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Dr. Woraphon Yamaka
Center of Excellence in Econometrics, Chiang Mai University

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0 Machine Learning Application
0 Statistcal modeling

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Conference paper
Published: 27 July 2021 in Prediction and Causality in Econometrics and Related Topics
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As we expect the heterogeneous effect of oil shocks on the exchange rate, in this paper, we consider using the Markov switching approach to quantify this shock’s effect in a different state of the economy, namely economic downturn, and upturn. We first quantify the structural oil shocks and find the causal effect of these shock indicators on BRICS currencies. Our empirical results demonstrate the presence of a non-linear structure of BRICS exchange rates, with the different effects of oil shocks on real exchange rates. Besides, there exists a strong effect of the oil shocks on real exchange rates in three countries, namely India, Russia, and South Africa.

ACS Style

Jirawan Suwannajak; Woraphon Yamaka; Songsak Sriboonchitta. The Impact of Oil Shock on Exchange Rates in BRICS Countries: A Markov Switching Model. Prediction and Causality in Econometrics and Related Topics 2021, 413 -422.

AMA Style

Jirawan Suwannajak, Woraphon Yamaka, Songsak Sriboonchitta. The Impact of Oil Shock on Exchange Rates in BRICS Countries: A Markov Switching Model. Prediction and Causality in Econometrics and Related Topics. 2021; ():413-422.

Chicago/Turabian Style

Jirawan Suwannajak; Woraphon Yamaka; Songsak Sriboonchitta. 2021. "The Impact of Oil Shock on Exchange Rates in BRICS Countries: A Markov Switching Model." Prediction and Causality in Econometrics and Related Topics , no. : 413-422.

Conference paper
Published: 27 July 2021 in Prediction and Causality in Econometrics and Related Topics
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In this study, we propose a copula-based stochastic production frontier efficiency effects model. This model estimates the inefficiency scores and exogenous effects in one single step. As the conventional model contains two independent error components with one representing the inefficiency effects and the other assuming the random normal errors, we are concerned about the independence error terms assumption in the conventional approach. Thus, we relax this assumption and join the two errors through copula function. The model is investigated for its performance using the simulation and real data sets. The results show the accuracy and higher performance of our model when compared to the classical model specifications.

ACS Style

Woraphon Yamaka. Efficiency Effects in a Copula Based Stochastic Frontier Model. Prediction and Causality in Econometrics and Related Topics 2021, 113 -122.

AMA Style

Woraphon Yamaka. Efficiency Effects in a Copula Based Stochastic Frontier Model. Prediction and Causality in Econometrics and Related Topics. 2021; ():113-122.

Chicago/Turabian Style

Woraphon Yamaka. 2021. "Efficiency Effects in a Copula Based Stochastic Frontier Model." Prediction and Causality in Econometrics and Related Topics , no. : 113-122.

Conference paper
Published: 27 July 2021 in Prediction and Causality in Econometrics and Related Topics
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This paper examines the dynamic volatility relationship following the COVID-19 impacts in three developed stock markets (DM) and three emerging stock markets (EM) using the DCC-GARCH-type models with various distributions. The finding indicates that the DCC-GARCH-X model with student-t distribution outperforms those with Gaussian and Skew student-t distributions for our dataset. Volatilities were found to be high during the COVID-19 pandemic and they were higher in the emerging markets than in the developed markets. The result on the volatility of each country confirms the high persistence of volatility in all stock market returns except for Italy. Our empirical results highlight the weak positive impact of COVID-19 pandemic on some developed and emerging stock volatilities.

ACS Style

Pichayakone Rakpho; Woraphon Yamaka; Terdthiti Chitkasame. Developed and Emerging Stock Markets Volatility During the Global Pandemic of Coronavirus Disease 2019 (COVID-19): Dynamic Correlation Approach. Prediction and Causality in Econometrics and Related Topics 2021, 446 -456.

AMA Style

Pichayakone Rakpho, Woraphon Yamaka, Terdthiti Chitkasame. Developed and Emerging Stock Markets Volatility During the Global Pandemic of Coronavirus Disease 2019 (COVID-19): Dynamic Correlation Approach. Prediction and Causality in Econometrics and Related Topics. 2021; ():446-456.

