Skip to main content
Log in

On the Transition Density and First Hitting Time Distributions of the Doubly Skewed CIR Process

  • Published:
Methodology and Computing in Applied Probability Aims and scope Submit manuscript

Abstract

In this paper, we study doubly skewed CIR processes, which are extensions of skew Brownian motion. We use modified spectral expansion to obtain some properties, including the transition densities and first hitting time distributions, of doubly skewed CIR processes.

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. Since ω(λ) is independent of x, it can equal \(\frac {1}{\mathfrak {s}_{Y}(\nu _{1})}(\xi (\nu _{1},\lambda )\eta _{x}^{\prime }(\nu _{1},\lambda )-\xi _{x}^{\prime }(\nu _{1},\lambda )\eta (\nu _{1},\lambda ))\). The two values are the same.

  2. when considering An, it can also be in this way, \(A_{n}=\frac {A_{4}\phi _{2}(\nu _{1},\lambda _{n})+B_{4}\psi _{2}(\nu _{1},\lambda _{n})}{A_{1}\phi _{2}(\nu _{1},\lambda _{n})+B_{1}\psi _{2}(\nu _{1},\lambda _{n})}\).

References

  • Cantrell RS, Cosner C (1999) Diffusion models for population dynamics incorporating individual behavior at boundaries: applications to refuge design. Theor Popul Biol 55:189–207

    Article  Google Scholar 

  • Decamps M, Goovaerts M, Schoutens W (2006a) Asymmetric skew Bessel processes and their applications to finance. J Comput Appl Math 186:130–147

    Article  MathSciNet  Google Scholar 

  • Decamps M, Goovaerts M, Schoutens W (2006b) Self exciting threshold interest rates models. Int J Theor Appl Finance 9:1093–1122

    Article  MathSciNet  Google Scholar 

  • Gairat A, Shcherbakov V (2017) Density of Skew Brownian motion and its functionals with application in finance. Math Finance 27:1069–1088

    Article  MathSciNet  Google Scholar 

  • Gorovoi V, Linetsky V (2004) Black’s model of interest rates as options, eigenfunction expansions and Japanese interest rates. Math Finance 14:49–78

    Article  MathSciNet  Google Scholar 

  • Harrison JM, Shepp LA (1981) On skew Brownian motion. Ann Probab 9:309–313

    MathSciNet  MATH  Google Scholar 

  • Itô K, McKean HP (1965) Diffusion processes and their sample paths. Springer, Berlin

    MATH  Google Scholar 

  • Lang R (1995) Effective conductivity and skew Brownian motion. J Stat Phys 80:125–146

    Article  MathSciNet  Google Scholar 

  • Lejay A (2003) Simulating a diffusion on a graph. Application to reservoir engineering. Monte Carlo Methods Appl 9:241–256

    Article  MathSciNet  Google Scholar 

  • Lejay A (2004) Monte Carlo methods for fissured porous media: a gridless approach. Monte Carlo Methods Appl 10:385–392

    Article  MathSciNet  Google Scholar 

  • Le Gall JF (1984) One-dimensional stochastic differential equations involving the local times of the unknown process. Stoch Anal Appl 1095:51–82

    MathSciNet  Google Scholar 

  • Linetsky V (2004a) Lookback options and diffusion hitting times: a spectral expansion approach. Finance Stoch 8:373–398

    Article  MathSciNet  Google Scholar 

  • Linetsky V (2004b) The spectral decomposition of the option value. Int J Theor Appl Finance 7:337–384

    Article  MathSciNet  Google Scholar 

  • Linetsky V (2005) On the transition densities for reflected diffusions. Adv Appl Probab 37:435–460

    Article  MathSciNet  Google Scholar 

  • Nikiforov AF, Uvarov VB (1988) Special functions of mathematical physics: a unified introduction with applications. Birkhauser, Basel, Boston

    Book  Google Scholar 

  • Ramirez JM (2011) Multi-skewed brownian motion and diffusion in layered media. Proc Amer Math Soc 139:3739–3752

    Article  MathSciNet  Google Scholar 

  • Song S, Wang Y (2017) Pricing double barrier options under a volatility regime-switching model with psychological barriers. Rev Deriv Res 20:255–280

    Article  Google Scholar 

  • Song S, Xu G, Wang Y (2014) On first hitting times for skew CIR processes. Methodol Comput Appl Probab 18:169–180

