48 resultados para stochastic volatility diffusions


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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.

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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.

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O objetivo deste trabalho é revisar os principais aspectos teóricos para a aplicação de Opções Reais em avaliação de projetos de investimento e analisar, sob esta metodologia, um caso real de projeto para investir na construção de uma Planta de Liquefação de gás natural. O estudo do caso real considerou a Opção de Troca de Mercado, ao avaliar a possibilidade de colocação de cargas spot de GNL em diferentes mercados internacionais e a Opção de Troca de Produto, devido à flexibilidade gerencial de não liquefazer o gás natural, deixando de comercializar GNL no mercado internacional e passando a vender gás natural seco no mercado doméstico. Para a valoração das Opções Reais foi verificado, através da série histórica dos preços de gás natural, que o Movimento Geométrico Browniano não é rejeitado e foram utilizadas simulações de Monte Carlo do processo estocástico neutro ao risco dos preços. O valor da Opção de Troca de Mercado fez o projeto estudado mais que dobrar de valor, sendo reduzido com o aumento da correlação dos preços. Por outro lado, o valor da Opção de Troca de Produto é menos relevante, mas também pode atingir valores significativos com o incremento de sua volatilidade. Ao combinar as duas opções simultaneamente, foi verificado que as mesmas não são diretamente aditivas e que o efeito do incremento da correlação dos preços, ao contrário do que ocorre na Opção de Troca de Mercado, é inverso na Opção de Troca de Produto, ou seja, o derivativo aumenta de valor com uma maior correlação, apesar do valor total das opções integradas diminuir.

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li consumption is log-Normal and is decomposed into a linear deterministic trend and a stationary cycle, a surprising result in business-cycle research is that the welfare gains of eliminating uncertainty are relatively small. A possible problem with such calculations is the dichotomy between the trend and the cyclical components of consumption. In this paper, we abandon this dichotomy in two ways. First, we decompose consumption into a deterministic trend, a stochastic trend, and a stationary cyclical component, calculating the welfare gains of cycle smoothing. Calculations are carried forward only after a careful discussion of the limitations of macroeconomic policy. Second, still under the stochastic-trend model, we incorporate a variable slope for consumption depending negatively on the overall volatility in the economy. Results are obtained for a variety of preference parameterizations, parameter values, and different macroeconomic-policy goals. They show that, once the dichotomy in the decomposition in consumption is abandoned, the welfare gains of cycle smoothing may be substantial, especially due to the volatility effect.

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In a general equilibrium model. we show that the value of the equilibrium real exchange rate is affected by its own volatility. Risk averse exporters. that make their exporting decision before observing the realization of the real exchange rate. choose to export less the more volatile is the real exchange rate. Therefore the trude balance and the variance of the real exchange rate are negatively related. An increase in the volatility of the real exchange rate for instance deteriorates the trade balance and to restore equilibrium a real exchange rate depreciation has to take place. In the empirical part of the paper we use the traditional (unconditional) standard deviation of RER changes as our measure of RER volatility.We describe the behavior of the RER volatility for Brazil,Argentina and Mexico.Monthly data for the three countries are used. and also daily data for Bruzil. Interesting patterns of volatility could be associated to the nature of the several stabilization plans adopted in those countries and to changes in the exchange rate regimes .

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A evidência empírica aponta que Termos de Troca é uma variável relevante tanto para dinâmica macroeconômica como para o risco de default em países emergentes. No entanto, a literatura de dívida soberana baseada nos trabalhos de Eaton e Gerzovitz (1981) e Arellano (2008) ainda não explorou de forma adequada as conecções entre a dinâmica de termos de troca e incentivos ao default. Nós contribuímos nessa área, introduzindo volatilidade de Termos de Troca no modelo proposto por Mendoza e Yue (2012), no qual as decisões de dívida soberana são vinculadas à um modelo de equilíbrio geral para a economia doméstica. Nós encontramos que uma economia exposta à volatilidade dos termos de troca consegue produzir uma variabilidade do consumo que supera significativamente a variabilidade do produto, característica que constitui um fato estilizado chave de business cycles de países emergentes. Nossos exercícios também mostram que decisões de default são geradas por mudanças bruscas nos termos de troca, mas não necessariamente estão vinculados à estados ruins da economia.

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Este trabalho estuda se existe impacto na volatilidade dos mercados de ações em torno das eleições nacionais nos países da OCDE e nos países em Desenvolvimento. Ao mesmo tempo, pretende, através de variáveis explicativas, descobrir os fatores responsáveis por esse impacto. Foi descoberta evidência que o impacto das eleições na volatilidade dos mercados de ações é maior nos países em Desenvolvimento. Enquanto as eleições antecipadas, a mudança na orientação política e o tamanho da população foram os factores que explicaram o aumento da volatilidade nos países da OCDE, o nível democrático, número de partidos da coligação governamental e a idade dos mercados foram os factores explicativos para os países em Desenvolvimento.

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Trabalho apresentado no XXXV CNMAC, Natal-RN, 2014.

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Trabalho apresentado no 37th Conference on Stochastic Processes and their Applications - July 28 - August 01, 2014 -Universidad de Buenos Aires

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Trabalho apresentado no International Conference on Scientific Computation And Differential Equations 2015

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We study the relationship between the volatility and the price of stocks and the impact that variables such as past volatility, financial gearing, interest rates, stock return and turnover have on the present volatility of these securities. The results show the persistent behavior of volatility and the relationship between interest rate and volatility. The results also showed that a reduction in stock prices are associated with an increase in volatility. Finally we found a greater trading volume tends to increase the volatility.

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We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

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We consider risk-averse convex stochastic programs expressed in terms of extended polyhedral risk measures. We derive computable con dence intervals on the optimal value of such stochastic programs using the Robust Stochastic Approximation and the Stochastic Mirror Descent (SMD) algorithms. When the objective functions are uniformly convex, we also propose a multistep extension of the Stochastic Mirror Descent algorithm and obtain con dence intervals on both the optimal values and optimal solutions. Numerical simulations show that our con dence intervals are much less conservative and are quicker to compute than previously obtained con dence intervals for SMD and that the multistep Stochastic Mirror Descent algorithm can obtain a good approximate solution much quicker than its nonmultistep counterpart. Our con dence intervals are also more reliable than asymptotic con dence intervals when the sample size is not much larger than the problem size.