The effect of asymmetries on optimal hedge ratios

There is widespread evidence that the volatility of stock returns displays an asymmetric response to good and bad news. This article considers the impact of asymmetry on time-varying hedges for financial futures. An asymmetric model that allows forecasts of cash and futures return volatility to respond differently to positive and negative return innovations gives superior in-sample hedging performance. However, the simpler symmetric model is not inferior in a hold-out sample. A method for evaluating the models in a modern risk-management framework is presented, highlighting the importance of allowing optimal hedge ratios to be both time-varying and asymmetric

Building a Better Fund of Hedge Funds: A Fractal and Alpha - Stable Distribution Approach

Markowitz’s (1952) portfolio theory has permeated financial institutions over the past 50 years. Assuming that returns are normally distributed, Markowitz suggests that portfolio optimization should be performed in a mean-variance framework. With the emergence of hedge funds and their non-normally distributed returns, mean-variance portfolio optimization is no longer adequate. Here, hedge fund returns are modeled with the alpha-stable distribution and a mean-CVaR portfolio optimization is performed. Results indicate that by using the alpha- stable distribution, a more efficient fund of hedge funds portfolio can be created than would be by assuming a normal distribution. To further increase efficiency, the Hurst exponent is considered as a filtering tool and it is found that combining hedge fund strategies within a range of Hurst exponents leads to the creation of more efficient portfolios as characterized by higher risk-adjusted ratios. These findings open the door for the further study of econophysics tools in the analysis of hedge fund returns.hedge funds, fund of funds, portfolio optimization, conditional value at risk, alpha-stable distribution, Hurst exponent, fractals

Speculation and hedging with virtuals

Virtual bid and Virtual offer are purely financial products offered in certain electricity markets. Theoretically, virtual bids and offers can change the electricity price as the bids and offers are stacked along with the demand and supply, respectively. This dissertation discusses how virtuals can be used to hedge and speculate in the electricity market. A statistical simulation model is developed based on the day-ahead (DA) demand and real time (RT) load data from Midwest Independent Transmission System Operator\u27s (MISO) footprint and DA and RT price observed at Cinergy hub. The simulation models are intended to mimic the load and price processes, taking the cyclical and correlation patterns in the market data into account as well as to provide a mechanism to incorporate stochastic variations that impact the processes. This model can then be utilized to study how the various trading strategies perform under deferent scenarios and thus provide better decision making tools to a trader. The DA Demand and RT Load are simulated using a combination of unobserved component models (UCM) and a set of regression variables. The DA Price and RT Price processes are replicated with GARCH based regression models. The regressor variables include principal components of different weather variables to capture the weather variation across MISO footprint and a set of dummy variables to model key patterns observed in the electricity market. The simulation models are used to generate test data sets which are then used to analyze different strategies involving virtuals. The simulation models also help to understand the relationship between DA and RT clearing prices. This research fins no evidence of DA/RT price convergence purely based on the virtuals trading at MISO. Based on the simulation results, the virtual bids appear to be most profitable during summer and winter and virtual offers appears to be most successful during shoulder months --Abstract, page iii

Algorithmic optimization and its application in finance

The goal of this thesis is to examine different issues in the area of finance and application of financial and mathematical models under consideration of optimization methods. Prior to the application of a model to its scope, the model results have to be adjusted according to the observed data. For this reason a target function is defined which is being minimized by using optimization algorithms. This allows finding the optimal model parameters. This procedure is called model calibration or model fitting and requires a suitable model for this application. In this thesis we apply financial and mathematical models such as Heston, CIR, geometric Brownian motion, as well as inverse transform sampling, and Chi-square test. Moreover, we test the following optimization methods: Genetic algorithms, Particle-Swarm, Levenberg-Marquardt, and Simplex algorithm. The first part of this thesis deals with the problem of finding a more accurate forecasting approach for market liquidity by using a calibrated Heston model for the simulation of the bid/ask paths instead of the standard Brownian motion and the inverse transformation method instead of compound Poisson process for the generation of the bid/ask volume distributions. We show that the simulated trading volumes converge to one single value which can be used as a liquidity estimator and we find that the calibrated Heston model as well as the inverse transform sampling are superior concerning the use of the standard Brownian motion, resp. compound Poisson process. In the second part, we examine the price markup for hedging or liquidity costs, that customers have to pay when they buy structured products by replicating the payoff of ten different structured products and comparing their fair values with the prices actually traded. For this purpose we use parallel computing, a new technology that was not possible in the past. This allows us to use a calibrated Heston model to calculate the fair values of structured products over a longer period of time. Our results show that the markup that clients pay for these ten products ranges from 0.9%-2.9%. We can also observe that products with higher payoff levels, or better capital protection, require higher costs. We also identify market volatility as a statistically significant driver of the markup. In the third part, we show that the tracking error of an passively managed ETF can be significantly reduced through the use of optimization methods if the correlation factor between Index and ETF is used as target function. By finding optimal weights of a self-constructed bond- and the DAX- index, the number of constituents can be reduced significantly, while keeping the tracking error small. In the fourth part, we develop a hedging strategy based on fuel prices that can be applied primarily to the end users of petrol and diesel fuels. This enables the fuel consumer to buy fuel at a certain price for a certain period of time by purchasing a call option. To price the American call option we use a geometric Brownian motion combined with a binomial model

