microstructure noise realized variance and optimal sampling a recent and extensive literature has pioneered the summing of squared observed intra daily returns realized variance to estimate the daily integrated variance of financial asset prices a traditional object of economic interest we show that in the presence of market microstructure noise realized variance does not identify the daily integrated variance of the frictionless equilibrium price however we demonstrate that the noise induced bias at very high sampling frequencies can be appropriately traded off with the variance reduction obtained by high frequency sampling and derive a mean squared error mse optimal sampling theory for the purpose of integrated variance estimation we show how our theory naturally leads to an identification procedure which allows us to recover the moments of the unobserved noise this procedure may be useful in other applications finally using the profits obtained by option traders on the basis of alternative variance forecasts as our economic metric we find that explicit optimization of realized variance s finite sample mse properties results in accurate forecasts and considerable economic gains copyright 2008 wiley blackwell

conditional dependence structure between oil prices and exchange rates a copula garch approach abstract we study the conditional dependence structure between crude oil prices and u s dollar exchange rates using a copula garch approach various copula functions of the elliptical archimedean and quadratic families are used to model the underlying dependence structure in both bearish and bullish market phases over the 2000 2011 period we find evidence of significant and symmetric dependence for almost all the oil exchange rate pairs considered the rise in the price of oil is found to be associated with the depreciation of the dollar moreover we show that student t copulas best capture the extreme dependence and that taking the extreme comovement into account leads to improve the accuracy of var forecasts our main results remain unchanged when considering alternative garch type specifications and the crisis period but are sensitive to the use of raw returns

economic policy uncertainty financial markets and probability of us recessions we use probit recession forecasting models to assess the ability of economic policy uncertainty indexes developed by baker et al 2013 to predict future us recessions the model specifications include policy indexes on their own and in combination with financial variables such as interest rate spreads stock returns and stock market volatility both in sample and out of sample analysis suggests that the policy uncertainty indexes are statistically and economically significant in forecasting recessions at the horizons beyond five quarters the index based on newspaper reports emerges as the best predictor outperforming the term spread at the longer forecast horizons

analytical evaluation of volatility forecasts estimation and forecasting for realistic continuous time stochastic volatility models is hampered by the lack of closed form expressions for the likelihood in response andersen bollerslev diebold and labys econometrica 71 2003 579 625 advocate forecasting integrated volatility via reduced form models for the realized volatility constructed by summing high frequency squared returns building on the eigenfunction stochastic volatility models we present analytical expressions for the forecast efficiency associated with this reduced form approach as a function of sampling frequency for popular models like garch multifactor affine and lognormal diffusions the reduced form procedures perform remarkably well relative to the optimal infeasible forecasts

nonlinear term structure dependence copula functions empirics and risk implications abstract this paper documents nonlinear cross sectional dependence in the term structure of us treasury yields and points out risk management implications the analysis is based on a kalman filter estimation of a two factor affine model which specifies the yield curve dynamics we then apply a broad class of copula functions for modeling dependence in factors spanning the yield curve our sample of monthly yields in the 1982 2001 period provides evidence of upper tail dependence in yield innovations i e large positive interest rate shocks tend to occur under increased dependence in contrast the best fitting copula model coincides with zero lower tail dependence this asymmetry has substantial risk management implications we give an example in estimating bond portfolio loss quantiles and report the biases which result from an application of the normal dependence model

bayesian analysis of structural credit risk models with microstructure noises in this paper a markov chain monte carlo mcmc technique is developed for the bayesian analysis of structural credit risk models with microstructure noises the technique is based on the general bayesian approach with posterior computations performed by gibbs sampling simulations from the markov chain whose stationary distribution converges to the posterior distribution enable exact finite sample inferences of model parameters the exact inferences can easily be extended to latent state variables and any nonlinear transformation of state variables and parameters facilitating practical credit risk applications in addition the comparison of alternative models can be based on deviance information criterion dic which is straightforwardly obtained from the mcmc output the method is implemented on the basic structural credit risk model with pure microstructure noises and some more general specifications using daily equity data from us and emerging markets we find empirical evidence that microstructure noises are positively correlated with the firm values in emerging markets

