ii Abstract This thesis focuses on one of the attractive topics of current financial literature, the application of wavelet-based methods in volatility modeling. It introduces a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH- family model capturing long-memory and asymmetry in volatility, and studies its properties. Based on an extensive Monte Carlo experiment, both the behavior of the new estimator in various situations and its relative performance with respect to two more traditional estimators (maximum likelihood estimator and Fourier-based Whittle estimator) are assessed, along with practical aspects of its application. Possible solutions are proposed for most of the issues detected, including suggestion of a new specification of the estimator. This uses maximal overlap discrete wavelet transform instead of the traditionally used discrete wavelet transform, which should improve the estimator performance in all its applications, not only in the case of FIEGARCH model estimation. The thesis concludes that, after optimization of the estimation setup, the wavelet-based estimator may become an attractive robust alternative to the traditional methods.

Nous soutenons la thèse que la sécurité alimentaire des pays d'Afrique sub-saharienne peut être renforcée par une meilleure maitrise de l'instabilité des prix des matières premières agricoles constituant leur panier alimentaire de base. A cet effet, nous évoquons dans un premier temps les mécanismes de fonctionnement des marchés agricoles, le rôle qu'y joue la notion de prix ainsi que le lien existant entre l'évolution instable des prix et l'insécurité alimentaire. Nous nous intéressons ensuite au lien existant entre l'insécurité alimentaire et la régulation du secteur agricole, en particulier dans le cadre des échanges internationaux et régionaux. Nous procédons enfin au traitement formalisé de l'insécurité alimentaire. En ayant recours aux outils économétriques, nous mettons en évidence le caractère instable des prix au niveau individuel des pays ainsi que les interdépendances entre les prix des différentes denrées alimentaires et des différents pays. Des mesures de sécurisation alimentaire sont suggérées tout au long de la thèse pour les pays d'Afrique sub-saharienne étudiés. Nous estimons que ces mesures peuvent servir de pistes de réflexion pour l'établissement de politiques économiques agricoles nationales et régionales. Ces politiques auraient pour but final de garantir la sécurité alimentaire des populations des pays de l'Afrique sub-saharienne par une meilleure maitrise de l'instabilité des prix alimentaires. / In our thesis, we assume that African Sub-saharan countries' food security status can be enhanced through a better management of agricultural commodities prices instability, which constitutes the basic food basket of local populations. To this aim, we initially review the dynamics of agricultural markets and the role played by “prices” in this mechanism as well as the existing linkages between unstable price trends and the notion of food insecurity. Focus is then directed to the relationship between “food insecurity” and the regulation of the agricultural sector, in particular within international trade theory frameworks.Finally, we proceed to the assessment of “food insecurity” through the empirical analysis of the instabilities affecting food prices of the region, and also that of price transmission and linkages within and between countries. We then highlight prices instabilities at individual (country) level, as well as the linkage of these prices (therefore of their unstable components) between the various constituents of the basic food basket of a given country, or that of neighboring countries.All along our thesis, food insecurity resilience measures for these countries are suggested. These measures are believed to potentially serve as initial steps in the establishment of national and regional agricultural policies aiming at attaining/safeguarding food security in African sub-Saharan countries.

The correlation between stock market returns and changes in bond market yields are of big interest among investors because this indicator helps them allocate their assets and diversify investment risk more effectively. An in- vestor should keep track of development of the economies of individual coun- tries, understand the causes of dissimilarities in the correlations among them and take these differences into account for successful international financial investment. The current author contributes to the existing researches by the modeling of stock-bond market co-movements using the updated datasets with focus on Central European countries and differences in public debt levels. The paper contains the empirical analysis of stock and bond market returns condi- tional correlations, modeled by the use of the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) Generalized Autoregressive Conditional Het- eroskedasticity (GARCH) specification, for nine Western and Central European countries (the United Kingdom, Germany, France, Spain, Portugal, Italy, Czech Republic, Poland and Hungary) that differ both by their geographic locations and economic development. The main distinctions in the correlations are ob- served during the European sovereign debt crisis. The three types of develop- ment are...

