFloatingCouponBond(bondparams, iborindex, spreads, process, dateparams) #example using default values #ConvertibleFloatingCouponBond(bondparams, iborindex,spreads, process) dateparams <- list(settlementDays=3, period = "Semiannual", businessDayConvention="Unadjusted") bondparams <- list( creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) #ConvertibleFloatingCouponBond(bondparams, iborindex, #spreads, process, dateparams) #this follow an example in test-suite/convertiblebond.cpp #for ConvertibleFixedCouponBond #set up arguments to build a pricing engine. params <- list(tradeDate=Sys.Date()-2, settleDate=Sys.Date(), dt=.25, interpWhat="discount", interpHow="loglinear") times <- seq(0,10,.1) dividendYield <- DiscountCurve(params, list(flat=0.02), times) riskFreeRate <- DiscountCurve(params, list(flat=0.05), times) dividendSchedule <- data.frame(Type=character(0), Amount=numeric(0), Rate = numeric(0), Date = as.Date(character(0))) callabilitySchedule <- data.frame(Price = numeric(0), Type=character(0), Date = as.Date(character(0))) process <- list(underlying=50, divYield = dividendYield, rff = riskFreeRate, volatility=0.15) today <- Sys.Date() bondparams <- list(exercise="am", faceAmount=100, divSch = dividendSchedule, callSch = callabilitySchedule, redemption=100, creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter="Actual360", period = "Once", calendar = "UnitedStates/GovernmentBond", businessDayConvention="Following" ) coupon <- c(0.05) ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) #example with default value ConvertibleFixedCouponBond(bondparams, coupon, process) dateparams <- list(settlementDays=3, dayCounter="Actual360") ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) bondparams <- list(creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) ConvertibleFixedCouponBond(bondparams, coupon, process, dateparams) #this follow an example in test-suite/convertiblebond.cpp params <- list(tradeDate=Sys.Date()-2, settleDate=Sys.Date(), dt=.25, interpWhat="discount", interpHow="loglinear") times <- seq(0,10,.1) dividendYield <- DiscountCurve(params, list(flat=0.02), times) riskFreeRate <- DiscountCurve(params, list(flat=0.05), times) dividendSchedule <- data.frame(Type=character(0), Amount=numeric(0), Rate = numeric(0), Date = as.Date(character(0))) callabilitySchedule <- data.frame(Price = numeric(0), Type=character(0), Date = as.Date(character(0))) process <- list(underlying=50, divYield = dividendYield, rff = riskFreeRate, volatility=0.15) today <- Sys.Date() bondparams <- list(exercise="am", faceAmount=100, divSch = dividendSchedule, callSch = callabilitySchedule, redemption=100, creditSpread=0.005, conversionRatio = 0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter="Actual360", period = "Once", calendar = "UnitedStates/GovernmentBond", businessDayConvention="Following" ) ConvertibleZeroCouponBond(bondparams, process, dateparams) #example with default values ConvertibleZeroCouponBond(bondparams, process) bondparams <- list(creditSpread=0.005, conversionRatio=0.0000000001, issueDate=as.Date(today+2), maturityDate=as.Date(today+3650)) dateparams <- list(settlementDays=3, dayCounter='Actual360') ConvertibleZeroCouponBond(bondparams, process, dateparams) ConvertibleZeroCouponBond(bondparams, process) ## End(Not run)
DiscountCurve constructs the spot term structure of interest
rates based on input market data including the settlement date,
deposit rates, futures prices, FRA rates, or swap rates, in various
combinations. It returns the corresponding discount factors, zero
rates, and forward rates for a vector of times that is specified
as input.
DiscountCurve(params, tsQuotes, times, legparams)DiscountCurve(params, tsQuotes, times, legparams)
params |
A list specifying the |
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tsQuotes |
Market quotes used to construct the spot term structure of interest rates. Must be a list of name/value pairs, where the currently recognized names are:
Here rates are expected as fractions (so 5% means .05).
If |
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times |
A vector of times at which to return the discount
factors, forward rates, and zero rates. Times must be specified such
that the largest time plus |
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legparams |
A list specifying the |
This function is based on QuantLib Version 0.3.10. It
introduces support for fixed-income instruments in RQuantLib.
Forward rates and zero rates are computed assuming continuous
compounding, so the forward rate over the
period from to is determined by the
relation
where and are discount factors
corresponding to the two times. In the case of the zero rate
is the current time (the spot date).
Curve construction can be a delicate problem and the algorithms may
fail for some input data sets and/or some combinations of the
values for interpWhat and interpHow.
Fortunately, the C++ exception mechanism seems to work well with the R
interface, and QuantLib exceptions are propagated back to the
R user, usually with a message that indicates what went wrong. (The
first part of the message contains technical information about the
precise location of the problem in the QuantLib code. Scroll to
the end to find information that is meaningful to the R user.)
DiscountCurve returns a list containing:
times |
Vector of input times |
discounts |
Corresponding discount factors |
forwards |
Corresponding forward rates with time span |
zerorates |
Corresponding zero coupon rates |
flatQuotes |
True if a flat quote was used, False otherwise |
params |
The input parameter list |
Dominick Samperi
Brigo, D. and Mercurio, F. (2001) Interest Rate Models: Theory and Practice, Springer-Verlag, New York.
For information about QuantLib see https://www.quantlib.org/.
For information about RQuantLib see
http://dirk.eddelbuettel.com/code/rquantlib.html.
