the message in weekly exchange rates in the european monetary system mean reversion conditional heteroscedasticity and jumps weekly rates of the european monetary system ems vis a vis the deutsche mark from april 1979 to march 1991 are modeled as a combined ma 1 garch 1 1 jump process the moving average ma part accounts for mean reversion required for the rates to stay inside the target zone the generalized autoregressive conditional heteroscedasticity garch part accounts for changing volatility whereas the jump process models parity changes and other erratic movements using an adjusted pearson chi squared goodness of fit test we find similar results for the bernoulli and the poisson jump processes in those cases in which the bernoulli normal distribution does not pass the goodness of fit test a mixture of three normals does finally the ma 1 garch 1 1 bernoulli jump models are jointly estimated assuming a constant contemporaneous correlation matrix for the disturbances and a common jump probability for all the currencies

modeling the co movements between crude oil and refined petroleum markets abstract in this paper we investigate two types of asymmetries i e the asymmetry in the lower and upper tail dependences and the asymmetry in the propagation of crisis bubble between crude oil market and refined petroleum markets based on copula models thirteen copula models with different types of dependence structures and time varying dependence parameters are considered we find that in general the malm copula fits our sample data best based on aic criterion we find that lower and upper tail dependences are both positive indicating that crude oil and refined product markets tend to move together using the asymmetric copulas we find asymmetry in tail dependence between crude oil and heating oil returns and that between crude oil and jet fuel returns interestingly upper tail dependence is significantly greater than the lower tail dependence for the pre crisis period while the result is reversed for the post crisis period finally although our data prefers the nonexchangeable malm copula the asymmetry in the propagation of crisis bubble between crude oil and refined product returns is very weak

forecasting portfolio value at risk with nonparametric lower tail dependence estimates abstract we propose to forecast the value at risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence we compare our proposed method to a conventional copula garch model where the parameter of a clayton copula is estimated via canonical maximum likelihood the superiority of our proposed model is exemplified by analyzing a data sample of nine different bivariate and one nine dimensional financial portfolio a comparison of the out of sample forecasting accuracy of both models confirms that our model yields economically significantly better value at risk forecasts than the competing parametric calibration strategy

linear time varying regression with copula dcc garch models for volatility abstractthis article provides a new linear state space model with time varying parameters for forecasting financial volatility the volatility estimates obtained from the model by using the us stock market data almost exactly match the realized volatility we further compare our model with traditional volatility models in the ex post volatility forecast evaluations in particular we use the superior predictive ability and the reality check for data snooping evidence can be found supporting that our simple but powerful regression model provides superior forecasts for volatility

correlations in price changes and volatility across international stock markets the short run interdependence of prices and price volatility across three major international stock markets is studied daily opening and closing prices of major stock indexes for the tokyo london and new york stock markets are examined the analysis utilizes the autoregressive conditionally heteroskedastic arch family of statistical models to explore these pricing relationships evidence of price volatility spillovers from new york to tokyo london to tokyo and new york to london is observed but no price volatility spillover effects in other directions are found for the pre october 1987 period article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

superfund cleanups and infant health in 1980 outcry over the health effects of toxic waste in love canal new york resulted in the comprehensive environmental response compensation and liability act which became known as superfund superfund was intended to provide a mechanism for conducting remedial clean ups at the most dangerous hazardous waste sites over the years it became the largest and most expensive federal program to deal with toxic waste in the us given the substantial cost and slow rate of clean up there is considerable debate on whether it is in the public interest to continue the program in its current form epa 2006 while the costs of the programs are clear its benefits are not well understood indeed the policy is controversial in part because there is a paucity of reliable information on the program s benefits some previous studies find poorer birth outcomes near a site while others do not see martine vrijheid 2000 however evidence of a correlation between proximity to a site and poor birth outcomes does not necessarily represent a causal effect because populations living near hazardous waste sites are typically different from the general population and their health outcomes are likely to differ even in the absence of negative health effects from exposure for example michael greenstone and justin gallagher 2008 found that residents of areas near hazardous waste sites are more likely to be poor and have lower levels of education than others our project is the first to examine the effect of site cleanups on infant health rather than simply focusing on proximity to a site we focus on single births that occurred within 5km of a superfund site between 1989 and 2003 in five large states florida michigan new jersey pennsylvania and texas the basis of our difference in differences approach is to compare changes in birth outcomes before and after a site s clean up among births to mothers who live within 2 000 meters of the site and among those who live between 2 000 and 5 000 meters away our approach is made feasible by access to confidential vital statistics data that includes the exact street address of the mother s residence our large sample gives us statistical power to detect small effects

