bdtprice

Instrument prices from Black-Derman-Toy interest-rate tree

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Syntax

[Price,PriceTree] = bdtprice(BDTTree,InstSet)
[Price,PriceTree] = bdtprice(___,Options)

Description

example

[Price,PriceTree] = bdtprice(BDTTree,InstSet) computes arbitrage-free prices for instruments using an interest-rate tree created with bdttree. All instruments contained in a financial instrument variable, InstSet, are priced.

bdtprice handles instrument types: 'Bond', 'CashFlow', 'OptBond', 'OptEmBond', 'OptFloat', 'OptEmFloat', 'Fixed', 'Float', 'Cap', 'Floor', 'RangeFloat', 'Swap'. See instadd to construct defined types.

example

[Price,PriceTree] = bdtprice(___,Options) adds an optional input argument for Options.

Examples

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Load the BDT tree and instruments from the data file deriv.mat to price the cap and bond instruments contained in the instrument set. 

load deriv.mat; 
BDTSubSet = instselect(BDTInstSet,'Type', {'Bond', 'Cap'});

instdisp(BDTSubSet)
instdisp(BDTSubSet)
Index Type CouponRate Settle         Maturity       Period Basis EndMonthRule IssueDate FirstCouponDate LastCouponDate StartDate Face Name     Quantity
1     Bond 0.1        01-Jan-2000    01-Jan-2003    1      NaN   NaN          NaN       NaN             NaN            NaN       NaN  10% Bond 100     
2     Bond 0.1        01-Jan-2000    01-Jan-2004    2      NaN   NaN          NaN       NaN             NaN            NaN       NaN  10% Bond  50     
 
Index Type Strike Settle         Maturity       CapReset Basis Principal Name    Quantity
3     Cap  0.15   01-Jan-2000    01-Jan-2004    1        NaN   NaN       15% Cap 30

Price the bond and cap.

[Price, PriceTree] = bdtprice(BDTTree, BDTSubSet)
Warning: Not all cash flows are aligned with the tree. Result will be approximated. 
> In checktree at 289
  In bdtprice at 85 

Price =

   95.5030
   93.9079
    1.4375


PriceTree = 

    FinObj: 'BDTPriceTree'
     PTree: {[3x1 double]  [3x2 double]  [3x3 double]  [3x4 double]  [3x4 double]}
    AITree: {[3x1 double]  [3x2 double]  [3x3 double]  [3x4 double]  [3x4 double]}
      tObs: [0 1 2 3 4]

You can use the treeviewer function to see the prices of these three instruments along the price tree.

Open Live Script

Price the following multi-stepped coupon bonds using the following data: 

Rates = [0.035; 0.042147; 0.047345; 0.052707];
ValuationDate = 'Jan-1-2010';
StartDates = ValuationDate;
EndDates = {'Jan-1-2011'; 'Jan-1-2012'; 'Jan-1-2013'; 'Jan-1-2014'};
Compounding = 1;

% Create RateSpec
RS = intenvset('ValuationDate', ValuationDate, 'StartDates', StartDates,...
'EndDates', EndDates,'Rates', Rates, 'Compounding', Compounding);

% Create a portfolio of stepped coupon bonds with different maturities
Settle = '01-Jan-2010';
Maturity = {'01-Jan-2011';'01-Jan-2012';'01-Jan-2013';'01-Jan-2014'};
CouponRate = {{'01-Jan-2011' .042;'01-Jan-2012' .05; '01-Jan-2013' .06; '01-Jan-2014' .07}};

% Display the instrument portfolio 
ISet = instbond(CouponRate, Settle, Maturity, 1);
instdisp(ISet)
Index Type CouponRate Settle         Maturity       Period Basis EndMonthRule IssueDate FirstCouponDate LastCouponDate StartDate Face
1     Bond [Cell]     01-Jan-2010    01-Jan-2011    1      0     1            NaN       NaN             NaN            NaN       100 
2     Bond [Cell]     01-Jan-2010    01-Jan-2012    1      0     1            NaN       NaN             NaN            NaN       100 
3     Bond [Cell]     01-Jan-2010    01-Jan-2013    1      0     1            NaN       NaN             NaN            NaN       100 
4     Bond [Cell]     01-Jan-2010    01-Jan-2014    1      0     1            NaN       NaN             NaN            NaN       100

Build a BDTTree to price the stepped coupon bonds. Assume the volatility to be 10%

Sigma = 0.1; 
BDTTimeSpec = bdttimespec(ValuationDate, EndDates, Compounding);
BDTVolSpec = bdtvolspec(ValuationDate, EndDates, Sigma*ones(1, length(EndDates))');
BDTT = bdttree(BDTVolSpec, RS, BDTTimeSpec);

% Compute the price of the stepped coupon bonds
PBDT = bdtprice(BDTT, ISet)
PBDT = 4×1

  100.6763
  100.7368
  100.9266
  101.0115
Open Live Script

Price a portfolio of stepped callable bonds and stepped vanilla bonds using the following data: The data for the interest rate term structure is as follows:

Rates = [0.035; 0.042147; 0.047345; 0.052707];
ValuationDate = 'Jan-1-2010';
StartDates = ValuationDate;
EndDates = {'Jan-1-2011'; 'Jan-1-2012'; 'Jan-1-2013'; 'Jan-1-2014'};
Compounding = 1;

%Create RateSpec
RS = intenvset('ValuationDate', ValuationDate, 'StartDates', StartDates,...
'EndDates', EndDates,'Rates', Rates, 'Compounding', Compounding);

% Create an instrument portfolio of 3 stepped callable bonds and three
% stepped vanilla bonds
Settle = '01-Jan-2010';
Maturity = {'01-Jan-2012';'01-Jan-2013';'01-Jan-2014'};
CouponRate = {{'01-Jan-2011' .042;'01-Jan-2012' .05; '01-Jan-2013' .06; '01-Jan-2014' .07}};
OptSpec='call';
Strike=100;
ExerciseDates='01-Jan-2011'; %Callable in one year

% Bonds with embedded option 
ISet = instoptembnd(CouponRate, Settle, Maturity, OptSpec, Strike,...
ExerciseDates, 'Period', 1);
                    
% Vanilla bonds 
ISet = instbond(ISet, CouponRate, Settle, Maturity, 1);

% Display the instrument portfolio
instdisp(ISet)
Index Type      CouponRate Settle         Maturity       OptSpec Strike ExerciseDates  Period Basis EndMonthRule IssueDate FirstCouponDate LastCouponDate StartDate Face AmericanOpt
1     OptEmBond [Cell]     01-Jan-2010    01-Jan-2012    call    100    01-Jan-2011    1      0     1            NaN       NaN             NaN            NaN       100  0          
2     OptEmBond [Cell]     01-Jan-2010    01-Jan-2013    call    100    01-Jan-2011    1      0     1            NaN       NaN             NaN            NaN       100  0          
3     OptEmBond [Cell]     01-Jan-2010    01-Jan-2014    call    100    01-Jan-2011    1      0     1            NaN       NaN             NaN            NaN       100  0          
 
Index Type CouponRate Settle         Maturity       Period Basis EndMonthRule IssueDate FirstCouponDate LastCouponDate StartDate Face
4     Bond [Cell]     01-Jan-2010    01-Jan-2012    1      0     1            NaN       NaN             NaN            NaN       100 
5     Bond [Cell]     01-Jan-2010    01-Jan-2013    1      0     1            NaN       NaN             NaN            NaN       100 
6     Bond [Cell]     01-Jan-2010    01-Jan-2014    1      0     1            NaN       NaN             NaN            NaN       100

Build a BDTTree and price the instruments. Build the tree Assume the volatility to be 10%

Sigma = 0.1;  
BDTTimeSpec = bdttimespec(ValuationDate, EndDates, Compounding);
BDTVolSpec = bdtvolspec(ValuationDate, EndDates, Sigma*ones(1, length(EndDates))');
BDTT = bdttree(BDTVolSpec, RS, BDTTimeSpec);

%The first three rows corresponds to the price of the stepped callable bonds and the
%last three rows corresponds to the price of the stepped vanilla bonds.
PBDT = bdtprice(BDTT, ISet)
PBDT = 6×1

  100.4799
  100.3228
  100.0840
  100.7368
  100.9266
  101.0115
Open Live Script

Compute the price of a portfolio with range notes and a floating rate note using the following data: The data for the interest rate term structure is as follows:

Rates = [0.035; 0.042147; 0.047345; 0.052707];
ValuationDate = 'Jan-1-2011';
StartDates = ValuationDate;
EndDates = {'Jan-1-2012'; 'Jan-1-2013'; 'Jan-1-2014'; 'Jan-1-2015'};
Compounding = 1;

%  Create RateSpec
RS = intenvset('ValuationDate', ValuationDate, 'StartDates', StartDates,...
'EndDates', EndDates,'Rates', Rates, 'Compounding', Compounding);
  
% Create an instrument portfolio with two range notes and a floating rate
% note with the following data:
Spread = 200;
Settle = 'Jan-1-2011';
Maturity = 'Jan-1-2014';

% First Range Note:
RateSched(1).Dates = {'Jan-1-2012'; 'Jan-1-2013'  ; 'Jan-1-2014'};
RateSched(1).Rates  = [0.045 0.055; 0.0525  0.0675; 0.06 0.08];

% Second Range Note:
RateSched(2).Dates = {'Jan-1-2012'; 'Jan-1-2013' ; 'Jan-1-2014'};
RateSched(2).Rates  = [0.048 0.059; 0.055  0.068 ; 0.07 0.09];

