the incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market abstract this paper aims to investigate whether investor fear gauge ifg contains incremental information content for forecasting the volatility of crude oil futures for this purpose we use oil volatility index ovx to measure the ifg adding the ifg to existing heterogeneous autoregressive har models we develop many har models with ifg subsequently we employ these har models to predict the volatility of crude oil futures the results from the parameter estimation and out of sample forecasting show that the in sample and out of sample performances of har models with ifg are significantly better than their corresponding har models without ifg the results are robust in different ways thus the har models with ifg are more beneficial to the decision making of all participants including financial traders manufacturers and policymakers in the crude oil futures market more importantly the results suggest that the investor fear gauge has a significant positive effect on volatility forecasting and can help improve the performances of almost all the existing har models

identifying jumps in financial assets a comparison between nonparametric jump tests we perform a comprehensive monte carlo comparison between nine alternative procedures available in the literature to detect jumps in financial assets using high frequency data we evaluate size and power properties of the procedures under alternative sampling frequencies persistence in volatility jump size and intensity and degree of contamination with microstructure noise the overall best performance is shown by the andersen bollerslev and dobrev 2007 and lee and mykland 2008 intraday procedures abd lm provided the price process is not very volatile we propose two extensions to the existing battery of tests the first regards the finite sample improvements based on simulated critical values for the abd lm procedure the second regards a procedure that combines frequencies and tests able to reduce the number of spurious jumps finally we report an empirical analysis using real high frequency data on five stocks listed in the new york stock exchange

answering the skeptics yes standard volatility models do provide accurate forecasts a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using arch and stochastic volatility models while most of these studies have documented highly significant in sample parameter estimates and pronounced intertemporal volatility persistence traditional ex post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts contrary to this contention we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications new methods for improved ex post interdaily volatility measurements based on high frequency intradaily data are also discussed

a multicountry characterization of the nonstationarity of aggregate output the authors compute the scaled varlogram the variances of kth differences scaled by the variance of first differences of the log of annual per capita real aggregate output gdp or gnp as measured by 1 the long series for the united states and united kingdom 2 angus maddison s 1982 long series for twelve countries and 3 the postwar ifs data for thirty two countries simulations show that the scaled varlogram of real output is nearly always more consistent with the data being generated by parsimonious difference stationary than trend stationary univariate processes in fact the data reveal some excess nonstationarity relative to parsimonious arima models the power of the scaled varlogram to discriminate between trend stationary and difference stationary processes is somewhat greater than that of a dickey fuller type f test copyright 1990 by ohio state university press

are ghettos good or bad spatial separation of racial and ethnic groups may theoretically have positive or negative effects on the economic performance of those groups we examine the effects of segregation on outcomes for blacks in schooling employment and single parenthood we find that blacks in more segregated areas have significantly worse outcomes than blacks in less segregated areas we control for the endogeneity of location choice using instruments based on political factors topographical features and residence before adulthood a one standard deviation decrease in segregation would eliminate one third of the black white differences in most of our outcomes

skill biased technological change and rising wage inequality some problems and puzzles the recent rise in wage inequality is usually attributed to skill biased technical change sbtc associated with new computer technologies we review the evidence for this hypothesis focusing on the implications of sbtc for overall wage inequality and for changes in wage differentials between groups a key problem for the sbtc hypothesis is that wage inequality stabilized in the 1990s despite continuing advances in computer technology sbtc also fails to explain the evolution of other dimensions of wage inequality including the gender and racial wage gaps and the age gradient in the return to education

international evidence on crude oil price dynamics applications of arima garch models abstract we examine the usefulness of several arima garch models for modeling and forecasting the conditional mean and volatility of weekly crude oil spot prices in eleven international markets over the 1 2 1997 10 3 2009 period in particular we investigate the out of sample forecasting performance of four volatility models garch egarch and aparch and figarch over january 2009 to october 2009 forecasting results are somewhat mixed but in most cases the aparch model outperforms the others also conditional standard deviation captures the volatility in oil returns better than the traditional conditional variance finally shocks to conditional volatility dissipate at an exponential rate which is consistent with the covariance stationary garch models than the slow hyperbolic rate implied by the figarch alternative

neighborhood wealth distributions abstract this paper uses data from the neighborhood clusters sample of the 1989 american housing survey and the panel study of income dynamics and its 1989 wealth supplement to study the distribution of wealth within us residential neighborhoods it uses the bourguignon decomposable inequality index and finds that wealth is more unequally distributed than income and income more than housing wealth at all levels of aggregation that is neighborhoods metropolitan areas regions and the entire us

asymmetric volatility spillovers between oil and stock markets evidence from china and the united states abstract the relationship between oil and stock markets is a hot topic but little research has focused on the time varying asymmetric volatility spillover in a quantitative manner in this study we use a new spillover directional measure and asymmetric spillover measures to investigate the dynamic asymmetric volatility spillover between oil and stock markets during the period of 2007 to 2016 using the intra day data of wti future prices the sp the results also show strong evidence of asymmetries in volatility shocks between the oil and stock markets due to bad volatility

