Bibliografie tematiche / Stock exchanges – Thailand

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Letteratura scientifica selezionata sul tema "Stock exchanges – Thailand"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 1 febbraio 2022

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Articoli di riviste sul tema "Stock exchanges – Thailand"

Adisetiawan, R., e Ahmadi Ahmadi. "CONTAGION EFFECT ANTAR NEGARA ASEAN-5". J-MAS (Jurnal Manajemen dan Sains) 3, n. 2 (17 ottobre 2018): 203. http://dx.doi.org/10.33087/jmas.v3i2.58.

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This study was conducted to determine whether there is a contagion effect on the stock exchanges among ASEAN-5 countries (Indonesia, Singapore, Malaysia, Thailand and Philippines) during 2001.1 - 2018.5 period using the monthly return data of the five ASEAN-5 stock exchanges. This study uses granger causality test to see the direction of mutual influence that indicates the existence of contagion effect. The results revealed that the Indonesian stock exchange has a mutually influential relationship with the Thai stock exchange.

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Chokethaworn, Kanchana, Chukiat Chaiboonsri e Satawat Wannapan. "Alternative prediction methods in the stock exchanges of Thailand". Journal of Physics: Conference Series 1324 (ottobre 2019): 012086. http://dx.doi.org/10.1088/1742-6596/1324/1/012086.

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Jarungkitkul, Wanida, e Sorasart Sukcharoensin. "Benchmarking the competitiveness of the ASEAN 5 equity markets". Benchmarking: An International Journal 23, n. 5 (4 luglio 2016): 1312–40. http://dx.doi.org/10.1108/bij-05-2014-0047.

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Purpose – The purpose of this paper is to study the competitiveness of the stock markets in ASEAN 5, which are the Stock Exchange of Thailand (SET), the Singapore Exchange (SGX), Bursa Malaysia (BM), the Indonesia Stock Exchange (IDX), and the Philippine Stock Exchange (PSE). Design/methodology/approach – This research applies Porter’s (1990) diamond model to analyze the competitiveness and the data were collected from World Economic Forum, International Institute for Management Development, the World Federation of Exchanges database, and DataStream. Findings – The results show that SGX is the most competitive exchange in ASEAN 5 region. It dominates other exchanges in every dimension. It gains its reputation for being the region’s most prominent exchange, followed by BM, SET, IDX, and the PSE, respectively. Practical implications – The results of this investigation provide rank for competitiveness of stock exchanges among ASEAN 5 and identify the way to improve its competitive position. Social implications – It is useful for public and private sectors involved in the development and policy making to promote funding and investment efficiency of the exchanges. It will be benefit to establish the well-planned development strategy and policy to build up the competitive advantage of the nations. Originality/value – Identifying and benchmarking the competitiveness of the stock markets in ASEAN economies. By using Diamond Model, the authors propose indicators to assess the competitiveness of the stock markets in ASEAN 5 countries. Assessing the competitiveness of the ASEAN stock markets in this paper will lead us to better understand about each country’s strengths and weaknesses and to promote a mutual collaboration among the region toward ASEAN Economic Community.

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Panjaitan, Yunia, e Siti Saadah. "Volatility Spillover Analysis Post Implementation of AEC 2015 Agreement: Empirical Study on ASEAN-5 Stock Market". International Journal of Financial Research 9, n. 2 (5 febbraio 2018): 105. http://dx.doi.org/10.5430/ijfr.v9n2p105.

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Efforts to improve financial integration that continue to be implemented after the implementation of the Asean Economic Community 2015 agreement, can encourage increased integration of capital markets in countries within the region. This study was conducted to investigate the spillover of volatility between stock markets that accompanied the ongoing efforts of financial integration carried out by ASEAN member countries. Investigation of volatility spillover is done by applying Exponential GARCH method on time series daily data of stock return of ASEAN-5 countries period September 2016 - December 20, 2017. If previous studies found significant spillover of volatility from Singapore, Malaysia, Thailand and Philippines, the results of this study show that only Singapore's stock exchanges consistently have a significant impact on the Indonesian stock market. The turmoil in the Singapore stock market will be consistently transmitted to the Indonesian stock market. However, efforts to improve the financial integration carried out by ASEAN member countries have not consistently caused the turmoil in Malaysia, Thailand and the Philippines stock exchange to be transmitted to the Indonesian stock market.

