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Open Journal of Statistics 2012年第5期2卷 498-503页

作者： pham van khanh Military Technical Academy Hanoi Vietnam

This paper considered an autoregressive time series where the slope contains random components with non-negative values. The authors determine the stationary condition of the series to estimate its parameters by the quasi-maximum likelihood method. The authors also simulates and estimates the coefficients of the simulation chain. In this paper, we consider modeling and forecasting gold chain on the free market in Hanoi, Vietnam.

关键词： Random Coefficient Autoregressive Model Quasi-Maximum Likelihood Consistency

When to Sell an Asset Where Its Drift Drops from a High Value to a Smaller One

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American Journal of Operations Research 2015年第6期5卷 514-525页

作者： pham van khanh Institute of Economics and Corporate Group Hanoi Vietnam

To solve the selling problem which is resembled to the buying problem in [1], in this paper we solve the problem of determining the optimal time to sell a property in a location the drift of the asset drops from a high value to a smaller one at some random change-point. This change-point is not directly observable for the investor, but it is partially observable in the sense that it coincides with one of the jump times of some exogenous Poisson process representing external shocks, and these jump times are assumed to be observable. The asset price is modeled as a geometric Brownian motion with a drift that initially exceeds the discount rate, but with the opposite relation after an unobservable and exponentially distributed time and thus, we model the drift as a two-state Markov chain. Using filtering and martingale techniques, stochastic analysis transform measurement, we reduce the problem to a one-dimensional optimal stopping problem. We also establish the optimal boundary at which the investor should liquidate the asset when the price process hit the boundary at first time.

关键词： Optimal Stopping Time Posterior Probability Threshold Markov Chain Jump Times Martingale Brownian Motion

Optimal Stopping Time to Buy an Asset When Growth Rate Is a Two-State Markov Chain

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American Journal of Operations Research 2014年第3期4卷 132-141页

作者： pham van khanh Military Technical Academy Hanoi Vietnam

In this paper we consider the problem of determining the optimal time to buy an asset in a position of an uptrend or downtrend in the financial market and currency market as well as other markets. Asset price is modeled as a geometric Brownian motion with drift being a two-state Markov chain. Based on observations of asset prices, investors want to detect the change points of price trends as accurately as possible, so that they can make the decision to buy. Using filtering techniques and stochastic analysis, we will develop the optimal boundary at which investors implement their decisions when the posterior probability process reaches a certain threshold.

关键词： Optimal Stopping Time Posterior Probability Threshold

Comparisons of VAR Model and Models Created by Genetic Programming in Consumer Price Index Prediction in Vietnam

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Open Journal of Statistics 2012年第3期2卷 237-250页

作者： pham van khanh Military Technical Academy Hanoi Vietnam

In this paper, we present an application of Genetic Programming (GP) to Vietnamese CPI in?ation one-step prediction problem. This is a new approach in building a good forecasting model, and then applying inflation forecasts in Vietnam in current stage. The study introduces the within-sample and the out-of-samples one-step-ahead forecast errors which have positive correlation and approximate to a linear function with positive slope in prediction models by GP. We also build Vector Autoregression (VAR) model to forecast CPI in quaterly data and compare with the models created by GP. The experimental results show that the Genetic Programming can produce the prediction models having better accuracy than Vector Autoregression models. We have no relavant variables (m2, ex) of monthly data in the VAR model, so no prediction results exist to compare with models created by GP and we just forecast CPI basing on models of GP with previous data of CPI.

关键词： Vector Autoregression Genetic Programming CPI Inflation Forecast

Optimal Stopping Time for Holding an Asset

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American Journal of Operations Research 2012年第4期2卷 527-535页

作者： pham van khanh Military Technical Academy Hanoi Vietnam

In this paper, we consider the problem to determine the optimal time to sell an asset that its price conforms to the Black-Schole model but its drift is a discrete random variable taking one of two given values and this probability distribution behavior changes chronologically. The result of finding the optimal strategy to sell the asset is the first time asset price falling into deterministic time-dependent boundary. Moreover, the boundary is represented by an increasing and continuous monotone function satisfying a nonlinear integral equation. We also conduct to find the empirical optimization boundary and simulate the asset price process.