Le marché boursier marocain a connu une chute brutale sans précédent à cause de la crise de subprimes américaines qui a été déclenchée à l'été 2007, l'indice MASI a perdu 20% en même année, donc nous pouvons parler sur un krach boursier. La bourse des valeurs a connu en Mars 2008 une volatilité de 70 milliards de dirhams. La baisse du marché boursier risque de se prolonger et que le sinistre scénario des années (2007-2009) pendant lesquelles la bourse a connu une chute du cours de l'indice MASI pourrait se reproduire. L'objet de notre thèse est de proposer une analyse empirique détaillée des rendements de l'indice MASI, de choisir les portefeuilles efficients, plus un modèle économétrique qui enregistre le score le plus bas de violations c'est-à-dire qu'il assure la meilleure couverture possible contre les risques baissiers du marché quel que soit le niveau de la volatilité atteint par le marché boursier marocain. Pour atteindre cet objectif nous faisons appel aux modèles Markowitz et Value at Risk. / The Moroccan stock market had experienced an unmatched Sharp collapse due to the subprime crisis that happened in the USA on summer 2007, the index of MASI lost 20% in the same year, thus we can talk here about a crash of stock. In 2008, the stock market lost 70 billion MAD. It is possible that it will continue decreasing, and that the scenario of 2007 - 2009 will happen again. The purpose of this thesis is to suggest a detailed empirical analysis of the yields of MASI index and choose the most efficient portfolios, and an econometric model that can record the lowest score of the violations, in other words, it can guarantee the best cover against the downside market risk Whatever the level of the volatility reached by the Moroccan stock market, to achieve this goal we use the Markowitz model and Value at Risk.

In this companion paper to Broll and Mukherjee (2017), we empirically analyse how exchange rate volatilities affect firms optimal production and exporting decisions. The firms elasticity of risk aversion determines the direction of the impact of exchange rate risk on exports. Based on a flexible utility function that incorporates all possible risk preferences, a unique structurally estimable equation is used to estimate the risk aversion elasticities for a panel of Indian service sector (non-financial) firms over 2004-2015, using the quantile regression method.

Investing in commodities may have important benefits for investors but only in the last few decades have they started to think more about this possibility. Furthermore, large investors are more inclined to change their own personal view. Therefore, understanding the benefits that commodities could give to an investment portfolio might alleviate investors’ concerns. Several previous studies, as Belousova and Dorfleitner (2012) suggest, that the commodities with higher benefits are precious metals and gold, in particular. The purpose of our work is to understand which possible benefits are for equity investors and if they are common for certain commodities with different physical characteristics. The first part of our empirical work focuses on the main descriptive statistics of the return distribution (mean, variance, volatility, skewness, kurtosis and correlation) for 8 stock indices and 7 commodity futures. The main goal of this is to understand the differences among the commodities and between the commodities and the stock indices. In the second part of the empirical work, we test the safe-haven and the hedge properties of these commodities on a weekly basis for all of them with stock indices, and we do the same on a daily and monthly basis for only commodities which are negatively correlated on average with the stock indices. In the last part of our work, we combine these 7 commodities, following the principles of Bloomberg Commodity Index (BCOM), in order to create a well-balanced and well-diversified commodity index. Additionally, we create some mixed portfolios using this index and a different stock index every time. After that we look at the volatilities and the returns of these mixed portfolios with different weight combinations. Our main goals in this section are to understand the characteristics of the commodity index in comparison with stock indices and then, finding which weight combinations give the mixed portfolios the optimal risk-return trade off. Understanding which are efficient weights, can lead to conclusions about the weight that commodities should have in a portfolio according to the risk tolerance of the investors.  The research is done considering three time frequencies: daily, weekly and monthly; in line with the ones used by Baur and McDermott (2010). The sample size differs among these three different time basis. In fact, daily data started in January 2007 and the other two time frequencies data began with January 1997. All the time samples ended in March 2016. The results of the first part show that gold is the only commodity with a volatility similar to the stock indices (it also has a higher average return) and that on the daily, weekly and monthly basis. Whereas, the other commodities are much riskier than stock indices since they have higher volatility for all the three time-frequencies analyzed.  The results of the second part suggest that only gold is both a safe-haven and hedging commodity in line with the methodology used by Baur and McDermott (2010), but only for DAX 30 on a weekly basis. Furthermore, our results also show that natural gas is strong hedge in some cases such as natural gas for STI (Singapore) on a monthly basis or gold for Nikkei 225 on daily, weekly and monthly basis. Other commodities are neither safe-haven nor hedge in any case, except for silver which is a safe-haven commodity for DAX 30 and Sensex which at its worst, 1% and 5%, declines in the market respectively. The results of the last part of our work show that all the minimum variance mixed portfolios (the ones with the weights give the lowest risk) - made on a weekly basis - reduce the portfolio volatility and make the portfolio returns higher than the stock indices returns in 5 cases out of 8. Additionally, the results show how investors, who add a well-balanced and well-diversified commodity index to their portfolios, are able to observe several weight combinations and choose the one which suits their risk tolerance. Moreover, our results show that the optimal-weight combinations for commodity weights are lower than 0,5 only for FTSE 100 and S&P 500 (both values are 0,49) and higher than 0,62 but lower than 0,7 for DAX 30, Nikkei 225, Hang Seng, Sensex, SSEC. Furthermore, the optimal weight for STI is 0,54.

