a bayesian approach to modeling stock return volatility for option valuation new measures of stock return volatility are developed to increase the precision of stock option price estimates with bayesian statistical methods volatility estimates for a given stock are developed using prior information on the cross sectional patterns in return volatil ities for groups of stocks sorted on size financial leverage and trading volume call option values computed with the bayesian procedure generally improve prediction accuracy for market prices of call options relative to those computed using implied volatility standard historical volatility or even the actual ex post volatility that occurred during each option s life although the bayesian methods produce biased call price estimators they do reduce the systematic tendency of standard pricing approaches to overprice underprice options on high low volatility stocks little bias improvement is observed with respect to the time to maturity and moneyness of the call options

trading patterns and prices in the interbank foreign exchange market the behavior of quote arrivals and bid ask spreads is examined for continuously recorded deutsche mark dollar exchange rate data over time across locations and by market participants a pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns models for the conditional mean and variance of returns and bid ask spreads indicate volatility clustering at high frequencies the proposition that trading intensity has an independent effect on returns volatility is rejected but holds for spread volatility conditional returns volatility is increasing in the size of the spread there is a growing body of theoretical studies on the pattern of trading activity in financial markets with implications for the time series behavior of transactions prices and intensity of trading the empirical literature addressing similar concerns using intraday market data appropriate for such tasks is sparse particularly in the area of the trading of currencies the purpose of this paper is to examine both international patterns of intraday trading activity and the time series properties of returns and bid ask spreads for the deutsche mark dollar exchange rate in the interbank foreign exchange market the goal is to provide information useful in the further development of market microstructure models of trading and to compare empirical findings against theoretical results already in existence the foreign exchange market is in operation twenty four hours a day seven

heterogeneous information arrivals and return volatility dynamics uncovering the long run in high frequency returns recent empirical evidence suggests that the interdaily volatility clustering for most speculative returns are best characterized by a slowly mean reverting fractionally integrated process meanwhile much shorter lived volatility dynamics are typically observed with high frequency intradaily returns the present article demonstrates that by interpreting the volatility as a mixture of numerous heterogeneous short run information arrivals the observed volatility process may exhibit long run dependence as such the long memory characteristics constitute an intrinsic feature of the return generating process rather than the manifestation of occasional structural shifts these ideas are confirmed by our analysis of a one year time series of fiveminute deutschemark u s dollar exchange rates among the most puzzling issues is the behavior of volatility while the general properties of volatility remain elusive perhaps the most intriguing feature revealed by empirical work on volatility is its long persistence such behavior has sparked a search almost akin to that for the holy grail for the perfect garch model but the underlying question of why such volatility persistence endures remains unanswered we conjecture that the ability to analyze higher frequency data may be particularly useful in pursuing this issue goodhart and o hara 1997 the pronounced volatility clustering is arguably one of the most striking features of financial price series recorded at daily or weekly intervals and a large body of literature seeking to characterize this aspect of speculative returns has emerged over the past decade 1 at the same time convincing theoretical explanations for the underlying sources of long run persistence in volatility remain elusive the recent advent of comprehensive high frequency andersen is from the j l kellogg graduate school of management of northwestern university bollerslev is from the university of virginia and is a research associate at the national bureau of economic research we gratefully acknowledge the financial support provided by a research grant from the institute for quantitative research in finance the q group special thanks are due to olsen and associates for making the intradaily exchange rate quotes and reuter s news tape available we have received valuable comments from wake epps clive w j granger stephen f gray j huston mcculloch as well as seminar participants at the december 1996 triangle econometrics workshop the 1997 afa meetings in new orleans academia sinica the wharton school usc and georgetown and york universities we remain fully responsible for the content 1 see bollerslev chou and kroner 1992 for a survey of this literature using arch type

volume and skewness in international equity markets abstract we examine the relation between trading volume and skewness in 11 international stock markets using daily and monthly data from january 1980 to august 2004 we construct single equation and var models of the relation between the first three moments of market returns and trading volumes our results show hitherto unrecognised channels of influence and support the investor heterogeneity approach to explaining return asymmetries

vector autoregression or simultaneous equations model the intraday relationship between index arbitrage and market volatility abstract we conduct simulations to compare the vector autoregression var and simultaneous equations models sem for examining temporal relationships among arbitrage spreads spot price volatility and futures price volatility contrary to koch 1993 we find that the var model can better reveal the underlying process and that sem can be misleading and may yield unreliable inferences

sources of meteor showers and heat waves in the foreign exchange market abstract we examine the role that news and heterogeneous expectations play in the persistence of exchange rate volatility or so called meteor shower effects our empirical focus is on the u s trade balance news which is shown to have a significant and persisting effect on the exchange rate and its conditional variance furthermore the impact of u s trade balance news is not isolated to the u s foreign exchange market the degree to which u s trade balance news affects other geographical market locations is functionally related to heterogeneous priors

rolling sampled parameters of arch and levy stable models in this paper an asymmetric autoregressive conditional heteroskedasticity arch model and a levy stable distribution are applied to some well known financial indices dax30 ftse20 ftse100 and sp500 using a rolling sample of constant size in order to investigate whether the values of the estimated parameters of the models change over time although there are changes in the estimated parameters reflecting that structural properties and trading behaviour alter over time the arch model adequately forecasts the one day ahead volatility a simulation study is run to investigate whether the time variant attitude holds in the case of a generated arch data process revealing that even in that case the rolling sampled parameters are time varying

price volatility trading volume and market depth evidence from futures markets the relations between volume volatility and market depth in eight physical and financial futures markets are examined evidence suggests that linking volatility to total volume does not extract all information when volume is partitioned into expected and unexpected components the paper finds that unexpected volume shocks have a larger effect on volatility further the relation is asymmetric the impact of positive unexpected volume shocks on volatility is larger than the impact of negative shocks finally consistent with theories of market depth the study shows large open interest mitigates volatility

