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Tilakaratne, Chandima University of Ballarat. "Stock market predictions based on quantified intermarket influences." University of Ballarat, 2007. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12798.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Doctor of Philosophy
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Tilakaratne, Chandima. "Stock market predictions based on quantified intermarket influences." University of Ballarat, 2007. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15394.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Doctor of Philosophy
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Tilakaratne, Chandima University of Ballarat. "A neural network approach for predicting the direction of the Australian stock market index." University of Ballarat, 2004. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12804.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Master of Information Technology by Research
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Tilakaratne, Chandima. "A neural network approach for predicting the direction of the Australian stock market index." University of Ballarat, 2004. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15397.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Master of Information Technology by Research
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Wongbangpo, Praphan. "Dynamic analysis on ASEAN stock markets." access full-text online access from Digital dissertation consortium, 2000. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?9982126.
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Eadie, Edward Norman. "Small resource stock share price behaviour and prediction." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09CM/09cme11.pdf.
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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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Tyandela, Luvo. "The construction of All SADC stock market indices." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52499.
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Thesis (MBA)--Stellenbosch University, 2001.This thesis presents a study on : (1) The construction of the SADC All Stock Market Indices, namely the SADIX (SADC Index Including South Africa) and the SADEX (SADC Index Excluding South Africa), which will serve as performance benchmarks for the region, and as indices for tracking the performance of the region excluding the JSE (2) Comparative analysis of the SADC bourses returns (3) Correlation Analysis between the SADC countries The SADC All Stock Market Indices, SADIX & SAD EX are market value, capitalization-weighted indices in which all components are weighted according to the total market value of their outstanding shares. They comprise all equity securities listed on the SADC region excluding Tanzania. Both series are calculated in local currencies and converted to US dollar terms, using end-af-week data with a base value of 1,000 as at 3rd September 1999. The dissertation presents a discussion on the regionalization of the African stock exchanges and how they this will impact the low liquidity levels which is endemic to most of the African Stock Exchanges. The results obtained indicate a significantly high correlation between the individual country indices with the SADe All Stock market Indices. Furthermore, observations are that the SADe stock exchanges show similar reactions to news flow and economic shocks. However, there are negative correlations, which will offer investors a fundamental basis for a diversification strategy in the region. Finally, the thesis concludes that despite the perception that African stock markets are in chaos, there are lucrative SADe markets, smaller in terms of size and market capitalization that will provide good returns.
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Lee, Sang H. "Index inclusion effect growth vs. value /." Diss., Connect to the thesis, 2008. http://hdl.handle.net/10066/1451.
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Chan, Kwei-sang, and 陳貴生. "Hongkong stock index future and portfolio management." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31264232.
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Potgieter, Damien. "An analysis of the turn-of-the-year effect in South African equity returns." Thesis, Rhodes University, 2007. http://hdl.handle.net/10962/d1007605.
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This study investigates FTSE/JSE All Share index monthly and daily equity returns for evidence of the January and TY effect. Four different measures of monthly return are analysed for the 1995-2006 period, whilst daily returns are analysed during the 1995-2005 period. In addition to this, analysis is conducted on monthly Fama-MacBeth risk premium estimates tor the FTSE/JSE All Share Index. Descriptive statistics are first analysed, followed by ANOV A or Kruskai-Wallis tests, the paired t-test and finally dummy variable regression analysis in investigating the seasonality of FTSE/JSE All Share Index returns and risk premia. Analysis on monthly returns reveals an absence of the January effect, however a positive slightly statistically significant December effect is found. Thus, investors earn abnormal returns on equity during the month of December. The results from the Fama-MacBeth risk premia estimates reveals highly statistically significant negative risk premia seasonal patterns during March, July and September. Thus, investors are in fact penalised for investing in equities during these months. In addition, the analysis reveals an absence of a December effect in risk premia, which contradicts the risk-return trade-off central to modem finance. The daily return analysis reveals a highly significant Turn-of-the-Year effect (TY), which suggests that investors earn abnormal returns on days at the turn of the year. Therefore, it is concluded that a December effect is apparent in South African equity monthly returns, whilst a March, July and September effect is apparent in South African equity risk premia contradicting the risk-return trade-off central to modem finance. In addition to this, a TY effect is present in South African equity daily returns.
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Mikhailitchenko, Serguei, and na. "The Australian Housing Market: Price Dynamics and Capital Stock Growth." Griffith University. Department of Accounting, Finance and Economics, 2008. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20100729.074134.
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This study was motivated by the desire to contribute to the understanding of the movement of house prices and the role of the so-called economic fundamentals in the housing market, especially within an Australian context. The core objective of this thesis is to aid understanding of the economic and other mechanisms by which the Australian housing market operates. We do this by constructing an analytical framework, or model, that encompasses the most important characteristics of the housing market. This thesis examines two important aspects of the Australian housing market: movements of house prices and changes in the net capital stock of dwellings in Australia. Movements of house prices are modelled from two perspectives: firstly, using the fundamental approach, which explains the phenomena by changes in such fundamental explanatory variables as income, interest rates, population and prices of building materials, and secondly, by analysing spatial interdependence of house prices in Australian capital cities. Changes in stock of dwellings were also modelled on the basis of a fundamental approach by states and for Australia as a whole...
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Fish, Therese. "The construction of African regional and all-Africa stock market indices." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52498.
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Thesis (MBA) --Stellenbosch University, 2001.ENGLISH ABSTRACT: Africa's stock markets are considered by many emerging market specialists to have great potential for investors. Developing models which track share/financial indices provide a means of disseminating information about market performance. With the active move towards regional stock markets, regional indices will provide an important tool for performance of the region. Stock market indices provide information to investors and portfolio managers about the performance of various markets or groups of stocks. Investors can use the movement of indices as a way of assessing market trends and opportunities for investment. As economic integration increases in Africa, it will become increasingly important to have markers of regional market performance. This study project collected weekly market capitalisation data from the markets in the various regions, which were utilised to construct regional all-share indices for the year 2000. Regional indices for three of the four regions within Africa were constructed. The three indices are the EASDEX (for East Africa), the NADEX (for North Africa) and the WADEX (for West Africa). The weekly market capitalisation data were further utilised to construct an All-Africa index. The Johannesburg Stock Exchange (JSE) dominates the Southern African Development Community (SADC) regional market's total market capitalisation. Similarly the SAOG region dominates the total market capitalisation for Africa. The JSE contributes 59% to the total market capitalisation of Africa (January 2000). The All-Africa index moves together with the SADIX (SAOG regional index) confirming the high weighting of South Africa in the total market capitalisation of Africa. Encouraging economic growth throughout Africa and not just in Southern Africa will assist the continent as a whole to attract market capital. In the long term this should increase market growth in the other regions of Africa and enable investors to diversify into Africa. There are certainly opportunities for investors in Africa. The low correlation between Egypt and the other two North African markets allows for diversification within the North African Region. Nigeria has been the market that had the highest returns during 2000, one that outperformed many international markets. SADIX has low or negative correlation coefficients with the rest of the African individual as well as the regional market indices. Historically emerging markets are volatile and risky. The case for diversification into emerging markets originates from the high economic growth potential of emerging markets, together with low correlation with other developed markets. The development of All-Share indices, which track market performance on the African continent, will assist both potential institutional as well as individual investors.
AFRIKAANSE OPSOMMING: Afrika se effektemarkte word deur baie opkomende markspesialiste beskou as potensieel gunstig vir beleggers. Deur modelle wat aandele/finansiële indekse volg te ontwikkel, word 'n middel voorsien om informasie oor markprestasie te ontleed. Met die aktiewe beweging na streeksaandelemarkte, sal streeksindekse 'n belangrike maatstaf vir die prestasie van 'n area voorsien. Aandelemarkindekse voorsien informasie aan beleggers en portefeulje bestuurders oor die prestasie van verskeie markte of aandelegroepe. Beleggers kan die beweging van die indekse gebruik om marktendense te ontleed asook om geleenthede vir investering te identifiseer. Dit sal belangriker raak om maatstawwe van streeksmarkprestasie te hê soos ekonomiese integrasie in Afrika toeneem. Hierdie studieprojek het weeklikse markkapitalisasie data van die markte in die verskeie areas versamel, wat gebruik is om 'n streeksindeks van alle aandele vir die jaar 2000 saam te stel. Streeksindekse vir drie van die vier streke binne Afrika is saamgestel. Die drie indekse is die EASDEX (Oos Afrika), die NADEX (Noord Afrika) en die WADEX (Wes Afrika). Die weeklikse markkapitalisasie data is verder aangewend om 'n Alle- Afrika indeks saam te stel. Die Johannesburgse Effektebeurs (JEB) domineer die totale markkapitalisasie van die Suidelike Afrika Ontwikkelingsgemeenskap (SAOG) se streeksmark. Insgelyk domineer die SAOG streek die totale markkapitalisasie vir Afrika. Die JES dra 59% by tot die totale markkapitalisasie van Afrika (Januarie 2000). Die Alle-Afrika indeks beweeg saam met die SADIX (SAOG streeksindeks) wat die gewigtigheid van Suid Afrika in die totale markkapitalisasie van Afrika bevestig. Deur ekonomiese groei regdeur Afrika en nie bloot in Suider Afrika nie, aan te spoor, sal dit die vasteland as 'n geheel steun om markkapitaal aan te trek. Op die lange duur behoort dit groei te bevorder in die ander streke van Afrika en beleggers in staat te stel om binne Afrika te diversifiseer. Daar is ongetwyfeld geleenthede vir beleggers in Afrika. Die lae onderlinge afhanklikheid tussen Egipte en die ander twee Noord Afrika markte laat diversifikasie binne die Noord Afrika streek toe. Nigerië is die mark met die hoogste opbrengste tydens 2000 en het selfs baie internasionale markte oortref. SADIX het lae of negatiewe korrelasiekoeffisiënte met die res van die Afrika individuele-, sowel as die streeksmarkindekse. Histories is opkomende markte onstabiel en riskant. Partydigheid vir diversifikasie in opkomende markte ontstaan vanuit die hoë ekonomiese groeipotensiaal van hierdie markte tesame met lae onderlinge afhanklikheid met ander ontwikkelde lande. Deur indekse van alle aandele wat markprestasie op die Afrika-vasteland volg saam te stel, sal beide potensiële institusionele, sowel as individuele beleggers se besluite/ontledings ondersteun word.
