• 제목/요약/키워드: wiener process

검색결과 111건 처리시간 0.03초

A Weak Convergence for a Linear Process with Positive Dependent Sequences

  • Kim, Tae-Sung;Ryu, Dae-Hee;Lee, Il-Hyun
    • Journal of the Korean Statistical Society
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    • 제31권4호
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    • pp.483-490
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    • 2002
  • A weak convergence is obtained for a linear process of the form (equation omitted) where {$\varepsilon$$_{t}$ } is a strictly stationary sequence of associated random variables with E$\varepsilon$$_{t}$ = 0 and E$\varepsilon$$^{^2}$$_{t}$ < $\infty$ and {a $_{j}$ } is a sequence of real numbers with (equation omitted). We also apply this idea to the case of linearly positive quadrant dependent sequence.

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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    • 제13권1호
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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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Tests for Mean Change with the Modified Cusum Statistics

  • Kim, Jae-Hee;Kim, Na-Yeon
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.187-199
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    • 2003
  • We deal with the problem of testing a sequence of independent normal random variables with constant, known or unknown, variance for no change in mean versus alternatives with a single change-point. Various tests based on the likelihood ratio and recursive residuals, score statistics and cusums are studied. Proposed tests are modified version of Buckley's cusum statistics. A comparison study of various change-point test statistics is done by Monte Carlo simulation with S-plus software.

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Computing the Ruin Probability of Lévy Insurance Risk Processes in non-Cramér Models

  • Park, Hyun-Suk
    • Communications for Statistical Applications and Methods
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    • 제17권4호
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    • pp.483-491
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    • 2010
  • This study provides the explicit computation of the ruin probability of a Le¢vy process on finite time horizon in Theorem 1 with the help of a fluctuation identity. This paper also gives the numerical results of the ruin probability in Variance Gamma(VG) and Normal Inverse Gaussian(NIG) models as illustrations. Besides, the paths of VG and NIG processes are simulated using the same parameter values as in Madan et al. (1998).

STOCHASTIC MEHLER KERNELS VIA OSCILLATORY PATH INTEGRALS

  • Truman, Aubrey;Zastawniak, Tomasz
    • Journal of the Korean Mathematical Society
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    • 제38권2호
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    • pp.469-483
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    • 2001
  • The configuration space and phase space oscillatory path integrals are computed in the case of the stochastic Schrodinger equation for the harmonic oscillator with a stochastic term of the form (K$\psi$(sub)t)(x) o dW(sub)t, where K is either the position operator or the momentum operator, and W(sub)t is the Wiener process. In this way formulae are derived for the stochastic analogues of the Mehler kernel.

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A FUBINI THEOREM FOR GENERALIZED ANALYTIC FEYNMAN INTEGRALS AND FOURIER-FEYNMAN TRANSFORMS ON FUNCTION SPACE

  • Chang, Seung-Jun;Lee, Il-Yong
    • Bulletin of the Korean Mathematical Society
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    • 제40권3호
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    • pp.437-456
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    • 2003
  • In this paper we use a generalized Brownian motion process to define a generalized analytic Feynman integral. We then establish a Fubini theorem for the function space integral and generalized analytic Feynman integral of a functional F belonging to Banach algebra $S(L^2_{a,b}[0,T])$ and we proceed to obtain several integration formulas. Finally, we use this Fubini theorem to obtain several Feynman integration formulas involving analytic generalized Fourier-Feynman transforms. These results subsume similar known results obtained by Huffman, Skoug and Storvick for the standard Wiener process.

FUNCTIONAL CENTRAL LIMIT THEOREMS FOR MULTIVARIATE LINEAR PROCESSES GENERATED BY DEPENDENT RANDOM VECTORS

  • Ko, Mi-Hwa
    • Communications of the Korean Mathematical Society
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    • 제21권4호
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    • pp.779-786
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    • 2006
  • Let $\mathbb{X}_t$ be an m-dimensional linear process defined by $\mathbb{X}_t=\sum{_{j=0}^\infty}\;A_j\;\mathbb{Z}_{t-j}$, t = 1, 2, $\ldots$, where $\mathbb{Z}_t$ is a sequence of m-dimensional random vectors with mean 0 : $m\times1$ and positive definite covariance matrix $\Gamma:m{\times}m$ and $\{A_j\}$ is a sequence of coefficient matrices. In this paper we give sufficient conditions so that $\sum{_{t=1}^{[ns]}\mathbb{X}_t$ (properly normalized) converges weakly to Wiener measure if the corresponding result for $\sum{_{t=1}^{[ns]}\mathbb{Z}_t$ is true.

Accurate Prediction of the Pricing of Bond Using Random Number Generation Scheme (난수 생성기법을 이용한 채권 가격의 정확한 예측)

  • Park, Ki-Soeb;Kim, Moon-Seong;Kim, Se-Ki
    • Journal of the Korea Society for Simulation
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    • 제17권3호
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    • pp.19-26
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    • 2008
  • In this paper, we propose a dynamic prediction algorithm to predict the bond price using actual data set of treasure note (T-Note). The proposed algorithm is based on term structure model of the interest rates, which takes place in various financial modelling, such as the standard Gaussian Wiener process. To obtain cumulative distribution functions (CDFs) of actual data for the interest rate measurement used, we use the natural cubic spline (NCS) method, which is generally used as numerical methods for interpolation. Then we also use the random number generation scheme (RNGS) to calculate the pricing of bond through the obtained CDF. In empirical computer simulations, we show that the lower values of precision in the proposed prediction algorithm corresponds to sharper estimates. It is very reasonable on prediction.

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Optimal portfolio and VaR of KOSPI200 using One-factor model (원-팩터 모형을 이용한 KOSPI200지수 구성종목의 최적 포트폴리오 구성 및 VaR 측정)

  • Ko, Kwang Yee;Son, Young Sook
    • Journal of the Korean Data and Information Science Society
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    • 제26권2호
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    • pp.323-334
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    • 2015
  • he current VaR model based on the J.P. Morgan's RiskMetrics structurally can not reflect the future economic situation. In this study, we propose a One-factor model resulting from the Wiener stochastic process decomposed into a systematic risk factor and an idiosyncratic risk factor. Therefore, we are able to perform a preemptive risk management by means of reflecting the predicted common risk factors in the model. Stocks in the portfolio are satisfied with the independence to each other because the common factors are fixed by the predicted value. Therefore, we can easily determine the investment in each stock to minimize the variance of the portfolio. In addition, the portfolio VaR is decomposed into the sum of the individual VaR. So we can effectively implement the constitution of the portfolio to meet the target maximum losses.