dynamic discrete mixtures for high frequency prices the tick structure of the financial markets entails discreteness of stock price changes based on this empirical evidence we develop a multivariate model for discrete price changes featuring a mec

economic determinants of trading volume in futures markets abstract in this paper we test first the hypothesis that the volume of trade in futures markets follows a random walk process next we examine the role of several monthly macroeconomic variables and find that these variables have a statistically significant impact on the trading volume the economic consequences of our findings indicate that futures traders futures exchanges regulatory agencies and others associated with futures markets activities act rationally in watching closely these macroeconomic variables

overnight information and stochastic volatility a study of european and us stock exchanges abstract this paper provides a comprehensive evaluation of the predictive ability of information accumulated during nontrading hours for a set of european and us stock indexes we introduce a stochastic volatility model which conditions on lagged overnight information distinguishes between the nontrading periods of weeknights weekends holidays and long weekends and allows for an asymmetric leverage effect on the impact of overnight news we implement bayesian methods for estimation and ranking of the empirical models and find two key results i there is substantial predictive ability in financial information accumulated during nontrading hours and ii the performance of stochastic volatility models improves considerably by separating the asymmetric impact of positive and negative news made available over weeknights weekends holidays and long weekends

informational linkages across trading regions evidence from foreign exchange markets abstract using a new high frequency data set from electronic broking services ebs this paper examines informational linkages in the euro dollar and dollar yen exchange rates across five trading regions asia pacific the asia europe overlap europe the europe america overlap and america information is proxied by exchange rate return direction of return volatility trading activity and order flow we find that informational linkages are statistically significant at both own region and inter region levels but own region spillovers dominate in economic significance especially for volatility and trading activity in addition order flow spillovers from the europe america overlap trading region are the most important source of spillovers to other trading regions for both currency pairs

on the impact of fundamentals liquidity and coordination on market stability complex interactions between fundamentals and liquidity during unstable periods in financial markets are succinctly modeled with co ordination games we propose a flexible framework to estimate such a model and use the efficient method of moments as estimation proce dure we illustrate the model by using exchange rates from the yen dollar carry trade induced uncertainty in 1998 interest rate spreads and global market volatility the model fits the data well with ev idence of low information disparities the market is generally very deep where global volatility is more important than fundamental un certainty in the determination of liquidity there is clear evidence of asymmetry between the buy and sell sides of the market

information time option pricing theory and empirical evidence abstract with a stochastic time change from calendar time to information time we derive a parsimonious option pricing formula with stochastic volatility as a risk neutral poisson sum of merton s 1973 prices over the option s information time maturity domain the formula contains two unobservable parameters information arrival intensity and information time asset volatility with stochastic volatility induced by random information arrival when the information arrival rate intensifies the option price increases and vice versa we test the formula in pricing hedging and excess profits capture empirically using currency and the s p 500 futures options transaction data

accelerated gaussian importance sampler with application to dynamic latent variable models summary we propose a new generic and highly efficient accelerated gaussian importance sampler agis for the numerical evaluation of very high dimensional density functions a specific case of interest to us is the evaluation of likelihood functions for a broad class of dynamic latent variable models the feasibility of our method is strikingly illustrated by means of an application to a first order dynamic stochastic volatility model for daily stock returns whose likelihood for an actual sample of size 2022 is evaluated with high numerical accuracy by means of 10 000 monte carlo replications the estimated model parsimoniously dominates arch and garch alternatives one of which includes twelve lags

causality in quantiles and dynamic stock return volume relations abstract this paper investigates the causal relations between stock return and volume based on quantile regressions we first define granger non causality in all quantiles and propose testing non causality by a sup wald test such a test is consistent against any deviation from non causality in distribution as opposed to the existing tests that check only non causality in certain moment this test is readily extended to test non causality in different quantile ranges in the empirical studies of three major stock market indices we find that the causal effects of volume on return are usually heterogeneous across quantiles and those of return on volume are more stable in particular the quantile causal effects of volume on return exhibit a spectrum of symmetric v shape relations so that the dispersion of return distribution increases with lagged volume this is an alternative evidence that volume has a positive effect on return volatility moreover the inclusion of the squares of lagged returns in the model may weaken the quantile causal effects of volume on return but does not affect the causality per se

an empirical application of stochastic volatility models textabstractthis paper studies the empirical performance of stochastic volatility models for twenty years of weekly exchange rate data for four major currencies we concentrate on the effects of the distribution of the exchange rate innovations for both parameter estimates and for estimates of the latent volatility series the density of the log of squared exchange rate innovations is modelled as a flexible mixture of normals we use three different estimation techniques quasi maximum likelihood simulated em and a bayesian procedure the estimated models are applied for pricing currency options the major findings of the paper are that 1 explicitly incorporating fat tailed innovations increases the estimates of the persistence of volatility dynamics 2 the estimation error of the volatility time series is very large 3 this in turn causes standard errors on calculated option prices to be so large that these prices are rarely significantly different from a model with constant volatility

short term interest rates as subordinated diffusions in this article we cbaracterize and estimate the process for short term interest rates using federal funds interest rate data we presume that we are observing a discrete time sample of a stationary scalar diffusion we concentrate on a class of models in whicb the local volatility elasticity is constant and the drift has aflexible specufication to accommodate missing observations and to break the link between economic time and calendar time we model the sampling scheme as an increasing process that is not directly observed we propose and implement two new methods for estimation we find evidence for a volatility elasticity between one and onehalf and two when interest rates are high local mean reversion is smaul and the mechanism for inducing stationarity is the increased volatility of the diffusion process

