8 resultados para Low Volatility Options
em Repositório digital da Fundação Getúlio Vargas - FGV
Resumo:
O cenário de continuo aumento do consumo de derivados do petróleo aliado a conscientização de que é necessário existir um equilíbrio com relação a exploração de recursos naturais e preservação do meio ambiente, vem impulsionando a busca por fontes alternativas de energia. Esse crescente interesse vem se aplicando a geração de energia a partir de biomassa da cana de açúcar, que vem se tornando cada vez mais comuns no Brasil, porém ainda existe um imenso potencial a ser explorado. Dentro deste contexto, se torna relevante a tomada de decisão de investimentos em projetos de cogeração e este trabalho busca incrementar a analise e tomada de decisão com a utilização da Teoria das Opções Reais, uma ferramenta de agregação de valor às incertezas, cabendo perfeitamente ao modelo energético brasileiro, onde grandes volatilidades do preço de energia são observadas ao longo dos anos. O objetivo do trabalho é determinar o melhor momento para uma biorrefinaria investir em unidades de cogeração. A estrutura do trabalho foi dividida em três cenários de porte de biorrefinarias, as de 2 milhões de capacidade de moagem de cana-de-açúcar por ano, as de 4 milhões e as de 6 milhões, visando assim ter uma representação amostral das biorrefinarias do país. Além disso, analisaram-se três cenários de volatilidade atrelados ao preço futuro de energia, dado que a principal variável de viabilização deste tipo de projeto é o preço de energia. As volatilidades foram calculadas de acordo com histórico do ambiente regulado, o dobro do ambiente regulado e projeção de PLD, representando, respectivamente, níveis baixos, médios e altos, de volatilidade do preço de energia. Após isso, foram elaboradas as nove árvores de decisão, que demonstram para os gestores de investimento que em um cenário de baixa volatilidade cria-se valor estar posicionado e ter a opção real de investir ou adiar investimento para qualquer porte de usina. No cenário de média volatilidade de preço, aconselha-se ao gestor estar posicionado em usinas de médio a grande porte para viabilização do investimento. Por fim, quando o cenário de preços é de grande volatilidade, tem-se um maior risco e existe a maior probabilidade de viabilização do investimento em usinas de grande porte.
Resumo:
This paper develops a methodology for testing the term structure of volatility forecasts derived from stochastic volatility models, and implements it to analyze models of S&P500 index volatility. U sing measurements of the ability of volatility models to hedge and value term structure dependent option positions, we fmd that hedging tests support the Black-Scholes delta and gamma hedges, but not the simple vega hedge when there is no model of the term structure of volatility. With various models, it is difficult to improve on a simple gamma hedge assuming constant volatility. Ofthe volatility models, the GARCH components estimate of term structure is preferred. Valuation tests indicate that all the models contain term structure information not incorporated in market prices.
Resumo:
Os mercados de derivativos são vistos com muita desconfiança por inúmeras pessoas. O trabalho analisa o efeito da introdução de opções sobre ações no mercado brasileiro buscando identificar uma outra justificativa para a existência destes mercados: a alteração no nível de risco dos ativos objetos destas opções. A evidência empírica encontrada neste mercado está de acordo com os resultados obtidos em outros mercados - a introdução de opções é benéfica para o investidor posto que reduz a volatilidade do ativo objeto. Existe também uma tênue indicação de que a volatilidade se torna mais estocástica com a introdução das opções.
Resumo:
We compare three frequently used volatility modelling techniques: GARCH, Markovian switching and cumulative daily volatility models. Our primary goal is to highlight a practical and systematic way to measure the relative effectiveness of these techniques. Evaluation comprises the analysis of the validity of the statistical requirements of the various models and their performance in simple options hedging strategies. The latter puts them to test in a "real life" application. Though there was not much difference between the three techniques, a tendency in favour of the cumulative daily volatility estimates, based on tick data, seems dear. As the improvement is not very big, the message for the practitioner - out of the restricted evidence of our experiment - is that he will probably not be losing much if working with the Markovian switching method. This highlights that, in terms of volatility estimation, no clear winner exists among the more sophisticated techniques.
Resumo:
Estimating the parameters of the instantaneous spot interest rate process is of crucial importance for pricing fixed income derivative securities. This paper presents an estimation for the parameters of the Gaussian interest rate model for pricing fixed income derivatives based on the term structure of volatility. We estimate the term structure of volatility for US treasury rates for the period 1983 - 1995, based on a history of yield curves. We estimate both conditional and first differences term structures of volatility and subsequently estimate the implied parameters of the Gaussian model with non-linear least squares estimation. Results for bond options illustrate the effects of differing parameters in pricing.
Resumo:
This paper studies how constraints on the timing of actions affect equilibrium in intertemporal coordination problems. The model exhibits a unique symmetric equilibrium in cut-o¤ strategies. The risk-dominant action of the underlying one-shot game is selected when the option to delay effort is commensurate with the option to wait longer for others' actions. The possibility of waiting longer for the actions of others enhances coordination, but the option of delaying one s actions can induce severe coordination failures: if agents are very patient, they might get arbitrarily low expected payoffs even in cases where coordination would yield arbitrarily large returns.
Resumo:
This paper performs a thorough statistical examination of the time-series properties of the daily market volatility index (VIX) from the Chicago Board Options Exchange (CBOE). The motivation lies not only on the widespread consensus that the VIX is a barometer of the overall market sentiment as to what concerns investors' risk appetite, but also on the fact that there are many trading strategies that rely on the VIX index for hedging and speculative purposes. Preliminary analysis suggests that the VIX index displays long-range dependence. This is well in line with the strong empirical evidence in the literature supporting long memory in both options-implied and realized variances. We thus resort to both parametric and semiparametric heterogeneous autoregressive (HAR) processes for modeling and forecasting purposes. Our main ndings are as follows. First, we con rm the evidence in the literature that there is a negative relationship between the VIX index and the S&P 500 index return as well as a positive contemporaneous link with the volume of the S&P 500 index. Second, the term spread has a slightly negative long-run impact in the VIX index, when possible multicollinearity and endogeneity are controlled for. Finally, we cannot reject the linearity of the above relationships, neither in sample nor out of sample. As for the latter, we actually show that it is pretty hard to beat the pure HAR process because of the very persistent nature of the VIX index.
Resumo:
There is strong empirical evidence that risk premia in long-term interest rates are time-varying. These risk premia critically depend on interest rate volatility, yet existing research has not examined the im- pact of time-varying volatility on excess returns for long-term bonds. To address this issue, we incorporate interest rate option prices, which are very sensitive to interest rate volatility, into a dynamic model for the term structure of interest rates. We estimate three-factor affine term structure models using both swap rates and interest rate cap prices. When we incorporate option prices, the model better captures interest rate volatility and is better able to predict excess returns for long-term swaps over short-term swaps, both in- and out-of-sample. Our results indicate that interest rate options contain valuable infor- mation about risk premia and interest rate dynamics that cannot be extracted from interest rates alone.