floorbyblk

Price floors using Black option pricing model

Syntax

[FloorPrice,Floorlets] = floorbyblk(RateSpec,Strike,Settle,Maturity,Volatility)

[FloorPrice,Floorlets] = floorbyblk(___,Name,Value)

Description

[FloorPrice,Floorlets] = floorbyblk(RateSpec,Strike,Settle,Maturity,Volatility) price floors using the Black option pricing model. floorbyblk computes prices of vanilla floors and amortizing floors.

Note

Alternatively, you can use the Floor object to price floor instruments. For more information, see Get Started with Workflows Using Object-Based Framework for Pricing Financial Instruments.

[FloorPrice,Floorlets] = floorbyblk(___,Name,Value) adds optional name-value pair arguments.

Examples

Price a Floor Using the Black Option Pricing Model

This example shows how to price a floor using the Black option pricing model. Consider an investor who gets into a contract that floors the interest rate on a $100,000 loan at 6% quarterly compounded for 3 months, starting on January 1, 2009. Assuming that on January 1, 2008 the zero rate is 6.9394% continuously compounded and the volatility is 20%, use this data to compute the floor price.

ValuationDate = datetime(2008,1,1);  
EndDates = datetime(2010,4,1);
Rates = 0.069394;
Compounding = -1; 
Basis = 1;

% calculate the RateSpec
RateSpec = intenvset('ValuationDate', ValuationDate, ...
'StartDates', ValuationDate,'EndDates', EndDates, ...
'Rates', Rates,'Compounding', Compounding,'Basis', Basis);

Settle = datetime(2009,1,1); % floor starts in a year
Maturity = datetime(2009,4,1);
Volatility = 0.20;
FloorRate = 0.06;
FloorReset = 4;
Principal=100000;

FloorPrice = floorbyblk(RateSpec, FloorRate, Settle, Maturity, Volatility,...
'Reset',FloorReset,'ValuationDate',ValuationDate,'Principal', Principal,...
'Basis', Basis)

FloorPrice = 
37.4864

Price a Floor Using a Different Curve to Generate the Future Forward Rates

Define the OIS and Libor rates.

Settle = datetime(2013,3,15);
CurveDates = daysadd(Settle,360*[1/12 2/12 3/12 6/12 1 2 3 4 5 7 10],1);
OISRates = [.0018 .0019 .0021 .0023 .0031 .006  .011 .017 .021 .026 .03]';
LiborRates = [.0045 .0047 .005 .0055 .0075 .0109  .0162 .0216 .0262 .0309 .0348]';

Create an associated RateSpec for the OIS and Libor curves.

OISCurve = intenvset('Rates',OISRates,'StartDate',Settle,'EndDates',CurveDates,'Compounding',2,'Basis',1);
LiborCurve = intenvset('Rates',LiborRates,'StartDate',Settle,'EndDates',CurveDates,'Compounding',2,'Basis',1);

Define the Floor instruments.

Maturity = [datetime(2018,3,15) ; datetime(2020,3,15)];
Strike = [.04;.05];
BlackVol = .2;

Price the floor instruments using the term structure OISCurve both for discounting the cash flows and generating future forward rates.

[Price, Floorlets] = floorbyblk(OISCurve, Strike, Settle, Maturity, BlackVol)

Price = 2×1

    9.9808
   16.9057

Floorlets = 2×7

    3.6783    3.0706    1.8275    0.7280    0.6764       NaN       NaN
    4.6753    4.0587    2.7921    1.4763    1.3442    1.4130    1.1462

Price the floor instruments using the term structure LiborCurve to generate future forward rates. The term structure OISCurve is used for discounting the cash flows.

[PriceLC, FloorletsLC] = floorbyblk(OISCurve, Strike, Settle, Maturity, BlackVol,'ProjectionCurve',LiborCurve)

PriceLC = 2×1

    8.0524
   14.3184

FloorletsLC = 2×7

    3.2385    2.5338    1.2895    0.5889    0.4017       NaN       NaN
    4.2355    3.5219    2.2286    1.2751    0.9169    1.1698    0.9706

Compute the Price of an Amortizing Floor Using the Black Model

Define the RateSpec.