a copula garch approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate product price arbitrage and crude oil price abstract global liquefied petroleum gas lpg trade shows an increasing trend but is under researched this paper focuses on the lpg market and aims to model the dependence dynamics among lpg freight rates crude oil price and propane location arbitrage conditional copula garch model is applied to estimate dependencies different types of copulas with both time invariant and time varying dependence structures are fitted and their suitability has been compared the findings suggest that firstly baltic lpg blpg freight rate and the arbitrage between propane far east and middle east prices have conditional time varying dependence and the dependence is higher in market downturns furthermore blpg and the arbitrage between far east and us propane prices have symmetric dependence and such a relationship has strengthened since 2013 secondly middle east propane price is found to have the strongest correlation with crude oil prices compared to far east and us propane prices indicating higher sensitivity to crude oil price changes last but not least the relationship between crude oil and blpg is relatively weak and mostly positive

dependence and extreme dependence of crude oil and natural gas prices with applications to risk management abstract in this article we show how the copula garch approach can be appropriately used to investigate the conditional dependence structure between the crude oil and natural gas markets as well as to derive implications for portfolio risk management in extreme economic conditions using daily price data from january 1997 to october 2011 our in sample results show evidence of asymmetric dependence between the two markets the crude oil and gas markets tend to comove closely together during bullish periods but not at all during bearish periods moreover taking the extreme comovement into account leads to an improvement in the accuracy of the out of sample value at risk forecasts

modeling exchange rate dependence dynamics at different time horizons despite an extensive body of research the best way to model the dependence of exchange rates remains an open question in this paper we present a new approach which employs a flexible time varying copula model it allows the conditional correlation between exchange rates to be both time varying and modeled independently from the marginal distributions we introduce a dynamic specification for the correlation using the fisher transformation applied to euro us dollar and japanese yen us dollar our results reveal a significantly time varying correlation dependent on the past return realizations we find that a time varying copula with the proposed correlation specification gives better results than alternative dynamic benchmark models the dynamic copula model outperforms at six different time horizons ranging from hourly to daily confirming the model specification c 2010 elsevier ltd all rights reserved

the copula garch model of conditional dependencies an international stock market application abstract modeling the dependency between stock market returns is a difficult task when returns follow a complicated dynamics when returns are non normal it is often simply impossible to specify the multivariate distribution relating two or more return series in this context we propose a new methodology based on copula functions which consists in estimating first the univariate distributions and then the joining distribution in such a context the dependency parameter can easily be rendered conditional and time varying we apply this methodology to the daily returns of four major stock markets our results suggest that conditional dependency depends on past realizations for european market pairs only for these markets dependency is found to be more widely affected when returns move in the same direction than when they move in opposite directions modeling the dynamics of the dependency parameter also suggests that dependency is higher and more persistent between european stock markets

irreversible environmental investments with uncertain benefit levels abstract the principal property of irreversibilities is that they generate incentives for policies that are smaller in scale than a myopic policy the circumstances in which this irreversibility effect occurs are first considered for a model with unit benefit uncertainty and time invariant cost functions with changes in cost relationships over time such as fixed costs for augmenting investment it may be desirable to adopt policies with scales that are larger than smaller than or the same as the scale of a myopic policy with rising unit benefits over time one adopts a policy scale larger than or the same as that in the myopic case and with declining unit benefits the opposite result holds irreversibilities will however lead to underinvestments in comparison with incompletely reversible investments with similar adjustment costs for increasing policy investments

evaluating density forecasts with applications to financial risk management density forecasting is increasingly more important and commonplace for example in financial risk management yet little attention has been given to the evaluation of density forecasts the authors develop a simple and operational framework for density forecast evaluation they illustrate the framework with a detailed application to density forecasting of asset returns in environments with time varying volatility finally the authors discuss several extensions copyright 1998 by economics department of the university of pennsylvania and the osaka university institute of social and economic research association

memory and infrequent breaks abstract we study how processes with infrequent regime switching may generate a long memory effect in the autocorrelation function in such a case the use of a strong fractional i d model for economic or financial analysis may lead to spurious results

hourly volatility spillovers between international equity markets abstract this paper examines the timing of mean and volatility spillovers between new york and london equity markets using an arch model it is found that the evidence of volatility spillovers between these markets is minimal and have a duration which lasts only an hour or so the most significant effects surround the movement of share prices around the new york opening but these results are not strong several new arch models are estimated including an asymmetric or leverage model and a non linear model which allows big shocks to have a different impact from small shocks