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Heger, Levin, and Lisa Åkerman. "Momentum in ESG Indexes : A study on the passive capital flows effect on ESG stock prices." Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185265.
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The aim with this thesis is to investigate whether increased capital flows to ESG screened indexes create higher price-to-earnings (P/E) ratios and momentum in the included stocks during the chosen time period of three years, from 2018 to 2020. The thesis will evaluate the capital flows to ESG indexes and compare both performance and P/E ratios between those and their corresponding Mother indexes. The study will also look at the development of capital flows, performance and P/E ratios separately in the four chosen geographical indexes; Global, Europe, US and Emerging Markets. The theoretical framework goes through four relevant subjects for this study; passive investing, ESG, momentum and the P/E ratio. The study has shown that the capital flows in all four ESG indexes increased during the chosen time period. Moreover, it could be proven that three out of four ESG indexes outperformed their Mother indexes, namely, Global, Europe and Emerging Markets. In the U.S. the Mother index outperformed the ESG index. Three out of four geographical indexes also had a higher increase in the average P/E ratio than their mother indexes. Here, the Global market stood out as the one that had a lower increase in P/E ratio than its Mother index. Lastly, regression analyses were made to see the relationship between the variables capital flows, average P/E ratios in the indexes and the performance of the indexes. The study showed significantly that capital flows is the explanatory variable for the increased P/E ratios on the European ESG index. However, for the other indexes no significant correlation could be proved. This led to an interesting discussion and conclusion, and also left us with a question mark. What is the reason behind this result on the European market, and why was it not possible to see any significant correlation on the other markets? Further research in this field is needed and some ideas are discussed in the last chapter of the thesis.
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Karanfil, Salih. "Obtaining the membership function by using the neural network in Istanbul stock exchange to find the relation between the low and closing prices." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/96007.
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Motladiile, Bopelokgale. "Relationship between share index volatility, basis and open interest in futures contracts : the South African experience." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53572.
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Study project (MBA)--University of Stellenbosch, 2003.ENGLISH ABSTRACT: In a rational efficiently functioning market, the price of the share index and share index futures contracts should be perfectly contemporaneously correlated. According to the cost of carry model, the futures price should equal its fair value at maturity. The basis should be equal to the cost of carry throughout the duration of the futures contract. However, in practice the cost of carry model is obscured and the basis varies and is normally not equal to the cost of carry. Reasons for this variability in basis include the mark-to-market requirement of the futures contract, the differential tax treatment of spot and futures contracts, as well as the transaction cost of entering into a contract. Transaction costs are lower for futures contracts than for spot contracts. This study uses the Chen, Cuny and Haugen (1995) model to examine the relationship between the basis and volatility of the underlying index and between the open interest of the futures contract and the volatility of the underlying index. Chen et al. (1995) predicted that the basis is negatively related to the volatility of the underlying index and that the open interest is positively related to the volatility of the underlying index. The study will also test the statement by Helmer and Longstaff (1991) that the basis has a negative concave relationship with the level of interest rate. The tests were performed on data from ALSI, FINI and INDI futures contracts. The sample period was from January 1998 to December 2001. The results correspond to those obtained by Chen et al. (1995) in that the basis is negatively related to the volatility of the underlying index. This is true for all the three indices. The other main prediction of the Chen, Cuny and Haugen (CCH) model (1995), which is also supported by the study, is that open interest is significantly related to the volatility of the underlying index. The study also supports the statement by Helmer and Longstaff (1991) that the there is a highly significant negative concave relationship between the basis and interest rate.
AFRIKAANSE OPSOMMING: In "n mark wat rasioneel funksioneer, behoort die prys van die aandele-indeks en aandele-indekstermynkontrakte perfek gekorreleer te wees in tyd. Volgens die drakostemodel behoort die termynkontrakprys op die vervaldatum gelyk te wees aan die billike waarde daarvan. Die basis behoort vir die looptyd van die termynkontrak gelyk te wees aan die drakoste. In die praktyk word die drakostemodel egter vertroebel en wissel die basis en is dit gewoonlik nie gelyk aan die drakoste nie. Redes vir hierdie veranderlikheid van die basis sluit in die waardasie teenoor markprys van die termynkontrak, die belasting van toepassing op loko- en termynkontrakte, asook die transaksiekoste by die aangaan van "n kontrak. transaksiekoste vir termynkontrakte is laer as vir lokokontrakte. Hierdie studie gebruik die model van Chen, Cuny en Haugen (1995) om die verwantskap tussen die basis en die volatiliteit van die onderliggende indeks en tussen die oop kontrakte van die termynkontrak en die volatiliteit van die onderliggende indeks te ondersoek. Chen et al. (1995) voer aan dat daar 'n negatiewe verwantskap is tussen die basis en die volatiliteit van die onderliggende indeks en dat daar "n positiewe verwantskap is tussen die oop rente en die volatiliteit van die onderliggende indeks. Die studie toets ook Helmer en Longstaff (1991) se hipotese dat daar 'n negatiewe, konkawe verhouding tussen die basis en die rentekoersvlak bestaan. Die toetse is uitgevoer op data van ALSI-, FINI- EN INDItermynkontrakte. Die steekproef was van Januarie 1998 tot Desember 2001. Die resultate stem ooreen met dié van Chen, Cuny en Haugen (1995) se model (CCH-model) in dié opsig dat daar "n negatiewe verband is tussen die basis en die volatiliteit van die onderliggende indeks. Dit geld vir al drie die indekse. Die ander hoofresultate van Chen et al. (1995), wat ook deur die studie ondersteun word, is dat daar "n beduidende verband tussen die oop kontrakte en die volatiliteit van die onderliggende indeks bestaan. Die studie ondersteun ook Helmer en Longstaff(1991) se siening dat daar 'n beduidende, negatiewe, konkawe verhouding tussen die basis en die rentekoers bestaan.
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Castilhos, Nádia Cristina de. "O grau de investimento corporativo das empresas listadas no IBRX50 : análise do rating divulgado pelas certificadoras." reponame:Repositório Institucional da UCS, 2017. https://repositorio.ucs.br/handle/11338/3357.
