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

the effect of life expectancy on fertility saving schooling and economic growth theory and evidence we construct a simple growth model where agents with uncertain survival choose schooling time life cycle consumption and the number of children we show that rising longevity reduces fertility but raises saving schooling time and the growth rate at a diminishing rate cross section analyses using data from 76 countries support these propositions life expectancy has a significant positive effect on the saving rate secondary school enrollment and growth but a significant negative effect on fertility through sensitivity analyses the effect on the saving rate is inconclusive while the effects on the other variables are robust and consistent these estimated effects are decreasing in life expectancy

identifying jumps in financial assets a comparison between nonparametric jump tests we perform a comprehensive monte carlo comparison between nine alternative procedures available in the literature to detect jumps in financial assets using high frequency data we evaluate size and power properties of the procedures under alternative sampling frequencies persistence in volatility jump size and intensity and degree of contamination with microstructure noise the overall best performance is shown by the andersen bollerslev and dobrev 2007 and lee and mykland 2008 intraday procedures abd lm provided the price process is not very volatile we propose two extensions to the existing battery of tests the first regards the finite sample improvements based on simulated critical values for the abd lm procedure the second regards a procedure that combines frequencies and tests able to reduce the number of spurious jumps finally we report an empirical analysis using real high frequency data on five stocks listed in the new york stock exchange

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

do switching costs make markets less competitive abstract the conventional wisdom in economic theory holds that switching costs make markets less competitive this article challenges this claim the authors formulate an empirically realistic model of dynamic price competition that allows for differentiated products and imperfect lock in they calibrate this model with data from frequently purchased packaged goods markets these data are ideal in the sense that they have the necessary variation to identify switching costs separately from consumer heterogeneity equally important consumers exhibit inertia in their brand choices a form of psychological switching cost this makes the results applicable to the broad range of products that are distinctly identified i e branded rather than just to products for which there is a product adoption cost or explicit switching fee in the simulations prices are as much as 18 lower with than without switching costs more important equilibrium prices do not increase even in the presence of switching costs that

international evidence on crude oil price dynamics applications of arima garch models abstract we examine the usefulness of several arima garch models for modeling and forecasting the conditional mean and volatility of weekly crude oil spot prices in eleven international markets over the 1 2 1997 10 3 2009 period in particular we investigate the out of sample forecasting performance of four volatility models garch egarch and aparch and figarch over january 2009 to october 2009 forecasting results are somewhat mixed but in most cases the aparch model outperforms the others also conditional standard deviation captures the volatility in oil returns better than the traditional conditional variance finally shocks to conditional volatility dissipate at an exponential rate which is consistent with the covariance stationary garch models than the slow hyperbolic rate implied by the figarch alternative

asymmetric volatility spillovers between oil and stock markets evidence from china and the united states abstract the relationship between oil and stock markets is a hot topic but little research has focused on the time varying asymmetric volatility spillover in a quantitative manner in this study we use a new spillover directional measure and asymmetric spillover measures to investigate the dynamic asymmetric volatility spillover between oil and stock markets during the period of 2007 to 2016 using the intra day data of wti future prices the sp the results also show strong evidence of asymmetries in volatility shocks between the oil and stock markets due to bad volatility

the rationale of the mean standard deviation analysis skewness preference and the demand for money publisher summary this chapter discusses the rationale of the mean standard deviation analysis skewness preference and the demand for money in january 1969 issue of the review of economic studies karl borch and martin feldstein separately criticized the widely used mean variance analysis of portfolio selection borch contended that any system of upward sloping mean standard deviation e s indifference curves can be shown to be inconsistent with the basic axiom of choice under uncertainty he pointed out that one can always pick any two points on an upward sloping indifference curve to represent two bernoulli distributions with probability 1 p of gaining the same amount x in both the cases and probability p of gaining y1 in the case of one distribution and y2 in the case of the second distribution with y2 y1 if the second distribution represents the point to the northeast of the other point then by the dominance axiom the second distribution must be preferred to the first which contradicts the basic meaning of indifference curves feldstein by using a log utility function and a lognormal distribution for investment outcome showed that e s indifference curves for a risk averter need not be convex downwards though upward sloping they would change from convex to concave once the standard deviation of the outcome exceeds the mean multiplied by on the face of it this seems to suggest that risk aversion might decrease as risk is increased beyond a certain extent

the economic impact of wireless number portability this paper examines the price response of wireless carriers to the introduction of number portability in the u s i find that wireless prices decreased in response to number portability but not uniformly across plans average prices for the plans with the fewest minutes decreased by only 0 19 month 0 97 but average prices for medium and high volume plans decreased by 3 64 month 4 84 and 10 29 month 6 81 respectively the results suggest that higher volume users in the wireless market benefited more from the policy induced reduction in switching costs