a repeated nested logit model of atlantic salmon fishing participation and site choice for atlantic salmon fishing are modeled in the context of a repeated three level nested logit model consumer s surplus measures are derived for different levels of species availability in the penobscot river the most important salmon river in new england for comparison six other travel cost models are estimated these include restrictive cases of the nested logit model a partial demand model and two single site demand models comparisons across these models indicate the importance of modeling the participation decision including income effects and of adopting a nested logit structure rather than a single level logit structure

optimized quantity within distance models of spatial welfare heterogeneity abstract spatial welfare heterogeneity is frequently modeled within stated preference analysis as a function of discrete or continuous distance between households and affected resources a common example is distance decay analysis although distance based models such as these are easily estimated the ubiquity of this paradigm can lead to analyses that overlook other forms of analysis with equal or greater relevance this paper develops an alternative approach to spatial heterogeneity in stated preference willingness to pay wtp based on the quantity or area of an affected resource surrounding each respondent at an optimized distance band or radius with distance bands optimized using a grid search algorithm that maximizes model likelihood methods and results are illustrated using a choice experiment on riparian land restoration in maine usa the resulting quantity within distance model identifies systematic spatial patterns that are undetectable using distance based analysis and directly relevant for welfare analysis

the distributional impacts of recreational fees a discrete choice model with incomplete data in this manuscript we explore the consequences to different income groups of various policies to reduce overfishing in the gulf marine recreational fishery to do so we estimate a discrete choice model of marine recreational fishing demand allowing for incomplete data and a non constant marginal utility of income by allowing the marginal utility of income to vary across three categorical income groups our model allows us to explore the distributional consequences of various fee schemes and other policy programs that would change catch in the fishery we find that flat fees have a strong proportional effect on the participation of shore fishermen where low income anglers predominate and a relatively small impact on the expensive charter fishing mode we also find that the welfare consequences of declining catch rates would fall disproportionately on low income anglers jel q51 q22

a note on choice of residential location in travel cost demand models where x is number of visits to a site p is price y is a k x 1 vector of observed individual characteristics and e is a random component 1 is a 1 x k parameter vector and p is a scalar parameter hundreds of models with this basic demand relationship as a basis have been estimated see smith s 1989 review my concern is that the price used in this model may be endogenous because people base decisions about where to live in part on proximity to recreation sites if so unobserved taste characteristics in the error term e will be

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

the demand for site specific recreational activities a characteristics approach abstract a model of constrained utility maximizing behavior is developed to explain how a representative individual allocates his ski days among alternative sites the physical characteristics of the ski areas and the individual s skiing ability are explicit arguments in the utility function the budget allocation is given along with the parametric costs to ski including travel costs entrance fees equipment costs and the opportunity cost of his time shares a site s share being the proportion of ski days that the individual spends at that site are derived and assumed multinomially distributed a stochastic specification which maintains the inherent properties of the shares maximum likelihood estimation confirms the basic hypothesis that costs ability and characteristics all are important determinants of the sites shares the model explains a large proportion of the skier s allocation of ski days a multinomial logit model of skier behavior is also developed and maximum likelihood estimates of its parameters are obtained examination of the summary statistics from my model and the logit model indicates that my model predicts the skier s choice of sites better than the logit model

semiparametric duration models in this article we consider semiparametric duration models and efficient estimation of the parameters in a non iid environment in contrast to classical time series models where innovations are assumed to be iid we show that in for example the often used autoregressive conditional duration acd model the assumption of independent innovations is too restrictive to describe financial durations accurately therefore we consider semiparametric extensions of the standard specification that allow for arbitrary kinds of dependencies between the innovations the exact nonparametric specification of these dependencies determines the flexibility of the semiparametric model we calculate semiparametric efficiency bounds for the acd parameters discuss the construction of efficient estimators and study the efficiency loss of the exponential pseudolikelihood procedure this efficiency loss proves to be sizeable in applications for durations observed on the paris bourse for the alcatel stock in july and august 1

