In this study, for elimination the bias of accounting traditional policy resulted, I use economic value added (EVA) to analyze the performance of Taiwan semiconductor industry. Its findings are as follows: 1.Taiwan semiconductor industry's operating performance is vloatile, the standard deviation of EVA-Spread is more than 14% for years, inter-firm difference in performance is becoming increasingly, and less of 50% of companies is worth to invest. 2.The reason of EVA-Spread performance influence as WACC, mainly be influenced by bank interest rates and industry capital structure changes. And the factors affect ROIC, including the global demand for semiconductor and the real GDP growth rate of Taiwan, Hong Kong, Japan and Singapore, but not related with China¡¦s real GDP growth rate. 3.In Sub-industries, IC design industry is the best performance and steady, but there is obviously different in inter-firm; semiconductor equipment industry has the worst performance and negative EVA-Spread in recent 7-years. IC manufacturing without DRAM has nice performce in recent 5 years and more and more stable. In the orher hand, DRAM industry has performed poorly. That means that corporations have obvious effect on performance in various sub-industries. 4.Focus on the stability of sub-industries performance, the IC design industry has minimum volatility, secondary is lead-frame, photomask and IC packaging and testing industries. And the maximum volatility is DRAM industry and then is DRAM module and semiconductor equipment industry. On the growth, IC packaging and testing, wafer material, manufacturing without DRAM and substrate industries are steady growing industries. Although lead-frame industry is a kind of slow-growing industry, but its EVA-Spreads are minus. Other, flash module and photomask industries are declining industries. 5.Focus on the investing behavior and value creation capcity, when IC packaging and testing, substrate, wafer material and photomask industries increasing their capital, would be helpful to increase EVA-Spread; and it would not be helpful on semiconductor equipment, flash module and IC design industries. 6.It is related with the sub-industries of IC design, substrate, packaging and testing, wafer material, discrete devices, DRAM and flash industries, and IC manufacturing industry without DRAM. It implied that these 7 sub-industries affected by the semiconductor business. It is not related with the sub-industries of semiconductor equipment, DRAM module, lead-frame, photomask and other industries, and the IC manufacturing without DRAM. It implied that these 5 Sub-industries deeply affected by other factors.

Economic Value Added ¡]EVA¡^to be a business performace indicator popularly. It surveys business¡¦ ability of value creation through tranditional accounting net income and capital opportunity cost. In this study, I focus on IC Design industries¡¦ performance by EVA and use ten years data to examine it. The study purposes as below, A. Does Taiwan IC Design Industry owns ability of value creation for share owners ? B. Find out the factors of Taiwan IC Design Industry¡¦s performance. C. Comment on Taiwan IC Design Industry¡¦s performance in various sub-industries D. Does Taiwan IC Design Industry exist variation in various sub-industries ? E. Find out which sub-industry owns the best efficiency and the lowest volatility in the meanwhile. F. Find out the factors of Taiwan IC Design Industry¡¦s ability of value creation. The study finding as below, A. The standard deviation and quartile deviation of Taiwan IC Design Industry are uniformity and it is implying that the normal distribution and probability distribution are similar. B. About 80% of EVA-Spread of Taiwan IC Design companies are positive, it implies that the ability of value creation of Taiwan IC Design Industry is very well. C. According to evidence-based data, the WACC of Taiwan IC Design Industry is influenced by the cost of equity capital. D. The ROIC of Taiwan IC Design Industry is influenced by Taiwan Semi-conductor Inductry¡¦s ROIC and the real GDP growth rate of Hongkong, China and South Korea. E. The capital turnover of Taiwan IC Design Industry does not link with the ROIC of Taiwan IC Design Industry. F. According to evidence-based data, the variation is exist between Taiwan IC Design Sub-industries. G. The result of regression analysis that past years Invested Capital Growth Rate of sub-industries to be independent variable and EVA-Spreads to be dependent variable implys that the EVA-Spread of Taiwan IC Design Industry is not effected by Invested Capital Growth Rate, then we know that Invested Capital is not the main factor of value creation of Taiwan IC Design Industry. H. The Capital Turnover Rate and the Return Rate of EBIT is the main factors of ROIC, they effected the sub-industries by different levels.

Jämfört med andra branscher har fastighetsmarknaden låg avkastning på totala tillgångar, de utnyttjar istället en hävstångsstrategi för att skapa mer effektiv utväxling på eget kapital. Det finns många riskvariabler kopplat till fastighetsbranschen och flera sätt att differentiera sig från den osystematiska risken. De kommunala fastighetsbolagen har en finansieringskälla Kommuninvest, som enbart vänder sig till allmännyttiga bolag och inte privata aktörer. Syftet med uppsatsen är att historiskt analysera hur risk och avkastning genererats av kommunala och privata fastighetsbolag. Metoden är kvantitativ, kombinerat med en deduktiv metod och som har en förklarande ansats. Utifrån teori har vi formulerat tre hypoteser för att undersöka om vi kan finna indikatorer på hur kommunala och privata fastighetsbolag skiljer sig till från varandra. För att genomföra undersökningen har uppsatsen utgått från en kvantitativ metod och statistiska test har gjorts för att kunna analysera utfallen. Resultaten indikerar på att det finns en signifikant skillnad mellan kommunala och privata fastighetsbolag i två av hypoteserna. Hur undersökningen är genomförd beskrivs i den empiriska metoden. Från de resultat som blivit har det fastställts att det finns mer att undersöka och nya förslag på fortsatt forskning har utformats. / Compared to other industries, real estate markets have historically low return on total assets, instead they use a leverage strategy to create a more efficient ratio on return on equity. There are many risk variables associated with real estate and several ways for real estate firms to differentiate themselves from the unsystematic risk. The municipal property firms have a funding source Kommuninvest, only turning to public utilities and not private actors. The purpose of this paper is to analyze the historical risk and return generated by municipal and private property firms. The method is quantitative, combined with a deductive theory, which has an explanatory approach. Based on theory we have formulated three hypotheses to explore and see if we can find indicators of how differences between municipal and private property is. To conduct the survey, the thesis has a quantitative method and statistical tests to analyze the outcomes. The results indicate that there is a significant difference in two of the hypotheses between municipal and private property. How the survey is conducted is described in the empirical method. From the results determined, the intention shows that there is more to explore, and new suggestions for further research have been suggested.

Background: Light has been shed on the textile industry as one of the leading industries when it comes to economic growth, global warming and sustainable development. The increasing demand for sustainable activities from stakeholders has led to the importance of measuring the sustainable development of companies. ESG reporting is a common tool used to indicate a company’s sustainability performance. Prior research has tended to focus on cross-sectional industries, and therefore a gap was identified for industry specific research.   Purpose: The purpose of this research is to explain the relationship between sustainability performance and financial performance in the textile industry in the European and North American markets to see if companies that invest in sustainability activities benefit financially.   Method: This research has followed a positivistic paradigm, with deductive reasoning and a quantitative approach. A probability sampling approach was performed by conducting secondary data from Thomson Reuters DataStream of companies in the textile industry in Europe and North America. This resulted in a final sample of ESG scores and ROIC of 44 companies. The data was later analysed in the SPSS software program by following the estimation method Ordinary Least Squares (OLS).    Findings: The literature review developed two hypotheses to address the research purpose and questions. The two hypotheses were analysed through two regression analyses that were satisfied through the OLS estimation method. The result showed that there was a significant relationship between the aggregated ESG score and ROIC which supported the first hypothesis. The second hypothesis of the multiple regression model showed that each component of ESG is correlated to ROIC, however, the environmental factor was not statistically significantly related.    Conclusion: The thesis showed that there is a positive relationship between ESG performance and ROIC in this study. This implies that companies that invest in sustainable development increase their financial performance. The aggregated ESG score as well as the social factor and the governance factor had the highest impact on ROIC, which is supported by the stakeholder theory as there has been an increasing demand on social and governance activities in the textile industry. This further supports that sustainability performance impact on financial performance is industry specific.

本研究以1992年至2017年計19,710筆台灣上市櫃公司為樣本，探討以企業乘數與資本報酬率為指標形成投資組合的績效表現與可行性。研究發現單純以低企業乘數指標組成的投資組合表現最佳，且能長期打敗大盤；以低企業乘數與高資本報酬率的綜合指標形成的投資組合表現次佳；而單純以高資本報酬率為指標形成的投資組合表現最差，且長期劣於大盤表現。研究結果亦包括企業乘數投資組合可以創造出顯著的超額報酬（Alpha），且其優異的表現可以歸因於投資人對於企業的未來盈餘表現預期錯誤，造成市場暫時出現錯誤定價的現象。 / We employ Taiwan’s listed companies from 1992 to 2017 as a sample to examine the performance and feasibility of forming a portfolio based on enterprise multiple and return on invested capital. We find that the portfolio which consists solely of low enterprise multiple stocks outperform the market in the long run; the portfolio formed by composite indicators of low enterprise multiple and high return on invested capital beats the market as well; while the pure high return on invested capital portfolio underperforms. We also find that the low-minus-high enterprise multiple portfolio generates Fama-French alpha, and its excellent performance can be attributed to investors' expectation errors of the company's future earnings performance, resulting in temporary market mispricing.