Rates = [0.0358; 0.0421; 0.0473; 0.0527; 0.0543];
ValuationDate = datetime(2011,11,15);
StartDates = ValuationDate;
EndDates = [datetime(2012,11,15) ; datetime(2013,11,15) ; datetime(2014,11,15) ; datetime(2015,11,15) ; datetime(2016,11,15)];
Compounding = 1;
RateSpec = intenvset('ValuationDate', ValuationDate,'StartDates', StartDates,...
             'EndDates', EndDates,'Rates', Rates, 'Compounding', Compounding)

RateSpec = struct with fields:
           FinObj: 'RateSpec'
      Compounding: 1
             Disc: [5×1 double]
            Rates: [5×1 double]
         EndTimes: [5×1 double]
       StartTimes: [5×1 double]
         EndDates: [5×1 double]
       StartDates: 734822
    ValuationDate: 734822
            Basis: 0
     EndMonthRule: 1

Define the floor instrument.

Settle = datetime(2011,11,15);
Maturity = datetime(2015,11,15);
Strike = 0.05;
Reset = 2;
Principal ={{datetime(2012,11,15) 100;datetime(2013,11,15) 70;datetime(2014,11,15) 40;datetime(2015,11,15) 10}};

Price the amortizing floor.

Volatility = 0.20;
Price = floorbyblk(RateSpec, Strike, Settle, Maturity, Volatility,...
'Reset',Reset,'Principal', Principal)

Price = 
1.9315

Price a Floor Using the Shifted Black Model

Create the RateSpec.

ValuationDate = datetime(2016,3,1);
EndDates = [datetime(2017,3,1) ; datetime(2018,3,1) ; datetime(2019,3,1) ; datetime(2020,3,1) ; datetime(2021,3,1)];
Rates = [-0.21; -0.12; 0.01; 0.10; 0.20]/100;
Compounding = 1;
Basis = 1;

RateSpec = intenvset('ValuationDate',ValuationDate,'StartDates',ValuationDate, ...
'EndDates',EndDates,'Rates',Rates,'Compounding',Compounding,'Basis',Basis)

RateSpec = struct with fields:
           FinObj: 'RateSpec'
      Compounding: 1
             Disc: [5×1 double]
            Rates: [5×1 double]
         EndTimes: [5×1 double]
       StartTimes: [5×1 double]
         EndDates: [5×1 double]
       StartDates: 736390
    ValuationDate: 736390
            Basis: 1
     EndMonthRule: 1

Price the floor with a negative strike using the Shifted Black model.

Settle = datetime(2016,6,1); % Floor starts in 3 months.
Maturity = datetime(2016,9,1);
ShiftedBlackVolatility = 0.31;
FloorRate = -0.001;  % -0.1 percent strike.
FloorReset = 4;
Principal = 100000;
Shift = 0.01; % 1 percent shift.

FloorPrice = floorbyblk(RateSpec,FloorRate,Settle,Maturity,ShiftedBlackVolatility,...
'Reset',FloorReset,'ValuationDate',ValuationDate,'Principal',Principal,...
'Basis',Basis,'Shift',Shift)

FloorPrice = 
31.2099

Input Arguments

RateSpec — Interest-rate term structure

structure

Interest-rate term structure (annualized and continuously compounded), specified by the RateSpec obtained from intenvset. For information on the interest-rate specification, see intenvset.

Data Types: struct

Strike — Rate at which floor is exercised

decimal

Rate at which floor is exercised, specified as a NINST-by-1 vector of decimal values.

Data Types: double

Settle — Settlement date for floor

datetime array | string array | date character vector

Settlement date for the floor, specified as a NINST-by-1 vector using a datetime array, string array, or date character vectors.

To support existing code, floorbyblk also accepts serial date numbers as inputs, but they are not recommended.

Maturity — Maturity date for floor

datetime array | string array | date character vector

Maturity date for the floor, specified as a NINST-by-1 vector using a datetime array, string array, or date character vectors.

To support existing code, floorbyblk also accepts serial date numbers as inputs, but they are not recommended.

Volatility — Volatilities values

numeric

Volatilities values, specified as a NINST-by-1 vector of numeric values.

The Volatility input is not intended for volatility surfaces or cubes. If you specify a matrix for the Volatility input, floorbyblk internally converts it into a vector. floorbyblk assumes that the volatilities specified in the Volatility input are flat volatilities, which are applied equally to each of the floorlets.

Data Types: double

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: [FloorPrice,Floorlets] = floorbyblk(RateSpec,Strike,Settle,Maturity,Volatility,'Reset',CapReset,'Principal',100000,'Basis',7)

Reset — Reset frequency payment per year

1 (default) | numeric

Reset frequency payment per year, specified as a NINST-by-1 vector.

Data Types: double

Principal — Notional principal amount

100 (default) | numeric

Notional principal amount, specified as a NINST-by-1 of notional principal amounts, or a NINST-by-1 cell array. When Principal is a NINST-by-1 cell array, each element is a NumDates-by-2 cell array, where the first column is dates and the second column is associated principal amount. The date indicates the last day that the principal value is valid.

