Skip to main content
Log in

Long-Term Yield in an Affine HJM Framework on \(S_{d}^{+}\)

  • Published:
Applied Mathematics & Optimization Submit manuscript

Abstract

We develop the HJM framework for forward rates driven by affine processes on the state space of symmetric positive semidefinite matrices. In this setting we find an explicit representation for the long-term yield in terms of the model parameters. This generalises the results of El Karoui et al. (Rev Deriv Res 1(4):351–369, 1997) and Biagini and Härtel (Int J Theor Appl Financ 17(3):1–24, 2012), where the long-term yield is investigated under no-arbitrage assumptions in a HJM setting using Brownian motions and Lévy processes respectively.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. For \(\alpha \) and \(\sigma \) we write the shortened version \(\alpha \!\left( s,T\right) := \alpha \!\left( \omega ,s,T\right) \) and \(\sigma \!\left( s,T\right) := \sigma \!\left( \omega ,s,T\right) \).

References

  1. Ahdida, A., Alfonsi, A.: Exact and high order discretization schemes for Wishart processes and their affine extensions. Ann. Appl. Probab. 23(3), 1025–1073 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  2. Ang, A., Piazzesi, M.: A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables. J. Monet. Econ. 50(4), 745–787 (2003)

    Article  Google Scholar 

  3. Applebaum, D.: Lévy Processes and Stochastic Calculus, 1st edn. Cambridge University Press, Cambridge (2004)

    Book  MATH  Google Scholar 

  4. Bauer, H.: Wahrscheinlichkeitstheorie, 5th edn. Walter de Gruyter, Berlin (2002)

    MATH  Google Scholar 

  5. Benabid, A., Bensusan, H., El Karoui, N.: Wishart stochastic volatility: asymptotic smile and numerical framework. HAL Working Paper (2010). HAL: http://hal.archives-ouvertes.fr/docs/00/45/83/71/PDF/ArticleWishart19Feb2010

  6. Biagini, F., Härtel, M.: Behavior of long-term yields in a Lévy term structure. Int. J. Theor. Appl. Financ. 17(3), 1–24 (2014)

    Article  MATH  Google Scholar 

  7. Björk, T., Kabanov, Y., Runggaldier, W.: Bond market structure in the presence of marked point processes. Math. Financ. 7(2), 211–223 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  8. Brigo, D., Mercurio, F.: Interest Rate Models: Theory and Practice, 2nd edn. Springer Finance, Heidelberg (2006)

    MATH  Google Scholar 

  9. Bru, M.F.: Wishart processes. J. Theor. Probab. 4(4), 725–751 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  10. Carmona, R., Tehranchi, M.: Interest Rate Models: An Infinite Dimensional Stochastic Analysis Perspective, 1st edn. Springer Finance, Heidelberg (2006)

    MATH  Google Scholar 

  11. Chiarella, C., Kwon, O.K.: Finite dimensional affine realisations of HJM models in terms of forward rates and yields. Rev. Deriv. Res. 6, 129–155 (2003)

    Article  MATH  Google Scholar 

  12. Cuchiero, C.: Affine and polynomial processes. PhD Thesis, ETH Zurich (2011)

  13. Cuchiero, C., Filipović, D., Mayerhofer, E., Teichmann, J.: Affine processes on positive semidefinite matrices. Ann. Appl. Probab. 21(2), 397–463 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  14. Cuchiero, C., Keller-Ressel, M., Mayerhofer, E., Teichmann, J.: Affine processes on symmetric cones. J. Theor. Probab. (2014). doi:10.1007/s10959-014-0580-x

    MATH  Google Scholar 

  15. Da Fonseca, J., Grasselli, M.: Riding on the smiles. Quan. Financ. 11(11), 1609–1632 (2011)

    Article  Google Scholar 

  16. Da Fonseca, J., Grasselli, M., Tebaldi, C.: A multifactor volatility Heston model. Quant. Financ. 8(6), 591–604 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  17. Da Fonseca, J., Gnoatto, A., Grasselli, M.: A flexible matrix Libor model with smiles. J. Econ. Dyn. Control 37, 774–793 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  18. Da Fonseca, J., Grasselli, M., Ielpo, F.: Estimating the Wishart affine stochastic correlation model using the empirical characteristic function. Stud. Nonlinear Dyn. Econom. 18(3), 253–289 (2013)