Chicago/Turabian Style

Pichayakone Rakpho; Woraphon Yamaka; Terdthiti Chitkasame. 2021. "Developed and Emerging Stock Markets Volatility During the Global Pandemic of Coronavirus Disease 2019 (COVID-19): Dynamic Correlation Approach." Prediction and Causality in Econometrics and Related Topics , no. : 446-456.

Journal article
Published: 28 April 2021 in Applied Sciences
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As the conventional models for time series forecasting often use single-valued data (e.g., closing daily price data or the end of the day data), a large amount of information during the day is neglected. Traditionally, the fixed reference points from intervals, such as midpoints, ranges, and lower and upper bounds, are generally considered to build the models. However, as different datasets provide different information in intervals and may exhibit nonlinear behavior, conventional models cannot be effectively implemented and may not be guaranteed to provide accurate results. To address these problems, we propose the artificial neural network with convex combination (ANN-CC) model for interval-valued data. The convex combination method provides a flexible way to explore the best reference points from both input and output variables. These reference points were then used to build the nonlinear ANN model. Both simulation and real application studies are conducted to evaluate the accuracy of the proposed forecasting ANN-CC model. Our model was also compared with traditional linear regression forecasting (information-theoretic method, parametrized approach center and range) and conventional ANN models for interval-valued data prediction (regularized ANN-LU and ANN-Center). The simulation results show that the proposed ANN-CC model is a suitable alternative to interval-valued data forecasting because it provides the lowest forecasting error in both linear and nonlinear relationships between the input and output data. Furthermore, empirical results on two datasets also confirmed that the proposed ANN-CC model outperformed the conventional models.

ACS Style

Woraphon Yamaka; Rungrapee Phadkantha; Paravee Maneejuk. A Convex Combination Approach for Artificial Neural Network of Interval Data. Applied Sciences 2021, 11, 3997 .

AMA Style

Woraphon Yamaka, Rungrapee Phadkantha, Paravee Maneejuk. A Convex Combination Approach for Artificial Neural Network of Interval Data. Applied Sciences. 2021; 11 (9):3997.

Chicago/Turabian Style

Woraphon Yamaka; Rungrapee Phadkantha; Paravee Maneejuk. 2021. "A Convex Combination Approach for Artificial Neural Network of Interval Data." Applied Sciences 11, no. 9: 3997.

Article
Published: 20 April 2021 in Quantum Information Processing
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Let p be an odd prime and m be a positive integer, \(q=p^m\), \({\mathcal {R}}={\mathbb {F}}_q+u{\mathbb {F}}_q\) with \(u^2=u\), and \({\mathcal {S}}={\mathbb {F}}_q+u{\mathbb {F}}_q+v{\mathbb {F}}_q\) with \(u^2=u, v^2=v, uv=vu=0\) and \(\Lambda =(\lambda _1,\lambda _2,\lambda _3)\in {\mathbb {F}}_q{\mathcal {R}}{\mathcal {S}}\). In this paper, we study the algebraic structure of constacyclic codes over \({\mathcal {R}}\) and \({\mathcal {S}}\). Further, we discuss the structure of \({\mathbb {F}}_q{\mathcal {R}}{\mathcal {S}}\)-\(\Lambda \)-constacyclic codes of block length \((\alpha ,\beta ,\gamma )\). This family of codes can be viewed as \({\mathcal {S}}[x]\)-submodules of \(\frac{{\mathbb {F}}_q[x]}{\langle x^{\alpha }-\lambda _1\rangle }\times \frac{{\mathcal {R}}[x]}{\langle x^{\beta }-\lambda _2\rangle }\times \frac{{\mathcal {S}}[x]}{\langle x^{\gamma }-\lambda _3\rangle }\). The generator polynomials of this family of codes are discussed. As application, we discuss the construction of quantum error-correcting codes (QECCs) from constacyclic codes over \({\mathbb {F}}_q{\mathcal {R}}{\mathcal {S}}\) and obtain several new QECCs from this study.

ACS Style

Hai Q. Dinh; Sachin Pathak; Tushar Bag; Ashish Kumar Upadhyay; Woraphon Yamaka. Constacyclic codes over mixed alphabets and their applications in constructing new quantum codes. Quantum Information Processing 2021, 20, 1 -35.