    Article  MathSciNet  Google Scholar 

  • Trutnau G (2010) Weak existence of the squared Bessel and CIR processes with skew reflection on a deterministic time-dependent curve. Stoch Proc Appl 120:381–402

    Article  MathSciNet  Google Scholar 

  • Trutnau G (2011) Pathwise uniqueness of the squared Bessel and CIR processes with skew reflection on a deterministic time dependent curve. Stoch Proc Appl 121:1845–1863

    Article  MathSciNet  Google Scholar 

  • Walsh JB (1978) A diffusion with a discontinuous local time. Asterisqué 52:37–45

    Google Scholar 

  • Xu G, Song S, Wang Y (2016a) Some properties of doubly skewed CIR processes. J Math Anal Appl 434:1194–1210

    Article  MathSciNet  Google Scholar 

  • Xu G, Song S, Wang Y (2016b) The valuation of options on foreign exchange rate in a target zone. Int J Theor Appl Finance 19:1–19

    Article  MathSciNet  Google Scholar 

  • Yin C, Wang H (2012) The first passage time and the dividend value function for one-dimensional diffusion processes between two reflecting barriers. Int J Stoch Anal 2012:1–15

  • Zhang M (2000) Calculation of diffusive shock acceleration of charged particles by skew brownian motion. Astrophys J 541:428–435

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xingchun Wang.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This study was supported by the National Natural Science Foundation of China (11701084, 11701085, 11671084) and supported by “the Fundamental Research Funds for the Central Universities” in UIBE (CXTD10-09).

Appendices

Appendix A: Proof of Proposition 2.1

First we note the fact that,

$$ p_{X}(t;x_{0},x)=G^{\prime}(x)p_{Y}(t;G(x_{0}),G(x)), $$

then the problem turns to computing the transition density of Yt whose general form is defined in Eq. 9. That is to say, we need to solve the SL equation \(-(\mathcal {G} u)(y)=\lambda u(y),\forall y\in (l_{1},\infty )\), i.e., the following ordinary differential equations (ODEs)

$$ \begin{array}{@{}rcl@{}} \left\{ \begin{array}{ll} -\frac{1}{2}{\sigma_{1}^{2}}(x-l_{1})u_{xx}-k(\theta_{1}-x)u_{x}=\lambda u(x), & x\in(l_{1},\nu_{1}),\\ -\frac{1}{2}{\sigma_{2}^{2}}(x-l_{2})u_{xx}-k(\theta_{2}-x)u_{x}=\lambda u(x), & x\in[\nu_{1},\nu_{2}),\\ -\frac{1}{2}{\sigma_{3}^{2}}(x-l_{3})u_{xx}-k(\theta_{3}-x)u_{x}=\lambda u(x), & x\in[\nu_{2},\infty). \end{array} \right. \end{array} $$

When solving the above ODEs, we adopt the approach of Gorovoi and Linetsky (2004). Let \(\xi (x,\lambda ), x\in (l_{1},\infty )\) be the unique (up to multiple independent of x) solution such that

$$ {\int}_{l_{1}}^{\nu_{1}}|\xi_(x,\lambda)|^{2}\mathfrak{m}_{Y}(x)\mathrm{d} x<\infty, $$

and

$$ \lim_{x\downarrow l_{1}}\frac{\xi_{x}^{\prime}(s,\lambda)}{\mathfrak{s}_{Y}(x)}=0, $$

for each \(\lambda \in \mathbb {C}\), and ξ(x, λ) and \(\xi _{x}^{\prime }(x,\lambda )\) are continuous in x and λ in \((l_{1},\infty )\times \mathbb {C}\) and entire in λ for each fixed \(x\in (l_{1},\infty )\). And let \(\eta (x,\lambda ), x\in (l_{1},\infty )\) be the unique (up to multiple independent of x) solution such that

$$ {\int}_{\nu_{2}}^{\infty}|\eta_(x,\lambda)|^{2}\mathfrak{m}_{Y}(x)\mathrm{d} x<\infty, $$

and

$$ \lim_{x\uparrow +\infty}\frac{\eta_{x}^{\prime}(x,\lambda)}{\mathfrak{s}_{Y}(x)}=0, $$

for each \(\lambda \in \mathbb {C}\), and ξ(x, λ) and \(\xi _{x}^{\prime }(x,\lambda )\) are continuous in x and λ in \((l_{1},\infty )\times \mathbb {C}\) and entire in λ for each fixed \(x\in (l_{1},\infty )\).

