• Title/Summary/Keyword: Brownian bridge

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FAST ANDROID IMPLIMENTATION OF MONTE CARLO SIMULATION FOR PRICING EQUITY-LINKED SECURITIES

  • JANG, HANBYEOL;KIM, HYUNDONG;JO, SUBEOM;KIM, HANRIM;LEE, SERI;LEE, JUWON;KIM, JUNSEOK
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.24 no.1
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    • pp.79-84
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    • 2020
  • In this article, we implement a recently developed fast Monte Carlo simulation (MCS) for pricing equity-linked securities (ELS), which is most commonly issued autocallable structured financial derivative in South Korea, on the mobile platform. The fast MCS is based on Brownian bridge technique. Although mobile platform devices are easy to carry around, mobile platform devices are slow in computation compared to desktop computers. Therefore, it is essential to use a fast algorithm for pricing ELS on the mobile platform. The computational results demonstrate the practicability of Android application implementation for pricing ELS.

Likelihood Approximation of Diffusion Models through Approximating Brownian Bridge (브라운다리 근사를 통한 확산모형의 우도 근사법)

  • Lee, Eun-kyung;Sim, Songyong;Lee, Yoon Dong
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.895-906
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    • 2015
  • Diffusion is a mathematical tool to explain the fluctuation of financial assets and the movement of particles in a micro time scale. There are ongoing statistical trials to develop an estimation method for diffusion models based on likelihood. When we estimate diffusion models by applying the maximum likelihood estimation method on data observed at discrete time points, we need to know the transition density of the diffusion. In order to approximate the transition densities of diffusion models, we suggests the method to approximate the path integral of the random process with normal random variables, and compare the numerical properties of the method with other approximation methods.

Comparison of Structural Change Tests in Linear Regression Models

  • Kim, Jae-Hee
    • The Korean Journal of Applied Statistics
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    • v.24 no.6
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    • pp.1197-1211
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    • 2011
  • The actual power performance of historical structural change tests are compared under various alternatives. The tests of interest are F, CUSUM, MOSUM, Moving Estimates and empirical distribution function tests with both recursive and ordinary least-squares residuals. Our comparison of the structural tests involves limiting distributions under the hypothesis, the ability to detect the alternative hypotheses under one or double structural change, and smooth change in parameters. Even though no version is uniformly superior to the other, the knowledge about the properties of those tests and connections between these tests can be used in practical structural change tests and in further research on other change tests.

Comparison of Change-point Estimators with Scores

  • Kim, Jae-Hee;Seo, Hyun-Joo
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.1
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    • pp.165-175
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    • 2002
  • We consider the problem of estimating the change-point in mean change model with the one change-point. Lombard (1987) suggested change-point estimation based on score functions. Gombay and Huskova (1998) derived a class of change-point estimators with the score function of rank. Various change-point estimators with the log score functions of ranks are suggested and compared via simulation.

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Comparison of Change-point Estimators in Hazard Rate Models

  • Kim, Jaehee
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.753-763
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    • 2002
  • When there is one change-point in the hazard rate model, a change-point estimator with the partial score process is suggested and compared with the previously developed estimators. The limiting distribution of the partial score process we used is a function of the Brownian bridge. Simulation study gives the comparison of change-point estimators.

CHANGE POINT TEST FOR DISPERSION PARAMETER BASED ON DISCRETELY OBSERVED SAMPLE FROM SDE MODELS

  • Lee, Sang-Yeol
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.4
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    • pp.839-845
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    • 2011
  • In this paper, we consider the cusum of squares test for the dispersion parameter in stochastic differential equation models. It is shown that the test has a limiting distribution of the sup of a Brownian bridge, unaffected by the drift parameter estimation. A simulation result is provided for illustration.

Cusum of squares test for discretely observed sample from multidimensional di usion processes

  • Na, Ok-Young;Ko, Bang-Won;Lee, Sang-Yeol
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.3
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    • pp.547-554
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    • 2010
  • In this paper, we extend the work by Lee et al. (2010) to multidimensional di usion processes. A test statistic analogous to the one-dimensional case is proposed to inves-tigate the joint stability of covariance matrix parameters and, under certain regularity conditions, is shown to have a limiting distribution of the sup of a multidimensional Brownian bridge. A simulation result is provided for illustration.

Cusum of squares test for discretely observed sample from diusion processesy

  • Lee, Sang-Yeol;Lee, Tae-Wook;Na, Ok-Young
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.1
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    • pp.179-183
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    • 2010
  • In this paper, we consider the change point problem in diusion processes based on discretely observed sample. Particularly, we consider the change point test for the dispersion parameter when the drift has unknown parameters. In performing a test, we employ the cusum of squares test based on the residuals. It is shown that the test has a limiting distribution of the sup of a Brownian bridge. A simulation result as to the Ornstein-Uhlenbeck process is provided for illustration. It demonstrates the validity of our test.

BOUNDARY-VALUED CONDITIONAL YEH-WIENER INTEGRALS AND A KAC-FEYNMAN WIENER INTEGRAL EQUATION

  • Park, Chull;David Skoug
    • Journal of the Korean Mathematical Society
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    • v.33 no.4
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    • pp.763-775
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    • 1996
  • For $Q = [0,S] \times [0,T]$ let C(Q) denote Yeh-Wiener space, i.e., the space of all real-valued continuous functions x(s,t) on Q such that x(0,t) = x(s,0) = 0 for every (s,t) in Q. Yeh [10] defined a Gaussian measure $m_y$ on C(Q) (later modified in [13]) such that as a stochastic process ${x(s,t), (s,t) \epsilon Q}$ has mean $E[x(s,t)] = \smallint_{C(Q)} x(s,t)m_y(dx) = 0$ and covariance $E[x(s,t)x(u,\upsilon)] = min{s,u} min{t,\upsilon}$. Let $C_\omega \equiv C[0,T]$ denote the standard Wiener space on [0,T] with Wiener measure $m_\omega$. Yeh [12] introduced the concept of the conditional Wiener integral of F given X, E(F$\mid$X), and for case X(x) = x(T) obtained some very useful results including a Kac-Feynman integral equation.

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Test and Estimation for Normal Mean Change

  • Kim, Jae-Hee;Ryu, Jong-Eun
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.607-619
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    • 2006
  • We consider the problem of testing the existence of change in mean and estimating the change-point when the data are from the normal distribution. A change-point estimator using the likelihood ratio test statistic, Gombay and Horvath (1990) test statistic, and nonparametric change-point estimator using Carlstein (1988) empirical distribution are studied when there exists one change-point in the mean. A power study is done to compare the change test statistics. And a comparison study of change-point estimators for estimation capability is done via simulations with S-plus software.