the role of transaction costs for financial volatility evidence from the paris bourse this paper analyzes the causal linkage between transaction costs and financial volatility under two methodological improvements over the existing literature first we use panel data in which exogenous transaction cost differences in the french stock market are induced by price level dependent minimum price variation rules tick size rules unlike in previous studies based on one time regulatory tick size changes like the u s decimalization we can separately identify and control for marketwide volatility changes second we avoid the pitfalls of biased volatility measurement across regimes by using the range as a tick size robust volatility metric panel regressions controlling for marketwide volatility effects show at high levels of statistical significance that the hourly range volatility of individual stocks increases by more than 30 for a 20 exogenous increase in transaction costs due to tick size variations in the french trading system in the light of this evidence higher transaction costs in general and security transaction taxes in particular should be considered as volatility increasing jel f3 g1 g14

oil prices brownian motion or mean reversion a study using a one year ahead density forecast criterion abstract for oil related investment appraisal an accurate description of the evolving uncertainty in the oil price is essential for example when using real option theory to value an investment a density function for the future price of oil is central to the option valuation the literature on oil pricing offers two views the arbitrage pricing theory literature for oil suggests geometric brownian motion and mean reversion models empirically driven literature suggests arma garch models in addition to reflecting the volatility of the market the density function of future prices should also incorporate the uncertainty due to price jumps a common occurrence in the oil market in this study the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour both those proposed in the literature and following from data analysis the kullbach leibler information criterion is used to measure the accuracy of density forecasts using two crude oil price series brent and west texas intermediate wti representing the us market we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two gaussians innovation processes with garch and no mean reversion

evaluating the bank of england density forecasts of inflation we consider evaluating the uk monetary policy committee s inflation density forecasts using probability integral transform goodness of fit tests these tests evaluate the whole forecast density we also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated where the ranges are chosen to be those of particular relevance to the mpc given its remit of maintaining inflation rates in a band around per annum finally we discuss the decision based approach to forecast evaluation in relation to the mpc forecasts

using survey data to test standard propositions regarding exchange rate expectations survey data provide a measure of exchange rate expectations superior to the forward rate in that no risk premium interferes we estimate extrapolative adaptive and regressive models of expectations static or random walk expectations and bandwagon expectations are rejected current appreciation generates the expectation of future depreciation because variables other than the contemporaneous spot rate receive weight in comparing expectations to the process governing the spot rate we find statistically significant bias no variable is as ubiquitous in international financial theory and yet as elusive empirically as investors expectations regarding exchange rates in the past expectations have been modeled in an ad hoc way often by using the forward exchange rate there is however a serious problem with using the forward discount as the measure of the expected change in the exchange rate in that the two may not be equal the gap that may separate the forward discount and expected depreciation is generally interpreted as a risk premium most of the large empirical literature testing the unbiasedness of the forward exchange rate for example has found it necessary either arbitrarily to assume away the existence of the risk premium if the aim

rational bias in macroeconomic forecasts do professional forecasters provide their true unbiased estimates or do they behave strategically in our model forecasters have common information confer actively and thus know the true pdf of future outcomes intensive users of economic forecasts monitor forecasters performance closely occasional users are drawn to the forecaster who fared best in the previous period in the resulting nash equilibrium even though economists have identical expectations they make a range of projections that mimics the true probability distribution of the forecast variable those whose wages depend most on publicity produce forecasts that differ most from the consensus empirical evidence supports the model

coca dollars and the dollarization of south america a unique data set on the informal loan market in a coca growing region of bolivia is used to explore the hypothesis that the dollarization of this market is related to the coca industry implications are then drawn for other nations where coca or cocaine is an important industry the authors find that loans are significantly more likely to be denominated in dollars in the season of the major coca harvest than at any other time of the year the effects of the term and size of loans is consistent with the financial needs of the drug industry which is highly dollarized copyright 1991 by ohio state university press

a conditional distribution model for limited stock index returns abstract when a price limit regime exists for all of the stocks involved in an index the index return is an aggregate of limited variables and thereby it is restricted to the same limits we argue that neither a censored nor a truncated distribution model is appropriate for the aggregate return the proposed mixed beta distribution allows for varying conditional mean and volatility and with increasing volatility it changes from leptokurtic to platykurtic densities the model is illustrated and statistically evaluated with an empirical application to the shanghai stock market index returns under a 10 price change limit regime

should speculators be taxed a number of economists have supported the taxation of speculation in financial markets we examine the welfare economics of such a tax in a model of a financial market where some agents have superior information and others have a hedging motive we show that a tax on speculators may actually increase speculative profits this occurs if the speculators benefit from less informative prices offsets the cost of the tax the effect on the welfare of other agents depends on how information revelation changes risk sharing opportunities it is possible for the introduction of a tax to cause a pareto improvement copyright 2000 by university of chicago press

federal reserve information and the behavior of interest rates this paper tests for the existence of asymmetric information between the federal reserve and the public by examining federal reserve and commercial inflation forecasts it demonstrates that the federal reserve has considerable information about inflation beyond what is known to commercial forecasters it also shows that monetary policy actions provide signals of the federal reserve s information and that commercial forecasters modify their forecasts in response to those signals these findings may explain why long term interest rates typically rise in response to shifts to tighter monetary policy jel e52 e43 d82 asymmetric information between the federal reserve and the public is a phenomenon that is often posited but rarely tested numerous models of central bank behavior for example show that the existence of asymmetric information has important implications for the effectiveness of policy and the consequences of dynamic inconsistency yet there

asymmetry loss aversion and forecasting conditional volatility models such as garch have been used extensively in financial applications to capture predictable variation in the second moment of asset returns however with recent theoretical literature emphasising the loss averse nature of agents this paper considers models which capture time variation in the second lower partial moment utility based evaluation is carried out on several approaches to modelling the conditional second order lower partial moment or semi variance including distribution and regime based models the findings show that when agents are loss averse