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Jarrett, Jeffrey E. "Day-of-the-Week Variation and Predicting Stock Returns: Taiwan and Thailand Stock Exchanges". Journal of Asia-Pacific Business 10, n. 3 (19 agosto 2009): 257–65. http://dx.doi.org/10.1080/10599230903094786.

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Kurniawan, Doni, e Mayar Afriyenti. "Pengaruh Harga Saham, Volume Perdagangan, dan Varian Return Terhadap Bid-Ask Spread (Studi Empiris pada Perusahaan yang Melakukan Stock Split yang Terdaftar di Bursa Efek di Asia Tenggara Tahun 2018)". Wahana Riset Akuntansi 7, n. 1 (25 giugno 2019): 1397. http://dx.doi.org/10.24036/wra.v7i1.104564.

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This study aims to determine the effect of stock prices, trading volume, and variance of return on the bid-ask spread in companies that do stock splits listed on stock exchanges in Southeast Asia in 2018. In this study the sampling technique used was nonprobability purposive sampling so that produced a total of 248 companies with 26 companies on the Indonesia Stock Exchange, 10 companies on the Philippines Stock Exchange, 56 companies on the Malaysia Stock Exchange, 18 companies on the Singapore Stock Exchange, 48 companies on the Thailand Stock Exchange and 90 companies on the Vietnam Stock Exchange. This study uses multiple regression methods using Eviews 10 to process data. The results of the study indicate that on the Indonesia Stock Exchange, stock prices have a negative and significant effect on the bid-ask spread, trading volume has no significant negative effect on the bid-ask spread, variance returns have a positive and insignificant effect on the bid-ask spread. On the Philippine Stock Exchange, stock prices have no significant negative effect on the bid-ask spread, trading volume has a positive and significant effect on the bid-ask spread, variance returns have a positive and insignificant effect on the bid-ask spread. On the Malaysia Stock Exchange, stock prices have a negative and significant effect on the bid-ask spread, trading volume and variance returns have a positive and significant effect on the bid-ask spread. On the Singapore Stock Exchange, stock prices and trading volume have a negative and significant effect on the bid-ask spread, variance returns have a positive and insignificant effect on the bid-ask spread. On the Thailand Stock Exchange, stock prices have a negative and significant effect on the bid-ask spread, trading volume and variance returns have a positive and significant effect on the bid-ask spread. On the Vietnam Stock Exchange, stock prices have no significant negative effect on the bid-ask spread, trading volume has no significant positive effect on the bid-ask spread, variance returns have a positive and significant effect on the bid-ask spread.Keywords: Stock Price, Trading Volume, Variant Return, Bid-Ask Spread, Stock Split

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Çinko, Murat, Emin Avci, Aslı Aybars e Mehtap Öner. "Analyzing the Existence of the Day of the Week Effect in Selected Emerging Country Stock Exchanges". International Journal of Corporate Finance and Accounting 1, n. 2 (luglio 2014): 33–43. http://dx.doi.org/10.4018/ijcfa.2014070103.

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Calendar anomalies, specifically Day of the Week (DoW) effect, have attracted considerable attention by academicians and practitioners during the last decades. This study investigates the existence of DoW effect in 13 emerging stock markets by utilizing an observation period of 12 years. Whereas the findings of the study reveal the presence of negative Monday effects for Indonesia, Malaysia, and Thailand; positive Monday returns are found in South Africa contrary to expectations. Furthermore; positive Friday returns are observed in 9 of the markets belonging to Argentina, Brazil, Bulgaria, Indonesia, Malaysia, Romania, Thailand, Tunisia, and Turkey. Additional results document the presence of positive Wednesday and Thursday returns for most of the markets analyzed.

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Bakhturazova, T. V., M. K. Mayorov, N. V. Mayorova e D. A. Edelev. "THREATS TO INDUSTRIAL POLICY, TRADE AND KNOWLEDGE SHARING IN A GLOBAL EMERGENCY". Vestnik Universiteta, n. 4 (29 giugno 2020): 42–46. http://dx.doi.org/10.26425/1816-4277-2020-4-42-46.