estimation of high frequency volatility an autoregressive conditional duration approach we propose a method to estimate the intraday volatility of a stock by integrating the instantaneous conditional return variance per unit time obtained from the autoregressive conditional duration acd model called the acd icv method we compare the daily volatility estimated using the acd icv method against several versions of the realized volatility rv method including the bipower variation rv with subsampling the realized kernel estimate and the duration based rv our monte carlo results show that the acd icv method has lower root mean squared error than the rv methods in almost all cases considered this article has online supplementary material

the impact of uncertainty shocks under measurement error a proxy svar approach a growing literature considers the impact of uncertainty using svar models that include proxies for uncertainty shocks as endogenous variables in this paper we consider the impact of measurement error in these proxies on the estimated impulse responses we show via a monte carlo experiment that measurement error can result in attenuation bias in impulse responses in contrast the proxy svar that uses the uncertainty shock proxy as an instrument does not suffer from this bias applying this latter method to the bloom 2009 data set results in impulse responses to uncertainty shocks that are larger in magnitude and more persistent than those obtained from a recursive svar

oil and the macroeconomy since world war ii all but one of the u s recessions since world war ii have been preceded typically with a lag of around three fourths of a year by a dramatic increase in the price of crude petroleum this does not mean that oil shocks caused these recessions evidence is presented however that even over the period 1948 72 this correlation is statistically significant and nonspurious supporting the proposition that oil shocks were a contributing factor in at least some of the u s recessions prior to 1972 by extension energy price increases may account for much of post opec macroeconomic performance

improving environmental valuation estimates through consistent use of revealed and stated preference information abstract environmental valuation data from stated and revealed preference methods are integrated into a unified model of preferences for environmental quality improvement that identifies the use and nonuse components of the total value estimate this articulates clearly what parts of the total value estimate come from each type of data and permits tests of whether estimated preferences satisfy weak complementarity between the environmental good of interest and related private goods the statistical advantages of using more information for the valuation problem are exploited while retaining flexibility to identify value estimates from any individual method of analysis

international economic policy uncertainty and stock prices revisited multiple and partial wavelet approach abstract this paper introduces a new dimension to the relationship between economic policy uncertainty epu and stock prices sp by extending the contributions of ko and lee 2015 by using multiple and partial wavelet coherence techniques the vulnerability of sp due to combined and isolated impact of international us epu and domestic policy uncertainty depu is investigated the main findings are a the combined effect of depu and us epu is more significant for developed market s sp b the emerging market s sp are more sensitive to depu and c amongst developed markets japan and european countries are more sensitive to us epu than depu

choice set formation for outdoor destinations the role of motivations and preference discrimination in site selection for the management of public expenditures on protected areas effective public expenditure currently dominates the management focus of many protected areas this calls for explicit modeling of constraints and motivations that respectively obstruct and stimulate visits to selected outdoor destinations choice set formation is the result of screening and or inclusion of specific sites alternatives to form the set of sites considered in real choices evidence shows that the omission of a structural representation of choice set formation is harmful to econometric inference yet the literature has largely ignored the underlying behavioral phenomenon we show using a discrete choice experiment involving selection among seven recreational sites in an italian national park that choice set formation is behaviorally relevant even after controlling for preference discrimination motivations why visit are important determinants of preliminary site screening for choice set inclusion as well as site selection justifying the additional value of such modeling extension

a note on the welfare effects of omitting substitute prices and qualities from travel cost models the bias to welfare estimates from omitting substitute prices or qualities in travel cost models is examined the presence of bias depends on whether single or multiple site changes are examined and the degree of correlation between the omitted and included prices for a multiple site price or quality change even when omitted price is uncorrelated with included price welfare estimates may be biased alternatively if omitted price is perfectly correlated the welfare measure may not be biased the presence of the bias depends equally on both the degree of correlation and whether a single or multiple change occurs this abstract was borrowed from another version of this item

dynamic co movements of stock market returns implied volatility and policy uncertainty we examine time varying correlations among stock market returns implied volatility and policy uncertainty our findings suggest that correlations are indeed time varying and sensitive to oil demand shocks and us recessions

the travel cost model for lake recreation a comparison of two methods for incorporating site quality and substitution effects this paper empirically illustrates how different assumptions regarding recreationists decision making behavior affect the predicted changes in recreational activity given a water quality improvement a multinomial logit model which reallocates visits away from other sites to the improved site predicts a smaller outward shift of the recreationist s demand curve than the more traditional travel cost model which does not assume any reallocation of visits among sites

measuring recreation values with multiple destination trips traditional travel cost analysis has either ignored multiple destination trips or arbitrarily allocated trip costs across visited sites in this paper combinations of multiple destinations are treated as unique sites and incorporated into a demand system empirical demand functions for multiple destination trips that include bryce national park are estimated consumer surplus calculations for single destination and multiple destination trips are compared

how does economic policy uncertainty drive gold stock correlations evidence from the uk abstractin this article we investigate the effects of economic policy uncertainty epu on correlations between the uk stock market and gold market we find that less certain economic policies result in lower correlations while more certain economic policies result in higher correlations the correlations are symmetric and show no structural breaks caused by the recent financial crisis the recent financial crisis has not changed epu effects on the correlations the effects of one positive one standard deviation shock of the logarithmic change rate of the epu on the correlations last approximately 19 months

the implications of model specification for welfare estimation in nested logit models nested logit models are increasingly being used to value environmental amenities the implications of nesting structure choice of estimator fiml or sequential and restrictions on parameters across nested groups on welfare estimates are examined these issues have received little previous attention model selection criteria that can be used to distinguish among the models are extended and applied additionally a simulation procedure is implemented to construct standard errors for the welfare measures

time changed levy processes and option pricing abstract the classic black scholes option pricing model assumes that returns follow brownian motion but return processes differ from this benchmark in at least three important ways first asset prices jump leading to non normal return innovations second return volatilities vary stochastically over time third returns and their volatilities are correlated often negatively for equities time changed levy processes can simultaneously address these three issues we show that our framework encompasses almost all of the models proposed in the option pricing literature and it is straightforward to select and test a particular option pricing model through the use of characteristic function technology

on measuring volatility of diffusion processes with high frequency data abstract we analyze a recently proposed method to estimate the volatility of a diffusion process with high frequency data the method is based on fourier analysis all observations are included in the computation without any data manipulation by monte carlo experiments we evaluate its performance in measuring volatility under the assumption that the asset price evolves according to models belonging to the sr sarv 1 class which includes garch 1 1 as a particular case we compare the performance of the method to that associated with the cumulative squared intraday returns the forecasting capability of the models is also evaluated

a theoretical comparison between integrated and realized volatility in this paper we provide both qualitative and quantitative measures of the precision of measuring integrated volatility by realized volatility for a fixed frequency of observation we start by characterizing for a general diffusion the difference between realized and integrated volatility for a given frequency of observation then we compute the mean and variance of this noise and the correlation between the noise and the integrated volatility in the eigenfunction stochastic volatility model of meddahi 2001a this model has as special cases log normal affine and garch diffusion models using previous empirical results we show that the noise is substantial compared with the unconditional mean and variance of integrated volatility even if one employs five minute returns we also propose a simple approach to capture the information about integrated volatility contained in the returns through the leverage effect we show that in practice the leverage effect does not matter copyright 2002 john wiley sons ltd

dependence structure between the equity market and the foreign exchange market a copula approach abstract this paper investigates the dependence structure between the equity market and the foreign exchange market by using copulas in particular several copulas with different dependence structure are compared and used to directly model the underlying dependence structure we find that there exists significant symmetric upper and lower tail dependence between the two financial markets and the dependence remains significant but weaker after the launch of the euro our findings have important implications for both global investment risk management and international asset pricing by taking into account joint tail risk

on estimating market microstructure noise variance abstract we study the market microstructure noise variance estimation of high frequency stock prices based on the hansen and lunde 2006 approach we propose estimates using subsampling method at different time scales we conduct a monte carlo study to compare our method against others in the literature our results show that our proposed estimates have lower absolute mean error and root mean squared error and their performance is quite stable at different time scales

common and country specific economic uncertainty abstract we use a factor model with stochastic volatility to decompose the time varying variance of macroeconomic and financial variables into contributions from country specific uncertainty and uncertainty common to all countries we find that the common component plays an important role in driving the time varying volatility of nominal and financial variables the cross country co movement in volatility of real and financial variables has increased over time with the common component becoming more important over the last decade simulations from a two country dsge model featuring epstein zin preferences suggest that increased globalisation and trade openness may be the driving force behind the increased cross country correlation in volatility