AMA Style

Hai Q. Dinh, Sachin Pathak, Tushar Bag, Ashish Kumar Upadhyay, Woraphon Yamaka. Constacyclic codes over mixed alphabets and their applications in constructing new quantum codes. Quantum Information Processing. 2021; 20 (4):1-35.

Chicago/Turabian Style

Hai Q. Dinh; Sachin Pathak; Tushar Bag; Ashish Kumar Upadhyay; Woraphon Yamaka. 2021. "Constacyclic codes over mixed alphabets and their applications in constructing new quantum codes." Quantum Information Processing 20, no. 4: 1-35.

Focus
Published: 17 April 2021 in Soft Computing
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When modeling the kink regression model, it is possible to have an excessive number of explanatory variables and their corresponding coefficients, thereby leading to the over-parameterization and multicollinearity problems. Motivated by these problems, five sparse estimation methods, namely LASSO, sparse Ridge, SCAD, MCP, and Bridge, are considered to perform simultaneous variable selection and parameter estimation, as alternatives to the Ordinary Least Squares (OLS), in the kink regression model. To compare the performance of these sparse estimators, both simulation and real data applications are proposed. According to the simulation results, we demonstrate the superior performance of sparse estimations in terms of selection accuracy and prediction by comparing them to the non-sparse estimations. However, it is not apparent which sparse estimations are more appropriate for estimating the kink regression. However, in an application study, the comparison result indicates that the SCAD penalty would be a preferable penalty function for the application of kink regression to the life expectancy data as the lowest EBIC and the highest \({\text{Adj - }}R^{2}\) are obtained.

ACS Style

Woraphon Yamaka. Sparse estimations in kink regression model. Soft Computing 2021, 25, 7825 -7838.

AMA Style

Woraphon Yamaka. Sparse estimations in kink regression model. Soft Computing. 2021; 25 (12):7825-7838.

Chicago/Turabian Style

Woraphon Yamaka. 2021. "Sparse estimations in kink regression model." Soft Computing 25, no. 12: 7825-7838.

Focus
Published: 15 April 2021 in Soft Computing
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In this paper, the interval approach for Markov switching capital asset pricing model (MS-CAPM) is proposed to quantify the beta risk in two different regimes, namely a bull and a bear regimes. Instead of fitting a MS-CAPM on specific fixed reference points, such as midpoints (center method), and lower and upper bounds (MinMax method), this study suggests choosing the reference points that better represent the intervals of excess stock return and excess market return. Therefore, the convex combination (CC) method is introduced to fit the interval MS-CAPM. The proposed interval MS-CAPM performance based on the CC method is assessed and compared with the center method and the MinMax method through a simulation study and two application studies.

ACS Style

Woraphon Yamaka; Rungrapee Phadkantha. A convex combination approach for Markov switching CAPM of interval data. Soft Computing 2021, 25, 7839 -7851.

AMA Style

Woraphon Yamaka, Rungrapee Phadkantha. A convex combination approach for Markov switching CAPM of interval data. Soft Computing. 2021; 25 (12):7839-7851.

Chicago/Turabian Style

Woraphon Yamaka; Rungrapee Phadkantha. 2021. "A convex combination approach for Markov switching CAPM of interval data." Soft Computing 25, no. 12: 7839-7851.

Original research
Published: 31 March 2021 in Journal of Applied Mathematics and Computing
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In this paper, we classify all self-dual \(\lambda \)-constacyclic codes of length \(2^s\) over the finite commutative local ring \(R_{u^2, v^2,2^m}=\mathbb {F}_{2^m}[u,v]/\langle u^2, v^2, uv-vu \rangle \) corresponding to units of the forms \(\lambda =\alpha +\gamma v+\delta uv\), \(\alpha +\beta u+\delta uv\), \(\alpha +\beta u+\gamma v+\delta uv\), where \(\alpha ,\beta ,\gamma \in \mathbb {F}^*_{2^m}\) and \(\delta \in \mathbb {F}_{2^m}\). Moreover, the Hamming distance of these \(\lambda \)-constacyclic codes are completely determined.