## Not run: savepar <- par(mfrow=c(3,3), mar=c(4,4,2,0.5)) ## This data is taken from sample code shipped with QuantLib 0.9.7 ## from the file Examples/Swap/swapvaluation params <- list(tradeDate=as.Date('2004-09-20'), settleDate=as.Date('2004-09-22'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-09-20")) ## We get numerical issue for the spline interpolation if we add ## any on of these three extra futures -- the original example ## creates different curves based on different deposit, fra, futures ## and swap data ## Removing s2y helps, as kindly pointed out by Luigi Ballabio tsQuotes <- list(d1w = 0.0382, d1m = 0.0372, d3m = 0.0363, d6m = 0.0353, d9m = 0.0348, d1y = 0.0345, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, # s2y = 0.037125, s3y = 0.0398, s5y = 0.0443, s10y = 0.05165, s15y = 0.055175) times <- seq(0,10,.1) # Loglinear interpolation of discount factors curves <- DiscountCurve(params, tsQuotes, times) plot(curves,setpar=FALSE) # Linear interpolation of discount factors params$interpHow="linear" curves <- DiscountCurve(params, tsQuotes, times) plot(curves,setpar=FALSE) # Spline interpolation of discount factors params$interpHow="spline" curves <- DiscountCurve(params, tsQuotes, times) plot(curves,setpar=FALSE) par(savepar) ## End(Not run)## Not run: savepar <- par(mfrow=c(3,3), mar=c(4,4,2,0.5)) ## This data is taken from sample code shipped with QuantLib 0.9.7 ## from the file Examples/Swap/swapvaluation params <- list(tradeDate=as.Date('2004-09-20'), settleDate=as.Date('2004-09-22'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-09-20")) ## We get numerical issue for the spline interpolation if we add ## any on of these three extra futures -- the original example ## creates different curves based on different deposit, fra, futures ## and swap data ## Removing s2y helps, as kindly pointed out by Luigi Ballabio tsQuotes <- list(d1w = 0.0382, d1m = 0.0372, d3m = 0.0363, d6m = 0.0353, d9m = 0.0348, d1y = 0.0345, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, # s2y = 0.037125, s3y = 0.0398, s5y = 0.0443, s10y = 0.05165, s15y = 0.055175) times <- seq(0,10,.1) # Loglinear interpolation of discount factors curves <- DiscountCurve(params, tsQuotes, times) plot(curves,setpar=FALSE) # Linear interpolation of discount factors params$interpHow="linear" curves <- DiscountCurve(params, tsQuotes, times) plot(curves,setpar=FALSE) # Spline interpolation of discount factors params$interpHow="spline" curves <- DiscountCurve(params, tsQuotes, times) plot(curves,setpar=FALSE) par(savepar) ## End(Not run)
Reference for parameters when constructing a bond
DayCounter |
an int value
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businessDayConvention |
an int value
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compounding |
an int value
|
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period or frequency |
an int value
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date generation |
an int value to specify date generation rule
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durationType |
an int value to specify duration type
|
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation, particularly the datetime classes.
None
Khanh Nguyen [email protected]
https://www.quantlib.org/ for details on QuantLib.
The EuropeanOption function evaluations an European-style
option on a common stock using the Black-Scholes-Merton solution. The
option value, the common first derivatives ("Greeks") as well as the
calling parameters are returned.
## Default S3 method: EuropeanOption(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, discreteDividends, discreteDividendsTimeUntil)## Default S3 method: EuropeanOption(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility, discreteDividends, discreteDividendsTimeUntil)
type |
A string with one of the values |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Volatility of the underlying stock |
discreteDividends |
Vector of discrete dividends (optional) |
discreteDividendsTimeUntil |
Vector of times to discrete dividends (in fractional years, optional) |
The well-known closed-form solution derived by Black, Scholes and Merton is used for valuation. Implied volatilities are calculated numerically.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The EuropeanOption function returns an object of class
EuropeanOption (which inherits from class
Option). It contains a list with the following
components:
value |
Value of option |
delta |
Sensitivity of the option value for a change in the underlying |
gamma |
Sensitivity of the option delta for a change in the underlying |
vega |
Sensitivity of the option value for a change in the underlying's volatility |
theta |
Sensitivity of the option value for a change in t, the remaining time to maturity |
rho |
Sensitivity of the option value for a change in the risk-free interest rate |
dividendRho |
Sensitivity of the option value for a change in the dividend yield |
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
EuropeanOptionImpliedVolatility,
EuropeanOptionArrays,
AmericanOption,BinaryOption
## simple call with unnamed parameters EuropeanOption("call", 100, 100, 0.01, 0.03, 0.5, 0.4) ## simple call with some explicit parameters, and slightly increased vol: EuropeanOption(type="call", underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.5, volatility=0.5) ## simple call with slightly shorter maturity: QuantLib 1.7 compiled with ## intra-day time calculation support with create slightly changed values EuropeanOption(type="call", underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.499, volatility=0.5)## simple call with unnamed parameters EuropeanOption("call", 100, 100, 0.01, 0.03, 0.5, 0.4) ## simple call with some explicit parameters, and slightly increased vol: EuropeanOption(type="call", underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.5, volatility=0.5) ## simple call with slightly shorter maturity: QuantLib 1.7 compiled with ## intra-day time calculation support with create slightly changed values EuropeanOption(type="call", underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.499, volatility=0.5)
The EuropeanOptionArrays function allows any two of the numerical
input parameters to be a vector, and a list of matrices is
returned for the option value as well as each of the 'greeks'. For
each of the returned matrices, each element
corresponds to an evaluation under the given set of parameters.
EuropeanOptionArrays(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility) oldEuropeanOptionArrays(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility) plotOptionSurface(EOres, ylabel="", xlabel="", zlabel="", fov=60)EuropeanOptionArrays(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility) oldEuropeanOptionArrays(type, underlying, strike, dividendYield, riskFreeRate, maturity, volatility) plotOptionSurface(EOres, ylabel="", xlabel="", zlabel="", fov=60)
type |
A string with one of the values |
underlying |
(Scalar or list) current price(s) of the underlying stock |
strike |
(Scalar or list) strike price(s) of the option |
dividendYield |
(Scalar or list) continuous dividend yield(s) (as a fraction) of the stock |
riskFreeRate |
(Scalar or list) risk-free rate(s) |
maturity |
(Scalar or list) time(s) to maturity (in fractional years) |
volatility |
(Scalar or list) volatilit(y|ies) of the underlying stock |
EOres |
result matrix produced by |
ylabel |
label for y-axsis |
xlabel |
label for x-axsis |
zlabel |
label for z-axsis |
fov |
viewpoint for 3d rendering |
The well-known closed-form solution derived by Black, Scholes and Merton is used for valuation.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The EuropeanOptionArrays function allows any two of the numerical
input parameters to be a vector or sequence. A list of
two-dimensional matrices is returned. Each cell corresponds to
an evaluation under the given set of parameters.