overwork and the slow convergence in the gender gap in wages despite rapid changes in women s educational attainment and continuous labor force experience convergence in the gender gap in wages slowed in the 1990s and stalled in the 2000s using cps data fr

unit roots and infrequent large shocks new international evidence on output growth the authors examine output growth for the g 7 countries they use nathan s balke and thomas fomby s procedure to identify the date and type of trend breaks and note that these occur in clusters the authors estimate country specific intervention models and test the unit root hypothesis their critical values explicitly take account of the prior outliner search procedure for italy japan and the united kingdom the unit root null hypothesis can be rejected this suggests that the variance of output growth in these countries is generated by low frequency high magnitude shocks rather than high frequency low magnitude shocks copyright 1995 by ohio state university press

income inequality and class divides in parental investments historic increases in income inequality have coincided with widening class divides in parental investments of money and time in children these widening class gaps are significant because parental investment is one pathway by which advantage is transmitted across generations using over three decades of micro data from the consumer expenditure survey and the american heritage time use survey linked to state year measures of income inequality we test the relationship between income inequality and class gaps in parental investment we find robust evidence of wider class gaps in parental financial investments in children but not parental time investments in children when state level income inequality is higher we explore mechanisms that may drive the relationship between rising income inequality and widening class gaps in parental financial investments in children this relationship is partially explained by the increasing concentration of income at the top of the income distribution in state years with hi

roughing it up including jump components in the measurement modeling and forecasting of return volatility a rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high frequency returns coupled with simple modeling procedures building on recent theoretical results in barndorff nielsen and shephard 2004a 2005 for related bi power variation measures the present paper provides a practical and robust framework for non parametrically measuring the jump component in asset return volatility in an application to the dm exchange rate the s p500 market index and the 30 year u s treasury bond yield we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process moreover many jumps appear directly associated with specific macroeconomic news announcements separating jump from non jump movements in a simple but sophisticated volatility forecasting model we find that almost all of the predictability in daily weekly and monthly return volatilities comes from the non jump component our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling forecasting and pricing the continuous and jump components of the total return variation process

forecasting volatility of crude oil markets abstract this article investigates the efficacy of a volatility model for three crude oil markets brent dubai and west texas intermediate wti with regard to its ability to forecast and identify volatility stylized facts in particular volatility persistence or long memory in this context we assess persistence in the volatility of the three crude oil prices using conditional volatility models the cgarch and figarch models are better equipped to capture persistence than are the garch and igarch models the cgarch and figarch models also provide superior performance in out of sample volatility forecasts we conclude that the cgarch and figarch models are useful for modeling and forecasting persistence in the volatility of crude oil prices

forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models this paper extends previous studies by investigating the relevance of structural breaks and long memory in modeling and forecasting the conditional volatility of oil spot and futures prices using a variety of garch type models our results can be summarized as follows first we provide evidence of parameter instability in five out of nine garch based conditional volatility processes for energy prices second long memory is effectively present in all the series considered and a figarch model seems to better fit the data but the degree of volatility persistence diminishes significantly after adjusting for structural breaks finally the out of sample analysis shows that volatility models accommodating instability and long memory characteristics of the data provide the best volatility forecasts for most cases

modelling energy spot prices empirical evidence from nymex this paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on nymex we consider two types of models a mean reverting model and a spike model with mean reversion that incorporates two different speeds of mean reversion one for the fast mean reverting behaviour of prices after a jump occurs and another for the slower mean reversion rate of the diffusive part of the model we also extend these models to incorporate time varying volatility in their specification modelled as a garch and an egarch process we compare the relative goodness of fit of the different modelling variations both in sample using monte carlo simulations as well as out of sample in a value at risk var setting our results indicate the presence of a leverage effect for wti heating oil and heating oil wti crack spread whereas for the remaining energy markets we find the presence of an inverse leverage effect also the addition of the egarch specification for the volatility process improves both the in sample fit as well as the out of sample var performance for most energy markets that we examine

income inequality in the united states 1913 1998 this paper presents new homogeneous series on top shares of income and wages from 1913 to 1998 in the united states using individual tax returns data top income and wages shares display a u shaped pattern over the century our series suggest that the large shocks that capital owners experienced during the great depression and world war ii have had a permanent effect on top capital incomes we argue that steep progressive income and estate taxation may have prevented large fortunes from fully recovering from these shocks top wage shares were flat before world war ii dropped precipitously during the war and did not start to recover before the late 1960s but are now higher than before world war ii as a result the working rich have replaced the rentiers at the top of the income distribution

good bad cojumps and volatility forecasting new evidence from crude oil and the u s stock markets abstract in this article we investigate the impacts of jumps cojumps and their signed components on forecasting oil futures price volatility in the framework of the heterogeneous autoregressive realized volatility model our empirical results reveal several noteworthy findings first the effects of signed jumps and cojumps based on the daily and intraday jump tests on future volatility are asymmetric and the negative components are much more powerful in forecasting volatility moreover our proposed models including the signed jump and cojump components are able to generate higher forecasting accuracy and we find that disentangling the effects of positive and negative jumps and cojumps can significantly improve forecasts of future volatility lastly our findings are reliable for various robustness checks and our study provides some new insights into forecasting oil price realized volatility which are useful for researchers market participants and policymakers