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

competition in telecommunications this paper discusses the scope for competition in the telecommunications industry taking into account the features of natural monopoly network externalities and customer inertia recent policy towards competition in the industry in the uk is surveyed with an emphasis on access pricing and interconnection finally recent theoretical developments in the economics of access pricing and interconnection are discussed and shown to lend some support for aspects of current policy in the uk copyright 1997 by oxford university press

multi period competition with switching costs an overlapping generations formulation i examine an infinite period duoply market with positive consumer switching costs and overlapping generations of consumers when consumers have a finite time horizon then unlike beggs and klemperer 1992 the two firms may alternate dominance from one period to the next alternately charging high and low prices this agrees with the intuition that firms with a high locked in market share may set price so as to exploit that market share which causes a subsequent low market share among the new cohort of buyers leading to lower prices etc jel codes l13 d21 d43 d92

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

intraconnectivity and interconnectivity when value creation may reduce profits this paper analyses firms decisions to provide connectivity to their customers we distinguish between intraconnectivity the ability of one firm s customers to connect to each other and interconnectivity the ability of one firm s customers to connect with another firm s customers the profitability implications of allowing connectivity are not a straightforward consequence of the consumer value of connectivity because connectivity affects not only the customer value but also the intensity of competition by creating or changing network externality we find that if sales are driven by brand switching rather than by category expansion a firm may find it optimal not to provide intraconnectivity even if providing it is not costly and may find it optimal to provide interconnectivity even at a cost exceeding the consumer value of connectivity on the other hand if category expansion is possible providing intraconnectivity may be profitable in this case either the equilibrium intraconnectivity provision may be asymmetric or both firms may find it individually optimal to provide intraconnectivity under certain conditions in the latter case the firms choice of intraconnectivity is a prisoner s dilemma game

disease and development the effect of life expectancy on economic growth we exploit the major international health improvements from the 1940s to estimate the effect of life expectancy on economic performance we construct predicted mortality using preintervention mortality rates from various diseases and dates of global interventions predicted mortality has a large impact on changes in life expectancy starting in 1940 but no effect before 1940 using predicted mortality as an instrument we find that a 1 percent increase in life expectancy leads to a 1 7 2 percent increase in population life expectancy has a much smaller effect on total gdp however consequently there is no evidence that the large increase in life expectancy raised income per capita

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

modelling energy spot prices empirical evidence from nymex this paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on nymex we consider two types of models a mean reverting model and a spike model with mean reversion that incorporates two different speeds of mean reversion one for the fast mean reverting behaviour of prices after a jump occurs and another for the slower mean reversion rate of the diffusive part of the model we also extend these models to incorporate time varying volatility in their specification modelled as a garch and an egarch process we compare the relative goodness of fit of the different modelling variations both in sample using monte carlo simulations as well as out of sample in a value at risk var setting our results indicate the presence of a leverage effect for wti heating oil and heating oil wti crack spread whereas for the remaining energy markets we find the presence of an inverse leverage effect also the addition of the egarch specification for the volatility process improves both the in sample fit as well as the out of sample var performance for most energy markets that we examine

fertility intra generational redistribution and social security sustainability incorporating heterogeneity in preference to having children into an overlapping generations model of a small open economy we examine the effects of changes in the size of pay as you go payg social security on fertility choices of individuals and population growth of the economy it is shown that payg social security will raise population growth by increasing the number of individuals who have children and the number of children parents have if the system involves redistribution between retirees with different contributions whereas if it has no redistribution payg social security does not affect the fertility decisions of individuals fecondite redistribution intra generationnelle et durabilite de la securite sociale incorporant l heterogeneite des preferences pour avoir des enfants dans un modele d une petite economie ouverte avec des generations qui se chevauchent on examine les effets de changements dans l importance de la securite sociale par repartition sur les choix de fecondite des individus et sur la croissance de la population dans l economie on montre que cette forme de securite sociale augmente la croissance de la population en accroissant a la fois le nombre de personnes qui ont des enfants et le nombre d enfants que les parents choisissent d avoir si le systeme implique une redistribution entre les gens a la retraite qui ont fait des contributions differentes alors que si le regime n implique aucune redistribution le regime de securite sociale par repartition n affecte pas les decisions de fecondite des individus