differential interpretation of public signals and trade in speculative markets most models of trade in speculative markets assume that agents interpret public information identically we provide empirical evidence on the relation between the volume of trade and stock returns around public announcements and we argue that the evidence is inconsistent with this assumption we then develop a model of trade around public announcements that incorporates differential interpretations and is consistent with the observed volume return relation then we test the standard model of belief revision underlying most models of trade using stock brokerage research analysts earnings forecasts the hypthesis of identical interpretations seems inconsistent with the forecast revisions in these data

the role of asymmetries and regime shifts in the term structure of interest rates we examine the relationship between interest rates of different maturities for the us germany and japan over the period 1982 2000 using a general multivariate vector equilibrium correction modelling framework capable of simultaneously allowing for asymmetric adjustment and regime shifts this approach has a very general underlying theoretical rationale that allows for time varying term premia and other short run deviations from the expectations model of the term structure the resulting nonlinear models provide good in sample fits display regime switches closely related to key state variables driving monetary policy decisions and have satisfactory out of sample forecasting properties

trimmed opinion pools and the crowd s calibration problem we introduce an alternative to the popular linear opinion pool for combining individual probability forecasts one of the well known problems with the linear opinion pool is that it can be poorly calibrated it tends toward underconfidence as the crowd s diversity increases i e as the variance in the individuals means increases to address this calibration problem we propose the exterior trimmed opinion pool to form this pool forecasts with low and high means or cumulative distribution function cdf values are trimmed away from a linear opinion pool exterior trimming decreases the pool s variance and improves its calibration a linear opinion pool however will remain overconfident when individuals are overconfident and not very diverse for these situations we suggest trimming away forecasts with moderate means or cdf values this interior trimming increases variance and reduces overconfidence using probability forecast data from u s and european surveys of professional forecasters we present empirical evidence that trimmed opinion pools can outperform the linear opinion pool this paper was accepted by rakesh sarin decision analysis

percentage and relative error measures in forecast evaluation properties of two large families of scale free forecast accuracy measures that include popular measures such as mean absolute percentage error relative error and squared percentage error are examined in this paper we describe the optimal reports when forecasts are evaluated using these measures we also provide analytic expressions for the optimal bayes act associated with these measures under a general power transformation for several well known probability distributions we then show that using measures from these two families may inadvertently provide incentives for either pessimism or optimism among forecasters i e rewarding underforecasts or overforecasts relative to some reference measure of central tendency as an illustration of these concepts we examine the use of these measures for model selection in a forecast aggregation example using stock price forecasts derived from the thomson reuters institutional brokers estimate system this example illustrates how aggregation methods that alw

real time forecasting with a mixed frequency var this article develops a vector autoregression var for time series which are observed at mixed frequencies quarterly and monthly the model is cast in state space form and estimated with bayesian methods under a minnesota style prior we show how to evaluate the marginal data density to implement a data driven hyperparameter selection using a real time dataset we evaluate forecasts from the mixed frequency var and compare them to standard quarterly frequency var and to forecasts from midas regressions we document the extent to which information that becomes available within the quarter improves the forecasts in real time this article has online supplementary materials

multinomial var backtests a simple implicit approach to backtesting expected shortfall under the fundamental review of the trading book frtb capital charges for the trading book are based on the coherent expected shortfall es risk measure which show greater sensitivity to tail risk in this paper it is argued that backtesting of expected shortfall or the trading book model from which it is calculated can be based on a simultaneous multinomial test of value at risk var exceptions at different levels an idea supported by an approximation of es in terms of multiple quantiles of a distribution proposed in emmer et al 2015 by comparing pearson nass and likelihood ratio tests lrts for different numbers of var levels n it is shown in a series of simulation experiments that multinomial tests with n 4 are much more powerful at detecting misspecifications of trading book loss models than standard bi nomial exception tests corresponding to the case n 1 each test has its merits pearson offers simplicity nass is robust in its size properties to the choice of n the lrt is very powerful though slightly over sized in small samples and more computationally burdensome a traffic light system for trading book models based on the multinomial test is proposed and the recommended procedure is applied to a real data example spanning the 2008 financial crisis

forecast accuracy of individual analysts in nine industries the purpose of this paper is to investigate whether financial analysts with superior earnings forecasting ability can be distinguished on the basis of ex post forecast accuracy i explore the question by estimating and comparing average accuracy across individuals and by considering whether the observed distribution of analyst forecast accuracies differs from the distribution expected if their relative performances each year were purely random overall i do not find systematic differences in forecast accuracy across individuals financial press coverage suggests there are superior financial analysts for example institutional investor s annual all american research team includes analysts rated by money managers as superior on a variety of criteria including earnings forecasting ability to pick stocks and the quality of written reports clearly financial analyst services other than forecast accuracy are valued by their clients i focus on only one activity earnings forecasting for two reasons first forecast data are available quantitative and can be evaluated against observable earnings outcomes services such as insightful well written research reports are harder to evaluate quantitatively second academic use of analyst forecasts as earnings expectations data in capital markets empir

nowcasting and the taylor rule actual federal funds rates in the u s have at times deviated from the recommendations of a simple taylor rule this paper proposes a nowcasting taylor rule that preserves the form of the taylor rule but encompasses realistic assumptions on information observable to policymakers because contemporaneous inflation rates and output gaps are not observable at the time policy is set policymakers must form nowcasts the optimal nowcast will depend in part on forecast uncertainty whenever policymakers have asymmetric costs to over and underpredicting inflation and output empirical evidence shows that actual policy rates are consistent with those recommended by a nowcasting taylor rule

