Closed-form approximations of moments and densities of continuous-time Markov models

被引:0
|
作者
Kristensen, Dennis [1 ]
Lee, Young Jun [2 ]
Mele, Antonio [3 ,4 ,5 ]
机构
[1] UCL, Dept Econ, London, England
[2] Korea Inst Int Econ Policy, Sejong City, South Korea
[3] USI, Lugano, Switzerland
[4] Swiss Finance Inst, Geneva, Switzerland
[5] CEPR, London, England
来源
关键词
Continuous-time models; Jump-diffusion; Transition density; Stochastic volatility; Closed-form approximations; Maximum-likelihood estimation; Option pricing; MAXIMUM-LIKELIHOOD-ESTIMATION; MONTE-CARLO; DIFFUSIONS; JUMP; INFERENCE;
D O I
10.1016/j.jedc.2024.104948
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper develops power series expansions of a general class of moment functions, including transition densities and option prices, of continuous-time Markov processes, including jump- diffusions. The proposed expansions extend the ones in Kristensen and Mele (2011) to cover general Markov processes, and nest transition density and option price expansions recently developed in the literature, thereby connecting seemingly different ideas in a unified framework. We show how the general expansion can be implemented for fully general jump-diffusion models. We provide a new theory for the validity of the expansions which shows that series expansions are not guaranteed to converge as more terms are added in general once the time span of interest gets larger than some model-specific threshold. Thus, these methods should be used with caution when applied to problems with a larger time span of interest, such as long-term options or data observed at a low frequency. At the same time, the numerical studies in this paper demonstrate good performance of the proposed implementation in practice when applied to pricing options with time to maturity below three months. Thus, our expansions are particularly well suited pricing ultra-short-term (such as "zero-day") options.
引用
收藏
页数:26
相关论文
共 50 条
  • [41] Continuous-time Markov models for geriatric patient behaviour
    Taylor, G
    McClean, S
    Millard, P
    APPLIED STOCHASTIC MODELS AND DATA ANALYSIS, 1997, 13 (3-4): : 315 - 323
  • [42] Continuous-Time Mean Field Markov Decision Models
    Baeuerle, Nicole
    Hoefer, Sebastian
    APPLIED MATHEMATICS AND OPTIMIZATION, 2024, 90 (01):
  • [43] Bayesian clustering for continuous-time hidden Markov models
    Luo, Yu
    Stephens, David A.
    Buckeridge, David L.
    CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2023, 51 (01): : 134 - 156
  • [44] Closed-form probabilistic models of time-of-flight sonar
    Harris, KD
    SIMULATION: PAST, PRESENT AND FUTURE, 1998, : 427 - 434
  • [45] New closed-form approximations to the logarithmic constant e
    Harlan J. Brothers
    John A. Knox
    The Mathematical Intelligencer, 1998, 20 : 25 - 29
  • [46] Closed-form approximations for operational value-at-risk
    Hernandez, Lorenzo
    Tejero, Jorge
    Suarez, Alberto
    Carrillo-Menendez, Santiago
    JOURNAL OF OPERATIONAL RISK, 2013, 8 (04): : 39 - 54
  • [47] CLOSED-FORM APPROXIMATIONS FOR FIN-LINE EIGENMODES
    SAAD, AMK
    SCHUNEMANN, K
    IEE PROCEEDINGS-H MICROWAVES ANTENNAS AND PROPAGATION, 1982, 129 (05) : 253 - 261
  • [48] Beyond Time-Homogeneity for Continuous-Time Multistate Markov Models
    Kendall, Emmett B.
    Williams, Jonathan P.
    Hermansen, Gudmund H.
    Bois, Frederic
    Thanh, Vo Hong
    JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2024,
  • [49] Closed-Form Approximations for the URLLC CapacityUsingG/G/sQueues
    Karamyshev, A. Yu.
    Porai, E. D.
    Khorov, E. M.
    PROBLEMS OF INFORMATION TRANSMISSION, 2024, 60 (03) : 255 - 272
  • [50] Closed-form approximations for spread option prices and Greeks
    Li, Minqiang
    Deng, Shi-Jie
    Zhou, Jeyun
    JOURNAL OF DERIVATIVES, 2008, 15 (03): : 58 - 80