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Dissertations / Theses on the topic 'Stock Forecasting'

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Published: 4 June 2021

Last updated: 26 July 2025

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1

Kwan, Wai-ching Josephine. "Trend models for price movements in financial markets /." [Hong Kong] : University of Hong Kong, 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13841397.

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2

Rahou, Amar A. M. "A generalised framework for modelling & forecasting share prices : a field study on modelling and forecasting the share prices from the banking sector." Thesis, University of South Wales, 2009. https://pure.southwales.ac.uk/en/studentthesis/a-generalised-framework-for-modelling--forecasting-share-prices(10fcca19-ff9a-4497-a0be-55f3e980cbed).html.

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Modelling and forecasting the stock market remains a challenge because of the high volatilities in individual stock prices and the market itself. Hence, this topic has received much attention in the literature since forecast errors represent the systematic risk faced by investors. Therefore, the ability to reliably forecast the future values of the shares would provide essential help in reducing that risk to those investors. The main aim of this research is to develop and calibrate a framework that can be used to model the daily share prices of the companies from the banking sector and hence p

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3

Gower, Craig Paul. "Modelling and forecasting stock and stock market volatility." Thesis, Swansea University, 2001. https://cronfa.swan.ac.uk/Record/cronfa42339.

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The examination of stock price volatility has come under increased scrutiny due to the large swings in stock price movements that have occurred with greater frequency than the historical average. Additionally, the substantial increases in the volume of options trading has increased the importance of accurate volatility forecasts due to the volatility forecast being the most important parameter affecting the pricing of options. Consequently, the aim of the thesis is to analyse the volatility of forty-five FTSE 100 stocks, the FTSE 100 index together with other major and emerging market stock in

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4

Shan, Yaowen School of Banking &amp finance UNSW. "Analysts' forecasts and future stock return volatility: a firm-level analysis for NYSE Firms." Awarded by:University of New South Wales. School of Banking & finance, 2006. http://handle.unsw.edu.au/1959.4/26963.

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This study demonstrates that financial analysts significantly affect short-term stock prices, by examining how non-accounting information particularly contained in analysts' forecasts contributes to the fluctuation of future stock returns. If current non-accounting information of future earnings is more unfavourable or more volatile, we could observe a larger shift in the current stock return. The empirical evidence strongly supports these theoretical predictions that stem from the combination of the accounting version of Campbell-Shiller model (Campbell and Shiller (1988) and Vuolteenaho (200

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5

Chen, Gary. "Behavioural heterogeneity in ASX 200 a dissertation submitted to Auckland University of Technology in fulfilment of the requirements for the degree of Master of Business (MBus), 2009 /." Click here to access this resource online, 2009. http://hdl.handle.net/10292/758.

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6

Rangel, Jose Gonzalo. "Stock market volatility and price discovery three essays on the effect of macroeconomic information /." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3220417.

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Thesis (Ph. D.)--University of California, San Diego, 2006.<br>Title from first page of PDF file (viewed September 7, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 125-130).

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7

Millevik, Daniel, and Michael Wang. "Stock Forecasting Using Artificial Neural Networks." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166455.

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This paper studies the potential of artificial neural networks (ANNs) in stock forecasting. It also investigates how the number of neurons in the network, as well as the distribution of the training data into training, validation and testing sets, affect the accuracy of the network. By using MATLAB and its Neural Network Toolbox tests were carried out with a two-layer feedforward neural network (FFNN). These are carried out by collecting five years of historical data from the Dow Jones Industrial Average (DJIA) stock index, which is then used for training the network. Finally, retraining the n

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8

NEVES, GUILHERME DE SOUSA. "STOCK FORECASTING FOR ELETRONICS SPARE PARTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11330@1.

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Existe consenso entre os pesquisadores de que o modelo de séries temporais não é adequado para previsão de peças de reposição. Entretanto, a maioria das ferramentas de previsão existentes no mercado emprega o modelo de séries temporais. Este trabalho apresenta a distribuição de Poisson como alternativa para a previsão de estoque de peças eletrônicas de reposição. A partir de noções básicas de gestão de estoques utilizando séries temporais e dos conceitos de confiabilidade, disponibilidade e do Processo de Poisson é proposto um modelo alternativo. Com o uso de exemplos reais são apresen

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9

Skagerström, William, and Daniel Skantz. "Stock forecasting using ensemble neural networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229798.