M.Com. (Economic Development and Policy Issues) / This research analyses the effect of exchange rate volatility on exports using a sample of nine emerging countries – Argentina, Brazil, India, Indonesia, Mexico, Malaysia, Poland, South Africa and Thailand – between 1995 and 2010. The study uses panel data models, with a standard exports equation with exports performance determined by exchange rate volatility, the level of exchange rate, demand conditions in major countries as well as terms of trade. Exchange rate volatility is measured by Generalised Autoregressive Conditional Heteroscedasticity (GARCH) and conventional standard deviation in order to determine if the instrument of volatility used influences the nature of the relationship between exchange rate volatility and exports. The results show that exchange rate volatility has a significant negative effect on the performance of exports regardless of the measure of volatility used. The Pedroni residual cointegration method was used to test for panel cointegration to determine if there is a long-run relationship among the variables, and the test showed that a long-run relationship does exists. Generally, the study concludes that policy mix that will reduce exchange rate volatility (such as managed exchange rate regimes) and relatively competitive exchange rates are essential for emerging markets in order to sustain their exports performance.

Chapter 1 of the dissertation investigates the firms' restructuring choice between minority carve-outs and tracking stocks using samples during 1990-2001. The extra compensation from the restructured units, the liquidity conditions, and the preservation of synergy are the significant factors determining a firm's restructuring decision. Additional compensation seems to be a major driving force behind restructuring via tracking stock. One year after the restructuring, the executive compensation of the tracking stock group increases by 241% compared to 32% for the carve-out sample. In spite of the significant increase in the compensation, the three-year buy-and-hold return for tracking stock parents is more negative than that of the carve-out parents. Thus, if the extra compensation was designed to align the interests of managers and shareholders, the goal did not materialize. The primary motive behind restructuring through carve-outs is to control the liquidity problem. Although the operating performance of the parents of either group does not improve three years after the restructuring, the long-term stock performance of carve-out parents improves when a restructured unit is less related to the parent. Chapter 2 of the dissertation compares the degree of overreaction between value stocks and growth stocks using the implied volatility from option prices. Applying Stein's (1989) mean reversion model and Heynen, Kemna, and Vorst's (1994) GARCH and EGARCH methods, I compare the theoretical and empirical measures of reaction of longterm options in respect to short-term options for the growth and the value portfolios, which are separately classified by price-to-book and price-to-earning ratios. The evidence suggests that growth portfolios largely overreact to a greater degree than the value portfolios assuming mean reversion, GARCH, and EGARCH models. The findings potentially explain why value stocks outperform growth stocks in the long run, lending support to overreaction as an explanation for the value effect.

Digital forensics is the investigation and recovery of data from digital hardware. The field has grown in recent years to include support for operating systems such as Windows, Linux and Mac OS X. However, little to no support has been provided for less well known systems such as the FreeBSD operating system. The project presented in this paper focuses on creating the foundational support for FreeBSD via Volatility, a leading forensic tool in the digital forensic community. The kernel and source code for FreeBSD were studied to understand how to recover various data from analysis of a given system’s memory image. This paper will focus on the base Volatility support that was implemented, as well as the additional plugins created to recover desired data, including but not limited to the retrieval of a system’s process list and mounted file systems.

In this paper we forecast daily returns of crypto-currencies using a wide variety of different econometric models. To capture salient features commonly observed in financial time series like rapid changes in the conditional variance, non-normality of the measurement errors and sharply increasing trends, we develop a time-varying parameter VAR with t-distributed measurement errors and stochastic volatility. To control for overparameterization, we rely on the Bayesian literature on shrinkage priors that enables us to shrink coefficients associated with irrelevant predictors and/or perform model specification in a flexible manner. Using around one year of daily data we perform a real-time forecasting exercise and investigate whether any of the proposed models is able to outperform the naive random walk benchmark. To assess the economic relevance of the forecasting gains produced by the proposed models we moreover run a simple trading exercise.