Gaussian Estimation of Single‐Factor Continuous Time Models of The Term Structure of Interest Rates

Nowman, K. Ben

doi:10.1111/j.1540-6261.1997.tb01127.x

Cited by 159 publications

(106 citation statements)

References 31 publications

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“…This was designed to see if there were significant difference between the approximate MLEs and the pseudo-likelihood estimators of Nowman (1997). The results are reported in Table 4.…”

Section: Univariate Processesmentioning

confidence: 99%

“…However, for most of diffusion processes, their transitional distributions are not explicitly known which prevents the use of the MLE. In these cases, several methods are available, which include the martingale estimating equation approach by Bibby and Sørensen (1995); the pseudo-Gaussian likelihood approach of Nowman (1997); the Generalized Method of Moments (GMM) estimator of Hansen and Scheinkman (1995); the Efficient Method of Moments of Gallant and Tauchen (1996)and the approximate likelihood approach of Aït-Sahalia (2002). Aït-Sahalia andMykland(2003 and2004) consider likelihood and the GMM based estimation when δ is random.…”

Section: A General Overviewmentioning

confidence: 99%

“…To gain insight on the parameter estimation, we consider pseudo-likelihood estimators proposed by Nowman (1997),…”

Section: Estimation For Cir Processmentioning

confidence: 99%

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Parameter estimation and bias correction for diffusion processes

Tang

Chen

2009

Journal of Econometrics

132

159

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“…This was designed to see if there were significant difference between the approximate MLEs and the pseudo-likelihood estimators of Nowman (1997). The results are reported in Table 4.…”

Section: Univariate Processesmentioning

confidence: 99%

Section: A General Overviewmentioning

confidence: 99%

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Parameter estimation and bias correction for diffusion processes

Tang

Chen

2009

Journal of Econometrics

132

159

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“…These data have been analyzed by many authors, including Aït-Sahalia (1996), Nowman (1997), and Yu and Phillips (2001), to mention a few. We do not pretend to give the definitive answer on the subject, but just to analyze the effect of the model selection via the LASSO in a real application.…”

Section: An Example Of Use In the Problem Of Identification Of The Tementioning

confidence: 99%

Adaptive Lasso-Type Estimation for Multivariate Diffusion Processes

Gregorio¹,

Iacus²

2012

Econom. Theory

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The least absolute shrinkage and selection operator (LASSO) is a widely used statistical methodology for simultaneous estimation and variable selection. It is a shrinkage estimation method that allows one to select parsimonious models. In other words, this method estimates the redundant parameters as zero in the large samples and reduces variance of estimates. In recent years, many authors analyzed this technique from a theoretical and applied point of view. We introduce and study the adaptive LASSO problem for discretely observed multivariate diffusion processes. We prove oracle properties and also derive the asymptotic distribution of the LASSO estimator. This is a nontrivial extension of previous results by Wang and Leng (2007, Journal of the American Statistical Association, 102(479), 1039-1048) on LASSO estimation because of different rates of convergence of the estimators in the drift and diffusion coefficients. We perform simulations and real data analysis to provide some evidence on the applicability of this method.

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“…[2,15] in this direction. Figure 4 (in the end of paper) is a sample path of the CIR model (3.2) for 17 years with the parameters above and initial value 4000.…”

Section: Mpr Based On Mean Reverting Sde Modelsmentioning

confidence: 99%

Mean percentage of returns for stock market linked savings accounts

Feng

Huang

Mao

2016

Applied Mathematics and Computation

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This version is available at https://strathprints.strath.ac.uk/54320/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Mean Percentage of Returns for Stock Market Linked Savings AccountsLing Feng 1 , Zhigang Huang 1 , Xuerong Mao 2 * 1 School of Economics and Management, Fuzhou University, China 2 Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, U.K. AbstractStock market linked savings accounts have become more and more popular. The returns of these accounts are random so the returns, even the initial capital, are not guaranteed. They are very much different from the familiar fixed-term-fixed-rate savings accounts. The aim of this paper is to perform the stochastic and numerical analysis on the stock market linked savings accounts in order to establish the theory on the mean percentage of return (MPR). We will mainly perform the case studies on 5 typical plans linked to the UK Financial Times Stock Exchange (FTSE) 100 Index, but the theory developed is fully illustrated so that it can be applied to other plans by the reader.

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Gaussian Estimation of Single‐Factor Continuous Time Models of The Term Structure of Interest Rates

Cited by 159 publications

References 31 publications

Parameter estimation and bias correction for diffusion processes

Parameter estimation and bias correction for diffusion processes

Adaptive Lasso-Type Estimation for Multivariate Diffusion Processes

Mean percentage of returns for stock market linked savings accounts

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