For these functions, the following components are returned:
value |
(matrix) value of option |
delta |
(matrix) change in value for a change in the underlying |
gamma |
(matrix) change in value for a change in delta |
vega |
(matrix) change in value for a change in the underlying's volatility |
theta |
(matrix) change in value for a change in delta |
rho |
(matrix) change in value for a change in time to maturity |
dividendRho |
(matrix) change in value for a change in delta |
parameters |
List with parameters with which object was created |
The oldEuropeanOptionArrays function is an older implementation
which vectorises this at the R level instead but allows more general
multidimensional arrays.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
## Not run: # define two vectos for the underlying and the volatility und.seq <- seq(10,180,by=2) vol.seq <- seq(0.1,0.9,by=0.1) # evaluate them along with three scalar parameters EOarr <- EuropeanOptionArrays("call", underlying=und.seq, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=1, volatility=vol.seq) # and look at four of the result arrays: value, delta, gamma, vega old.par <- par(no.readonly = TRUE) par(mfrow=c(2,2),oma=c(5,0,0,0),mar=c(2,2,2,1)) plot(EOarr$parameters.underlying, EOarr$value[,1], type='n', main="option value", xlab="", ylab="") topocol <- topo.colors(length(vol.seq)) for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$value[,i], col=topocol[i]) plot(EOarr$parameters.underlying, EOarr$delta[,1],type='n', main="option delta", xlab="", ylab="") for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$delta[,i], col=topocol[i]) plot(EOarr$parameters.underlying, EOarr$gamma[,1],type='n', main="option gamma", xlab="", ylab="") for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$gamma[,i], col=topocol[i]) plot(EOarr$parameters.underlying, EOarr$vega[,1],type='n', main="option vega", xlab="", ylab="") for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$vega[,i], col=topocol[i]) mtext(text=paste("Strike is 100, maturity 1 year, riskless rate 0.03", "\nUnderlying price from", und.seq[1],"to", und.seq[length(und.seq)], "\nVolatility from",vol.seq[1], "to",vol.seq[length(vol.seq)]), side=1,font=1,outer=TRUE,line=3) par(old.par) ## End(Not run)## Not run: # define two vectos for the underlying and the volatility und.seq <- seq(10,180,by=2) vol.seq <- seq(0.1,0.9,by=0.1) # evaluate them along with three scalar parameters EOarr <- EuropeanOptionArrays("call", underlying=und.seq, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=1, volatility=vol.seq) # and look at four of the result arrays: value, delta, gamma, vega old.par <- par(no.readonly = TRUE) par(mfrow=c(2,2),oma=c(5,0,0,0),mar=c(2,2,2,1)) plot(EOarr$parameters.underlying, EOarr$value[,1], type='n', main="option value", xlab="", ylab="") topocol <- topo.colors(length(vol.seq)) for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$value[,i], col=topocol[i]) plot(EOarr$parameters.underlying, EOarr$delta[,1],type='n', main="option delta", xlab="", ylab="") for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$delta[,i], col=topocol[i]) plot(EOarr$parameters.underlying, EOarr$gamma[,1],type='n', main="option gamma", xlab="", ylab="") for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$gamma[,i], col=topocol[i]) plot(EOarr$parameters.underlying, EOarr$vega[,1],type='n', main="option vega", xlab="", ylab="") for (i in 1:length(vol.seq)) lines(EOarr$parameters.underlying, EOarr$vega[,i], col=topocol[i]) mtext(text=paste("Strike is 100, maturity 1 year, riskless rate 0.03", "\nUnderlying price from", und.seq[1],"to", und.seq[length(und.seq)], "\nVolatility from",vol.seq[1], "to",vol.seq[length(vol.seq)]), side=1,font=1,outer=TRUE,line=3) par(old.par) ## End(Not run)
The EuropeanOptionImpliedVolatility function solves for the
(unobservable) implied volatility, given an option price as well as
the other required parameters to value an option.
## Default S3 method: EuropeanOptionImpliedVolatility(type, value, underlying, strike, dividendYield, riskFreeRate, maturity, volatility)## Default S3 method: EuropeanOptionImpliedVolatility(type, value, underlying, strike, dividendYield, riskFreeRate, maturity, volatility)
type |
A string with one of the values |
value |
Value of the option (used only for ImpliedVolatility calculation) |
underlying |
Current price of the underlying stock |
strike |
Strike price of the option |
dividendYield |
Continuous dividend yield (as a fraction) of the stock |
riskFreeRate |
Risk-free rate |
maturity |
Time to maturity (in fractional years) |
volatility |
Initial guess for the volatility of the underlying stock |
The well-known closed-form solution derived by Black, Scholes and Merton is used for valuation. Implied volatilities are then calculated numerically.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The EuropeanOptionImpliedVolatility function returns an numeric
variable with volatility implied by the given market prices and given parameters.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
EuropeanOption,AmericanOption,BinaryOption
EuropeanOptionImpliedVolatility(type="call", value=11.10, underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.5, volatility=0.4)EuropeanOptionImpliedVolatility(type="call", value=11.10, underlying=100, strike=100, dividendYield=0.01, riskFreeRate=0.03, maturity=0.5, volatility=0.4)
FittedBondCurve fits a term structure to a set of bonds
using three different fitting methodologies. For more detail,
see QuantLib/Example/FittedBondCurve.
FittedBondCurve(curveparams, lengths, coupons, marketQuotes, dateparams)FittedBondCurve(curveparams, lengths, coupons, marketQuotes, dateparams)
curveparams |
curve parameters
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lengths |
an numeric vector, length of the bonds in year |
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coupons |
a numeric vector, coupon rate of the bonds |
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marketQuotes |
a numeric vector, market price of the bonds |
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dateparams |
(Optional) a named list, QuantLib's date parameters of the bond.
