Practitioners' Corner

The first 150 words of the full text of this article appear below. The analysis of volatility remains a preoccupation. In our veryfirst issue, "Practitioners' Corner" offered a brief retrospectiveon volatility modeling, surveying several strategies in thehistory of volatility modeling and locating the contributionsof the first issue within these broad themes. Of course, notall the highlights of this voluminous literature could be visitedor all noteworthy references cited. Nonetheless, we should havereferred to the venerable literature on mixture models introducedby the polymath Simon Newcomb in the late 19th century and subsequentlystudied by Karl Pearson. A neglected reminder was certainlysupplied by Lanne and Saikkonen (2003), who in this same firstissue of JFEC offered the wry understatement that the conditionalheteroskedasticity inherent in mixture autoregressive modelsmay not adequately capture the time-series properties of financialdata. The point is made again in the contribution to this issueby Markus Haas, Stefan Mittnik, and Marc . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. Spring at last. Here in Montreal, the transition from winteris particularly delicious. There is more light, the world looksless grey, and the trepidation that another storm may be aroundthe corner is put away with the winter tires. In this issueof JFEC, the editors appear to be underscoring seasonal changein an issue whose unifying theme involves parameter and modelstability. Parameter stability is an important issue in econometrics. Achanging economic environment may be captured by allowing theparameters of a reduced form model to vary to reflect changingconditions. The challenge for the econometrician is to constructmodels that do more than reflect changes in an ad hoc manner.For want of more insightful approaches, the challenge is oftensidestepped in practice by focusing on shorter samples whereno structural change can be assumed to have occurred. However,in so constricting the sample size, . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. The transition from some preliminary qualitative assessmentsto quantitative assertions is a hallmark of scientific progress.One dollar today is more valuable than one dollar availabletomorrow, but the scientific issue is by how much and why thisamount? Similarly a random gain with unit expectation and significantrisk is less valuable than one dollar available with certainty.Financial theories of the discount rate and the mean-variancetrade-off have afforded helpful quantitative answers to thesecrucial issues in asset pricing, investment, and risk management.Meanwhile, modern financial econometrics has characterized thedynamic features of interest rates as well as of risk and returnthrough state variables models with volatility clustering, mean-volatilityfeedback, and dynamic correlations. From this perspective, a striking common feature of all thearticles in the current issue of the Journal of Financial Econometricsis the reintroduction of qualitative variables previously treatedusing purely quantitative approaches. The first . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. In our discussion in the last issue of Journal of FinancialEconometrics (JFEC) of the nonparametric methods developed byBarndorff-Nielsen and Shephard (2006) to detect jumps in thelocal behavior of the continuous time path of a price process,we observed these tests were not designed to detect major pricediscontinuity events such as the 1987 crash, since the testingmethodology precludes jumps in adjacent time intervals. Indeed,a major event such as Black Monday is characterized by a sequenceof jumps in consecutive time intervals throughout the day. Inthe interest of thematic continuity, let’s pursue thematter of jumps further. The first article in the current issue by Hossein Asgharianand Chistoffer Bengtsson addresses directly the detection ofbig events in stock prices. More particularly, the authors analyzethe spillover of jumps across international stock markets. Tomeasure jumps, the authors formulate a parametric model in . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. The year 1982 was not a particularly good period for the worldeconomy. At year's end, the Organization for Economic Cooperationand Development (OECD) revised its growth figures for membernations from slightly over 1% to –0.5%, with some 32 millionunemployed in its 24 member states. In the United States thejobless rate was 11% and 30% of plant capacity stood idle. OttoEckstein found the economy in its worst shape in nearly halfa century. Truly the year belonged to Scrooge. Yet 1982 was a very good year indeed for financial econometrics,the debut of an explosion of activity in the area that continuesvigorously 20 years later, as the emergence of the Journal ofFinancial Econometrics attests. In fact, it can convincinglybe argued that 1982 heralded the beginning of our subject, andperhaps with the recent awarding of the Nobel Prize in Economicsto Robert Engle . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. This issue of the Journal of Financial Econometrics containspapers that were presented at the (EC)² conference Econometricsof Financial and Insurance Risks held in Istanbul on December15–17, 2005. Launched in 1990, (EC)² is an annual seriesof international conferences on research in quantitative economicsand econometrics. The acronym stands for European Conferencesof the Econom[etr]ics Community. Its primary aim is to providea vibrant forum where both senior and junior European researchersin quantitative economics and econometrics can discuss the resultsand progress of their research. (EC)² conferences are of relativelysmall scale (less than 200 participants) and quite intensive.Each year a different topic is selected as the major theme ofthe conference. A few leading quantitative economists or econometriciansare invited as keynote speakers, such as Eric Ghysels, who alsoacts as co-Guest editor of this issue; the other speakers areselected . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. During the 1980s, the early stages of modeling financial timeseries focused on the striking stylized fact that while returnswere themselves not serially correlated, squared returns were.This history has been nicely documented in the influential bookby Taylor (1986) and, indeed, the opening chapters of contemporaryfinancial econometrics open with Engle (1982) and Bollerslev(1986) who provided a specific ARMA structure of squared returnsvia the celebrated [G]ARCH models. This general orientationin effect acknowledged that there was some room for predictingrisk, as measured by squared values or absolute values of returns,while at the same time maintaining the hypothesis that returnsthemselves were hardly predictable in keeping with some versionof market efficiency. However, this paradigmatic view has beenchallenged over the subsequent 20 years in at least three regards. First, with Nelson (1991), it has been widely acknowledged thatalthough GARCH modeling is about . . . [Full Text of this Article]     

