Implementation of an IoT-based Sensor Network Integrating IoT-based Sensor Networks with Large-Scale Message Distribution

As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.

Intraday volatility

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

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

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.

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.

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.

Money never sleeps – overnight returns in equity markets

The present research analyses overnight returns’ outperformance in relation to daytime returns. In a first stage, it will be assessed whether these returns are robust throughout time, markets and across different scopes of analysis (e.g. weekdays, months, states of the economy). In a second stage, several hypothesis will be empirically tested, in an attempt to understand what drives non-trading period returns (e.g. liquidity, market volatility). Even though several authors have analysed overnight returns and suggested several explanatory factors, there seems to be no consensus in the literature regarding its drivers.

Exploiting the cointrgration between vix and CDS in a credit market timing model

We investigate the cointegration between VIX and CDS indices, and the possibility of exploiting it in an existing credit market timing investment model. We find cointegration over most of the sample period and the leadership of VIX over the CDS in the price discovery process. We present two methods for including cointegration into the model. Both strategies improve the in-sample and out-of-sample model performances, even though out-of-sample results are weaker. We find that in-sample better performances are explained by a stronger cointegration, concluding that in the presence of cointegration our strategies can be profitable in an investment model that considers transaction costs.

A negociação no mercado a prazo do MIBEL

This master thesis has been developed during the internship in the Supervision Department of Supervision of the Intermediation and Market Structures of CMVM. My collaboration in such department was mainly focused on the derivatives market of the Iberian Electricity Market (MIBEL). MIBEL embodies two organized markets – the derivatives market in Portugal and the spot market in Spain The trading activity in the derivatives market of MIBEL is processed through the trading platform of the regulated market managed by OMIP, however, much of the negotiation is over-the-counter. The aim of this work is to describe the market from a legal and economic perspective and to analyse the evolution of the negotiation, namely the impact of OTC in the regulated market trading. To achieve this, I propose to analyse also MiFID and EMIR rules over derivative contracts and the role of central counterparties, as they both are important to the discussion. In parallel, we found that OTC transactions are considerably higher than those traded in the regulated market managed by OMIP, those findings can be justified by the contractual relationships based on trust already established between the partiesarties. Nevertheless, since 2011 this trend changed by an increase of the registered OTC. Thereafter, although the parties continued to trade bilaterally, these transactions were registered in a central counterparty in order to eliminate the inherent risks related to the OTC derivatives transactions. This change in the negotiation pattern may also be influenced by the mandatory reporting of transactions imposed by EMIR, that requires for some classes of derivatives the centralized clearing and for all other requires the implementation of risk mitigation techniques.