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As empresas são constantemente avaliadas, no que tange a resultados financeiros e econômicos, bem como as suas estratégias. As demonstrações financeiras são relatórios importantes na avaliação do desempenho da evolução patrimonial das organizações, fornecendo uma visão global da organização. Este estudo tem como objetivo identificar a relação entre Grau de Investimento, definido pelo rating do método de Guth, com o das certificadoras Standard & Poor's, Moody's e Fitch Ratings, com base nos dados das empresas listadas no IBRX 50. O grau de investimento de uma empresa concede um selo de “bom pagador”, esta avaliação ocorre de forma quantitativa e qualitativa, permitindo uma visão ampla dos negócios da organização. Para analisar a aderência do método que utiliza apenas indicadores financeiros e o divulgado pelas principais certificadoras será realizada uma pesquisa pelo método quantitativo-descritivo, utilizando as empresas listadas no IBRX50. A pesquisa é classificada como aplicada, com abordagem quantitativa, sendo apurado o grau de investimento pelo método de Guth através das demonstrações contábeis das empresas listadas no IBRX50, no ano de 2016, comparando com o divulgado pelas agencias certificadoras. Quanto ao objetivo é descritiva, utilizando procedimentos documentais, baseada em relatórios contábeis financeiros para calcular o grau de investimentos e os pareceres divulgados pelas certificadoras para comparar o rating divulgado como o apurado a partir dos seguintes indicadores financeiros: liquidez, rentabilidade, lucratividade, , solvência, endividamento e giro do ativo. Como resultados verificou-se a existência de diferenças entre o rating divulgado pelas agências, empresas que não possuem classificação divulgada pelas três certificadoras concomitantemente. A lista do IBRX50 contempla empresas que não foram avaliadas pelas certificadoras.Submitted by Ana Guimarães Pereira (agpereir@ucs.br) on 2017-12-06T16:50:26Z No. of bitstreams: 1 Dissertacao Nadia Cristina de Castilhos.pdf: 1045174 bytes, checksum: 3baf5f6c86f3e49a4273a261fa6b1479 (MD5)
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Companies are constantly evaluated in terms of financial and economic results as well as their strategies. The financial statements are important reports in assessing the performance of the organization's equity evolution, providing a global view of the organization. This study has as general objective to identify the relation between Investment Grade, defined by the rating of Guth’s Method, with the certifiers Standard & Poor's, Moody's and Fitch Ratings, based on the data of the companies listed in the IBRX 50. The degree of investment of a company grants it a "good payer" seal, this evaluation occurs quantitatively and qualitatively, allowing a broad view of the organization's business. In order to analyze the adherence of the method that uses only financial indicators and that disclosed by the main certifiers, a research based on a quantitative-descriptive method will be done, using the companies listed in the IBRX50, in 2016. The objective is descriptive, using documentary procedures, based on financial accounting reports to calculate the degree of investments and the opinions published by the certifiers to compare the rating disclosed as calculated from the financial indicators: Liquidity indebtedness, Immediate liquidity, Profitability of the asset, Profitability, Current liquidity, Dry liquidity, Solvency, Indebtedness of Liquid Equity, Return on Liquid Equity and Asset turnover. As results it was verified that there are differences between the ratings disclosed by the three agencies. The IBRX50 list includes companies that have not been evaluated by the certifiers.
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Gottschling, Andreas Peter. "Three essays in neural networks and financial prediction /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1997. http://wwwlib.umi.com/cr/ucsd/fullcit?p9728773.
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Bunger, R. C. (Robert Charles). "Derivation of Probability Density Functions for the Relative Differences in the Standard and Poor's 100 Stock Index Over Various Intervals of Time." Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc330882/.
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In this study a two-part mixed probability density function was derived which described the relative changes in the Standard and Poor's 100 Stock Index over various intervals of time. The density function is a mixture of two different halves of normal distributions. Optimal values for the standard deviations for the two halves and the mean are given. Also, a general form of the function is given which uses linear regression models to estimate the standard deviations and the means.
The density functions allow stock market participants trading index options and futures contracts on the S & P 100 Stock Index to determine probabilities of success or failure of trades involving price movements of certain magnitudes in given lengths of time.
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Lapanan, Nicha, and Stefan Anchev. "Wealth effects from asset securitization : (the case of Australia)." Thesis, Umeå universitet, Företagsekonomi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-47813.
Full textAbstract:
Asset securitization is one of the most important financial innovations recently. With an impressive growth in terms of volume of issuance, from almost zero to five trillion USD, in a period of 15-20 years, it is one of the most rapidly growing markets in the financial world. Yet, little is known about this, literally invisible market. Companies engage in asset securitization for a variety of reasons and numerous advantages and disadvantages of asset securitization can be found throughout the literature. Asset securitization has an impact on a number of stakeholder groups: shareholders, managers, employees, investors, the financial markets and ultimately the overall economy and society. Asset securitization is one of the reasons for the financial crisis that started in mid 2007. Since the recent financial turmoil, it became clear the asset securitization was the primary funding source for companies in the financial industry and it was the primary supplier of credit in developed economies. Because of its importance and impact, it is very important that we study the reasons, the motivations, the consequences and the effects from this so powerful financial innovation. And it is important to study it from as many different aspects as possible. Many questions surrounding asset securitization are unanswered and it is important to answer them sooner. This study investigates the wealth effects from asset securitization on the shareholders of the securitizing companies. We study whether the announcement about a pending securitization transaction has any impact on the stock price of the securitizing company. That way we can discover whether asset securitization creates wealth, destroys wealth or has no impact on wealth at all. Not many studies have been done on this topic so far. The existing seven studies are focused mainly on the US and the EU market and report contradicting results. In this study, for the first time, data from Australia is being used. The Australian securitization market is the second, single most active securitization market in the world, after the US market. We conduct quantitative analysis on a sample of 98 securitization transactions during the period 2000-2006. With this sample, we cover almost 29% of the number of securitization transactions during that period and almost 39% in terms of volume of issuance. To analyze the data we use standard event study methodology, common for this type of studies. Our analysis reveals that investors in Australia do not perceive asset securitization favorably. Securitizing companies’ stock price decreases in the 10 days around the securitization announcement day, resulting in statistically significant wealth losses for the originating companies’ shareholders. Furthermore, the wealth losses are significant for less frequent securitizers, for securitizers that engage in small volume securitization transactions and for securitizing companies with low asset quality. With this study we make theoretical and practical contribution. We lend empirical support to the previous theories and we help managers, shareholders and investors shape their forecasts.
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O'Grady, Thomas A. "The profitability of technical analysis and stock returns from a traditional and bootstrap perspective : evidence from Australia, Hong Kong, Malaysia and Thailand." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2012. https://ro.ecu.edu.au/theses/506.
Full textAbstract:
This research questions whether technical trading rules can help predict stock price movements for a sample of stocks selected from four equity markets from the Asia-Pacific region: Australia, Malaysia, Hong Kong and Thailand for the period 1989-2008. The research is split into two stages. Stage-1 of the research tests the predictability of technical trading rules against a buyand- hold strategy. The variable moving average (VMA), fixed moving average (FMA) and the trading range break (TRB) trading rules are applied to this research. Economic predictability of these rules is examined by comparing returns conditional on a trading rule buy (sell) signal against an unconditional buy-and-hold return. Any existence of excess returns can thus be established. This follows with a statistical analysis of returns using a traditional t-test methodology. Traditional statistical tests assume normally distributed returns with independent observations and a non-changing distribution across time. In Stage-2 of this research a bootstrap checks whether features such as non-normality, time-varying moments and serial correlation bias test statistics. The bootstrap involves assumptions regarding the underlying returns generating process (RGP) and allows returns conditional on a trading rule buy (sell) signal from the original stock price series to be compared with conditional returns simulated from four common null models: RW, AR (1), GARCH-M and E-GARCH models. Simulated p-values are calculated in conjunction with simulated distributions and are applied in lieu of the theoretical normal distribution. Given this process it is possible to infer as to whether non-linear dependencies in returns can be captured by any of the three trading rules. Given the null model output standard t-test outcomes of predictability of technical trading rules may be diminished and/or eliminated. Conclusions are drawn as to the predictability and profitability of the VMA, FMA and TRB trading rules when applied to the chosen stock samples. Findings of this research indicate returns conditional on technical trading rules exceed unconditional buy-and-hold returns for all stocks. Thai sample output indicates strong support in favour of the predictability of standard test results supporting the use of technical trading rules. Output for Australia, Hong Kong and Malaysia indicates that previous standard t-test outcomes of predictability may be diminished and/or eliminated. This implies that the underlying RGP may be characterised by underlying features of some/all of the stochastic models.
22
Novoselova, Mariya, and Nhar Soklim. "Is there any effect of going concern audit opinion public announcements on the stock price behavior in a short term period? : Empirical evidence from Australia." Thesis, Umeå universitet, Handelshögskolan vid Umeå universitet, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-45161.
Full textAbstract:
The research paper explores the value of information content incorporated in the first-time going concern opinion from the perspective of investors. The signaling effects of the auditors’ opinion with going concern remark issued to financially distressed companies are of a great value in case the auditor statements deliver new information content which has not been incorporated in the previously disclosed financial information. Otherwise a going concern audit opinion remains not relevant for the purpose of investors’ decision making. If the going concern audit opinion adds new information content, we gain an ability to detect a stock market reaction to the relevant public announcement. The paper examines the Australian stock market reaction to public announcements of going concern audit opinion in a short term period for the sample of the 29 first-time going concern listed companies during the 2007 to 2009 years observation period. High sample criteria are determined in order to avoid contamination effects of other price sensitive information. The impact of both the preliminary financial report and the final annual report is examined by means of the parametric and non-parametric tests aligned with the event study methodology. Consistent with previous studies in Australia, no significant financial market reaction to the final going concern audit opinion announcements inherent to the Australian environment has been found. We document that the more negative impact on the market reaction is caused by the preliminary financial report rather than the final report, which contains an audit opinion note. Correspondently, the audit opinions with going concern qualification do not add new information content for the Australian stock market participants, who base their expectations on the previously disclosed financial information.
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Yang, Wenling. "M-GARCH Hedge Ratios And Hedging Effectiveness In Australian Futures Markets." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2000. https://ro.ecu.edu.au/theses/1530.