a discrete choice model of recreational participation site choice and activity valuation when complete trip data are not available abstract a discrete choice model of the demand for site specific recreational activities is developed and estimated it simultaneously predicts both how many trips the individual will take and which site will be chosen on each trip the model is formulated to estimate demand when the data set reports the total number of trips in a given time period but the actual destinations for only a subset of the total the model also includes a correction for sample selectivity bias the application is marine recreational fishing the consumer s surplus associated with any change in supply conditions is derived and used to assess the impact of changes in species availability

a wavelet analysis of mean and volatility spillovers between oil and brics stock markets this paper investigates the spillover effects of volatility and shocks between oil prices and the brics stock markets using multivariate approach and wavelet analysis at different time horizons hence we combine a multivariate arma garch model and wavelet multiresolution analysis to study this phenomenon a bivariate arma 1 1 garch 1 1 cdcc student t model was joined with modwt filter to capture a broad range of possible spillover effects in mean and variances of level prices at various time horizons generally empirical results provide strong evidence of time varying volatility in all markets under study however our proposed approach shows that oil price and stock market prices are directly affected by their own news and volatilities and indirectly affected by the volatilities of other prices and wavelet scale the results show also that mean and volatility spillover effects was decomposed into many sub spillovers on different time scales according to heterogeneous investors and market participants the practical implications of this study are critical innovative and useful for the local and international investors and also for the portfolio managers they can utilize this study to formulate the optimal oil bricks stock portfolios as well as lead to more accurate predictions of volatility spillovers patterns also in developing their hedging strategies

dynamic spillovers of oil price shocks and economic policy uncertainty this study examines the dynamic relationship between changes in oil prices and the economic policy uncertainty index for a sample of both net oil exporting and net oil importing countries over the period 1997 01 2013 06 to achieve that an extension of the diebold and yilmaz 2009 2012 dynamic spillover index based on structural decomposition is employed the results reveal that economic policy uncertainty oil price shocks responds negatively to aggregate demand oil price shocks economic policy uncertainty shocks furthermore during the great recession of 2007 2009 total spillovers increase considerably reaching unprecedented heights moreover in net terms economic policy uncertainty becomes the dominant transmitter of shocks between 1997 and 2009 while in the post 2009 period there is a significant role for supply side and oil specific demand shocks as net transmitters of spillover effects these results are important for policy makers as well as investors interested in the oil market

economic policy uncertainty and risk spillovers in the eurozone this paper focuses on the impact of economic policy uncertainty on risk spillovers within the eurozone and contributes to these two growing literatures to this end we adapt the two step procedure developed by adrian and brunnermeier forthcoming in the framework of financial systemic risk to the sovereign bond market accordingly we attempt i to measure the extent to which distress affecting one given country s sovereign spreads can affect the eurozone s bond market as a whole and then ii to identify the determinants of risk spillovers by estimating a panel data model with macroeconomic state variables and economic policy uncertainty epu indices introduced by baker et al 2013 as regressors epu indices considered concern the four largest eurozone countries i e germany france italy and spain as well as the united states the model is estimated with quarterly data for ten countries representing the bulk of debt issuances within the eurozone over a period ranging from q4 2008 to q2 2013 which is characterized by historically high dispersion of sovereign bond spreads either across time or across countries our results support the idea that economic policy uncertainty in the core economies of the eurozone i e germany and france as well as in the largest periphery countries i e italy and spain can create an environment likely to exacerbate the transmission of risk arising from abnormal developments of individual countries sovereign spreads to the eurozone bond market as a whole in this respect our results plead for larger effort of eurozone leaders to reduce the uncertainty surrounding their economic policy in periods of crisis not only to avoid adverse effects on their own economies but also to reduce the risk of a destabilization of the eurozone sovereign bond market as a whole

does economic policy uncertainty in the u s influence stock markets in china and india time frequency evidence this paper uses continuous and discrete wavelet tools to evaluate the dynamic correlation and causality between the u s economic policy uncertainty epu and stock markets in china and india from

a new statistic and practical guidelines for nonparametric granger causality testing abstract in this paper we introduce a new nonparametric test for granger non causality which avoids the over rejection observed in the frequently used test proposed by hiemstra and jones 1994 testing for linear and nonlinear granger causality in the stock price volume relation journal of finance 49 1639 1664 after illustrating the problem by showing that rejection probabilities under the null hypothesis may tend to one as the sample size increases we study the reason behind this phenomenon analytically it turns out that the hiemstra jones test for the null of granger non causality which can be rephrased in terms of conditional independence of two vectors x and z given a third vector y is sensitive to variations in the conditional distributions of x and z that may be present under the null to overcome this problem we replace the global test statistic by an average of local conditional dependence measures by letting the bandwidth tend to zero at appropriate rates the variations in the conditional distributions are accounted for automatically based on asymptotic theory we formulate practical guidelines for choosing the bandwidth depending on the sample size we conclude with an application to historical returns and trading volumes of the standard and poor s index which indicates that the evidence for volume granger causing returns is weaker than suggested by the hiemstra jones test

economic policy uncertainty in the us does it matter for the euro area abstract we investigate the effects of a us economic policy uncertainty shock on some euro area macroeconomic aggregates via structural vars we model the indicators of economic policy uncertainty recently developed by baker et al 2013 jointly with the aggregate price indexes and alternative indicators of the business cycle for the two above indicated economic areas according to our svars a one standard deviation shock to us economic policy uncertainty leads to a statistically significant fall in the european industrial production and prices of 0 12 and 0 06 respectively the contribution of the us uncertainty shock on the european aggregates is shown to be quantitatively larger than the one exerted by an euro area specific uncertainty shock

testing for linear and nonlinear granger causality in the stock price volume relation linear and nonlinear granger causality tests are used to examine the dynamic relation between daily dow jones stock returns and percentage changes in new york stock exchange trading volume we find evidence of significant bidirectional nonlinear causality between returns and volume we also examine whether the nonlinear causality from volume to returns can be explained by volume serving as a proxy for information flow in the stochastic process generating stock return variance as suggested by clark s 1973 latent common factor model after controlling for volatility persistence in returns we continue to find evidence of nonlinear causality from volume to returns

selection and recreation demand increased use of on site and user group surveys to estimate travel cost demand models e g caulkins bishop and bowes smith and desvousges has raised inevitable questions about the significance of relying on demand estimates derived solely from surveys of users many of the questions relate to selection effects that is the potential for specification errors and bias caused by an inability to reflect the decisions of nonusers with these types of surveys this issue has received some attention in the recreation literature brown et al bockstael and mcconnell but specific empirical evidence on the implications of alternative approaches for estimating demand models from on site surveys does not exist this article reports the first such evidence using a data set based on a general population sample to compare five methods for estimating travel cost demand models with microdata the findings suggest that the differences in the demand and in the benefit estimates raised by treating the problem using models with either single heckman or double selection catsiapis and robinson ham poirier effects are small however the effects of using alternative estimators for site demands are not these findings are limited because they apply to only one site nonetheless they do highlight the importance of the assumptions used to consider the behavior of nonusers consequently they provide direct motivation for more detailed conceptual and empirical work on the choice processes underlying recreation decisions

the reliability of estimates of environmental benefits from recreation demand models recreation demand models are commonly employed tools of economists interested in valuing improvements in environmental amenities despite their importance little comparative work has been undertaken to examine the ability of the models to accurately estimate welfare changes a simulation study designed to compare the reliability of estimated welfare measures compensating variation and consumer surplus from several commonly employed recreation demand models is presented results of the study indicate that choice of functional form and model specification are important determinants of the resulting estimates of benefits

properties of realized variance under alternative sampling schemes this article investigates the statistical properties of the realized variance estimator in the presence of market microstructure noise different from the existing literature the analysis relies on a pure jump process for high frequency security prices and explicitly distinguishes among alternative sampling schemes including calendar time sampling business time sampling and transaction time sampling the main finding in this article is that transaction time sampling is generally superior to the common practice of calendar time sampling in that it leads to a lower mean squared error mse of the realized variance the benefits of sampling in transaction time are particularly pronounced when the trade intensity pattern is volatile based on ibm transaction data over the period 2000 2004 the empirical analysis finds an average optimal sampling frequency of about 3 minutes with a steady downward trend and significant day to day variation related to market liquidity and a consistent reduction in mse of th