option pricing with mean reversion and stochastic volatility many underlying assets of option contracts such as currencies commodities energy temperature and even some stocks exhibit both mean reversion and stochastic volatility this paper investigates the valuation of options when the underlying asset follows a mean reverting lognormal process with stochastic volatility a closed form solution is derived for european options by means of fourier transform the proposed model allows the option pricing formula to capture both the term structure of futures prices and the market implied volatility smile within a unified framework a bivariate trinomial lattice approach is introduced to value path dependent options with the proposed model numerical examples using european options american options and barrier options demonstrate the use of the model and the quality of the numerical scheme

a simple approximation for semivariance abstract semivariance can differentiate among skewed return distributions but variance is unable to do so thus semivariance has been used as a risk surrogate in portfolio analysis and capital budgeting problems unfortunately semivariance analysis is relatively unknown and poses difficult analytic and computational problems in this paper an expression is derived which very closely approximates semivariance this expression is simple in form and uses only familiar statistics namely mean variance critical value and cumulative probability below the critical value

the nonstationarity of aggregate output some additional international evidence in this paper the stationarity of aggregate output is examined using the scaled variogram for a sample of twelve countries it is argued that if the true data generating process of output is stationary around a deterministic trend with a change in mean and or growth rate the results of previous studies are biased once the authors allow for a one time exogenous shock the conclusions are indeed less clear cut and for some countries even reversed copyright 1994 by ohio state university press

the relation between implied and realized volatility abstract previous research finds the volatility implied by s p 100 index option prices to be a biased and inefficient forecast of future volatility and to contain little or no incremental information beyond that in past realized volatility in contrast we find that implied volatility outperforms past volatility in forecasting future volatility and even subsumes the information content of past volatility in some of our specifications our results differ from previous studies because we use longer time series and nonoverlapping data a regime shift around the october 1987 crash explains why implied volatility is more biased in previous work

modeling special day effects for forecasting intraday electricity demand abstract we propose and apply a novel approach for modeling special day effects to predict electricity demand in korea notably we model special day effects on an hourly rather than a daily basis hourly specified predictor variables are implemented in the regression model with a seasonal autoregressive moving average sarma type error structure in order to efficiently reflect the special day effects the interaction terms between the hour of day effects and the hourly based special day effects are also included to capture the unique intraday patterns of special days more accurately the multiplicative sarma mechanism is employed in order to identify the double seasonal cycles namely the intraday effect and the intraweek effect the forecast results of the suggested model are evaluated by comparing them with those of various benchmark models for the following year the empirical results indicate that the suggested model outperforms the benchmark models for both special and non special day predictions

volatility in crude oil futures a comparison of the predictive ability of garch and implied volatility models the wti future contract quoted at the nymex is the most actively traded instrument in the energy sector this paper compares the predictive ability of two approaches which can be used to forecast volatility garch type models where forecasts are obtained after estimating time series models and an implied volatility model where forecasts are obtained by inverting one of the models used to price options although the main scope of the research discussed here is to evaluate which model produces the best forecast of volatility for the wti future contract evaluated according to statistical and regression based criteria we also investigate whether volatility of the oil futures are affected by asymmetric effects whether parameters of the garch models are influenced by the distribution of the errors and whether allowing for a time varying long run mean in the volatility produces any improvement on the forecast obtained from garch models

estimating oil price value at risk using the historical simulation approach abstract in this paper we propose using value at risk var for oil price risk quantification var provides an estimation for the maximum oil price change associated with a likelihood level and can be used for designing risk management strategies we analyse three var calculation methods the historical simulation standard approach the historical simulation with arma forecasts hsaf approach developed in this paper and the variance covariance method based on autoregressive conditional heteroskedasticity models forecasts the results obtained indicate that hsaf methodology provides a flexible var quantification which fits the continuous oil price movements well and provides an efficient risk quantification

predicting volatility in the foreign exchange market measures of volatility implied in option prices are widely believed to be the best available volatility forecasts in this article we examine the information content and predictive power of implied standard deviations isds derived from chicago mercantile exchange options on foreign currency futures the article finds that statistical time series models even when given the advantage of ex post parameter estimates are outperformed by isds isds however also appear to be biased volatility forecasts using simulations to investigate the robustness of these results the article finds that measurement errors and statistical problems can substantially distort inferences even accounting for these however isds appear to be too variable relative to future volatility it is widely believed that the volatility implied in option prices is the market s best estimate of future volatility after all if it were not one could devise a trading strategy that could generate profits by identifying mispriced options the purpose of this article is to investigate the information content and predictive power of volatility implied in options on foreign currencies the paper focuses on options on currency futures traded on the chicago mercantile exchange cme because of the depth and liquidity of cme futures and options traded side by side in the same market implied standard deviations isds allow for clean tests of the predictive power of implied volatilities early studies of the information content of isds have generally found that these contain substantial information for future volatility latane and rendleman 1976 chiras and manaster 1978 and beckers 1981 for example regress future volatility on the weighted implied volatility across a broad sample of chicago board options exchange cboe stocks and find that options contain volatility forecasts that are more accurate than historical measures 1 these studies performed shortly after the 1973 beginning of the cboe option market could only use a relatively short time span and therefore focused on cross sections rather than time series predictions

how did the increase in economic inequality between 1970 and 1990 affect children s educational attainment 1 this study estimates the effect of changes in economic inequality between 1970 and 1990 on children s educational attainment data on individual children from the panel study of income dynamics is combined with other data on state characteristics growing up in a state with widespread economic inequality increases educational attainment for high income children and lowers it for low income children most of the effect is due to factors unassociated with family income or economic segregation in the state these other factors include state spending for schooling and the increase in the returns to schooling over this period

forecasting the volatility of crude oil futures using har type models with structural breaks abstract we introduce sixteen har type volatility models with structural breaks and estimate their parameters by applying 5 min high frequency transaction data for wti crude oil futures we find significant structural breaks in the volatility of crude oil futures additionally the historical realized volatility continuous sample path variation negative realized semivariance signed jump signed semi jump and leverage components contain substantial and salient information for forecasting the volatility of crude oil futures then we use loss functions to assess the forecasting performance of these sixteen new models and finally rank these models using the promethee ii method our results indicate that different models exhibit different predictive power in forecasting the 1 day 1 week and 1 month volatility of crude oil futures of the new har type models the new har rsv model performs best at forecasting the 1 day and 1 month volatilities whereas the new har cj best forecasts the 1 week volatility

a closed form garch option valuation model this paper develops a closed form option valuation formula for a spot asset whose variance follows a garch p q process that can be correlated with the returns of the spot asset it provides the first readily computed option formula for a random volatility model that can be estimated and implemented solely on the basis of observables the single lag version of this model contains heston s 1993 stochastic volatility model as a continuous time limit empirical analysis on s p500 index options shows that the out of sample valuation errors from the single lag version of the garch model are substantially lower than the ad hoc black scholes model of dumas fleming and whaley 1998 that uses a separate implied volatility for each option to fit to the smirk smile in implied volatilities the garch model remains superior even though the parameters of the garch model are held constant and volatility is filtered from the history of asset prices while the ad hoc black scholes model is updated every period the improvement is largely due to the ability of the garch model to simultaneously capture the correlation of volatility with spot returns and the path dependence in volatility article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

are output fluctuations transitory according to the conventional view of the business cycle fluctuations in output represent temporary deviations from trend the purpose of this paper is to question this conventional view if fluctuations in output are dominated by temporary deviations from the natural rate of output then an unexpected change in output today should not substantially change one s forecast of output in say five or ten years our examination of quarterly postwar united states data leads us to be skeptical about this implication the data suggest that an unexpected change in real gnp of 1 percent should change one s forecast by over 1 percent over a long horizon

income inequality and income segregation this article investigates how the growth in income inequality from 1970 to 2000 affected patterns of income segregation along three dimensions the spatial segregation of poverty and affluence race specific patterns of income segregation and the geographic scale of income segregation the evidence reveals a robust relationship between income inequality and income segregation an effect that is larger for black families than for white families in addition income inequality affects income segregation primarily through its effect on the large scale spatial segregation of affluence rather than by affecting the spatial segregation of poverty or by altering small scale patterns of income segregation

higher moment risk premiums for the crude oil market a downside and upside conditional decomposition abstract relying on options written on the uso an exchange traded fund tracking the daily price changes of the wti light sweet crude oil we extract variance and skew risk premiums in a model free way we further decompose these risk premiums into downside and upside conditional components and show that they can be partially explained by uso excess returns and more importantly these decomposed risk premiums enable a much better prediction of uso excess returns than the standard or undecomposed variance and skew risk premiums a comparison with existing results for the equity index option market further confirms the usefulness of the decomposition for the crude oil market

searching for a break in gnp it has been suggested that existing estimates of the long run impact of a surprise move in income may have a substantial upward bias due to the presence of a trend break in postwar u s gross national product data this article shows that the statistical evidence does not warrant abandoning the no trend break null hypothesis a key part of the argument is that conventionally computed p values overstate the likelihood of the trend break alternative hypothesis this is because they do not take into account that in practice the date is chosen based on pretest examination of the data

explaining credit default swap spreads by means of realized jumps and volatilities in the energy market abstract this paper studies the relationship between credit default swap cds spreads for the energy sector and oil futures dynamics using data on light sweet crude oil futures from 2004 to 2013 which contains a crisis period we examine the importance of volatility and jumps extracted from the futures in explaining cds spread changes the analysis is performed at an index level and by rating group as well as for the pre crisis crisis and post crisis periods our findings are consistent with merton s theoretical framework at an index level futures jumps are important when explaining cds spread changes with negative jumps having higher impact during the crisis the continuous volatility part is significant and positive indicating that futures volatility conveys relevant information for the cds market as for the analysis per rating group negative jumps have an increasing importance as the credit rating deteriorates and during the crisis period while the results for positive jumps and futures volatility are mixed overall the relation between the cds market and the futures market is stronger during volatile periods and strengthened after the global financial crisis