See example below. |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
table, a three columns "date - zeroRate - discount" data frame
Khanh Nguyen [email protected] for the inplementation; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
# commented-out as it runs longer than CRAN likes ## Not run: lengths <- c(2,4,6,8,10,12,14,16,18,20,22,24,26,28,30) coupons <- c( 0.0200, 0.0225, 0.0250, 0.0275, 0.0300, 0.0325, 0.0350, 0.0375, 0.0400, 0.0425, 0.0450, 0.0475, 0.0500, 0.0525, 0.0550 ) marketQuotes <- rep(100, length(lengths)) dateparams <- list(settlementDays=0, period="Annual", dayCounter="ActualActual", businessDayConvention ="Unadjusted") curveparams <- list(method="ExponentialSplinesFitting", origDate = Sys.Date()) curve <- FittedBondCurve(curveparams, lengths, coupons, marketQuotes, dateparams) z <- zoo::zoo(curve$table$zeroRates, order.by=curve$table$date) plot(z) ## End(Not run)# commented-out as it runs longer than CRAN likes ## Not run: lengths <- c(2,4,6,8,10,12,14,16,18,20,22,24,26,28,30) coupons <- c( 0.0200, 0.0225, 0.0250, 0.0275, 0.0300, 0.0325, 0.0350, 0.0375, 0.0400, 0.0425, 0.0450, 0.0475, 0.0500, 0.0525, 0.0550 ) marketQuotes <- rep(100, length(lengths)) dateparams <- list(settlementDays=0, period="Annual", dayCounter="ActualActual", businessDayConvention ="Unadjusted") curveparams <- list(method="ExponentialSplinesFitting", origDate = Sys.Date()) curve <- FittedBondCurve(curveparams, lengths, coupons, marketQuotes, dateparams) z <- zoo::zoo(curve$table$zeroRates, order.by=curve$table$date) plot(z) ## End(Not run)
The FixedRateBond function evaluates a fixed rate bond using discount curve, the yield or the clean price.
More specificly, when a discount curve is provided the calculation is done by DiscountingBondEngine from QuantLib.
The NPV, clean price, dirty price, accrued interest, yield, duration, actual settlement date and cash flows of the bond is returned.
When a yield is provided instead, no engine is provided to the bond class and prices are computed from yield. In the latter case, NPV is set to NA. Same situation when the clean price is given instead of discount curve or yield.
For more detail, see the source codes in QuantLib's file test-suite/bond.cpp.
The FixedRateBondPriceByYield function calculates the theoretical price of a fixed rate bond from its yield.
The FixedRateBondYield function calculates the theoretical yield of a fixed rate bond from its price.
## Default S3 method: FixedRateBond(bond, rates, schedule, calc=list(dayCounter='ActualActual.ISMA', compounding='Compounded', freq='Annual', durationType='Modified'), discountCurve = NULL, yield = NA, price = NA) ## Default S3 method: FixedRateBondPriceByYield( settlementDays=1, yield, faceAmount=100, effectiveDate, maturityDate, period, calendar="UnitedStates/GovernmentBond", rates, dayCounter=2, businessDayConvention=0, compound = 0, redemption=100, issueDate) ## Default S3 method: FixedRateBondYield( settlementDays=1, price, faceAmount=100, effectiveDate, maturityDate, period, calendar="UnitedStates/GovernmentBond", rates, dayCounter=2, businessDayConvention=0, compound = 0, redemption=100, issueDate)## Default S3 method: FixedRateBond(bond, rates, schedule, calc=list(dayCounter='ActualActual.ISMA', compounding='Compounded', freq='Annual', durationType='Modified'), discountCurve = NULL, yield = NA, price = NA) ## Default S3 method: FixedRateBondPriceByYield( settlementDays=1, yield, faceAmount=100, effectiveDate, maturityDate, period, calendar="UnitedStates/GovernmentBond", rates, dayCounter=2, businessDayConvention=0, compound = 0, redemption=100, issueDate) ## Default S3 method: FixedRateBondYield( settlementDays=1, price, faceAmount=100, effectiveDate, maturityDate, period, calendar="UnitedStates/GovernmentBond", rates, dayCounter=2, businessDayConvention=0, compound = 0, redemption=100, issueDate)
bond |
(Optional) bond parameters, a named list whose elements are:
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rates |
a numeric vector, bond's coupon rates |
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schedule |
(Optional) a named list, QuantLib's parameters of the bond's schedule.
See example below. |
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calc |
(Optional) a named list, QuantLib's parameters for calculations.
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discountCurve |
Can be one of the following:
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yield |
yield of the bond |
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price |
clean price of the bond |
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settlementDays |
an integer, 1 for T+1, 2 for T+2, etc... |
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effectiveDate |
bond's effective date |
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maturityDate |
bond's maturity date |
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period |
frequency of events,0=NoFrequency, 1=Once, 2=Annual, 3=Semiannual, 4=EveryFourthMonth, 5=Quarterly, 6=Bimonthly ,7=Monthly ,8=EveryFourthWeek,9=Biweekly, 10=Weekly, 11=Daily. For more information, see QuantLib's Frequency class |
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calendar |
Business Calendar. Either |
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faceAmount |
face amount of the bond |
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businessDayConvention |
convention used to adjust a date in case it is not a valid business day. See quantlib for more detail. 0 = Following, 1 = ModifiedFollowing, 2 = Preceding, 3 = ModifiedPreceding, other = Unadjusted |
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dayCounter |
day count convention. 0 = Actual360(), 1 = Actual365Fixed(), 2 = ActualActual(), 3 = Business252(), 4 = OneDayCounter(), 5 = SimpleDayCounter(), all other = Thirty360(). For more information, see QuantLib's DayCounter class |
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compound |
compounding type. 0=Simple, 1=Compounded, 2=Continuous, all other=SimpleThenCompounded. See QuantLib's Compound class |
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redemption |
redemption when the bond expires |
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issueDate |
date the bond is issued |
A discount curve is built to calculate the bond value.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The FixedRateBond function returns an object of class
FixedRateBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
clean price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
duration |
the duration of the bond |
settlementDate |
the actual settlement date used for the bond |
cashFlows |
cash flows of the bond |
The FixedRateBondPriceByYield function returns an object of class
FixedRateBondPriceByYield (which inherits from class
Bond). It contains a list with the following
components:
price |
price of the bond |
The FixedRateBondYield function returns an object of class
FixedRateBondYield (which inherits from class
Bond). It contains a list with the following
components:
yield |
yield of the bond |
The interface might change in future release as QuantLib
stabilises its own API.