Submitted by Catarino Lacerda e Silva (catarinolacerda@gmail.com) on 2018-09-18T12:35:32Z No. of bitstreams: 1 Dissertação - Catarino Lacerda e Silva - ESTRATÉGIAS DE INVESTIMENTOS EM AÇÕES .pdf: 1217319 bytes, checksum: 472a152e89a76ba49bfdb192b147d76f (MD5) / Rejected by Thais Oliveira (thais.oliveira@fgv.br), reason: Boa tarde, Catarino, Para que possamos aprovar sua Dissertação, serão necessárias as seguintes alterações: - A numeração de páginas começa na capa, porém deve aparecer A PARTIR da "Introdução" (pág 12) - A Ficha catalográfica deve conter o "texto" que existe fora do quadro, exatamente como foi enviado. Por gentileza, alterar e submeter novamente. Obrigada. on 2018-09-18T21:10:24Z (GMT) / Submitted by Catarino Lacerda e Silva (catarinolacerda@gmail.com) on 2018-09-19T10:54:33Z No. of bitstreams: 1 Dissertação - Catarino Lacerda e Silva - ESTRATÉGIAS DE INVESTIMENTOS EM AÇÕES .pdf: 1219830 bytes, checksum: a2aa93b6d34310ed33ec91af8f364412 (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2018-09-19T14:33:48Z (GMT) No. of bitstreams: 1 Dissertação - Catarino Lacerda e Silva - ESTRATÉGIAS DE INVESTIMENTOS EM AÇÕES .pdf: 1219830 bytes, checksum: a2aa93b6d34310ed33ec91af8f364412 (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-09-19T17:39:21Z (GMT) No. of bitstreams: 1 Dissertação - Catarino Lacerda e Silva - ESTRATÉGIAS DE INVESTIMENTOS EM AÇÕES .pdf: 1219830 bytes, checksum: a2aa93b6d34310ed33ec91af8f364412 (MD5) / Made available in DSpace on 2018-09-19T17:39:21Z (GMT). No. of bitstreams: 1 Dissertação - Catarino Lacerda e Silva - ESTRATÉGIAS DE INVESTIMENTOS EM AÇÕES .pdf: 1219830 bytes, checksum: a2aa93b6d34310ed33ec91af8f364412 (MD5) Previous issue date: 2018-09-27 / O objetivo deste trabalho é examinar quais indicadores levaram a retornos excedentes no mercado brasileiro durante o período de 31 de março de 2000 a 31 de março de 2018, através das carteiras de ações construídas anualmente com base em um indicador ou dois indicadores quantitativos. Sendo os fatores testados: Retorno sobre Capital Investido (ROIC), Retorno sobre Ativos (ROA), Earnings Yield, Preço sobre Valor Patrimonial (PVPA), Preço sobre Vendas (PSR) e Índice de Força Relativa 120 dias úteis. Nas estratégias de um fator, o primeiro quartil do indicador Earnings Yield mostrou ser o melhor para seleção de ações no período, com maior índice de Sharpe 0,571, com maior média dos retornos anuais 41,03%, maior alfa 27,82%, superando Ibovespa 88,89% do tempo e com maior discrepância entre os retornos dos quartis, tanto que o pior resultado foi 4º quartil do Earnings Yield. Nas estratégias de dois fatores, a combinação dos indicadores de valor PSR e Earnings Yield, P/VPA e Earnings Yield obteve os maiores retornos médios anuais 42,51% e 39,1%, maiores alfas 29,40% e 26,19%, superando o Ibovespa em 88,89% e 83,33% do tempo, respectivamente. Porém foram as estratégias que combinaram um indicador de valor com um indicador de retorno, ROIC e Earnings Yield, ROA e Earnings Yield, que apresentaram os maiores índices de sharpe 0,623 e 0,619, respectivamente. / The objective of this study is examine which indicators led to excess returns in the Brazilian market during the period from March 31 2000 to March 31 2018, through stock portfolios constructed annually based on one indicator or two quantitative indicators. The following factors were test: Return on invested capital (ROIC), Return on Assets (ROA), Earnings Yield, Price-to-book (PVPA), Price Sales Ratio (PSR) and Relative Strength Index 120. In the one-factor strategies, the first quartile of the Earnings Yield indicator was the best for stock selection in the period, with highest Sharpe ratio 0.571, with the highest average annual returns 41.03%, the highest alpha 27.82% outperformed the Ibovespa 88.89% of the time and with greater discrepancy among quartile returns, so much that the worse result was fourth quartile of the Earnings Yield. In the two-factor strategies, the combination of the PSR and Earnings Yield, P/VPA and Earnings Yield value indicators obtained the highest average annual returns of 42.51% and 39.1%, higher alpha 29.40% and 26.19%, outperformed the Ibovespa in 88.89% and 83.33% of the time, respectively. However, it was the strategies that combined a value indicator with a return indicator, ROIC and Earnings Yield, ROA and Earnings Yield, which had the highest Sharpe ratio of 0.623 and 0.619, respectively.