Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

The impact and performance of new equity derivatives : evidence from universal stock futures

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Liquidity and liquidity risk of UK equity options

This doctoral thesis investigates the role of liquidity in potential channels of liquidity risk in the UK equity options market. It conjectures that liquidity risk channels are associated with market-wide factors of both the options market and the underlying stock market. It assesses whether the liquidity of individual stock options comoves with that of the options market only or with that of the stock market as well. It also assesses how the persistence of liquidity in the options market and the stock market affects option returns over time. Moreover, once the time variation of liquidity in the options market and in the stock market are analysed, this study forwards a rationale that option returns can be partly explained by the liquidity of an option, liquidity of the underlying stock, and different sources of liquidity risk, such as: the covariance of the liquidity and return of the option with the returns of the stock market; the covariance of the liquidity and return of the option with the liquidity of the options and stock markets; the covariance of the liquidity of the stock with returns of the stock market; and the covariance of the liquidity of the stock with the liquidity of the options and stock markets. The factor risk premia that include the standard market factor and liquidity risk factors are estimated using the standard two-pass Fama-MacBeth (1973) procedure. This study uses UK equity options data on the most actively traded FTSE 100 stocks covering the period from 22 February 2008 to 31 December 2010. It documents new evidence of liquidity comovement between options and their underlying stock market, option return sensitivity to unexpected illiquidity in the options markets, and sources of liquidity risk being priced in equity options returns. It also confirms the already documented findings of Cao and Wei (2010) on liquidity comovement between options and their market, the size effect and the volatility effects in the liquidity comovement. We find new evidence that the liquidity of options comoves with the liquidity of the underlying stock market. Although small in magnitude when compared to the liquidity comovement between options and their market, it still is significant across option portfolios. This suggests that liquidity of the underlying plays an important role in explaining liquidity in options as measured by the bid-ask spread. It is also evidence for the derivative hedge theory that the bid-ask spread in the derivatives market exist partly due to the bid-ask spreads in the underlying market. However, when we investigate the role of inventory risk, information asymmetry and derivative hedge theory in explaining the daily changes in option proportional bid-ask spreads, we find that information asymmetry helps explain spreads in the option market, since both changes in option volume and open interest have positive relationships with the change in option spreads. The thesis documents first time evidence on the sensitivity of option returns to expected and unexpected illiquidity in the options and stock markets. We find that the effect of expected illiquidity on option returns is significant and positive for calls only, whereas the effect of unexpected illiquidity on option returns is significant and negative for both calls and puts. For calls, the latter effect decreases in moneyness and maturity, and for puts, increases in maturity. We further document that generally option portfolios do not show strong sensitivity to the expected and unexpected illiquidity in the stock market. Only deep-in-the-money call options show significant effect of expected and unexpected illiquidity on their option returns. This could be mainly because deep-in-the-money calls act more like a stock as their delta is close to one. The implication is that option traders consider expected and unexpected illiquidity in the options market based on the type of option they are trading. They generally are little concerned about stock market illiquidity, probably because all options analysed are on the liquid FTSE 100 stocks. The most important findings in the thesis relate to the pricing of option liquidity, stock liquidity and liquidty risk channels in the equity options market. We define option return as the return of a delta-hedged portfolio net of the risk-free rate. Based on this definition, we document that option liquidity affects option returns negatively for calls and puts. The relationship is significant for most moneyness portfolios of put options only. This suggests that on average option traders pay a premium for the expected liquidity of the option. We do not find evidence that stock liquidity affects delta-hedged option returns. This finding is contrary to that of Cetin et al. (2006) who report that when the underlying asset is not perfectly liquid, the liquidity cost of the asset is a significant component of the option price and the impact on the option price depends on its moneyness. We further document new evidence that the different sources of liquidity risk are priced in equity options, and this depends on the type as well as the moneyness of the options. For calls, we document that liquidity comovement between options and their market, the sensitivity of option reutrns to the option market liquidity, the sensitivity of option liquidity to stock market return, and liquidity comovement between the stock market and the option market are priced. For puts, we document that liquidity comovement between options and their market, liquidity comovement between options and their underlying market and sensitivity of stock liquidity to stock returns are priced. Finally, we document that the premium related to various sources of liquidity risk is 0.515 pence for at-themoney calls and 0.318 pence for at-the-money puts. We conclude that although more sources of liquidity risk are priced in puts than in calls across all moneyness portfolios, the results suggest that the liquidity risk premium demanded by investors for calls is higher than that for puts. This suggests that calls are riskier than puts, as far as liquidity is concerned. The overall results in this thesis on the UK equity options market, compared to the findings in the literature on equity options of other markets, indicate that option traders consider liquidity as an important determinant of option prices. Most importantly, liquidity of an option and the channels of liquidity risk related to liquidity comovement between options and their market, liquidity comovement between options and the stock market, sensitivity of option returns to option market liquidity, sensitivity of option liquidity to stock market return, and liquidity comovement between the stock and the options market, are priced in UK equity options

Risk Management using Model Predictive Control

Forward planning and risk management are crucial for the success of any system or business dealing with the uncertainties of the real world. Previous approaches have largely assumed that the future will be similar to the past, or used simple forecasting techniques based on ad-hoc models. Improving solutions requires better projection of future events, and necessitates robust forward planning techniques that consider forecasting inaccuracies. This work advocates risk management through optimal control theory, and proposes several techniques to combine it with time-series forecasting. Focusing on applications in foreign exchange (FX) and battery energy storage systems (BESS), the contributions of this thesis are three-fold. First, a short-term risk management system for FX dealers is formulated as a stochastic model predictive control (SMPC) problem in which the optimal risk-cost profiles are obtained through dynamic control of the dealers’ positions on the spot market. Second, grammatical evolution (GE) is used to automate non-linear time-series model selection, validation, and forecasting. Third, a novel measure for evaluating forecasting models, as a part of the predictive model in finite horizon optimal control applications, is proposed. Using both synthetic and historical data, the proposed techniques were validated and benchmarked. It was shown that the stochastic FX risk management system exhibits better risk management on a risk-cost Pareto frontier compared to rule-based hedging strategies, with up to 44.7% lower cost for the same level of risk. Similarly, for a real-world BESS application, it was demonstrated that the GE optimised forecasting models outperformed other prediction models by at least 9%, improving the overall peak shaving capacity of the system to 57.6%

Application of Machine Learning to Financial Time Series Analysis

This multidisciplinary thesis investigates the application of machine learning to financial time series analysis. The research is motivated by the following thesis question: ‘Can one improve upon the state of the art in financial time series analysis through the application of machine learning?’ The work is split according to the following time series trichotomy: 1) characterization — determine the fundamental properties of the time series; 2) modelling — find a description that accurately captures features of the long-term behaviour of the system; and 3) forecasting — accurately predict the short-term evolution of the system

NONPARAMETRIC ESTIMATION OF CONDITIONAL VARIANCE AND COVARIANCE FUNCTIONS

Ph.DDOCTOR OF PHILOSOPH