Gestion durable des ressources dans la chaîne de valeur européenne de l’acier

The present thesis delved into the current and future interactions within the European Steel Industry and of it with the environment it is a part of, with the main objective of supporting decision- and policy-making efforts oriented towards sustainability and circularity, helping to shape the future of steel in the European Community. The thesis used the European Steel Industry as a case study to explore the potential benefits of integrating Life Cycle Assessment (LCA) into System Dynamics (SD) under the scopes of Circular Economy and Industrial Ecology. A model representative of the European Steel Industry was built modularly in Stella Architect, following ILCD and ISO guidelines and standards for LCA. Throughout 4 of the 5 articles developed for the present thesis, 21 simulation runs were performed on the aforementioned model: 12 on identifying potential constraints and benefits of End-of-Life policies; 5 assessing the advantages and disadvantages of different Supply Chain Integration (SCI) strategies along European steel supply chains; and 4 addressing the interactions between biophysical and economic dynamics in the steel market. An additional article was developed using the methodologies of Circles of Sustainability and Sustainable Urban Metabolism to appraise the challenges and contributions of steel as part of servitization initiatives in urban environments. Overall results indicated that integrating LCA into SD was not only feasible and capable of reproducing results, trends and behaviors from previous scientific studies, but also of contributing to both methodologies in different levels. This approach has potential to interest policy-makers who seek more granularity within the European Steel Industry as well as decision-makers searching for a broader understanding of their operation’s dynamics beyond the gates, notably regarding raw material scarcity, resource self-sufficiency, and resource ownership retention. From the results of each article it was observed that, (a) pushing for recycling and reuse could generate interesting medium- to long-term results for circularity, transitioning away from fossil fuels and developing a whole new market around end-of-life services; (b) different SCI approaches can be environmentally and strategically promising; (c) six key biophysical variables can distinctively affect spot prices, future prices, EBITDA margins, capacity utilization, dividend payouts, and costs of steelmaking; and (d) servitization can provide significant benefits to sustainable cities, while also being able to substantially alter the supply-side dynamics of steelmaking, highlighting how important it is for steelmakers to pay close attention to the service-providing initiatives that may concern their clients and products.La présente thèse entend examiner les interactions présentes et futures entre l'industrie sidérurgique européenne et son environnement, avec pour objectifs principaux, l’amélioration de la prise de décision et l'élaboration de politiques industrielles en matière de durabilité et de circularité. La thèse contribue à l’émergence de propositions contribuant à façonner l'avenir de l'acier dans l’Union Européenne. L'industrie sidérurgique européenne est utilisée ici comme un cas d’école, visant à explorer les avantages potentiels pour l’économie circulaire et l’écologie industrielle, d’une intégration d’un outil (Analyse du Cycle de Vie – ACV) dans une méthodologie (Dynamique des Systèmes – SD). Un modèle modulaire pour l’industrie sidérurgique européenne a été construit et, pour 4 des 5 articles développés dans la thèse, 21 simulations ont été effectuées. 12 simulations ont permis d’identifier les contraintes potentielles et les avantages des stratégies de fin de vie; 5 d’évaluer les avantages et les inconvénients des différentes stratégies d’intégration de la chaîne d’approvisionnement (SCI) dans la filière européenne de l’acier; et 4 de traiter des interactions entre les dynamiques biophysiques et économiques sur le marché de l'acier. Le dernier article s’appuie sur une nouvelle méthodologie – les Cercles de Durabilité et le Métabolisme Urbain Durable – pour évaluer les défis et les contributions de l'acier dans le cadre de l’éco-fonctionnalité en milieu urbain. Les résultats ont montré que l’intégration de l’ACV dans les stratégies de développement durable permettait de reproduire assez fidèlement les résultats et les scénarios d’études scientifiques antérieures, tout en suggérant des apports méthodologiques relativement novateurs. Cette recherche opérationnelle est susceptible d'intéresser les managers et des chefs d’entreprises qui s’attachent aux questions d’efficience et de résilience de l’outil industriel, ainsi que les décideurs politiques qui souhaitent cerner les enjeux d’une pénurie de matières premières ou d’une politique de recyclage de l’acier à l’échelle européenne. D'après les résultats de chaque article, il a été observé que (a) le recyclage et la réutilisation pourraient générer des résultats intéressants à moyen et à long terme en matière de circularité, en abandonnant notamment les combustibles fossiles et en développant un tout nouveau marché autour des services de fin de vie; (b) différentes approches en matière de chaine logistique intégrée semblent être prometteuses d'un point de vue environnemental et stratégique; (c) six variables biophysiques clés peuvent avoir une incidence notoire sur les cours au comptant, les cours à terme, les marges d'EBITDA, l'utilisation des capacités de production, la distribution des dividendes et les coûts de fabrication de l'acier; et (d) la dynamique servicielle dans le cadre de l’éco-fonctionnalité peut apporter des avantages significatifs aux villes durables, tout en modifiant considérablement la structure de l’offre sur le marché de l’acier