    MathSciNet  MATH  Google Scholar 

  19. Diebold, F., Rudebusch, G.D., Aruoba, S.B.: The macroeconomy and the yield curve: a dynamic latent factor approach. J. Econom. 131(1–2), 309–338 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  20. Duffie, D., Kan, R.: A yield-factor model of interest rates. Math. Financ. 6(4), 379–406 (1996)

    Article  MATH  Google Scholar 

  21. Duffie, D., Filipović, D., Schachermayer, W.: Affine processes and applications in finance. Ann. Appl. Probab. 13(3), 984–1053 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  22. Dybvig, P.H., Ingersoll, J.E., Ross, S.A.: Long forward and zero-coupon rates can never fall. J. Bus. 69(1), 1–25 (1996)

    Article  Google Scholar 

  23. El Karoui, N., Frachot, A., Geman, H.: A note on the behavior of long zero coupon rates in a no arbitrage framework. Rev. Deriv. Res. 1(4), 351–369 (1997)

    Google Scholar 

  24. European Central Bank: Long-term interest rates for EU member states (2013). ECB: http://www.ecb.int/stats/money/long/html/index.en.html. Accessed 21 Aug 2015

  25. Filipović, D.: Term Structure Models–A Graduate Course, 1st edn. Springer, Berlin (2009)

    Book  MATH  Google Scholar 

  26. Georgii, H.-O.: Stochastik, 1st edn. Walter de Gruyter, Berlin (2004)

    MATH  Google Scholar 

  27. Gnoatto, A.: The Wishart short-rate model. Int. J. Theor. Appl. Financ. 15(8), 1250056 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  28. Gnoatto, A., Grasselli, M.: The explicit Laplace transform for the Wishart process. J. Appl. Probab. 51(3), 640–656 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  29. Goldammer, V., Schmock, U.: Generalization of the Dybvig-Ingersoll-Ross theorem and asymptotic minimality. Math. Financ. 22(1), 185–213 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  30. Gourieroux, C.: Continuous time Wishart process for stochastic risk. Econom. Rev. 25, 177–217 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  31. Gourieroux, C., Sufana, R.: Derivative pricing with Wishart multivariate stochastic volatility. J. Bus. Econ. Stat. 28(3), 438–451 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  32. Grasselli, M., Tebaldi, C.: Solvable affine term structure models. Math. Financ. 18(1), 135–153 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  33. Gürkaynak, R., Sack, B., Swanson, E.: The sensitivity of long-term interest rates to economic news: evidence and implications for macroeconomic news. Am. Econ. Rev. 95(1), 425–436 (2005)

    Article  Google Scholar 

  34. Hansen, L.P., Scheinkman, J.A.: Pricing growth-rate risk. Financ. Stoch. 16(1), 1–15 (2012)

    Article  Google Scholar 

  35. Härtel, M.: The asymptotic behavior of the term structure of interest rates. PhD Thesis, LMU Munich (2016)

  36. Heath, D., Jarrow, R., Morton, A.: Bond pricing and the term structure of interest rates: a new methodology. Econometrica 60(1), 77–105 (1992)

    Article  MATH  Google Scholar 

  37. Hördahl, P., Tristani, O., Vestin, D.: A joint econometric model of macroeconomic and term-structure dynamics. J. Econom. 131(1–2), 405–444 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  38. Hubalek, F., Klein, I., Teichmann, J.: A general proof of the Dybvig-Ingersoll-Ross-theorem. Math. Financ. 12(4), 447–451 (2002)