Full textAbstract:
This study deals with the estimation of the optimal hedge ratios using various econometric models. Most of the recent papers have demonstrated that the conventional ordinary least squares (OLS) method of estimating constant hedge ratios is inappropriate, other more complicated models however seem to produce no more efficient hedge ratios. Using daily AOIs and SPI futures on the Australian market, optimal hedge ratios are calculated from four different models: the OLS regression model, the bivariate vector autoaggressive model (BVAR), the error-correction model (ECM) and the multivariate diagonal Vcc GARCH Model. The performance of each hedge ratio is then compared. The hedging effectiveness is measured in terms of ex-post and ex-ante risk-return traHe-off at various forcasting horizons. It is generally found that the GARCH time varying hedge ratios provide the greatest portfolio risk reduction, particularly for longer hedging horizons, but hey so not generate the highest portfolio return.
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Yeoh, Daniel Ghee Chong, and danielyeoh@cimb com my. "An Empirical Examination of Physical Asset Expenditure Announcements in Australia: Growth Opportunities, Free Cash Flow and Capital Market Monitoring." The Australian National University. Commerce, 2001. http://thesis.anu.edu.au./public/adt-ANU20010702.160428.
Full textAbstract:
This thesis examines the stock market price variations associated with physical asset expenditure announcements in Australia. With the exception of the study of Chen and Ho (1997) in Singapore, most capital expenditure studies in other markets investigate the announcement effects associated with changes in budgeted capital expenditures. The fact that there is almost never any firm level capital budget announcement in Australia presents a unique opportunity to examine individual physical asset expenditure announcements.
¶
Three primary hypotheses pertaining to growth opportunities, free cash flow theory, and the capital market monitoring argument are developed and tested. These arguments are formulated to explain the abnormal return variations associated with physical asset expenditure announcements. The growth opportunities hypothesis posits that the abnormal returns at physical asset expenditure announcements are positively related to a firm's growth opportunities. Both free cash flow theory and capital market monitoring hypothesis postulate that the abnormal returns at physical asset expenditure announcements are negatively related to a firm's free cash flow, and cash flow respectively. Other control explanators are incorporated from the merger and takeovers literature.
¶
Event study methodology is used to examine the abnormal returns associated with physical asset expenditure announcements. Two sets of data, intraday and daily, are used to investigate the market reaction. Intraday returns are calculated on a time-weighted approach and two methods are used to calculate intraday abnormal returns. The first method defines abnormal returns as the difference between actual returns and market returns. The second method defines abnormal returns as the difference between market-adjusted returns and market-adjusted returns on a control portfolio. Daily abnormal returns are calculated using the market model.
¶
Both univariate and multivariate analyses provide strong support for the growth opportunities hypothesis. The results suggest the quality of firms' growth opportunities is the key variable determining the direction and magnitude of the abnormal returns at announcement. Support for the capital monitoring argument and the free cash flow theory is mixed, generally with a lack of support. The free cash flow variable is found to be significantly negatively related to abnormal returns, only when a finer dummy is used in the multivariate regression. All other control variables are found to be insignificant in explaining the stock market variations once the growth opportunities variable is included in the regression.
¶
This thesis makes the following contributions. First, this thesis presents the initial empirical evidence concerning physical asset expenditure announcements in Australia. Second, the thesis shows that the quality of a firm's growth opportunities is the key factor in determining the direction and magnitude of abnormal returns around physical asset expenditure announcements. These results also suggest that the equity market in Australia reacts to physical asset expenditure announcements which contain information pertaining to growth opportunities rather than the relative size of the physical asset expenditure transactions to firm value. Third, support for the capital monitoring argument and the free cash flow theory is not strong. Fourth, all other control variables are found to be insignificant in explaining the stock market variations once market to book ratio is included in the regression. Fifth, the results suggest that prior research which fails to segregate market to book ratio and free cash flow proxy into finer partitions may have possibly underestimated the market to book and the free cash flow effects.
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Colliri, Tiago Santos. "Avaliação de preços de ações: proposta de um índice baseado nos preços históricos ponderados pelo volume, por meio do uso de modelagem computacional." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/100/100132/tde-07072013-015903/.
Full textAbstract:
A importância de se considerar os volumes na análise dos movimentos de preços de ações pode ser considerada uma prática bastante aceita na área financeira. No entanto, quando se olha para a produção científica realizada neste campo, ainda não é possível encontrar um modelo unificado que inclua os volumes e as variações de preços para fins de análise de preços de ações. Neste trabalho é apresentado um modelo computacional que pode preencher esta lacuna, propondo um novo índice para analisar o preço das ações com base em seus históricos de preços e volumes negociados. O objetivo do modelo é o de estimar as atuais proporções do volume total de papéis negociados no mercado de uma ação (free float) distribuídos de acordo com os seus respectivos preços passados de compra. Para atingir esse objetivo, foi feito uso da modelagem dinâmica financeira aplicada a dados reais da bolsa de valores de São Paulo (Bovespa) e também a dados simulados por meio de um modelo de livro de ordens (order book). O valor do índice varia de acordo com a diferença entre a atual porcentagem do total de papéis existentes no mercado que foram comprados no passado a um preço maior do que o preço atual da ação e a sua respectiva contrapartida, que seria a atual porcentagem de papéis existentes no mercado que foram comprados no passado a um preço menor do que o preço atual da ação. Apesar de o modelo poder ser considerado matematicamente bastante simples, o mesmo foi capaz de melhorar significativamente a performance financeira de agentes operando com dados do mercado real e com dados simulados, o que contribui para demonstrar a sua racionalidade e a sua aplicabilidade. Baseados nos resultados obtidos, e também na lógica bastante intuitiva que está por trás deste modelo, acredita-se que o índice aqui proposto pode ser bastante útil na tarefa de ajudar os investidores a definir intervalos ideais para compra e venda de ações no mercado financeiro.The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.
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Hodgson, Allan Clement. "Information transfer, microstructures and arbitrage in related stock and futures markets." Phd thesis, 1995. http://hdl.handle.net/1885/128733.
Full textAbstract:
A general result from theoretical and empirical research in financial market is that
information, market microstructure and trading clientele affect prices and trading
patterns. Previous research, however, concentrated mainly on larger well traded security
markets. This thesis extend this research to the thinly traded and informationally
dependent Australian All Ordinaries Index (AOI), the Share Price Index (SPI) future
contract and the arbitrage pricing series between these two markets. Time series and
transfer function techniques are applied to intraday and interday data to examine the
impact of information flow and trading structures on trading and price patterns and the
spillover effect across markets.
The empirical evidence from this the is thesis is consistent with a number of complex and
dynamic relationship which vary across trading times and market place. Reults
indicate that in individual AOI and SPI markets, structural trading halts, price setting
mechanism, and the arrival of information at market opening are associated with price
overreaction and higher volatility, but this is not the case in the arbitrage price series. At
the close of trading there are significant average price deviations in the individual and
arbitrage erie, but without any excess price volatility. Unexpected intraday trading
activity in the futures market preceded price exchange in the stock and future markets; the
arrival of information has a greater impact on future price and the short term volatility
in the futures markets is significantly higher than in the stock market. These influence
in the future market, however, did not lead to any spillover effect which increased the
long term volatility of the stock market. However, there is evidence of sustained and
predictable mispricing in the SPI index futures arbitrage series with mean reversion in the
arbitrage series being a function of different time of the day and possible market
psychology. On the other hand, significant mean reversion is associated with increased
trading volume and efficient transaction cost bound argument.
Overall, the research in this thesis indicate that market are affected by a mixture of
information, trading micro structure and subtle market reaction, which are both rational
and irrational. The major conclusion is that price and volume reaction are complex and
flexible theories are required to explain the intricate working of the marketplace. These
are important consideration to be borne in mind by policy makers, regulator and market
traders.
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ZHANG, ZHI-MING, and 張志銘. "A study of integrating stock market indexes to predict stock price." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/31392282911731993631.
Full text
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Liou, Yann Liang, and 劉彥良. "Taiwan OTC stock cointegration relationship of sector price indexes." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/64056160368552205756.
Full text
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Sha, Yi-Ming, and 沙益民. "The Cointegration of Taiwan Stock Exchange Sector Price Indexes." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/39519395148123668321.
Full text
30
White, Alan G. "Economic and financial indexes." Thesis, 1999. http://hdl.handle.net/2429/10137.
Full textAbstract:
This thesis examines the theoretical underpinnings and practical construction of select economic
and financial indexes. Such indexes are used for a variety of purposes, including the
measurement of inflation, portfolio return performance, and firm productivity.
Chapter 1 motivates interest in economic and financial indexes and introduces the principal
ideas in the thesis.
