# swapbybk

Price swap instrument from Black-Karasinski interest-rate tree

## Syntax

## Description

`[`

prices a swap instrument from a Black-Karasinski interest-rate tree.
`Price`

,`PriceTree`

,`CFTree`

,`SwapRate`

]
= swapbybk(`BKTree`

,`LegRate`

,`Settle`

,`Maturity`

)`swapbybk`

computes prices of vanilla swaps, amortizing swaps and
forward swaps.

**Note**

Alternatively, you can use the `Swap`

object to price swap
instruments. For more information, see Get Started with Workflows Using Object-Based Framework for Pricing Financial Instruments.

## Examples

### Price an Interest-Rate Swap

Price an interest-rate swap with a fixed receiving leg and a floating paying leg. Payments are made once a year, and the notional principal amount is $100. The values for the remaining arguments are:

Coupon rate for fixed leg: 0.06 (6%)

Spread for floating leg: 20 basis points

Swap settlement date: Jan. 01, 2004

Swap maturity date: Jan. 01, 2006

Based on the information above, set the required arguments and build the `LegRate`

, `LegType`

, and `LegReset`

matrices:

Settle = datetime(2004,1,1); Maturity = datetime(2006,1,1); Basis = 0; Principal = 100; LegRate = [0.06 20]; % [CouponRate Spread] LegType = [1 0]; % [Fixed Float] LegReset = [1 1]; % Payments once per year

Price the swap using the `BKTree`

included in the MAT-file `deriv.mat`

. `BKTree`

contains the time and forward-rate information needed to price the instrument.

`load deriv.mat;`

Use `swapbybk`

to price of the swap.

Price = swapbybk(BKTree, LegRate,... Settle, Maturity, LegReset, Basis, Principal, LegType)

Price = 5.0425

Using the previous data, calculate the swap rate, which is the coupon rate for the fixed leg, such that the swap price at time = 0 is zero.

LegRate = [NaN 20]; [Price, PriceTree, SwapRate] = swapbybk(BKTree, LegRate,... Settle, Maturity, LegReset, Basis, Principal, LegType)

Price = -2.8422e-14

`PriceTree = `*struct with fields:*
FinObj: 'BKPriceTree'
PTree: {[-2.8422e-14] [-0.4327 -0.3749 -0.3180] [0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0]}
tObs: [0 1 2 3 4]
Connect: {[2] [2 3 4] [2 2 3 4 4]}
Probs: {[3x1 double] [3x3 double] [3x5 double]}

SwapRate = 0.0336

### Price an Amortizing Swap

Price an amortizing swap using the `Principal`

input argument to define the amortization schedule.

Create the `RateSpec`

.

Rates = 0.035; ValuationDate = datetime(2011,1,1); StartDates = ValuationDate; EndDates = datetime(2017,1,1); Compounding = 1; RateSpec = intenvset('ValuationDate', ValuationDate,'StartDates', StartDates,... 'EndDates', EndDates,'Rates', Rates, 'Compounding', Compounding)

`RateSpec = `*struct with fields:*
FinObj: 'RateSpec'
Compounding: 1
Disc: 0.8135
Rates: 0.0350
EndTimes: 6
StartTimes: 0
EndDates: 736696
StartDates: 734504
ValuationDate: 734504
Basis: 0
EndMonthRule: 1

Create the swap instrument using the following data:

Settle ='1-Jan-2011'; Maturity = '1-Jan-2017'; Period = 1; LegRate = [0.04 10];

Define the swap amortizing schedule.

Principal ={{datetime(2013,1,1) 100;datetime(2014,1,1) 80;datetime(2015,1,1) 60;datetime(2016,1,1) 40;datetime(2017,1,1) 20}};

Build the BK tree and assume volatility is 10%.

```
MatDates = [datetime(2012,1,1) ; datetime(2013,1,1) ; datetime(2014,1,1) ; datetime(2015,1,1) ; datetime(2016,1,1) ; datetime(2017,1,1)];
BKTimeSpec = bktimespec(ValuationDate, MatDates);
Volatility = 0.10;
AlphaDates = datetime(2017,1,1);
AlphaCurve = 0.1;
BKVolSpec = bkvolspec(ValuationDate, MatDates, Volatility*ones(1,length(MatDates))',...
AlphaDates, AlphaCurve);
BKT = bktree(BKVolSpec, RateSpec, BKTimeSpec);
```

Compute the price of the amortizing swap.