    Article  MATH  Google Scholar 

  39. Jacod, J., Shiryaev, A.N.: Limit Theorems for Stochastic Processes, 1st edn. Springer, Berlin (2003)

    Book  MATH  Google Scholar 

  40. Kardaras, C., Platen, E.: On the Dybvig-Ingersoll-Ross theorem. Math. Financ. 22(4), 729–740 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  41. Kim, D.H., Wright, J.H.: An arbitrage-free three factor term structure model and the recent behavior of long-term yields and distant-horizon forward rates. Fed. Reserv. Board Financ. Econ. Discuss. Ser. 33, 2005 (2005)

  42. Klenke, A.: Wahrscheinlichkeitstheorie, 1st edn. Springer, Berlin (2006)

    MATH  Google Scholar 

  43. Mankiw, N.G., Summers, L.H., Weiss, L.: Do long-term interest rates overreact to short-term interest rates? Brook. Pap. Econ. Activity 1984(1), 223–247 (1984)

    Article  Google Scholar 

  44. Mayerhofer, E.: Affine processes on positive semidefinite \(d \times d\) matrices have jumps of finite variation in dimension \(d > 1\). Stoch. Process. Appl. 122(10), 3445–3459 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  45. Mayerhofer, E., Pfaffel, O., Stelzer, R.: On strong solutions for positive definite jump-diffusions. Stoch. Process. Appl. 121(9), 2072–2086 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  46. McCulloch, J.H.: Long forward and zero-coupon rates indeed can never fall. Working Paper # 00(12), Ohio State University (2000)

  47. Muhle-Karbe, J., Pfaffel, O., Stelzer, R.: Option pricing in multivariate stochastic volatility models of OU type. SIAM J. Financ. Math. 3(1), 66–94 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  48. Pfaffel, O.: Wishart Processes. Student Research project supervised by Claudia Klüppelberg and Robert Stelzer, TU Munich (2008)

    Google Scholar 

  49. Protter, P.: Stochastic Integration and Differential Equations, 2nd edn. Springer, Berlin (2005)

    Book  Google Scholar 

  50. Richter, A.: Explicit solutions to quadratic BSDEs and applications to utility maximization in multivariate affine stochastic volatility models. Stoch. Process. Appl. 124(11), 3578–3611 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  51. Schulze, K.: Asymptotic maturity behavior of the term structure. Bonn Econ Discussion Papers, University of Bonn (2008)

  52. Shiller, R.J.: The volatility of long-term interest rates and expectations models of the term structure. J. Polit. Econ. 87(6), 1190–1219 (1979)

    Article  Google Scholar 

  53. Yao, Y.: Term structure modeling and asymptotic long rate. Insurance 25, 327–336 (1999)

    MATH  Google Scholar 

  54. Yao, Y.: Term structure models: a perspective from the long rate. N. Am. Actuar. J. 3(3), 122–138 (2000)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

The research leading to these results has received funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement No. [228087].

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Francesca Biagini.

Appendix 1

Appendix 1

Here we provide the proofs of Proposition 3.1 and Theorem 3.1. The results follow by applying the Fubini theorem for integrable functions (cf.  Theorem 14.16 in Chap. 14 of [42]) and the stochastic Fubini theorem (cf.  Theorem 65 in Chap. IV of [49]). For further details on the following computations, we refer to [35].

Proof of Proposition 3.1

Let us introduce for every maturity \(T > 0\) the quantity

$$\begin{aligned} Z\!\left( t,T\right) := -\int _{t}^{T} f\!\left( t,u\right) \, du, \end{aligned}$$
(5.7)

for all \(0 \le t \le T\). From the dynamics of the forward rate (3.1) we deduce that for all \(T > 0\)

$$\begin{aligned} Z\!\left( t,T\right) \mathop {=}\limits ^{(5.7)} -\int _{t}^{T} \! f\!\left( 0,u\right) \, du - \int _{t}^{T} \! \int _{0}^{t} \! \alpha \!\left( s,u\right) \, ds \, du - \int _{t}^{T} \! \int _{0}^{t} \! {\text {Tr}}\!\left[ \sigma \!\left( s,u\right) dX_s \right] du, \end{aligned}$$
(5.8)

