day of the week effects and asset returns the number of empirical studies using daily stock returns is rapidly increasing researchers generally assume that the distribution of stock returns is identical for all days of the week a convenient statistical assumption but not a necessary condition of market equilibrium nevertheless there are reasons to suspect that the distribution of returns may vary according to the day of the week the most obvious is the impact of weekends on monday s return since monday s return is calculated over three instead of one calender day the mean and variance may well be higher on monday compared with any other daily return perhaps three times as large previous research has examined the daily distribution of stock returns for a monday effect while fama 1965 does not compare daily mean returns he does report that monday s variance is about 20o greater than other daily returns with a traditional distributional assumption regarding the returns on a financial asset specifies that the expected returns are identical for all days of the week contrary to this plausible assumption this paper discovers that the expected returns on common stocks and treasury bills are not constant across days of the week the most notable evidence is for monday s returns where the mean is unusually low or even negative several explanations of the results are investigated but none proves satisfactory aside from documenting significant day of the week effects the implications of the results for tests of market efficiency are examined while market adjusted returns continue to exhibit day of the week effects these effects are no longer concentrated on monday during the last year we have had many conversations with our colleagues throughout the professions we are particularly thankful to the participants at sessions of the western and american finance associations where preliminary versions of this paper were presented special thanks are due to gene fama gailen hite jon ingersoll robert jarrow merton miller clifford smith and rex thompson the expert research assistance of frank rabinovitch and youngsup yun is gratefully acknowledged 1 the list of papers using daily stock returns is too long to name recent examples include charest 1978 dodd 1980 banz 1981 and reinganum 1981

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

charitable giving by married couples who decides and why does it matter we examine how charitable giving is influenced by who in the household is primarily responsible for giving decisions looking first at single person households we find men and women to have significantly different tastes for giving setting up a potential conflict for married couples we find that with respect to total giving married households tend to resolve these conflicts largely in favor of the husband s preferences bargaining over charitable giving rather than letting one spouse take charge reduces giving by about six percent when the woman is the decision maker she will still make a significantly different allocation of those charity dollars preferring to give to more charities but to give less to each our results give new insights into both the demographics of charitable giving and the costliness of household bargaining

forecasting the term structure of volatility of crude oil price changes this is a pioneering effort to test the comparative performance of two competing models for out of sample forecasting the term structure of volatility of crude oil price changes employing both symmetric and asymmetric evaluation criteria under symmetric error statistics our empirical model using the estimated growth factor of volatility through time is overall superior and it beats in most cases the benchmark model of the square root of time t for holding periods between one and 250 days under asymmetric error statistics if over prediction under prediction of volatility is undesirable the empirical benchmark model is consistently superior relative performance of the empirical model is much higher for holding periods up to fifty days

optimizing an emission trading scheme for local governments a stackelberg game model and hybrid algorithm this study investigates a policy making problem for a local government to implement an emission trading scheme by considering the interactive production decisions of firms in its administrative region the market based allowance trading price formed freely among the firms in the region is investigated by taking into account regional environmental bearing capacities under the scheme the government sets the emission reduction target of the region and allocates tradable initial allowances to firms and firms plan their production according to their allowances on hand a stackelberg game model is formulated to analyze the decisions of the government and firms aiming to maximize the social welfare of the region and maximize the profit of each firm in view of the non concavity and discreteness of the decision model for the government we propose a hybrid algorithm to solve the game model efficiently this algorithm consists of a polynomial time dynamic programming binary search and genetic algorithm results reveal that i the stackelberg game model greatly supports local governments policy making on the market driven emission allowance trading scheme and that ii the social welfare is a great metric for policy making decisions on environmental regulations the market driven emission trading scheme is an effective mechanism for local governments to induce emission reduction through green technology adoption by firms however governments should set their emission reduction targets appropriately because a tight or easy regulation policy significantly affects the environmental and economic benefits as well as the social welfare

