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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

credit reallocation deleveraging and financial crises this paper studies how the process of reallocation of credit across firms behaves before and after financial crises applying the methodology typically used for measuring job reallocation we track credit reallocation across korean firms for over three decades 1980 2012 the credit boom preceding the 1997 crisis featured a slowdown of credit reallocation after the crisis and the associated reforms the creditless recovery deleveraging masked a dramatic intensification and increased procyclicality of credit reallocation the findings suggest that the intensification of reallocation was efficiency enhancing

interactive learning informal networks and innovation evidence from electronics firm survey in the pearl river delta china learning by interacting defines the endogenous path of economic development in modern innovation studies in this paper we aim to investigate the way that firms undertake interactive learning in the chinese context by introducing the role of informal guanxi network in this way this paper tries to bridge the gap between studies on firm innovation activities and those on the role of informal network for business performance based on an electronics firm survey in the pearl river delta china this article demonstrates that firms undertaking the highest intensity of interactive learning with the widest scope of business partners such as foreign customers domestic customers parent companies universities and sales agents tend to achieve better innovation outcomes it also verifies a more important role of interactive learning in incremental product innovation than in discontinuous innovation as electronics firms operate in highly modularized value chains furthermore the intensive interactive learning firms have a much higher tendency to apply informal guanxi networks with long term business partners as a complement to deficient formal institutions in interactive learning than other firms overall this paper contributes to the understanding of the form and effect of interactive learning in the chinese context finally the paper addresses the possible lock in issue and points out further research questions on the changing pattern of interactive learning within a maturing institutional framework

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

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

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

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