model complexity and out of sample performance evidence from s p 500 index returns abstract we apply a range of out of sample specification tests to more than forty competing stochastic volatility models to address how model complexity affects out of sample performance using daily s p 500 index returns model confidence set estimations provide strong evidence that the most important model feature is the non affinity of the variance process despite testing alternative specifications during the turbulent market regime of the global financial crisis of 2008 we find no evidence that either finite or infinite activity jump models or other previously proposed model extensions improve the out of sample performance further applications to value at risk demonstrate the economic significance of our results furthermore the out of sample results suggest that standard jump diffusion models are misspecified

modeling the co movements between crude oil and refined petroleum markets abstract in this paper we investigate two types of asymmetries i e the asymmetry in the lower and upper tail dependences and the asymmetry in the propagation of crisis bubble between crude oil market and refined petroleum markets based on copula models thirteen copula models with different types of dependence structures and time varying dependence parameters are considered we find that in general the malm copula fits our sample data best based on aic criterion we find that lower and upper tail dependences are both positive indicating that crude oil and refined product markets tend to move together using the asymmetric copulas we find asymmetry in tail dependence between crude oil and heating oil returns and that between crude oil and jet fuel returns interestingly upper tail dependence is significantly greater than the lower tail dependence for the pre crisis period while the result is reversed for the post crisis period finally although our data prefers the nonexchangeable malm copula the asymmetry in the propagation of crisis bubble between crude oil and refined product returns is very weak

evaluating interval forecasts a complete theory for evaluating interval forecasts has not been worked out to date most of the literature implicitly assumes homoskedastic errors even when this is clearly violated and proceed by merely testing for correct unconditional coverage consequently i set out to build a consistent framework for conditional interval forecast evaluation which is crucial when higher order moment dynamics are present the new methodology is demonstrated in an application to the exchange rate forecasting procedures advocated in risk management

explanations of the inconsistencies in survey respondents forecasts a comparison of the point forecasts and the probability distributions of inflation and output growth made by individual respondents to the us survey of professional forecasters indicates that the two sets of forecasts are sometimes inconsistent we evaluate a number of possible explanations and find that not all forecasters update their histogram forecasts as new information arrives this is supported by the finding that the point forecasts are more accurate than the histograms in terms of first moment prediction c 2009 elsevier b v all rights reserved

the wisdom of competitive crowds when several individuals are asked to forecast an uncertain quantity they often face implicit or explicit incentives to be the most accurate despite the desire to elicit honest forecasts such competition induces forecasters to report strategically and nontruthfully the question we address is whether the competitive crowd s forecast the average of strategic forecasts is more accurate than the truthful crowd s forecast the average of truthful forecasts from the same forecasters we analyze a forecasting competition in which a prize is awarded to the forecaster whose point forecast is closest to the actual outcome before reporting a forecast we assume each forecaster receives two signals one common and one private these signals represent the forecasters past shared and personal experiences relevant for forecasting the uncertain quantity of interest in a set of equilibrium results we characterize the nature of the strategic forecasts in this game as the correlation among the forecasters priva

biased predictors rationality and the evaluation of forecasts abstract optimal rational forecasts are often biased and thus the empirical finding that actual forecasts are biased is not necessarily evidence of irrational behavior using an asymmetric loss function and a regression forecasting problem these points are explicitly demonstrated

modifying variability and correlations in winner take all contests we consider contests with a fixed proportion of winners based on relative performance special attention is paid to winner take all contests which we define as contests with relatively few winners receiving relatively large awards but we consider the full range of values of the proportion of winners if a contestant has the opportunity to modify the distribution of her performance what strategy is advantageous when the proportion of winners is less than one half a riskier performance distribution is preferred when this proportion is greater than one half it is better to choose a less risky distribution using a multinormal model we consider modifications in the variability of the distribution and in correlations with the performance of other contestants increasing variability and decreasing correlations lead to improved chances of winning when the proportion of winners is less than one half and the opposite directions should be taken for proportions greater than one half thus it is better to take chances and to attempt to distance oneself from the other contestants i e to break away from the herd when there are few winners a more conservative herding strategy makes sense when there are many winners our analytical and numerical results indicate that the probability of winning can change substantially as variability and or correlations are modified furthermore in a game theoretic setting in which all contestants can make modifications choosing a riskier less risky performance distribution when the proportion of winners is low high is the dominant best response strategy we briefly consider some practical issues related to the recommended strategies and some possible extensions

momentum investment strategies portfolio performance and herding a study of mutual fund behavior this study analyzes the extent to which mutual funds purchase stocks based on their past returns as well as their tendency to exhibit herding behavior i e buying and selling the same stocks at the same time the authors find that 77 percent of the mutual funds were momentum investors buying stocks that were past winners however most did not systematically sell past losers on average funds that invested on momentum realized significantly better performance than other funds the authors also find relatively weak evidence that funds tended to buy and sell the same stocks at the same time copyright 1995 by american economic association

forecast encompassing tests and probability forecasts we consider tests of forecast encompassing for probability forecasts for both quadratic and logarithmic scoring rules we propose test statistics for the null of forecast encompassing present the limiting distributions of the test statistics and investigate the impact of estimating the forecasting models parameters on these distributions the small sample performance is investigated in terms of small numbers of forecasts and model estimation sample sizes we show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables and for evaluating survey based probability forecasts copyright c 2010 john wiley sons ltd

bias in federal reserve inflation forecasts is the federal reserve irrational or just cautious abstract inflation forecasts of the federal reserve seem to have systematically under predicted inflation from the fourth quarter of 1968 until volcker s appointment as chairman and to systematically over predict it afterwards until the second quarter of 1998 furthermore under quadratic loss commercial forecasts seem to have information not contained in those forecasts to investigate the cause of this apparent irrationality this paper recovers the loss function implied by federal reserve s inflation forecasts the results suggest that the cost of having inflation above an implicit time varying target was larger than the cost of having inflation below it for the period since volcker and that the opposite was true for the pre volcker era once these asymmetries are taken into account the federal reserve s inflation forecasts are found to be rational

optimal aggregation of money supply forecasts accuracy profitability and market efficiency we present a general procedure for aggregating expert forecasts which exploits regularities in the structure of information within the forecaster population specific information structures lead to aggregation methods which adjust for additive bias differences in individual accuracy and correlation among forecasts as an application we construct composite predictions of the weekly change in the money supply from forecasts made by twenty major securities dealers for which high positive correlation is found to be a significant characteristic due to instability in the information structure our methods cannot improve on the accuracy of a simple average in this case however they do capture information about the correlation among money supply forecasts which is not fully impounded in short term interest rates forecasts from our models accurately predict the direction of price changes for treasury bills and treasury bill futures after a money supply announcement the adjustment of prices to information in financial markets has been studied at length mostly from the perspective of the efficient markets hypothesis market efficiency tests typically look at the behavior of prices the end product

comparing smooth transition and markov switching autoregressive models of us unemployment logistic smooth transition and markov switching autoregressive models of a logistic transform of the monthly us unemployment rate are estimated by markov chain monte carlo methods the markov switching model is identified by constraining the first autoregression coefficient to differ across regimes the transition variable in the lstar model is the lagged seasonal difference of the unemployment rate out of sample forecasts are obtained from bayesian predictive densities although both models provide very similar descriptions bayes factors and predictive efficiency tests both bayesian and classical favor the smooth transition model copyright 2008 john wiley sons ltd

average of forecasts an improvement stein rules are used in forming combination forecasts such forecasts have smaller prediction risk under certain conditions than the preferred method of average of forecasts the new composite forecasts will be theoretically biased but are likely to have smaller mean squared error of forecasts as shown in the empirical exercises examined when the forecasts appear to be unbiased and have a common mean lindley type combination is most useful

disagreement as a measure of uncertainty this paper presents evidence from the livingston survey of inflation forecasts that forecaster disagreement provides a useful measure of forecast uncertainty the evidence is analogous to the evidence for arch effects disagreement at the time of the forecast has as large positive effect on the conditional variance of the subsequent forecast error as a conditioning variable forecaster disagreement dominates arch for both survey errors and the error terms in robert engle s quarterly model of inflation as measured by the resulting conditional variances disagreement indicates larger and more variable levels of uncertainty for the 1946 94 period copyright 1996 by ohio state university press

conditional jump dynamics in stock market returns this article develops a new conditional jump model to study jump dynamics in stock market returns we propose a simple filter to infer ex post the distribution of jumps this permits construction of the shock affecting the time t conditional jump intensity and is the main input into an autoregressive conditional jump intensity model the model allows the conditional jump intensity to be time varying and follows an approximate autoregressive moving average arma form the time series characteristics of 72 years of daily stock returns are analyzed using the jump model coupled with a generalized autoregressive conditional heteroscedasticity garch specification of volatility we find significant time variation in the conditional jump intensity and evidence of time variation in the jump size distribution the conditional jump dynamics contribute to good in sample and out of sample fits to stock market volatility and capture the rally often observed in equity markets following a significant downturn

evaluating density forecasts with applications to financial risk management density forecasting is increasingly more important and commonplace for example in financial risk management yet little attention has been given to the evaluation of density forecasts the authors develop a simple and operational framework for density forecast evaluation they illustrate the framework with a detailed application to density forecasting of asset returns in environments with time varying volatility finally the authors discuss several extensions copyright 1998 by economics department of the university of pennsylvania and the osaka university institute of social and economic research association

differential interpretation of information in inflation forecasts we test the hypothesis associated with a standard assumption in the theoretical literature on learning that economic agents interpret information identically we use a data set based on a survey o

the strategy of professional forecasting we develop and compare two theories of professional forecasters strategic behavior the first theory reputational cheap talk posits that forecasters endeavor to convince the market that they are well informed the market evaluates their forecasting talent on the basis of the forecasts and the realized state if the market expects forecasters to report their posterior expectations honestly then forecasts are shaded toward the prior mean with correct market expectations equilibrium forecasts are imprecise but not shaded the second theory posits that forecasters compete in a forecasting contest with pre specified rules in a winner take all contest equilibrium forecasts are excessively differentiated

macroeconomic expectations of households and professional forecasters economists have long emphasized the importance of expectations in determining macroeconomic outcomes yet there has been almost no recent effort to model actual empirical expectations data instead m acroeconomists usually simply assume that expectations are rational this paper shows that while empirical household expectations are not rational in the usual sense expectational dynamics are well captured by a model in which households views derive from news reports of the views of professional forecasters which in turn may be rational the model s estimates imply that people only occasionally pay attention to news reports this inattention generates stickyness in aggregate expectations with important macroeconomic consequences

taking the pulse of the economy measuring gdp national income and product accounts best known by one of their principle aggregates gross domestic product gdp are produced by virtually every nation in the world simon kuznets and richard stone both later to become nobel prize winners led the creation of the national accounts for the united states and the united kingdom respectively so what exactly does gdp measure how is it constructed why do the gdp and other national accounts estimates sometimes present a different picture of the economy than other economic indicators this article is intended to help answer these questions by providing a broad overview of the measurement techniques used in estimating gdp and the national accounts in the united states in the united states the gdp and the national accounts estimates are fundamentally based on detailed economic census data and other information that is available only once every five years the challenge lies in developing a framework and methods that take these economic census data and combine them using a mosaic of monthly quarterly and annual economic indicators to produce quarterly and annual gdp estimates for example one problem is that the other economic indicators that are used to extrapolate gdp in between the five year economic census data such as retail sales housing starts and manufacturers shipments of capital goods are often collected for purposes other than estimating gdp and

combining var and dsge forecast densities a popular macroeconomic forecasting strategy utilizes many models to hedge against instabilities of unknown timing see among others stock and watson 2004 clark and mccracken 2010 and jore et al 2010 existing studies of this forecasting strategy exclude dynamic stochastic general equilibrium dsge models despite the widespread use of these models by monetary policymakers in this paper we use the linear opinion pool to combine inflation forecast densities from many vector autoregressions vars and a policymaking dsge model the dsge receives a substantial weight in the pool at short horizons provided the var components exclude structural breaks in this case the inflation forecast densities exhibit calibration failure allowing for structural breaks in the vars reduces the weight on the dsge considerably but produces well calibrated forecast densities for inflation