for all \(0 \le t \le T\). By combining (2.11), (3.3), (5.8), and (3.13), we derive the following identity

$$\begin{aligned} Z\!\left( t,T\right)&\mathop {=}\limits ^{(5.8)} Z\!\left( 0,T\right) \!+\! \int _{0}^{t} \! f\!\left( 0,u\right) \, du \!-\! \int _{t}^{T} \! \int _{0}^{t} \! \alpha \!\left( s,u\right) \, ds \, du \!-\! \int _{t}^{T} \! \int _{0}^{t} \! {\text {Tr}}\!\left[ \sigma \!\left( s,u\right) dX_{s} \right] du\\&\mathop {=}\limits ^{(3.13)} Z\!\left( 0,T\right) + \int _{0}^{t} \! r_{s} \, ds -\int _{0}^{t} \! \int _{s}^{T}\! \alpha \!\left( s,u\right) \, du \, ds - \int _{0}^{t} \! \int _{s}^{T}\! {\text {Tr}}\!\left[ \sigma \!\left( s,u\right) \, du \, dX_{s} \right] \\&\mathop {=}\limits _{(3.3)}^{(2.11)} Z\!\left( 0,T\right) + \int _{0}^{t} \! r_{s} \, ds -\int _{0}^{t} \! \int _{s}^{T}\! \alpha \!\left( s,u\right) \, du \, ds \\&\quad +\! \int _{0}^{t} \!{\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \left( \sqrt{X_{s}}\,dW_{s}\,Q + Q^{\top } dW_{s}^{\top } \sqrt{X_{s}}\right) \right] \\&\quad +\! \int _{0}^{t} {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \left( b +\! B\!\left( X_{s}\right) \right) \right] ds +\! \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \xi \right] \mu ^{X\!}\!\left( ds,d\xi \right) . \end{aligned}$$

Note that in general for \(A, B \in \mathcal {M}_{d}\) with A symmetric, i.e. \(A \in S_{d}\), it holds

$$\begin{aligned} {\text {Tr}}\!\left[ A \left( B + B^{\top }\right) \right]&= {\text {Tr}}\!\left[ A B \right] + {\text {Tr}}\!\left[ A B^{\top } \right] = {\text {Tr}}\!\left[ A B \right] + {\text {Tr}}\!\left[ \left( B A\right) ^{\top } \right] \nonumber \\&= {\text {Tr}}\!\left[ A B \right] + {\text {Tr}}\left[ B A \right] = 2 {\text {Tr}}\!\left[ A B \right] . \end{aligned}$$
(5.9)

Therefore, we get due to \(\sigma \!\left( s,t\right) \in S_{d}\) for all \(s, t \ge 0\) that

$$\begin{aligned} Z\!\left( t,T\right)&\mathop {=}\limits ^{(5.9)} Z\!\left( 0,T\right) \!+\! \int _{0}^{t} \! r_{s} \, ds \!-\!\int _{0}^{t} \! \int _{s}^{T}\! \alpha \!\left( s,u\right) \, du \, ds \!+\! 2 \int _{0}^{t} \! {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW_{s}\, Q \right] \nonumber \\&\quad +\! \int _{0}^{t} {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \left( b +\! B\!\left( X_{s}\right) \right) \right] ds +\! \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \xi \right] \mu ^{X\!}\!\left( ds,d\xi \right) . \end{aligned}$$
(5.10)

Note that for all \(0 \le t \le T\)

$$\begin{aligned} \Delta Z\!\left( t,T\right) = {\text {Tr}}\left[ \Sigma \!\left( t,T\right) \Delta X_{t}\right] . \end{aligned}$$
(5.11)