intradaily price volume adjustments of nyse stocks to unexpected earnings the speed and path of adjustment in stocks to the degree of earnings surprise in their quarterly announcements are studied using price volume transactions data a differential price adjustment process was observed with stocks having large positive earnings surprises experiencing a faster adjustment compared with those stocks with negative earnings surprises volume transaction frequency and size were found to be directly related to the absolute degree of surprise but very favorable earnings surprise stocks experienced initially a large number of smaller trades while stocks with large unfavorable earnings surprises had relatively fewer transactions but higher volume per trade the stock market s microstructure has received increasing attention from researchers especially from an empirical perspective as transaction data on prices and volume have become more readily available 1 an important subset of this research has been the study of stock price adjustments to significant news events specifically publicly announced information with economic content should be quickly reflected in prices in an unbiased manner this paper contains a study of the intradaily adjustment in stocks to the informational content of earnings reports using price changes trading volume and transaction frequency and size we examine the transaction to transaction and time series stock behavior associated with different degrees of earnings surprise embedded in earnings announcements the degree of surprise is measured by a comparison of actual with forecasted earnings for 325 new york stock exchange nyse firms these firms are subdivided into five earnings surprise categories in order to determine whether the speed and path of their price volume adjustment processes are different one question of interest is whether the adjustment process for favorable versus unfavorable earnings surprises is similar or different another is whether any adjustment is distinguished by a few large trades or a large number of smaller

endogenous trading volume and momentum in stock return volatility this article examines the ability of volume data to shed light on the source of persistence in stock return volatility a mixture model in which a latent common factor restricts the joint density of volume and returns is used to relax the assumption of exogenous volume used in previous studies we use a point in time signal extraction procedure to identify this latent process and a calibrated simulation to conduct analysis of the viability of the model to explain important properties of the data using daily returns and volume on individual stocks our procedure cannot accommodate serial dependence in squared returns

oil and stock market volatility a multivariate stochastic volatility perspective abstract this paper models the volatility of stock and oil futures markets using the multivariate stochastic volatility structure in an attempt to extract information intertwined in both markets for risk prediction it offers four major findings first the stock and oil futures prices are inter related their correlation follows a time varying dynamic process and tends to increase when the markets are more volatile second conditioned on the past information the volatility in each market is very persistent i e it varies in a predictable manner third there is inter market dependence in volatility innovations that hit either market can affect the volatility in the other market in other words conditioned on the persistence and the past volatility in their respective markets the past volatility of the stock oil futures market also has predictive power over the future volatility of the oil futures stock market finally the model produces more accurate value at risk estimates than other benchmarks commonly used in the financial industry

how effective are trading pauses abstract exploiting nasdaq order book data and difference in differences methodology we identify the distinct effects of trading pause mechanisms introduced on us stock exchanges after may 2010 we show that the mere existence of such a regulation makes market participants behave differently in anticipation of a pause pauses enhance price discovery during the break but have adverse effects on price stability and liquidity after the pause we find that pauses ultimately do not cool off markets but cause extra volatility this implies a regulatory trade off between the protective role of trading pauses and their adverse effects on market quality

deutsche mark dollar volatility intraday activity patterns macroeconomic announcements and longer run dependencies this paper provides a detailed characterization of the volatility in the deutsche mark dollar foreign exchange market using an annual sample of five minute returns the approach captures the intraday activity patterns the macroeconomic announcements and the volatility persistence arch known from daily returns the different features are separately quantified and shown to account for a substantial fraction of return variability both at the intraday and daily level the implications of the results for the interpretation of the fundamental driving forces behind the volatility process is also discussed the efficient market hypothesis contends that financial asset prices provide rational assessments of fundamental values and future payoffs by implication price changes should reflect the arrival and processing of all relevant new information however the proportion of return variability that can be ascribed to public news announcements is low for example cutler poterba and summers 1989 find that even the largest daily price changes in the stock market generally cannot be associated with any significant economic news 1 moreover proxies for the flow of public information e g the number of news items released by reuter s news service berry and hiowe 1994 or dow jones company mitchell and mulherin 1994 explain little of the overall variation thus if private information is ruled out proponents of rational price formation have to assert the existence of important news items

liquidity credit quality and the relation between volatility and trading activity evidence from the corporate bond market this paper investigates the roles of illiquidity and credit risk in determining the relations between price volatility of a bond and its trading frequency and trade size based on a large transaction dataset from october 2004 to june 2012 we find a positive relation between volatility and trading frequency and a negative relation between volatility and trade size consistent with the prediction of the search based theory the relations are much stronger for illiquid and risky bonds furthermore both liquidity and credit risk become more important in times of stress and their effects are reinforcing results strongly suggest that search frictions and credit risk are important factors driving the relation between volatility and trading activity in the corporate bond market

bid ask spreads in the interbank foreign exchange markets abstract this study provides evidence on quotations and bid ask spreads in the wholesale foreign exchange market and introduces a method to document variation in the placement of quotes relative to asset value i find that spreads widen with proxies for inventory carrying costs including forecasts of price risk and a measure of liquidity costs increases in spreads before nontrading periods can also be attributed to inventory costs the location of currency quotes in relation to value is not constant and the outcome of hypothesis tests regarding changes in currency value can be sensitive to allowances for variation in quote location

