Enhancing and implementing a pairs trading strategy

This paper designs a pairs trading model with the intent to identify existing profitable market opportunities to invest, i.e. traditionally strong correlated stocks that have diverged from its historical norm. It comprises a broad literature review on this strategy whose relevant findings (strategy improvements) are contemplated in the model. The authors combine the statistical results of the model with a backtesting analysis in order to provide guidance on the best investment opportunities.

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.

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.

Credit default swap (CDS) prediction model & trading strategy

This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

Pair trading: Clustering based on principal component analysis

This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.

Trading the differences in expectations between the CDS and bond markets

This paper uses the framework developed by Vrugt (2010) to extract the recovery rate and term-structure of risk-neutral default probabilities implied in the cross-section of Portuguese sovereign bonds outstanding between March and August 2011. During this period the expectations on the recovery rate remain firmly anchored around 50 percent while the instantaneous default probability increases steadily from 6 to above 30 percent. These parameters are then used to calculate the fair-value of a 5-year and 10- year CDS contract. A credit-risk-neutral strategy is developed from the difference between the market price of a CDS of the same tenors and the fair-value calculated, yielding a sharpe ratio of 3.2

O abuso de informação privilegiada (insider trading)

In the stock market, information takes on special relevance, due to the market’s permanent updating and the great fluidity of information existent therein. Just as in any other negotiations, the party with the better information has a bargaining advantage, as it is able to make more advantageous business decisions. However, unlike most other markets, the proper functioning of the stock market is greatly dependent on investors’ trust in the market itself. As such, if there are investors who, due to any condition they possess or office they hold, have access to relevant information which is not accessible to the general public, distrust is bred within the market and, consequently, investment is lessened. Thus, there is a need to prevent those who hold privileged information from using it in abusive ways. In Portugal, abuse of privileged information is set out and punished criminally in Article 378. of the Portuguese Securities Code (‘Código dos Valores Mobiliários’). In this dissertation, I have set out, firstly, to analyze the inherent conditions for there to be a crime of abuse of privileged information; secondly, to analyze two well-known cases, which took place and were decided in other jurisdictions, and attempt to understand how these cases would fall under Article 378. of the Portuguese Securities Code. Whereas the first case, Chiarella v. United States, was scrutinize under Article 378 of the Portuguese Securities Code, in the second, Lafonta v. AMF, the conclusion arrived at was that the crime taken place was different. This analysis allowed, on one hand, the application to a particular case of prerequisites and concepts which were explained, at a first approach, from a more theoretical perspective; on the other hand, it also allowed the further development of specific aspects of the regime, namely the difference between an insider and a tipee, as well as to more clearly set out the limits to the precise character of the information at hand.

Trading the changes of stock market index composition: Evidence from European markets

This paper studies the changes in European stock market indexes composition from 1995 to 2015. It was found that there are mixed price effects producing abnormal returns around the effective replacement of added and deleted stocks. The price pressure hypothesis seems to hold for added stocks in some indexes but not for deleted stocks as there is not a clear inversion of behaviour after the replacement. Finally, the building and back testing of a trading strategy aiming to capture some of those abnormal returns shows it yields a Sharpe Ratio of 1.4 and generates an annualised alpha of 11%.

Using artificial neural networks to generate trading signals for crude oil, copper and gold futures

In this thesis, a feed-forward, back-propagating Artificial Neural Network using the gradient descent algorithm is developed to forecast the directional movement of daily returns for WTI, gold and copper futures. Out-of-sample back-test results vary, with some predictive abilities for copper futures but none for either WTI or gold. The best statistically significant hit rate achieved was 57% for copper with an absolute return Sharpe Ratio of 1.25 and a benchmarked Information Ratio of 2.11.