Practitioners' Corner

The first 150 words of the full text of this article appear below. The article by Christian Gourieroux and Razvan Sufana providesa complete characterization of two-factor affine diffusion termstructure models. The presentation of the article may seem forbiddingto the practitioner audience, so it is perhaps useful that thisinstallment of the column provide some context for the resultsof this article. Prominent among affine diffusion models in the term structureliterature are the Gaussian and square-root diffusion modelsof Vacisek (1977) and Cox, Ingersoll, and Ross (1985). The seminalcontribution of Duffie and Kan (1996) had been to provide anecessary and sufficient condition on the stochastic model toobtain the desirable property of "affine yields," whereby theyield of any zero-coupon bond is seen as a maturity-dependentaffine combination of a selected "basis" set of yields. SubsequentlyDuffie, Pan, and Singleton (2000) proved that the aforementionedcharacterization is even more general, both for the stochasticmodel that may . . . [Full Text of this Article]     

LARCH, Leverage, and Long Memory

We consider the long-memory and leverage properties of a modelfor the conditional variance of an observable stationary sequence X_t, where is the square of an inhomogeneous linear combination of X_s, s < t, withsquare summable weights b_j. This model, which we call linearautoregressive conditionally heteroskedastic (LARCH), specializes,when depends only on X_t–1, to theasymmetric ARCH model of Engle (1990, Review of Financial Studies3, 103–106), and, when depends only on finitely many X_s, to a version of the quadratic ARCH modelof Sentana (1995, Review of Economic Studies 62, 639–661),these authors having discussed leverage potential in such models.The model that we consider was suggested by Robinson (1991,Journal of Econometrics 47, 67–84), for use as a possiblylong-memory conditionally heteroskedastic alternative to i.i.d.behavior, and further studied by Giraitis, Robinson and Surgailis(2000, Annals of Applied Probability 10, 1002–1004), whoshowed that integer powers , =" BORDER="0">2 can have long-memory autocorrelations. We establish conditionsunder which the cross-autocovariance function between volatilityand levels, , decays in the manner of moving average weights of long-memory processes on suitable choiceof the b_j. We also establish the leverage property that h_t <0 for 0 < t k, where the value of k (which may be infinite)again depends on the b_j. Conditions for finiteness of thirdand higher moments of X_t are also established.     