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

price density forecasts in the u s hog markets composite procedures we develop and evaluate quarterly out of sample individual and composite density forecasts for u s hog prices individual density forecasts are generated using time series models and the implied distributions of usda and iowa state university outlook forecasts composite density forecasts are constructed using linear and logarithmic combinations of the individual forecasts and several weighting schemes density forecasts are evaluated on predictive accuracy sharpness goodness of fit calibration and their economic value in a hedging simulation logarithmic combinations using equal and mean square error weights outperform all individual density forecasts and are modestly better than linear composites comparison of the outlook forecasts to the best composite demonstrates the usefulness of the composite procedure and identifies the economic value that more accurate expected price probability distributions can provide to producers

trading volume and asset liquidity since the depth and liquidity of a market depend on the entry decisions of all potential participants each trader assesses them according to conjectures about entry by others if trade is equally costly across markets this externality leads to the concentration of trade on one market if not it can produce multiple conjectural equilibria some where trade concentrates on one market and others where large traders resort to a separate market or to search for a trading partner while fragmentation is welfare reducing in the two market case no such ranking is possible if it involves off exchange search

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

multivariate density forecast evaluation and calibration in financial risk management high frequency returns on foreign exchange we provide a framework for evaluating and improving multivariate density forecasts among other things the multivariate framework lets us evaluate the adequacy of density forecasts involving cross variable interactions such as time varying conditional correlations we also provide conditions under which a technique of density forecast calibration can be used to improve deficient density forecasts and we show how the calibration method can be used to generate good density forecasts from econometric models even when the conditional density is unknown finally motivated by recent advances in financial risk management we provide a detailed application to multivariate high frequency exchange rate density forecasts

are china s new energy stock prices driven by new energy policies abstract this paper studies the impact of china s new energy policies on expected changes and volatility in new energy stock prices considering different kinds of policies energy legislation binding targets for new energies economic incentives and technological research and development and several new energy indexes china s new energy sector and the solar wind nuclear and lithium battery subsectors we used a regression model with a garch specification and dummy variables to differentiate policy pre and post announcement effects on expected returns and volatility our evidence indicates that pre and post announcement energy legislation policies dampened price volatility in all subsector indexes and that economic incentives had a positive policy announcement effect on all subsector index prices other new energy policies had no significant impact on either the mean or the volatility of the new energy assets the potential implications for policy makers and investors are discussed

an empirical test of pricing kernel monotonicity summary a large class of asset pricing models predicts that securities which have high payoffs when market returns are low tend to be more valuable than those with high payoffs when market returns are high more generally we expect the projection of the stochastic discount factor on the market portfolio that is the discounted pricing kernel evaluated at the market portfolio to be a monotonically decreasing function of the market portfolio numerous recent empirical studies appear to contradict this prediction the non monotonicity of empirical pricing kernel estimates has become known as the pricing kernel puzzle in this paper we propose and apply a formal statistical test of pricing kernel monotonicity we apply the test using 17 years of data from the market for european put and call options written on the s p 500 index statistically significant violations of pricing kernel monotonicity occur in a substantial proportion of months suggesting that observed non monotonicities are unlikely to be the product of statistical noise copyright 2014 john wiley sons ltd

is it better to average probabilities or quantiles we consider two ways to aggregate expert opinions using simple averages averaging probabilities and averaging quantiles we examine analytical properties of these forecasts and compare their ability to harness the wisdom of the crowd in terms of location the two average forecasts have the same mean the average quantile forecast is always sharper it has lower variance than the average probability forecast even when the average probability forecast is overconfident the shape of the average quantile forecast still offers the possibility of a better forecast using probability forecasts for gross domestic product growth and inflation from the survey of professional forecasters we present evidence that both when the average probability forecast is overconfident and when it is underconfident it is outperformed by the average quantile forecast our results show that averaging quantiles is a viable alternative and indicate some conditions under which it is likely to be more useful than averaging probabil

dollarization in post hyperinflationary argentina abstract this paper analyzes the continued dollarization of the argentine economy which experienced a rapid decline in inflation following its hyperinflations of the 1980s first a measure of dollar currency circulating in argentina is developed thereby improving upon previous studies of dollarization and currency substitution that focused on dollar deposit holdings only second cointegration analysis of peso money demand in argentina finds a negative ratchet effect from inflation the reduction in peso money demand attributable to the ratchet mirrors the estimated stock of all dollar assets held domestically by argentine residents consistent with the hypothesis of irreversible dollarization

distributions of forecasting errors of forecast combinations implications for inventory management inventory control systems rely on accurate and robust forecasts of future demand to support decisions such as setting of safety stocks the combination of multiple forecasts is shown to be effective not only in reducing forecast errors but also in being less sensitive to limitations of a single model research on forecast combination has primarily focused on improving accuracy largely ignoring the overall shape and distribution of forecast errors nonetheless these are essential for managing the level of aversion to risk and uncertainty for companies this study examines the forecast error distributions of base and combination forecasts and their implications for inventory performance it explores whether forecast combinations transform the forecast error distribution towards desired properties for safety stock calculations typically based on the assumption of normally distributed errors and unbiased forecasts in addition it considers the similarity between in and out of sample characteristics of such errors and the impact of different lead times the effects of established combination methods are explored empirically using a representative set of forecasting methods and a dataset of 229 weekly demand series from a leading household and personal care uk manufacturer findings suggest that forecast combinations make the in and out of sample behaviour more consistent requiring less safety stock on average than base forecasts furthermore we find that using in sample empirical error distributions of combined forecasts approximates well the out of sample ones in contrast to base forecasts

is a group of economists better than one than none can economists forecast the direction of economic growth casual observation indicates that individual economists make poor predictions of economic growth and that their forecasts are highly correlated this article discusses the loss of information resulting from correlation and develops a method of combining forecasts that are cross sectionally correlated this approach greatly increases the accuracy of near term forecasts of the direction of economic growth although the individual with the best historical performance is better over longer horizons overall when the data are properly aggregated economists predict the direction of near term economic growth and call turning points reasonably well copyright 1996 by university of chicago press

testing the rationality of price forecasts new evidence from panel data this paper tests the rationality of individual price forecasts in a panel of professional forecasters here unlike in most previous studies rationality is not rejected the results here differ because 1 using individual forecasts avoids aggregation bias 2 comparison of forecasts to initial data avoids bias due to data revision 3 the professional forecasters have economic incentives to state their expectations accurately and 4 a new covariance matrix estimator consistent when forecast errors are correlated across individuals is used copyright 1990 by american economic association

managing volumetric risk of long term power purchase agreements abstract a negative dependence between wind power production and electricity spot price exists this is an important fact to consider for risk management of long term power purchase agreements ppas in this study we investigate this dependence by constructing a joint model using constant as well as time varying copulas we propose to use score driven models as marginal model for the spot price of electricity as these are more robust to extreme events compared to arma garch models we apply the new model to pricing and risk management of ppas and benchmark it against the arma garch specification our comparison shows that the score driven model results in a statistically significant improvement of predicting the value at risk var which is of high importance for risk management of long term ppas further comparing constant and time varying copulas we find that all time varying copulas are significantly better than their constant counterparts at predicting the var hence time varying copulas should be used in risk management of ppas

comparing the point predictions and subjective probability distributions of professional forecasters we use data from the survey of professional forecasters spf to compare point predictions of gross domestic product gdp growth and inflation with the subjective probability distributions held by forecasters we find that most spf point predictions are quite close to the central tendencies of forecasters subjective distributions tend to be asymmetric with spf forecasters tending to report point predictions that give a more favorable view of the economy than do their subjective means medians modes

forecast uncertainty ex ante and ex post u s inflation and output growth survey respondents who make point predictions and histogram forecasts of macro variables reveal both how uncertain they believe the future to be ex ante as well as their ex post performance macroeconomic forecasters tend to be overconfident at horizons of a year or more but overestimate i e are underconfident regarding the uncertainty surrounding their predictions at short horizons ex ante uncertainty remains at a high level compared to the ex post measure as the forecast horizon shortens there is little evidence of a link between individuals ex post forecast accuracy and their ex ante subjective assessments

transaction costs and asset prices a dynamic equilibrium model in this article we study the effects of transaction costs on asset prices we assume an overlapping generations economy with a riskless liquid bond and many risky stocks carrying proportional transaction costs we obtain stock prices and turnover in closed form surprisingly a stock s price may increase in transaction costs and a more frequently traded stock may be less adversely affected by an increase in transaction costs calculations based on the marginal investor overestimate the effects of transaction costs for realistic parameter values transaction costs have very small effects on stock prices but large effects on turnover

tourism forecasting to combine or not to combine abstract existing non tourism related literature shows that forecast combination can improve forecasting accuracy this study tests this proposition in the tourism context by examining the efficiency of combining forecasts based on three different combination methods the data used for this study relate to tourist arrivals in hong kong from the top ten tourism generating countries regions the forecasts are derived from four different forecasting models autoregressive integrated moving average arima model autoregressive distributed lag model adlm error correction model ecm and vector autoregressive var model all forecasts are ex post and the empirical results show that the relative performance of combination versus single model forecasts varies according to the origin destination tourist flow under consideration which parallels previous findings regarding the relative performance of individual forecasting methods the results also vary with the combination techniques used furthermore although the combined forecasts do not always outperform the best single model forecasts almost all the combined forecasts are not outperformed by the worst single model forecasts this suggests that forecast combination can considerably reduce the risk of forecasting failure this conclusion also implies that combined forecasts are likely to be preferred to single model forecasts in many practical situations

market based measures of monetary policy expectations a number of recent articles have used different financial market instruments to measure near term expectations of the federal funds rate and the high frequency changes in these instruments around federal open market committee announcements to measure monetary policy shocks this article evaluates the empirical success of a variety of financial market instruments in predicting the future path of monetary policy all of the instruments we consider provide forecasts that are clearly superior to those of standard time series models at all of the horizons considered among financial market instruments we find that federal funds futures dominate all the other securities in forecasting monetary policy at horizons out to six months for longer horizons the predictive power of many of the instruments we consider is very similar in addition we present evidence that monetary policy shocks computed using the current month federal funds futures contract are influenced by changes in the timing of policy actions tha

consensus and uncertainty in economic prediction we define consensus as the degree of agreement among point predictions aimed at the same target by different individuals and uncertainty as the diffuseness of the corresponding probability distributions this distinction is made operational with the aid of the nber asa survey data on matched point and probabilistic forecasts of inflation and the rate of change in gross national product the means of the two sets of forecasts agree closely standard deviations of point forecasts tend to understate uncertainty as measured by standard deviations of the predictive probability distributions however these measures of consensus and uncertainty are on the whole positively correlated there is evidence that expectations of higher inflation generate greater uncertainty about inflation tests also favor the hypothesis that a rise in inflation uncertainty has adverse effects on real growth

an empirical investigation of the effects of rounding on the spf probabilities of decline and output growth histograms i consider the possibility that respondents to the survey of professional forecasters round their probability forecasts of the event that real output will decline in the future as well as their reported output growth probability distributions i make various plausible assumptions about respondents rounding practices and show how these impinge upon the apparent mismatch between probability forecasts of a decline in output and the probabilities of this event implied by the annual output growth histograms i find that rounding accounts for about a quarter of the inconsistent pairs of forecasts