assessing market microstructure effects via realized volatility measures with an application to the dow jones industrial average stocks transaction prices of financial assets are contaminated by market microstructure effects this is particularly relevant when estimating volatility using high frequency data in this article we assess statistically the effect of microstructure noise on volatility estimators and test the hypothesis that its variance is independent of the sampling frequency we provide evidence based on the dow jones industrial average stocks we find that noise has a statistically significant effect on volatility estimators at frequencies of 2 3 min or higher the independently and identically distributed specification with constant variance seems to be a plausible model for microstructure noise except for ultra high frequencies

the behavior of intra daily exchange rates abstract the behavior of exchange rates is examined as they evolve continuously over time the data consist of swiss franc u s dollar rates for nine days during the years 1978 1980 as quoted by a major swiss dealer operating on the interbank market since this market is highly organized the observations are market prices at the same time the distributions of relative changes in exchange rates measured over one minute are highly leptokurtic the normal distribution is rather rapidly approached when the measurement interval is lengthened from one up to ten minutes time series analysis reveals that the natural logarithms of exchange rates are adequately described by a random walk the same stochastic process as has been found for daily weekly monthly and quarterly observations for short time intervals significant autocorrelations sometimes occur at the first few lags which are however not stable enough over time to form a basis for reliable forecasts

comparing welfare estimates of environmental quality changes from recreation demand models abstract this paper presents a procedure for examining the reliability of welfare estimates resulting from the estimation of multiple site recreation demand models a simulation approach is suggested where a utility function is combined with observations on individual and site characteristics to generate simulated data sets welfare measures associated with an improvement in site quality are calculated recreation demand models are estimated using the simulated data sets estimated welfare measures resulting from the recreation demand models are then compared to the true welfare measures calculated from the simulated data the procedure is demonstrated using two commonly employed recreation demand models

uncertainty and crude oil returns we use a copula approach to investigate the effect of uncertainty on crude oil returns using copulas to construct multivariate distributions of time series data permit the calculation of the dependence structure between the series independently of the marginal distributions further we implement the copula estimation using a rolling window method to allow for a time varying effect of equity and economic policy uncertainty on oil returns the results show that higher uncertainty as measured by equity and economic policy uncertainty indices significantly increase crude oil returns only during certain periods of time that is we find a positive dependence prior to the financial crisis and great recession interestingly estimation of the copula over the entire sample period leads to a negative dependence between the equity and economic policy indices and the crude oil return

macroeconomic uncertainty indices based on nowcast and forecast error distributions abstract we propose new indices to measure macroeconomic uncertainty the indices measure how unexpected a realization of a representative macroeconomic variable is relative to the unconditional fo

a guide to wavelets for economists abstract wavelet analysis although used extensively in disciplines such as signal processing engineering medical sciences physics and astronomy has not fully entered the economics discipline yet in this survey article wavelet analysis is introduced in an intuitive manner and the existing economics and finance literature that utilizes wavelets is surveyed and explored extensive examples of exploratory wavelet analysis are given most using canadian us and finnish industrial production data finally potential and possible future applications for wavelet analysis in economics are discussed

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

estimation of time varying adjusted probability of informed trading and probability of symmetric order flow shock summary recently duarte and young 2009 studied the probability of informed trading pin proposed by easley et al 2002 and decomposed it into two parts the adjusted pin apin as a measure of asymmetric information and the probability of symmetric order flow shock psos as a measure of illiquidity they provide some cross section estimates of these measures using daily data over annual periods in this paper we propose a method to estimate daily apin and psos by extending the method in tay et al 2009 using high frequency transaction data our empirical results show that while pin is positively contemporaneously correlated with variance apin is not on the other hand psos is positively correlated with daily average effective spread and variance which is consistent with the interpretation of psos as a measure of illiquidity compared to apin psos exhibits clustering and sporadic bursts over time copyright 2012 john wiley sons ltd

