The role of qualitative data and systems thinking in addressing service decline in market towns

Retail services are a main contributor to municipal budget and are an activity that affects perceived quality-of-life, especially for those with mobility difficulties (e.g. the elderly, low income citizens). However, there is evidence of a decline in some of the services market towns provide to their citizens. In market towns, this decline has been reported all over the western world, from North America to Australia. The aim of this research was to understand retail decline and enlighten on some ways of addressing this decline, using a case study, Thornbury, a small town in the Southwest of England. Data collected came from two participatory approaches: photo-surveys and multicriteria mapping. The interpretation of data came from using participants as analysts, but also, using systems thinking (systems diagramming and social trap theory) for theory building. This research moves away from mainstream economic and town planning perspectives by making use of different methods and concepts used in anthropology and visual sociology (photo-surveys), decision-making and ecological economics (multicriteria mapping and social trap theory). In sum, this research has experimented with different methods, out of their context, to analyse retail decline in a small town. This research developed a conceptual model for retail decline and identified the existence of conflicting goals and interests and their implications for retail decline, as well as causes for these. Most of the potential causes have had little attention in the literature. This research also identified that some of the measures commonly used for dealing with retail decline may be contributing to the causes of retail decline itself. Additionally, this research reviewed some of the measures that can be used to deal with retail decline, implications for policy-making and reflected on the use of the data collection and analysis methods in the context of small to medium towns.

Felmini, the success of a Portuguese footwear company in the Italian market

NSBE - UNL

Internationalization of UniPlaces to the Spanish market: Internationalization plan to Madrid, Spain

Field Lab in Entrepreneurial Innovative Ventures

Are the L'oreal hair care brands currently operating in the Kenyan mass market adequately positioned and adapted to the Kenyan consumers?: A recommendation to the new L'oreal East Africa Office concerning the hair care brand positioning and portfolio in Kenya

NSBE - UNL

A marketing plan for Companhia das Quintas to strengthen its position in the Chinese wine market

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.

Indoor location-based analytics systems: Portuguese market compettive assessment and entry procing strategy of BIPs' technology in Sonae Sierra Shopping malls stores

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.

Buy, sell and chatter: A case analysis of a Lisbon flea market

This thesis aims explore the sociocultural as well as economic significance of the modern-day flea market, as a form of alternative marketplace system. More specifically, the main goal of the research is to determine the motivation for participation in flea markets of different participants, from vendors to consumers, using an interactionist perspective. By studying these groups in details, I seek to explore the embeddedness of social aspects in economic activity and vice versa. The basic assumption is to put aside the previous notions of the flea market as a second-order system with implied inferiority, and to explore the potential of the flea market to both challenge and complement more formal marketplace systems, by comparing and contrasting the flea market with market venues that belong to the formal sector. Feira da Ladra in Lisbon, Portugal, the oldest a hugely successful flea market in Europe, was chosen to be the research site, where its economic participants were studied in details in various exchanges, using naturalistic observations, semi-structured interviews and a sociocultural perspective.

Predictability of stock market returns: Evidence from Eurozone's banking sectors

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.

A method to correct the flow distortion of offshore wind data using CFD simulation and experimental wind tunnel tests

The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

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.

Market risk charge of the trading book: a comparison of the Basel II and Basel III

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.

Evidence of market anomalies in the Eurozone: A practical implementation

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

Modeling and forecasting value-at-risk for the Portuguese stock market

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.

Predicting market direction with hidden Markov models

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.