Use Principal to pass a schedule to compute the price for an amortizing floor.

Data Types: double | cell

Basis — Day-count basis of instrument

0 (actual/actual) (default) | integer from 0 to 13

Day-count basis representing the basis used when annualizing the input forward rate, specified as a NINST-by-1 vector of integers.

• 0 = actual/actual

• 1 = 30/360 (SIA)

• 2 = actual/360

• 3 = actual/365

• 4 = 30/360 (PSA)

• 5 = 30/360 (ISDA)

• 6 = 30/360 (European)

• 7 = actual/365 (Japanese)

• 8 = actual/actual (ICMA)

• 9 = actual/360 (ICMA)

• 10 = actual/365 (ICMA)

• 11 = 30/360E (ICMA)

• 12 = actual/365 (ISDA)

• 13 = BUS/252

For more information, see Basis.

Data Types: double

ProjectionCurve — Rate curve used in generating future forward rates

if ProjectionCurve is not specified, then RateSpec is used both for discounting cash flows and projecting future forward rates (default) | structure

The rate curve to be used in generating the future forward rates. This structure must be created using intenvset. Use this optional input if the forward curve is different from the discount curve.

Data Types: struct

Shift — Shift in decimals for shifted Black model

0 (no shift) (default) | positive decimal

Shift in decimals for the shifted Black model, specified using a scalar or NINST-by-1 vector of rate shifts in positive decimals. Set this parameter to a positive rate shift in decimals to add a positive shift to the forward rate and strike, which effectively sets a negative lower bound for the forward rate. For example, a Shift of 0.01 is equal to a 1% shift.

Data Types: double

Output Arguments

FloorPrice — Expected price of floor

vector

Expected price of the floor, returned as a NINST-by-1 vector.

Floorlets — Floorlets

array

Floorlets, returned as a NINST-by-NCF array of floorlets, padded with NaNs.

More About

Floor

A floor is a contract that includes a guarantee setting the minimum interest rate to be received by the holder, based on an otherwise floating interest rate.

The payoff for a floor is:

$$\max (FloorRate-CurrentRate,0)$$

Shifted Black

The Shifted Black model is essentially the same as the Black’s model, except that it models the movements of (F + Shift) as the underlying asset, instead of F (which is the forward rate in the case of floorlets).

This model allows negative rates, with a fixed negative lower bound defined by the amount of shift; that is, the zero lower bound of Black’s model has been shifted.

Algorithms

Black Model

$$\begin{array}{l}dF={\sigma }_{Black}Fdw\\ call=e^{-\gamma T}\left[FN(d_1)-KN(d_2)\right]\\ put=e^{-\gamma T}\left[KN(-d_2)-FN(-d_1)\right]\\ d_1=\frac{\ln \left(\frac{F}{K}\right)+\left(\frac{{\sigma }_B{}^2}{2}\right)T}{{\sigma }_B\sqrt{T}},d_2=d_1-{\sigma }_B\sqrt{T}\\ {\sigma }_B={\sigma }_{Black}\end{array}$$

Where F is the forward value and K is the strike.

Shifted Black Model

$$\begin{array}{l}dF={\sigma }_{Shifted\_Black}\left(F+Shift\right)dw\\ call=e^{-\gamma T}\left[\left(F+Shift\right)N(d_{s1})-\left(K+Shift\right)N(d_{s2})\right]\\ put=e^{-\gamma T}\left[\left(K+Shift\right)N(-d_{s2})-\left(F+Shift\right)N(-d_{s1})\right]\\ d_{s1}=\frac{\ln \left(\frac{F+Shift}{K+Shift}\right)+\left(\frac{{\sigma }_{sB}{}^2}{2}\right)T}{{\sigma }_{sB}\sqrt{T}},d_{s2}=d_{s1}-{\sigma }_{sB}\sqrt{T}\\ {\sigma }_{sB}={\sigma }_{Shifted\_Black}\end{array}$$

Where F+Shift is the forward value and K+Shift is the strike for the shifted version.

Version History

Introduced in R2009a

R2022b: Serial date numbers not recommended

Although floorbyblk supports serial date numbers, datetime values are recommended instead. The datetime data type provides flexible date and time formats, storage out to nanosecond precision, and properties to account for time zones and daylight saving time.

To convert serial date numbers or text to datetime values, use the datetime function. For example:

t = datetime(738427.656845093,"ConvertFrom","datenum");
y = year(t)

y =

        2021

There are no plans to remove support for serial date number inputs.