Khanh Nguyen [email protected] for the inplementation; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
#Simple call with a flat curve bond <- list(settlementDays=1, issueDate=as.Date("2004-11-30"), faceAmount=100, dayCounter='Thirty360', paymentConvention='Unadjusted') schedule <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), period='Semiannual', calendar='UnitedStates/GovernmentBond', businessDayConvention='Unadjusted', terminationDateConvention='Unadjusted', dateGeneration='Forward', endOfMonth=1) calc=list(dayCounter='Actual360', compounding='Compounded', freq='Annual', durationType='Modified') coupon.rate <- c(0.02875) params <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-19'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-11-22")) discountCurve.flat <- DiscountCurve(params, list(flat=0.05)) FixedRateBond(bond, coupon.rate, schedule, calc, discountCurve=discountCurve.flat) #Same bond with a discount curve constructed from market quotes tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) tsQuotes <- list("flat" = 0.02) ## While discount curve code is buggy discountCurve <- DiscountCurve(params, tsQuotes) FixedRateBond(bond, coupon.rate, schedule, calc, discountCurve=discountCurve) #Same bond calculated from yield rather than from the discount curve yield <- 0.02 FixedRateBond(bond, coupon.rate, schedule, calc, yield=yield) #same example with clean price price <- 103.31 FixedRateBond(bond, coupon.rate, schedule, calc, price = price) #example with default calc parameter FixedRateBond(bond, coupon.rate, schedule, discountCurve=discountCurve) #example with default calc and schedule parameters schedule <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30")) FixedRateBond(bond, coupon.rate, schedule, discountCurve=discountCurve) #example with default calc, schedule and bond parameters FixedRateBond(, coupon.rate, schedule, discountCurve=discountCurve) FixedRateBondPriceByYield(,0.0307, 100000, as.Date("2004-11-30"), as.Date("2008-11-30"), 3, , c(0.02875), , , , ,as.Date("2004-11-30")) FixedRateBondYield(,90, 100000, as.Date("2004-11-30"), as.Date("2008-11-30"), 3, , c(0.02875), , , , ,as.Date("2004-11-30"))#Simple call with a flat curve bond <- list(settlementDays=1, issueDate=as.Date("2004-11-30"), faceAmount=100, dayCounter='Thirty360', paymentConvention='Unadjusted') schedule <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), period='Semiannual', calendar='UnitedStates/GovernmentBond', businessDayConvention='Unadjusted', terminationDateConvention='Unadjusted', dateGeneration='Forward', endOfMonth=1) calc=list(dayCounter='Actual360', compounding='Compounded', freq='Annual', durationType='Modified') coupon.rate <- c(0.02875) params <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-19'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-11-22")) discountCurve.flat <- DiscountCurve(params, list(flat=0.05)) FixedRateBond(bond, coupon.rate, schedule, calc, discountCurve=discountCurve.flat) #Same bond with a discount curve constructed from market quotes tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) tsQuotes <- list("flat" = 0.02) ## While discount curve code is buggy discountCurve <- DiscountCurve(params, tsQuotes) FixedRateBond(bond, coupon.rate, schedule, calc, discountCurve=discountCurve) #Same bond calculated from yield rather than from the discount curve yield <- 0.02 FixedRateBond(bond, coupon.rate, schedule, calc, yield=yield) #same example with clean price price <- 103.31 FixedRateBond(bond, coupon.rate, schedule, calc, price = price) #example with default calc parameter FixedRateBond(bond, coupon.rate, schedule, discountCurve=discountCurve) #example with default calc and schedule parameters schedule <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30")) FixedRateBond(bond, coupon.rate, schedule, discountCurve=discountCurve) #example with default calc, schedule and bond parameters FixedRateBond(, coupon.rate, schedule, discountCurve=discountCurve) FixedRateBondPriceByYield(,0.0307, 100000, as.Date("2004-11-30"), as.Date("2008-11-30"), 3, , c(0.02875), , , , ,as.Date("2004-11-30")) FixedRateBondYield(,90, 100000, as.Date("2004-11-30"), as.Date("2008-11-30"), 3, , c(0.02875), , , , ,as.Date("2004-11-30"))
The FloatingRateBond function evaluates a floating rate bond using discount curve.
More specificly, the calculation is done by DiscountingBondEngine from QuantLib.
The NPV, clean price, dirty price, accrued interest, yield and cash flows of the bond is returned.
For more detail, see the source codes in quantlib's test-suite. test-suite/bond.cpp
## Default S3 method: FloatingRateBond(bond, gearings, spreads, caps, floors, index, curve, dateparams )## Default S3 method: FloatingRateBond(bond, gearings, spreads, caps, floors, index, curve, dateparams )
bond |
bond parameters, a named list whose elements are:
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gearings |
(Optional) a numeric vector, bond's gearings. See quantlib's doc on FloatingRateBond for more detail. Default value is an empty vector c(). |
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spreads |
(Optional) a numeric vector, bond's spreads. See quantlib's doc on FloatingRateBond for more detail.Default value is an empty vector c() |
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caps |
(Optional) a numeric vector, bond's caps. See quantlib's doc on FloatingRateBond for more detail. Default value is an empty vector c() |
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floors |
(Optional) a numeric vector, bond's floors. See quantlib's doc on FloatingRateBond for more detail. Default value is an empty vector c() |
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curve |
Can be one of the following:
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index |
a named list whose elements are parameters of an IborIndex term structure.
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dateparams |
(Optional) a named list, QuantLib's date parameters of the bond.
See example below. |
A discount curve is built to calculate the bond value.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The FloatingRateBond function returns an object of class
FloatingRateBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
clean price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
cashFlows |
cash flows of the bond |
The interface might change in future release as QuantLib
stabilises its own API.