estimating the effects of information surprises and trading on stock returns using a mixed jump diffusion model i present a methodology that uses the mixed jump diffusion model for stock returns to estimate the separate effects of information surprises and strategic trading around corporate events using simulation techniques i show that for events with multiple announcements spread over a long time the estimators derived from the mixed jump diffusion model are more powerful compared to the traditional cumulative abnormal return estimators the new methodology is used to study the separate effects of information surprises and strategic trading associated with blockholdings and subsequent targeted repurchases i find that for more than 93 percent of the firms in our sample the mixed jump diffusion model is statistically superior to the pure diffusion model in describing stock returns more important i find a statistically significant negative effect due to trading while the average effect around announcements is statistically insignificant in contrast the standard cumulative abnormal return is not statistically different from zero article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

volatility and trading activity in short sterling futures the objective of the present study is to examine the interplay between information trading volume and volatility in short sterling futures more specifically the paper concentrates on the role of liquidity variables as conduits of information arrival and whether such variables could be an exclusive platform of the market s information set the analytical framework employed to examine the interaction among those factors is based on the conditional volatility family of techniques the approach is well suited as it naturally leads to examine the interaction among volatility and sources of information in an attempt to identify proxies of information and their role in determining volatility four main conclusions have emerged first the empirical findings suggest that both volume and open interest exhibit a positive correlation with volatility second based on the current methodology one can observe the persistence and importance of garch effects after accounting for liquidity third the liquidity varia

modelling s p 100 volatility the information content of stock returns abstract theoretical models that relate volatility to the quantity of information are extended to a multi asset setting and it is deduced that stock returns may or may not have incremental information when modelling index volatility depending on the sources of information that move stock prices the first empirical study that can help resolve this theoretical uncertainty is presented a detailed analysis of the daily volatility of the s p 100 index from 1984 to 1998 shows there is some incremental volatility information in the returns from the 100 shares that define the index this evidence is obtained from arch models that incorporate leverage effects dummy variables for the 1987 crash and aggregate measures of stock return volatility significant differences between estimated volatilities are found for various stock measures and sub periods

endogenous market thinness and stock price volatility thin equity markets cannot accommodate temporary bulges of buy or sell orders without large price movements the resulting volatility can induce risk averse transactors who face transaction costs to desert these markets thus thinness and the related price volatility may become joint self perpetuating features of an equity market irrespective of the volatility of asset fundamentals if however appropriate incentive schemes are adopted to encourage entry by additional investors this vicious circle can be broken eventually shifting the market to a selfsustaining superior equilibrium characterized by a higher number of transactors lower price volatility and larger supply of the asset a number of empirical studies cohen et al 1976 telser and higimbotham 1977 pagano 1986 tauchen and pitts 1983 have found that thin speculative markets are ceteris paribus more volatile than deep ones a plausible explanation for this finding is that thin markets are generally characterized by small numbers of transactors per unit time and thus their prices are more sensitive to the impact of individual traders demand shocks conversely in deep markets transactors are so many that the uncorrelated demand shocks experienced by individual traders tend to offset each other and leave market prices largely unaffected while this suggests a rationale for the observed relationship between market size and price volatility it does so by taking market size as the exogenous factor however the volatility of a speculative market may feed back on its size in the sense that the high liquidation risk implied by very volatile prices can induce potential entrants to keep out of the market this paper shows that in a stock market with transaction costs this interaction between thinness and volatility can produce multiple steady state equilibria some characterized by low trade and high volatility and others by high trade and low volatility whether the market will settle in one equilibrium or another depends entirely on the expectations held by economic agents sections 2 and 3 the existence of these multiple bootstrap equilibria can be explained heuristically as follows each additional trader generates a positive externality for other actual or potential traders by decreasing the riskiness of the stock lower risk in turn tends to attract more investors with the effect of raising stock prices and inducing corporations to issue additional equity we thus have a feedback loop between market size and price volatility where market size is measured both along the dimension of the number of traders and along that of the total stock of equities if however investors face transactions costs in the stock market this positive feedback may fail to be operative if the volume of trade is expected to be small investors with relatively high transaction costs will abstain from trading thus the market

estimation of dynamic bivariate mixture models this note compares a bayesian markov chain monte carlo approach implemented by watanabe with a maximum likelihood ml approach based on an efficient importance sampling procedure to estimate dynamic bivariate mixture models in these models stock price volatility and trading volume are jointly directed by the unobservable number of price relevant information arrivals which is specified as a serially correlated random variable it is shown that the efficient importance sampling technique is extremely accurate and that it produces results that differ significantly from those reported by watanabe

a non linear filtering approach to stochastic volatility models with an application to daily stock returns this paper develops a new model for the analysis of stochastic volatility sv models since volatility is a latent variable in sv models it is difficult to evaluate the exact likelihood in this paper a non linear filter which yields the exact likelihood of sv models is employed solving a series of integrals in this filter by piecewise linear approximations with randomly chosen nodes produces the likelihood which is maximized to obtain estimates of the sv parameters a smoothing algorithm for volatility estimation is also constructed monte carlo experiments show that the method performs well with respect to both parameter estimates and volatility estimates we illustrate our model by analysing daily stock returns on the tokyo stock exchange since the method can be applied to more general models the sv model is extended so that several characteristics of daily stock returns are allowed and this more general model is also estimated copyright 1999 john wiley sons ltd

liquidity surprise volume and return premia in the oil market abstract we investigate oil market price dynamics in the context of the mixture of distributions hypothesis mdh our econometric model addresses autoregressive properties in returns the impact of surprise volume and conditional oil market return volatility as well as oil market liquidity in the conditional return equation surprise volume as a proxy of private information flow is shown to be unrelated to a set of standard market liquidity proxies oil return heteroscedasticity is found to be partly explained by surprise volume a finding that is consistent with the mdh our findings further show that both oil market liquidity as well as surprise volume shocks are priced in the oil market as such lower levels of lagged market liquidity relate to above average conditional returns surprise volume shocks are associated with lower conditional oil market returns jointly with higher contemporaneous conditional return volatility lagged market liquidity dominates conditional volatility in predicting conditional oil price returns