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The coronavirus epidemic 2019-nCoV in China has already led to a slowdown in the country’s economic growth and the fall of the yuan exchange rate on the stock exchanges. The Russian government has banned visa-free tourist trips between Russia and China and the issuance of work visas to Russia for Chinese citizens; Australia, New Zealand, Japan, Pakistan, and Italy have imposed similar bans. Great Britain, South Korea, Singapore and New Zealand have imposed quarantine for arrivals from China. Military aircrafts of Russia, India and Thailand take their citizens out of China. The US authorities have declared public health emergency and ban on the entry of all foreign citizens who have visited China over the past two weeks. This article gives forecast, how these measures of the governments will affect on global academic mobility and economic growth.

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Adiputra, I. Gede, e Azhar Affandi. "The Effect of Micro and Macroeconomic on Investment Opportunity". AMAR (Andalas Management Review) 2, n. 2 (23 novembre 2018): 59–81. http://dx.doi.org/10.25077/amar.2.2.59-81.2018.

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The purpose of this study is to obtain results: the influence of micro and macroeconomic factors of the company on investment opportunities. This research is conducted in five ASEAN countries, such as; Indonesia, Malaysia, Singapore, Thailand, and the Philippines (ASEAN-5). The microeconomic factors are measured by firm size, financial risk, profitability, and debt policy. The macroeconomic factors are measured by interest rates, exchange rates, inflation, and economic growth. The analysis unit of this study is 175 large capacity manufacturing industries listed on ASEAN-5 stock exchanges for the 2012-2017 period. The data analysis technique used is panel data regression analysis. The result shows that the Debt Equity Ratio has a negative and significant effect on investment opportunities in Microeconomic influence for the ASEAN-5 Countries. Risk does not have a significant effect on investment opportunities. Profitability is insignificant for the ASEAN-5 Countries and is significant for the State of Singapore, Thailand. Firm Size is significant for Indonesia, Malaysia, Singapore, and the Philippines. GDP growth has a significant effect on investment opportunities for the ASEAN-5 countries. The interest rate has harmed the opportunities of investment in Indonesia, Malaysia, and Singapore. Inflation has a negative and significant effect in Indonesia, Malaysia, Thailand, and the Philippines. Exchange rates are significant for Indonesia, Malaysia, and Singapore. Investment opportunities have a positive effect on the value of the company in ASEAN-5 Countries. The benefits of this study for creditors are as a guideline for disbursing credit, and for investors it is as a guideline for placing capital investments in companies that have favorable debt and equity considerations in five (5) ASEAN Countries.

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Susono, Juhasdi. "PENGARUH NET INTEREST MARGIN (NIM), BEBAN OPERASIONAL PENDAPATAN OPERASIONAL (BOPO), CAPITAL ADEQUACY RATIO (CAR), DAN NON PERFORMING LOAN (NPL) TERHADAP PROFITABILITAS PERUSAHAAN PERBANKAN BURSA EFEK DI NEGARA INDONESIA, MALAYSIA, DAN THAILAND". PARAMETER: Jurnal Pendidikan Universitas Negeri Jakarta 29, n. 1 (4 maggio 2017): 9–19. http://dx.doi.org/10.21009/parameter.291.02.