关键词： Optimal Stopping Time Boundary Brownian Motion Black-Schole Model

A Chance–Constrained Data Envelopment Analysis Approach to Problem Provincial Productivity Growth in Vietnamese Agriculture from 1995 to 2007

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Open Journal of Statistics 2011年第3期1卷 217-235页

作者： Nguyen Khac Minh pham van khanh 不详

This study employs a chance-constrained data envelopment analysis (CDEA) approach with two models (model A and model B) to decompose provincial productivity growth in Vietnamese agriculture from 1995 to 2007 into technological progress and efficiency change. The differences between the chance - constrained programming model A and model B are assumptions imposed on the covariance matrix. The decomposition allows us to identify the contributions of technical change and the improvement in technical efficiency to productivity growth in Vietnamese production. Sixty-one provinces in Vietnam are classified into Mekong - technology and other -technology categories. We conduct a Mann-Whitney test to verify whether the two samples, the Mekong technology province sample and the other technology sample, are drawn from the same productivity change populations. The result of the Mann-Whitney test indicates that the differences between the Mekong technology category and the other technology category from two models are more significant. Two important questions are whether some provinces in the samples could maintain their relative efficiency rank positions in comparison with the others over the study period and how to further examine the agreements between the two models. The Kruskal - Wallis test statistic shows that technical efficiency from both models for some provinces are higher than those of them in the study period. The Malmquist results show that production frontier has contracted by around 1.3 percent and 0.31 percent from chance-constrained model A and model B, respectively, a year on average over the sample period. To examine the agreements or disagreements in the total factor productivity indexes we compute the correlation between Malmquist indexes, which is positive and not very high. Thus there is a little discrepancy between the two Malmquist indexes, estimated from the chance - constrained models A and B.

关键词： Total Factor Productivity Technical Efficiency Change Technological Progress Chance-Constrained Programming

Forecasting the Convergence State of per Capital Income in Vietnam

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American Journal of Operations Research 2013年第6期3卷 487-496页

作者： Nguyen Khac Minh pham van khanh Military Technical Academy Hanoi Vietnam National Economics University Hanoi Vietnam

Convergence problem of an economic variable represents an underlying forecast of neoclassical economic growth model. This paper aims to analyze the convergence of provincial per capita GDP stability in Vietnam over the period of 1991-2007. This can be done by two approaches including bias data-based regression method for testing convergence and Markov chain model for describing features of long-term tendency of per capita income in Vietnam growth in provinces. The regression method results in the signs of convergence. To apply Markov process, we divide total pattern into 5 per capita income classes. Result estimated from the Markov chain model shows the poor convergence.

关键词： Convergence Regression Method Markov Proces

A New Approach for Ranking Efficient Units in Data Envelopment Analysis and Application to a Sample of Vietnamese Agricultural Bank Branches

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American Journal of Operations Research 2012年第1期2卷 126-136页

作者： Nguyen Khac Minh pham van khanh pham Anh Tuan Air Defence-Air Force Academy Hanoi Vietnam Military Technical Academy Hanoi Vietnam Water Resources University Hanoi Vietnam

This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of efficiency (SBM) for dealing with objective function used to classify all of the decision-making units allows the ranking of all inefficient DMUs and overcomes the disadvantages of infeasibility. This method also is applied to rank super-efficient scores for the sample of 145 agricultural bank branches in Viet Nam during 2007-2010. We then compare the estimated results from the new SCI model and the exsisting SBM model by using some statistical tests.

关键词： Data Envelopment Analysis (DEA) Slacks-Based Measure of Efficiency (SBM) SCI Super-Efficient

The Optimal Stopping Time for Selling an Asset When It Is Uncertain Whether the Price Process Is Increasing or Decreasing When the Horizon Is Infinite

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American Journal of Operations Research 2018年第2期8卷 82-91页

作者： Nguyen Khac Minh Nguyen Thanh Trung pham van khanh Thang Long Institute of Mathematics and Applied Science Hanoi Vietnam Faculty of Fundamental Science Military Academy of Logistics Hanoi Vietnam

Assume that we want to shell an asset with unknown drift but known that the drift is a two value random variable, and the initial distribution can be estimated. As time goes by, this distribution is updated and base on the probability of the drift takes the small one gives us the stopping rule. Research results show that the optimal strategy to sell the asset is if the initial probability that the drift receives a small value greater than a certain threshold then liquidates the asset immediately, otherwise the asset holder will wait until the probability of the drift receives a small value passing a certain threshold, it is the optimal time to liquidate the asset.

关键词： Optimal Stopping Time Incomplete Information Probability Process

Expanded Barro Regression in Studying Convergence Problem

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American Journal of Operations Research 2014年第5期4卷 301-310页

作者： Nguyen Khac Minh Nguyen Khac Minh pham van khanh National Economics University Hanoi Vietnam Institute of Economics and Corporate Group Hanoi Vietnam

This study develops the approach by Minh & khanh [1] to the classic Barro and Sala-i-Martin method [2], [3] named “expanded Barro regression method”, and applies this approach in analyzing the convergence of provincial per capita GDP in Vietnam over the period of 1991-2007. Different aspects of provincial convergence are considered in this paper. The estimated result on conver-gence from our model is compared to other models.

关键词： Convergence Barro Regression Markov Model Expanded Barro Regression