Abstract
This paper studies a comparison theorem for solutions of stochastic differential equations and its generalization to the multi-dimensional case. We show, that even though the proof of the generalized theorem follows that of the one-dimensional comparison theorem, the multi-dimensional case requires a different condition on the drift coefficient, known in the theory of differential equations as Kamke-Wazewski condition. We also present several examples of possible applications to option price estimation in finance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bassan, B., Çinlar, E., Scarsini, M.: Stochastic comparison of Itô processes. Stoch. Process. Appl. 45, 1–11 (1993)
Cox, J.C., Ross, S.A.: The valuation of options for alternative stochastic processes. J. Financ. Econ. 3, 145–166 (1976)
Ding, X., Wu, R.: A new proof for comparison theorems for stochastic differential inequalities with respect to semimartingales. Stoch. Process. Appl. 78, 155–171 (1998)
Dittmann, I.: Fractional cointegration of voting and non-voting shares. Appl. Financ. Econ. 11(3), 321–332 (2001)
Gal’chuk, L.I.: A comparison theorem for stochastic equations with integral with respect to martingales and random measures. Theory Probab. Appl. 27(3), 450–460 (1982)
Gal’chuk, L.I., Davis, M.H.A.: A note on a comparison theorem for equations with different diffusions. Stochastics 6(2), 147–149 (1982)
Geiß, C., Manthey, R.: Comparison theorems for stochastic differential equations in finite and infinite dimensions. Stoch. Process. Appl. 53, 23–35 (1994)
Hajek, B.: Mean stochastic comparison of diffusions. Z. Wahrscheinlichkeitstheor. Verw. Geb. 68, 315–329 (1985)
Henderson, V.: Price comparison results and superreplication: an application to passport options. Appl. Stoch. Models Bus. Ind. 16, 297–310 (2000)
Jacod, J., Shiryayev, A.N.: Limit Theorems for Stochastic Processes. Springer, Berlin (1987)
Melnikov, A.V.: On the theory of stochastic equations in components of semimartingales. Mat. Sb. 110(3), 414–427 (1979). In English: Sb. Math. 38(3), 381–394 (1981)
Melnikov, A.V.: On solutions of stochastic equations with driving semimartingales. In: Proceedings of the Third European Young Statisticians Meeting, Catholic University, Leuven, pp. 120–124 (1983)
Melnikov, A.V.: Stochastic differential equations: singularity of coefficients, regression models and stochastic approximation. Russ. Math. Surv. 51(5), 43–136 (1996)
O’Brien Ci, L.: A new comparison theorem for solution of stochastic differential equations. Stochastics 3, 245–249 (1980)
Peng, S., Zhu, X.: Necessary and sufficient condition for comparison theorem of 1-dimensional stochastic differential equations. Stoch. Process. Appl. 116, 370–380 (2006)
Situ, R.: Reflecting Stochastic Differential Equations with Jumps and Applications. Chapman Hall/CRC, Boca Raton (2000)
Skorokhod, A.V.: Studies in the Theory of Random Process (1961). Addison-Wesley, Reading (1965) (in English)
Vasicek, O.A.: An equilibrium characterization of the term structure. J. Financ. Econ. 5(2), 177–188 (1977)
Večeř, J., Xu, M.: The mean comparison theorem cannot be extended to the Poisson case. J. Appl. Probab. 41(4), 1199–1202 (2004)
Yamada, T.: On comparison theorem for solutions of stochastic differential equations and its applications. J. Math. Kyoto Univ. 13, 497–512 (1973)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Krasin, V.Y., Melnikov, A.V. (2009). On Comparison Theorem and its Applications to Finance. In: Optimality and Risk - Modern Trends in Mathematical Finance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02608-9_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-02608-9_8
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02607-2
Online ISBN: 978-3-642-02608-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)