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This paper explores the viability of creating an artificial neural network for stock forecasting using an ensemble method, where each network is differentiated with a different set of input parameters. The inputs were chosen based on previous research and by using a stepwise addition parameter search method. The problem was approached as both a regression and a classification problem, where we evaluated the networks performance for the purpose of stock forecasting using relevant measurements. For the regression part, the result was negative: the neural network was not able to beat a naive pred

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10

Zhang, Yuzhao. "Essays on return predictability and volatility estimation." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1666139151&sid=3&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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11

Zhang, Shaorong. "Essays on security issuance /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144472.

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12

Mathew, Prem George. "Long-horizon event study methodology and seasoned equity offering performance in the Pacific Rim financial markets /." free to MU campus, to others for purchase, 1999. http://wwwlib.umi.com/cr/mo/fullcit?p9953880.

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13

Yiu, Fu-keung. "Time series analysis of financial index /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18003047.

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14

Rank, Christian. "Forecasting stock price movements using neural networks." Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/4392.

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Includes bibliographical references (p. 99-101).<br>The prediction of security prices has shown to be one of the most important but most difficult tasks in financial operations. Linear approaches failed to model the non-linear behaviour of markets and non-linear approaches turned out to posses too many constraints. Neural networks seem to be a suitable method to overcome these problems since they provide algorithms which process large sets of data from a non-linear context and yield thorough results. The first problem addressed by this research paper is the applicability of neural networks wit

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15

Lin, Gang. "Nesting regime-switching GARCH models and stock market volatility, returns and the business cycle /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9906497.

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16

Chavarnakul, Thira. "The development of hybrid intelligent systems for technical analysis based equivolume charting." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.umr.edu/thesis/pdf/Thira_Chavarnakul_Dissertation_2007_09007dcc803425db.pdf.

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Thesis (Ph. D.)--University of Missouri--Rolla, 2007.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed October 25, 2007) Includes bibliographical references.

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17

Fodor, Bryan D. "The effect of macroeconomic variables on the pricing of common stock under trending market conditions." Thesis, Department of Business Administration, University of New Brunswick, 2003. http://hdl.handle.net/1882/49.

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Thesis (MBA) -- University of New Brunswick, Faculty of Administration, 2003.<br>Typescript. Bibliography: leaves 83-84. Also available online through University of New Brunswick, UNB Electronic Theses & Dissertations.

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18

Wong, Chun-mei May. "The statistical tests on mean reversion properties in financial markets /." [Hong Kong : University of Hong Kong], 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13705568.

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19

Andersson, Magnus, and Johan Palm. "Forecasting the Stock Market : A Neural Network Approch." Thesis, Mälardalen University, School of Education, Culture and Communication, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5564.

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<p>Forecasting the stock market is a complex task, partly because of the random walk behavior of the stock price series. The task is further complicated by the noise, outliers and missing values that are common in financial time series. Despite of this, the subject receives a fair amount of attention, which probably can be attributed to the potential rewards that follows from being able to forecast the stock market.</p><p>Since artificial neural networks are capable of exploiting non-linear relations in the data, they are suitable to use when forecasting the stock market. In addition to this,

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20

SILVA, PAULO DE TARSO GOMIDE CASTRO. "A SYSTEM FOR STOCK MARKET FORECASTING AND SIMULATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28979@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>Nos últimos anos, vem crescendo o interesse acerca da predição do comportamento do mercado de capitais, tanto por parte dos investidores quanto dos pesquisadores. Apesar do grande número de publicações tratando esse problema, predizer com eficiência futuras tendências e desenvolver estratégias de negociação capazes de traduzir boas predições em lucros são ainda grandes desafios. A dificuldade em realizar tais tarefas se deve tanto à não linea

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21

Cunha, Ronan. "Automatic model selection for forecasting Brazilian stock returns." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13635.