% Create InstSet
InstSet = instadd('RangeFloat', Spread, Settle, Maturity, RateSched);

% Add a floating-rate note
InstSet = instadd(InstSet, 'Float', Spread, Settle, Maturity);

% Display the portfolio instrument
instdisp(InstSet)
Index Type       Spread Settle         Maturity       RateSched FloatReset Basis Principal EndMonthRule
1     RangeFloat 200    01-Jan-2011    01-Jan-2014    [Struct]  1          0     100       1           
2     RangeFloat 200    01-Jan-2011    01-Jan-2014    [Struct]  1          0     100       1           
 
Index Type  Spread Settle         Maturity       FloatReset Basis Principal EndMonthRule CapRate FloorRate
3     Float 200    01-Jan-2011    01-Jan-2014    1          0     100       1            Inf     -Inf

Build a BDTTree and price the instruments. Build the tree Assume the volatility to be 10%.

Sigma = 0.1;  
BDTTS = bdttimespec(ValuationDate, EndDates, Compounding);
BDTVS = bdtvolspec(ValuationDate, EndDates, Sigma*ones(1, length(EndDates))');
BDTT = bdttree(BDTVS, RS, BDTTS);

% Price the portfolio 
Price = bdtprice(BDTT, InstSet)
Price = 3×1

  100.2841
   98.0757
  105.5147
Open Live Script

Use instswap to create a float-float swap and price the swap with bdtprice. 

RateSpec = intenvset('Rates',.05,'StartDate',today,'EndDate',datemnth(today,60));
IS = instswap([.02 .03],today,datemnth(today,60),[], [], [], [1 1]);
VolSpec = bdtvolspec(today,datemnth(today,[10 60]),[.01 .02]);
TimeSpec = bdttimespec(today,cfdates(today,datemnth(today,60),1));
BDTTree = bdttree(VolSpec,RateSpec,TimeSpec);
bdtprice(BDTTree,IS)
ans = -4.3220

Use instswap to create multiple swaps and price the swaps with bdtprice.

RateSpec = intenvset('Rates',.05,'StartDate',today,'EndDate',datemnth(today,60));
IS = instswap([.03 .02],today,datemnth(today,60),[], [], [], [1 1]);
IS = instswap(IS,[200 300],today,datemnth(today,60),[], [], [], [0 0]);
IS = instswap(IS,[.08 300],today,datemnth(today,60),[], [], [], [1 0]);
VolSpec = bdtvolspec(today,datemnth(today,[10 60]),[.01 .02]);
TimeSpec = bdttimespec(today,cfdates(today,datemnth(today,60),1));
BDTTree = bdttree(VolSpec,RateSpec,TimeSpec);
bdtprice(BDTTree,IS)

ans =

    4.3220
   -4.3220
   -0.2701

Input Arguments

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Interest-rate tree structure, specified by using bdttree.

Data Types: struct

Instrument variable containing a collection of NINST instruments, specified using instadd. Instruments are categorized by type; each type can have different data fields. The stored data field is a row vector or character vector for each instrument.

Data Types: struct

(Optional) Derivatives pricing options structure, created using derivset.

Data Types: struct

Output Arguments

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Price for each instrument at time 0, returned as a NINST-by-1 vector. The prices are computed by backward dynamic programming on the interest-rate tree. If an instrument cannot be priced, a NaN is returned in that entry.

Related single-type pricing functions are:

  • bondbybdt — Price a bond from a BDT tree.

  • capbybdt — Price a cap from a BDT tree.

  • cfbybdt — Price an arbitrary set of cash flows from a BDT tree.

  • fixedbybdt — Price a fixed-rate note from a BDT tree.

  • floatbybdt — Price a floating-rate note from a BDT tree.

  • floorbybdt — Price a floor from a BDT tree.

  • optbndbybdt — Price a bond option from a BDT tree.

  • optfloatbybdt — Price a floating-rate note with an option from a BDT tree.

  • optemfloatbybdt — Price a floating-rate note with an embedded option from a BDT tree.

  • optembndbybdt — Price a bond with embedded option by a BDT tree.

  • rangefloatbybdt — Price range floating note using a BDT tree.

  • swapbybdt — Price a swap from a BDT tree.

  • swaptionbybdt — Price a swaption from a BDT tree.

Tree structure of instrument prices, returned as a MATLAB® structure of trees containing vectors of instrument prices and accrued interest, and a vector of observation times for each node. Within PriceTree:

  • PriceTree.PTree contains the clean prices.

  • PriceTree.AITree contains the accrued interest.

  • PriceTree.tObs contains the observation times.

See Also

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Topics

Introduced before R2006a

Financial Instruments Toolbox Documentation
Support
A Practical Guide to Modeling Financial Risk with MATLAB

A Practical Guide to Modeling Financial Risk with MATLAB

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