forecasting realized volatility a bayesian model averaging approach summary how to measure and model volatility is an important issue in finance recent research uses high frequency intraday data to construct ex post measures of daily volatility this paper uses a bayesian modelaveraging approach to forecast realized volatility candidate models include autoregressive and heterogeneous autoregressive specifications based on the logarithm of realized volatility realized power variation realized bipower variation a jump and an asymmetric term applied to equity and exchange rate volatility over several forecast horizons bayesian model averaging provides very competitive density forecasts and modest improvements in point forecasts compared to benchmark models we discuss the reasons for this including the importance of using realized power variation as a predictor bayesian model averaging provides further improvements to density forecasts when we move away from linear models and average over specifications that allow for garch effects in the innovations to log volatility copyright 2009 john wiley sons ltd

the samuelson hypothesis in futures markets an analysis using intraday data this paper considers the samuelson hypothesis which argues that the futures price volatility increases as the futures contract approaches its expiration utilizing intraday data from 20 futures markets in six futures exchanges we find strong support for the samuelson hypothesis in agricultural futures however the samuelson hypothesis does not hold for other futures contracts we also provide supporting evidence that the negative covariance hypothesis is the key factor for the empirical support of the samuelson hypothesis in addition our findings remain largely unaltered even after we control for seasonality and liquidity effects

forecasting the realized volatility of the oil futures market a regime switching approach considering nonlinear and highly persistent dynamics of realized volatility we introduce markov regime switching models to the heterogeneous autoregressive model of the realized volatility har rv models to forecast the realized volatility of the crude oil futures market in sample results demonstrate that the high volatility regime is short lived out of sample results suggest that har rv models with regime switching increase the forecasting ability significantly than those without regime switching moreover these findings are robust for different actual volatility benchmarks forecasting windows and model settings

futures based forecasts how useful are they for oil price volatility forecasting oil price volatility forecasts have recently attracted the attention of many studies in the energy finance field the literature mainly concentrates its attention on the use of daily data using garch type models it is only recently that efforts to use more informative intraday data to forecast oil price realized volatility have been made despite all these previous efforts no study has examined the usefulness of futures based models for oil price realized volatility forecasting although the use of such models is extensive for oil price predictions this study fills this void and shows that futures based forecasts based on intra day data provide informative forecasts for horizons that span between 1 day and 66 days ahead more importantly these results hold true even during turbulent times for the oil market such as the global financial crisis of 2007 09 and the oil collapse period of 2014 15

a markov switching model of the conditional volatility of crude oil futures prices abstract this paper examines the temporal behaviour of volatility of daily returns on crude oil futures using a generalised regime switching model that allows for abrupt changes in mean and variance garch dynamics basis driven time varying transition probabilities and conditional leptokurtosis this flexible model enables us to capture many complex features of conditional volatility within a relatively parsimonious set up we show that regime shifts are clearly present in the data and dominate garch effects within the high volatility state a negative basis is more likely to increase regime persistence than a positive basis a finding which is consistent with previous empirical research on the theory of storage e g fama and french 1988a fama and french 1988b and ng and pirrong 1994 the volatility regimes identified by our model correlate well with major events affecting supply and demand for oil out of sample tests indicate that the regime switching model performs noticeably better than non switching models regardless of evaluation criteria we conclude that regime switching models provide a useful framework for the financial historian interested in studying factors behind the evolution of volatility and to oil futures traders interested short term volatility forecasts

shifting trends segmented trends and infrequent permanent shocks abstract a stochastic trend model is considered in which permanent shocks occur infrequently and randomly we show that this model is observationally equivalent to shifting segmented deterministic trend models moreover we show that standard full sample time series methods are incapable of distinguishing between small frequent permanent shocks and large infrequent permanent shocks an outlier search however reveals substantial evidence of large infrequent shocks to the gnp deflator and that these shocks account for most of the persistence in the gnp deflator for real gnp evidence of infrequent permanent shocks is weaker

news good or bad and its impact on volatility predictions over multiple horizons we examine whether the sign and magnitude of intra daily returns have impact on expected volatility the next day or over longer future horizons we first let the data speak namely with minimal interference we capture the mapping between intra daily returns and future volatility we revisit the concept of news impact curves introduced by engle and ng 1993 overall we find that moderately good intra daily news reduces volatility the next day while both very good news unusual high intra daily positive returns and bad news negative returns increase volatility with the latter having a more severe impact the asymmetries disappear over longer horizons we also introduce a new class of parametric models which feature asymmetries and with close ties to arch type models albeit applicable to a mixture of high and low frequency data models featuring asymmetries dominate especially during the 2007 2008 financial crisis

permanent and transitory components in macroeconomic fluctuations fluctuations in real gnp have traditionally been viewed as transitory deviations from a deterministic time trend the purpose of this paper is to review some of the recent developments that have led to a new view of output fluctuations and then to provide some additional evidence using post war quarterly data it is hard to reject the view that real gnp is as persistent as a random walk with drift we also consider the hypothesis that the recent finding of persistence are due to the failure to distinguish the business cycle from other fluctuations in real gnp we use the measured unemployment rate to decompose output fluctuations we find no evidence for the view that business cycle fluctuations are more quickly trend reverting this abstract was borrowed from another version of this item

forecasting crude oil market volatility further evidence using garch class models abstract this paper extends the work of kang et al 2009 we use a greater number of linear and nonlinear generalized autoregressive conditional heteroskedasticity garch class models to capture the volatility features of two crude oil markets brent and west texas intermediate wti the one five and twenty day out of sample volatility forecasts of the garch class models are evaluated using the superior predictive ability test and with more loss functions unlike kang et al 2009 we find that no model can outperform all of the other models for either the brent or the wti market across different loss functions however in general the nonlinear garch class models which are capable of capturing long memory and or asymmetric volatility exhibit greater forecasting accuracy than the linear ones especially in volatility forecasting over longer time horizons such as five or twenty days

good volatility bad volatility signed jumps and the persistence of volatility abstract using estimators of the variation of positive and negative returns realized semivariances and high frequency data for the s p 500 index and 105 individual stocks this paper sheds new light on the predictability of equity price volatility we showthat future volatility is more strongly related to the volatility of past negative returns than to that of positive returns and that the impact of a price jump on volatility depends on the sign of the jump with negative positive jumps leading to higher lower future volatility we show that models exploiting these findings lead to significantly better out of sample forecast performance

forecasting the volatility of crude oil futures using intraday data abstract we use the information in intraday data to forecast the volatility of crude oil at a horizon of 1 66 days using a variety of models relying on the decomposition of realized variance in its positive or negative semivariances part and its continuous or discontinuous part jumps we show the importance of these decompositions in predictive in sample regressions using a number of specifications nevertheless an important empirical finding comes from an out of sample analysis which unambiguously shows the limited interest of considering these components overall our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance

does gnp have a unit root a re evaluation abstract stock and watson 1986 test the hypothesis that real per capita gnp has a unit root by using a test statistic due to phillips 1985 which incorporates a non parametric correction for the serial correlation induced by system and error dynamics the version of this test that is used by stock and watson does not accomodate the presence of a drift and to compensate they detrend the series by extracting a 1 5 annual trend growth we use a version of this class of non parametric tests developed by phillips and perron 1986 which allows for an estimated drift and reassess the stock and watson findings

correlated arch corrarch modelling the time varying conditional correlation between financial asset returns abstract although the time variation of the conditional correlations of asset returns is a well established stylized fact and of crucial importance for efficient financial decisions there is no explicit general model available for its estimation and forecasting in this paper we propose a bivariate garch covariance structure in which conditional variances can follow any garch type process while conditional correlation is generated by an explicit discrete time stochastic process the corrarch process a high order corrarch can parsimoniously be represented by a corgarch process the model successfully generates the reported stylized facts establishes an autocorrelation structure for correlations and thus provides an explicit framework for out of sample forecasting we provide empirical evidence from the g7 stock market indexes

on the volatility volume relationship in energy futures markets using intraday data this paper investigates the relationship between trading volume and price volatility in the crude oil and natural gas futures markets when using high frequency data by regressing various realized volatility measures with without jumps on trading volume and trading frequency our results feature a contemporaneous and largely positive relationship furthermore we test whether the volatility volume relationship is symmetric for energy futures by considering positive and negative realized semivariances we show that i an asymm etric volatility volume relationship indeed exists ii trading volume and trading frequency significantly affect negative and positive realized semivariance and iii the information content of negative realized semivariance is higher than for positive realized semivariance

long term trends in earnings inequality what the cps can tell us abstract changes in current population survey cps topcoding rules in the 1990s artificially increased measured earnings inequality we create a time consistent cps data series and compare trends in earnings inequality from 1975 to 2001

forecasting the good and bad uncertainties of crude oil prices using a har framework abstract good or bad uncertainty is the volatility that is associated with positive or negative innovations to asset prices this paper proposes new heterogeneous autoregressive type har type models to forecast the good and bad uncertainties of crude oil prices in this paper we investigate the effects of lagged bad and good uncertainties daily positive and negative signed jump variations and leverages on predicting good and bad uncertainties by in sample and out of sample analysis the in sample results show that bad and good uncertainties have long memory property and the predictability of long term good and bad uncertainties is stronger than that of short and mid term good and bad uncertainties the out of sample results indicate that lagged bad or good uncertainties daily positive signed jump variation and daily negative signed jump variation contain incremental out of sample information for forecasting good or bad uncertainties and in most cases lagged leverages also play indispensable roles in forecasting the good and bad uncertainties in the crude oil market moreover the results of out of sample analysis remain robust across using the other estimation window other har type models and the other sample