combining economic forecasts a method for combining forecasts may or may not account for dependence and differing precision among forecasts in this article we test a variety of such methods in the context of combining forecasts of gnp from four major econometric models the methods include one in which forecasting errors are jointly normally distributed and several variants of this model as well as some simpler procedures and a bayesian approach with a prior distribution based on exchangeability of forecasters the results indicate that a simple average the normal model with an independence assumption and the bayesian model perform better than the other approaches that are studied here

forecasting efficiency concepts and applications this article introduces the concept of forecast efficiency in which the forecast contains all information available at the time of the forecast empirical tests investigate weak efficiency where the information set is all past forecasts and where all forecast revisions and errors should be uncorrelated with past forecast revisions tests of macroeconomic energy consumption and oil price forecasts find a significant autocorrelation of forecast revisions with fifty of fifty one tests showing positive correlation of forecast revisions as opposed to zero correlation consistent with forecast efficiency copyright 1987 by mit press

securities transaction taxes an overview of costs benefits and unresolved questions many major developed countries including germany japan and the united kingdom have some form of tax on securities transactions the clinton administration recently considered imposing fees of from 14 on transactions in futures contracts past budgets have considered fees of from 6 to 15 proponents of a securities transaction tax in the u s argue that it would tap into a significant source of revenues and would in addition act to reduce excess volatility in securities markets by discouraging speculative and noise trading some have argued that it would also increase investors expected holding periods hence encourage corporate managers to build for the long term opponents argue that any benefits from such a tax would be overwhelmed by its costs they point out that a tax on transactions would increase the cost of capital reduce market liquidity and bring down security values furthermore as the tax would change the relative costs of holding and issuing different classes of securities it might be expected to change capital structures and investment portfolios too at its worst a securities transaction tax could drive trading in some securities to overseas markets not burdened by taxation the economic and societal distortions resulting from taxation and avoidance would likely be large

alternatives to coca production in bolivia a computable general equilibrium approach pressured and aided by the united states bolivia has reembarked on a program to eradicate the cultivation of coca used for cocaine production over the next three years the united states plans to inject us soo million into bolivia to wean the country from producing drugs and replace the cultivation of coca with other crops and agricultural activities previous research has shown that coca cultivation and cocaine production benefits the bolivian economy de franc0 and godoy 1992 by raising income creating employment and increasing the availability of credit particularly for smallholders and the informal sector melvin and ladman 1991 given that the macroeconomic impact of a reduction in coca leaf production could devastate the economy the bolivian government has little economic or political incentive to eradicate coca a solution could be to find substitute crops and agricultural activities which would provide comparable levels and distribution of income we use a computable general equilibrium cge model to study the effects of alternatives to coca production the model contains 38 sectors and four social classes the model allows for a detailed assessment of the economic feasibility of switching from coca to other crops in the simulations we reduce coca production and allow each substitute to adjust to restore the real income of smallholders which existed before eradication twenty one crops are then ranked by the feasibility of the needed price and output change the effect on gross domestic product gdp inflation and workers real incomes the results of the simulations suggest that sugar cattle forestry and maize are the strongest candidates for a coca substitution program but there are practical complications in implementing each of the substitutes as will be discussed below indeed the results of this study justify the reluctance on the part of the bolivian authorities to fully cooperate with us efforts to eradicate coca section 2 provides the background to bolivia s coca dependence in section 3 we develop the model and in section 4 we present the equations and an explicit closure statement for the model the results of the simulations are discussed in section 5 the conclusion section 6 contains a discussion of the problems likely to surface in implementing alternatives to coca cultivation

financial transaction taxes market composition and liquidity we use the introduction of a financial transaction tax ftt in france in 2012 to test competing theories on its impact we find no support for the idea that an ftt improves market quality by affecting the composition of trading volume instead our results are in line with the hypothesis that a lower trading volume reduces liquidity and in turn market quality consistent with theories of asset pricing under transaction costs we document a shift in security holdings from short term to long term investors finally we find that moderate aggregate effects on market quality can mask large adjustments made by individual agents

unanimity and compromise among probability forecasters when two forecasters agree regarding the probability of an uncertain event should a decision maker adopt that probability as his or her own a decision maker who does so is said to act in accord with the unanimity principle we examine a variety of bayesian consensus models with respect to their conformance or lack thereof to the unanimity principle and a more general compromise principle in an analysis of a large set of probability forecast data from meteorology we show how well the various models when fit to the data reflect the empirical pattern of conformance to these principles

business cycles indicators and forecasting acknowledgments introduction james h stock and mark w watson 1 twenty two years of the nber asa quarterly economic outlook surveys aspects and comparisons of forecasting performance victor zarnowitz and phillip braun comment allen sinai 2 a procedure for predicting recessions with leading indicators econometric issues and recent experience james h stock and mark w watson comment kenneth f wallis 3 estimating event probabilities from macroeconometric models using stochastic simulation ray c fair comment james d hamilton 4 a nine variable probabilistic macroeconomic forecasting model christopher a sims comment pierre perron 5 why does the paper bill spread predict real economic activity benjamin m friedman and kenneth n kuttner comment ben s bernanke 6 further evidence on business cycle duration dependence francis x diebold glenn d rudebusch and daniel e sichel comment bruce e hansen 7 dynamic index models for large cross sections danny quah and thomas j sargent comment john geweke 8 modelling non linearity over the business cycle clive w j granger timo terdsvirta and heather anderson comment andrew harvey contributors author index subject index

averages of forecasts some empirical results an alternative to using a single forecasting method is to average the forecasts obtained from several methods in this paper we investigate empirically the impact of the number and choice of forecasting methods on the accuracy of simple averages it is concluded that the forecasting accuracy improves and that the variability of accuracy among different combinations decreases as the number of methods in the average increases thus combining forecasts seems to be a reasonable practical alternative when as is often the case a true model of the data generating process or a single best forecasting method cannot be or is not for whatever reasons identified