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Submitted by Ronan Cunha (cunha.ronan@gmail.com) on 2015-04-14T13:26:14Z No. of bitstreams: 1 Dissertação - Ronan Cunha.pdf: 661334 bytes, checksum: dbb8ee6517fa128ea12981554ad549ad (MD5)<br>Rejected by Vera Lúcia Mourão (vera.mourao@fgv.br), reason: Prezado Ronan, preciso que você faça algumas correções em seu arquivo: Na list of tables, list of figures, contentes e no número de referência (no texto) aparece uma borda vermelha, é necessário retirar. existe também uma página em branco, logo após essas lista, também tem que excluir. att. Vera on 2015-04-14T18:00:45Z (GMT)<br>Subm

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22

Tsakou, Katina. "Essays on financial volatility forecasting." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/25403.

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The accurate estimation and forecasting of volatility is of utmost importance for anyone who participates in the financial market as it affects the whole financial system and, consequently, the whole economy. It has been a popular subject of research with no general conclusion as to which model provides the most accurate forecasts. This thesis enters the ongoing debate by assessing and comparing the forecasting performance of popular volatility models. Moreover, the role of key parameters of volatility is evaluated in improving the forecast accuracy of the models. For these purposes a number o

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23

Cheng, Xin. "Three essays on volatility forecasting." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1183.

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24

Woodgate, Artemiza. "The impact of earnings management on price momentum /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/8755.

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25

Kot, Hung Wan. "Two essays in empirical finance /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?FINA%202004%20KOT.

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26

Al, Nasseri Alya Ali Mansoor. "The predictive power of stock micro-blogging sentiment in forecasting stock market behaviour." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13575.

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Online stock forums have become a vital investing platform on which to publish relevant and valuable user-generated content (UGC) data such as investment recommendations and other stock-related information that allow investors to view the opinions of a large number of users and share-trading ideas. This thesis applies methods from computational linguistics and text-mining techniques to analyse and extract, on a daily basis, sentiments from stock-related micro-blogging messages called “StockTwits”. The primary aim of this research is to provide an understanding of the predictive ability of stoc

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27

Wu, Ruojun. "Essays on the predictability and volatility of returns in the stock market." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3316421.

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Thesis (Ph. D.)--University of California, San Diego, 2008.<br>Title from first page of PDF file (viewed Sept. 4, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 127-132).

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28

Scott, Laurie Croslin Zeng Yong. "Bayesian inference via filtering of micro-movement multivariate stock price models with discrete noises." Diss., UMK access, 2006.

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Thesis (Ph. D.)--Dept. of Mathematics and Statistics and Dept. of Economics. University of Missouri--Kansas City, 2006.<br>"A dissertation in mathematics and economics." Advisor: Yong Zeng. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed Jan. 29, 2007. Includes bibliographical references (leaves 121-124). Online version of the print edition.

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29

Ma, Chin-wan Raymond. "A study on the beta coefficients of securities in Hong Kong." Click to view the E-thesis via HKUTO, 1989. http://sunzi.lib.hku.hk/hkuto/record/B31976050.

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30

Law, Ka-chung, and 羅家聰. "A comparison of volatility predictions in the HK stock market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B30163535.

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31

Lu, Qunfang Flora. "Bayesian forecasting of stock prices via the Ohlson model." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050605-155155/.

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32

Lakshminarayanan, Sriram. "An Integrated Stock Market Forecasting Model Using Neural Networks." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1127333497.

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33

Elsegai, Heba. "Network inference and data-based modelling with applications to stock market time series." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=228017.

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The inference of causal relationships between stock markets constitutes a major research topic in the field of financial time series analysis. A successful reconstruction of the underlying causality structure represents an important step towards the overall aim of improving stock market price forecasting. In this thesis, I utilise the concept of Granger-causality for the identification of causal relationships. One major challenge is the possible presence of latent variables that affect the measured components. An instantaneous interaction can arise in the inferred network of stock market relat

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34

Hassan, Mahamood Mahomed. "Testing the pricing and informational efficiency of the S&P 500 stock index futures market." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184858.

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Three empirical studies are conducted examining the efficiency of S&P 500 futures prices and the pricing of these futures contracts. In the first study, the ability of futures prices to predict the realized spot S&P 500 index prices on the expiration date is examined for near term contracts. The futures prices are found to be unbiased predictors of the realized spot index prices for the nineteen quarterly contracts from 1982 to 1986. Previous studies report significant deviations in S&P SOO futures prices from theoretically determined Cost of Carry Model (CCM) prices. In the second study, it i

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35

CHIU, POH-LIM, and 邱柏霖. "Forecasting Taiwan stock prices." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/63500112352295597390.

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碩士<br>淡江大學<br>財務金融學系<br>86<br>Many economists believe that the overall performance of a country''s economy is strongly related to the performance of its stock market. Some empirical studies, however, show that this relationship does not necessarily hold. In the sense that stock market performance is highly unpredictable, the movement of stock prices has sometimes been expressed as a random walk process. Shiller (1989) and DeBond (1991) have also shown that stock price are both unpredictable

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36

"Tests on relative strength index trading rules in China stock market." 2002. http://library.cuhk.edu.hk/record=b5890950.

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by Leung Kwok Chu, Wong Cheuk Fung.<br>Thesis (M.B.A.)--Chinese University of Hong Kong, 2002.<br>Includes bibliographical references (leaves 54-55).<br>ABSTRACT --- p.ii<br>TABLE OF CONTENTS --- p.iv<br>ACKNOWLEDGMENTS --- p.vi<br>Chapter<br>Chapter I. --- INTRODUCTION --- p.1<br>Technical Analysis --- p.2<br>The Characteristics and Efficiency of China's Equity Markets --- p.3<br>Market Participants --- p.4<br>Transaction Costs and Tradability of Shares --- p.5<br>Availability of Information --- p.7<br>Implication on Weak Form Market Efficiency --- p.8<br>Relative Strength Index ---

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37

Ohn, Jonathan Kong. "Dynamics of the return generating process and mean reversion of the US stock prices /." Diss., 1997. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:9814980.

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Kwon, Ki-Yeol. "Stock price, volatility and volume : the profitability of technical trading rules using bootstrap methodology /." Diss., 1999. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:9935167.

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39

Yang, Rong-Jie, and 楊榮桀. "Forecasting Taiwan Weighted Stock Index With Stock Chart Heuristic." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/56447509846678404975.

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碩士<br>雲林科技大學<br>財務金融系碩士班<br>96<br>This study utilizes a bull flag as the technical analysis tool to evaluate its trading performance for the Taiwan Weighted Index(TWI).We advance a procedure of constructing new bull flag template ,and compare with Leigh et al(2001)，Leigh et al.(2002 )，Leigh et al(2002 )，Leigh et al.(2002 )，Leigh et al.(2002 )，Leigh et al(2004) and Leigh et al.(2005)。This study adopts Leigh et al.(2002 ) template matching method: a 40 trading days moving window is fitted to calculate the data fitness.We use the average daily return of 10 to 80 trading days after the bull flag s

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"Modeling and forecasting Hong Kong stock market return." 1999. http://library.cuhk.edu.hk/record=b5889916.

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by Wong Hiu Ming.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.<br>Includes bibliographical references (leaves 74-79).<br>Abstracts in English and Chinese.<br>ACKNOWLEDGMENTS --- p.iii<br>LIST OF TABLES --- p.iv<br>LIST OF ILLUSTRATIONS --- p.v<br>CHAPTER<br>Chapter ONE --- INTRODUCTION --- p.1<br>Chapter TWO --- THE LITERATURE REVIEW --- p.5<br>ARCH/GARCH Models<br>Nonparametric Method<br>Chapter THREE --- METHODOLOGY --- p.14<br>ARCH Modeling<br>Semiparametric GARCH Modeling<br>Causality Test<br>Local Polynomial Model<br>Chapter FOUR --- DATA AND EMPIRICAL RESULTS --- p.

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Dern, Dean, and 鄧之昌. "Taiwan stock index research and forecasting." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/96268592853669288991.

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碩士<br>國立政治大學<br>統計學系<br>87<br>The article utilizes the transfer function model in time series to make prediction on closing volume with closing value of the stock market, the American Dow Jones average index with the index of Taiwan stock market index, NASDAQ index with Taiwan electronic stock. In additional to discovering the appropriate prediction model, we can simultaneously see the influence of America with great economic power on Taiwan and how the concept that the volume determines the value is verified. During the process of this research, the outcome of the analysis i

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CHOU, TZUNG CHING, and 周宗慶. "Using Neural Network for Stock Forecasting." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/03567379456275607876.

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碩士<br>大葉大學<br>工業工程與科技管理學系碩士在職專班<br>94<br>Numerous methods are employed in stock market forecasting. These methods are classified as either technical analysis or fundamental analysis. Fundamental analysis may change because of different times and market environments, and is unable to conclude a constant explanation and research. Therefore, this study is conducted by technical analysis. In respect of short-/mid-term trading, KD is a popularly accepted indicator and is suitable for investors’ short-term trading. In recent years, as a result of enhancement of computer capability and the accelerati

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Chung-Liang, Cheng, and 鄭忠樑. "Forecasting the Stock Returns Using CART." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/12927542205784646219.

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碩士<br>元智大學<br>資訊管理學系<br>90<br>The stock price should reasonably reflect the status of the company’s management and profitability. This paper tried to use CART to build a model in order to forecast the stock price rising or falling from the company’s financial ratios. The CART software developed by Salford-Systems is the main analysis tool in this study. 　　This study uses the electronic stocks in Taiwan from the first season of 1995 through the second season of 2001 as samples, and all data informations are from Taiwan Economic Journal (TEJ). The independent variables are the comp

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Seca, José Diogo Teixeira de Sousa. "Forecasting stock trends through Machine Learning." Master's thesis, 2019. https://hdl.handle.net/10216/121271.

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Masinga, Zamani Calvin. "Modeling and forecasting stock return volatility in the JSE Securities Exchange." Thesis, 2016. http://hdl.handle.net/10539/21053.

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Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Wits Business School, 2016<br>Modeling and forecasting volatility is one of the crucial functions in various fields of financial engineering, especially in the quantitative risk management departments of banks and insurance companies. Forecasting volatility is a task of any analyst in the space of portfolio management, risk management and option pricing. In this study we examined different GARCH models in Johannesburg Stock Exchange (JSE) using univariate GARCH models (GARCH (1, 1),

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46

Ward, Benjamin D. "Forecasting short term trends in prices of U.S. stock market." 2006. http://etd1.library.duq.edu/theses/available/etd-11262006-224050/.

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Dias, Tiago Bento da Rocha Baptista. "Volatility forecasting : the role of financial news in forecasting stock market volatility." Master's thesis, 2014. http://hdl.handle.net/10400.14/22084.

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Cet article a pour objectif d’analyser l’influence des nouvelles financières sur la volatilité implicite du marché boursier. Nous analysons toutes les valeurs du DJII et le S&P 500 Index ainsi que le nombre de nouvelles publiées dans le FT.com comme une mesure du flux d’informations. Pour faire ces estimations, nous utilisons les régressions OLS et les régressions Neural Networks. Nos résultats montrent que la moyenne des nouvelles du mois précédent est pertinente pour prévoir la volatilité du prochain mois, conduisant à meilleures performances hors de l’échantillon analysé.

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Tzeng, Jing-Ru, and 曾靖儒. "Applying Fuzzy time series for Stock Forecasting." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/3589p2.

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碩士<br>崑山科技大學<br>企業管理研究所<br>93<br>It is necessary to split historical data into equal interval while use traditional fuzzy time series, because the splitting is too subjective, and neglect the attribute of data distributed, it makes result appeared to uncertainty, this research hope propose a technology that have more effective and accurate, and could use it to be the fuzzy tool among numerous fuzzy time series methods. According to the characteristics of data distributed, New method that variation and non- regular of interval to be proposed of this research, and with number of people entrance

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Hsuan, Huang Yu, and 黃語軒. "Forecasting Taiwan weighted stock Index with VECM." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/47926946503142244152.

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碩士<br>國立彰化師範大學<br>財務金融技術學系<br>102<br>Taking advantage of the unit root test, Johansen cointegration test, VECM, Granger causality test and the prediction of TAIEX, the study investigates the connections between TAIEX and macroeconomic variables that include TAIEX, composite index of coincident indicators, composite index of leading economic indicators, value of exports, Consumer Price Index, rates…etc. from 2007 to 2012 to carry out the empirical analysis. The findings are repectively shown as follows: 1. The cointegration exists in TAIEX and macroeconomic variables. 2. From VECM the postive s

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Tseng, Hong-Chih, and 曾鴻志. "A Forecasting Model of Taiwan Stock Market." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/25112469251307559054.

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