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This study aims to determine the effect of Net Interest Margin (NIM), Operational Income Operating Cost (BOPO), Capital Adequacy Ratio (CAR), and Non-Performing Loan (NPL) on banking stock exchange company profitability in Indonesia, Malaysia and Thailand. This research was a quantitative, aimed to work out a systematically explain on the facts and properties of object in the research then merger was done between related variables in it with the presentation of secondary data from the financial statements of banking companies in Indonesia, Malaysia and Thailand. The population used in this study was banking company listed in Indonesia, Malaysia and Thailand stock exchanges in the period of 2010 to 2016. The sample used in this study as many as 24 banking companies in Indonesia, Malaysia and Thailand using purpose sampling method to obtain a representative sample that matches the criteria that have been made. In this study, data analysis method used was panel data (pooled data) which is a combination of time-series data and data between individuals or space (cross section) in banking companies in Indonesia, Malaysia and Thailand. Research Results for banking companies in Indonesia gained value of R square model of 0.222 percent, means that the variation of the profit that can be explained by the independent variables in the analysis of NIM, BOPO, CAR and NPL of 22.20 percent of the remaining 78.80 percent explained by other factors not studied here. Next, In Malaysia R value of this model square of 0.335 percent means that the variation of the profit that can be explained by the independent variables in the analysis of NIM, BOPO, CAR and NPL of 33.50 percent on the remaining 66.50 percent explained by other factors not included in the study this. While in Thailand, R square value of this model was 0.266 percent means that the variation of the profit that can be explained by the independent variables in the analysis of NIM, BOPO, CAR and NPL of 26.60 percent of 73.40 percent was explained by other factors not discussed in this study. Abstrak Penelitian ini bertujuan untuk untuk mengetahui pengaruh Net Interest Margin (NIM), Biaya Operasional Pendapatan Operasional (BOPO), Capital Adequacy Ratio (CAR), dan Non Performing Loan (NPL) terhadap pofitabilitas perbankan di negara indonesia, malaysia, dan thailand. Penelitian ini merupakan penelitian kuantitatif yang tujuanya untuk mengerjakan suatu yang di jelaskan secara sistematis tentang fakta-fakta serta sifat dalam suatu objek dalam penelitian kemudian melakukan penggabungan antar variabel yang terkait di dalamnya dengan penyajian data sekunder dari laporan keuangan dari perusahaan perbankan di negara indonesia, malaysia dan thailand. Populasi yang di gunakan pada penelitian ini adalah perusahaan perbankan yang terdaftar di bursa efek indonesia, malaysia dan thailand dalam kurun waktu 2010 sampai 2016. Sampel yang di gunakan dalam penelitian ini sebanyak 24 perusahaan perbankan di negara indonesia, malaysia, dan thailand dengan menggunakan metode purpose sampling tujuanya untuk memperoleh sampel representatif yang sesuai kriteria yang sudah di pastikan. Pada penelitian ini, metode analisa data yang digunakan adalah data panel (pooled data) yang merupakan gabungan dari data antar waktu (time series) dan data antar individu atau ruang (cross section) di perusahaan perbankan di negara indonesia, malaysia dan thailand. Hasil Penelitian untuk perusahaan perbankan di negara indonesia Nilai R square model ini sebesar 0,222 persen artinya bahwa variasi dari profit yang dapat dijelaskan oleh variabel bebas yang di analisis yaitu NIM, BOPO, CAR dan NPL sebesar 22.20 persen sisanya sebesar 78.80 persen dijelaskan oleh faktor lain yang tidak dimasukkan dalam penelitian ini. Selanjutnya Di negara malaysia Nilai R square model ini sebesar 0,335 persen artinya bahwa variasi dari profit yang dapat dijelaskan oleh variabel bebas yang di analisis yaitu NIM, BOPO, CAR dan NPL sebesar 33.50 persen sisanya sebesar 66.50 persen dijelaskan oleh faktor lain yang tidak dimasukkan dalam penelitian ini. Sedangkan di negara thailand. Nilai R square model ini sebesar 0,266 persen artinya bahwa variasi dari profit yang dapat dijelaskan oleh variabel bebas yang di analisis yaitu NIM, BOPO, CAR dan NPL sebesar 26.60 persen sisanya sebesar 73.40 persen dijelaskan oleh faktor lain yang tidak dimasukkan dalam penelitian ini.

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Più fonti

Tesi sul tema "Stock exchanges – Thailand"

Sangmanee, Amporn. "An Empirical Analysis of Stock Market Anomalies and Spillover Effects: Evidence from the Securities Exchange of Thailand". Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc277737/.

