817 resultados para Volatility


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This study examines the effect of the Great Moderation on the relationship between U.S. output growth and its volatility over the period 1947 to 2006. First, we consider the possible effects of structural change in the volatility process. In so doing, we employ GARCH-M and ARCH-M specifications of the process describing output growth rate and its volatility with and without a one-time structural break in volatility. Second, our data analyses and empirical results suggest no significant relationship between the output growth rate and its volatility, favoring the traditional wisdom of dichotomy in macroeconomics. Moreover, the evidence shows that the time-varying variance falls sharply or even disappears once we incorporate a one-time structural break in the unconditional variance of output starting 1982 or 1984. That is, the integrated GARCH effect proves spurious. Finally, a joint test of a trend change and a one-time shift in the volatility process finds that the one-time shift dominates.

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Previous studies (e.g., Hamori, 2000; Ho and Tsui, 2003; Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Bai and Perronâs (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility.

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This paper empirically assesses whether monetary policy affects real economic activity through its affect on the aggregate supply side of the macroeconomy. Analysts typically argue that monetary policy either does not affect the real economy, the classical dichotomy, or only affects the real economy in the short run through aggregate demand new Keynesian or new classical theories. Real business cycle theorists try to explain the business cycle with supply-side productivity shocks. We provide some preliminary evidence about how monetary policy affects the aggregate supply side of the macroeconomy through its affect on total factor productivity, an important measure of supply-side performance. The results show that monetary policy exerts a positive and statistically significant effect on the supply-side of the macroeconomy. Moreover, the findings buttress the importance of countercyclical monetary policy as well as support the adoption of an optimal money supply rule. Our results also prove consistent with the effective role of monetary policy in the Great Moderation as well as the more recent rise in productivity growth.

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This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the four countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the unconditional variance of output growth. One structural break exists in each of the four countries. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

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The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^

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This paper is an empirical investigation of the relationship between exchange rate volatility and international trade, focusing on East Asia. It finds that intra-East Asian trade is discouraged by exchange rate volatility more seriously than trade in other regions because intermediate goods trade in production networks, which is quite sensitive to exchange rate volatility compared with other types of trade, occupies a significant fraction of trade. In addition, this negative effect of volatility is mainly induced by the unanticipated volatility and has an even greater impact than that of tariffs.

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In recent years, a large and expanding literature has examined the properties of developing economies with regard to the macroeconomic cycle.1 One such property that is characteristic of developing economies is large fluctuations in consumption. Meanwhile, aid for the low income countries is extremely volatile, and under certain circumstances, the volatile aid amplifies the consumption volatility. This document examines whether it is possible that the volatile aid yields high consumption volatility in African countries that constitute the majority of the low income countries. Our numerical analysis reveals that the strongly influential aid disbursements yield a considerably large fluctuation in consumption.

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Two groups of questions were addressed in this paper: (1) Is voter punishment of the incumbent the primary factor in electoral volatility? Are there any other types of vote swings that underlie volatility? (2) In general, does a decline in economic growth destabilize voter behavior? If so, what kinds of vote swings does an economic downturn tend to generate? Provincial-level panel data analysis yielded the following results: (1) Changes in volatility is primarily due to vote swings from the incumbent to the opposition and also to and from left-wing and right-wing parties. (2) Lower economic growth increases electoral volatility. Economic decline induces vote swings not only from the government to the opposition but also from left-wing to right-wing parties. This is probably because right-wing parties seem more concerned with economic issues and are thus more popular than left-wing parties with lower-income voters.

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In recent years fractionally differenced processes have received a great deal of attention due to its flexibility in financial applications with long memory. This paper considers a class of models generated by Gegenbauer polynomials, incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the statistical properties of the new model, suggest using the spectral likelihood estimation for long memory processes, and investigate the finite sample properties via Monte Carlo experiments. We apply the model to three exchange rate return series. Overall, the results of the out-of-sample forecasts show the adequacy of the new GLMSV model.

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We analyse volatility spillovers in EMU sovereign bond markets. First, we examine the unconditional patterns during the full sample (April 1999-January 2014) using a measure recently proposed by Diebold and Yılmaz (2012). Second, we make use of a dynamic analysis to evaluate net directional volatility spillovers for each of the eleven countries under study, and to determine whether core and peripheral markets present differences. Finally, we apply a panel analysis to empirically investigate the determinants of net directional spillovers of this kind.

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This paper examines the sources of real exchange rate (RER) volatility in eighty countries around the world, during the period 1970 to 2011. Our main goal is to explore the role of nominal exchange rate regimes and financial crises in explaining the RER volatility. To that end, we employ two complementary procedures that consist in detecting structural breaks in the RER series and decomposing volatility into its permanent and transitory components. The results confirm that exchange rate volatility does increase with the global financial crises and detect the existence of an inverse relationship between the degree of flexibility in the exchange rate regime and RER volatility using a de facto exchange rate classification.

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The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

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There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices.