The social stock exchange: A quantitative exploration

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

The fitting of the German yield curve: A dynamic approach using latent, macroeconomic and stock market variables

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Bank capital and stock performance around the subprime lending risis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Business model analysis of Mobitto: How to solve the chicken and egg problem of a multi-sided platform?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Experimentation with accumulation

We study signal-dependent experimentation in the presence of accumulation and show that the passive-learner’s action surprisingly coincides with the experimentor’s when the unknown term is the one determining the decay rate of the stock, while they differ when the parameter being learned is the one measuring the accumulation rate. These results highlight the importance of the dynamic structure of the problem in signal-dependent experimentation. Moreover, they have important consequences for the pollution-accumulation debate currently in progress.

Exploring the predictive power of Google searches over the US stock market

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Three essays on economics of predictability of stock returns

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

Flexible multivariate GARCH modeling with an application to international stock markets

This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the nev^ estimator with a number of existing ones.

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.

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.

Financial depth, stock markets and economic growth in the EU-15 countries

The aim of this paper is to assess the impact of financial depth on economic growth in the EU-15 countries from 1970 until 2012, using the two-step System GMM estimator. Even though it might be expected a positive impact, the results show it is negative and sometimes even negative and statistically significant. Among the reasons presented for this, the existence of banking crises seems to better explain these results. In tranquil periods, financial deepening appears to have a positive impact, whereas in banking crises it is persistently negative and statistically significant. Also, after an assessment of the impact of stock markets on economic growth, it appears that more developed countries in the EU-15 have an economy more reliant on this segment of the financial system rather than in bank intermediation.

The accuracy of the escrowed dividend model on the value of European options on a stock paying discrete dividend

This project characterizes the accuracy of the escrowed dividend model on the value of European options on a stock paying discrete dividend. A description of the escrowed dividend model is provided, and a comparison between this model and the benchmark model is realized. It is concluded that options on stocks with either low volatility, low dividend yield, low ex-dividend to maturity ratio or that are deep in or out of the money are reasonably priced with the escrowed dividend model.

Overstock and stock-out in Volkswagen Autoeuropa

The following work is a case study of overstock and stock-out problems at Volkswagen Autoeuropa (VWAE). It introduces the supply chain of Autoeuropa and specializes then on failures connected to inventory problems. Having a successful supply chain is important in a world where products become more and more similar as it can give to companies an edge over their competitors. The case shows three practices that VWAE uses to prevent and to overcome stock problems. Information was gathered by doing interviews with different managers, by analyzing the company’s key processes and by literature research related to the topics of supply chain management and flexibility in the supply chain. Three practices were further investigated: the use of alternative parts, support of the supplier and a rating system of suppliers. In the question section of this work the importance of flexibility and Supplier Relationship Management (SRM) when connected to supply chain management are explained. The described different practices are numerically analyzed and it is concluded that each practice brings both cost savings and the possibility of achieving target numbers to the company, showing the company’s flexibility to react to supply chain disturbances. Because of confidentiality reasons, persons in the case are fictionalized and numbers are wherever possible equalized to 100 in order to display true proportions.