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

network competition ii price discrimination our companion article developed a clear conceptual framework of negotiated or regulated interconnection agreements between rival operators and studied competition between interconnected networks under the assumption of nondiscriminatory pricing this article relaxes this assumption and allows networks to charge different prices for calls terminating on the subscriber s network and those terminating on a rivals network this creates a price differential between services that are identical for the consumer and generates network externalities despite network interconnection we show that in both the mature and entry phases of the industry the nature of competition is substantially affected by such price discrimination

entry deterrence in markets with consumer switching costs in many markets consumers have transaction or learning switching costs between functionally undifferentiated brands new entry into such markets may be deterred either by large customer bases and or large switching costs which deny customers to an entrant or by small customer bases and or small switching costs which mean an incumbent will respond aggressively to an entrant an incumbent threatened by entry may therefore price either lower or higher than otherwise a firm with the right to enter early may make less profits over time than an otherwise identical firm that is unable to enter the market until later

a simple approximation for semivariance abstract semivariance can differentiate among skewed return distributions but variance is unable to do so thus semivariance has been used as a risk surrogate in portfolio analysis and capital budgeting problems unfortunately semivariance analysis is relatively unknown and poses difficult analytic and computational problems in this paper an expression is derived which very closely approximates semivariance this expression is simple in form and uses only familiar statistics namely mean variance critical value and cumulative probability below the critical value

option pricing with mean reversion and stochastic volatility many underlying assets of option contracts such as currencies commodities energy temperature and even some stocks exhibit both mean reversion and stochastic volatility this paper investigates the valuation of options when the underlying asset follows a mean reverting lognormal process with stochastic volatility a closed form solution is derived for european options by means of fourier transform the proposed model allows the option pricing formula to capture both the term structure of futures prices and the market implied volatility smile within a unified framework a bivariate trinomial lattice approach is introduced to value path dependent options with the proposed model numerical examples using european options american options and barrier options demonstrate the use of the model and the quality of the numerical scheme

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

two moment decision models and expected utility maximization two moment decision models are consistent with expected utility maximization only if the choice set or the agent s preferences are restricted this paper identifies a restriction which is sufficient to ensure this consistency and confirms that it holds in many economic models the implications for economic analysis are then derived two different approaches to representing an agent s preferences over strategies yielding random payoffs are in wide use under the mean standard deviation ms approach the agent is assumed to rank the alternatives according to the value of some function defined over the first two moments of the random payoff while the expected utility eu criterion assumes that the expected value of some utility function defined over payoffs is used instead the fact that there are these two competing approaches has generated a considerable literature some authors are concerned with the advantages and disadvantages of each while others deal with conditions under which the potentially different approaches would yield the same results or at least approximately so space does not

modeling special day effects for forecasting intraday electricity demand abstract we propose and apply a novel approach for modeling special day effects to predict electricity demand in korea notably we model special day effects on an hourly rather than a daily basis hourly specified predictor variables are implemented in the regression model with a seasonal autoregressive moving average sarma type error structure in order to efficiently reflect the special day effects the interaction terms between the hour of day effects and the hourly based special day effects are also included to capture the unique intraday patterns of special days more accurately the multiplicative sarma mechanism is employed in order to identify the double seasonal cycles namely the intraday effect and the intraweek effect the forecast results of the suggested model are evaluated by comparing them with those of various benchmark models for the following year the empirical results indicate that the suggested model outperforms the benchmark models for both special and non special day predictions

