Financial Engineering Instruments and their Assessment Under EU State Aid Rules. Bruges European Economic Policy (BEEP) Briefing 26/2013

Financial engineering instruments such as guarantees, loans and equity are increasingly used in public funding of enterprises. These instruments have three attractive features: they are repayable, they “leverage” private involvement, and they have a multiplier effect because they generate new income. At the same time, however, they are technically complex and they are subject to state aid rules. Their assessment under EU state aid rules creates two additional problems. First, under certain conditions financial instruments may not contain state aid. This is when public authorities act as “private investors”. This means that state aid cannot be presumed to exist in all financial instruments. It must first be established through market analysis. Second, when state aid is found to be present it is not always possible to quantify it. For this reason the state aid rules that apply to financial instruments differ significantly from other rules. This paper reviews how financial instruments have been assessed by the European Commission and under which conditions the state aid they may contain can be considered to be compatible with the internal market. The paper finds that by and large Member States have succeeded to design measures that have all been approved by the Commission.

Forecasting daily volatility using high frequency financial data

Aiming at empirical findings, this work focuses on applying the HEAVY model for daily volatility with financial data from the Brazilian market. Quite similar to GARCH, this model seeks to harness high frequency data in order to achieve its objectives. Four variations of it were then implemented and their fit compared to GARCH equivalents, using metrics present in the literature. Results suggest that, in such a market, HEAVY does seem to specify daily volatility better, but not necessarily produces better predictions for it, what is, normally, the ultimate goal. The dataset used in this work consists of intraday trades of U.S. Dollar and Ibovespa future contracts from BM&FBovespa.

Modelling financial time series with switching state space models

The deficiencies of stationary models applied to financial time series are well documented. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly appropriate for financial markets. We use a dynamic switching (modelled by a hidden Markov model) combined with a linear dynamical system in a hybrid switching state space model (SSSM) and discuss the practical details of training such models with a variational EM algorithm due to [Ghahramani and Hilton,1998]. The performance of the SSSM is evaluated on several financial data sets and it is shown to improve on a number of existing benchmark methods.

O contrato de Project Finance

Currently, Angola portrays a notorious economic growth and due to recent innovative legislations, it has become the major investment attracting pole, especially in Sub-Saharan Africa, having, thus, an extraordinary potentiality for a rapid and sustainable development, likely to place her in outstanding positions in the world economic ranking. Yet, such economic growth entails demanding levels of intensive investment in infrastructure, what has been reported of the Angolan Government to be unable to respond to, save if recurring to very high index of external debt, poisoning, in this way, the future budgeting of the country. Due to these infrastructure investment shortages, the cost of production remains highly onerous and the cost of life extremely unaffordable. On this account, the current study disserts about the contract of Project Finance; an alternative finance resource given as a viable solution for the private financing of infrastructure, aiming to demonstrate that such contractual figure, likewise the experience of several emerging economies and others, is a contract bid framework to take into account in today’s world. It refers to a financing technique – through which the Government may satisfy a common need (for example, the construction of a public domain or public servicing), without having to pay neither offer any collateral – based on a complex legal-financial engineering, arranged throughout a coalition of typical and atypical agreements, whereby it is mandatory to look back at the basic concepts of corporate law. More than just a simple financial study, the dissertation at stake analyses the nature and legal framework of Project Finance, which is a legally atypical and innominate contract, concluding that there is a relevant need for regulating and devoting a special legal regime in the Angolan jurisdiction for this promising legal form in the contemporary corporate finance world.

How to bring equity investors to the social sector? A quasi-equity approach through the case study of SPEAK

As nonprofits do not have access to the same capital markets as for-profit enterprises, organizations usually scramble for funding to keep up with their mission. This scenario can be changed through the use of the right financial engineering. This Work Project aims at studying an innovative financing mechanism based on the concept of quasi-equity for organizations devoted to social ends to cope with their capital needs. A quasi-equity investment model is built for the Portuguese social business SPEAK, and an in-depth assessment of its current financial, organizational and impact situations is conducted. This is a pioneer case study in Portugal.