With the help of (5.10) and the fact that

$$\begin{aligned} \left\langle W_{lm}, W_{ru} \right\rangle _{s} = \left\{ \begin{array}{ll} s &{}\quad \text {if}\; l = r\; \text {and}\; m = u,\\ 0 &{}\quad \text {else,} \end{array}\right. \end{aligned}$$
(5.12)

we can calculate the quadratic variation of Z for all \(T > 0\) follows

$$\begin{aligned} \left\langle Z\!\left( \,\cdot ,T\right) \right\rangle _{t}^{c}&= \left\langle {\text {Tr}}\!\left[ \int _{0}^{\cdot }\! \Sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW_{s}\, Q\right] \right\rangle _{t} \mathop {=}\limits ^{(5.12)} 4 \int _{0}^{t}\! {\text {Tr}}\!\left[ Q\, \Sigma \!\left( s,T\right) X_{s}\, \Sigma \!\left( s,T\right) Q^{\top }\right] \, ds. \end{aligned}$$
(5.13)

Further, we see that due to Eq. (2.27) of [13] for all \(u \in S_{d}^{+}\) and a process Y on \(S_{d}^{+}\) it holds

$$\begin{aligned} {\text {Tr}}\!\left[ B^{\top }\!\left( u\right) Y \right] = {\text {Tr}}\!\left[ B\!\left( Y\right) u \right] , \end{aligned}$$
(5.14)

where B is defined according to (2.13) and therefore for all \(0\le t\le T\) and \(\alpha = Q^{\top }Q\)

$$\begin{aligned}&\int _{0}^{t}\!{\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \left( b + B\!\left( X_{s}\right) \right) \right] + 2\, {\text {Tr}}\!\left[ Q\, \Sigma \!\left( s,T\right) X_{s}\, \Sigma \!\left( s,T\right) Q^{\top } \right] ds \nonumber \\&\qquad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!\left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \, \xi \right] } - 1\right) \, \nu \!\left( ds,d\xi \right) \nonumber \\&\quad \mathop {=}\limits _{(5.14)}^{(2.12)} -\int _{0}^{t}\!{\text {Tr}}\!\left[ -\Sigma \!\left( s,T\right) b - 2\, \Sigma \!\left( s,T\right) \alpha \Sigma \!\left( s,T\right) X_{s} + B^{\top }\!\left( -\Sigma \!\left( s,T\right) \right) X_{s}\right] ds \nonumber \\&\qquad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!\left( e^{-{\text {Tr}}\left[ -\Sigma \left( s,T\right) \, \xi \right] } - 1\right) \, m\!\left( d\xi \right) ds\nonumber \\&\qquad + \int _{0}^{t}\!{\text {Tr}}\!\left[ X_{s} \int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!\left( e^{-{\text {Tr}}\left[ -\Sigma \left( s,T\right) \, \xi \right] } - 1\right) \, \mu \!\left( d\xi \right) \right] ds \nonumber \\&\quad \mathop {=}\limits _{(2.9)}^{(2.8)} \int _{0}^{t}\!\left( -F\!\left( -\Sigma \!\left( s,T\right) \right) -{\text {Tr}}\!\left[ R\!\left( -\Sigma \!\left( s,T\right) \right) X_{s}\right] \right) ds. \end{aligned}$$
(5.15)

Now, we apply Itô’s formula on \(P\!\left( t,T\right) := \exp \!\left( Z\!\left( t,T\right) \right) \) for every maturity \(T > 0\) (cf.  Definition 1.4.2 of [8]) and obtain the following representation, where we use Proposition 1.28 of Chap. II in [39] to combine the measures \(\mu ^{X\!}\!\left( ds,d\xi \right) \) and \(\nu \!\left( ds,d\xi \right) \), since the affine process X has only jumps of finite variation (cf.  (2.10)).