Inequality Constraints in the Fractionally Integrated GARCH Model

In this article we derive necessary and sufficient conditionsfor the nonnegativity of the conditional variance in the fractionallyintegrated generalized autoregressive conditional heteroskedastic(p, d, q) (FIGARCH) model of the order p 2 and sufficient conditionsfor the general model. These conditions can be seen as beinganalogous to those derived by Nelson and Cao (1992, Journalof Business & Economic Statistics 10, 229–235) forthe GARCH(p, q) model. However, the inequality constraints whichwe derive for the FIGARCH model illustrate two remarkable propertiesof the FIGARCH model which are in contrast to the GARCH model:(i) even if all parameters are nonnegative, the conditionalvariance can become negative and (ii) even if all parametersare negative (apart from d), the conditional variance can benonnegative almost surely. In particular, the conditions forthe (1, d, 1) model substantially enlarge the sufficient parameterset provided by Bollerslev and Mikkelsen (1996, Journal of Econometrics73, 151–184). The importance of the result is illustratedin an empirical application of the FIGARCH(1, d, 1) model toJapanese yen versus U.S. dollar exchange rate data.     

Estimating Value at Risk and Expected Shortfall Using Expectiles

Expectile models are derived using asymmetric least squares.A simple formula has been presented that relates the expectileto the expectation of exceedances beyond the expectile. We usethis as the basis for estimating the expected shortfall. Ithas been proposed that the quantile be estimated by the expectilefor which the proportion of observations below the expectileis . In this way, an expectile can be used to estimate valueat risk. Using expectiles has the appeal of avoiding distributionalassumptions. For univariate modeling, we introduce conditionalautoregressive expectiles (CARE). Empirical results for thenew approach are competitive with established benchmarks methods.     

A closed-form GARCH option valuation model

This paper develops a closed-form option valuation formula fora spot asset whose variance follows a GARCH(p, q) process thatcan be correlated with the returns of the spot asset. It providesthe first readily computed option formula for a random volatilitymodel that can be estimated and implemented solely on the basisof observables. The single lag version of this model containsHeston's (1993) stochastic volatility model as a continuous-timelimit. Empirical analysis on S&P500 index options showsthat the out-of-sample valuation errors from the single lagversion of the GARCH model are substantially lower than thead hoc Black-Scholes model of Dumas, Fleming and Whaley (1998)that uses a separate implied volatility for each option to fitto the smirk/smile in implied volatilities. The GARCH modelremains superior even though the parameters of the GARCH modelare held constant and volatility is filtered from the historyof asset prices while the ad hoc Black-Scholes model is updatedevery period. The improvement is largely due to the abilityof the GARCH model to simultaneously capture the correlationof volatility, with spot returns and the path dependence involatility.     

Auctions vs. Bookbuilding and the Control of Underpricing in Hot IPO Markets

Market returns before the offer price is set affect the amountand variability of initial public offering (IPO) underpricing.Thus an important question is "What IPO procedure is best adaptedfor controlling underpricing in "hot" versus "cold" market conditions?"The French stock market offers a unique arena for empiricalresearch on this topic, since three substantially differentissuing mechanisms (auctions, bookbuilding, and fixed price)are used there. Using 1992–1998 data, we find that theauction mechanism is associated with less underpricing and lowervariance of underpricing. We show that the auction procedure'sability to incorporate more information from recent market conditionsinto the IPO price is an important reason.     

Household Portfolio Diversification: A Case for Rank-Dependent Preferences

The proliferation of novel preference theories in financialeconomics is hampered by a lack of non-experimental evidenceand by the theories’ additional complexity which has notbeen shown to be critical in applications. In this article Ipresent arguments in support of preferences with rank dependency.Using the Survey of Consumer Finances data, I document two widespreadpatterns inconsistent with expected utility: (i) many householdssimultaneously invest in well-deversified funds and in poorly-diversifiedportfolios of stocks; and (ii) some households with substantialsavings do not invest anything in equities. I show that portfoliochoice models with rank-dependent preferences, plausibly parameterizedand under fully rational assumptions, are quantitatively consistentwith the observed diversification. These results call for furtherefforts to integrate the models of rank-dependent preferencesin portfolio theory and asset pricing.     

Approximating the Effective Protection Coefficient without Reference to Technological Data

When proposals for reform of tariff or subsidy policies aremade, attempts to predict the effect on incentives are frequentlyhampered by the need for input-output technical data. This articledevelops and illustrates the use of a methodology for approximatingeffective protection coefficients (EPCs) when such data areunavailable or outdated. It derives the equations which approximatethe EPC from statistical analysis of a cross section of existingEPC studies for four agricultural commodities: corn, cotton,rice, and wheat. Informational requirements for computing approximationsinclude the nominal protection coefficients on output and tradableinputs and readily available macroeconomic data. These approximationequations perform well in an out-of-sample test.     