When considering each interval (l1,ν1), [ν1,ν2) and \([\nu _{2},\infty )\) separately, we know ϕi(x, λ) = F(α, β, zi) and ψi(x, λ) = U(α, β, zi) are two linearly independent solutions of each ODE on each interval for i = 1, 2, 3 from Xu et al. (2016b) with α, zi defined in Eq. 10 and β showed in Eq. 5. Then we can assume ξ(x, λ) and η(x, λ) on interval \((l_{1},\infty )\) to have the following forms,

$$ \begin{array}{@{}rcl@{}} \xi(x,\lambda)&=\left\{ \begin{array}{ll} \phi_{1}(x,\lambda), & l_{1}<x<\nu_{1},\\ A_{1}\phi_{2}(x,\lambda)+B_{1}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x<\nu_{2},\\ A_{2}\phi_{3}(x,\lambda)+B_{2}\psi_{3}(x,\lambda), & x\geqslant\nu_{2}, \end{array} \right. \\ \eta(x,\lambda)&=\left\{ \begin{array}{ll} A_{3}\phi_{1}(x,\lambda)+B_{3}\psi_{1}(x,\lambda), & l_{1}<x<\nu_{1},\\ A_{4}\phi_{2}(x,\lambda)+B_{4}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x<\nu_{2},\\ \psi_{3}(x,\lambda), & x\geqslant\nu_{2}. \end{array} \right. \end{array} $$

The continuity of ξ(x, λ), \(\xi _{x}^{\prime }(x,\lambda )\), η(x, λ) and \( \eta _{x}^{\prime }(x,\lambda )\) at x = ν1 and x = ν2 uniquely implies the following facts:

$$ \begin{array}{@{}rcl@{}} \left\{\begin{array}{l} \phi_{1}(\nu_{1},\lambda)=A_{1}\phi_{2}(\nu_{1},\lambda)+B_{1}\psi_{2}(\nu_{1},\lambda),\\ \phi_{1x}^{\prime}(\nu_{1},\lambda)=A_{1}\phi_{2x}^{\prime}(\nu_{1},\lambda)+B_{1}\psi_{2x}^{\prime}(\nu_{1},\lambda),\\ A_{1}\phi_{2}(\nu_{2},\lambda)+B_{1}\psi_{2}(\nu_{2},\lambda)=A_{2}\phi_{3}(\nu_{2},\lambda)+B_{2}\psi_{3}(\nu_{2},\lambda),\\ A_{1}\phi_{2x}^{\prime}(\nu_{2},\lambda)+B_{1}\psi_{2x}^{\prime}(\nu_{2},\lambda)=A_{2}\phi_{3x}^{\prime}(\nu_{2},\lambda)+B_{2}\psi_{3x}^{\prime}(\nu_{2},\lambda),\\ A_{3}\phi_{1}(\nu_{1},\lambda)+B_{3}\psi_{1}(\nu_{1},\lambda)=A_{4}\phi_{2}(\nu_{1},\lambda)+B_{4}\psi_{2}(\nu_{1},\lambda),\\ A_{3}\phi_{1x}^{\prime}(\nu_{1},\lambda)+B_{3}\psi_{1x}^{\prime}(\nu_{1},\lambda)=A_{4}\phi_{2x}^{\prime}(\nu_{1},\lambda)+B_{4}\psi_{2x}^{\prime}(\nu_{1},\lambda),\\ A_{4}\phi_{2}(\nu_{2},\lambda)+B_{4}\psi_{2}(\nu_{2},\lambda)=\psi_{3}(\nu_{2},\lambda),\\ A_{4}\phi_{2x}^{\prime}(\nu_{2},\lambda)+B_{4}\psi_{2x}^{\prime}(\nu_{2},\lambda)=\psi_{3x}^{\prime}(\nu_{2},\lambda). \end{array} \right. \end{array} $$