a contribution to event study methodology with an application to the dutch stock market abstract this paper proposes an extended market model for event studies based on daily stock returns for actual data the assumptions of the simple market model are violated the return distribution is not normal and neither the variance of the error term nor the risk parameter beta are constant our model incorporates the generalized autoregressive conditional heteroskedasticity garch model with t distributed errors and a time dependent beta we test for anomalies by adding dummy variables in the regression equation our model is fairly general and could be used in a wide variety of event study situations we illustrate the model by an analysis of the weekend and the option expiration effect we use return data from the dutch stock market the weekend effect on stock returns is significant but no expiration effect could be detected

the day of the week effect the international evidence abstract we re examine the day of the week effect for eleven indexes from nine countries during the 1969 1992 period the standard methodology as well as the moving average methodology are used and we find returns to be lower at the beginning of the week but not necessarily on monday for the full period as in chang et al international evidence on the robustness of the day of the week effect journal of financial and quantitative analysis 28 1993 497 514 the anomaly disappears for the most recent period in the usa however the effect is still strong for european countries hong kong and toronto

forecasting volatility in the indian equity market using return and range based models abstractin this article we assess the time varying volatility of the national stock exchange in the indian equity market using unconditional estimators and asymmetric conditional econometric models the volatility estimate and forecast is computed from the interday return and intraday range based data of the exchange s flagship index cnx nifty for the time period spanning 1 january 2009 through 31 december 2013 these are our findings first we determine that the time varying volatility of the index is asymmetric with qualities of stationarity and leptokurtic distribution second the one step ahead volatility forecast derived from the univariate time series parameters through the gjr garch process indicates that the model evaluation criteria of the autoregressive process tends towards range based models vis a vis a return based model the validity of this methodology is further analysed with the superior predictive ability test the outcome of which supports the use of range based conditional mo

conditional heteroscedasticity in time series of stock returns evidence and forecasts this article presents new evidence about the time series behavior of stock prices daily return series exhibit significant levels of second order dependence and they cannot be modeled as linear white noise processes a reasonable return generating process is empirically shown to be a first order autoregressive process with conditionally heteroskedastic innovations in particular generalized autoregressive conditional heteroskedastic garch 1 1 processes fit to data very satisfactorily various out of sample forecasts of monthly return variances are generated and compared statistically forecasts based on the garch model are found to be superior copyright 1989 by the university of chicago

impact of efficiency investment and competition on low carbon manufacturing abstract low carbon economy has become a top agenda for many countries following the agreement in the paris meeting on climate change in this article we take price and emission sensitive demand into account and incorporate competition between the two rival manufacturers in the demand function this research takes more proactive actions incorporating carbon emissions in the strategic and operational decisions which complements the existing literature on low carbon manufacturing in which the carbon emissions attribute is often used as a constraint or only the single manufacturer s demand is considered based on game theory the pricing and carbon emissions reduction decisions are investigated our study contributes to the existing literature on low carbon manufacturing by specifically examining the impact of production efficiency carbon emissions reduction efficiency and market power structure on achieving low carbon manufacturing through the systematic analysis of optimal pricing and green technology investment decisions to improve the economic and environmental performance under different market power structures our findings provide valuable managerial implications which will help many manufacturing firms to make important strategic and operational decisions regarding low carbon manufacturing

modelling oil price volatility with structural breaks in this paper we provide two main innovations i we analyze oil prices of two prominent markets namely west texas intermediate wti and brent using the two recently developed tests by narayan and popp 2010 and liu and narayan 2010 both of which allow for two structural breaks in the data series and ii the latter method is modified to include both symmetric and asymmetric volatility models we identify two structural breaks that occur in 1990 and 2008 which coincidentally correspond to the iraqi kuwait conflict and the global financial crisis respectively we find evidence of persistence and leverage effects in the oil price volatility while further extensions can be pursued the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling oil price volatility

an evaluation of volatility forecasting techniques the existing literature contains conflicting evidence regarding the relative quality of stock market volatility forecasts evidence can be found supporting the superiority of relatively complex models including arch class models while there is also evidence supporting the superiority of more simple alternatives these inconsistencies are of particular concern because of the use of and reliance on volatility forecasts in key economic decision making and analysis and in asset option pricing this paper employs daily australian data to examine this issue the results suggest that the arch class of models and a simple regression model provide superior forecasts of volatility however the various model rankings are shown to be sensitive to the error statistic used to assess the accuracy of the forecasts nevertheless a clear message is that volatility forecasting is a notoriously difficult task

the effects of race gender and survey methodologies on giving in the us this study examines the effects of race and gender on philanthropy and interaction effects between race or gender and survey methodologies results indicate differences in philanthropic behaviors by gender but not by race we also find significant interaction effects between survey methodologies and race and gender which may have important implications for social science research in which race and or gender explain or predict behaviors d 2004 elsevier b v all rights reserved

design of sustainable supply chains under the emission trading scheme increase in environmental concerns together with legislations are forcing industries to take a fresh look at the impact of their supply chain operations on the environment this paper introduces a mixed integer linear programming based framework for sustainable supply chain design that considers life cycle assessment lca principles in addition to the traditional material balance constraints at each node in the supply chain indeed the framework distinguishes between solid and liquid wastes as well as gaseous emissions due to various production processes and transportation systems the framework is used to evaluate the tradeoffs between economic and environmental objectives under various cost and operating strategies in the aluminum industry the results suggest that current legislation and emission trading schemes ets must be strengthened and harmonized at the global level in order to drive a meaningful environmental strategy moreover the model demonstrates that efficient carbon management strategies will help decision makers to achieve sustainability objectives in a cost effective manner

inventory management under joint product recovery and cap and trade constraints abstract the influence of environmental legislation in inventory control policies is explored previous work on product recovery is extended using the introduction of a cap and trade mechanism in an infinite horizon inventory system in which demand and returns are uncertain demand is met through two different sources namely manufacturing and remanufacturing which differ in cost and greenhouse gas emissions the main contributions of this paper are 1 comparison of system operation in terms of cost and environmental performance under conventional and green inventory policies and 2 managerial insights into the structure of green inventory policies to illustrate the impact of a cap and trade scheme a numerical example is used we solved the problem as a markov decision process and characterized the inventory policies based on the optimal replenishment strategy we also conducted a sensitivity analysis to examine the effect of underlying environmental parameters such as the emission cap and the allowance price in the policy structures the results indicate that decisions are sensitive to carbon prices the inventory policy could play an important role in compliance with environmental legislation although there is threshold carbon price beyond which the company must focus on strategic decisions rather than tactical decisions

the directional volatility connectedness between crude oil and equity markets new evidence from implied volatility indexes in this paper we use a set of newly introduced implied volatility indexes to investigate the directional connectedness between oil and equities in eleven major stock exchanges around the globe from 2008 to 2015 the inference on the oil equity implied volatility relationships depends on diebold and yilmaz 2012 2014 2015 who proposed a set of directional measures that enable the dynamic and directional characterization of the relationships among financial variables we find uniform results across the sample countries indicating that the connectedness between oil and equity is established by the bi directional information spillovers between the two markets however we find that the bulk of association is largely dominated by the transmissions from the oil market to equity markets and not the other way around the pattern of transmissions is varying over the sample period however most of the linkages between oil and equities are established from the mid of 2009 to the mid of 2012 which is a period that witnessed the start of global recovery

global reverse supply chain redesign for household plastic waste under the emission trading scheme with increasing global resource scarcity waste becomes a resource that can be managed globally a reverse supply chain network for waste recycling needs to process all the waste with minimum costs and environmental impact as re processing of waste is one of the major sources of pollution in the recycling processes a mechanism is needed to control and reduce the emission impact in the re processing as a key to facilitate the globalized reverse supply chain and avoid spreading pollutants overseas emission trading schemes ets can function as policy instruments for controlling emissions the ets introduces a trade off between the economic efficiency and the environmental impacts ets has been implemented in europe and is developing rapidly in china too the aim of the research is to re design a reverse supply chain from a global angle based on a case study conducted on household plastic waste distributed from europe to china emission trading restrictions are set on the processing plants in both europe and china we modeled a network optimization problem using integer programing approach allowing the re allocation of intermediate processing plants under emission trading restrictions optimization results show that global relocation of re processors leads to both a reduction of total costs and total transportation emission ets applied to re processors further helps to reduce emissions from both re processing and transportation sectors carbon cap should be carefully set in order to be effective with a given carbon cap the model also shows the effective carbon price range these results give an insight into the feasibility of building a global reverse supply chain for household plastic waste recycling and demonstrate the impact of ets on the network design

a word of caution on calculating market based minimum capital risk requirements this paper demonstrates that the use of garch type models for the calculation of minimum capital risk requirements mcrrs may lead to the production of inaccurate and therefore inefficient capital requirements we show that this inaccuracy stems from the fact that garch models typically overstate the degree of persistence in return volatility a simple modification to the model is found to improve the accuracy of mcrr estimates in both back and out of sample tests given that internal risk management models are currently in widespread usage in some parts of the world most notably the usa and will soon be permitted for ec banks and investment firms we believe that our paper should serve as a valuable caution to risk management practitioners who are using or intend to use this popular class of models

volatility forecasting without data snooping abstract data snooping arises when the properties of a data series influence the researcher s choice of model specification when data has been snooped tests undertaken using the same series are likely to be misleading this study seeks to predict equity market volatility using daily data on u k stock market returns over the period 1955 1989 we find that even apparently innocuous forms of data snooping significantly enhance reported forecast quality and that relatively sophisticated forecasting methods operated without data snooping often perform worse than naive benchmarks for predicting stock market volatility we therefore recommend two alternative models both of which are extremely simple

a further investigation of the weekend effect in stock returns this study uses a longer time period and additional stocks to further investigate the weekend effect we find consistently negative monday returns 1 for the s p composite as early as 1928 2 for exchange traded stocks of firms of all sizes and 3 for actively traded over the counter otc stocks the otc results are based on bid prices and therefore appear to reject specialist related explanations for the 30 individual stocks of the dow jones industrial index the average correlation between friday and monday returns is positive and the highest of all pairs of successive days the latter finding is inconsistent with fairly general measurement error explanations some of the most puzzling empirical findings reported in recent years indicate that the distribution of common stock returns varies by day of the week most notably the average return for monday close friday to close monday is significantly negative cross 3 and french 6 find negative monday returns using the standard and poor s composite index and gibbons and hess 7 find negative monday returns for the 30 individual stocks of the dow jones industrial index 1 this negative monday return or weekend effect has yet to be explained this study undertakes a further investigation of the weekend effect in stock returns we examine additional time periods extending the total period covered to 55 years we examine additional stocks such as those of small low capitalization firms and those traded over the counter in all cases the data exhibit a weekend effect that is at least as strong as that reported in previous studies the study also readdresses potential explanations for the effect such as measurement error but concludes that none of these explanations is satisfactory the first section presents a history of the weekend effect from 1928 through 1982 based on the standard and poor s composite index we essentially double the length of the period beginning in 1953 examined by french 6 the results indicate consistently negative monday returns throughout the 55 year period during much of the 25 year period from 1928 through 1952 the new york stock exchange was open on saturdays so monday s return is then computed from saturday s close to monday s close 2 these returns for one day weekends are consistently negative and not significantly different from the two day weekend

analyzing internal barriers for automotive parts remanufacturers in china using grey dematel approach abstract automotive industries have attracted attention from international sectors recently this attention to the industry results in many innovative technologies being integrated in these manufacturing arenas in developing countries such as the bric brazil russia india and china countries especially china who is a global leader in automotive sales and production researchers see substantial attempts to increase economic and societal values in automotive sectors through the use of many sustainable strategies among these sustainable strategies remanufacturing has witnessed much debate in recent years in china automotive parts remanufacturing is still in a nascent stage but the country is striving hard to implement a strategy in industries to result in cleaner production additionally remanufacturing yields high financial societal and environmental returns and it provides advantages such as reducing costs compared to virgin products an increase in jobs and the conservation of scare resources some earlier studies examined chinese remanufacturing issues but they only focused on modeling concepts without considering significant barriers to bridge this gap this paper analyzes internal barriers met by automotive parts remanufacturers and evaluates causal barriers by a proposed model framework this objective is illustrated by employing the grey decision making trial and evaluation laboratory dematel approach by virtue of these findings remanufacturers can eradicate major internal barriers and can increase the chances of practicing more productive remanufacturing in the chinese automotive environments this study extends the scope of this problem through varied applications of different techniques such as a fuzzy approach matrix laboratory and operations research tools by diversifying and including additional barriers

a conditional extreme value volatility estimator based on high frequency returns abstract this paper introduces a conditional extreme value volatility estimator evt based on high frequency returns the relative performance of the evt is compared with the discrete time garch and implied volatility models for 1 day and 20 day ahead forecasts of realized volatility this is also a first attempt towards detecting any time series variation in extreme value distributions using high frequency intraday data the information content of evt is examined in the context of forecasting sp 2 vix generally yields a less accurate characterization of realized volatility than evt and garch models these results have implications for financial risk management and are thus relevant to both regulators and practitioners

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

comparative forecasting performance of symmetric and asymmetric conditional volatility models of an exchange rate abstract the relative out of sample forecasting quality of symmetric and asymmetric conditional volatility models of an exchange rate differs according to the symmetric and asymmetric evaluation criteria both symmetric and asymmetric forecast competitors of currency volatility are biased and systematically over predict volatility

tactical supply chain planning under a carbon tax policy scheme a case study greenhouse gas emissions are receiving greater scrutiny in many countries due to international forces to reduce anthropogenic global climate change industry and their supply chains represent a major source of these emissions this paper presents a tactical supply chain planning model that integrates economic and carbon emission objectives under a carbon tax policy scheme a modified cross entropy solution method is adopted to solve the proposed nonlinear supply chain planning model numerical experiments are completed utilizing data from an actual organization in australia where a carbon tax is in operation the analyses of the numerical results provide important organizational and policy insights on 1 the financial and emissions reduction impacts of a carbon tax at the tactical planning level 2 the use of cost emission tradeoff analysis for making informed decisions on investments 3 the way to price carbon for maximum environmental returns per dollar increase in supply chain cost

weekly patterns in japanese stock returns this study investigates the day of the week effect in the japanese stock returns low tuesday and high wednesday returns are observed most of the positive returns arise during the nontrading period the monday effect is also observed in the week whose previous week is closed by friday trading low tuesday returns appear to be related to low monday returns in the u s the weekly pattern is more pronounced for the returns of smaller firms a reverse size effect is observed during the trading period

including sustainability criteria into inventory models research on sustainability performance has considerably enriched operations management literature in recent years however work with quantitative models is still scarce this paper contributes by revisiting classical inventory methods taking sustainability concerns into account we believe that reducing all aspects of sustainable development to a single objective is not desirable we thus reformulate the classical economic order quantity model as a multiobjective problem we refer to this model as the sustainable order quantity model then a multi echelon extension of the sustainable order quantity model is studied for both models the set of efficient solutions pareto optimal solutions is analytically characterized these results are used to provide some insights about the effectiveness of different regulatory policies to control carbon emissions we also use an interactive procedure that allows the decision maker to quickly identify the best option among these solutions the proposed interactive procedure is a new combination of multi criteria decision analysis techniques

