A framework for valuing derivative securities

This paper develops a general framework for valuing a wide range of derivative securities. Rather than focusing on the stochastic process of the underlying security and developing an instantaneously-riskless hedge portfolio, we focus on the terminal distribution of the underlying security. This enables the derivative security to be valued as the weighted sum of a number of component pieces. The component pieces are simply the different payoffs that the security generates in different states of the world, and they are weighted by the probability of the particular state of the world occurring. A full set of derivations is provided. To illustrate its use, the valuation framework is applied to plain-vanilla call and put options, as well as a range of derivatives including caps, floors, collars, supershares, and digital options.

A duration e um modelo alternativo: um teste empírico

Estratégias de hedge para portfólios de renda fixa são comumente baseadas na duration. Esse conceito foi desenvolvido tendo como pressuposto que alterações nas taxas de juros serão constantes para toda a estrutura a termo da yield curve, ou seja, que os deslocamentos na yield curve serão paralelos. Este artigo pretende testar esse pressuposto para o mercado futuro de DI1 da BM&F, tendo como base o ano de 1996. Além disso, o artigo compara estratégias de hedge baseadas na duration com estratégias cujo balanceamento é dado por um modelo alternativo que incorpora os efeitos de deslocamentos não-paralelos na yield curve.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Análise de clusters e volatilidade de índices de acções

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Futuros financeiros: uma abordagem aos commodities de algodão

Dissertação de Mestrado Apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Mestre José Carlos Pedro

Contratos de Futuros sobre Taxas de Juro

Mestrado em Contabilidade Internacional

A trader portfolio optimization of bilateral contracts in electricity retail markets

Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

How can Public Administrations handle the societal crisis?

Comunicação apresentada na Universidade de Wroclow.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees : the PredictAL study

Background: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score >= 8 in men and >= 5 in women. Results: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

Impact of Black-Scholes assumptions on Delta Hedging

In this work we are going to evaluate the different assumptions used in the Black- Scholes-Merton pricing model, namely log-normality of returns, continuous interest rates, inexistence of dividends and transaction costs, and the consequences of using them to hedge different options in real markets, where they often fail to verify. We are going to conduct a series of tests in simulated underlying price series, where alternatively each assumption will be violated and every option delta hedging profit and loss analysed. Ultimately we will monitor how the aggressiveness of an option payoff causes its hedging to be more vulnerable to profit and loss variations, caused by the referred assumptions.

Carry and trend-following strategies

Recent research has shown that carry and trend strategies when combined lead to significant risk-adjusted returns that can be very attractive to investors, at a low cost with small and positive skewness. This study proposes to combine both carry and trend-following, considering a data set of ten years (09/2005-09/2015), within a portfolio composed by three major asset classes: currencies, commodities and equity indices. Following a futures-based methodology, the obtained results show that, indeed, the strategy results inevitably in higher returns and greater sharpe ratios for every asset class in study. This outcome results from the fact that trend proved to provide a significant hedge to the downside risk that carry is exposed to.

Geometria da valva mitral derivada da ressonância magnética cardiovascular na avaliação da gravidade da regurgitação mitral

FUNDAMENTO: A regurgitação mitral é a doença valvar cardíaca mais comum em todo o mundo. A ressonância magnética pode ser uma ferramenta útil para analisar os parâmetros da valva mitral. OBJETIVO: diferenciar padrões geométricos da valva mitral em pacientes com diferentes gravidades por regurgitação mitral (RM) com base na ressonância magnética cardiovascular. MÉTODOS: Sessenta e três pacientes foram submetidos à ressonância magnética cardiovascular. Os parâmetros da valva mitral analisados foram: área (mm2) e ângulo (graus) de tenting, altura do ventrículo (mm), altura do tenting (mm), folheto anterior, comprimento posterior do folheto (leaflet) e diâmetro do anulo (mm). Os pacientes foram divididos em dois grupos, um incluindo pacientes que necessitaram de cirurgia da valva mitral e o outro os que não. RESULTADOS: Trinta e seis pacientes apresentaram de RM discreta a leve (1-2+) e 27 RM de moderada a grave (3-4+). Dez (15,9%) dos 63 pacientes foram submetidos à cirurgia. Pacientes com RM mais grave tiveram maior diâmetro sistólico final do ventrículo esquerdo (38,6 ± 10,2 vs. 45,4 ± 16,8, p < 0,05) e diâmetro diastólico final esquerdo (52,9 ± 6,8 vs. 60,1 ± 12,3, p = 0,005). Na análise multivariada, a área de tenting foi a determinante mais forte de gravidade de RM (r = 0,62, p = 0,035). Comprimento do anulo (36,1 ± 4,7 vs. 41 ± 6,7, p< 0,001), área de tenting (190,7 ± 149,7 vs. 130 ± 71,3, p= 0,048) e comprimento do folheto posterior (15,1 ± 4,1 vs. 12,2 ± 3,5, p= 0,023) foram maiores em pacientes que precisaram de cirurgia da valva mitral. CONCLUSÕES: Área de tenting, anulo e comprimento do folheto posterior são possíveis determinantes da gravidade da RM. Estes parâmetros geométricos podem ser usados para individualizar a gravidade e, provavelmente, no futuro, orientar o tratamento do paciente com base na anatomia individual do aparelho mitral.

The long run relationship between stock prices and goods prices: new evidence from panel cointegration

We examine the long run relationship between stock prices and goods prices to gauge whether stock market investment can hedge against inflation. Data from sixteen OECD countries over the period 1970-2006 are used. We account for different inflation regimes with the use of sub-sample regressions, whilst maintaining the power of tests in small sample sizes by combining time-series data across our sample countries in a panel unit root and panel cointegration econometric framework. The evidence supports a positive long-run relationship between goods prices and stock prices with the estimated goods price coefficient being in line with the generalized Fisher hypothesis.