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This study examines two interrelated but separate issues: cross-sectional predictability of equity returns in the Stock Exchange of Thailand (SET), and transmission of stock market movements. The first essay empirically investigates to what extent the evidence of three major documented stock market anomalies (earnings-price ratio, firm size, and book-to-market ratio) can be generalized across national stock markets. The second essay studies the price and volatility spillover effects from the New York Stock Exchange (NYSE) to the SET. The first essay, using the Fama-Macbeth procedure and the pooled time-series cross-sectional GLS regressions, finds a weak relation between the beta and average stock returns. The adjustment of estimated beta for the effect of thin trading does not change the implications of the results. Of the three anomalies investigated, the size effect has the most prominent and consistent role in explaining average returns. For the earnings-price ratio, the results indicate that the significance of the E/P ratio variable persists only if the nonfinancial firms are considered. In contrast to the previous empirical results for the U.S. and Japanese stock markets, the book-to-market ratio fails to explain the SET equity returns. The second essay employs a generalized autoregressive conditionally heteroskedastic (GARCH) model with conditional t-distributed errors to investigate the spillover effects. No evidence of price spillover effects is found for the full sample period. However, the spillover effects are significant during the period in which the Federal Reserve Board raised interest rates. Further examinations reveal that information inferred from price changes in the U.S. market influences only the opening price in the SET, not the open-to-close Thai stock market returns. This implies that price in the SET is informationally efficient with respect to the price determined in the U.S. stock market. The evidence is generally supportive of international financial integration and informational efficiency in the Thai stock market.

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Poongam, Karan. "Equity premium in business cycle model in Thailand". Bangkok, Thailand : Faculty of Economics, Thammasat University, 2004. http://catalog.hathitrust.org/api/volumes/oclc/56680613.html.

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Suvanprakorn, Pratarnporn. "Thai economic crisis and its impact on the Thai stock market trends". Online version, 2001. http://www.uwstout.edu/lib/thesis/2001/2001suvanprakornp.pdf.

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Thammaraks, Angsu-apa. "Stock market anomalies and return predictability on the stock exchange of Thailand". Thesis, University of Exeter, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312080.

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Naranong, Teerasak. "The analysis of Thai economy and Stock Exchange of Thailand". Thesis, University of Exeter, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407294.

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Gautier, Bernardo Froes. "Corporate disclousure and the use of information by financial intermediaries in Thailand". Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/14170.

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Mestrado em Finanças
O objetivo deste trabalho foi explorar a relação da divulgação financeira face ao comportamento dos investidores. A maioria dos registos e contabilidade escrita apontam que os níveis de exposição dos dados, que na sua maioria são utilizados como intermediários devido à natureza dos mesmos, apresentados por empresas registradas afeta o funcionamento do mercado financeiro, especificamente sobre a liquidez e a estimativa de ações individuais. Ao revelar mais dados, as empresas são vistas a diminuir as assimetrias de dados e, dessa forma, expandindo a certeza financeira especializada. Da mesma forma, as empresas devem fornecer critérios de tomada de decisão e de declarações financeiras "transparentes" aos investidores, para que os mesmos não sejam induzidos em erro por números e valorizações demasiado otimista ou fictícias. Os resultados desta pesquisa revelaram que existem diferenças significativas nas perceções dos investidores da Bolsa de Valores da Tailândia de acordo com a dimensão da transparência da informação financeira associado a variáveis demográficas, exceto para o grupo mais intelectualizado. Esta pesquisa também encontrou uma relação entre as perceções dos investidores relativamente à transparência da dimensão financeira e o seu comportamento na Bolsa de Valores da Tailândia. E, finalmente, a pesquisa também elucidou para o facto de existirem diferenças no comportamento do investidor no Mercado de ações da Tailândia de acordo com as diferentes categorias e experiência mesmos.
The purpose of this dissertation was to explore the relationship of financial disclosure and investor behavior. The majority of the surviving back and bookkeeping writing recommends that the levels of data exposure, for the most part utilized as an intermediary for the nature of data unveiled, by recorded organizations affects the financial market, specifically on the liquidity and estimating of individual stocks. By revealing more data, organizations are seen to diminish data asymmetries and by so doing, expand a financial specialist certainty. Likewise, companies should provide such "transparent" financial statements and decision making criteria to investors in order to ensure that investors are not being misled with fictitious or better than expected numbers and figures. The results of this research revealed that there are significant differences in Stock Exchange of Thailand investor perceptions regarding each dimension of financial information transparency according to demographic variables, except for the education group. This research also found that there are relationships between Stock Exchange of Thailand (SET) investor perceptions of dimensions of financial information transparency and investor behavior in the Thai stock market. And finally, the research also found that there are differences in Stock Exchange of Thailand investor behavior according to different categories of investor experience.
info:eu-repo/semantics/publishedVersion

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Wiboonprapat, Nittaya. "Stock price movement analysis of the financials industry on the stock exchange of Thailand". 2005. http://catalog.hathitrust.org/api/volumes/oclc/124067708.html.

