1 Modelling Term Structures MGT 821/ECON 873 Modelling Term Structures.

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Presentation transcript:

1 Modelling Term Structures MGT 821/ECON 873 Modelling Term Structures

2 Term Structure Models Black’s model is concerned with describing the probability distribution of a single variable at a single point in time A term structure model describes the evolution of the whole yield curve

3 The Zero Curve The process for the instantaneous short rate, r, in the traditional risk-neutral world defines the process for the whole zero curve in this world If P(t, T ) is the price at time t of a zero- coupon bond maturing at time T where is the average r between times t and T

4 Equilibrium Models

5 Mean Reversion Interest rate HIGH interest rate has negative trend LOW interest rate has positive trend Reversion Level

6 Alternative Term Structures in Vasicek & CIR Zero Rate Maturity Zero Rate Maturity Zero Rate Maturity

Affine term structure models Both Vasicek and CIR are affine term structure models 7

8 Equilibrium vs No-Arbitrage Models In an equilibrium model today’s term structure is an output In a no-arbitrage model today’s term structure is an input

9 Developing No-Arbitrage Model for r A model for r can be made to fit the initial term structure by including a function of time in the drift

10 Ho-Lee Model dr =  ( t ) dt +  dz Many analytic results for bond prices and option prices Interest rates normally distributed One volatility parameter,  All forward rates have the same standard deviation

Diagrammatic Representation of Ho-Lee 11 Short Rate r r r r Time

12 Hull-White Model dr = [  ( t ) – ar ] dt +  dz Many analytic results for bond prices and option prices Two volatility parameters, a and  Interest rates normally distributed Standard deviation of a forward rate is a declining function of its maturity

13 Diagrammatic Representation of Hull and White Short Rate r r r r Time Forward Rate Curve

14 Black-Karasinski Model Future value of r is lognormal Very little analytic tractability

15 Options on Zero-Coupon Bonds In Vasicek and Hull-White model, price of call maturing at T on a bond lasting to s is LP (0, s ) N ( h )- KP (0, T ) N ( h -  P ) Price of put is KP (0, T ) N (- h +  P )- LP (0, s ) N ( h ) where

16 Options on Coupon Bearing Bonds In a one-factor model a European option on a coupon-bearing bond can be expressed as a portfolio of options on zero-coupon bonds. We first calculate the critical interest rate at the option maturity for which the coupon- bearing bond price equals the strike price at maturity The strike price for each zero-coupon bond is set equal to its value when the interest rate equals this critical value

17 Interest Rate Trees vs Stock Price Trees The variable at each node in an interest rate tree is the  t-period rate Interest rate trees work similarly to stock price trees except that the discount rate used varies from node to node

18 Two-Step Tree Example Payoff after 2 years is MAX[100(r – 0.11), 0] p u =0.25; p m =0.5; p d =0.25; Time step=1yr 10% 0.35** 12% 1.11* 10% % % 3 12% 1 10% 0 8% 0 6% 0 *: (0.25× × ×0)e –0.12×1 **: (0.25× × ×0)e –0.10×1

19 Alternative Branching Processes in a Trinomial Tree (a)(b)(c)

20 Procedure for Building Tree dr = [  ( t ) – ar ] dt +  dz 1.Assume  ( t ) = 0 and r (0) = 0 2.Draw a trinomial tree for r to match the mean and standard deviation of the process for r 3.Determine  ( t ) one step at a time so that the tree matches the initial term structure

21 Example  = 0.01 a = 0.1  t = 1 year The zero curve is as follows

22 Building the First Tree for the  t rate R Set vertical spacing: Change branching when j max nodes from middle where j max is smallest integer greater than 0.184/( a  t ) Choose probabilities on branches so that mean change in R is - aR  t and S.D. of change is

23 The First Tree A B C D E F G H I Node ABCDEFGHI R 0.000%1.732%0.000%-1.732%3.464%1.732%0.000%-1.732%-3.464% p u p m p d

24 Shifting Nodes Work forward through tree Remember Q ij the value of a derivative providing a $1 payoff at node j at time i  t Shift nodes at time i  t by  i so that the (i+1)  t bond is correctly priced

25 The Final Tree A B C D E F G H I Node ABCDEFGHI R 3.824% 6.937%5.205%3.473%9.716%7.984%6.252%4.520%2.788% p u p m p d

26 Extensions The tree building procedure can be extended to cover more general models of the form: dƒ(r ) = [  (t ) – a ƒ(r )]dt +  dz We set x=f(r) and proceed similarly to before

27 Calibration to determine a and  The volatility parameters a and  (perhaps functions of time) are chosen so that the model fits the prices of actively traded instruments such as caps and European swap options as closely as possible We minimize a function of the form where U i is the market price of the i th calibrating instrument, V i is the model price of the i th calibrating instrument and P is a function that penalizes big changes or curvature in a and 

HJM Model: Notation 28 P ( t, T ):price at time t of a discount bond with principal of $1 maturing at T W t :vector of past and present values of interest rates and bond prices at time t that are relevant for determining bond price volatilities at that time v(t,T,W t ):volatility of P ( t, T )

Notation continued 29 ƒ(t,T 1,T 2 ) :forward rate as seen at t for the period between T 1 and T 2 F(t,T):F(t,T):instantaneous forward rate as seen at t for a contract maturing at T r(t):r(t):short-term risk-free interest rate at t dz(t) :Wiener process driving term structure movements

30 Modeling Bond Prices

31 The process for F(t,T)

32 Tree Evolution of Term Structure is Non-Recombining Tree for the short rate r is non- Markov

33 The LIBOR Market Model The LIBOR market model is a model constructed in terms of the forward rates underlying caplet prices

34 Notation

35 Volatility Structure

36 In Theory the  ’s can be determined from Cap Prices

37 Example If Black volatilities for the first three caplets are 24%, 22%, and 20%, then  0 =24.00%  1 =19.80%  2 =15.23%

38 Example

39 The Process for F k in a One-Factor LIBOR Market Model

40 Rolling Forward Risk-Neutrality It is often convenient to choose a world that is always FRN wrt a bond maturing at the next reset date. In this case, we can discount from t i+1 to t i at the  i rate observed at time t i. The process for F k is

41 The LIBOR Market Model and HJM In the limit as the time between resets tends to zero, the LIBOR market model with rolling forward risk neutrality becomes the HJM model in the traditional risk-neutral world

42 Monte Carlo Implementation of LMM Model

43 Multifactor Versions of LMM LMM can be extended so that there are several components to the volatility A factor analysis can be used to determine how the volatility of F k is split into components

44 Ratchet Caps, Sticky Caps, and Flexi Caps A plain vanilla cap depends only on one forward rate. Its price is not dependent on the number of factors. Ratchet caps, sticky caps, and flexi caps depend on the joint distribution of two or more forward rates. Their prices tend to increase with the number of factors

45 Valuing European Options in the LIBOR Market Model There is an analytic approximation that can be used to value European swap options in the LIBOR market model.

46 Calibrating the LIBOR Market Model In theory the LMM can be exactly calibrated to cap prices as described earlier In practice we proceed as for short rate models to minimize a function of the form where U i is the market price of the i th calibrating instrument, V i is the model price of the i th calibrating instrument and P is a function that penalizes big changes or curvature in a and 

47 Types of Mortgage-Backed Securities (MBSs) Pass-Through Collateralized Mortgage Obligation (CMO) Interest Only (IO) Principal Only (PO)

48 Option-Adjusted Spread (OAS) To calculate the OAS for an interest rate derivative we value it assuming that the initial yield curve is the Treasury curve + a spread We use an iterative procedure to calculate the spread that makes the derivative’s model price = market price. This spread is the OAS.