Economic Impact of Identity Theft in India: Lessons from Western Countries

In this computerized, globalised and internet world our computer collects various types of information’s about every human being and stores them in files secreted deep on its hard drive. Files like cache, browser history and other temporary Internet files can be used to store sensitive information like logins and passwords, names addresses, and even credit card numbers. Now, a hacker can get at this information by wrong means and share with someone else or can install some nasty software on your computer that will extract your sensitive and secret information. Identity Theft posses a very serious problem to everyone today. If you have a driver’s license, a bank account, a computer, ration card number, PAN card number, ATM card or simply a social security number you are more than at risk, you are a target. Whether you are new to the idea of ID Theft, or you have some unanswered questions, we’ve compiled a quick refresher list below that should bring you up to speed. Identity theft is a term used to refer to fraud that involves pretending to be someone else in order to steal money or get other benefits. Identity theft is a serious crime, which is increasing at tremendous rate all over the world after the Internet evolution. There is widespread agreement that identity theft causes financial damage to consumers, lending institutions, retail establishments, and the economy as a whole. Surprisingly, there is little good public information available about the scope of the crime and the actual damages it inflicts. Accounts of identity theft in recent mass media and in film or literature have centered on the exploits of 'hackers' - variously lauded or reviled - who are depicted as cleverly subverting corporate firewalls or other data protection defenses to gain unauthorized access to credit card details, personnel records and other information. Reality is more complicated, with electronic identity fraud taking a range of forms. The impact of those forms is not necessarily quantifiable as a financial loss; it can involve intangible damage to reputation, time spent dealing with disinformation and exclusion from particular services because a stolen name has been used improperly. Overall we can consider electronic networks as an enabler for identity theft, with the thief for example gaining information online for action offline and the basis for theft or other injury online. As Fisher pointed out "These new forms of hightech identity and securities fraud pose serious risks to investors and brokerage firms across the globe," I am a victim of identity theft. Being a victim of identity theft I felt the need for creating an awareness among the computer and internet users particularly youngsters in India. Nearly 70 per cent of Indian‘s population are living in villages. Government of India already started providing computer and internet facilities even to the remote villages through various rural development and rural upliftment programmes. Highly educated people, established companies, world famous financial institutions are becoming victim of identity theft. The question here is how vulnerable the illiterate and innocent rural people are if they suddenly exposed to a new device through which some one can extract and exploit their personal data without their knowledge? In this research work an attempt has been made to bring out the real problems associated with Identity theft in developed countries from an economist point of view.

Enterprise intelligence: searching for a single version of the truth

Multiple versions of information and associated problems are well documented in both academic research and industry best practices. Many solutions have proposed a single version of the truth, with Business intelligence being adopted by many organizations. Business Intelligence (BI), however, is largely based on the collection of data, processing and presentation of information to meet different stakeholders’ requirement. This paper reviews the promise of Enterprise Intelligence, which promises to support decision-making based on a defined strategic understanding of the organizations goals and a unified version of the truth.

Normas internacionais de contabilidade: percepções dos peritos criminais federais sobre os impactos de sua adoção na atividade de perícia oficial realizada em fraudes contábeis no Brasil

Os impactos da adoção das Normas Internacionais de Contabilidade (IFRSs) tem sido objeto de debates nos meios profissionais e acadêmicos, entretanto, pouco tem sido pesquisado sobre as repercussões da adoção dos IFRSs na atividade pericial criminal. Portanto, o objetivo deste estudo é captar e analisar a percepção dos Peritos Criminais Federais sobre os impactos da adoção dos IFRSs na atividade de perícia criminal oficial realizada em fraudes contábeis. Lastreou-se numa abordagem quantitativa e qualitativa utilizada para verificar associações entre as percepções, recorrendo-se ao teste Qui-quadrado de Pearson e a análise de conteúdo, respectivamente. Os resultados evidenciaram que a maior parte dos respondentes concorda parcial ou totalmente que a adoção dos IFRSs facilitará o trabalho de perícia criminal federal, encontrando associação estatística com a percepção de que fraudes cometidas sem engenharia financeira são mais fáceis de comprovar e com a percepção que um maior espaço para julgamentos técnicos tem impacto positivo na atividade de perícia criminal. Outros benefícios apontados foram o aumento da comparabilidade, a diminuição da complexidade e a valorização profissional. Entretanto, constatou-se como riscos a possibilidade de aumento nas contestações técnicas aos laudos periciais, o risco de viés e a necessidade de qualificação, porém sem associação estatística com a percepção de que os IFRSs facilitarão ou não o trabalho pericial. Não foram identificadas diferenças estatísticas de percepção em função do nível de conhecimento dos preceitos sobre os IFRSs e dos conhecimentos teóricos e práticos dos pesquisados. O estudo apresenta limitações que dizem respeito principalmente à generalização dos resultados, uma vez que a abordagem pretendida foi qualitativa e quantitativa e o número de questionários respondidos não possibilitou realizar testes estatísticos com maior robustez.

Analysis of the Iberian electricity forward market hedging efficiency

An assessment of the hedging performance in the Iberian Forward Electricity Market is performed. Aggregated data from the Portuguese and Spanish clearing houses for energy derivatives are considered. The hedging performance is measured through the ratio of the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). This hedging ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation.

Energy forward price prediction with a hybrid adaptive model

This paper presents a forecasting technique for forward electricity/gas prices, one day ahead. This technique combines a Kalman filter (KF) and a generalised autoregressive conditional heteroschedasticity (GARCH) model (often used in financial forecasting). The GARCH model is used to compute next value of a time series. The KF updates parameters of the GARCH model when the new observation is available. This technique is applied to real data from the UK energy markets to evaluate its performance. The results show that the forecasting accuracy is improved significantly by using this hybrid model. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

Aplicaciones de los modelos de predicción bio-inspirados en la administración

Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.