sovereign bond market dependencies and crisis transmission around the eurozone debt crisis a dynamic copula approach abstractwe examine the dependency between the european government bond markets around the recent sovereign debt crisis a dynamic copula approach is used to model the time varying dependence struct

conditional volatility skewness and kurtosis existence persistence and comovements abstract recent portfolio choice asset pricing value at risk and option valuation models highlight the importance of modeling the asymmetry and tail fatness of returns these characteristics are captured by the skewness and the kurtosis we characterize the maximal range of skewness and kurtosis for which a density exists and show that the generalized student t distribution spans a large domain in the maximal set we use this distribution to model innovations of a garch type model where parameters are conditional after demonstrating that an autoregressive specification of the parameters may yield spurious results we estimate and test restrictions of the model for a set of daily stock index and foreign exchange returns the estimation is implemented as a constrained optimization via a sequential quadratic programming algorithm adequacy tests demonstrate the importance of a time varying distribution for the innovations in almost all series we find time dependency of the asymmetry parameter whereas the degree of freedom parameter is generally found to be constant over time we also provide evidence that skewness is strongly persistent but kurtosis is much less so a simulation validates our estimations and we conjecture that normality holds for the estimates in a cross section setting we also document covariability of moments beyond volatility suggesting that extreme realizations tend to occur simultaneously on different markets

international diversification a copula approach abstract the viability of international diversification involves balancing benefits and costs this balance hinges on the degree of asset dependence in light of theoretical research linking diversification and dependence we examine international diversification using two measures of dependence correlations and copulas we document several findings first dependence has increased over time second we find evidence of asymmetric dependence or downside risk in latin america but less in the g5 the results indicate very little downside risk in east asia third east asian and latin american returns exhibit some correlation complexity interestingly the regions with maximal dependence or worst diversification do not command large returns our results suggest international limits to diversification they are also consistent with a possible tradeoff between international diversification and systemic risk

heteroskedasticity in stock return data volume versus garch effects this paper provides empirical support for the notion that autoregressive conditional heterqskedasticity arch in daily stock return data reflects time dependence in the process generating information flow to the market daily trading volume used as a proxy for information arrival time is shown to have significant explanatory power regarding the variance of daily returns which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns furthermore arch effects tend to disappear when volume is included in the variance equation the autoregressive conditiqnal heteroskedasticity arch process of engle 1982 has been shown to provide a good fit for many financial return time series 1 arch imposes an autoregressive structure on conditional variance allqwing volatility shocks to persist over time this persistence captures the propensity of returns of like magnitude to clu ter in time and can explain the well documented nonnormality and nonstability of empirical asset return distributions see especially fama 1965 an appealing explanation for the presence of arch is based upon the hypothesis that daily returns are generated by a maiture of distributions in which the rate of daily information arrival is the stochastic mixing variable as suggested by diebold 1986 gallant hsieh and tauchen 1988 and stock 1987 1988 arch might capture the time series properties e g serial correlation of this mixing variable hqwever this linkage has not been broadly documented with the datia the objective of this study is to examine the validity of this explanation for daily stock returns the empirical strategy exploits the implication of the mixture model that the variance of daily price increments is heteroskedastic specifically positively related to the rate of daily information arrival using daily trading volume as a proxy for the mixing variable we show that for a sample of 20 common stocks arch effects vanish when volume is included as an explanatory variable in the conditional variance equation

asset market linkages in crisis periods we characterize asset return linkages during periods of stress by an extremal dependence measure contrary to correlation analysis this nonparametric measure is not predisposed toward the normal distribution and can allow for nonlinear relationships our estimates for the g 5 countries suggest that simultaneous crashes between stock markets are much more likely than between bond markets however for the assessment of financial system stability the widely disregarded cross asset perspective is particularly important for example our data show that stock bond contagion is approximately as frequent as flight to quality from stocks into bonds extreme cross border linkages are surprisingly similar to national linkages illustrating a potential downside to international financial integration

modeling asymmetric comovements of asset returns existing time varying covariance models usually impose strong restrictions on how past shocks affect the forecasted covariance matrix in this article we compare the restrictions imposed by the four most popular multivariate garch models and introduce a set of robust conditional moment tests to detect misspecification we demonstrate that the choice of a multivariate volatility model can lead to substantially different conclusions in any application that involves forecasting dynamic covariance matrices like estimating the optimal hedge ratio or deriving the risk minimizing portfolio we therefore introduce a general model which nests these four models and their natural asymmetric extensions the new model is applied to study the dynamic relation between large and small firm returns article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies