investor preference for large firms new evidence on economies of size in the last several decades industrial organization literature has been replete with studies demonstrating a systematic relationship between accounting rates of return and firm size in the direction of greater and more stable accounting profits for larger firms these studies have been subject to criticism for an alarming number of statistical and conceptual problems the most important of which alleges a serious bias in accounting profit measures as proxies for economic profit 2 the criticisms have resulted in a stalemate in the interpretation of empirical evidence on firm size and performance nevertheless there is continued interest in the area ostensibly resulting from policy concerns with large firm advantages in both product and capital markets this paper provides new evidence concerning the industrial organization literature controversy of the connection between firm size and performance stock market data are used to examine the relationship between capital market returns risk and firm size the findings suggest that even if there were no advantages of large size in the product market equal rates of operating profit large firms would still have a substantial capital raising advantage over small firms this advantage is unrelated to the widely recognized floatation cost economies even after controlling for nondiversifiable risk using the capital asset pricing model capm investors still demonstrate a statistically significant and economically important preference for the securities of larger firms investors apparently place a premium on large firms which is not attributable to large firms observed lower risk as captured by the widely used measure of nondiversifiable risk beta risk this finding a fresh contribution to the

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

can oil prices forecast exchange rates an empirical analysis of the relationship between commodity prices and exchange rates we show the existence of a very short term relationship at the daily frequency between changes in the price of a country s major commodity export and changes in its nominal exchange rate the relationship appears to be robust and to hold when we use contemporaneous realized commodity price changes in our regression however when we use lagged commodity price changes the predictive ability is ephemeral mostly appearing after instabilities have been appropriately taken into account

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

moments based spillovers across gold and oil markets abstract in this paper we use intraday futures market data on gold and oil to compute returns realized volatility volatility jumps realized skewness and realized kurtosis using these daily metrics associated with two markets over the period of december 2 1997 to may 26 2017 we conduct linear nonparametric and time varying rolling tests of causality with the latter two approaches motivated due to the existence of nonlinearity and structural breaks while there is hardly any evidence of spillovers between the returns of these two markets strong evidence of bidirectional causality is detected for realized volatility which seems to be resulting from volatility jumps evidence of spillovers are also detected for the crash risk variables i e realized skewness and for realized kurtosis as well with the effect on the latter being relatively stronger based on a moments based test of causality evidence of co volatility is deduced whereby we find that extreme positive and negative returns of gold and oil tend to drive the volatilities in these markets in our robustness check we identify a causal chain in the realized volatility from oil to gold via the financial stress our results have important implications for not only investors but also policymakers

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

constant and variable returns to scale dea models for socially responsible investment funds abstract in order to evaluate the performance of socially responsible investment sri funds we propose some models which use data envelopment analysis dea and can be computed in all phases of the business cycle these models focus on the most crucial elements of an investment in mutual funds in the literature both constant and variable returns to scale dea models have been used to evaluate the performance of mutual funds we carry out an empirical investigation on european sri equity funds to test the presence of returns to scale rts another aspect taken into account by the empirical investigation is the measurement of the degree of social responsibility of sri equity funds in various european countries in addition we analyse the performance of the funds considered with the different dea models proposed which differ in the way the ethical objective is taken into account moreover the paper focuses on another crucial issue regarding socially responsible investing the comparison of the performances between sri and non sri funds the empirical study suggests that the ethical objective can be pursued without having to renounce financial rewards

magnitude and persistence of extreme risk spillovers in the global energy market a high dimensional left tail interdependence perspective abstract this paper studies the magnitude and persistence of extreme risk spillovers among stock returns of 124 energy companies worldwide between january 2006 and june 2019 as well as the corresponding firm specific determinants of firms extreme risk spillovers the high dimensional nonparametric method the coefficient of tail interdependence cti enables us to make better use of available information and to evaluate risk spillovers more precisely moreover we use spatial panel models that consider spatial heterogeneity among firms to explore the determinants of the risk spillovers the empirical findings from a study of energy firms risk spillover effects verify the necessity of persistence measurement also the most systemically risky energy companies are not necessarily the largest and some small firms can also generate large risk spillovers when they are in distress which indicates that determinants other than firm size could also affect the spillover effect such as business complexity and geographic location our regression results suggest that the extreme risk spillover of the energy companies exhibits significant heterogeneity in terms of business and region which deserves more attention for energy risk management the estimates can be used for making portfolio decisions and designing regulatory policies