Khanh Nguyen [email protected] for the inplementation; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
bond <- list(faceAmount=100, issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100, effectiveDate=as.Date("2004-11-30")) dateparams <- list(settlementDays=1, calendar="UnitedStates/GovernmentBond", dayCounter = 'ActualActual', period=2, businessDayConvention = 1, terminationDateConvention=1, dateGeneration=0, endOfMonth=0, fixingDays = 1) gearings <- spreads <- caps <- floors <- vector() params <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-19'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-11-22")) tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) tsQuotes <- list("flat" = 0.02) ## While discount curve code is buggy ## when both discount and libor curves are flat. discountCurve.flat <- DiscountCurve(params, list(flat=0.05)) termstructure <- DiscountCurve(params, list(flat=0.03)) iborIndex.params <- list(type="USDLibor", length=6, inTermOf="Month", term=termstructure) FloatingRateBond(bond, gearings, spreads, caps, floors, iborIndex.params, discountCurve.flat, dateparams) ## discount curve is constructed from market quotes ## and a flat libor curve discountCurve <- DiscountCurve(params, tsQuotes) termstructure <- DiscountCurve(params, list(flat=0.03)) iborIndex.params <- list(type="USDLibor", length=6, inTermOf="Month", term = termstructure) FloatingRateBond(bond, gearings, spreads, caps, floors, iborIndex.params, discountCurve, dateparams) #example using default values FloatingRateBond(bond=bond, index=iborIndex.params, curve=discountCurve)bond <- list(faceAmount=100, issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100, effectiveDate=as.Date("2004-11-30")) dateparams <- list(settlementDays=1, calendar="UnitedStates/GovernmentBond", dayCounter = 'ActualActual', period=2, businessDayConvention = 1, terminationDateConvention=1, dateGeneration=0, endOfMonth=0, fixingDays = 1) gearings <- spreads <- caps <- floors <- vector() params <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-19'), dt=.25, interpWhat="discount", interpHow="loglinear") setEvaluationDate(as.Date("2004-11-22")) tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) tsQuotes <- list("flat" = 0.02) ## While discount curve code is buggy ## when both discount and libor curves are flat. discountCurve.flat <- DiscountCurve(params, list(flat=0.05)) termstructure <- DiscountCurve(params, list(flat=0.03)) iborIndex.params <- list(type="USDLibor", length=6, inTermOf="Month", term=termstructure) FloatingRateBond(bond, gearings, spreads, caps, floors, iborIndex.params, discountCurve.flat, dateparams) ## discount curve is constructed from market quotes ## and a flat libor curve discountCurve <- DiscountCurve(params, tsQuotes) termstructure <- DiscountCurve(params, list(flat=0.03)) iborIndex.params <- list(type="USDLibor", length=6, inTermOf="Month", term = termstructure) FloatingRateBond(bond, gearings, spreads, caps, floors, iborIndex.params, discountCurve, dateparams) #example using default values FloatingRateBond(bond=bond, index=iborIndex.params, curve=discountCurve)
This function returns a named vector of boolean variables describing several configuration options determined at compilation time of the QuantLib library.
getQuantLibCapabilities()getQuantLibCapabilities()
Not all of these features are used (yet) by RQuantLib.
A named vector of logical variables
Dirk Eddelbuettel
https://www.quantlib.org for details on QuantLib.
getQuantLibCapabilities()getQuantLibCapabilities()
This function returns the QuantLib version string as encoded in the header
file config.hpp and determined at compilation time of the QuantLib library.
getQuantLibVersion()getQuantLibVersion()
A character variable
Dirk Eddelbuettel
https://www.quantlib.org for details on QuantLib.
getQuantLibVersion()getQuantLibVersion()
This class forms the basis from which the more specific classes are derived.
## S3 method for class 'ImpliedVolatility' print(x, digits=3, ...) ## S3 method for class 'ImpliedVolatility' summary(object, digits=3, ...)## S3 method for class 'ImpliedVolatility' print(x, digits=3, ...) ## S3 method for class 'ImpliedVolatility' summary(object, digits=3, ...)
x |
Any option-price implied volatility object derived from this base class |
object |
Any option-price implied volatility object derived from this base class |
digits |
Number of digits of precision shown |
... |
Further arguments |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
None, but side effects of displaying content.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
AmericanOptionImpliedVolatility,
EuropeanOptionImpliedVolatility,
AmericanOption,EuropeanOption,
BinaryOption
impVol<-EuropeanOptionImpliedVolatility("call", value=11.10, strike=100, volatility=0.4, 100, 0.01, 0.03, 0.5) print(impVol) summary(impVol)impVol<-EuropeanOptionImpliedVolatility("call", value=11.10, strike=100, volatility=0.4, 100, 0.01, 0.03, 0.5) print(impVol) summary(impVol)
This class forms the basis from which the more specific classes are derived.
## S3 method for class 'Option' print(x, digits=4, ...) ## S3 method for class 'Option' plot(x, ...) ## S3 method for class 'Option' summary(object, digits=4, ...)## S3 method for class 'Option' print(x, digits=4, ...) ## S3 method for class 'Option' plot(x, ...) ## S3 method for class 'Option' summary(object, digits=4, ...)
x |
Any option object derived from this base class |
object |
Any option object derived from this base class |
digits |
Number of digits of precision shown |
... |
Further arguments |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
None, but side effects of displaying content.
The interface might change in future release as QuantLib
stabilises its own API.
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
AmericanOption,EuropeanOption,
BinaryOption
EO<-EuropeanOption("call", strike=100, volatility=0.4, 100, 0.01, 0.03, 0.5) print(EO) summary(EO)EO<-EuropeanOption("call", strike=100, volatility=0.4, 100, 0.01, 0.03, 0.5) print(EO) summary(EO)
SabrSwaption prices a swaption with specified
expiration or time range if Bermudan, strike, and maturity, using quantlibs SABR model for europeans
and quantlib's markovfunctional for Bermudans. Currently the input is a zero offset log-normal vol surface.