ACS Style

Hai Q. Dinh; Pramod Kumar Kewat; Sarika Kushwaha; Woraphon Yamaka. Self-dual constacyclic codes of length $$2^s$$ over the ring $$\mathbb {F}_{2^m}[u,v]/\langle u^2, v^2, uv-vu \rangle $$. Journal of Applied Mathematics and Computing 2021, 1 -29.

AMA Style

Hai Q. Dinh, Pramod Kumar Kewat, Sarika Kushwaha, Woraphon Yamaka. Self-dual constacyclic codes of length $$2^s$$ over the ring $$\mathbb {F}_{2^m}[u,v]/\langle u^2, v^2, uv-vu \rangle $$. Journal of Applied Mathematics and Computing. 2021; ():1-29.

Chicago/Turabian Style

Hai Q. Dinh; Pramod Kumar Kewat; Sarika Kushwaha; Woraphon Yamaka. 2021. "Self-dual constacyclic codes of length $$2^s$$ over the ring $$\mathbb {F}_{2^m}[u,v]/\langle u^2, v^2, uv-vu \rangle $$." Journal of Applied Mathematics and Computing , no. : 1-29.

Journal article
Published: 02 March 2021 in Mathematics
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This study investigates the nonlinear impact of various modes of transportation (air, road, railway, and maritime) on the number of foreign visitors to China originating from major source countries. Our nonlinear tourism demand equations are determined through the Markov-switching regression (MSR) model, thereby, capturing the possible structural changes in Chinese tourism demand. Due to many variables and the limitations from the small number of observations confronted in this empirical study, we may face multicollinearity and endogeneity bias. Therefore, we introduce the two penalized maximum likelihoods, namely Ridge and Lasso, to estimate the high dimensional parameters in the MSR model. This investigation found the structural changes in all tourist arrival series with significant coefficient shifts in transportation variables. We observe that the coefficients are relatively more significant in regime 1 (low tourist arrival regime). The coefficients in regime 1 are all positive (except railway length in operation), while the estimated coefficients in regime 2 are positive in fewer numbers and weak. This study shows that, in the process of transportation, development and changing inbound tourism demand from ten countries, some variables with the originally strong positive effect will have a weak positive effect when tourist arrivals are classified in the high tourist arrival regime.

ACS Style

Woraphon Yamaka; Xuefeng Zhang; Paravee Maneejuk. Analyzing the Influence of Transportations on Chinese Inbound Tourism: Markov Switching Penalized Regression Approaches. Mathematics 2021, 9, 515 .

AMA Style

Woraphon Yamaka, Xuefeng Zhang, Paravee Maneejuk. Analyzing the Influence of Transportations on Chinese Inbound Tourism: Markov Switching Penalized Regression Approaches. Mathematics. 2021; 9 (5):515.

Chicago/Turabian Style

Woraphon Yamaka; Xuefeng Zhang; Paravee Maneejuk. 2021. "Analyzing the Influence of Transportations on Chinese Inbound Tourism: Markov Switching Penalized Regression Approaches." Mathematics 9, no. 5: 515.

Original research
Published: 05 February 2021 in Social Indicators Research
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In this paper, we analyze time-varying predictability of labor productivity for growth in income (and consumption) inequality of the United Kingdom (UK) based on a high-frequency (quarterly) data set over 1975:Q1 to 2016:Q1. Results indicate that the growth rate of an index of labor productivity has a strong predictive power on growth rate of income (and consumption) inequality in the UK. Interestingly, the strength of the predictive power is found to be higher towards the end of the sample period in the wake of the global financial crisis. In addition, based on time-varying impulse response function analysis, we find that inequality and labor productivity growth rates are in general negatively associated over our sample period, barring a short-lived positive impact initially.

ACS Style

David Gabauer; Rangan Gupta; Jacobus Nel; Woraphon Yamaka. Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom. Social Indicators Research 2021, 155, 771 -788.

AMA Style

David Gabauer, Rangan Gupta, Jacobus Nel, Woraphon Yamaka. Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom. Social Indicators Research. 2021; 155 (3):771-788.

Chicago/Turabian Style

David Gabauer; Rangan Gupta; Jacobus Nel; Woraphon Yamaka. 2021. "Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom." Social Indicators Research 155, no. 3: 771-788.

Journal article
Published: 04 February 2021 in Discrete Mathematics
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Let R=F2+uF2 (u2=0) and S=F2+uF2+u2F2 (u3=0) be two finite commutative chain rings. This paper studies F2RS-cyclic codes, which are described as S[x]-submodules of the S[x]-module F2[x]∕〈xr−1〉×R[x]∕〈xs−1〉×S[x]∕〈xt−1〉. We study their generator polynomials and the minimal generating sets. We classify each case of the generating sets separately and determine the size of each such case. Free F2RS-cyclic codes and separable codes are discussed, and the structural properties of dual codes of free F2RS-cyclic codes are investigated. Moreover, we determine the relationship between the generator polynomials of free F2RS-cyclic codes and their duals. As applications, we provide several examples of optimal and near-optimal binary codes which are obtained from the Gray images of F2RS-cyclic codes.

ACS Style

Hai Q. Dinh; Sachin Pathak; Tushar Bag; Ashish Kumar Upadhyay; Ramakrishna Bandi; Woraphon Yamaka. On F2RS-cyclic codes and their applications in constructing optimal codes. Discrete Mathematics 2021, 344, 112310 .

AMA Style

Hai Q. Dinh, Sachin Pathak, Tushar Bag, Ashish Kumar Upadhyay, Ramakrishna Bandi, Woraphon Yamaka. On F2RS-cyclic codes and their applications in constructing optimal codes. Discrete Mathematics. 2021; 344 (5):112310.

Chicago/Turabian Style

Hai Q. Dinh; Sachin Pathak; Tushar Bag; Ashish Kumar Upadhyay; Ramakrishna Bandi; Woraphon Yamaka. 2021. "On F2RS-cyclic codes and their applications in constructing optimal codes." Discrete Mathematics 344, no. 5: 112310.

Journal article
Published: 07 January 2021 in Sustainability
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: This study analyzed the nonlinear impacts of education, particularly higher education, on economic growth in the ASEAN-5 countries (i.e., Thailand, Indonesia, Malaysia, Singapore, and the Philippines) over the period 2000–2018. The impacts of education on economic growth are assessed through various education indicators, consisting of public expenditure on tertiary education per student, enrolment rates of primary, secondary, and tertiary levels, educated workforce, and the novel indicator of unemployment rates with advanced education. This study establishes nonlinear regression models—the time-series kink regression and the panel kink regression—to investigate the kink effects of education on the individual country’s economic growth and the ASEAN-5 region, respectively. There are three main findings. Firstly, the nonlinear effects of the government expenditure per tertiary student on economic growth are confirmed for the ASEAN-5 region. However, the impacts do not follow the law of diminishing returns. Secondly, our findings reveal that an increase in unemployment of advanced educated workers can positively or negatively impact economic growth, which requires an appropriate policy to handle the negative impacts. Lastly, secondary and higher education enrollment rates can contribute to the ASEAN-5’s economic growth (both the individual and regional levels). However, the regional analysis reveals that higher education impacts become twice as strong when the enrollment rates are greater than a certain level (a kink point). Therefore, we may conclude that secondary enrollment rates positively affect economic growth; however, higher education is the key to future growth and sustainability.

ACS Style

Paravee Maneejuk; Woraphon Yamaka. The Impact of Higher Education on Economic Growth in ASEAN-5 Countries. Sustainability 2021, 13, 520 .

AMA Style

Paravee Maneejuk, Woraphon Yamaka. The Impact of Higher Education on Economic Growth in ASEAN-5 Countries. Sustainability. 2021; 13 (2):520.

Chicago/Turabian Style

Paravee Maneejuk; Woraphon Yamaka. 2021. "The Impact of Higher Education on Economic Growth in ASEAN-5 Countries." Sustainability 13, no. 2: 520.