why are professional forecasters biased agency versus behavioral explanations professional forecasters may not simply aim to minimize expected squared forecast errors in models with repeated forecasts the pattern of forecasts reveals valuable information about the forecasters even before the outcome is realized rational forecasters will compromise between minimizing errors and mimicking prediction patterns typical of able forecasters simple models based on this argument imply that forecasts are biased in the direction of forecasts typical of able forecasters our models of strategic bias are rejected empirically as forecasts are biased in directions typical of forecasters with large mean squared forecast errors this observation is consistent with behavioral explanations of forecast bias

transaction taxes and the behavior of the swedish stock market abstract this paper studies the effects of transaction taxes on the behavior of swedish equity returns during the 1980 1987 period sweden provides an excellent laboratory style setting for such a study as taxes were imposed for political purposes rather than to alter the behavior of the stock market volatility did not decline in response to the introduction of taxes although stock price levels and turnover did large proportions of trading activity migrated overseas to london when the tax rate was increased to 2 in 1986

biases in macroeconomic forecasts irrationality or asymmetric loss empirical studies using survey data on expectations have frequently observed that forecasts are biased and have concluded that agents are not rational we establish that existing rationality tests are not robust to even small deviations from symmetric loss and hence have little ability to tell whether the forecaster is irrational or the loss function is asymmetric we quantify the exact trade off between forecast inefficiency and asymmetric loss leading to identical outcomes of standard rationality tests and explore new and more general methods for testing forecast rationality jointly with flexible families of loss functions that embed quadratic loss as a special case an empirical application to survey data on forecasts of nominal output growth demonstrates the empirical significance of our results and finds that rejections of rationality may largely have been driven by the assumption of symmetric loss

rationality and the role of judgement in macroeconomic forecasting this paper examines the effects of judgemental adjustments on the rationality of macroeconomic forecasts published forecasts based on large scale models are rarely purely model based but often include extensive adjustments forecasters adjustments tend to improve forecast accuracy but there is no evidence of their impact on the rationality of forecasts using series of revisions to forecasts we find little evidence that published forecasts are excessively smooth in the nordhaus i 987 sense but intercept corrections do appear to reduce the variation over time in purely modelbased forecasts and to alter the underlying output inflation trade off implicit in the model there is a large literature on the rationality of forecasts and on the efficient use of information in forecasting equally it is now generally recognised that published forecasts are rarely based on the estimated model alone but that adjustments are often made to the model based predictions in arriving at a final forecast thus published forecasts reflect in varying degree the properties of the model and the skills of the model s proprietors while forecasters adjustments do appear to improve forecast accuracy see the work of the esrc

optimal binary prediction for group decision making we address the problem of optimally forecasting a binary variable for a heterogeneous group of decision makers facing various binary decision problems that are tied together only by the unknown outcome a typical example is a weather forecaster who needs to estimate the probability of rain tomorrow and then report it to the public given a conditional probability model for the outcome of interest e g logit or probit we introduce the idea of maximum welfare estimation and derive conditions under which traditional estimators such as maximum likelihood or nonlinear least squares are asymptotically socially optimal even when the underlying model is misspecified

forecasting the distribution of economic variables in a data rich environment this article investigates the relevance of considering a large number of macroeconomic indicators to forecast the complete distribution of a variable the baseline time series model is a semiparametric specification based on the quantile autoregressive qar model that assumes that the quantiles depend on the lagged values of the variable we then augment the time series model with macroeconomic information from a large dataset by including principal components or a subset of variables selected by lasso we forecast the distribution of the h month growth rate for four economic variables from 1975 to 2011 and evaluate the forecast accuracy relative to a stochastic volatility model using the quantile score the results for the output and employment measures indicate that the multivariate models outperform the time series forecasts in particular at long horizons and in tails of the distribution while for the inflation variables the improved performance occurs mostly at the 6 month horizon we also illustra

the value of combining forecasts in inventory management a case study in banking managing inventories in the face of uncertain stochastic demand requires an investment in safety stocks these are related to the accuracy in forecasting future demands and the noise in the demand generation process reducing the demand forecasting error can free up capital and space and reduce the operating costs of managing the inventories a leading bank in hong kong consumes more than three hundred kinds of printed forms for its daily operations a major problem of its inventory control system for the forms management is to forecast the monthly demand of these forms in this study the idea of combining forecasts is introduced and its practical application is addressed the individual forecasts come from well established time series models and the weights for combination are estimated with quadratic programming the combined forecast is found to perform better than any of the individual forecasts

can rational stubbornness explain forecast biases this paper examines whether the rational jumpiness stubbornness hypothesis can explain forecast biases using a dataset of professional gdp forecasts for the g7 countries over the period 1989 2010 we find evidence supporting the rational stubbornness hypothesis specifically forecasters underreact more when large forecast revisions are highly indicative of low forecast ability underreaction is less likely when the size of forecast revisions is unrelated to ability these findings are consistent with the hypothesis that forecasters choose to smooth gdp forecasts to maximize their perceived ability

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

estimation and testing of forecast rationality under flexible loss in situations where a sequence of forecasts is observed a common strategy is to examine rationality conditional on a given loss function we examine this from a different perspective supposing that we have a family of loss functions indexed by unknown shape parameters then given the forecasts can we back out the loss function parameters consistent with the forecasts being rational even when we do not observe the underlying forecasting model we establish identification of the parameters of a general class of loss functions that nest popular loss functions as special cases and provide estimation methods and asymptotic distributional results for these parameters this allows us to construct new tests of forecast rationality that allow for asymmetric loss the methods are applied in an empirical analysis of imf and oecd forecasts of budget deficits for the g7 countries we find that allowing for asymmetric loss can significantly change the outcome of empirical tests of forecast rationality