An example of a dataset can be found in the dataset rqlib inlcuded with Rquantlib. It is assumed that the
swaption is
exercisable at the start of a forward start swap if params$european flag is set to TRUE or starting
immediately on each reset date (Bermudan) of an existing underlying swap or spot start
swap if params$european flag is set to FALSE.
SabrSwaption(params, ts, volCubeDF, legparams = list(dayCounter = "Thirty360", fixFreq = "Annual", floatFreq = "Semiannual"), tsUp01 = NA, tsDn01 = NA, vega = FALSE)SabrSwaption(params, ts, volCubeDF, legparams = list(dayCounter = "Thirty360", fixFreq = "Annual", floatFreq = "Semiannual"), tsUp01 = NA, tsDn01 = NA, vega = FALSE)
params |
A list specifying the |
ts |
A term structure built with DiscountCurve is required. See the
help page for |
volCubeDF |
The swaption volatility cube in dataframe format with columns Expiry, Tenor, Spread, and LogNormalVol stored by rows. See the example below. |
legparams |
A list specifying the |
tsUp01 |
Discount for a user specied up move in rates. |
tsDn01 |
Discount for a user specied down move in rates. |
vega |
Discount for a user specied up move. |
This function is based on QuantLib Version 1.64. It
introduces support for fixed-income instruments in RQuantLib.
SabrSwaption returns a list containing the value of the payer and receiver swaptions at the
strike specified in params.
NPV |
NPV of swaption in basis points (actual price
equals |
strike |
swaption strike |
params |
Input parameter list |
atmRate |
fair rate for swap at swap start date for european or fair swap rate for swap at expiration for bermudan |
vol |
vol for swaption at swap start date and rate strike for european or vol for swaption for given expiration and strike for bermudan |
rcvDv01 |
reveiver value for a change in rates defined by dv01Up |
payDv01 |
payer value for a change in rates defined by dv01Up |
rcvCnvx |
reveiver second order value change for a change in rates defined by dv01Up & dv01Dn |
payCnvx |
payer second order value for a change in rates defined by dv01Up & dv01Dn |
strike |
swaption strike |
Terry Leitch
Brigo, D. and Mercurio, F. (2006) Interest Rate Models: Theory and Practice, 2nd Edition, Springer-Verlag, New York.
For information about QuantLib see https://www.quantlib.org/.
For information about RQuantLib see
http://dirk.eddelbuettel.com/code/rquantlib.html.
params <- list(tradeDate=as.Date('2016-2-15'), settleDate=as.Date('2016-2-17'), startDate=as.Date('2017-2-17'), maturity=as.Date('2022-2-17'), european=TRUE, dt=.25, expiryDate=as.Date('2017-2-17'), strike=.02, interpWhat="discount", interpHow="loglinear") # Set leg paramters for generating discount curve dclegparams=list(dayCounter="Thirty360", fixFreq="Annual", floatFreq="Semiannual") setEvaluationDate(as.Date("2016-2-15")) times<-times <- seq(0,14.75,.25) data(tsQuotes) dcurve <- DiscountCurve(params, tsQuotes, times=times,dclegparams) # Price the Bermudan swaption swaplegparams=list(fixFreq="Semiannual",floatFreq="Quarterly") data(vcube) pricing <- SabrSwaption(params, dcurve,vcube,swaplegparams) pricingparams <- list(tradeDate=as.Date('2016-2-15'), settleDate=as.Date('2016-2-17'), startDate=as.Date('2017-2-17'), maturity=as.Date('2022-2-17'), european=TRUE, dt=.25, expiryDate=as.Date('2017-2-17'), strike=.02, interpWhat="discount", interpHow="loglinear") # Set leg paramters for generating discount curve dclegparams=list(dayCounter="Thirty360", fixFreq="Annual", floatFreq="Semiannual") setEvaluationDate(as.Date("2016-2-15")) times<-times <- seq(0,14.75,.25) data(tsQuotes) dcurve <- DiscountCurve(params, tsQuotes, times=times,dclegparams) # Price the Bermudan swaption swaplegparams=list(fixFreq="Semiannual",floatFreq="Quarterly") data(vcube) pricing <- SabrSwaption(params, dcurve,vcube,swaplegparams) pricing
The Schedule function generates a schedule of dates conformant to
a given convention in a given calendar.
## Default S3 method: Schedule(params)## Default S3 method: Schedule(params)
params |
a named list, QuantLib's parameters of the schedule.
See example below. |
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The Schedule function returns an object of class
Schedule. It contains the list of dates in the schedule.
Michele Salvadore [email protected] for the inplementation;
Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
params <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), period='Semiannual', calendar='UnitedStates/GovernmentBond', businessDayConvention='Unadjusted', terminationDateConvention='Unadjusted', dateGeneration='Forward', endOfMonth=1) Schedule(params)params <- list(effectiveDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), period='Semiannual', calendar='UnitedStates/GovernmentBond', businessDayConvention='Unadjusted', terminationDateConvention='Unadjusted', dateGeneration='Forward', endOfMonth=1) Schedule(params)
Vol Cube Example Data
Short time series examples
A series of tenors and rates approppriate for calling DiscountCurve
TBA
Data for valuing swaption examples including rates and a lognormal vol cube
data(vcube)data(vcube)
two data frames: vcube, a data frame with four columns: Expiry, Tenor,
LogNormalVol, and Spread
TBA
The ZeroCouponBond function evaluates a zero-coupon plainly using discount curve.
More specificly, the calculation is done by DiscountingBondEngine from QuantLib.
The NPV, clean price, dirty price, accrued interest, yield and cash flows of the bond is returned.
For more detail, see the source code in the QuantLib file test-suite/bond.cpp.
The ZeroPriceYield function evaluates a zero-coupon clean price based on its yield.
The ZeroYield function evaluations a zero-coupon yield based.