does vix or volume improve garch volatility forecasts abstractthis article considers whether the inclusion of two additional variables can improve volatility forecasts over a standard garch based model we consider three alternative ways of incorporating the volatility index vix and trading volume as exogenous variables within a selection of garch models we are particularly interested in whether these variables have additional incremental forecast power over and above the baseline garch specification our results suggest that both the vix and volume do provide some additional forecast power and this is generally improved when considering both of these series jointly in the model however while the results may be statistically significant the gain is marginal and the coefficient values small moreover in a horse race exercise vix does not outperform the garch approach in answering the question of whether vix produces better forecasts than the garch model then the answer is no but the informational content of vix cannot be ignored and should be incorp

continuous time models realized volatilities and testable distributional implications for daily stock returns we provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous time jump diffusion models traditionally used in asset pricing finance our approach builds directly on recently developed realized variation measures and non parametric jump detection statistics constructed from high frequency intra day data a sequence of simple to implement moment based tests involving various transformations of the daily returns speak directly to the importance of different distributional features and may serve as useful diagnostic tools in the specification of empirically more realistic continuous time asset pricing models on applying the tests to the 30 individual stocks in the dow jones industrial average index we find that it is important to allow for both time varying diffusive volatility jumps and leverage effects to satisfactorily describe the daily stock price dynamics copyright 2009 john wiley sons ltd

can speculative trading explain the volume volatility relation we derive a speculative trading model with endogenous informed trading that yields a conditionally heteroscedastic time series for trading volume and the squared price changes we use half hourly price change and volume data for ibm during 1988 to test the model and estimate the structural parameters using the simulated method of moments estimation procedure although the model seems to do a reasonable job fitting the unconditional moments of the volume and the squared price change processes it fares less well in fitting the relation between current trading volume and lags of trading volume and squared volume s and its lag s relation to squared price changes

stock prices and volume the authors undertake a comprehensive investigation of price and volume co movement using daily new york stock exchange data from 1928 to 1987 they adjust the data to take into account well known calendar effects and long run trends to describe the process they use a seminonparametric estimate of the joint density of current price change and volume conditional on past price changes and volume four empirical regularities are found 1 positive correlation between conditional volatility and volume 2 large price movements are followed by high volume 3 conditioning on lagged volume substantially attenuates the leverage effect and 4 after conditioning on lagged volume there is a positive risk return relation article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

exchange rate risk and transactions costs evidence from bid ask spreads abstract this paper develops a model of exchange rate bid ask spreads which is used to examine the relationship between exchange rate risk and volatility and to measure transactions costs the empirical results indicate that market makers judge the probability of exchange rate changes based on both recent and long term volatility and that the second moment alone is not a complete measure of volatility while a proxy for trading volume does not have the expected relationship with spreads weekend and holiday effects conform to theory transactions costs vary over time and seem responsive to the imposition of exchange controls

a maximum likelihood approach for non gaussian stochastic volatility models a maximum likelihood approach for the analysis of stochastic volatility models is developed the method uses a recursive numerical integration procedure that directly calculates the marginal likelihood only conventional integration techniques are used making this approach both flexible and simple experimentation shows that the method matches the performance of the best estimation tools currently in use new stochastic volatility models are introduced and estimated the model that best fits recent stock index data is characterized by a highly non gaussian stochastic volatility innovation distribution this model dominates a model that includes an autoregressive conditional heteroscedastic effect in the stochastic volatility process and a model that includes a stochastic volatility effect in the conditional mean

transactions volume and volatility we show that the positive volatility volume relation documented by numerous researchers actually reflects the positive relation between volatility and the number of transactions thus it is the occurrence of transactions per se and not their size that generates volatility trade size has no information beyond that contained in the frequency of transactions our results suggest that theoretical research needs to entertain scenarios in which 1 both the frequency and size of trades are endogenously determined yet 2 the size of trades has no information content beyond that contained in the number of transactions article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

the behaviour of futures prices over time 1985 the behaviour of futures prices over time applied economics vol 17 no 4 pp 713 734

arch models properties estimation and testing abstract the aim of this survey paper is to provide an account of some of the important developments in the autoregressive conditional heteroskedasticity arch model since its inception in a seminal paper by engle 1982 this model takes account of many observed properties of asset prices and therefore various interpretations can be attributed to it we start with the basic arch models and discuss their different interpretations arch models have been generalized in different directions to accommodate more and more features of the real world we provide a comprehensive treatment of many of the extensions of the original arch model next we discuss estimation and testing for arch models and note that these models lead to some interesting and unique problems there have been numerous applications and we mention some of these as we present different models the paper includes a glossary of the acronyms for the models we describe

a carbon market sensitive optimization model for integrated forward reverse logistics globalized supply chains volatile energy and material prices increased carbon regulations and competitive marketing pressure for environmental sustainability are driving supply chain decision makers to reduce carbon emissions enterprises face the necessity and the challenge of implementing strategies to reduce their supply chain environmental impact in order to remain competitive one of the most important strategic issues in this context is the configuration of the logistics network the decision concerning the design of an optimal network of the supply chain plays a vital role in determining the total carbon footprint across the supply chain and also the total cost therefore the logistics network should be designed in a way that it could reduce both the cost and the carbon footprint across the supply chain in this context this research proposes a quantitative optimization model for integrated forward reverse logistics with carbon footprint considerations by integrating the carbon emission into a quantitative operational decision making model with regard to facility layout decisions the proposed research incorporates carbon emission parameters with various decision variables and modifies traditional integrated forward reverse logistics model into decision making quantitative operational model minimizing both the total cost and the carbon footprint the proposed model investigates the extent to which carbon reduction requirements can be addressed under a particular set of parameters such as customer demand rate of return of products etc by selecting proper policy as an alternative to the costly investment in carbon reducing technologies to solve the quantitative model this research implements a modified and efficient forest data structure to derive the optimal network configuration minimizing both the cost and the total carbon footprint of the network a comparative analysis shows the outperformance of the proposed approach over the conventional genetic algorithm ga for large problem sizes