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

predicting volatility in the foreign exchange market measures of volatility implied in option prices are widely believed to be the best available volatility forecasts in this article we examine the information content and predictive power of implied standard deviations isds derived from chicago mercantile exchange options on foreign currency futures the article finds that statistical time series models even when given the advantage of ex post parameter estimates are outperformed by isds isds however also appear to be biased volatility forecasts using simulations to investigate the robustness of these results the article finds that measurement errors and statistical problems can substantially distort inferences even accounting for these however isds appear to be too variable relative to future volatility it is widely believed that the volatility implied in option prices is the market s best estimate of future volatility after all if it were not one could devise a trading strategy that could generate profits by identifying mispriced options the purpose of this article is to investigate the information content and predictive power of volatility implied in options on foreign currencies the paper focuses on options on currency futures traded on the chicago mercantile exchange cme because of the depth and liquidity of cme futures and options traded side by side in the same market implied standard deviations isds allow for clean tests of the predictive power of implied volatilities early studies of the information content of isds have generally found that these contain substantial information for future volatility latane and rendleman 1976 chiras and manaster 1978 and beckers 1981 for example regress future volatility on the weighted implied volatility across a broad sample of chicago board options exchange cboe stocks and find that options contain volatility forecasts that are more accurate than historical measures 1 these studies performed shortly after the 1973 beginning of the cboe option market could only use a relatively short time span and therefore focused on cross sections rather than time series predictions

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

a closed form garch option valuation model this paper develops a closed form option valuation formula for a spot asset whose variance follows a garch p q process that can be correlated with the returns of the spot asset it provides the first readily computed option formula for a random volatility model that can be estimated and implemented solely on the basis of observables the single lag version of this model contains heston s 1993 stochastic volatility model as a continuous time limit empirical analysis on s p500 index options shows that the out of sample valuation errors from the single lag version of the garch model are substantially lower than the ad hoc black scholes model of dumas fleming and whaley 1998 that uses a separate implied volatility for each option to fit to the smirk smile in implied volatilities the garch model remains superior even though the parameters of the garch model are held constant and volatility is filtered from the history of asset prices while the ad hoc black scholes model is updated every period the improvement is largely due to the ability of the garch model to simultaneously capture the correlation of volatility with spot returns and the path dependence in volatility article published by oxford university press on behalf of the society for financial studies in its journal the review of financial studies

higher moment risk premiums for the crude oil market a downside and upside conditional decomposition abstract relying on options written on the uso an exchange traded fund tracking the daily price changes of the wti light sweet crude oil we extract variance and skew risk premiums in a model free way we further decompose these risk premiums into downside and upside conditional components and show that they can be partially explained by uso excess returns and more importantly these decomposed risk premiums enable a much better prediction of uso excess returns than the standard or undecomposed variance and skew risk premiums a comparison with existing results for the equity index option market further confirms the usefulness of the decomposition for the crude oil market

technology adoption in the presence of network externalities we analyze technology adoption in industries where network externalities are significant the pattern of adoption depends on whether technologies are sponsored a sponsor is an entity that has property rights to the technology and hence is willing to make investments to promote it key findings include the following 1 compatibility tends to be undersupplied by the market but excessive standardization can occur 2 in the absence of sponsors the technology superior today has a strategic advantage and is likely to dominate the market 3 when one of two rival technologies is sponsored that technology has a strategic advantage and may be adopted even if it is inferior 4 when two competing technologies both are sponsored the technology that will be superior tomorrow has a strategic advantage

explaining credit default swap spreads by means of realized jumps and volatilities in the energy market abstract this paper studies the relationship between credit default swap cds spreads for the energy sector and oil futures dynamics using data on light sweet crude oil futures from 2004 to 2013 which contains a crisis period we examine the importance of volatility and jumps extracted from the futures in explaining cds spread changes the analysis is performed at an index level and by rating group as well as for the pre crisis crisis and post crisis periods our findings are consistent with merton s theoretical framework at an index level futures jumps are important when explaining cds spread changes with negative jumps having higher impact during the crisis the continuous volatility part is significant and positive indicating that futures volatility conveys relevant information for the cds market as for the analysis per rating group negative jumps have an increasing importance as the credit rating deteriorates and during the crisis period while the results for positive jumps and futures volatility are mixed overall the relation between the cds market and the futures market is stronger during volatile periods and strengthened after the global financial crisis

collusive conduct in duopolies multimarket contact and cross ownership in the mobile telephone industry the deregulation of the telecommunications industry has resulted in a variety of industry structures which have been created in hopes of increasing competition one example is the licensing of cellular telephone services in the united states where the fcc created duopolies in which two firms were granted licenses to compete in strictly defined product and geographic markets taking advantage of the unique regulatory environment we test to what degree duopolistic competition leads to competitive market outcomes we find that cross ownership and multimarket contact are important factors in explaining non competitive prices