Effectiveness of CDS regulation : an insight Into the Cyprus and Greek crisis

Esta dissertação realiza-se no âmbito de tentar averiguar se as mais recents regulamentações relativas ao mercado de CDS surtiram algum efeito na regularização deste. Mais especificamente, são estudadas as medidas da inclusão do bail-in como medida de qualidade de crédito na ISDA 2014 e a proibição de transações de CDS sem qualquer cobertura ao risco. Devido ao elevado crescimento do mercado CDS, torna-se imperativo que as autoridades competentes tomem medidas de forma a controlar um mercado em ascensão e com um impacto cada vez maior. No entanto não existe ainda quaisquer provas conclusivas que nos levem a crer que as medidas recentmente tomadas tenham sido a melhor solução para o problema, existindo inclusive indícios que tais medidas poderão exercer precisamente o efeito contrário ao pretendido. Os resultados aqui analisados mostram precisamente que tais medidas não conseguiram controlar o comportamento explosivo dos spreads dos CDS, sendo assim necessário rever as medidas usadas e planear novas medidas, para que exista um controlo de mercado de maneira mais eficaz.This dissertation is realized in the context of understanding if recent measures taken by European authorities relative to the CDS market were effective. More specifically this paper study the bail-in inclusion on ISDA 2014 as a credit quality event and the ban of uncovered CDS. Due to CDS market rapidly growth, it becomes imperative that competent authorities take actions with the view to control this ascending market. Nevertheless there are no conclusive evidences that support the idea that the recent measures were the best solution to the problem, having in counterpart suspicious that such measures could exert the contrary effect. The analysed results precisely suggest that those measures ere not able to control the CDS spreads explosive behavior, showing that it requires new measure planning in order to obtain a more efficiente market control to stabilize the market

Computational Finance

With the availability of new and more comprehensive financial market data, making headlines of massive public interest due to recent periods of extreme volatility and crashes, the field of computational finance is evolving ever faster thanks to significant advances made theoretically, and to the massive increase in accessible computational resources. This volume includes a wide variety of theoretical and empirical contributions that address a range of issues and topics related to computational finance. It collects contributions on the use of new and innovative techniques for modeling financial asset returns and volatility, on the use of novel computational methods for pricing, hedging, the risk management of financial instruments, and on the use of new high-dimensional or high-frequency data in multivariate applications in today’s complex world. The papers develop new multivariate models for financial returns and novel techniques for pricing derivatives in such flexible models, examine how pricing and hedging techniques can be used to assess the challenges faced by insurance companies, pension plan participants, and market participants in general, by changing the regulatory requirements. Additionally, they consider the issues related to high-frequency trading and statistical arbitrage in particular, and explore the use of such data to asses risk and volatility in financial markets

Assessing the Reliability, Resilience and Sustainability of Water Resources Systems in Data-rich and Data-sparse Regions

Uncertainty associated with the potential impact of climate change on supply availability, varied success with demand-side interventions such as water efficiency and changes in priority relating to hydrometric data collection and ownership, have resulted in challenges for water resources system management particularly in data-sparse regions. Consequently, the aim of this thesis is to assess the reliability, resilience and sustainability of water resources systems in both data-rich and data-sparse regions with an emphasis on robust decision-making in data-sparse regions. To achieve this aim, new resilience indicators that capture water resources system failure duration and extent of failure (i.e. failure magnitude) from a social and environmental perspective were developed. These performance indicators enabled a comprehensive assessment of a number of performance enhancing interventions, which resulted in the identification of a set of intervention strategies that showed potential to improve reliability, resilience and sustainability in the case studies examined. Finally, a multi-criteria decision analysis supported trade-off decision making when the reliability, resilience and sustainability indicators were considered in combination. Two case studies were considered in this research: Kingston and St. Andrew in Jamaica and Anyplace in the UK. The Kingston and St. Andrew case study represents the main data-sparse case study where many assumptions were introduced to fill data gaps. The intervention strategy that showed great potential to improve reliability, resilience and sustainability identified from Kingston and St. Andrew water resources assessment was the ‘Site A-east’ desalination scheme. To ameliorate uncertainty and lack of confidence associated with results, a methodology was developed that transformed a key proportion of the Anyplace water resources system from a data-rich environment to a data-sparse environment. The Anyplace water resources system was then assessed in a data-sparse environment and the performance trade-offs of the intervention strategies were analysed using four multi-criteria decision analysis (MCDA) weighting combinations. The MCDA facilitated a robust comparison of the interventions’ performances in the data-rich and data-sparse case studies. Comparisons showed consistency in the performances of the interventions across data-rich and data-sparse hydrological conditions and serve to demonstrate to decision makers a novel approach to addressing uncertainty when many assumptions have been introduced in the water resources management process due to data sparsity.Commonwealth Scholarship Commission in the U