the dependence between hourly prices and trading volume this study provides evidence on joint characteristics of hourly common stock trading vol ume and returns on the new york stock exchange average volume traded shows signifi cant differences across trading hours of the day and across days of the week average returns differ across hours ofthe day and to some extent across days ofthe week there is a strong contemporaneous relation between trading volume and returns and also a rela tion between trading volume and returns lagged up to four hours furthermore the trading volume returns relation is steeper for positive returns than for nonpositive returns

time varying international stock market interaction and the identification of volatility signals abstract this paper investigates the dependency of international stock market interaction on financial volatility we show in a stylized economic model that volatility dependent cross market spillovers can be interpreted in two different ways as indicating information flow or uncertainty if higher volatility in one market leads to higher lower reactions in another market volatility reflects information uncertainty we apply a simultaneous time varying coefficient model where structural arch type variances serve two purposes governing the time variation of spillovers and ensuring statistical identification we analyze data of us and further stock markets indeed we find strong nonlinear volatility dependent spillovers

intraday volatility in the stock index and stock index futures markets we examine the intraday relationship between returns and returns volatility in the stock index and stock index futures markets our results indicate a strong intermarket dependence in the volatility of the cash and futures returns price innovations that originate in either the stock or futures markets can predict the future volatility in the other market we show that this relationship persists even during periods in which the dependence in the returns themselves appears to weaken the findings are robust to controlling for potential market frictions such as asynchronous trading in the stock index our results have implications for understanding the pattern of information flows between the two markets article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

are harvest forecasts news usda announcements and futures market reactions futures market price data for maize and soyabeans are used to examine reactions to us department of agriculture harvest forecasts these forecasts are widely known and reasonably accurate so failure to find significant reaction would indicate that the usda did not contribute additional news relative to information already possessed by traders various t tests f tests and nonparametric chi square tests indicate rejection of the null hypothesis of no significant difference between means of absolute values or variances of changes in closing prices on days following a usda announcement and other days thus the data indicate that significant information is contained in the forecasts

the relation between price changes and trading volume a survey this paper reviews previous and current research on the relation between price changes and trading volume in financial markets and makes four contributions first two empiri cal relations are established volume is positively related to the magnitude of the price change and in equity markets to the price change per se second previous theoretical research on the price volume relation is summarized and critiqued and major insights are emphasized third a simple model ofthe price volume relation is proposed that is consis tent with several seemingly unrelated or contradictory observations and fourth several directions for future research are identified

an empirical analysis of the stock price volume relationship abstract this paper investigates the empirical relationship between absolute stock price changes and trading volume in the stock market using granger causality tests we find that there is a significant causal relationship between absolute price changes and volume at the firm level and that this relationship is stronger in periods surrounding earnings announcements we view this as suggesting that information arrival follows a sequential rather than a simultaneous process although the results do not support an extreme version of either information arrival model

the role of consensus and disagreement in portfolio adjustment a trading volume approach abstract this paper shows that the diffusion of opinions slows down the portfolio adjustment a variance component model of trading volumes is used to analyze nyse and s p 100 index option trading volumes

in defense of inequality this is a perfect time to discuss inequality after a period of three decades when wage inequality among men in the united states grew to approximate pre world war ii levels measured inequality apparently has stabilized and may in fact be decreasing claudia goldin and robert a margo 1992 it is therefore a good time to assess the changes to compare the gains and losses i choose this topic not to offend but because i believe inequality is an economic good that has received too much bad press i also think you will agree that it is a good which like any other can be scarce or overly abundant i am neither trying to praise nor defend poverty and i hope it is understood that the link between wages and income is not especially close particularly at lower incomes where nonemployment dominates wages play many roles in our economy along with time worked they determine labor income but they also signal relative scarcity and abundance and with malleable skills wages provide incentives to render the services that are most highly valued further we all buy and sell labor either directly or indirectly as labor is embodied in products to reverse one of the themes of milton friedman s introductory theory class one man s poison can be another s meat together with rising relative wages the post 1950 increase in the job market employment of women is one of our major accomplishments but it is an accomplishment that has been fueled in part by the low wages earned by those the census classifies as private household workers childcare workers workers in laundries and cleaning establishments food service workers etc as the population ages the prospect of increasing dependence on personal assistance looms for the most part personal assistants and aides earn low wages wages that extend the services we can afford friedman s actual observation is however that one man s meat is not necessarily another s poison friedman 1976 the relatively high wages earned by physicians scientists and university professors have attracted many immigrants to the united states would we be better off if they had not immigrated we could in fact reduce wage inequality by simply proscribing immigration because the wage distribution of immigrants is u shaped relative to that of natives see j p smith and b edmonston 1997 p 180 table 5 4 my guess is that most economists faced with such an option would respond by directing attention to the services immigrants provide my objective is to examine the recent period of increasing wage inequality with an eye toward the positive i describe some of the changes that have occurred speculate about the causes and wrap up with illustrations of consequences i contend that growing inequality has created opportunities that have been exploited by many and that the gains are not restricted to the traditional elite moreover when we have adopted policies to mitigate the downside of increasing inequality which is falling real wages in the lower parts of the distribution a surprising number of individuals have also capitalized on those opportunities in ways that are not productive before turning to the data i want to make a few general observations department of economics texas a m university college station tx 77843 4228 i am indebted to martin gritsch for assistance in extracting the data and to barbara charlton for secretarial support i am also indebted to participants in the ucla rand labor workshop and especially to janet currie and james p smith for comments and suggestions on an earlier draft i have drawn heavily on my previous work much of it in collaboration with kevin m murphy

intra day futures price volatility information effects and variance persistence this paper was prepared for presentation at the conference on nonlinear dynamics and econometrics ucla 5 6 april 1991 under the title information and chronological time effects in intra day futures price volatility the authors are grateful to participants of the nonlinear dynamics conference and to leigh riddick george wang and two anonymous referees for helpful comments the bds program was provided by w d dechert and the bispec program was provided by doug patterson the views stated within are those of the authors and do not necessarily reflect those of the commodity futures trading commission or its staff this paper examines the role of the rate of information arrival proxy variables as they relate to persistence in the variance structure of minute by minute s p 500 index futures returns series the role of contract volume floor transactions the number of price changes executed order imbalance and an information composite in reducing variance persistence is examined all proxy variables are found to explain a significant amount of returns variance while the characteristics of returns data vary daily some evidence of remaining variance persistence is found regardless of the definition of the rate of information arrival variable our results suggest that utilization of a pure arch type model for highfrequency returns data implies a mis specification

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

feedback traders and stock return autocorrelations evidence from a century of daily data the authors investigate whether the degree of autocorrelation shown by high frequency stock returns changes with volatility this may result from nontrading effects feedback trading strategies or variable risk aversion the authors results indicate that when volatility is low daily and hourly stock returns exhibit positive autocorrelation but when it is high returns exhibit negative serial correlation they also find an important asymmetry negative serial correlation is more likely after price declines this is consistent with price declines being more likely to induce positive feedback trading the authors also find no significant relation between margin requirements and the autocorrelation of returns copyright 1992 by royal economic society

volatility volume causality across single stock spot futures markets in india abstractthis study examines the causal relationships between volatility and volume across spot and futures market for the 50 constituent stocks of the cnx nifty index granger non causality tests implemented using vector autoregression var and asymmetric var models indicate the presence of significant causal relations from both the spot and futures volume to both the spot and futures volatility bidirectional causal relationships between spot and futures volume were observed for almost all stocks but few stocks displayed a similar relationship between volatilities the results highlight the importance of volume in absorbing information and its behaviour as the conduit of information

the impact of energy derivatives on the crude oil market we examine the effects of energy derivatives trading on the crude oil market there is a common public and regulatory perception that derivative securities increase volatility and can have a destabilizing effect on the underlying market consistent with this view we find an abnormal increase in volatility for three consecutive weeks following the introduction of nymex crude oil futures while there is also evidence of a longer term volatility increase this is likely due to exogenous factors such as the continuing deregulation of the energy markets subsequent introductions of crude oil options and derivatives on other energy commodities have no effect on crude oil volatility we also examine the effects of derivatives trading on the depth and liquidity of the crude oil market this analysis reveals a strong inverse relation between the open interest in crude oil futures and spot market volatility specifically when open interest is greater the volatility shock associated with a given unexpected increase in volume is much smaller

common trends in global volatility abstract this paper investigates the long term patterns in global foreign exchange equity and bond markets in three different trading zones namely japan europe and the united states recent advances in the measurement of volatility from high frequency data are used together with the concepts of fractional integration and cointegration the specific objective is to consider whether there are common trends that drive volatility in the global marketplace this so called commonality in volatility hypothesis is formulated using a cofractional model the results confirm that volatility in all three financial asset markets across all three trading zones share a single common trend which lends itself to interpretation as a global news stream

the dynamic relationship between stock returns and trading volume domestic and cross country evidence abstract this paper examines the dynamic relations causal relations and the sign and magnitude of dynamic effects between stock market trading volume and returns and volatility for both domestic and cross country markets by using the daily data of the three largest stock markets new york tokyo and london major findings are as follows first trading volume does not granger cause stock market returns on each of three stock markets second there exists a positive feedback relationship between trading volume and return volatility in all three markets third regarding the cross country relationships us financial market variables in particular us trading volume contains an extensive predictive power for uk and japanese financial market variables fourth sub sample analyses show evidence of stronger spillover effects after the 1987 market crash and an increased importance of trading volume as an information variable after the introduction of options in the us and japan

volume volatility and public news announcements we provide new empirical evidence for the way in which financial markets process information our results rely critically on high frequency intraday price and volume data for the s p 500 equity portfolio and u s treasury bonds along with new econometric techniques for making inference on the relationship between trading intensity and spot volatility around public news announcements consistent with the predictions derived from a theoretical model in which investors agree to disagree our estimates for the intraday volume volatility elasticity around important news announcements are systematically below unity our elasticity estimates also decrease significantly with measures of disagreements in beliefs economic uncertainty and textual based sentiment further highlighting the key role played by differences of opinion

using implied volatility on options to measure the relation between asset returns and variability abstract prior research has documented that volatility in financial asset markets is most directly related to trading rather than calendar days and that there is an inverse asymmetric relation between volatility and returns in both stocks and long term bonds we examine these relations in 37 futures options markets representing a wide variety of asset types using futures prices and implied volatilities from this extensive array of markets we confirm that in all of them save one market volatility is more directly related to trading days however the nature of the association between implied volatility and underlying asset returns varies greatly across asset categories and across exchanges thus we show that findings from equity markets apparently are not generalizable to other asset classes

