Pricing of exchange traded funds

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

Sustainability and consumer responses: The effect of bad industry reputation and fit

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

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Earnings overseas and cash holdings

I investigate the impact of foreign pre-tax income on the total amount of cash held by companies and on the amount of cash that is held in companies’ foreign subsidiaries. I also investigate the impact of the existence and amount of cash held on companies’ foreign subsidiaries in the composition of cash holdings in terms of risk and liquidity. Using a sample of 100 largest U.S. non-financial and non-utilities companies I find that companies with higher earnings overseas present higher cash reserves and invest a higher fraction of their cash in risky assets. My evidence suggests that companies have a different optimization strategy for cash overseas, in which precautionary motives are not the main driver for holding cash.

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

An analog model for global macro investing

This study proposes a systematic model that is able to fit the Global Macro Investing universe. The Analog Model tests the possibility of capturing the likelihood of an optimal investment allocation based on similarity across different periods in history. Instead of observing Macroeconomic data, the model uses financial markets’ variables to classify unknown short-term regimes. This methodology is particularly relevant considering that asset classes and investment strategies react differently to specific macro environment shifts.

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.

The spin-off of Sonae Capital

The purpose of this project is to study the spin-off of Sonae Capital, which took place in January 2008. Taking the form of a case study, this project is divided between the case narrative and a teaching note. I study the background and motivation of the transaction, along with its outcome. With the available information at the time of the case, I value Sonae Capital at the date of the spin-off and describe a possible trading strategy involving both the spun-off and the demerged companies. Finally, I conclude that the transaction was more beneficial for the parent company, Sonae SGPS, and that it did not follow the typical outperformance pattern observed in other spin-offs.

Tracking error of exchange-traded funds: Evidence from the UK

This paper is mainly concerned with the tracking accuracy of Exchange Traded Funds (ETFs) listed on the London Stock Exchange (LSE) but also evaluates their performance and pricing efficiency. The findings show that ETFs offer virtually the same return but exhibit higher volatility than their benchmark. It seems that the pricing efficiency, which should come from the creation and redemption process, does not fully hold as equity ETFs show consistent price premiums. The tracking error of the funds is generally small and is decreasing over time. The risk of the ETF, daily price volatility and the total expense ratio explain a large part of the tracking error. Trading volume, fund size, bid-ask spread and average price premium or discount did not have an impact on the tracking error. Finally, it is concluded that market volatility and the tracking error are positively correlated.

Cross sectional default probabilities in european corporate bonds

This study attempts to identify basis-trading opportunities in the European banking sector by comparing two different measures for the market’s assessment of risk: market-observed CDS spreads and model-implied Z-spreads. Using a sample of 10 banks, over a period of 3 years following the European banking crisis, it can be concluded that there were arbitrage opportunities in the sector, as evidenced by the derived negative bases.

Future lending income and security value

I test the Duffie, Gârleanu, and Pedersen hypothesis that security prices incorporate expected future securities lending income. To determine whether institutional investors anticipate gains from future lending of securities, I examine their trading behavior around loan-fee increases. The evidence suggests that institutions buy shares in response to an increase in lending fees, and that this could explain the premium associated with high- lending-fee stocks. Expected future lending income affects stock prices, although the effect seems to be attenuated by the negative information that arises from short selling.

Drilling deeper: Understanding trade in Angola

The present study analyzes Angola’s trading partners from 2005 to 2015 in order to understand the main drivers of Exports and Imports growth. Departing from a gravity model, foreign GDP growth and real exchange rate fluctuations were interpreted as demand and supply disturbances on Exports. While nominal and real exports both increase with demand expansions, they react differently to supply shocks. Imports are growing at the same rate as Angola’s economy while exchange rate fluctuations capture the wealth effect of Oil price in the economy.

Analysis of a controversial decision process: the case of the pumped hydro storage power plant Atdorf in Germany

Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

Microstructural changes befor macroeconomic announcements: Predictability of economic surprises in the U.S. market

Flow of new information is what produces price changes, understanding if the market is unbalanced is fundamental to know how much inventory market makers should keep during an important economic release. After identifying which economic indicators impact the S&P and 10 year Treasuries. The Volume Synchronized Probability of Information-Based Trading (VPIN) will be used as a predictability measure. The results point to some predictability power over economic surprises of the VPIN metric, mainly when calculated using the S&P. This finding appears to be supported when analysing depth imbalance before economic releases. Inferior results were achieved when using treasuries. The final aim of this study is to fill the gap between microstructural changes and macroeconomic events.

Macroeconomic risk in commodities market

The thesis studies the presence of macroeconomic risk in the commodities futures market. I present strong evidence that there is a strong relationship between macroeconomic risk and individual commodities future returns. Furthermore, long-only trading strategies seem to be strongly exposed to systematic risk, while long-short trading strategies (based on basis, momentum and basis-momentum) are found to present no such risk. Instead, I found a strong sentiment exposure in the portfolio returns of these long-short strategies, mainly during recessions. The advantages of following long-short strategies become even clearer when analyzing different macroeconomic regimes.