forecasting realized volatility a bayesian model averaging approach summary how to measure and model volatility is an important issue in finance recent research uses high frequency intraday data to construct ex post measures of daily volatility this paper uses a bayesian modelaveraging approach to forecast realized volatility candidate models include autoregressive and heterogeneous autoregressive specifications based on the logarithm of realized volatility realized power variation realized bipower variation a jump and an asymmetric term applied to equity and exchange rate volatility over several forecast horizons bayesian model averaging provides very competitive density forecasts and modest improvements in point forecasts compared to benchmark models we discuss the reasons for this including the importance of using realized power variation as a predictor bayesian model averaging provides further improvements to density forecasts when we move away from linear models and average over specifications that allow for garch effects in the innovations to log volatility copyright 2009 john wiley sons ltd

price competition with reduced consumer switching costs the case of wireless number portability in the cellular phone industry wireless number portability wnp is a telecommunication regulatory policy that requires cellular phone service providers to allow customers who switch service subscriptions to retain their original phone numbers the right to retain the number lowers the switching cost for a consumer thus the purpose of the policy is to induce more competition and facilitate the growth of new or small service providers in this paper we show that wnp drives market price downward as expected but with a surprising twistrather than helping the smaller firms grow the policy may accelerate the process of market concentration we find that the main contributing factor to this peculiarity is the discriminatory pricing scheme prevalent in the industrythat is a service provider charges a lower per minute fee for the calls initiated and received within the same network than for the calls connected across two networks under this pricing scheme a consumer who subscribes to a larger network would benefit more than if subscribing to a smaller network despite the relatively higher fixed access fee that the former may charge by lowering the barrier of switching wnp creates a market condition conducive for a larger network to gain market share we support our analysis with the empirical evidence gathered from hong kong where wnp was adopted in march 1999

quantity discounts managerial issues and research opportunities marketing managers frequently administer pricing policies involving substantial quantity discounts however our understanding of the precise role of these discounts and their design is quite limited this paper reviews and integrates the economics and marketing literature and presents a detailed analysis of the policies of four firms in order to i specify the variety of motivations for quantity discounts ii provide guidelines to managers in designing quantity discount schedules and iii set out the most fruitful directions for future research

forecasting the realized volatility of the oil futures market a regime switching approach considering nonlinear and highly persistent dynamics of realized volatility we introduce markov regime switching models to the heterogeneous autoregressive model of the realized volatility har rv models to forecast the realized volatility of the crude oil futures market in sample results demonstrate that the high volatility regime is short lived out of sample results suggest that har rv models with regime switching increase the forecasting ability significantly than those without regime switching moreover these findings are robust for different actual volatility benchmarks forecasting windows and model settings

a markov switching model of the conditional volatility of crude oil futures prices abstract this paper examines the temporal behaviour of volatility of daily returns on crude oil futures using a generalised regime switching model that allows for abrupt changes in mean and variance garch dynamics basis driven time varying transition probabilities and conditional leptokurtosis this flexible model enables us to capture many complex features of conditional volatility within a relatively parsimonious set up we show that regime shifts are clearly present in the data and dominate garch effects within the high volatility state a negative basis is more likely to increase regime persistence than a positive basis a finding which is consistent with previous empirical research on the theory of storage e g fama and french 1988a fama and french 1988b and ng and pirrong 1994 the volatility regimes identified by our model correlate well with major events affecting supply and demand for oil out of sample tests indicate that the regime switching model performs noticeably better than non switching models regardless of evaluation criteria we conclude that regime switching models provide a useful framework for the financial historian interested in studying factors behind the evolution of volatility and to oil futures traders interested short term volatility forecasts