a note on intraday foreign exchange volatility and the informational role of quote arrivals abstract the conditional variance for five different hourly foreign exchange rates is modeled using a garch model with the number of incoming quotes as a regressor in the conditional variance equation we find that the number of quotes is positively and significantly related to the volatility of all rates examined the empirical findings support the conjecture of a time consuming information process

a dynamic equilibrium model of asset prices and transaction volume a dynamic general equilibrium model of capital asset pricing is constructed in which the volume of capital traded is determined endogenously the model also gives rise to a novel asset pricing formula it is shown that temporary shocks can give rise to serially correlated changes in the price of capital and transaction volume that persist long after the initial disturbance the frequency and amplitude of the resulting cycles are related to the length of the agent s planning horizon and the discount factor the model s implications for explaining asset price volatility are also explored

futures trading with information asymmetry and otc predominance another look at the volume volatility relations in the european carbon markets this paper constitutes the first exercise of analysing the european carbon market efficiency from a double perspective combining both nature of execution venues screen vs otc trading and their volatility liquidity relations using a bivariate asymmetric gjr garch model we first document that otc exchange traded trading volume shows consistent bi uni directional granger causality to our volatility estimates consistent with greater responsiveness of the otc exchange traded market to changes in market wide idiosyncratic risks second we report significant contemporaneous and lagged positive causality of otc derivatives volume on spot futures volatility confirming that the sequential information arrival hypothesis siah applies third we find that the one way causality from otc to futures volumes is mainly driven by heterogeneous investor beliefs trading volume provides an indication on how private information is dispersed and held at different levels rather than proxying information signal itself after rejecting execution venues substitutability we advocate for systematic clearing and netting of otc positions through a unique clearing house and reporting rules to identify speculation in line with mifid art 59 proposals

volatility volume co movements evidence from china metal markets abstractthis article investigates the interactional relationship between price volatility and futures trading activity for three heavily traded metal products on the shanghai metal exchange and the shanghai futures exchange using models based on vector autoregression and generalized method of moments we show in particular that futures trading activity has a strong impact on both spot and futures price volatility in copper and aluminium markets futures trading activity leads spot market volatility in copper and aluminium markets which suggests that futures markets have a destabilizing effect in order to disentangle the effect of different traders types on asset price movements we decompose futures trading into speculators and hedgers trading and investigate their contributions to volatility as a robustness check we investigate the impact of endogenous structural breaks on the interactional relationship between price volatility and futures trading

the price variability volume relationship on speculative markets this paper concerns the relationship between the variability of the daily price change and the daily volume of trading on the speculative markets our work extends the theory of speculative markets in two ways first we derive from economic theory the joint probability distribution of the price change and the trading volume over any interval of time within the trading day and second we determine how this joint distribution changes as more traders enter or exit from the market the model s parameters are estimated by fiml using daily data from the 90 day t bills futures market the results of the estimation can reconcile a conflict between the price variability volume relationship for this market and the relationship obtained by previous investigators for other speculative markets this paper concerns the relationship between the variability of the daily price change and the volume of trading on speculative markets previous empirical studies 2 3 6 12 14 16 of both futures and equity markets always find a positive association between price variability as measured by the squared price change ap2 and the trading volume 2 there are two explanations for the relationship clark s 2 explanation which is secondary to his effort to explain why the probability distribution of the daily price change is leptokurtic emphasizes randomness in the number of within day transactions in clark s model the daily price change is the sum of a random number of within day price changes the variance of the daily price change is thus a random variable with a mean proportional to the mean number of daily transactions clark argues that the trading volume is related positively to the number of within day transactions and so the trading volume is related positively to the variability of the price change the second explanation is due to epps and epps 6 their model examines the mechanics of within day trading the change in the market price on each within day transaction or market clearing is the average of the changes in all of the traders reservation prices epps and epps assume there is a positive relationship between the extent to which traders disagree when they revise their reservation prices and the absolute value of the change in the market price that is an increase in the extent to which traders disagree is associated with a larger absolute price change the price variability volume relationship arises then because the volume of trading is positively related to the extent to which traders disagree when they revise their reservation prices

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

long memory in volatility and trading volume abstract we use fractionally integrated time series models to investigate the joint dynamics of equity trading volume and volatility bollerslev and jubinski 1999 show that volume and volatility have a similar degree of fractional integration and they argue that this evidence supports a long run view of the mixture of distributions hypothesis we examine this issue using more precise volatility estimates obtained using high frequency returns i e realized volatilities our results indicate that volume and volatility both display long memory but we can reject the hypothesis that the two series share a common order of fractional integration for a fifth of the firms in our sample moreover we find a strong correlation between the innovations to volume and volatility which suggests that trading volume can be used to obtain more precise estimates of daily volatility for cases in which high frequency returns are unavailable

bridging the gap between the distribution of realized ecu volatility and arch modelling of the euro the garch nig model summary this paper bridges the gap between traditional arch modelling and recent advances on realized volatilities based on a ten year sample of five minute returns for the ecu basket currencies versus the us dollar we find that the realized volatilities constructed from the summation of the high frequency intraday squared returns conditional on the lagged squared daily returns are approximately inverse gaussian ig distributed while the distribution of the daily returns standardized by their realized volatilities is approximately normal moreover the implied daily garch model with normal inverse gaussian nig errors estimated for the ecu returns results in very accurate out of sample predictions for the three years of actual daily euro us dollar exchange rates copyright 2002 john wiley sons ltd

information aggregation in a noisy rational expectations economy abstract this paper analyzes a general equilibrium model of a competitive security market in which traders possess independent pieces of information about the return of a risky asset each trader conditions his estimate of the return both on his own private source of information and price which in equilibrium serves as a noisy aggregator of the total information observed by all traders a closed form characterization of the rational expectations equilibrium is presented a counter example to the existence of fully revealing equilibrium is developed