Journal article
Published: 24 December 2020 in Finite Fields and Their Applications
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Let p≠3 be a prime, s, m be positive integers, and λ be a nonzero element of the finite field Fpm. In [22] and [20], when the generator polynomials have one or two different irreducible factors, the Hamming distances of λ-constacyclic codes of length 3ps over Fpm have been considered. In this paper, we obtain that the Hamming distances of the repeated-root λ-constacyclic codes of length lps can be determined by the Hamming distances of the simple-root γ-constacyclic codes of length l, where l is a positive integer and λ=γps. Based on this result, the Hamming distances of the repeated-root λ-constacyclic codes of length 3ps are given when the generator polynomials have three different irreducible factors. Hence, the Hamming distances of all such constacyclic codes are determined. As an application, we obtain all optimal λ-constacyclic codes of length 3ps with respect to the Griesmer bound and the Singleton bound. Among others, several examples show that some of our codes have the best known parameters with respect to the code tables in [19].

ACS Style

Hai Q. Dinh; Xiaoqiang Wang; Hongwei Liu; Woraphon Yamaka. Hamming distances of constacyclic codes of length 3p and optimal codes with respect to the Griesmer and Singleton bounds. Finite Fields and Their Applications 2020, 70, 101794 .

AMA Style

Hai Q. Dinh, Xiaoqiang Wang, Hongwei Liu, Woraphon Yamaka. Hamming distances of constacyclic codes of length 3p and optimal codes with respect to the Griesmer and Singleton bounds. Finite Fields and Their Applications. 2020; 70 ():101794.

Chicago/Turabian Style

Hai Q. Dinh; Xiaoqiang Wang; Hongwei Liu; Woraphon Yamaka. 2020. "Hamming distances of constacyclic codes of length 3p and optimal codes with respect to the Griesmer and Singleton bounds." Finite Fields and Their Applications 70, no. : 101794.

Journal article
Published: 17 November 2020 in IEEE Access
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The motivation of this study is built from the previous research to find a way to enhance the forecast of advanced and emerging market currency volatilities. Given the exchange rate’s nonlinear and time-varying characteristics, we introduce the neural networks (NN) approach to enhance the Markov Switching Beta-Exponential Generalized Autoregressive Conditional Heteroscedasticity (MS-Beta-t-EGARCH) model. Our hybrid model synthesizes these two approaches’ advantages to predict exchange rate volatility. We validate the performance of our proposed model by comparing it with various traditional volatility forecasting models. In-sample and out-of-sample volatility forecasts are considered to achieve our comparison. The empirical results suggest that our hybrid NN-MS Beta-t-EGARCH outperforms the other models for both emerging and advanced market currencies.

ACS Style

Ruofan Liao; Woraphon Yamaka; Songsak Sriboonchitta. Exchange Rate Volatility Forecasting by Hybrid Neural Network Markov Switching Beta-t-EGARCH. IEEE Access 2020, 8, 207563 -207574.

AMA Style

Ruofan Liao, Woraphon Yamaka, Songsak Sriboonchitta. Exchange Rate Volatility Forecasting by Hybrid Neural Network Markov Switching Beta-t-EGARCH. IEEE Access. 2020; 8 ():207563-207574.

Chicago/Turabian Style

Ruofan Liao; Woraphon Yamaka; Songsak Sriboonchitta. 2020. "Exchange Rate Volatility Forecasting by Hybrid Neural Network Markov Switching Beta-t-EGARCH." IEEE Access 8, no. : 207563-207574.

Chapter
Published: 14 November 2020 in Econometrics for Financial Applications
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This study aims to determine the effects of macroeconomic factors on trade openness. We use panel regression with heterogeneous time trends to explore the causal relationship between macroeconomic factors and trade openness. The analysis relies on a sample of 85 countries for the period 1990–2017. We segment the data set into three sub-panels according to per capita income classification that distinguishes countries as belonging to low-income, middle-income, and high-income groups. Various types of panel regression are also considered, and it is found that time fixed effects model is the best model for all income groups. The key finding of this study is that GDP per capita shows a decisive evidence for its positive effects on trade openness in all income groups.

ACS Style

Wiranya Puntoon; Jirawan Suwannajak; Woraphon Yamaka. Macroeconomic Determinants of Trade Openness: Empirical Investigation of Low, Middle and High-Income Countries. Econometrics for Financial Applications 2020, 383 -395.

AMA Style

Wiranya Puntoon, Jirawan Suwannajak, Woraphon Yamaka. Macroeconomic Determinants of Trade Openness: Empirical Investigation of Low, Middle and High-Income Countries. Econometrics for Financial Applications. 2020; ():383-395.