$$\begin{aligned} P\!\left( t,T\right)&= P\!\left( 0,T\right) + \int _{0}^{t} \! P\!\left( s-,T\right) \, dZ\!\left( s,T\right) + \frac{1}{2}\int _{0}^{t} P\!\left( s,T\right) \, d\left\langle Z\!\left( \,\cdot ,T\right) \right\rangle ^{c}_{s}\\&\quad + \sum _{0 < s \le t}^{\Delta Z\left( s,T\right) \ne 0} \left[ e^{Z\left( s,T\right) } - e^{Z\left( s-,T\right) } - \Delta Z\!\left( s,T\right) e^{Z\left( s-,T\right) }\right] \\&\mathop {=}\limits _{(5.11)}^{(5.13)} P\!\left( 0,T\right) + \int _{0}^{t} \! P\!\left( s-,T\right) \, dZ\!\left( s,T\right) \\&\quad + 2 \int _{0}^{t} \! P\!\left( s,T\right) {\text {Tr}}\!\left[ Q\, \Sigma \!\left( s,T\right) X_{s}\, \Sigma \!\left( s,T\right) Q^{\top } \right] \, ds\\&\quad + \sum _{0 \le s \le t}^{\Delta X_{s}\ne 0} \left[ e^{Z\left( s,T\right) } - e^{Z\left( s-,T\right) } - {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \Delta X_{s}\right] e^{Z\left( s-,T\right) }\right] \\&\mathop {=}\limits _{(5.10)}^{(2.1)} P\!\left( 0,T\right) + 2 \int _{0}^{t} \! P\!\left( s,T\right) {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW_{s}\, Q \right] \nonumber \\&\quad + \int _{0}^{t}\! P(s,T)\left( r_{s} - \int _{s}^{T}\!\alpha \!\left( s,u\right) du\right) \, ds \\&\quad + \int _{0}^{t}\! P(s,T) {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \left( b + B\!\left( X_{s}\right) \right) \right] \, ds\\&\quad + \int _{0}^{t}\! P(s-,T) \int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \xi \right] \, \mu ^{X\!}\!\left( ds,d\xi \right) \\&\quad + 2 \int _{0}^{t} \! P\!\left( s,T\right) {\text {Tr}}\!\left[ Q\, \Sigma \!\left( s,T\right) X_{s}\, \Sigma \!\left( s,T\right) Q^{\top } \right] \, ds \\&\quad + \sum _{0 \le s \le t}^{\Delta X_{s}\ne 0} \left[ e^{\Delta Z\left( s,T\right) }P\!\left( s-,T\right) \! -\! P\!\left( s-,T\right) \! -\! {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \Delta X_{s}\right] P\!\left( s-,T\right) \right] \\&\mathop {=}\limits _{(5.11)}^{(5.15)} P\!\left( 0,T\right) + \int _{0}^{t}\! P\!\left( s-,T\right) \left( r_{s} + A\!\left( s,T\right) \right) ds\\&+ 2 \int _{0}^{t}\! P\!\left( s,T\right) {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \sqrt{X_{s}} \, dW_{s} Q\right] \\&\quad + \int _{0}^{t}\! P\!\left( s-,T\right) \int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\! \left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] } - 1\right) \left( \mu ^{X} - \nu \right) \left( ds,d\xi \right) . \end{aligned}$$

Assumption 1 guarantees that all integrals above are finite. \(\square \)

Proof of Theorem 3.1

By using (3.7) we see that the discounted bond price process under \(\mathbb {Q}\) is

$$\begin{aligned} \frac{P\!\left( t,T\right) }{\beta _{t}}&\mathop {=}\limits ^{(3.8)} P\!\left( 0,T\right) + \int _{0}^{t}\! \frac{P\!\left( s,T\right) }{\beta _{s}}\left( A\!\left( s,T\right) + 2 {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \! \sqrt{X_{s}}\, \gamma _{s}\, Q\right] \right) ds \nonumber \\&\quad + 2 \int _{0}^{t}\! \frac{P\!\left( s,T\right) }{\beta _{s}} {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW^{*}_{s} \, Q\right] \nonumber \\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\! \frac{P\!\left( s-,T\right) }{\beta _{s}}\left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] }\! -\! 1\right) \left( \mu ^{X\!} - \nu ^{*\!}\right) \!\left( ds,d\xi \right) \nonumber \\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\! \frac{P\!\left( s-,T\right) }{\beta _{s}}\left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] }\! -\! 1\right) \left( K\!\left( s,\xi \right) \!-\!1\right) \nu \!\left( ds,d\xi \right) \end{aligned}$$
(5.16)