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

news good or bad and its impact on volatility predictions over multiple horizons we examine whether the sign and magnitude of intra daily returns have impact on expected volatility the next day or over longer future horizons we first let the data speak namely with minimal interference we capture the mapping between intra daily returns and future volatility we revisit the concept of news impact curves introduced by engle and ng 1993 overall we find that moderately good intra daily news reduces volatility the next day while both very good news unusual high intra daily positive returns and bad news negative returns increase volatility with the latter having a more severe impact the asymmetries disappear over longer horizons we also introduce a new class of parametric models which feature asymmetries and with close ties to arch type models albeit applicable to a mixture of high and low frequency data models featuring asymmetries dominate especially during the 2007 2008 financial crisis

the samuelson hypothesis in futures markets an analysis using intraday data this paper considers the samuelson hypothesis which argues that the futures price volatility increases as the futures contract approaches its expiration utilizing intraday data from 20 futures markets in six futures exchanges we find strong support for the samuelson hypothesis in agricultural futures however the samuelson hypothesis does not hold for other futures contracts we also provide supporting evidence that the negative covariance hypothesis is the key factor for the empirical support of the samuelson hypothesis in addition our findings remain largely unaltered even after we control for seasonality and liquidity effects

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

welfare effects of entry into markets with switching costs in many markets consumers have costs of switching between products that are functionally identical this note shows that entry of efficient low cost competitors into these markets may be socially detrimental in a linear model entry reduces social welfare as conventionally defined in more than half of the relevant parameter space in a more general model there is always a range of values of switching costs for which entry reduces welfare even if the entrant s production costs are lower than the incumbent s copyright 1988 by blackwell publishing ltd

good volatility bad volatility signed jumps and the persistence of volatility abstract using estimators of the variation of positive and negative returns realized semivariances and high frequency data for the s p 500 index and 105 individual stocks this paper sheds new light on the predictability of equity price volatility we showthat future volatility is more strongly related to the volatility of past negative returns than to that of positive returns and that the impact of a price jump on volatility depends on the sign of the jump with negative positive jumps leading to higher lower future volatility we show that models exploiting these findings lead to significantly better out of sample forecast performance

elderly labor supply and fertility decisions in aging population economies with a longer life expectancy individuals who plan to work when they are old may increase the number of their children therefore when individuals choose the time of retirement the fertility rate may not necessarily decline but even rise

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

correlated arch corrarch modelling the time varying conditional correlation between financial asset returns abstract although the time variation of the conditional correlations of asset returns is a well established stylized fact and of crucial importance for efficient financial decisions there is no explicit general model available for its estimation and forecasting in this paper we propose a bivariate garch covariance structure in which conditional variances can follow any garch type process while conditional correlation is generated by an explicit discrete time stochastic process the corrarch process a high order corrarch can parsimoniously be represented by a corgarch process the model successfully generates the reported stylized facts establishes an autocorrelation structure for correlations and thus provides an explicit framework for out of sample forecasting we provide empirical evidence from the g7 stock market indexes

how do switching costs affect market concentration and prices in network industries i investigate the effects of switching costs on the market outcome in network industries using a dynamic duopoly model of price competition in the presence of an outside option i find that the role of switching costs depends on network effects and the outside option without a viable outside option high switching costs can neutralize the tendency towards high market concentration associated with network effects but with a viable outside option switching costs increase market concentration furthermore switching costs lower prices if network effects are modest and there exists a viable outside option but generally raise prices otherwise

on the volatility volume relationship in energy futures markets using intraday data this paper investigates the relationship between trading volume and price volatility in the crude oil and natural gas futures markets when using high frequency data by regressing various realized volatility measures with without jumps on trading volume and trading frequency our results feature a contemporaneous and largely positive relationship furthermore we test whether the volatility volume relationship is symmetric for energy futures by considering positive and negative realized semivariances we show that i an asymm etric volatility volume relationship indeed exists ii trading volume and trading frequency significantly affect negative and positive realized semivariance and iii the information content of negative realized semivariance is higher than for positive realized semivariance

forecasting the good and bad uncertainties of crude oil prices using a har framework abstract good or bad uncertainty is the volatility that is associated with positive or negative innovations to asset prices this paper proposes new heterogeneous autoregressive type har type models to forecast the good and bad uncertainties of crude oil prices in this paper we investigate the effects of lagged bad and good uncertainties daily positive and negative signed jump variations and leverages on predicting good and bad uncertainties by in sample and out of sample analysis the in sample results show that bad and good uncertainties have long memory property and the predictability of long term good and bad uncertainties is stronger than that of short and mid term good and bad uncertainties the out of sample results indicate that lagged bad or good uncertainties daily positive signed jump variation and daily negative signed jump variation contain incremental out of sample information for forecasting good or bad uncertainties and in most cases lagged leverages also play indispensable roles in forecasting the good and bad uncertainties in the crude oil market moreover the results of out of sample analysis remain robust across using the other estimation window other har type models and the other sample

commodity derivatives pricing with cointegration and stochastic covariances abstract empirically cointegration and stochastic covariances including stochastic volatilities are statistically significant for commodity prices and energy products to capture such market phenomena we develop a continuous time dynamics of cointegrated assets with a stochastic covariance matrix and derive the joint characteristic function of asset returns in closed form the proposed model offers an endogenous explanation for the stochastic mean reverting convenience yield the time series of spot and futures prices of wti crude oil and gasoline shows cointegration relationship under both physical and risk neutral measures the proposed model also allows us to fit the observed term structure of futures prices and calibrate the market implied cointegration relationship we apply it to value options on a single commodity and on multiple commodities

two kinds of consumer switching costs in this article i introduce a distinction between two kinds of consumer switching costs transaction costs and learning costs while transaction costs are incurred by a consumer at every switch between suppliers learning costs are incurred only at a switch to a supplier that is new to him in a multiperiod duopoly model i examine the effects of changing the proportion of each kind of consumer switching costs while holding total switching costs constant i show that an increase in transaction costs relative to learning costs increases the price offered to loyal consumers this then has the further effect of decreasing the introductory price in the market it also leads to a decrease in welfare

endogenous fertility and optimal population size pareto optimality which is the standard criterion of efficiency in general equilibrium models takes population size as given and therefore cannot be directly applied to analyze the question of optimal population size the criterion then for optimal population size must be based on a more restrictive definition of optimality this paper extends peter diamonds 1965 golden golden rule growth model by assuming that individuals derive utility from their own consumptionand from their own children offspring are assumed to consume resources before reaching adulthood the authors show that the optimal steady state utility yields a higher population growth rate when it converges to the golden rule allocation they then demonstrate that a voluntary social security program in which the size of the transfer to a particular agent is directly tied to his own fertility leads the competitive allocation to be identical to the allocation corresponding to the maximum of the steady state utility of the representative individual

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

costly switching from a status quo abstract we axiomatically characterize a theory of status quo dependent choice where an agent faces switching costs that depend upon both the status quo and the alternative he switches to in a choice problem with a status quo the agent chooses the alternatives that yield the highest utility net of switching cost this generates status quo bias and also allows for a wide range of reference effects we examine the behavior of such agents in prisoner s dilemma pd games in a single pd game switching costs can lead to cooperation however across different pd games it is not anything goes and instead we derive necessary and sufficient conditions for cooperation rates to be consistent with our model we then verify that these conditions are satisfied by charness et al s 2016 experimental data we also perform a similar analysis for other theories such as models of status quo bias magical thinking inequity aversion and fairness and find that these theories make either invalidated or looser predictions

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

network competition i overview and nondiscriminatory pricing we develop a model of unregulated competition between interconnected networks and analyze the mature and transition phases of the industry in this deregulated environ ment networks pay negotiated or regulated access charges to each other and com pete in prices for customers we show that a competitive equilibrium may fail to exist for large access charges or for large network substitutability and that freely negotiated access charges may prevent effective competition in the mature phase of the industry and erect barriers to entry in the transition toward competition last we examine the meaning and impact of policies such as the efficient component pricing rule

the access pricing problem a synthesis the baumol willig efficient component pricing rule states that it is efficient to set the price of access to an essential facility equal to the direct cost of access plus the opportunity cost to the integrated access provider the authors analyze the relevant notion of opportunity cost under various assumptions about demand and supply conditions including product differentiation bypass and substitution possibilities which all reduce opportunity cost compared to the benchmark case they show that the ramsey approach to access pricing developed by j j laffont and j tirole 1994 is closely related to the efficient component pricing rule provided opportunity cost is correctly interpreted

a risk return model with risk and return measured as deviations from a target return two attribute risk and return models are very popular in the economics and finance literature for analyzing decisions under uncertainty their popularity stems primarily from the intuitive appeal of the dichotomy into risk and return and from the ease with which the concepts can be diagrammed in two dimensions the most commonly used risk return model is the mean variance model in which risk is measured as the variance and return by the mean of the probability distribution over outcomes the mean variance model has a number of shortcomings which are widely known but of particular concern here are the facts that 1 mean variance dominance is neither necessary nor sufficient for second degree stochastic dominance 2 unless the form of the probability distribution is restricted mean variance is consistent with von neumann morgenstern utility theory only if the utility function is quadratic and 3 as peter fishburn has noted

