177 resultados para Market Potential


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Field Lab in Entrepreneurial Innovative Ventures

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Currently, China has the biggest automobile industry in the world. China’s economic situation helped the automobile market, as the internal demand of passenger cars increased substantially in the last years. Chinese automobile industry’s astonishing expansion over the past years has attracted many foreign automobile groups. SEAT decided to enter the Chinese market, following its expansion strategy to enter new markets. The purpose of this study is to analyse and understand the strategic entry of SEAT in the Chinese market, hence the choice of an explanatory case study (Yin, 2003). This study extends this analysis by examining the chines automobile market, more specifically the demand, the market segmentation and the intensity of competition, reviewing the SEAT company history, their competitive positioning and resources. I conclude that, although the Chinese market has growing potential, SEAT has failed to achieve its initial objective. The company has not been able to create a brand awareness in the Chinese market, unlike other foreign brands that have managed to accomplish that. This occurred, mostly, because of the high prices in comparison to its competitors due to additional import cost, such as import duties, transportation and distribution.

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Companhia das Quintas, Limited Company wishes to conquer the Chinese market with its wines. For that, it decided to enter in a partnership with a local importer and distributor. This project analyses the macroeconomic factors of the country, the local market and the consumer behavior, using on-site research that included interviews with professionals of the industry, unstructured observation of the consumer and existing statistical data analysis. Finally, the project presents a marketing plan to make this partnership a success.

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This project attempts to provide an in-depth competitive assessment of the Portuguese indoor location-based analytics market, and to elaborate an entry-pricing strategy for Business Intelligence Positioning System (BIPS) implementation in Portuguese shopping centre stores. The role of industry forces and company’s organizational resources platform to sustain company’s competitive advantage was explored. A customer value-based pricing approach was adopted to assess BIPS value to retailers and maximize Sonae Sierra profitability. The exploratory quantitative research found that there is a market opportunity to explore every store area types with tailored proposals, and to set higher-than-tested membership fees to allow a rapid ROI, concluding there are propitious conditions for Sierra to succeed in BIPS store’s business model in Portugal.

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Following the European Commission’s 2009 Recommendation on the Regulatory Treatment of Fixed and Mobile Termination Rates in the EU, the Portuguese regulatory authority (ANACOM) decided to reduce termination prices in mobile networks to their long-run incremental cost (LRIC). Nevertheless, no serious quantitative assessment of the potential effects of this decision was carried out. In this paper, we adapt and calibrate the Harbord and Hoernig (2014) model of the UK mobile telephony market to the Portuguese reality, and simulate the likely impact on consumer surplus, profits and welfare of four different regulatory approaches: pure LRIC, reciprocal termination charges with fixed networks, “bill & keep”, and asymmetric termination rates. Our results show that reducing MTRs does increase social welfare, profits and consumer surplus in the fixed market, but mobile subscribers are seriously harmed by this decision.

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Unilever Jerónimo Martins is a Portuguese joint-venture leading firm in what concerns the supply chain industry of fast-moving consumer goods in Portugal. The scope of analysis of this Work Project is focusing on Unilever-JM operations and services in the Portuguese market regarding quality, efficiency and effectiveness over B2B customers. It will be analysed the possibility of development and implementation of a performance measurement system, Tableau de Bord, which will be crucial for the identification of potential opportunities of improvement with impact in the supply chain processes. This will be completed through the establishment of KPI’s to monitor and manage periodically logistics, planning and customer service processes’ performance, which are the ones where the bottlenecks are impacting more in the supply chain. In this work project the nexus causality for the problems will also be discussed and some recommendations will be prepared to tackle the inefficiencies found through the monitoring of the previous core processes, in order to improve efficacy and quality service of the supply chain.

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This paper analyzes the in-, and out-of sample, predictability of the stock market returns from Eurozone’s banking sectors, arising from bank-specific ratios and macroeconomic variables, using panel estimation techniques. In order to do that, I set an unbalanced panel of 116 banks returns, from April, 1991, to March, 2013, to constitute equal-weighted country-sorted portfolios representative of the Austrian, Belgian, Finish, French, German, Greek, Irish, Italian, Portuguese and Spanish banking sectors. I find that both earnings per share (EPS) and the ratio of total loans to total assets have in-sample predictive power over the portfolios’ monthly returns whereas, regarding the cross-section of annual returns, only EPS retain significant explanatory power. Nevertheless, the sign associated with the impact of EPS is contrarian to the results of past literature. When looking at inter-yearly horizon returns, I document in-sample predictive power arising from the ratios of provisions to net interest income, and non-interest income to net income. Regarding the out-of-sample performance of the proposed models, I find that these would only beat the portfolios’ historical mean on the month following the disclosure of year-end financial statements. Still, the evidence found is not statistically significant. Finally, in a last attempt to find significant evidence of predictability of monthly and annual returns, I use Fama and French 3-Factor and Carhart models to describe the cross-section of returns. Although in-sample the factors can significantly track Eurozone’s banking sectors’ stock market returns, they do not beat the portfolios’ historical mean when forecasting returns.

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In this paper we investigate what drives the prices of Portuguese contemporary art at auction and explore the potential of art as an asset. Based on a hedonic prices model we construct an Art Price Index as a proxy for the Portuguese contemporary art market over the period of 1994 to 2014. A performance analysis suggests that art underperforms the S&P500 but overperforms the Portuguese stock market and American Government bonds. However, It does it at the cost of higher risk. Results also show that art as low correlation with financial markets, evidencing some potential in risk mitigation when added to traditional equity portfolios.

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With this dissertation we aim to analyze the most relevant aspects of the excise duties harmonized regime, considering Community origins, but having also in attention all legal specifications of its implementation in Portugal. The legal regime of excise duties is presented as an ambitious theme, considering the challenge of different branches of law that influence this subject, such as Tax, Economic and Community laws, the inescapable influence of customs procedures, or regarding environmental objectives. In the European context, the harmonization of excise duties was seen as a condition for the implementation of the internal market, contributing to undo secular tax barriers between Member States and, since so, ensure fair competition and free movement of services and goods. Along with VAT, the excise duties harmonization process could represent a potential European tax system, essential for a full and integrated single market. In this context, it is essential to pay special attention to specific characteristics of excise duties regime, such as ‘duty suspension arrangement’ applicable during the production phase, storage and movement in certain conditions. The growing importance of excise duties, as for revenue or extra-fiscal purposes, recommends new academic studies on this subject, seeking new opportunities and challenges.

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Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

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This paper aims to investigate if the market capital charge of the trading book increased in Basel III compared to Basel II. I showed that the capital charge rises by 232% and 182% under the standardized and internal model, respectively. The varying liquidity horizons, the calibration to a stress period, the introduction of credit spread risk, the restrictions on correlations across risk categories and the incremental default charge boost Basel III requirements. Nevertheless, the impact of Expected shortfall at 97.5% is low and long term shocks decrease the charge. The standardized approach presents advantages and disadvantages relative to internal models.

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A Work Project, presented as part of the requirements for the Award of a Master’s Double Degree in Finance and Financial Economics from NOVA – School of Business and Economics and Maastricht University

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The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.

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This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.