for all \(0\le t\le T\). Since \(\frac{P\left( t,T\right) }{\beta _{t}}\), \(t \le T\), has to be a local martingale under \(\mathbb {Q}\), the drift in (5.16) must disappear, i.e.  for all \(0\le t\le T\)

$$\begin{aligned} 0&\mathop {=}\limits ^{(2.12)} \int _{0}^{t}\! \frac{P\!\left( s,T\right) }{\beta _{s}} A\!\left( s,T\right) \, ds + 2 \int _{0}^{t}\! \frac{P\!\left( s,T\right) }{\beta _{s}} {\text {Tr}}\!\left[ \Sigma \!\left( s,T\right) \! \sqrt{X_{s}}\, \gamma _{s}\, Q\right] ds \nonumber \\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\! \frac{P\!\left( s-,T\right) }{\beta _{s}}\left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] }\! -\! 1\right) \left( K\!\left( s,\xi \right) \!-\!1\right) \left( m\!\left( d\xi \right) \! +\! {\text {Tr}}\!\left[ X_{s} \mu \!\left( d\xi \right) \right] \right) ds. \end{aligned}$$

It follows for all \(0\le t\le T\) that

$$\begin{aligned} A\!\left( t,T\right)&= - 2 {\text {Tr}}\!\left[ \Sigma \!\left( t,T\right) \! \sqrt{X_{t}}\, \gamma _{t}\, Q\right] \nonumber \\&\quad - \int _{S_{d}^{+}\! \setminus \left\{ 0\right\} \!}\!\left( e^{{\text {Tr}}\left[ \Sigma \left( t,T\right) \,\xi \right] }\! -\! 1\right) \left( K\!\left( t,\xi \right) \!-\!1\right) \left( m\!\left( d\xi \right) \! +\! {\text {Tr}}\!\left[ X_{t} \mu \!\left( d\xi \right) \right] \right) \end{aligned}$$

\(dt \otimes d\mathbb {P}\)-a.s.

Consequently we get for all \(0\le t\le T\) by Satz 6.28 in [42]

$$\begin{aligned} \alpha \!\left( t,T\right)&\mathop {=}\limits ^{(3.4)} - \partial _{T} A\!\left( t,T\right) - \partial _{T} F\!\left( -\Sigma \!\left( t,T\right) \right) - \partial _{T} {\text {Tr}}\!\left[ R\!\left( -\Sigma \!\left( t,T\right) \right) X_{t}\right] \\&\mathop {=}\limits ^{(5.9)} -\! {\text {Tr}}\!\left[ \sigma \!\left( t,T\right) \left( b + B\!\left( X_{t}\right) + 2 \sqrt{X_{t}}\, \gamma _{t}\, Q\right) \right] \! -\! 4 {\text {Tr}}\!\left[ Q\, \sigma \!\left( t,T\right) X_{t}\, \Sigma \!\left( t,T\right) Q^{\top }\right] \\&\quad - \int _{S_{d}^{+}\! \setminus \left\{ 0\right\} \!}\! {\text {Tr}}\left[ \sigma \!\left( t,T\right) \xi \right] e^{{\text {Tr}}\left[ \Sigma \left( t,T\right) \,\xi \right] } K\!\left( t,\xi \right) \left( m\!\left( d\xi \right) \! +\! {\text {Tr}}\!\left[ X_{t} \mu \!\left( d\xi \right) \right] \right) \end{aligned}$$

\(dt \otimes d\mathbb {P}\)-a.s.