Chicago/Turabian Style

Wiranya Puntoon; Jirawan Suwannajak; Woraphon Yamaka. 2020. "Macroeconomic Determinants of Trade Openness: Empirical Investigation of Low, Middle and High-Income Countries." Econometrics for Financial Applications , no. : 383-395.

Chapter
Published: 14 November 2020 in Econometrics for Financial Applications
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Recently, regression kink model has gained an increasing popularity as it provides a richer information than the ordinary linear model in the light of an economic structural change. However, as the number of parameters in the kink regression model is larger than that of the linear version, the traditional least squares estimates are not valid and may provide infinite solutions, especially when the number of observations is small and there are many coefficients. To deal with this problem, the LASSO variable selection method is suggested to estimate the unknown parameters in the model. It not only provides the estimated coefficients, but also shrinks the magnitude of all the coefficients and removes some whose values have been shrunk to zero. This process helps decrease variance without increasing the bias of the parameter estimates. Thus, LASSO could play an important role in the kink regression model building process, as it improves the result accuracy by choosing an appropriate subset of regression predictors.

ACS Style

Woraphon Yamaka. Variable Selection and Estimation in Kink Regression Model. Econometrics for Financial Applications 2020, 151 -164.

AMA Style

Woraphon Yamaka. Variable Selection and Estimation in Kink Regression Model. Econometrics for Financial Applications. 2020; ():151-164.

Chicago/Turabian Style

Woraphon Yamaka. 2020. "Variable Selection and Estimation in Kink Regression Model." Econometrics for Financial Applications , no. : 151-164.

Chapter
Published: 14 November 2020 in Econometrics for Financial Applications
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Google search volume index has been widely used as a proxy of investor attention. In this study, we use Google search volume index to forecast energy return volatility. In order to find the keywords, we start with glossary of crude oil terms provided by the U.S. Energy Information Administration (EIA) and then add keywords based on Google Search’s suggestions. Then, we arrive at a set of 75 Google keywords as a proxy of investor attention. As there are a large number of keywords to be considered, the conventional method may not be appropriate for the statistical inference. Thus, we propose using the LASSO to deal with this problem. Finally, we also compare the predictive power of LASSO with three types of stepwise method.

ACS Style

Payap Tarkhamtham; Woraphon Yamaka; Paravee Maneejuk. Forecasting Volatility of Oil Prices via Google Trend: LASSO Approach. Econometrics for Financial Applications 2020, 459 -471.

AMA Style

Payap Tarkhamtham, Woraphon Yamaka, Paravee Maneejuk. Forecasting Volatility of Oil Prices via Google Trend: LASSO Approach. Econometrics for Financial Applications. 2020; ():459-471.

Chicago/Turabian Style

Payap Tarkhamtham; Woraphon Yamaka; Paravee Maneejuk. 2020. "Forecasting Volatility of Oil Prices via Google Trend: LASSO Approach." Econometrics for Financial Applications , no. : 459-471.

Chapter
Published: 14 November 2020 in Econometrics for Financial Applications
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This study aims to apply the concept of mixed copula to the problem of finding the risk, return, and portfolio diversification at the industry level in the stock markets of Thailand and Vietnam. Six industry indices are considered in this study. Prior to constructing the portfolio, we compare the mixed copula with the traditional copula to show the better performance of the mixed copula in terms of the lower AIC and BIC. The empirical results show that the mixed Student-t and Clayton copula model can capture the dependence structure of the portfolio returns much better than the traditional model. Then, we apply the best-fit model to do the Monte Carlo simulation for constructing the efficiency frontier and find the optimal investment combination from five portfolio optimization approaches including Uniform portfolio, Global Minimum Variance Portfolio (GMVP), Markowitz portfolio, Maximum Sharpe ratio portfolio, and Long-Short quintile. The findings suggest that, overall, the industry index of Vietnam and the consumer services index of Thailand should be given primary attention because they exhibit the highest performance compared to other industries in the stock markets. This suggestion is supported by the results of the Maximum Sharpe ratio portfolio (the best portfolio optimization approach) that assign the largest portfolio allocation to the industry sector for Vietnam and the consumer services sector for Thailand.