`Price = swapbybk(BKT, LegRate, Settle, Maturity, 'Principal' , Principal)`

Price = 1.4574

### Price a Forward Swap

Price a forward swap using the `StartDate`

input argument to define the future starting date of the swap.

Create the `RateSpec`

.

Rates = 0.0374; ValuationDate = datetime(2012,1,1); StartDates = ValuationDate; EndDates = datetime(2018,1,1); Compounding = 1; RateSpec = intenvset('ValuationDate', ValuationDate,'StartDates', StartDates,... 'EndDates', EndDates,'Rates', Rates, 'Compounding', Compounding)

`RateSpec = `*struct with fields:*
FinObj: 'RateSpec'
Compounding: 1
Disc: 0.8023
Rates: 0.0374
EndTimes: 6
StartTimes: 0
EndDates: 737061
StartDates: 734869
ValuationDate: 734869
Basis: 0
EndMonthRule: 1

Build a BK tree.

VolDates = [datetime(2013,1,1) ; datetime(2014,1,1) ; datetime(2015,1,1) ; datetime(2016,1,1) ; datetime(2017,1,1) ; datetime(2018,1,1)]; VolCurve = 0.1; AlphaDates = datetime(2018,1,1); AlphaCurve = 0.1; BKVolSpec = bkvolspec(RateSpec.ValuationDate, VolDates, VolCurve,... AlphaDates, AlphaCurve); BKTimeSpec = bktimespec(RateSpec.ValuationDate, VolDates, Compounding); BKT = bktree(BKVolSpec, RateSpec, BKTimeSpec);

Compute the price of a forward swap that starts in a year (Jan 1, 2013) and matures in four years with a forward swap rate of 4.25%.

```
Settle = datetime(2012,1,1);
Maturity = datetime(2017,1,1);
StartDate = datetime(2013,1,1);
LegRate = [0.0425 10];
Price = swapbybk(BKT, LegRate, Settle, Maturity, 'StartDate', StartDate)
```

Price = 1.4434

Using the previous data, compute the forward swap rate, the coupon rate for the fixed leg, such that the forward swap price at time = 0 is zero.

```
LegRate = [NaN 10];
[Price, ~,SwapRate] = swapbybk(BKT, LegRate, Settle, Maturity, 'StartDate', StartDate)
```

Price = 1.4211e-14

SwapRate = 0.0384

## Input Arguments

`BKTree`

— Interest-rate structure

structure

Interest-rate tree structure, created by `bktree`

**Data Types: **`struct`

`LegRate`

— Leg rate

matrix

Leg rate, specified as a `NINST`

-by-`2`

matrix,
with each row defined as one of the following:

`[CouponRate Spread]`

(fixed-float)`[Spread CouponRate]`

(float-fixed)`[CouponRate CouponRate]`

(fixed-fixed)`[Spread Spread]`

(float-float)

`CouponRate`

is the decimal annual rate.
`Spread`

is the number of basis points over the reference rate. The
first column represents the receiving leg, while the second column represents the
paying leg.

**Data Types: **`double`

`Settle`

— Settlement date

datetime array | string array | date character vector

Settlement date, specified either as a scalar or
`NINST`

-by-`1`

vector using a datetime array, string
array, or date character vectors.

To support existing code, `swapbybk`

also
accepts serial date numbers as inputs, but they are not recommended.

The `Settle`

date for every swap is set to the
`ValuationDate`

of the BK tree. The swap argument
`Settle`

is ignored.

`Maturity`

— Maturity date

datetime array | string array | date character vector

Maturity date, specified as a `NINST`

-by-`1`

vector using a
datetime array, string array, or date character vectors representing the maturity date
for each swap.

