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Search Results: 1 - 10 of 1868 matches for " PhichHang Ou "
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Financial Volatility Forecasting by Least Square Support Vector Machine Based on GARCH, EGARCH and GJR Models: Evidence from ASEAN Stock Markets
Phichhang Ou,Hengshan Wang
International Journal of Economics and Finance , 2010, DOI: 10.5539/ijef.v2n1p51
Abstract: In this paper, we aim at comparing semi-parametric method, LSSVM (Least square support vector machine), with the classical GARCH(1,1), EGARCH(1,1) and GJR(1,1) models to forecast financial volatilities of three major ASEAN stock markets. More precisely, the experimental results suggest that using hybrid models, GARCH-LSSVM, EGARCH-LSSVM and GJR-LSSVM provides improved performances in forecasting the leverage effect volatilities, especially during the recently global financial market crashes in 2008.
Modeling and Forecasting Stock Market Volatility by Gaussian Processes based on GARCH, EGARCH and GJR Models
PhichHang Ou,Hengshan Wang
Lecture Notes in Engineering and Computer Science , 2011,
Abstract:
Prediction of Stock Market Index Movement by Ten Data Mining Techniques
Phichhang Ou,Hengshan Wang
Modern Applied Science , 2009, DOI: 10.5539/mas.v3n12p28
Abstract: Ability to predict direction of stock/index price accurately is crucial for market dealers or investors to maximize their profits. Data mining techniques have been successfully shown to generate high forecasting accuracy of stock price movement. Nowadays, in stead of a single method, traders need to use various forecasting techniques to gain multiple signals and more information about the future of the markets. In this paper, ten different techniques of data mining are discussed and applied to predict price movement of Hang Seng index of Hong Kong stock market. The approaches include Linear discriminant analysis (LDA), Quadratic discriminant analysis (QDA), K-nearest neighbor classification, Na ve Bayes based on kernel estimation, Logit model, Tree based classification, neural network, Bayesian classification with Gaussian process, Support vector machine (SVM) and Least squares support vector machine (LS-SVM). Experimental results show that the SVM and LS-SVM generate superior predictive performances among the other models. Specifically, SVM is better than LS-SVM for in-sample prediction but LS-SVM is, in turn, better than the SVM for the out-of-sample forecasts in term of hit rate and error rate criteria.
Predict GARCH Based Volatility of Shanghai Composite Index by Recurrent Relevant Vector Machines and Recurrent Least Square Support Vector Machines
Phichhang Ou,Hengshan Wang
Journal of Mathematics Research , 2010, DOI: 10.5539/jmr.v2n2p11
Abstract: A new machine learning method so called Relevant Vector Machine (RVM) is an efficiently learning technique for classification and regression problems, including financial time series forecasting. One of the main advantages is that the model is treated by Bayesian approach and its functional form is identical to a powerful prediction tool Support Vector Machine. In this paper, we propose a new recurrent algorithm of the relevant vector machine to predict GARCH (1,1) based volatility of Shanghai composite index. The recurrent support vector machine, recurrent least square support vector machine and normal GARCH (1,1) models are also employed to make a comparison with the proposed model. Our empirical results show that the proposed approach generates superior forecasting performance.
Does Benefit Relationship Affect Analysts’ Earnings Forecast?—Evidence from Chinese Stock Market  [PDF]
Yinlin Ou
Open Journal of Accounting (OJAcct) , 2017, DOI: 10.4236/ojacct.2017.62003
Abstract: Under the information asymmetrical theory, the Chinese securities analysts are affected by many benefit factors, so the purpose of the study is trying to figure out what benefit elements and how to affect analysts’ earnings forecasts. Using data from 2012 to 2015, the author creatively quantifies interest factors, and does the empirical analysis. Regression results indicate that the closer relationship between securities analysts and the listed companies management or institutional investors, the greater accuracy of their earnings forecasts. Besides, analysts’ reputation exists a negative correlation between earnings forecasts accuracy. Furthermore, securities’ underwriting relationships have no significant influence on the accuracy of analysts’ earnings forecasts, but the underwriting analysts are more likely to overestimate earnings per share of the target companies.
Dust Effect on the Performance of Wind Turbine Airfoils  [PDF]
Nianxin Ren, Jinping Ou
Journal of Electromagnetic Analysis and Applications (JEMAA) , 2009, DOI: 10.4236/jemaa.2009.12016
Abstract: The full two-dimensional Navier-Stokes algorithm and the SST k-? turbulence model were used to investigate incom-pressible viscous flow past the wind turbine two-dimensional airfoil under clean and roughness surface conditions. The NACA 63-430 airfoil is chosen to be the subject, which is widely used in wind turbine airfoil and generally located at mid-span of the blade with thickness to chord length ratio of about 0.3. The numerical simulation of the airfoil under clean surface condition has been done. As a result, the numerical results had a good consistency with the experimental data. The wind turbine blade surface dust accumulation according to the operational periods in natural environment has been taken into consideration. Then, the lift coefficients and the drag coefficients of NACA 63-430 airfoil have been computed under different roughness heights, different roughness areas and different roughness locations. The role that roughness plays in promoting premature transition to turbulence and flow separation has been verified by the numeri-cal results. The trends of the lift coefficients and the drag coefficients with the roughness height and roughness area increasing have been obtained. What’s more, the critical values of roughness height, roughness area, and roughness location have been proposed. Furthermore, the performance of the airfoil under different operational periods has been simulated, and an advice for the period of cleaning wind turbine blades is proposed. As a result, the numerical simula-tion method has been verified to be economically available for investigation of the dust effect on wind turbine airfoils.
Anti-Money Laundering Regulation of China’s Mobile Payment and Settlement Industry  [PDF]
Yanwei Wang, Yangchao Ou
Open Journal of Social Sciences (JSS) , 2015, DOI: 10.4236/jss.2015.311033
Abstract: In recent years, with the continuous advance of payment equipment and technologies like China’s internet Finance, Big Data and Mobile Network, the anonymity, rapidity and cross-border transaction of mobile payment business have also brought many money laundering risks. Therefore, it is necessary to strengthen cooperation with the supervision organization of international payment and anti-money laundering business, and meanwhile to constantly improve the supervision mechanism of China’s payment and anti-money laundering business.
The Effect of Graphene/Ag Nanoparticles Addition on the Performances of Organic Solar Cells  [PDF]
Cheng Fang Ou
Journal of Materials Science and Chemical Engineering (MSCE) , 2015, DOI: 10.4236/msce.2015.312006
Abstract:

Graphene/Ag nanoparticles (GAg) were fabricated via a facile method, employing graphite oxide as a precursor of graphene sheet (GNS), AgNO3 as a precursor of Ag nanoparticles, and sodium citrate as a reducing and stabilizing agent. We synthesized three kinds of GAg as GAg-1, GAg-2 and GAg-3. We introduced high electron mobility GAg into the active layer of polymer solar cell. The cell structure was ITO/PEDOT:PSS/P3HT:PCBM:GAg/Ca/Al. The weight ratio of P3HT:PCBM:GAg of active layer is 1:1:0.01. We study the effect of GAg addition on the photovoltaic performance. We use the UV-Vis, SPM, FE-SEM and solar simulator to measure the absorbance, roughness, surface morphology, and power conversion efficiency (PCE), respectively. From these results, we found that the fill factor (FF) and PCE of the cells with GNS or GAg are always higher than those of cell without GNS or GAg. The cell with GAg-2 had the highest short circuit current density (Jsc) of 8.56 mA/cm2, an increase of 20.2%, the highest fill factor (FF) of 0.56, an increase of 14.3% and the highest PCE of 2.78%. This is a 24.7% increase in efficiency compared to the cell without GNS or GAg. These improvements were due to the high carrier mobility of grapheme.

Local Solutions to a Class of Parabolic System Related to the P-Laplacian  [PDF]
Qitong Ou, Huashui Zhan
Advances in Pure Mathematics (APM) , 2016, DOI: 10.4236/apm.2016.612065
Abstract: In this paper, the existence and uniqueness of local solutions to the initial and boundary value problem of a class of parabolic system related to the p-Laplacian are studied. The regularization method is used to construct a sequence of approximation solutions, with the help of monotone iteration technique, then we get the existence of solution of a regularized system. By the use of a standard limiting process, the existence of the local solutions of the system is obtained. Finally, the uniqueness of the solution is also proven.
Governance, Corruption, and the Informal Economy  [PDF]
Idrissa M. Ouédraogo
Modern Economy (ME) , 2017, DOI: 10.4236/me.2017.82018
Abstract: This paper uses data from 23 Sub-Saharan countries to analyze the relationship between governance, corruption, and the size of the informal economy. The results show that corruption, the quality of governance, the quality of institutional settings, and the unemployment rates are major determinants of the size of the informal economy. More specifically, it is found that a high level of corruption and poor institutional settings favor an increase of the informal economy. The unemployment rate is negatively related to the size of the informal economy, and greater fiscal freedom and business freedom are associated with a larger informal economy, while monetary freedom reduces the size of the informal sector.
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