Solving the above equations, we can derive the unknown coefficients Ai,Bi,i = 1, 2, 3, 4. Then the Wronskian of ξ(x, λ) and η(x, λ) isFootnote 1

$$ \begin{array}{@{}rcl@{}} \omega(\lambda)&=&\xi(x,\lambda)\frac{\eta_{x}^{\prime}(x,\lambda)}{\mathfrak{s}_{Y}(x)}-\eta(x,\lambda)\frac{\xi_{x}^{\prime}(x,\lambda)}{\mathfrak{s}_{Y}(x)}\\ &=&\frac{1}{\mathfrak{s}_{Y}(\nu_{2})}(\xi(\nu_{2},\lambda)\eta_{x}^{\prime}(\nu_{2},\lambda)-\xi_{x}^{\prime}(\nu_{2},\lambda)\eta(\nu_{2},\lambda)), \end{array} $$

which yields the value ω(λ) in Proposition 2.1. At an eigenvalue λ = λn (zero of the function ω(λ)), the Wronskian vanishes and ξ(x, λn) and η(x, λn) become linearly dependent, i.e.,Footnote 2

$$ \eta(x,\lambda_{n})=A_{n}\xi(x,\lambda_{n}), \ \ \ A_{n}=\frac{\psi_{3}(\nu_{2},\lambda_{n})}{A_{2}\phi_{3}(\nu_{2},\lambda_{n})+B_{2}\psi_{3}(\nu_{2},\lambda_{n})}. $$

Finally, according to Theorem 5 in Linetsky (2004b), the corresponding normalized eigenfunctions can take the form

$$ \varphi_{n}(x)= \sqrt{\frac{A_{n}}{{\Delta}_{n}}}\xi(x,\lambda_{n}), \ \ \text{or},\ \ \frac{1}{\sqrt{A_{n}{\Delta}_{n}}}\eta(x,\lambda_{n}), $$

where \({\Delta }_{n}=\frac {d\omega (\lambda )}{d\lambda }|_{\lambda =\lambda _{n}}\) and we arrive at the result in Proposition 2.1.

Appendix B: Proof of Proposition 3.1

The proof is similar to the proof of Proposition 2.1. The different point is that we need to solve the SL equation \(-(\mathcal {G}_{|(l_{1},y]} u)(x)=\lambda u(x)\) for all x ∈ (l1,y] and the solution η(x, λ) satisfy the boundary conditions

$$ \eta(y,\lambda)=0,\ \ \eta_{x}^{\prime}(y,\lambda)=\frac{\partial\eta(x,\lambda)}{\partial x}|_{x=y}=-1. $$
(B.1)

For the case when y > ν2, we assume that ξ(x, λ) and η(x, λ) have the following form

$$ \begin{array}{@{}rcl@{}} \xi(x,\lambda)&=\left\{ \begin{array}{ll} \phi_{1}(x,\lambda), & l_{1}<x<\nu_{1},\\ \tilde{A}_{1}\phi_{2}(x,\lambda)+\tilde{B}_{1}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x<\nu_{2},\\ \tilde{A}_{2}\phi_{3}(x,\lambda)+\tilde{B}_{2}\psi_{3}(x,\lambda), & \nu_{2}\leqslant x\leqslant y, \end{array} \right. \\ \eta(x,\lambda)&=\left\{ \begin{array}{ll} \tilde{A}_{3}\phi_{1}(x,\lambda)+\tilde{B}_{3}\psi_{1}(x,\lambda), & l_{1}<x<\nu_{1},\\ \tilde{A}_{4}\phi_{2}(x,\lambda)+\tilde{B}_{4}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x<\nu_{2},\\ \tilde{A}_{5}\phi_{3}(x,\lambda)+\tilde{B}_{5}\psi_{3}(x,\lambda), & \nu_{2}\leqslant x\leqslant y. \end{array} \right. \end{array} $$

For the case when \(\nu _{1}<y\leqslant \nu _{2}\), we assume that

$$ \begin{array}{@{}rcl@{}} \xi(x,\lambda)&=\left\{ \begin{array}{ll} \phi_{1}(x,\lambda), & l_{1}<x<\nu_{1},\\ \hat{A}_{1}\phi_{2}(x,\lambda)+\hat{B}_{1}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x\leqslant y, \end{array} \right. \\ \eta(x,\lambda)&=\left\{ \begin{array}{ll} \hat{A}_{2}\phi_{1}(x,\lambda)+\hat{B}_{2}\psi_{1}(x,\lambda), & l_{1}<x<\nu_{1},\\ \hat{A}_{3}\phi_{2}(x,\lambda)+\hat{B}_{3}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x\leqslant y. \end{array} \right. \end{array} $$

For the case when \(y\leqslant \nu _{1}\), ξ(x, λ) = ϕ1(x, λ) and we assume that \(\eta (x,\lambda )=\check {A}_{1}\phi _{1}(x,\lambda )+\check {B}_{1}\psi _{1}(x,\lambda )\) which should satisfy the boundary conditions presented in Eq. B.1.