does output have a unit root new international evidence in this paper unit root tests for per capita output of 12 oecd countries are performed using traditional unit root tests it follows that the unit root hypothesis cannot be rejected except for the us however following the approach of perron 1989 which takes shifts in mean and or trend into account the null hypothesis of a unit root can be rejected in most countries in our sample in contrast to perron a method suggested by christiano 1992 is used to determine the break date endogenously

nonmarital first births marriage and income inequality many aggregate level studies suggest a relationship between economic inequality and socio demographic outcomes such as family formation health and mortality but individual level evidence is lacking nor is there satisfactory evidence on the mechanisms by which inequality may have an effect we study the determinants of transitions to a nonmarital first birth as a single parent or as a cohabiting parent compared to transitions to marriage prior to a first birth among unmarried childless young adults in the national longitudinal survey of youth 1997 cohort from 1997 to 2011 we include measures of county group level household income inequality and of the availability of jobs typically held by high school graduates and which pay above poverty wages we find that greater income inequality is associated with a reduced likelihood of transitioning to marriage prior to a first birth for both women and men the association between levels of inequality and transitions to marriage can be partially accounted for by the availability of jobs of the type we measured some models also suggest that greater income inequality is associated with a reduced likelihood of transitioning to a first birth while cohabiting

commodity derivatives pricing with cointegration and stochastic covariances abstract empirically cointegration and stochastic covariances including stochastic volatilities are statistically significant for commodity prices and energy products to capture such market phenomena we develop a continuous time dynamics of cointegrated assets with a stochastic covariance matrix and derive the joint characteristic function of asset returns in closed form the proposed model offers an endogenous explanation for the stochastic mean reverting convenience yield the time series of spot and futures prices of wti crude oil and gasoline shows cointegration relationship under both physical and risk neutral measures the proposed model also allows us to fit the observed term structure of futures prices and calibrate the market implied cointegration relationship we apply it to value options on a single commodity and on multiple commodities

international evidence on the size of the random walk in output this paper contributes three extensions of cochrane s work on measuring the relative stability of long term growth it estimates variance ratios for nine oecd countries over the period 1871 1985 presents an improved approximation to the distribution of the variance ratio and considers the comovements of long growth cycles across countries the evidence indicates that the relative stability of long term growth found by cochrane is unique to the united states relative to the united states most countries have more variable dynamics at low frequencies and smoother dynamics at frequencies traditionally associated with business cycles

inequality in children s contexts income segregation of households with and without children past research shows that income segregation between neighborhoods increased over the past several decades in this article i reexamine income segregation from 1990 to 2010 in the 100 largest metropolitan areas and i find that income segregation increased only among families with children among childless households two thirds of the population income segregation changed little and is half as large as among households with children i examine two factors that may account for these differences by household composition first i find that increasing income inequality identified by past research as a driver of income segregation was a much more powerful predictor of income segregation among families with children among whom income inequality has risen more second i find that local school options delineated by school district boundaries contribute to higher segregation among households with children compared to households without rising income inequality provided high income households more resources

modeling and forecasting the volatility of petroleum futures prices we investigate volatility models and their forecasting abilities for three types of petroleum futures contracts traded on the new york mercantile exchange west texas intermediate crude oil heating oil 2 and unleaded gasoline and suggest some stylized facts about the volatility of these futures markets particularly in regard to volatility persistence or long memory properties in this context we examine the persistence of market returns and volatility simultaneously using the following arfima garch class models arima garch arfima garch arfima igarch and arfima figarch although the arfima figarch model better captures long memory properties of returns and volatility the out of sample analysis indicates no unique model for all three types of petroleum futures contracts suggesting that investors should be careful when measuring and forecasting the volatility risk of petroleum futures markets

neighborhood income distributions this paper studies the distribution of income within neighborhoods and contrasts it with the national income distribution it relies on a unique feature of the american housing survey whose 1985 1989 and 1993 waves of interviews provide data for small residential neighborhoods these consist of a dwelling unit and up to ten of its nearest neighbors most previous work on neighborhoods has used information for much larger groupings of the population such as census tracts the paper employs a variety of parametric and nonparametric econometric tools to study income sorting across us residential neighborhoods it documents the patterns of dependence among neighbors income and imperfect sorting with moderate but very significant correlation among incomes of neighbors and of considerable income mixing in u s neighborhoods

forecasting oil price realized volatility using information channels from other asset classes motivated from ross 1989 who maintains that asset volatilities are synonymous to the information flow we claim that cross market volatility transmission effects are synonymous to cross market information flows or information channels from one market to another based on this assertion we assess whether cross market volatility flows contain important information that can improve the accuracy of oil price realized volatility forecasting we concentrate on realized volatilities derived from the intra day prices of the brent crude oil and four different asset classes stocks forex commodities and macro which represent the different information channels by which oil price volatility is impacted from we employ a har framework and estimate forecasts for 1 day to 66 days ahead our findings provide strong evidence that the use of the different information channels enhances the predictive accuracy of oil price realized volatility at all forecasting horizons numerous forecasting evaluation tests and alternative model specifications confirm the robustness of our results