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Me-o-padmongcon, Supat. "Financial development and economic development role of stock market /". 1998. http://catalog.hathitrust.org/api/volumes/oclc/40703982.html.

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Pavabutr, Pantisa Titman Sheridan Yan Hong. "Foreign portfolio flows and emerging markets lessons from Thailand /". 2004. http://wwwlib.umi.com/cr/utexas/fullcit?p3143444.

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Pavabutr, Pantisa. "Foreign portfolio flows and emerging markets : lessons from Thailand /". Thesis, 2004. http://bibpurl.oclc.org/web/21164.

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Più fonti

Libri sul tema "Stock exchanges – Thailand"

Thai, Talāt Laksap hǣng Prathēt. The stock market in Thailand. Bangkok]: Stock Exchange of Thailand, 1999.

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Islam, Sardar M. N., e Sethapong Watanapalachaikul. Empirical Finance: Modelling and Analysis of Emerging Financial and Stock Markets (Contributions to Economics). Physica-Verlag Heidelberg, 2004.

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Capitoli di libri sul tema "Stock exchanges – Thailand"

Punwong, Siriluk, Nachatchapong Kaewsompong e Roengchai Tansuchat. "Impact of Economic Policy Uncertainty on the Stock Exchange of Thailand: Evidence from the Industry-Level Stock Returns in Thailand". In Studies in Computational Intelligence, 393–406. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49728-6_26.

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Nimanussornkul, Kunsuda, e Chaiwat Nimanussornkul. "Herding Behavior from Loss Aversion Effect in the Stock Exchange of Thailand". In Studies in Computational Intelligence, 317–32. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49728-6_21.

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Yammeesri, Jira, Seung Hwan Kang e Sim Kim Lau. "Ontology-Driven Accounting Information System: Case Study of the Stock Exchange of Thailand". In Knowledge, Information, and Creativity Support Systems, 68–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24788-0_7.

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Namwong, Natnarong, Woraphon Yamaka e Roengchai Tansuchat. "Trading Signal Analysis with Pairs Trading Strategy in the Stock Exchange of Thailand". In Structural Changes and their Econometric Modeling, 378–88. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04263-9_29.

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Thamprasert, Karn, Pathairat Pastpipatkul e Woraphon Yamaka. "Interval-Valued Estimation for the Five Largest Market Capitalization Stocks in the Stock Exchange of Thailand by Markov-Switching CAPM". In Econometrics for Financial Applications, 916–25. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73150-6_67.

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Tibprasorn, Phachongchit, Somsak Chanaim e Songsak Sriboonchitta. "A Copula-Based Stochastic Frontier Model and Efficiency Analysis: Evidence from Stock Exchange of Thailand". In Lecture Notes in Computer Science, 637–48. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49046-5_54.

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Puangyanee, Senee, e Krisakorn Duangsawang. "Factors Affecting the Level of Corporate Governance Disclosure by Companies Listed on the Stock Exchange of Thailand". In International Dimensions of Sustainable Management, 151–61. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04819-8_10.

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Chaysiri, Rujira, e Chanrathanak Ngauv. "Prediction of Closing Stock Prices Using the Artificial Neural Network in the Market for Alternative Investment (MAI) of the Stock Exchange of Thailand (SET)". In Lecture Notes in Computer Science, 335–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62509-2_28.

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Phoprachak, Dararat, e Theenida Buntornwon. "Influence of Firm Size on the Environmental Disclosure and Performance of the Listed Companies on the Stock Exchange of Thailand". In Responsible Business in a Changing World, 159–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36970-5_9.

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Charoenkitthanalap, Songwit, Jiraporn Kradphet, Dararat Phoprachak e Theenida Buntornwon. "The Impact of Environmental Accountants’ Ability on CSR Disclosure and Profitability of the Listed Companies on the Stock Exchange of Thailand". In Responsible Business in a Changing World, 183–94. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36970-5_11.