managing carbon footprints in inventory management abstract there is a broad consensus that mankind must reduce carbon emissions to mitigate global warming it is generally accepted that carbon emission trading is one of the most effective market based mechanisms to curb the amount of carbon emissions this paper investigates how firms manage carbon footprints in inventory management under the carbon emission trading mechanism we derive the optimal order quantity and analytically and numerically examine the impacts of carbon trade carbon price and carbon cap on order decisions carbon emissions and total cost we make interesting observations from the numerical examples and provide managerial insights from the analytical results

the predictive power of the implied volatility of options traded otc and on exchanges abstract this paper investigates the efficiency of stock index options traded over the counter otc and on the exchanges in hong kong and japan our findings suggest that implied volatility is superior to either historical volatility or a garch type volatility forecast in predicting future volatility in both the otc and exchange markets this paper is also one of the first to compare the predictive power of the implied volatility of stock index options traded otc to that of exchange traded stock index options our evidence suggests that the otc market is more efficient than the exchanges in japan but that the opposite is true in hong kong

stock returns and volatility an empirical study of the uk stock market abstract attempts to quantify the relationship between stock returns and volatility have produced conflicting conclusions in recent u s studies our paper examines this issue in the u k context for the first time using daily weekly fortnightly and monthly returns on the financial times all share index from january 1965 to december 1989 volatility estimates are obtained from monthly sample variances and arch models expected returns are shown to have had a positive though not statistically significant relationship with expected volatility the relationship between the unexpected components of the returns and volatility series is less clear we find evidence for a negative relationship but only when volatility expectations are represented by standard deviations

environmentally responsible inventory models non classical models for a non classical era abstract mathematical models of inventory typically include the three inventory associated costs of surplus shortage and ordering these classic inventory models are then analysed so as to choose inventory parameters that usually minimise the total cost of operating the inventory system being investigated unfortunately classic inventory models do not provide a meaningful basis for analysing many real and increasingly important practical inventory problems and situations it is therefore not surprising that over recent years several authors have discussed these issues in broad terms and suggested that a new paradigm needs to be developed this paper develops some specific aspects of this discussion in particular the paper identifies a range of inventory problems that are not covered appropriately by traditional inventory analysis one of these is to design responsible inventory systems i e systems that reflect the needs of the environment the paper then examines the importance of inventory planning to the environment in greater detail for example packaging is important not only because of its costs and the protection that it provides to the inventory items but also because of its eventual effects on the environment in terms of the use of resources and potential landfill for similar reasons waste which can result from poor inventory management is highly important the location of stores is important because location affects transport costs thus the influence of the secondary aspects of most inventory models packaging waste and location are important but even more important are the inter relations with the total system in particular the location of the manufacturing plants and the effect that inventory planning has on the logistics chain potentially have considerable environmental implications inventory is part of a wider system however until the cost charged for an activity reflects the true environmental cost of that activity it is likely that decisions will be made on the basis of erroneous data in that situation we are faced with either determining the environmental cost of specific actions or to use environmental costs that are somewhat contrived in which case it may be more sensible to use very different performance measures and models the paper discusses these ideas and ways in which inventory policies may reassure us with our environmental concerns

still different after all these years solidarity behavior in east and west germany abstract using data from laboratory experiments we find that east germans show consistently less solidarity than west germans there has been no convergence in the 20 years after the reunification while it has recently been estimated that political values converge 20 to 40 years after the reunification alesina and fuchs schundeln 2007 we conclude from our findings that social behavior changes more slowly than political values we hypothesize that this is due to complementarities involved in individual social behavior and the necessity to coordinate on social norms on the society level

industrial production volatility and the supply chain abstract the issue of production volatility is important to firms interested in managing their supply chain this paper empirically estimates the volatility of industrial production using the garch and egarch time series models three questions are addressed can volatility be predicted is the effect of unexpected changes in production on volatility asymmetric and how persistent is volatility following a production disturbance the results indicate that production volatility is time varying and can be predicted in the majority of cases examined and that overestimates of production lead to greater increases in volatility than do underestimates

are levels effects important in out of sample performance of short rate models abstract this paper derives short term interest rate volatility forecasts from various interest rate models while models that specify both garch and levels effects are superior in their forecasts accuracy they systematically under predict interest rate volatility more frequently than simple short rate models

the week end effect in common stock returns the international evidence this paper examines the daily stock market returns for four foreign countries we find a so called week end effect in each country in addition the lowest mean returns for the japanese and australian stock markets occur on tuesday the remainder of the paper answers four questions are seasonal patterns in foreign stock markets independent of those previously reported in the u s do japan and australia exhibit a seasonal one day out of phase due to different time zones do settlement procedures across countries bias week end effects does the seasonal pattern in foreign exchange offset the week end effect in stocks for americans investing overseas some of the most anomalous empirical findings in finance are associated with the sample distributions of daily common stock returns cross 1 french 2 gibbons and hess 3 and keim and stambaugh 4 have documented that the average return on friday is abnormally high and the average return on monday is abnormally low to our knowledge this so called day of the week effect or week end effect has yet to be explained because this anomaly has been reported primarily for u s stock returns it is appropriate to investigate whether similar results occur for other countries positive findings would strongly support the proposition that the weekly seasonal effect is a general world wide phenomenon rather than the result of a special type of institutional arrangement in the u s to shed more light on this proposition our paper examines stock market returns in the u k japan canada and australia since we find a week end effect in each country we can examine a set of interesting questions for example are these seasonals independent of the previously reported seasonal in the u s due to different time zones do far eastern countries exhibit a seasonal one day out of phase do different settlement procedures across countries influence weekend effects does the seasonal in foreign exchange fluctuations see mcfarland pettit and sung 7 and levi 6 offset the week end effect in stock market returns for americans investing overseas

the role of regulatory uncertainty in certificate markets a case study of the swedish norwegian market abstract price volatility in green certificate markets reflects uncertainty over future prices representing a major source of risk for renewable energy generators price risk is considered the principal deficiency of this market based policy since it causes investors to require higher returns moreover investors are exposed to regulatory risk namely the risk that a change in the regulation will materially impact the certificate price regulatory uncertainty is reflected in market volatility exacerbating certificate price risk using an econometric approach we investigate the role of regulatory changes on price volatility in the swedish certificate market the results of our analysis indicate that regulatory changes strongly affect certificate markets resulting in periods of higher volatility moreover we analyze whether certificate price volatility has changed after creating a joint swedish norwegian market results indicate that the ambivalence surrounding the creation of this bigger market led to a period of increased price volatility between 2010 and 2011 overall this article brings a better understanding of the role of regulatory uncertainty on certificate markets and gives evidence for its negative impact in terms of increased price volatility

a twist on the monday effect in stock prices evidence from the u s and foreign stock markets abstract one of the most unusual empirical results in finance is the significantly negative average return on the stock market on mondays the present paper documents a twist on this effect we find that abnormally low returns on monday seem to follow stock market declines in fact the monday effect virtually disappears when the market has previously risen cross keim stambaugh and jaffe westerfield point out that monday s return is positively correlated with the previous friday s return surprisingly our findings hold even after one accounts for this friday monday correlation

forecasting energy market volatility using garch models can multivariate models beat univariate models abstract in this paper we forecast energy market volatility using both univariate and multivariate garch class models first we forecast volatilities of individual assets and find that multivariate models display better performance than univariate models second we forecast crack spread volatility and contrast the performance of multivariate models for two underlyings with the alternative of univariate ones for crack spreads directly our evidence shows that univariate models allowing for asymmetric effects display the greatest accuracy we also discuss the hedging strategy based on multivariate models and its implications for market participants

the impact of carbon pricing on a closed loop supply chain an australian case study concerns about industrial and supply chain implications on our natural environment have existed for decades climate change and greenhouse gas emissions have caused countries to implement various instruments ranging from taxes permits and voluntary incentives to required regulatory policies given this environment we develop a unified optimization model for a closed loop supply chain in which the carbon emission is expressed in terms of dollar carbon cost this study is one of the first to evaluate the forward and reverse supply chain influences on the carbon footprint a comparative analysis is completed with a decomposition of cost and environmental influences across supply chain functions we utilize data from a company located in australia where the government is currently introducing a carbon pricing scheme we find that variations in cost and environmental impacts occur over ranges of carbon pricing characteristics and patterns of the numerical results over these ranges provide insights for corporate key strategies and potential additional government policies these results and implications are analyzed along with limitations and directions for future research

evaluating and improving garch based volatility forecasts with range based estimators this article investigates the feasibility of using range based estimators to evaluate and improve generalized autoregressive conditional heteroscedasticity garch based volatility forecasts due to their computational simplicity and readily availability the empirical results show that daily range based estimators are sound alternatives for true volatility proxies when using superior predictive ability spa test of hansen 2005 to assess garch based volatility forecasts in addition the inclusion of the range based estimator of garman and klass 1980 can significantly improve the forecasting performance of garch t model

forecasting volatility and volume in the tokyo stock market long memory fractality and regime switching abstract we investigate the predictability of both volatility and volume for a large sample of japanese stocks the particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short memory counterparts since long memory models should have a particular advantage over long forecasting horizons we consider predictions of up to 100 days ahead in most respects the long memory models arfima figarch and the recently introduced multifractal model dominate over garch and arma models however while figarch and arfima also have quite a number of cases with dramatic failures of their forecasts the multifractal model does not suffer from this shortcoming and its performance practically always improves upon the naive forecast provided by historical volatility as a somewhat surprising result we also find that for figarch and arfima models pooled estimates i e averages of parameter estimates from a sample of time series give much better results than individually estimated models

persistence in variance structural change and the garch model this article examines the persistence of the variance as measured by the generalized autoregressive conditional heteroskedasticity garch model in stock return data in particular we investigate the extent to which persistence in variance may be overstated because of the existence of and failure to take account of deterministic structural shifts in the model both an analysis of daily stock return data and a monte carlo simulation experiment confirm the hypothesis that garch measures of persistence in variance are sensitive to this type of model misspecification

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

analyzing the impacts of carbon regulatory mechanisms on supplier and mode selection decisions an application to a biofuel supply chain this paper analyzes the impacts of carbon regulatory mechanisms on replenishment decisions in a biofuel supply chain we employ mathematical models for operations which integrate replenishment and supplier transportation mode selection decisions these models explicitly account for carbon emissions that may result from transportation and inventory storage activities this research is motivated by observations indicating that nearly 19 of the energy consumption and 25 of the energy related carbon dioxide emissions worldwide arise from transportation because freight transportation is expected to continue to grow we consider the impacts of different carbon regulatory mechanisms on transportation and inventory replenishment decisions in a biofuel supply chain a set of extensive numerical experiments uses the biofuel supply chain context to analyze the impacts of different regulatory mechanisms including carbon cap carbon tax carbon cap and trade and carbon offset on performance we use existing methodologies to calculate emissions as a function of distance traveled load weight and transportation mode used we also use publicly available data to derive representative biomass transportation costs as a consequence our numerical results are meaningful and give a realistic representation of the relationships between emissions from different transportation modes and the resulting costs the results of our computational experiments indicate that carbon regulatory mechanisms have a non trivial impact on replenishment schedules and as a consequence costs and emissions in the supply chain

stock returns and volatility most asset pricing models postulate a positive relationship between a stock portfolio s expected returns and risk which is often modeled by the variance of the asset price this paper uses garch in mean models to examine the relationship between mean returns on a stock portfolio and its conditional variance or standard deviation after estimating a variety of models from daily and monthly portfolio return data we conclude that any relationship between mean returns and own variance or standard deviation is weak the results suggest that investors consider some other risk measure to be more important than the variance of portfolio returns