Chapter 2 focuses on one potential source of bias in the Canadian consumer price index
(CPI) that arises from the emergence of large discount/warehouse stores—the so-called outlet
substitution bias. Such outlets have gained market share in Canada in recent years, but
current CPI procedures fail to capture the declines in average prices that consumers enjoy
when they switch to such outlets. Unrepresentative sampling, and the fact that discount
stores often deliver lower rates of price increase can further bias the CPI. Bias estimates
for some elementary indexes are computed using data from Statistics Canada's CPI production
files for the province of Ontario. It is shown that the effect on the Canadian CPI of
inappropriately accounting for such discount outlets can be substantial.
Another area in which indexes are frequently used is the stock market. Several stock
market indexes exist, including those produced by Dow Jones and Company, Standard and
Poor's Corporation, Frank Russell and Company, among others. These indexes differ in two
fundamental respects: their composition and their method of computation—with important
implications for their usage and interpretation. Chapter 3 introduces the concept of a stock
index by asking what, in fact a stock market index is—this is tantamount to considering the
purpose for which the index is intended, since stock indexes should be constructed according
to their usage. Because stock indexes are most commonly used as measures of returns on
portfolios, the main considerations in constructing such return indexes are examined.
Chapter 4 uses the Dow Jones Industrial Average (DJIA) as a case study to examine
its properties as a return index. It is shown that the DJIA is not the return on a market
portfolio consisting of its thirty component stocks: in fact the DJIA measures the return
performance on a very particular (and unusual) investment strategy, a fact that is not well
understood by institutional investors. An examination of some other popular stock indexes
shows that they all differ in their computational formula and that each is consistent with a
particular investment strategy. Numerical calculations reveal that the return performance of
the DJIA can vary considerably with the choice of basic index number formula, particularly
over shorter time horizons.
Given the numerous ways of constructing stock market return indexes, the user is left to
determine which is 'best' in some sense. The choice of an appropriate (or 'best') formula for
a stock market index is formally addressed in chapter 5. The test or axiomatic approach to
standard bilateral index number theory as in Eichhorn & Voeller (1983), Diewert (1993a),
and Balk (1995) is adapted here. A number of a priori desirable properties (or axioms) are
proposed for a stock index whose purpose is to measure the gross return on a portfolio of
stocks. It is shown that satisfaction of a certain subset of axioms implies a definite functional
form for a stock market return index.
Chapter 6 evaluates the various stock indexes is use today in terms of their usefulness
as measures of gross returns on portfolios. To this end the axioms developed in chapter 5
are used to provide a common evaluative framework, in the sense that some of the indexes
satisfy certain axioms while others do not. It is shown that the shortcomings of the DJIA as
a measure of return arise from its failure to satisfy a number of the basic axioms proposed.
Notwithstanding this, each index corresponds to a different investment strategy. Thus, when
choosing an index for benchmarking purposes an investor should select one which closely
matches his/her investment strategy—a choice that cannot be made by appealing to axioms
alone.
31
"Performance, market anomalies, trading volume & stock index relationships in neglected markets." 1998. http://library.cuhk.edu.hk/record=b5896254.
Full textAbstract:
by Ip Ka Tsun Anthony and Tang Ying Wa.Thesis (M.B.A.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references (leaves 42-46).
ABSTRACT --- p.i
TABLE OF CONTENTS --- p.iii
LIST OF TABLES --- p.iv
ACKNOWLEDGMENTS --- p.v
Chapter
Chapter I. --- INTRODUCTION --- p.1
Chapter II . --- LITERATURE REVIEW --- p.4
Selection Criteria of the Neglected Markets --- p.4
Market Review --- p.4
Day-of-the-Week Effect --- p.9
Month- of - the - Year Effect --- p.11
Spill´ؤOver Effect Across National Stock Markets --- p.11
Granger Causality Between Aggregate Stock Price and Trading Volume --- p.13
Chapter III. --- DATA and METHODOLOGY --- p.16
Day-of-the-Week Effect and Month-of-the-Year Effect --- p.16
Spill-Over Effect Across National Stock Markets and Granger Causality Between Aggregate Stock Price and Trading Volume --- p.18
Chapter IV. --- EMPIRICAL RESULTS --- p.24
Day-of-the-Week Effect --- p.24
Month-of-the-Year Effect --- p.26
Spill-Over Effect Across National Stock Markets --- p.28
Granger Causality Between Aggregate Stock Price and Trading Volume --- p.31
Chapter V. --- CONCLUSION --- p.36
Direction of Further Studies --- p.38
APPENDIX --- p.40
BIBLIOGRAPHY --- p.42
32
CHENG, YU-HSUAN, and 鄭宇軒. "The Prediction Effects of Economic Indicators on Weighted Stock Price Indexes." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/2zns77.
Full textAbstract:
碩士華梵大學
工業工程與經營資訊學系碩士班
107
After countless ups and downs as well as the 10,000 point-threshold, finally the market reached 10,000 points again in 2017, and remained there for over 65 transaction days. As for the future perspectives, the market boasts growth potential, however significant uncertainties exist for the actual results. With the rapid development of the Internet, information is exploding. Investors used to trade stocks at the securities exchange or via telephone calls. Now, they can do the same at any time during the stock transaction period using various hand-held devices, so that any information may have an impact on the decisions of investors or cause irrational stock trading, making the fluctuations of the Taiwan market even more unpredictable. As high-risk and high-return investment products, stocks are quite popular with investor, but their prices are changeable. To increase the possibility of making profits, it becomes a trend to predict the trajectory of the Taiwan stock market. There are many literatures around the world about stock price prediction, but the factors that can better predict the stock market remains unknown. This thesis discusses the prediction of the weighted, automobile and finance insurance stock price indexes with supply chain-related economic indicators and general economic indicators. Supply chain-related economic indicators include the Manufacturing Industrial Production Index and International Crude Oil price. The supply chain consists of the upstream and downstream. The upstream is production where market conditions will affect the production, inventories and number of order of factories, while the downstream is sales where the consumers’ perspectives toward future economy will affect their buying will, which in turn, affects the profit performance of enterprises. General economic indicators include the Overnight Interbank Call-Loan Rate and Monitoring indicator. The data of the supply chain-related economic indicators and general economic indicators in the thesis come from the Department of Statistics and the Bureau of Energy belonging to the Ministry of Economic Affairs of the Executive Yuan, the Bankers Association of the Republic of China, website of the National Development Council; while the closing information of the weighted stock price index, automobile stock price index and finance insurance stock price index comes from the website of the Taiwan Stock Exchange Corporation. The data sampling is from January 2008 to December 2017, for a total of ten years. Then the above data are analyzed using the multiple regression equations, There the stock price index as the dependent variable and various economic indicators as the independent variables. By exploring the prediction effect on the weighted stock price index, this thesis aims to serve as a stock investment reference for investors. The result of the study is that the supply chain-related economic indicators and the general economic indicators are combined to observe the relationships with on the weighted, automobile and financial insurance stock price indexes, and the results show that most of the indicators have a significant and positive effect on the above-mentioned stock price index.
33
Lin, Wei-Liang, and 林威良. "Predicting Stock Price Fluctuation by Applying Polynomial Regression to Analyze Financial Indexes." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/18402353034995692930.
Full textAbstract:
碩士中國文化大學
資訊管理學系
100
The main factors which affect stock prices can be elaborated to two respects: one is the fundamental plane, and the other is the technical plane. Analysis in the fundamental plane can indicate financial statement of a corporation. Financial index is the spindle of fundamental-plane analysis; we can analyze financial structure, debt-paying ability, business capacity, profit ability, cash flow and so on from financial index of a corpora-tion so as to realize the factors influence stock price fluctuation further. This paper proposes methods using linear polynomial and polynomial regression. To begin with acquiring weighting coefficient of financial index, and then it is combined with the financial index resulted from a polynomial regression forecasting. As a result, the prediction of stock price rise and fall is obtained. In conclusion, there are two results indicated from this paper. First, the methods of the research that use the relationship between financial index and stock price can obtain the credibility of the financial factor weight. Investors giving priority to the fundamental plane could see the degree of correlation as a reference, to know whether the stock investing is able to meet the expectation via estimating by financial index. Second, selecting 39 listed companies, when the financial index weight of the credibility is higher than 83%, the accuracy rate of the 39 listed companies of forecasting stock price rise and fall was 58.57% ~ 64.71%. This result provides a valuable reference of forecasting stock price variation to a certain degree.
34
Li, Yihan. "GARCH models for forecasting volatilities of three major stock indexes : using both frequentist and Bayesian approach." 2013. http://liblink.bsu.edu/uhtbin/catkey/1712468.