See also http://www.mathworks.com/access/helpdesk/help/toolbox/finfixed/zeroyield.html
## Default S3 method: ZeroCouponBond(bond, discountCurve, dateparams) ## Default S3 method: ZeroPriceByYield(yield, faceAmount, issueDate, maturityDate, dayCounter=2, frequency=2, compound=0, businessDayConvention=4) ## Default S3 method: ZeroYield(price, faceAmount, issueDate, maturityDate, dayCounter=2, frequency=2, compound=0, businessDayConvention=4)## Default S3 method: ZeroCouponBond(bond, discountCurve, dateparams) ## Default S3 method: ZeroPriceByYield(yield, faceAmount, issueDate, maturityDate, dayCounter=2, frequency=2, compound=0, businessDayConvention=4) ## Default S3 method: ZeroYield(price, faceAmount, issueDate, maturityDate, dayCounter=2, frequency=2, compound=0, businessDayConvention=4)
bond |
bond parameters, a named list whose elements are:
|
|||||||||||||||||||||
discountCurve |
Can be one of the following:
|
|||||||||||||||||||||
dateparams |
(Optional) a named list, QuantLib's date parameters of the bond.
See example below. |
|||||||||||||||||||||
yield |
yield of the bond |
|||||||||||||||||||||
price |
price of the bond |
|||||||||||||||||||||
faceAmount |
face amount of the bond |
|||||||||||||||||||||
issueDate |
date the bond is issued |
|||||||||||||||||||||
maturityDate |
maturity date, an R's date type |
|||||||||||||||||||||
dayCounter |
day count convention. 0 = Actual360(), 1 = Actual365Fixed(), 2 = ActualActual(), 3 = Business252(), 4 = OneDayCounter(), 5 = SimpleDayCounter(), all other = Thirty360(). For more information, see QuantLib's DayCounter class |
|||||||||||||||||||||
frequency |
frequency of events,0=NoFrequency, 1=Once, 2=Annual, 3=Semiannual, 4=EveryFourthMonth, 5=Quarterly, 6=Bimonthly ,7=Monthly ,8=EveryFourthWeely,9=Biweekly, 10=Weekly, 11=Daily. For more information, see QuantLib's Frequency class |
|||||||||||||||||||||
compound |
compounding type. 0=Simple, 1=Compounded, 2=Continuous, all other=SimpleThenCompounded. See QuantLib's Compound class |
|||||||||||||||||||||
businessDayConvention |
convention used to adjust a date in case it is not a valid business day. See quantlib for more detail. 0 = Following, 1 = ModifiedFollowing, 2 = Preceding, 3 = ModifiedPreceding, other = Unadjusted |
A discount curve is built to calculate the bond value.
Please see any decent Finance textbook for background reading, and the
QuantLib documentation for details on the QuantLib
implementation.
The ZeroCouponBond function returns an object of class
ZeroCouponBond (which inherits from class
Bond). It contains a list with the following
components:
NPV |
net present value of the bond |
cleanPrice |
clean price of the bond |
dirtyPrice |
dirty price of the bond |
accruedAmount |
accrued amount of the bond |
yield |
yield of the bond |
cashFlows |
cash flows of the bond |
The ZeroPriceByYield function returns an object of class
ZeroPriceByYield (which inherits from class
Bond). It contains a list with the following
components:
price |
price of the bond |
The ZeroYield function returns an object of class
ZeroYield (which inherits from class
Bond). It contains a list with the following
components:
yield |
yield of the bond |
The interface might change in future release as QuantLib
stabilises its own API.
Khanh Nguyen [email protected] for the inplementation; Dirk Eddelbuettel [email protected] for the R interface;
the QuantLib Group for QuantLib
https://www.quantlib.org/ for details on QuantLib.
# Simple call with all parameter and a flat curve bond <- list(faceAmount=100,issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100 ) dateparams <-list(settlementDays=1, calendar="UnitedStates/GovernmentBond", businessDayConvention='Unadjusted') discountCurve.param <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-15'), dt=0.25, interpWhat='discount', interpHow='loglinear') discountCurve.flat <- DiscountCurve(discountCurve.param, list(flat=0.05)) ZeroCouponBond(bond, discountCurve.flat, dateparams) # The same bond with a discount curve constructed from market quotes tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) tsQuotes <- list("flat" = 0.02) ## While discount curve code is buggy discountCurve <- DiscountCurve(discountCurve.param, tsQuotes) ZeroCouponBond(bond, discountCurve, dateparams) #examples with default arguments ZeroCouponBond(bond, discountCurve) bond <- list(issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30")) dateparams <-list(settlementDays=1) ZeroCouponBond(bond, discountCurve, dateparams) ZeroPriceByYield(0.1478, 100, as.Date("1993-6-24"), as.Date("1993-11-1")) ZeroYield(90, 100, as.Date("1993-6-24"), as.Date("1993-11-1"))# Simple call with all parameter and a flat curve bond <- list(faceAmount=100,issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30"), redemption=100 ) dateparams <-list(settlementDays=1, calendar="UnitedStates/GovernmentBond", businessDayConvention='Unadjusted') discountCurve.param <- list(tradeDate=as.Date('2002-2-15'), settleDate=as.Date('2002-2-15'), dt=0.25, interpWhat='discount', interpHow='loglinear') discountCurve.flat <- DiscountCurve(discountCurve.param, list(flat=0.05)) ZeroCouponBond(bond, discountCurve.flat, dateparams) # The same bond with a discount curve constructed from market quotes tsQuotes <- list(d1w =0.0382, d1m =0.0372, fut1=96.2875, fut2=96.7875, fut3=96.9875, fut4=96.6875, fut5=96.4875, fut6=96.3875, fut7=96.2875, fut8=96.0875, s3y =0.0398, s5y =0.0443, s10y =0.05165, s15y =0.055175) tsQuotes <- list("flat" = 0.02) ## While discount curve code is buggy discountCurve <- DiscountCurve(discountCurve.param, tsQuotes) ZeroCouponBond(bond, discountCurve, dateparams) #examples with default arguments ZeroCouponBond(bond, discountCurve) bond <- list(issueDate=as.Date("2004-11-30"), maturityDate=as.Date("2008-11-30")) dateparams <-list(settlementDays=1) ZeroCouponBond(bond, discountCurve, dateparams) ZeroPriceByYield(0.1478, 100, as.Date("1993-6-24"), as.Date("1993-11-1")) ZeroYield(90, 100, as.Date("1993-6-24"), as.Date("1993-11-1"))