Similarly, using the continuity of ξ(x, λ), \(\xi _{x}^{\prime }(x,\lambda )\), η(x, λ) and \( \eta _{x}^{\prime }(x,\lambda )\) at x = ν1 and x = ν2, we can derive the unknown coefficients in ξ(x, λ) and η(x, λ) for each case. After obtaining ξ(x, λ) and η(x, λ) in each case, we can know each Wronskian ω(λ), eigenvalues, eigenfunctions and then derive our results.

Appendix C: Proof of Proposition 3.2

The proof is also similar to the proof of Proposition 2.1. The different point is that we need to solve the SL equation \(-(\mathcal {G}_{|[y,\infty )} u)(x)=\lambda u(x)\) for all \(x\in [y,\infty )\) and the solution ξ(x, λ) satisfy the boundary conditions

$$ \xi(y,\lambda)=0,\ \ \xi_{x}^{\prime}(y,\lambda)=\frac{\partial\xi(x,\lambda)}{\partial x}|_{x=y}=1. $$
(C.1)

For the case when y < ν1, we suppose ξ(x, λ) and η(x, λ) to have the following form

$$ \begin{array}{@{}rcl@{}} \xi(x,\lambda)&=\left\{ \begin{array}{ll} \tilde{C}_{1}\phi_{1}(x,\lambda)+\tilde{D}_{1}\psi_{1}(x,\lambda), & y\leqslant x<\nu_{1},\\ \tilde{C}_{2}\phi_{2}(x,\lambda)+\tilde{D}_{2}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x<\nu_{2},\\ \tilde{C}_{3}\phi_{3}(x,\lambda)+\tilde{D}_{3}\psi_{3}(x,\lambda), & x\geqslant\nu_{2}, \end{array} \right. \\ \eta(x,\lambda)&=\left\{ \begin{array}{ll} \tilde{C}_{4}\phi_{1}(x,\lambda)+\tilde{D}_{4}\psi_{1}(x,\lambda), &y\leqslant x<\nu_{1},\\ \tilde{C}_{5}\phi_{2}(x,\lambda)+\tilde{D}_{5}\psi_{2}(x,\lambda), & \nu_{1}\leqslant x<\nu_{2},\\ \psi_{3}(x,\lambda), & x\geqslant\nu_{2}. \end{array} \right. \end{array} $$

For the case when \(\nu _{1}\leqslant y<\nu _{2}\), we suppose that

$$ \begin{array}{@{}rcl@{}} \xi(x,\lambda)&=\left\{ \begin{array}{ll} \hat{C}_{1}\phi_{2}(x,\lambda)+\hat{D}_{1}\psi_{2}(x,\lambda), & y\leqslant x<\nu_{2},\\ \hat{C}_{2}\phi_{3}(x,\lambda)+\hat{D}_{2}\psi_{3}(x,\lambda), & x\geqslant\nu_{2}, \end{array} \right. \\ \eta(x,\lambda)&=\left\{ \begin{array}{ll} \hat{C}_{3}\phi_{2}(x,\lambda)+\hat{D}_{3}\psi_{2}(x,\lambda), & y\leqslant x<\nu_{2},\\ \psi_{3}(x,\lambda), & x\geqslant\nu_{2}. \end{array} \right. \end{array} $$

For the case when \(y\leqslant \nu _{1}\), η(x, λ) = ψ3(x, λ) and we suppose that ξ(x, λ) = C1ϕ3(x, λ) + D1ψ3(x, λ) which should satisfy the boundary conditions showed in Eq. C.1.

Similarly, the continuity of ξ(x, λ), \(\xi _{x}^{\prime }(x,\lambda )\), η(x, λ) and \( \eta _{x}^{\prime }(x,\lambda )\) at x = ν1 and x = ν2 uniquely determines the unknown coefficients in each ξ(x, λ) and η(x, λ), and then we can get the Wronskian ω(λ), eigenvalues, eigenfunctions and our results.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, G., Wang, X. On the Transition Density and First Hitting Time Distributions of the Doubly Skewed CIR Process. Methodol Comput Appl Probab 23, 735–752 (2021). https://doi.org/10.1007/s11009-020-09775-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11009-020-09775-0

Keywords

Mathematics Subject Classification (2010)

Navigation