ACS Style

Sukrit Thongkairat; Woraphon Yamaka. Risk, Return, and Portfolio Optimization for Various Industries Based on Mixed Copula Approach. Econometrics for Financial Applications 2020, 311 -325.

AMA Style

Sukrit Thongkairat, Woraphon Yamaka. Risk, Return, and Portfolio Optimization for Various Industries Based on Mixed Copula Approach. Econometrics for Financial Applications. 2020; ():311-325.

Chicago/Turabian Style

Sukrit Thongkairat; Woraphon Yamaka. 2020. "Risk, Return, and Portfolio Optimization for Various Industries Based on Mixed Copula Approach." Econometrics for Financial Applications , no. : 311-325.

Chapter
Published: 14 November 2020 in Econometrics for Financial Applications
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The phenomena of trade war between China and United States (US) leads us to examine the spillover effects of US stock market volatility on the BRICV stock markets (Brazil, Russia, India, China, and Vietnam). Thus, the dynamic correlations between US and each BRICV stock market, is measured using the flexible dynamic conditional correlations based bivariate GARCH-with-jumps model. The result of both classical bivariate GARCH(1,1) model and bivariate GARCH(1,1)-with-jumps model show that all stock returns have high volatility persistence with the value higher than 0.95. Moreover, the result of DCC-Copula part shows a dynamic correlations between US and each stock in BRICV. We find that the dynamic correlations for all pairs are similar and are not constant. We also find that US stock market has a positive correlations with BRICV stocks between 2012 and 2019. When, we compare the correlations between pre and post trade war in 2018, we observe that bivariate copula between US-China, US-Vietnam and US-Brazil seems to be affected by the trade war as there exhibit a large drop of the correlations after 2018.

ACS Style

Worrawat Saijai; Woraphon Yamaka; Paravee Maneejuk. Measuring Dependence in China-United States Trade War: A Dynamic Copula Approach for BRICV and US Stock Markets. Econometrics for Financial Applications 2020, 583 -595.

AMA Style

Worrawat Saijai, Woraphon Yamaka, Paravee Maneejuk. Measuring Dependence in China-United States Trade War: A Dynamic Copula Approach for BRICV and US Stock Markets. Econometrics for Financial Applications. 2020; ():583-595.

Chicago/Turabian Style

Worrawat Saijai; Woraphon Yamaka; Paravee Maneejuk. 2020. "Measuring Dependence in China-United States Trade War: A Dynamic Copula Approach for BRICV and US Stock Markets." Econometrics for Financial Applications , no. : 583-595.

Journal article
Published: 06 November 2020 in Mathematics
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Let R=F4+uF4,withu2=u and S=F4+uF4+vF4,withu2=u,v2=v,uv=vu=0. In this paper, we study F4RS-cyclic codes of block length (α,β,γ) and construct cyclic DNA codes from them. F4RS-cyclic codes can be viewed as S[x]-submodules of Fq[x]〈xα−1〉×R[x]〈xβ−1〉×S[x]〈xγ−1〉. We discuss their generator polynomials as well as the structure of separable codes. Using the structure of separable codes, we study cyclic DNA codes. By using Gray maps ψ1 from R to F42 and ψ2 from S to F43, we give a one-to-one correspondence between DNA codons of the alphabets {A,T,G,C}2,{A,T,G,C}3 and the elements of R,S, respectively. Then we discuss necessary and sufficient conditions of cyclic codes over F4, R, S and F4RS to be reversible and reverse-complement. As applications, we provide examples of new cyclic DNA codes constructed by our results.

ACS Style

Hai Dinh; Sachin Pathak; Ashish Upadhyay; Woraphon Yamaka. New DNA Codes from Cyclic Codes over Mixed Alphabets. Mathematics 2020, 8, 1977 .

AMA Style

Hai Dinh, Sachin Pathak, Ashish Upadhyay, Woraphon Yamaka. New DNA Codes from Cyclic Codes over Mixed Alphabets. Mathematics. 2020; 8 (11):1977.

Chicago/Turabian Style

Hai Dinh; Sachin Pathak; Ashish Upadhyay; Woraphon Yamaka. 2020. "New DNA Codes from Cyclic Codes over Mixed Alphabets." Mathematics 8, no. 11: 1977.