Full textAbstract:
Forecasting volatility with precision in financial market is very important. This paper examines the use of various forms of GARCH models for forecasting volatility. Three financial data sets from Japan (NIKKEI 225 index), the United States (Standard & Poor 500) and Germany (DAX index) are considered. A number of GARCH models, such as EGARCH, IGARCH, TGARCH, PGARCH and QGARCH models with normal distribution and student’s t distribution are used to fit the data sets and to forecast volatility. The Maximum Likelihood method and the Bayesian
approach are used to estimate the parameters in the family of the GARCH models. The results show that the QGARCH model under student’s t distribution is the precise model for the NIKKEI 225 index in terms of fitting the data and forecasting volatility. The TGARCH under the student’s t distribution fits the S&P 500 index data better while the traditional GARCH model under the same distribution performs better in forecasting volatility. The PGARCH with student’s t distribution is the precise model for the DAX index in terms of fitting the data and forecasting volatility.Department of Mathematical Sciences
35
Hsiao, Wei-Han, and 蕭為瀚. "An Empirical Analysis of the Relation between Selected U.S. and Taiwan Stock Price Indexes." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/66821396181549970017.
Full textAbstract:
碩士淡江大學
美國研究所
90
Stock markets have always played a pivotal role in the financial markets of advanced nations worldwide. The USA is Taiwan’s biggest export partner and also a key country for its overseas financial investments. Naturally, the vitality of the American economy is of central concern to the people of Taiwan. When the American stock market prospers, Taiwan’s market is positively affected. By contrast, if the American stock market experiences a serious drop, then Taiwan’s market typically falls, as well. So the two stock markets exist within the same sphere of influence whereby the performance of one (the us) inevitably impacts on that of the other (Taiwan). The study adopts the Vector Auto-regression (VAR) to examine the lead-lag relation between Selected U.S. and Taiwan Stock Price Indexes. We select eight indices including American Dow Jones Index, American S&P500 Index, Nasdaq Composite Index, Nasdaq 100 Index, Nasdaq Computer Index and Philadelphia Semiconductor Index which started from Jan 1,1995 to June 30, 2001. The main empirical results are as followed: 1. This study indicates that the rates of return of the (American Dow Jones Index, American S&P500 Index, Nasdaq Composite Index, Nasdaq 100 Index, Nasdaq Computer Index and Philadelphia Semiconductor Index) unilaterally and positively impact the Taiwan Weighted Index and Taiwan Electronic Index. 2. This study indicates that the key American stock market indices are an evident short-term leader of the Taiwan Weighted Index and Taiwan Electronic Index. 3. This study finds that the Taiwan Weighted Index and Taiwan Electronic Index react systematically to the impact from the major American stock indices, with the reverberations being the greatest in the first quarter and rapidly waning by the third period. 4. The impulse-response function tells us that such function is the greatest on the Taiwan Weighted Index due to the effect of the American Dow Jones Index, while the Philadelphia Semiconductor Index has the same influence on the Taiwan Electronic Index. Noteworthy, the major American indices have an impulse-response function on the Taiwan Classified Electronics Index that is almost twice that on the Taiwan Weighted Index. 5. The error-variance decomposition tells us that the interpretation of error-variance decomposition of the American Dow Jones Indices are the strongest regarding the Taiwan Weighted Index; while that of the Philadelphia Semiconductor Index is the same with respect to the Taiwan Electronic Index.
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Cancela, Ângela Mar isa Roldão. "Comparative Study Of Artificial Neural Network And Box-Jenkins Arima For Stock Price Indexes." Master's thesis, 2008. http://hdl.handle.net/10071/1472.
Full textAbstract:
The accuracy in forecasting financial time series, such as stock price indexes, has focused a
great deal of attention nowadays. Conventionally, the Box-Jenkins autoregressive integrated
moving average (ARIMA) models have been one of the most widely used linear models in
time series forecasting. Recent research suggests that artificial neural networks (ANN) can be
a promising alternative to the traditional ARIMA structure in forecasting.
This thesis aims to study the efficiency of ARIMA and ANN models for forecasting the value
of four Stock Price Indexes, of four different countries (Germany, Italy, Greece and Portugal),
during 2006 – 2007, using the data from preceding 15 years.
In order to reach the goal of this study, it is used the Eviews software that allows to find an
appropriate ARIMA specification, offered also a powerful evaluation, testing and forecasting
tools. In order to predict the time series is used the Matlab software, which provides a
package that allows generating a suitable ANN model.
It is found that ANN provides forecasted results closest to the actual ones when used the
logarithmic transformation. The first difference transformation is required in ARIMA but no
one founding model is satisfactory. When this transformation is also used with ANN, the
forecasted results are less satisfactory.
In fact, it wasn’t possible to compare the efficiency of ARIMA and ANN models for
forecasting the time series, due to the founding ARIMA models were not satisfactory. A
possible solution would be to reduced the input period of 15 years.Actualmente a precisão na previsão de séries financeiras, tais como Índices Accionistas, têm captado uma enorme atenção. Tradicionalmente, o modelo Box-Jenkins Autorregressivos Integrados de Médias Móveis (ARIMA) é um dos modelos lineares mais utilizados na previsão de séries temporais. Pesquisas recentes têm demonstrado que as Redes Neuronais Artificiais (RNA) podem constituir uma potencial alternativa à tradicional estrutura ARIMA, na previsão. Esta tese tem por objectivo o estudo da eficiência dos ARIMA e dos modelos de RNA na previsão de quarto índices accionistas de quatro diferentes países (Alemanha, Itália, Grécia e Portugal), desde 2006 a 2007, considerando os 15 anos antecedentes. De modo a atingir este objectivo, foram utilizados dois softwares. Para determinar uma especificação apropriada para os modelos ARIMA foi utilizado o software Eviews que dispõe, também, de ferramentas poderosas para avaliar e testar os modelos, possibilitando ainda a previsão através dos mesmos. De forma a encontrar modelos RNA apropriados, para prever as séries em estudo, foi utilizado o software Matlab. As RNA forneceram uma boa precisão na previsão das quatro séries logaritmizadas. Uma vez que os modelos ARIMA requerem estacionaridade das séries, foram utilizadas as séries das primeiras diferenças, no entanto não foi encontrado nenhum modelo que pudesse fornecer uma previsão aceitável. Considerando as séries temporais diferenciadas nas RNA, os resultados da previsão foram menos satisfatórios. De facto, não foi possível comparar a eficiência dos modelos na previsão dos índices, uma vez que os modelos ARIMA encontrados não foram satisfatórios. Uma hipótese, na tentativa de encontrar modelos satisfatórios seria reduzir o intervalo de 15 anos de input.
37
Huang, Chih-Yang, and 黃智揚. "Revisiting the Dynamic Linkage between the Stock Price Indexes of Taiwan Listed Banking Companies." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/21955176572870272392.
Full textAbstract:
碩士樹德科技大學
金融與風險管理系碩士班
99
In this dissertation we investigates the dynamic linkage between the stock price indexes of Taiwan listed banking companies under the influence of some selected exogenous variables, such as U.S. Dow Jones Industrial Index, Taiwan overnight interbank offered rate and the construction industry stock price index by Rahbek and Mosconi (1998)’s cointegration test, Granger (1969)’s causality test and Pesaran and Shin (1998)’s generalized impulse response function. Our empirical results show that: First, there is a long term equilibrium relationship between the state-owned and non-state-owned banking industry stock price indexes. Moreover, the state-owned and non-state-owned banking industry stock price indexes Granger cause each other. Finally, non-state-owned banking industry stock price index has more permanent impact on the state-owned one than the latter’s impact on the former. Most of the halflives are about one to three months, and the impacts seem to be all permanent.
38
Huang, Chun-Ying, and 黃俊穎. "An Empirical Study on the Relationships among Oil Price, Automobile Stock Index and Macroeconomic Indexes." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/08453804735409273793.
Full textAbstract:
碩士國立屏東科技大學
財務金融研究所
97
The volatility of oil price has resulted in the significant impacts on macroeconomy and industries, especially the automobile industry. This study investigates the long run equilibrium among automobile stock index, oil price, unemployment rate and CPI. The empirical results are as follows: 1.Johansen cointegration test shows that there exist long run equilibrium relations among automobile stock index, oil price, unemployment rate and CPI, which implies that the impacts of volatility of oil price on macroeconomy and automobile stock index exist. 2.From VECM model, the adjustments to long run equilibrium for automobile stock index, oil price, unemployment rate and CPI are slow. The oil price is affected by automobile stock index one period ahead; while unemployment is affected by itself one period ahead. 3.The Granger Causality shows that automobile stock index leads unemployment rate by two periods, leads oil price by one period; unemployment rate leads CPI by twelve periods, while oil price leads unemployment rate by three periods. The results imply that automobile stock index can be regarded as leading index of macroeconomy.
39
Chan, Ming-Hsueh, and 詹明學. "Revisiting the Dynamic Linkage between the Stock Price Indexes of Taiwan Listed Solar Energy Companies." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/22556638481244257022.