market risk in commodity markets a var approach we put forward value at risk models relevant for commodity traders who have long and short trading positions in commodity markets in a 5 year out of sample study on aluminium copper nickel brent crude oil and wti crude oil daily cash prices and cocoa nearby futures contracts we assess the performance of the riskmetrics skewed student aparch and skewed student arch models while the skewed student aparch model performs best in all cases the skewed student arch model delivers good results and its estimation does not require non linear optimization procedures as such this new model could be relatively easily integrated in a spreadsheet like environment and used by market practitioners

income inequality and early nonmarital childbearing using individual level data from the united states we empirically investigate the role of lower tail income inequality in determining rates of early nonmarital childbearing among low socioeconomic status ses women we present robust evidence that young low ses women are more likely to have a nonmarital birth when they live in places with larger lower tail income inequality all else held constant we calculate that differences in the level of inequality are able to explain a sizeable share of the geographic variation in teen fertility rates we propose a model of adolescent decision making that facilitates the interpretation of our results

international evidence on the persistence of economic fluctuations abstract this paper presents new evidence on the persistence of fluctuations in real gnp we estimate two measures of persistence nonparametrically using post war quarterly data from canada france germany italy japan the united kingdom and the united states we compare these estimates with monte carlo results from various ar 2 processes for six out of seven countries the point estimates indicate that a 1 shock to output should change the long run unvariate forecast of output by well over 1 low order arma models yield similar conclusions finally we examine the persistence in relative outputs of different countries

variance vs downside risk is there really that much difference abstract the popularity of downside risk among investors is growing and mean return downside risk portfolio selection models seem to oppress the familiar mean variance approach the reason for the success of the former models is that they separate return fluctuations into downside risk and upside potential this is especially relevant for asymmetrical return distributions for which mean variance models punish the upside potential in the same fashion as the downside risk the paper focuses on the differences and similarities between using variance or a downside risk measure both from a theoretical and an empirical point of view we first discuss the theoretical properties of different downside risk measures and the corresponding mean downside risk models against common beliefs we show that from the large family of downside risk measures only a few possess better theoretical properties within a return risk framework than the variance on the empirical side we analyze the differences between some us asset allocation portfolios based on variances and downside risk measures among other things we find that the downside risk approach tends to produce on average slightly higher bond allocations than the mean variance approach furthermore we take a closer look at estimation risk viz the effect of sampling error in expected returns and risk measures on portfolio composition on the basis of simulation analyses we find that there are marked differences in the degree of estimation accuracy which calls for further research

volatility and persistence of fluntuations individual production series in italy 1890 1985 the analysis is focused on possible time related changes in the cyclical behaviour of production using a set of individual production series disaggregate data are used to analyse whether short run fluctuations have actually become less extreme or erratic in time and whether the tendency of shocks to have permanent or transitory effects has changed between the pre war and post war eras a third aspect of cyclical trends examined concerns the correlation of short term changes across sectors the main finding of the paper is that there has been little change in the behaviour of the individual series over time in fluctuation size persistence and frequency thus a reduction in variability appears also to be due to a problem of statistical measurement rather then suggesting as the standard literature does that demand shocks were unimportant in the post war period which implies that supply shocks were more important an estimate of the italian experience gives evidence of the importance of both causes

how relevant is volatility forecasting for financial risk management it depends if volatility fluctuates in a forecastable way volatility forecasts are useful for risk management hence the interest in volatility forecastability in the risk management literature volatility forecastability however varies with horizon and different horizons are relevant in different applications moreover existing assessments of volatility forecastability are plagued by the fact that they are joint assessments of volatility forecastability and an assumed model and the results can vary not only with the horizon but also with the assumed model to address this problem we develop a model free procedure for assessing volatility forecastability across horizons perhaps surprisingly we find that volatility forecastability decays quickly with horizon volatility forecastability although clearly of relevance for risk management at the short horizons relevant for say trading desk management may be much less important at longer horizons

forecasting petroleum futures markets volatility the role of regimes and market conditions in this paper we employ regime volatility models to describe time dependency in petroleum markets using a sample of nymex and ice futures contracts we establish the existence of a regime process and link this process to market fundamentals this formulation results in two distinct states a highly persistent conditional volatility process characterised by long memory and low sensitivity to market shocks and a relatively short lived nonstationary process with less memory but higher sensitivity to shocks moreover to investigate the relationship between disequilibrium and volatility of oil futures across high and low volatility regimes we use augmented regime garch models to address in a realistic way the potential diverse response of volatility to forward curve shocks the performance of these models is compared to benchmarks using both statistical tests and risk management loss functions to test the robustness of the forecasting strategies we also perform a reality check employing the stationary bootstrap approach the findings of this paper have important implications for decision making concerning trading and risk management as well as energy market operations such as refining and budget planning by providing valuable information on the oil price volatility dynamics and the ability to predict risk

forecasting realized volatility of crude oil futures with equity market uncertainty this paper examines whether the equity market uncertainty emu index contains incremental information for forecasting the realized volatility of crude oil futures we use 5 min high frequency tran