Hence, \(\frac{P\left( t,T\right) }{\beta _{t}}\), \(t \le T\), is a \(\mathbb {Q}\)-local martingale if and only if equation (3.10) is fulfilled \(dt \otimes d\mathbb {P}\)-a.s. Eq. (3.10) represents the HJM condition on the drift in the affine setting on \(S_{d}^{+}\). Then, the forward rate under \(\mathbb {Q}\) follows a process of the form

$$\begin{aligned} f\!\left( t,T\right)&\mathop {=}\limits _{(3.1)}^{(2.11)} f\!\left( 0,T\right) + \int _{0}^{t}\! \alpha \!\left( s,T\right) ds + \int _{0}^{t}\! {\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \left( b + B\!\left( X_{s}\right) + 2 \sqrt{X_{s}}\, \gamma _{s}\, Q\right) \right] ds \\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\! {\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] \, \mu ^{X\!}\!\left( ds,d\xi \right) + 2 \int _{0}^{t}\! {\text {Tr}}\left[ \sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW^{*}_{s}\, Q\right] \\&\mathop {=}\limits ^{(3.10)} f\!\left( 0,T\right) - 4 \int _{0}^{t}\! {\text {Tr}}\left[ Q\, \sigma \!\left( s,T\right) \, X_{s}\, \Sigma \!\left( s,T\right) \, Q^{\top }\right] \,ds\\&\quad - \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] }K\!\left( s,\xi \right) \nu \!\left( ds,d\xi \right) \\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\! {\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] \, \mu ^{X\!}\!\left( ds,d\xi \right) + 2 \int _{0}^{t}\! {\text {Tr}}\left[ \sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW^{*}_{s}\, Q\right] \nonumber \\&\mathop {=}\limits ^{(3.3)} f\!\left( 0,T\right) + 4 \int _{0}^{t}\! {\text {Tr}}\left[ Q\, \sigma \!\left( s,T\right) X_{s}\, \int _{s}^{T}\!\sigma \!\left( s,u\right) du\ Q^{\top }\right] \,ds\\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] \left( \mu ^{X\!}-\nu ^{*\!}\right) \!\left( ds,d\xi \right) \\&\quad - \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] \left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] } - 1\right) \nu ^{*\!}\!\left( ds,d\xi \right) \\&\quad + 2 \int _{0}^{t}\! {\text {Tr}}\left[ \sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW^{*}_{s}\, Q\right] \\&\mathop {=}\limits ^{(2.12)} f\!\left( 0,T\right) + \int _{0}^{t}\! \left\{ 4 {\text {Tr}}\left[ Q\, \sigma \!\left( s,T\right) X_{s}\, \int _{s}^{T}\!\sigma \!\left( s,u\right) du\ Q^{\top }\right] \right. \\&\quad \left. - \int _{S_{d}^{+}\! \setminus \left\{ 0\right\} \!}\! K\!\left( s,\xi \right) {\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] \left( e^{{\text {Tr}}\left[ \Sigma \left( s,T\right) \,\xi \right] }\! -\! 1\right) \left( m\!\left( d\xi \right) \! +\! {\text {Tr}}\!\left[ X_{s} \mu \!\left( d\xi \right) \right] \right) \right\} ds \\&\quad + \int _{0}^{t}\!\int _{S_{d}^{+}\! \setminus \left\{ 0\right\} }\!{\text {Tr}}\!\left[ \sigma \!\left( s,T\right) \xi \right] \left( \mu ^{X\!}-\nu ^{*\!}\right) \!\left( ds,d\xi \right) \\&\quad + 2 \int _{0}^{t}\! {\text {Tr}}\left[ \sigma \!\left( s,T\right) \sqrt{X_{s}}\, dW^{*}_{s}\, Q\right] , \end{aligned}$$

where we have used again Proposition 1.28 of Chap. II in [39]. \(\square \)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Biagini, F., Gnoatto, A. & Härtel, M. Long-Term Yield in an Affine HJM Framework on \(S_{d}^{+}\) . Appl Math Optim 77, 405–441 (2018). https://doi.org/10.1007/s00245-016-9379-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00245-016-9379-8

Keywords

Navigation