Full textAbstract:
碩士樹德科技大學
金融與風險管理系碩士班
101
In this dissertation we investigate the dynamic linkage between the stock price indexes of Taiwan listed solar energy companies under the influence of some selected exogenous variables, such as U.S. Dow Jones Industrial Index, crude oil price by Rahbek and Mosconi(1998)''s cointegration test, Granger(1969)''s Causality test and Pesaran and Shin(1998)''s generalized impulse response function. The sample period is from July, 2004 to June, 2008, The conclusions are as follows：First, there is a long-term equilibrium relationship between the stock price indexes for the upstream, middle-stream, and downstream in the solar energy industry. Second, from Granger Causality test we find that the stock price index of the middle-stream Granger causes up-stream and downstream. Moreover, downstream Granger causes upstream. Finally, from the generalized impulse response analysis we show that the impacts of the indexes of stock price for the upstream, middle-stream and downstream on each other are all permanent, and the half lives are about one to two months.
40
Chang, Hsin-Ho, and 張心和. "Recurrent Neural Network using Advanced Industrial Wastewater Indexes for the research of stock price prediction." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/8z5hfb.
Full textAbstract:
碩士國立中央大學
資訊管理學系在職專班
107
This research uses Deep Learning technology, LSTM Network, to solve the prediction issue of future stock price. In contrast to traditional methods, it uses industrial wastewater dataset to train LSTM model. In experiment, it is designed to different models by deferred periods of the affected stock price and finds the most accurate model for stock price prediction. Moreover, this paper designs experiments to ascertain the hypothesis, industrial wastewater of factories influencing its future stock price trend, whether they have the positive correlation. The contribution of this research proves the future stock price prediction of manufacturing industry can use the leading index, industrial wastewater, effectively. And it also finds out using industrial wastewater dataset to intensify the accuracy of LSTM network in stock price prediction is a useful way. Ultimately to produce a non-finance leading index of stock prediction, New River index, by LSTM approach that helps investors to judge investment in advance is this research contribution.
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"Nonparametric analysis of hedge ratio: the case of Nikkei Stock Average." 1998. http://library.cuhk.edu.hk/record=b5889511.
Full textAbstract:
by Lee Chi Kau.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references (leaves 115-119).
Abstract also in Chinese.
ACKNOWLEDGMENTS --- p.iii
LIST OF TABLES --- p.iv
LIST OF ILLUSTRATIONS --- p.vi
CHAPTER
Chapter ONE --- INTRODUCTION --- p.1
Chapter TWO --- THE LITERATURE REVIEW --- p.6
Parametric Models
Nonparametric Estimation Techniques
Chapter THREE --- ANALYTICAL FRAMEWORKS --- p.21
Parametric Models
Nonparametric Models
Chapter FOUR --- EMPIRICAL FINDINGS --- p.36
Data
Estimation Results
Evaluation of Model Performance
Out-of-Sample Forecast and Evaluation
Chapter FIVE --- CONCLUSION --- p.54
TABLES --- p.58
ILLUSTRATIONS --- p.76
BIBLIOGRAPHY --- p.115
42
Wu, Chiann-Chiann, and 吳茜茜. "To Investigate the Relationship between Stock Exchange Price and Exchange Rate－Taking Taiwan Stock Exchange Electronic Indexes as an Example." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/74227538519875468434.
Full textAbstract:
碩士朝陽科技大學
財務金融系碩士班
95
Taiwan itself is a shallow domestic economics and this district depends heavily upon international trade and investment flows to maintain its economic growth and standard of living. The main economic activity is engaged in international business. While involving with international economics closely, increasing link of district’s economics daily, and resulting in internationalization of Taiwan stock market rapidly, the external factors become more and more important to influence variation of Taiwan stock market. Stock market is an epitome of economic development and plays an important role. When the value of stock market is extensive, we assume economic development is growing fast. Since last few years, the government has permitted Securities Agent to apply establishment, relaxing foreign capital’s restrictions to invest domestic stock market and releasing foreign exchange control that helps the rate of domestic stock market investment going up. When foreign capital flows in or out, it brings a huge wave in the Taiwan stock market. So, Domestic and foreign investors and fund managers evaluate and conduct stock investment policy, and they try to avoid investment risk through exchange rate in foreign exchange market. Thus, the changeable waves between stock and foreign exchange market are very close. This study mainly takes Taiwan Weighted Stock Index, Taiwan Stock Exchange Electronic Indexes and Exchange Rate as an example, utilizes non-linear mode, and researches transmitting effect among Taiwan Weighted Stock Index Returns, Taiwan Stock Exchange Electronic Indexes Returns and Exchange Rate from January 1, 2001 to December 31, 2005. This research utilizes KSS, Unit Root Test to test non-linear qualitative relationship, and takes Threshold Autoregressive Model and Momentum-Threshold Autoregressive Model to process Threshold Cointegration Test. Moreover, using Threshold Error-Correction Model Test analyze long-term asymmetric relationship and transmitting effect among Taiwan Weighted Stock Index Returns, Taiwan Stock Exchange Electronic Indexes Returns and Exchange Rate Returns. The result of study is as follows: Taiwan Weighted Stock Index Returns, Taiwan Stock Exchange Electronic Indexes Returns and Exchange Rate Returns exist threshold Cointegration asymmetric relationship and this means three variations have non-linear relationship under long-term balance. In the threshold Error-Correction Model, the experimental result between three variations is roughly the same except the Taiwan Weighted Stock Index returns to Taiwan Stock Exchange Electronic Indexes Returns and Exchange rate Returns which did not have obvious influence. The strike of Taiwan Weighted Stock Index returns to Taiwan Stock Exchange Electronic Indexes Returns is negative; however, the strike of Taiwan Weighted Stock Index returns to Exchange rate Returns is positive. On the other hand, the strike of Exchange rate Returns to Taiwan Stock Exchange Electronic Indexes Returns is negative, and the strike of Exchange rate Returns to Exchange rate Returns is negative. In the long-term balance relationship, three variations deviate long-term balance, it will back to balance status automatically.
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He, Meng-Chun, and 何孟純. "The Analysis of the Relationship of Crude Oil, Shipping Companies Stock Price, Baltic Dry Index and Taiwan Accumulate Stock Indexes." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/sbcy3q.
Full textAbstract:
碩士國立虎尾科技大學
財務金融系碩士班
104
Taiwan is an export-oriented country, However, most of the crude oil can only rely on imports. Rising crude oil prices will increase production costs, the stock market and economic have a significant impact. This research period from the first day of 2006 through the end of 2015.The data used in the analysis include information on the Brant crude oil price, Listed shipping company stock price, Baltic Dry Index and Taiwan Accumulate Stock Indexes. This paper adopts some of path-analysis, mediator, unit root test, ARMA, ARCH and GARCH to study for the analysis of the relationship between crude oil and Listed shipping company stock price, Baltic Dry Index and Taiwan Accumulate Stock Indexes. The empirical results show that in Taiwan stock index as the mediated variables, Due to the estimated parameter reduction is that, in the shipping company''s share price is according to the variables and Baltic Dry Index and Taiwan Stock Index as the independent variable has a partial mediation effect. From the path analysis, it can be found that the direct effect of crude oil on the shipping company''s stock price is the cost side, The Taiwan stock index is the index to predict the economy, So it is between the mediated variables affect for the economy, The results show the WANHAI and crude oil negatively correlated. EVER, U-MING, YANG MING,WAN HAI and SINCERE impact of the cost side is greater than the economy. Baltic Dry Index and EVER, U-MING, YANG MING, WAN HAI positive correlated but the WANHAI and Baltic Dry Index negatively correlated. Using the construction of ARMA model to estimate the lag period of the mode, And using the least AIC value to select the most appropriate model, Due to the selection of the ARMA model, the H0 hypothesis is rejected, so existedheterogeneity variation and the ARCH(1) model received H0hypothesisthen no autocorrelation and heterogeneity variation, along with U-MING and SINCERE. But UMING and SINCERE continuously employ the GARCH model. Finally, UMING and SINCERE use AIC to select the appropriate model of the GARCH, which are GARCH(1.2) and GARCH(2.2).
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Chang, Yi-Ling, and 張倚綾. "An Analysis of the Correlation between the Macroeconomic Variables， Foreign and Domestic Stock Price Indexes and the Electronics Stock Prices." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/a96w27.
Full textAbstract:
碩士國立臺中科技大學
企業管理系碩士班
104
This research aims at discussing the correlation between the macroeconomic variables，fundamental factors，foreign and domestic stock price indexes and the electronics stock prices. It studies the monthly average stock prices from July 1，2005 to June 30，2015; each variable has 120 monthly data， which are mainly from Taiwan Economic Journal (TEJ). It conducts the empirical analysis using ADF unit root test，Johansen co-integration test，vector auto-regression model，Granger causality test， the impulse response test and the vector error correction model. Empirical results show： I. It can be known from the impulse response function that the secondary market interest rate of the commercial paper，interbank call loan rate and one-year fixed-term deposit interest rate have lasting and positive effects on the electronics stock prices; Taiwan’s coincident index and unemployment rate have lasting and negative effects on the electronics stock prices. II. It can be known from the variance decomposition result that the top 3 variables that can explain the electronics stock prices are weighted index，PHLX semiconductor index and Standard & Poor’s 500 Index in sequence. III. It can be known from VECM Model Verification that when the unemployment rate and the electronics stock prices breaks away from the long term equilibrium relationship，the adjustment is made mainly through the unemployment rate. When foreign deal value proportion and the electronics stock prices breaks away from the long term equilibrium relationship，the adjustment is made mainly through the foreign deal value proportion.