variance vs downside risk is there really that much difference abstract the popularity of downside risk among investors is growing and mean return downside risk portfolio selection models seem to oppress the familiar mean variance approach the reason for the success of the former models is that they separate return fluctuations into downside risk and upside potential this is especially relevant for asymmetrical return distributions for which mean variance models punish the upside potential in the same fashion as the downside risk the paper focuses on the differences and similarities between using variance or a downside risk measure both from a theoretical and an empirical point of view we first discuss the theoretical properties of different downside risk measures and the corresponding mean downside risk models against common beliefs we show that from the large family of downside risk measures only a few possess better theoretical properties within a return risk framework than the variance on the empirical side we analyze the differences between some us asset allocation portfolios based on variances and downside risk measures among other things we find that the downside risk approach tends to produce on average slightly higher bond allocations than the mean variance approach furthermore we take a closer look at estimation risk viz the effect of sampling error in expected returns and risk measures on portfolio composition on the basis of simulation analyses we find that there are marked differences in the degree of estimation accuracy which calls for further research

how relevant is volatility forecasting for financial risk management it depends if volatility fluctuates in a forecastable way volatility forecasts are useful for risk management hence the interest in volatility forecastability in the risk management literature volatility forecastability however varies with horizon and different horizons are relevant in different applications moreover existing assessments of volatility forecastability are plagued by the fact that they are joint assessments of volatility forecastability and an assumed model and the results can vary not only with the horizon but also with the assumed model to address this problem we develop a model free procedure for assessing volatility forecastability across horizons perhaps surprisingly we find that volatility forecastability decays quickly with horizon volatility forecastability although clearly of relevance for risk management at the short horizons relevant for say trading desk management may be much less important at longer horizons

pricing patterns of cellular phones and phonecalls a segment level analysis one expectation of the u s federal communications commission fcc in the early stages of the cellular communications industry was that the presence of two licensees in each market would ensure competition and thereby result in declining prices over time for both cellular phones handsets and phonecalls however industry observers have noted recently that although the price of handsets has declined over time the price of the phonecalls has not we investigate this interesting pricing issue by modeling the market interaction between the providers of cellular services and also their interaction with customers using a game theoretic framework a critical assumption in the development of our model is that there exist segments of customers with different valuations usage levels and price sensitivities for cellular service empirically we provide support for the existence of two customer segments viz business professional and personal from both secondary data on industry usage and revenue and primary data collected from a conjoint analysis study of cellular service customers from the latter source we also establish that the business professional customers are more sensitive to prices of phonecalls than the personal segment from our analytical model we characterize the conditions under which penetration and skimming pricing strategies for the handsets are profit maximizing from the sellers standpoint and derive the corresponding price of phonecalls one of our main analytical results is that a competitive structure can result in lower prices over time for the handset but higher prices for the phonecalls depending on production costs of the handset we are thus able to provide a theoretical explanation for the observed price patterns for the handset and phonecalls

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

market structure and the competitive effects of switching costs abstract we revisit the effects of switching costs on dynamic competition we consider stationary markovian strategies with market shares being the state variable and characterize a relatively simple markov perfect pricing equilibrium at which there is switching by some consumers at all times for the case of low switching costs and infinitely lived consumers we show that switching costs are pro competitive in the long run steady state while the overall effect in the short run transient state depends on market structure in particular switching costs are anti competitive in relatively concentrated markets and pro competitive otherwise

market concentration and competition in oecd mobile telecommunications markets this study analyses the progress of market concentration in oecd member states mobile telecommunications markets and evaluates the relationship between market concentration and performance using annual panel data from 24 oecd member states for the 1998 2011 period the study estimates regression equations for market concentration mobile prices and profits the empirical results indicate that the more concentrated the mobile market the higher the prices and profits providing support for the market power hypothesis if this hypothesis holds then market concentration can be a useful indicator of market performance on the other hand the applicability of the hypothesis is unclear for the second half of the sample period the results provide evidence that regulatory policies influence the structure and performance of mobile markets

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