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Atti di convegni sul tema "Stock exchanges – Thailand"

Lestari, Reni. "Analysis of Stock Market Integration Among ASEAN Countries by Using Vector Error Correction Model (VECM) Approach". In Japan International Business and Management Research Conference. RSF Press & RESEARCH SYNERGY FOUNDATION, 2020. http://dx.doi.org/10.31098/jibm.v1i1.220.

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Globalization has driven the economy of countries to relate to each other. It brings relationships in the capital among countries in the world, especially in ASEAN region countries. This study aimed to analyze the integration of the stock market among countries in the ASEAN region. The stock market was analyzed are the Indonesia Stock Exchange, Malaysia Stock Exchange, Singapore Stock Exchange, Thailand Stock Exchange, Vietnam Stock Exchange, and Philippine Stock Exchange. This study using the Vector Error Correction Model (VECM) as the method. The result of this study shows that, in the long term Singapore Stock Index (STI), Malaysia Stock Index (KLSE), Philippines (PSEi), and Indonesia Stock Index (JKSE) are positively correlated. This means the change of stock index price in one country will affect other related countries in the long term. In the short term of VECM estimation, found the Vietnam Stock Index (VNI), Singapore Stock Exchange (STI), Philippine (PSEi) are positively correlated and negatively correlated with Thailand Stock Exchange (SET). For the managerial implication, the result of this study is expected as a reference or basis of consideration of investment decisions. This because long-term stock market movements are important because they impact international portfolio management and risk diversification.

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Mueadkhunthod, Krittiyaporn, Natchaya Khunmood, Sirawit Khittiwichayakul, Watid Phakphisut e Pornchai Supnithi. "Stock Analysis System for the Stock Exchange of Thailand". In 2019 34th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC). IEEE, 2019. http://dx.doi.org/10.1109/itc-cscc.2019.8793357.

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Sirijunyapong, Warut, Adisorn Leelasantitham, Supapogrn Kiattisin e Waranyu Wongseree. "Predict the stock exchange of Thailand - Set". In 2014 4th Joint International Conference on Information and Communication Technology, Electronic and Electrical Engineering (JICTEE). IEEE, 2014. http://dx.doi.org/10.1109/jictee.2014.6804126.

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Pongsupatt, Tharinee, e Apichat Pongsupatt. "FACTORS AFFECTING STOCK PRICE: THE CASE OF THAILAND STOCK EXCHANGE SET 100 INDEX". In 51st International Academic Conference, Vienna. International Institute of Social and Economic Sciences, 2019. http://dx.doi.org/10.20472/iac.2019.051.032.

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Sutheebanjard, Phaisarn, e Wichian Premchaiswadi. "Factors analysis on Stock Exchange of Thailand (SET) index movement". In Knowledge Engineering 2009). IEEE, 2009. http://dx.doi.org/10.1109/ictke.2009.5397320.

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"The Behavior of Speculators in the Stock Exchange of Thailand". In Nov. 29-30, 2016 London (UK). ICEHM, 2016. http://dx.doi.org/10.15242/icehm.ed1116043.

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Thitaweera, Nuttapol, e Sukree Sinthupinyo. "Correlation Network Analysis in the Stock Exchange of Thailand (SET)". In ICMLT 2021: 2021 6th International Conference on Machine Learning Technologies. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3468891.3468917.

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Lertyingyod, Weerachart, e Nunnapus Benjamas. "Stock price trend prediction using Artificial Neural Network techniques: Case study: Thailand stock exchange". In 2016 International Computer Science and Engineering Conference (ICSEC). IEEE, 2016. http://dx.doi.org/10.1109/icsec.2016.7859878.

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Rimcharoen, S., D. Sutivong e P. Chongstitvatana. "Prediction of the Stock Exchange of Thailand using adaptive evolution strategies". In 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05). IEEE, 2005. http://dx.doi.org/10.1109/ictai.2005.99.

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Sutheebanjard, Phaisarn, e Wichian Premchaiswadi. "Stock Exchange of Thailand Index Prediction Using Back Propagation Neural Networks". In 2010 Second International Conference on Computer and Network Technology. IEEE, 2010. http://dx.doi.org/10.1109/iccnt.2010.21.

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