To support existing code, `swapbybk`

also
accepts serial date numbers as inputs, but they are not recommended.

### 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: **`[Price,PriceTree,CFTree,SwapRate] = swapbybk(BKTree,LegRate,Settle,Maturity,LegReset,Basis,Principal,LegType)`

`LegReset`

— Reset frequency per year for each swap

`[1 1]`

(default) | vector

Reset frequency per year for each swap, specified as the comma-separated pair consisting of
`'LegReset'`

and a `NINST`

-by-`2`

vector.

**Data Types: **`double`

`Basis`

— Day-count basis representing the basis for each leg

`0`

(actual/actual) (default) | integer from `0`

to `13`

Day-count basis representing the basis for each leg, specified as the comma-separated pair
consisting of `'Basis'`

and a
`NINST`

-by-`1`

array (or
`NINST`

-by-`2`

if `Basis`

is
different for each leg).

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`

`Principal`

— Notional principal amounts or principal value schedules

`100`

(default) | vector or cell array

Notional principal amounts or principal value schedules, specified as the comma-separated pair
consisting of `'Principal'`

and a vector or cell array.

`Principal`

accepts a `NINST`

-by-`1`

vector
or `NINST`

-by-`1`

cell array (or `NINST`

-by-`2`

if `Principal`

is
different for each leg) of the notional principal amounts or principal
value schedules. For schedules, each element of the cell array is
a `NumDates`

-by-`2`

array where
the first column is dates and the second column is its associated
notional principal value. The date indicates the last day that the
principal value is valid.

**Data Types: **`cell`

| `double`

`LegType`

— Leg type

`[1 0]`

for each instrument (default) | matrix with values `[1 1]`

(fixed-fixed), ```
[1
0]
```

(fixed-float), `[0 1]`

(float-fixed),
or `[0 0]`

(float-float)

Leg type, specified as the comma-separated pair consisting of `'LegType'`

and
a `NINST`

-by-`2`

matrix with values ```
[1
1]
```