recreation demand models with taste differences over people we estimate random parameter logit models of anglers choice of fishing site the models generalize logit by allowing coefficients to vary randomly over anglers rather than being fixed the models do not exhibit the restrictive independence from irrelevant alternatives property of logit and can represent any substitution pattern estimation explicitly accounts for the fact that the variation in coefficients over anglers induces correlation in unobserved utility over trips by the same angler willingness to pay for improved fish stock and the value to anglers of specific sites are calculated from the models and compared with the estimates obtained from a standard logit model

estimating the benefits of low flow alleviation in rivers the case of the ticino river in switzerland 60 of electricity is produced by hydropower plants the construction and operation of these plants determine some negative environmental externalities such as diminishing groundwater levels and spring flows and a reduction in river flow which can severely curtail recreational and fishing activities this study concentrates on an ex ante appraisal of the monetary benefits resulting from an enhancement of river flow for recreational fishing purposes a comparison of estimates of these benefits to the corresponding costs in terms of loss of electricity production incurred by hydropower plants to alleviate low flows may be useful for policy makers for this analysis as suggested by layman et al land economics 72 pp 113 128 1996 the travel cost method tcm is extended to estimate the economic value of recreational fishing in the ticino river the most important river of the canton ticino under existing and hypothetical river flow conditions anglers were asked to state how the nu

international economic policy uncertainty and stock prices wavelet approach this paper examines the link between economic policy uncertainty and stock price in both a time and frequency domain wavelet analysis reveals that the relationship is generally negative but changes over time exhibiting low to high frequency cycles moreover the timing of frequency changes overlaps when us policy uncertainty comoves with other countries policy uncertainty

valuing environmental quality weak complementarity with sets of goods in practice it is frequently impossible to identify a single good which is a weak complement to an environmental amenity for which welfare measures are desired however a set of goods exhibiting this property sometimes exists e g water related recreational activities when the nonmarket good to be valued is water quality a set of weak complements is defined and implications for welfare measurement presented the proper welfare measure now involves evaluation of a line integral and simple additions of areas under demand curves will not always be correct however under certain econometric circumstances approximate welfare measures can be obtained from estimated functions

conditional duration models for high frequency data a review on recent developments this paper reviews the recent literature on conditional duration modeling in high frequency finance these conditional duration models are associated with the time interval between trades price and volume changes of stocks traded in a financial market an earlier review by pacurar provides an exhaustive survey of the first and some of the second generation conditional duration models we consider almost all of the third generation and some of the second generation conditional duration models notable applications of these models and related empirical studies are discussed the paper may be seen as an extension to pacurar

how do you capture liquidity a review of the literature on low frequency stock liquidity researchers have various ways to measure liquidity but most of them come with both merits and demerits this study provides a literature review of low frequency liquidity measures with a primary focus on liquidity measurement as well as its implication on asset pricing based on the dimension it captures a range of existing low frequency measures are divided into four categories of liquidity proxies including transaction cost volume price impact and multidimension based measures we review some well established liquidity proxies a new bid ask spread estimator and price impact ratios proposed recently finally we discuss how good low frequency liquidity measures are at capturing standard liquidity benchmarks which are constructed from high frequency intraday data

the statistical and economic role of jumps in continuous time interest rate models this paper analyzes the role of jumps in continuous time short rate models i first develop a test to detect jump induced misspecification and using treasury bill rates find evidence for the presence of jumps second i specify and estimate a nonparametric jump diffusion model results indicate that jumps play an important statistical role estimates of jump times and sizes indicate that unexpected news about the macroeconomy generates the jumps finally i investigate the pricing implications of jumps jumps generally have a minor impact on yields but they are important for pricing interest rate options

hedonic price analysis and selectivity bias hedonic valuation of quality attributes can be misleading when theassumption that these attributes are exogenous to sample selection isviolated this paper considers the simultaneity between hedonic valuationand sample selection in the context of a model of producer behavior andinvestigates empirically the case where land is demanded for use as an inputeither in agricultural production or in touristic development the empiricalanalysis suggests that failing to correct for sample selection results in abiased valuation of the effect of water salinity on agricultural land