an equilibrium efficiency frontier data envelopment analysis approach for evaluating decision making units with fixed sum outputs abstract based on the minimal reduction strategy yang et al 2011 developed a fixed sum output data envelopment analysis fsodea approach to evaluate the performance of decision making units dmus with fixed sum outputs however in terms of such a strategy all dmus compete over fixed sum outputs with no memory that will result in differing efficient frontiers evaluations to address the problem in this study we propose an equilibrium efficiency frontier data envelopment analysis eefdea approach by which all dmus with fixed sum outputs can be evaluated based on a common platform or equilibrium efficient frontier the proposed approach can be divided into two stages stage 1 constructs a common evaluation platform via two strategies an extended minimal adjustment strategy and an equilibrium competition strategy the former ensures that original efficient dmus are still efficient guaranteeing the existence of a common evaluation platform the latter makes all dmus achieve a common equilibrium efficient frontier then based on the common equilibrium efficient frontier stage 2 evaluates all dmus with their original inputs and outputs finally we illustrate the proposed approach by using two numerical examples

nowcasting the real time informational content of macroeconomic data abstract a formal method is developed for evaluating the marginal impact that intra monthly data releases have on current quarter forecasts nowcasts of real gross domestic product gdp growth the method can track the real time flow of the type of information monitored by central banks because it can handle large data sets with staggered data release dates each time new data are released the nowcasts are updated on the basis of progressively larger data sets that reflecting the unsynchronized data release dates have a jagged edge across the most recent months

issuing costs to existing shareholders in competitive and negotiated underwritten public utility equity offerings abstract this paper presents the results of an empirical investigation of whether there is any difference in the cost incurred by public utilities if they issue new equity through a negotiated or competitive underwriting we conclude that the expected cost of a competitive offer is less than the expected cost of a negotiated offer but that the variance of the cost is substantially greater with a competitive offer these results are interesting because most public utilities use negotiated underwriting unless forced by regulation to use competitive offers this paper is also an addition to the growing agency theory literature

macro economy stock market and oil prices do meaningful relationships exist among their cyclical fluctuations this paper examines the relationship among consumer price index industrial production stock market and oil prices in greece initially we use a unified statistical framework cointegration and vecm to study the data in levels we then employ a multivariate var model to examine the relationship among the cyclical components of our series the period of the study is from 1996 1 to 2008 6 findings suggest that oil prices and the stock market exercise a positive effect on the greek cpi in the long run cyclical components analysis suggests that oil prices exercise significant negative influence to the stock market in addition oil prices are negatively influencing cpi at a significant level however we find no effect of oil prices on industrial production and cpi finally no relationship can be documented between the industrial production and stock market for the greek market the findings of this study are of particular interest and importance to policy makers financial managers financial analysts and investors dealing with the greek economy and the greek stock market

some models for estimating technical and scale inefficiencies in data envelopment analysis in management contexts mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best in this capacity mathematical programming serves as a planning aid to management data envelopment analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments however they may have been planned or executed mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities the ccr ratio form introduced by charnes cooper and rhodes as part of their data envelopment analysis approach comprehends both technical and scale inefficiencies via the optimal value of the ratio form as obtained directly from the data without requiring a priori specification of weights and or explicit delineation of assumed functional forms of relations between inputs and outputs a separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of dea directly on observational data technical inefficiencies are identified with failures to achieve best possible output levels and or usage of excessive amounts of inputs methods for identifying and correcting the magnitudes of these inefficiencies as supplied in prior work are illustrated in the present paper a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing constant or decreasing returns to scale in multiple input and multiple output situations the results are discussed and related not only to classical single output economics but also to more modern versions of economics which are identified with contestable market theories

volatility spillovers between oil prices and stock sector returns implications for portfolio management abstract in this article we take a recent generalized var garch approach to examine the extent of volatility transmission between oil and stock markets in europe and the united states at the sector level the empirical model is advantageous in that it typically allows simultaneous shock transmission in the conditional returns and volatilities insofar as volatility transmission across oil and stock sector markets is a crucial element for portfolio designs and risk management we also analyze the optimal weights and hedge ratios for oil stock portfolio holdings with respect to the results our findings point to the existence of significant volatility spillover between oil and sector stock returns however the spillover is usually unidirectional from oil markets to stock markets in europe but bidirectional in the united states our back testing procedures finally suggest that taking the cross market volatility spillovers estimated from the var garch models often leads to diversification benefits and hedging effectiveness better than those of commonly used multivariate volatility models such as the ccc garch of bollerslev 1990 the diagonal bekk garch of engle and kroner 1995 and the dcc garch of engle 2002

does high frequency crude oil futures data contain useful information for predicting volatility in the us stock market new evidence abstract this study examines whether high frequency crude oil futures data contain useful information to forecast the realized volatility rv of the us stock market from both in and out of sample perspectives there are several significant findings first from the in sample analysis crude oil futures rv exhibits a significant positive impact on the future s p 500 volatility second the out of sample results reveal that the prediction models including crude oil futures rv outperform the related competing models implying that crude oil rv is an important predictive factor for the us stock market third we further find that the primary forecasting ability of crude oil rv is reflected in high frequency information negative crude oil rv and high volatility level finally the out of sample empirical results based on different forecasting windows alternative forecast evaluation approaches subsample analysis different prediction models alternative midas lags and controlling the leverage effect are robust to our conclusions

convertible bond underpricing renegotiable covenants seasoning and convergence we investigate the long standing puzzle on the underpricings of convertible bonds we hypothesize that the observed underpricing is induced by the possibility that a convertible bond might renegotiate on some of its covenants e g an imbedded put option in financial difficulties consistent with our hypothesis we find that the initial underpricing is larger for lower rated bonds the underpricing worsens if the issuer experiences subsequent financial difficulties however conditional on no rating downgrades our main empirical result shows that convertible bond prices do converge to their theoretical prices within two years this seasoning period is shorter for higher rated convertible bonds

realized volatility transmission the role of jumps and leverage effects this paper is the first to employ a multivariate extension of the lhar cj model for realized volatility of corsi and reno 2012 considering continuous and jump volatility components and leverage effects the model is applied to financial s p 500 commodity wti crude oil and forex us eur intraday futures data and allows new insights in the transmission mechanisms among these markets besides significant leverage effects we find that the jump components of all considered assets do not contain incremental information for the one step ahead realized volatility the volatility of s p 500 and us eur exchange rate futures exhibits significant spillovers to the realized volatility of wti moreover decreasing equity prices appear to increase volatility in other markets while strengthening of the us seems to calm down the crude oil market

forecasting volatility of the u s oil market abstract we examine the information content of the cboe crude oil volatility index ovx when forecasting realized volatility in the wti futures market additionally we study whether other market variables such as volume open interest daily returns bid ask spread and the slope of the futures curve contain predictive power beyond what is embedded in the implied volatility in out of sample forecasting we find that econometric models based on realized volatility can be improved by including implied volatility and other variables our results show that including implied volatility significantly improves daily and weekly volatility forecasts however including other market variables significantly improves daily weekly and monthly volatility forecasts

portfolio performance evaluation in a mean variance skewness framework abstract astronomical amounts of money are being invested in financial markets consequently the evaluation of portfolio performance has created a great deal of interest among practitioners as well as academic researchers the literature suggests that portfolio efficiency based on mean variance skewness is more desirable than the one based on mean variance however there are no well established procedures to measure efficiency in this framework mainly due to the computational difficulties the aim of this paper is to develop a portfolio performance measure based on mean variance skewness framework by utilizing a non parametric efficiency analysis tool namely data envelopment analysis

equilibrium pricing and portfolio composition in the presence of uncertain parameters abstract we analyze the effect of parameter uncertainty on equilibrium asset prices for the symmetric case when the amount of estimation risk is the same for all securities the existing literature argues that parameter uncertainty is largely irrelevant for equilibrium our results differ we find that symmetric estimation risk affects equilibrium values of relative asset prices expected returns market weights and betas

resampling dea estimates of investment fund performance abstract data envelopment analysis dea is attractive for comparing investment funds because it handles different characteristics of fund distribution and gives a way to rank funds there is substantial literature applying dea to funds based on the time series of funds returns this article looks at the issue of uncertainty in the resulting dea efficiency estimates investigating consistency and bias it uses the bootstrap to develop stochastic dea models for funds derive confidence intervals and develop techniques to compare and rank funds and represent the ranking it investigates how to deal with autocorrelation in the time series and considers models that deal with correlation in the funds returns

on the diversification observability and measurement of estimation risk this paper reexamines how risk return relationships are affected by investor uncertainty about the exact parameters of the joint rate of return distribution we attempt to clarify results relating to three central issues first we address the issue of diversification focusing on an apt factor model framework second we discuss the observability of estimation risk and describe research experimental designs that should encompass the existence of estimation risk and reveal it in the data finally we suggest exploiting contemporaneous return observations on high and low information securities to aid in the measurement of return parameters for low information securities

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

efficiency of mutual funds and portfolio performance measurement a non parametric approach abstract in finance portfolio performance assessment is an important area of research the two popular indices of performance are the jensen s alpha and the sharpe index however there are a number of shortcomings of the above measures that have been highlighted in the literature we propose a new measure of performance that seeks to address the limitations of the earlier indices the new index is calculated by employing a well known method in operations research called data envelopment analysis we show the benefits of the proposed approach and assess the performance of mutual funds we compare the results with traditional indices of performance an interesting result we obtain is that the mutual funds are all approximately mean variance efficient

on the seasoning process of new bonds some are more seasoned than others in recent years there have been a number of studies investigating the yield spread phenomena between new and seasoned bonds 1 2 3 4 8 10 13 this literature focuses upon two aspects of the equilibrium pricing of new versus seasoned bonds l analysis of the microeconomic determinants of new issue seasoned issue yield spreads such as specific differences in coupon rates call features maturity features and the like and 2 analysis of macroeconomic determinants of yield spreads such as economic growth interest rate cycles changing marginal tax rates and the like

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

the optimal spread and offering price for underwritten securities abstract the paper develops the net proceeds maximization theory explaining how the spread and offering price are determined in all underwritten offerings in the u s the theory yields solutions for the optimal spread and offering price for all underwritten securities and it yields comparative statics that explain the cross sectional variation in actual spreads and initial returns across different types of underwritten securities the theory also suggests two alternative explanations to the ones offered by chen and ritter j finance 55 2000 1105 for the clustering of unseasoned equity offerings spreads at 7

what central bankers need to know about forecasting oil prices central banks routinely use short horizon forecasts of the quarterly price of oil in assessing the global and domestic economic outlook we address a number of econometric issues specific to the construction of quarterly oil price forecasts in the united states and abroad we show that quarterly forecasts of the real price of oil from suitably designed vector autoregressive models estimated on monthly data generate the most accurate real time forecasts overall among a wide range of methods including quarterly averages of forecasts based on monthly oil futures prices no change forecasts and forecasts based on regression models estimated on quarterly data

disagreement portfolio optimization and excess volatility disagreement a key factor inducing trading has been receiving ever increasing attention in recent years most research has focused on disagreement about the expected returns several authors have shown that if the average belief coincides with the true expected return in the portfolio context prices are unaffected by disagreement in this paper we study the pricing effects of disagreement about return variances we show that i disagreement about variances has systematic and significant pricing effects more disagreement leads to higher prices and ii prices are very sensitive to the degree of disagreement even if the average belief about the variance is constant tiny fluctuations in the disagreement about the variance lead to substantial price fluctuations this second result may offer an explanation for the excess volatility puzzle when small changes in the degree of disagreement occur they induce relatively large price changes yet the changes in disagreement may be hard to directly detect empirically leading to apparent excess volatility

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

dynamics of oil price precious metal prices and exchange rate this study examines the co movements and information transmission among the spot prices of four precious metals gold silver platinum and palladium oil price and the us dollar euro exchange rate we find evidence of a weak long run equilibrium relationship but strong feedbacks in the short run the spot precious metal markets respond significantly but temporarily to a shock in any of the prices of the other metal prices and the exchange rate furthermore we discover some evidence of market overreactions in the palladium and platinum cases as well as in the exchange rate market in conclusion whether there are overreactions and re adjustments or not investors may diversify at least a portion of the risk away by investing in precious metals oil and the euro policy implications are provided

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

a nonparametric garch model of crude oil price return volatility the use of parametric garch models to characterise crude oil price volatility is widely observed in the empirical literature in this paper we consider an alternative approach involving nonparametric method to model and forecast oil price return volatility focusing on two crude oil markets brent and west texas intermediate wti we show that the out of sample volatility forecast of the nonparametric garch model yields superior performance relative to an extensive class of parametric garch models these results are supported by the use of robust loss functions and the hansen s 2005 superior predictive ability test the improvement in forecasting accuracy of oil price return volatility based on the nonparametric garch model suggests that this method offers an attractive and viable alternative to the commonly used parametric garch models

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

frontier based vs traditional mutual fund ratings a first backtesting analysis we explore the potential benefits of a series of existing and new non parametric convex and non convex frontier based fund rating models to summarize the information contained in the moments of the mutual fund price series limiting ourselves to the traditional mean variance portfolio setting we test in a simple backtesting setup whether these efficiency measures fare any better than more traditional financial performance measures in selecting promising investment opportunities the evidence points to a remarkable superior performance of these frontier models compared to most but not all traditional financial performance measures

forecasting oil prices high frequency financial data are indeed useful abstract the paper examines the importance of combining high frequency financial information along with the oil market fundamentals in order to gain incremental forecasting accuracy for oil prices inspired by french et al 1987 and bollerslev et al 1988 who maintain that future asset returns are also influenced by past volatility we use daily volatilities and returns from financial and commodity markets to generate real out of sample forecasts for the monthly oil futures prices our results convincingly show that although the oil market fundamentals are useful for long run forecasting horizons the combination of the latter with high frequency financial data significantly improve oil price forecasts by reducing the rmse of the no change forecast by approximately 68 results are even more impressive during the oil price collapse period of 2014 15 these findings suggest that we cannot ignore the information extracted from the financial markets when forecasting oil prices our results are both statistically and economically significant as suggested by several robustness tests

modeling volatility and correlations between emerging market stock prices and the prices of copper oil and wheat abstract increased financial integration between countries and the financialization of commodity markets are providing investors with new ways to diversify their investment portfolios this paper uses varma agarch and dcc agarch models to model volatilities and conditional correlations between emerging market stock prices copper prices oil prices and wheat prices the dynamic conditional correlation model is found to fit the data the best and used to generate dynamic conditional correlations hedge ratios and optimal portfolio weights emerging market stock prices and oil prices display leverage effects where negative residuals tend to increase the variance conditional volatility more than positive ones correlations between these assets increased considerably after 2008 and have yet to return to their pre 2008 values on average oil provides the cheapest hedge for emerging market stock prices while copper is the most expensive but given the variability in the hedge ratios one should probably not put too much emphasis on average hedge ratios

misspecification of capital asset pricing this study documents empirical anomalies which suggest that either the simple one period capital asset pricing model capm is misspecified or that capital markets are inefficient in particular portfolios based on firm size or earnings price e p ratios experience average returns systematically different from those predicted by the capm furthermore the abnormal returns persist for at least two years this persistence reduces the likelihood that these results are being generated by a market inefficiency rather the evidence seems to indicate that the equilibrium pricing model is misspecified however the data also reveals that an e p effect does not emerge after returns are controlled for the firm size effect the firm size effect largely subsumes the e p effect thus while the e p anomaly and value anomaly exist when each variable is considered separately the two anomalies seem to be related to the same set of missing factors and these factors appear to be more closely associated with firm size than e p ratios

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

energy markets volatility modelling using garch abstract this paper investigates the empirical properties of oil natural gas and electricity price volatilities using a range of univariate and multivariate garch models and daily data from wholesale markets in the united states for the period from 2001 to 2013 the key contribution to the literature is the estimation of trivariate bekk and dcc models that allow us to observe spillovers and interactions among energy markets we evaluate and compare the performance of univariate and multivariate models with a range of diagnostic and forecast performance tests and assess forecasting performance and conditional correlation dynamics

can exchange rates forecast commodity prices we show that commodity currency exchange rates have surprisingly robust power in predicting global commodity prices both in sample and out of sample and against a variety of alternative benchmarks this result is of particular interest to policy makers given the lack of deep forward markets in many individual commodities and broad aggregate commodity indices in particular we also explore the reverse relationship commodity prices forecasting exchange rates but find it to be notably less robust we offer a theoretical resolution based on the fact that exchange rates are strongly forward looking whereas commodity price fluctuations are typically more sensitive to short term demand imbalances

the effects of crude oil shocks on stock market shifts behaviour a regime switching approach abstract in this paper we develop a two regime markov switching egarch model introduced by henry henry o 2009 regime switching in the relationship between equity returns and short term interest rates journal of banking and finance 33 405 414 to examine the relationship between crude oil shocks and stock markets an application to stock markets of uk france and japan over the sample period january 1989 to december 2007 illustrates plausible results we detect two episodes of series behaviour one relative to low mean high variance regime and the other to high mean low variance regime furthermore there is evidence that common recessions coincide with the low mean high variance regime in addition we allow both real stock returns and probability of transitions from one regime to another to depend on the net oil price increase variable the findings show that rises in oil price has a significant role in determining both the volatility of stock returns and the probability of transition across regimes

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

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

data envelopment analysis of mutual funds based on second order stochastic dominance abstract although data envelopment analysis dea has been extensively used to assess the performance of mutual funds mf most of the approaches overestimate the risk associated to the endogenous benchmark portfolio this is because in the conventional dea technology the risk of the target portfolio is computed as a linear combination of the risk of the assessed mf this neglects the important effects of portfolio diversification other approaches based on mean variance or mean variance skewness are non linear we propose to combine dea with stochastic dominance criteria thus in this paper six distinct dea like linear programming lp models are proposed for computing relative efficiency scores consistent in the sense of necessity with second order stochastic dominance ssd the aim is that being ssd efficient the obtained target portfolio should be an optimal benchmark for any rational risk averse investor the proposed models are compared with several related approaches from the literature

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

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

realized volatility transmission between crude oil and equity futures markets a multivariate har approach this paper differs from extant literature because it studies volatility co movements with a multivariate orthogonalized har model a flexible specification for the time series of realized volatility which is able to identify short mid and long term spillover effects we examine volatility transmission mechanisms using high frequency data of the stock index futures on s p 500 nikkei 225 ftse 100 and the futures on the west texas intermediate crude oil during the period from september 2002 to september 2012 considering the full sample the short term volatility of the equity futures contains information about future oil volatility incremental to the information inherent in the time series of oil volatility on the other hand weekly and monthly volatilities do not exhibit a significant spillover effect breaking the whole sample into three subsamples no significant granger causalities are observed in the pre crisis period while in the crisis time and its aftermath we document that the us and uk equity market volatilities to granger cause the oil futures volatility which itself leads the japanese market in terms of magnitude we observe an increase in the short term volatility spillover over time studying the residuals of the har transmission models within a ccc dcc garch framework reveals increasing instantaneous correlation between the energy and equity volatilities in the course of time

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

the rise and demise of the convertible arbitrage strategy this article analyzes convertible arbitrage one of the most successful hedge fund strategies the aim of the strategy is to exploit underpricing of convertible bonds by taking a long position in a convertible and a short position in the underlying asset the authors find that convertible bonds are underpriced at the issuance dates at the same time short sales of underlying equity increase significantly both effects are stronger and more persistent for equity like convertibles than for debtlike convertibles furthermore short sale pressures negatively affect stock returns around the announcement and issuance dates of convertibles all these factors have likely contributed to the shift toward issuing more debtlike convertibles in recent years which in turn has substantially lowered the returns from convertible arbitrage

stochastic dominance and expected utility survey and analysis while stochastic dominance has been employed in various forms as early as 1932 it has only been since 1969 1970 that the notion has been developed and extensively employed in the area of economics finance agriculture statistics marketing and operations research in this survey the first second and third order stochastic dominance rules are discussed with an emphasis on the development in the area since the 1980s

price stabilization in the market for new issues abstract this study examines price stabilization in new equity issues stabilizationtruncates the distribution of post issue prices at a floor price lowering the risk of adverse price moves and hence in a competitive dealer market reducing the bid ask spread using 1 523 nasdao traded firm commitment initial public offerings issued between 1982 and 1987 we find that spreads narrow when the market price is close to the offer price and stabilization is most likely moreover significant negative returns are documented after the hypothesized termination of stabilizing activities suggesting that stabilization and its cessation affect market prices

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

underpricing of newly issued bonds evidence from the swiss capital market the pricing of newly issued bonds on the swiss capital market is investigated over the years 1980 1982 the results reveal a slight underpricing of new bonds at the issue date that is roughly equal to the difference in transactions costs between the markets for new and seasoned bonds underpricing is no longer observed when the new bonds start to be traded on the stock exchange that is after about two days tests of several hypotheses show that unexpected changes in interest rates over the offering period explain part of the underpricing the capital acquisition process of firms has been the subject of intensive research in finance 1 the pricing of newly issued securities is one of the central topics in this area several studies for the bond market find systematic and partly persistent underpricing and therefore higher returns for new bonds relative to seasoned bonds the term seasoning process is generally used to describe this phenomenon 2 typically yields to maturity or holding period returns of either individual new bonds or portfolios of new bonds are compared to portfolios of existing bonds so far only data from the united states have been evaluated this study extends previous research by investigating observations from the swiss capital market due to different institutional characteristics various hypotheses can be tested in a more revealing way in order to allow a reliable identification of the seasoning process individual new and seasoned bonds are selected so that they are identical in as many relevant characteristics as possible holding periods are defined over shorter time spans than commonly used in the literature leading to a more exact estimate of the persistence of systematic differences in returns the paper is organized as follows the methodology underlying the empirical work is developed in section i section ii discusses the institutional setting and the data base the empirical importance of the seasoning process is documented in section iii various explanations and their respective test results are presented in sections iv and v some conclusions complete the paper study center gerzensee foundation of swiss national bank and bank pictet co geneva respectively the comments by j williams as well as by participants at the 13th annual meeting of the european finance association dublin 1986 are gratefully acknowledged the unusually detailed suggestions by two referees resulted in a significant improvement of the paper

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

the pricing of convertible debt offerings abstract we present the first empirical evidence on the pricing of convertible debt offerings using a sample of 91 convertible debt offerings from the period 1988 1992 we show a significant mean initial excess return of 1 11 our underpricing result is invariant to zero nonzero coupons maturity issue size or bond ratings further analysis reveals that various types of risk inherent in the new convertible issues are useful in explaining the cross sectional variation in the initial excess returns we offer an explanation for our results based on the arguments of the differential information model

underwriter price support and the ipo underpricing puzzle abstract this paper reassesses the apparent systematic underpricing of initial public offerings ipos investigation of the distribution of initial returns following ipos shows that positive mean initial returns may reflect the existence of a partially unobserved left negative tail moreover most ipos with zero one day returns subsequently fall in price suggesting that underwriter price support may account for the skewed distribution and hence the phenomenon of positive average initial ipo returns even if offering prices are set at expected market value this paper thus challenges the presumption underlying previous research that positive average initial ipo returns result primarily from deliberate underpricing

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

differential information and security market equilibrium we propose a simple model of equilibrium asset pricing in which there are differences in the amounts of information available for developing inferences about the returns parame ters of alternative securities in contrast with earlier work we show that parameter uncer tainty or estimation risk can have an effect upon market equilibrium under reasonable conditions securities for which there is relatively little information are shown to have relatively higher systematic risk when that risk is properly measured ceteris paribus the initially very limited model is shown to be robust with respect to relaxation of a number of its principal assumptions we provide theoretical support for the empirical examination of at least three proxies for relative information period of listing number of security returns observations available and divergence of analyst opinion

diversification consistent data envelopment analysis with general deviation measures abstract we propose new efficiency tests which are based on traditional dea models and take into account portfolio diversification the goal is to identify the investment opportunities that perform well without specifying our attitude to risk we use general deviation measures as the inputs and return measures as the outputs we discuss the choice of the set of investment opportunities including portfolios with limited number of assets we compare the optimal values efficiency scores of all proposed tests leading to the relations between the sets of efficient opportunities strength of the tests is then discussed we test the efficiency of 25 world financial indices using new dea models with cvar deviation measures

modeling and predicting the cboe market volatility index abstract this paper performs a thorough statistical examination of the time series properties of the daily market volatility index vix from the chicago board options exchange cboe the motivation lies not only on the widespread consensus that the vix is a barometer of the overall market sentiment as to what concerns investors risk appetite but also on the fact that there are many trading strategies that rely on the vix index for hedging and speculative purposes preliminary analysis suggests that the vix index displays long range dependence this is well in line with the strong empirical evidence in the literature supporting long memory in both options implied and realized variances we thus resort to both parametric and semiparametric heterogeneous autoregressive har processes for modeling and forecasting purposes our main findings are as follows first we confirm the evidence in the literature that there is a negative relationship between the vix index and the s p 500 index return as well as a positive contemporaneous link with the volume of the s p 500 index second the term spread has a slightly negative long run impact in the vix index when possible multicollinearity and endogeneity are controlled for finally we cannot reject the linearity of the above relationships neither in sample nor out of sample as for the latter we actually show that it is pretty hard to beat the pure har process because of the very persistent nature of the vix index

dea frontier improvement and portfolio rebalancing an application of china mutual funds on considering sustainability information disclosure abstract data envelopment analysis dea has been a widely used methodology for evaluating the relative performance of portfolios extensive work has appeared for realizing the role of dea in the aspect of assessing portfolio performance and deriving the relative rankings however the role of providing realizable benchmarks is not fully explored in the existing literatures most importantly the dea based portfolio performance evaluation methods developed in the existing literatures can hardly provide support for fund managers in pursuing sustainability performance in this paper we first propose a dea frontier improvement approach under the mean variance framework this approach provides investor with a rebalancing strategy as well as an improved dea frontier which approximates the portfolio efficient frontier better than the traditional dea model does then this approach is extended to a general return risk framework our in sample simulation results verify the effectiveness of the proposed approach for a wide range of applications in addition the out of sample tests show that the rebalancing investment strategies can achieve higher sharpe ratios and sortino ratios than those of the original ones finally we apply the proposed approach to evaluate mutual fund performance in china with the consideration of sustainability information disclosure we construct a disclosure index to indicate the extent of sustainable information disclosure of each mutual fund the results show that the proposed approach provides not only investment recommendations but also references for constructing sustainable green funds

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

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

investment incentives debt and warrants abstract this paper models and characterizes investment incentive problems associated with debt financing the decision problem of residual claimants is explicity formulated and their investment policies are characterized the paper also analyzes the use of conversion features and warrants to control distortionary incentives these claims reverse the convex shape of levered equity over the upper range of the firm s earnings and this mitigates the incentive to take risk it is shown that under certain conditions such claims can be constructed to restore net present value maximizing incentives and simultaneously meet the financing requirements of the firm

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

stochastic dominance and expected utility while stochastic dominance has been employed in various forms as early as 1932 it has only been since 1969 1970 that the notion has been developed and extensively employed in the area of economics

data envelopment analysis models of investment funds abstract this paper develops theory missing in the sizable literature that uses data envelopment analysis to construct return risk ratios for investment funds it explores the production possibility set of the investment funds to identify an appropriate form of returns to scale it discusses what risk and return measures can justifiably be combined and how to deal with negative risks and identifies suitable sets of measures it identifies the problems of failing to deal with diversification and develops an iterative approximation procedure to deal with it it identifies relationships between diversification coherent measures of risk and stochastic dominance it shows how the iterative procedure makes a practical difference using monthly returns of 30 hedge funds over the same time period it discusses possible shortcomings of the procedure and offers directions for future research

portfolio selection in multidimensional general and partial moment space abstract this paper develops a general approach for the single period portfolio optimization problem in a multidimensional general and partial moment space a shortage function is defined that looks for possible increases in odd moments and decreases in even moments a main result is that this shortage function ensures sufficient conditions for global optimality it also forms a natural basis for developing tests on the influence of additional moments furthermore a link is made with an approximation of an arbitrary order of a general indirect utility function this non parametric efficiency measurement framework permits to differentiate mainly between portfolio efficiency and allocative efficiency finally information can in principle be inferred about the revealed risk aversion prudence temperance and other higher order risk characteristics of investors

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

volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory abstract this paper explores the relevance of asymmetry and long memory in modeling and forecasting the conditional volatility and market risk of four widely traded commodities crude oil natural gas gold and silver a broad set of the most popular linear and nonlinear garch type models is used to investigate this relevancy our in sample and out of sample results show that volatility of commodity returns can be better described by nonlinear volatility models accommodating the long memory and asymmetry features in particular the fiaparch model is found to be the best suited for estimating the var forecasts for both short and long trading positions this model also gives for all four commodities the lowest number of violations under the basel ii accord rule given a risk exposure at the 99 confidence level several implications for commodity market risks policy regulations and hedging strategies can be drawn from the obtained results

dynamic spillovers among major energy and cereal commodity prices abstract over the past decade the sharp increases in the prices of oil and agricultural commodities have raised serious concerns about the heightened volatility of these markets and the possible negative interactions between them this article deals with the dynamic return and volatility spillovers across international energy and cereal commodity markets it also examines the impacts of three types of opec news announcements on the volatility spillovers and persistence in these markets for this purpose we make use of the var bekk garch and var dcc garch models for the daily spot prices of eight major commodities including wti oil europe brent oil gasoline heating oil barley corn sorghum and wheat our results provide evidence of significant linkages between these energy and cereal markets moreover the opec news announcements are found to exert influence on the oil markets as well as on the oil cereal relationships finally we show that the persistence of volatility decreases increases for the crude oil and heating oil gasoline returns after accounting for the opec announcements in these multivariate garch models however the results are more mixed for the cereal markets overall our results can be used to improve the risk adjusted performance by having more diversified portfolios and also serve to hedge the oil risk more effectively

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