Appraisement of under-average lives in Norway

Abstract

When it was proposed in 1917 to proceed to insurance of »under-average lives» in Norway through the company Norske Folk we had very little statistical data to build upon. There existed no Norwegian or Scandinavian statistics in this field. Some American statistics were, it is true, available, but in many cases these could not be applied direct to Norwegian conditions. However, we could not let ourselves be deterred by this, but proceeded to feel our way forward as well as possible, having constantly ascertained by means of summary annual calculations of mortality that the actual mortality for the aggregate number of insured lay somewhat below the expected figure. The intention was, however, to investigate the mortality in some of the different groups of under-average lives, as soon as the order of magnitude within these groups had become such as to render such investigation possible. The first investigation was made in 1936 for the period from 1917 to the anniversary date in 1935. The results of the mortality inquiry were submitted at the Congress of Actuaries in Paris in 1937. ¹ Olav Aabakken: The Insurance of Under-average Lives in Norway, Statistical Investigations.      

Robust Multidimensional Spatial Poverty Comparisons in Ghana, Madagascar, and Uganda

Spatial poverty comparisons are investigated in three Africancountries using multidimensional indicators of well-being. Thework is analogous to the univariate stochastic dominance literaturein that it seeks poverty orderings that are robust to the choiceof multidimensional poverty lines and indices. In addition,the study seeks to ensure that the comparisons are robust toaggregation procedures for multiple welfare variables. In contrastto earlier work, the methodology applies equally well to whatcan be defined as "union," "intersection," and "intermediate"approaches to dealing with multidimensional indicators of well-being.Furthermore, unlike much of the stochastic dominance literature,this work computes the sampling distributions of the povertyestimators to perform statistical tests of the difference inpoverty measures. The methods are applied to two measures ofwell-being, the log of household expenditures per capita andchildren’s height-for-age z scores, using data from the1988 Ghana Living Standards Study survey, the 1993 NationalHousehold Survey in Madagascar, and the 1999 National HouseholdSurvey in Uganda. Bivariate poverty comparisons are at oddswith univariate comparisons in several interesting ways. Mostimportant, it cannot always be concluded that poverty is lowerin urban areas in one region compared with that in rural areasin another, even though univariate comparisons based on householdexpenditures per capita almost always lead to that conclusion.     

How Firms Should Hedge

Substantial academic research explains why firms should hedge,but little work has addressed how firms should hedge. We assumethat firms can experience costly states of nature and deriveoptimal hedging strategies using vanilla derivatives (e.g.,forwards and options) and custom "exotic" derivative contractsfor a value-maximizing firm facing both hedgable (price) andunhedgable (quantity) risks. Customized exotic derivatives aretypically better than vanilla contracts when correlations betweenprices and quantities are large in magnitude and when quantityrisks are substantially greater than price risks. Finally, wediscuss how our model may be applied in practice.     

Trading volume: definitions, data analysis, and implications of portfolio theory

We examine the implications of portfolio theory for the cross-sectionalbehavior of equity trading volume. Two-fund separation theoremssuggest a natural definition for trading activity: share turnover.If two-fund separation holds, share turnover must be identicalfor all securities. If (K + 1)-fund separation holds, we showthat turnover satisfies an approximately linear K-factor structure.These implications are examined empirically using individualweekly turnover data for NYSE and AMEX securities from 1962to 1996. We find strong evidence against two-fund separation,and a principal-components decomposition suggests that turnoveris well approximated by a two-factor linear model.     

A Theory of IPO Waves

In the IPO market, investors coordinate on acceptable IPO pricebased on the performance of past IPOs, and this generates anincentive for investment banks to produce information aboutIPO firms. In hot periods, the information produced by investmentbanks improves the quality of IPO firms, and this allows exante low quality firms to go public and increases the secondarymarket price, thus synchronizing high IPO volumes and high firstday returns. When investment banks behave asymmetrically ininformation production, the "reputations" of investment banksare interpreted as a form of market segmentation to economizeon the social cost of information production.