(fixed-fixed), `[1 0]`

(fixed-float), ```
[0
1]
```

(float-fixed), or `[0 0]`

(float-float). Each row
represents an instrument. Each column indicates if the corresponding leg is fixed
(`1`

) or floating (`0`

). This matrix defines the
interpretation of the values entered in `LegRate`

.
`LegType`

allows `[1 1]`

(fixed-fixed),
`[1 0]`

(fixed-float), `[0 1]`

(float-fixed), or
`[0 0]`

(float-float) swaps

**Data Types: **`double`

`Options`

— Derivatives pricing options structure

structure

Derivatives pricing options structure, specified as the comma-separated pair consisting of
`'Options'`

and a structure obtained from using `derivset`

.

**Data Types: **`struct`

`EndMonthRule`

— End-of-month rule flag for generating dates when `Maturity`

is end-of-month date for month having 30 or fewer days

`1`

(in effect) (default) | nonnegative integer `[0,1]`

End-of-month rule flag for generating dates when `Maturity`

is an
end-of-month date for a month having 30 or fewer days, specified as the
comma-separated pair consisting of `'EndMonthRule'`

and a nonnegative
integer [`0`

, `1`

] using a
`NINST`

-by-`1`

(or
`NINST`

-by-`2`

if `EndMonthRule`

is different for each leg).

`0`

= Ignore rule, meaning that a payment date is always the same numerical day of the month.`1`

= Set rule on, meaning that a payment date is always the last actual day of the month.

**Data Types: **`logical`

`AdjustCashFlowsBasis`

— Flag to adjust cash flows based on actual period day count

`false`

(default) | value of `0`

(false) or `1`

(true)

Flag to adjust cash flows based on actual period day count, specified as the comma-separated
pair consisting of `'AdjustCashFlowsBasis'`

and a
`NINST`

-by-`1`

(or
`NINST`

-by-`2`

if
`AdjustCashFlowsBasis`

is different for each leg) of logicals with
values of `0`

(false) or `1`

(true).

**Data Types: **`logical`

`BusinessDayConvention`

— Business day conventions

`actual`

(default) | character vector | cell array of character vectors

Business day conventions, specified as the comma-separated pair consisting of
`'BusinessDayConvention'`

and a character vector or a
`N`

-by-`1`

(or
`NINST`

-by-`2`

if
`BusinessDayConvention`

is different for each leg) cell array of
character vectors of business day conventions. The selection for business day
convention determines how non-business days are treated. Non-business days are defined
as weekends plus any other date that businesses are not open (e.g. statutory
holidays). Values are:

`actual`

— Non-business days are effectively ignored. Cash flows that fall on non-business days are assumed to be distributed on the actual date.`follow`

— Cash flows that fall on a non-business day are assumed to be distributed on the following business day.`modifiedfollow`

— Cash flows that fall on a non-business day are assumed to be distributed on the following business day. However if the following business day is in a different month, the previous business day is adopted instead.`previous`

— Cash flows that fall on a non-business day are assumed to be distributed on the previous business day.`modifiedprevious`

— Cash flows that fall on a non-business day are assumed to be distributed on the previous business day. However if the previous business day is in a different month, the following business day is adopted instead.

**Data Types: **`char`

| `cell`

`Holidays`

— Holidays used in computing business days

if not specified, the default is to use
`holidays.m`

(default) | MATLAB^{®} dates

Holidays used in computing business days, specified as the comma-separated pair consisting of
`'Holidays'`

and MATLAB dates using a `NHolidays`

-by-`1`

vector.

**Data Types: **`datetime`

`StartDate`

— Date swap actually starts

`Settle`

date (default) | datetime array | string array | date character vector

Date swap actually starts, specified as the comma-separated pair consisting of
`'StartDate'`

and a
`NINST`

-by-`1`

vector using a datetime array,
string array, or date character vectors.

To support existing code, `swapbybk`

also
accepts serial date numbers as inputs, but they are not recommended.

Use this argument to price forward swaps, that is, swaps that start in a future date

## Output Arguments

`Price`

— Expected swap prices at time 0

vector

Expected swap prices at time 0, returned as a `NINST`

-by-`1`

vector.

`PriceTree`

— Tree structure of instrument prices

structure

Tree structure of instrument prices, returned as a MATLAB structure
of trees containing vectors of swaption instrument prices and a vector
of observation times for each node. Within `PriceTree`

:

`PriceTree.PTree`

contains the clean prices.`PriceTree.tObs`

contains the observation times.`PriceTree.Connect`

contains the connectivity vectors. Each element in the cell array describes how nodes in that level connect to the next. For a given tree level, there are`NumNodes`

elements in the vector, and they contain the index of the node at the next level that the middle branch connects to. Subtracting 1 from that value indicates where the up-branch connects to, and adding 1 indicated where the down branch connects to.`PriceTree.Probs`

contains the probability arrays. Each element of the cell array contains the up, middle, and down transition probabilities for each node of the level.

`CFTree`

— Swap cash flows

structure

Swap cash flows, returned as a tree structure with a vector
of the swap cash flows at each node. This structure contains only `NaN`

s
because with binomial recombining trees, cash flows cannot be computed
accurately at each node of a tree.

`SwapRate`

— Rates applicable to fixed leg

matrix

Rates applicable to the fixed leg, returned as a `NINST`

-by-`1`

vector
of rates applicable to the fixed leg such that the swaps’ values
are zero at time 0. This rate is used in calculating the swaps’
prices when the rate specified for the fixed leg in `LegRate`

is `NaN`

.
The `SwapRate`

output is padded with `NaN`

for
those instruments in which `CouponRate`

is not set
to `NaN`

.

## More About

### Amortizing Swap

In an amortizing swap, the notional principal decreases periodically because it is tied to an underlying financial instrument with a declining (amortizing) principal balance, such as a mortgage.

### Forward Swap

Agreement to enter into an interest-rate swap arrangement on a fixed date in future.

## Version History

**Introduced before R2006a**

### R2022b: Serial date numbers not recommended

Although `swapbybk`

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.

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