45
"Index-linked certificates of deposit: facts & fate." Chinese University of Hong Kong, 1988. http://library.cuhk.edu.hk/record=b5887175.
Full text
46
Li, Chun-Yi, and 李俊易. "Revisiting the Dynamic Linkage in the Stock Price Indexes ofTaiwan Listed Corporations in the Textile Industry." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/13222275259540998563.
Full textAbstract:
碩士樹德科技大學
金融與風險管理系碩士班
99
This research uses the statistical methods proposed by Rahbek and Mosconi(1998) and Granger(1969) and Pesaran and Shin(1998) is to investigate the dynamic linkage between stock price indexes of the upstream, middle-stream, and downstream of Taiwan listed companies in the textile industry under the exogenous variables such as exchange rate, oil prices and cotton prices and Dow Jones Industrial Index. The sample period is as from July, 2004 to June, 2008, The conclusions are follows：First, there is a long-term in equilibrium relationship between the stock price of indexes the upstream, middle-stream, and downstream in the textile industry. Second, from Granger Causality test we that the stock price indexes of the upstream and middle-stream Granger cause each. Moreover, the stock price index of the downstream Granger cause those of the upstream and middle-stream. Finally, from the generalized impulse response analysis we show that the impacts of the stock price indexes of the upstream, middle-stream and downstream on each other are all permanent, and the half lifes are about two to three months.
47
Allison, Dylan Mayne. "Adopting price-earnings and enterprise multiples to beat the Johannesburg Stock Exchange All Share Index." Thesis, 2009. http://hdl.handle.net/10413/6170.
Full textAbstract:
The theory behind the efficient market hypothesis exerts that it is not possible to consistently outperform
the overall stock market by using stock picking and market timing strategies. The argument holds
that, in an efficient market, all stock prices are appropriately priced and there is no over- or undervalued
stocks to be found. Nevertheless, deviations from true stock prices can occur according to the hypothesis,
although these deviations are mostly random occurrences. Thus, the only way an investor can
outperform the overall stock market is by luck alone. However, the efficient market hypothesis is a
controversial topic where it is often discussed within modern financial circles where academic theory
has strong arguments both for and against the theory.
Purpose:
The purpose of this study is to investigate whether it is feasible to outperform the overall stock market
through investing in stocks that appear undervalued according to enterprise multiple (EV/EBITDA)
and the price-earnings ratio.Thesis (MBA)-University of KwaZulu-Natal, Westville, 2009.
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"Market effects of changes in the composition of the Hang Seng Index." 1998. http://library.cuhk.edu.hk/record=b5889419.
Full textAbstract:
by Chiu Mei-Yee, Pamela, Pong Kwok-Hung, Patrick.Thesis (M.B.A.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references (leaf 52).
ABSTRACT --- p.ii
TABLE OF CONTENT --- p.iii
LIST OF ILLUSTRATIONS --- p.iv
LIST OF TABLES --- p.v
ACKNOWLEGEMENTS --- p.vi
Chapter
Chapter I. --- INTRODUCTION --- p.1
Chapter II. --- OBJECTIVES --- p.3
Chapter III. --- LITERATURE REVIEW --- p.4
Chapter IV. --- THE SAMPLE --- p.9
Chapter V. --- METHODOLOGY --- p.14
The Market Model --- p.15
Methods to Estimate the Excess Returns --- p.16
Chapter VI. --- RESULTS AND ANALYSIS --- p.19
Price Effects on Inclusion in HSI --- p.19
Price Effects on Exclusion from HSI --- p.33
Comparison between Inclusion and Exclusion --- p.41
Chapter VII. --- IMPLICATIONS --- p.42
Chapter VIII. --- CONCLUSION --- p.45
APPENDIX --- p.47
BIBLIOGRAPHY --- p.52
49
Xiang, Dong. "Efficiency of Australian banks: its determinants and stock price relevance." Thesis, 2011. http://hdl.handle.net/1959.13/928001.
Full textAbstract:
Research Doctorate - Doctor of Philosophy (PhD)The aim of this thesis is to conduct a thorough analysis of the performance of Australian banks over a long period of time, covering a period of various regulatory measures. To achieve this aim, the following four objectives are set in this thesis: first, to investigate economic efficiency (i.e. cost and profit efficiency) of the Australian banks before and after the implementation of the prudential regulation; second, to examine whether the Australian banks operate at the minimum efficient scale; third, to assess whether the efficiencies achieved contribute to wealth maximization of shareholders; fourth, to examine the determinants of Australian bank efficiency. Using a data set covering a period from 1985 through 2008, I first apply the stochastic frontier analysis (SFA) to examine the technical, cost and profit efficiency of Australian banks. A standard data envelopment analysis (DEA), as well as a slack-based DEA model (Tone 2001), is then used to assess the technical and scale efficiency of Australian banks. In addition, a Malmquist index model is used to investigate bank productivity changes over the sample period. The relationship between bank efficiency and bank stock returns is also examined using the market model. Lastly, a mixed two-step approach is used to examine efficiency and the determinants of efficiency using panel data from 1988 to 2008 across three countries, namely, Australia, Canada and the U.K.. In the first stage, a common efficiency frontier for banks in three countries is constructed including the environmental factors. The firm-level determinants of efficiency are then investigated by regressing these efficiencies on firm-specific factors. A key finding of this thesis is that, over the period from 1985 through 2008, the technical, cost and profit efficiency of Australian banks improved. However, scale efficiency showed a declining trend, which was mainly due to the scale inefficiency of the big-four banks over the sample period. Australian banks have a high level of cost and profit efficiency, but have a relatively low level of technical efficiency. Technological improvement is found to be the major driving force behind productivity changes of Australian banks, and also has a positive effect on the profit efficiency frontier. It is also observed that technical, cost and profit efficiency have a positive effect on bank stock returns, suggesting that bank efficiency is properly recognized by market participants. Compared to their regional counterparts, the big-four banks have a lower level of technical efficiency, but a higher level of cost efficiency. The low level of technical efficiency of the big-four banks is attributed to scale inefficiency. In comparison, the regional banks can achieve the same level of profit efficiency as that of the big-four banks by devising a better way of transforming inputs into outputs. Australian banks show a superior performance in terms of technical, cost and profit efficiency compared with that of Canadian and U.K. banks. The factors such as intangible assets, loans to deposits ratio and, loans to assets ratio exert a positive influence on technical efficiency. On the other hand, technical efficiency is inversely affected by size, ratio of loan loss provisions to total loans and debt to equity ratio. The findings of this thesis appear to provide justifications for the deregulatory measures and the prudential regulation framework introduced by the Australian regulatory bodies. Australian banks with increased efficiency levels and relatively high capital adequacy ratios demonstrated resilience to external shocks, such as the Asian financial crisis and the subprime mortgage crisis. An investigation of the determinants of bank efficiency suggests that an Australian bank manager has the choice of tuning up either the capital structure or the asset structure to improve efficiency. However, these findings should be interpreted with caution due to the limitations relating to data unavailability and efficiency evaluation techniques.
50
YANG, HSIU-YA, and 楊琇雅. "Taiwan stock indexes、North Sea Brent Crudev’s oil price and World Energy to the stock index returns of Taiwan LED industry." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/v4j33y.
Full textAbstract:
碩士國立中正大學
財務金融學系碩士在職專班
104
This study discusses the impact of Taiwan stock indexes、North Sea Brent Crudev’s oil price and World Energy to the stock index returns of Taiwan LED industry.The information contained within the data applies to the period of January 1,2006 to December 31,2013.For data measurement and results,an empirical analysis method including unit root tests,cointegration tests VECM,impulse response,variancedecomposition,and granger causality tests,was used. The study showed that Taiwan stock indexes、World Energy、North Sea Brent Crudev’s oil price and the stock index returns of Taiwan LED industry appear to be stationary after the first difference in unit root test. Cointegration Test reveals thatTaiwan stock indexes、World Energy、North Sea Brent Crudev’s oil price and the stock index returns of Taiwan LED industry have two cointegrated vector，which indicates the existence of a long-running equilibrium.In the VECM，Impact of oil prices on the World Energy and Taiwan stock indexes is more significant。By way of impulse response, Taiwan stock indexes affected by oil prices,World Energy and the stock index returns of Taiwan LED industry impulse reaction.The stock index returns of Taiwan LED industry affected by World Energy impulse reaction.World Energy affected by oil prices impulse reaction.Finally, a granger causality test showed that only the stock index returns of Taiwan LED industry leads Taiwan stock indexes,it exists feedback relationship between World Energy and Taiwan stock indexes and oil prices.