93 resultados para conditional beta pricing

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Among the underlying assumptions of the Black-Scholes option pricingmodel, those of a fixed volatility of the underlying asset and of aconstantshort-term riskless interest rate, cause the largest empirical biases. Onlyrecently has attention been paid to the simultaneous effects of thestochasticnature of both variables on the pricing of options. This paper has tried toestimate the effects of a stochastic volatility and a stochastic interestrate inthe Spanish option market. A discrete approach was used. Symmetricand asymmetricGARCH models were tried. The presence of in-the-mean and seasonalityeffectswas allowed. The stochastic processes of the MIBOR90, a Spanishshort-terminterest rate, from March 19, 1990 to May 31, 1994 and of the volatilityofthe returns of the most important Spanish stock index (IBEX-35) fromOctober1, 1987 to January 20, 1994, were estimated. These estimators wereused onpricing Call options on the stock index, from November 30, 1993 to May30, 1994.Hull-White and Amin-Ng pricing formulas were used. These prices werecomparedwith actual prices and with those derived from the Black-Scholesformula,trying to detect the biases reported previously in the literature. Whereasthe conditional variance of the MIBOR90 interest rate seemed to be freeofARCH effects, an asymmetric GARCH with in-the-mean and seasonalityeffectsand some evidence of persistence in variance (IEGARCH(1,2)-M-S) wasfoundto be the model that best represent the behavior of the stochasticvolatilityof the IBEX-35 stock returns. All the biases reported previously in theliterature were found. All the formulas overpriced the options inNear-the-Moneycase and underpriced the options otherwise. Furthermore, in most optiontrading, Black-Scholes overpriced the options and, because of thetime-to-maturityeffect, implied volatility computed from the Black-Scholes formula,underestimatedthe actual volatility.

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We derive an international asset pricing model that assumes local investorshave preferences of the type "keeping up with the Joneses." In aninternational setting investors compare their current wealth with that oftheir peers who live in the same country. In the process of inferring thecountry's average wealth, investors incorporate information from the domesticmarket portfolio. In equilibrium, this gives rise to a multifactor CAPMwhere, together with the world market price of risk, there existscountry-speciffic prices of risk associated with deviations from thecountry's average wealth level. The model performs signifficantly better, interms of explaining cross-section of returns, than the international CAPM.Moreover, the results are robust, both for conditional and unconditionaltests, to the inclusion of currency risk, macroeconomic sources of risk andthe Fama and French HML factor.

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In this paper we consider the equilibrium effects of an institutionalinvestor whose performance is benchmarked to an index. In a partialequilibrium setting, the objective of the institutional investor is modeledas the maximization of expected utility (an increasing and concave function,in order to accommodate risk aversion) of final wealth minus a benchmark.In equilibrium this optimal strategy gives rise to the two-beta CAPM inBrennan (1993): together with the market beta a new risk-factor (that wecall active management risk) is brought into the analysis. This new betais deffined as the normalized (to the benchmark's variance) covariancebetween the asset excess return and the excess return of the market overthe benchmark index. Different to Brennan, the empirical test supports themodel's predictions. The cross-section return on the active management riskis positive and signifficant especially after 1990, when institutionalinvestors have become the representative agent of the market.

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A number of existing studies have concluded that risk sharing allocations supported by competitive, incomplete markets equilibria are quantitatively close to first-best. Equilibrium asset prices in these models have been difficult to distinguish from those associated with a complete markets model, the counterfactual features of which have been widely documented. This paper asks if life cycle considerations, in conjunction with persistent idiosyncratic shocks which become more volatile during aggregate downturns, can reconcile the quantitative properties of the competitive asset pricing framework with those of observed asset returns. We begin by arguing that data from the Panel Study on Income Dynamics support the plausibility of such a shock process. Our estimates suggest a high degree of persistence as well as a substantial increase in idiosyncratic conditional volatility coincident with periods of low growth in U.S. GNP. When these factors are incorporated in a stationary overlapping generations framework, the implications for the returns on risky assets are substantial. Plausible parameterizations of our economy are able to generate Sharpe ratios which match those observed in U.S. data. Our economy cannot, however, account for the level of variability of stock returns, owing in large part to the specification of its production technology.

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Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

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Estudi elaborat a partir d’una estada al Royal Brompton Hospital, Londres, Regne Unit, durant octubre i novembre del 2006.Els beneficis de la estimulació beta-adrenèrgica en pacients amb lesió pulmonar aguda (LPA) són coneguts, però no es disposa de dades sobre el possible efecte antiinflamatori. El condensat d'aire exhalat (CAE) és una tècnica no-invasiva de recollida de mostres del tracte respiratori inferior, podent ser útil en la monitorització de patologies respiratòries. S’ha usat marcadors biològics en el CAE de pacients ventilats mecànicament amb LPA per estudiar el possible efecte antiinflamatori que el salbutamol hi podria exercir. El CAE va ser recollit abans i després de l'administració de salbutamol inahalat. Inmediatament després es va mesurar la conductivitat i el pH abans i després de la desgasificació amb heli. Es va mesurar la concentració de nitrits i nitrats. Les mostres varen ser liofilitzades i guardades a -80ºC. La concentració de leucotriè B4 es va mesurar després de la reconstitució de la mostra. Els resultats s'expressen com a mitjana (error estàndard de la mostra). No s'han detectat diferències entre els valors de CAE basals dels pacients amb LPA i els de referència de la població sana de Barcelona. Es conclou doncs que el CAE és una tècnica no invasiva que pot ser usada en la monitorització de paceints ventilats mecànicament. El salbutamol inhalat incrementa de manera significativa el pH del CAE dels paceints amb LPA, tot i que un efecte directe de la inhalació de slabutamol no pot ser desestimat.

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This paper studies price determination in pharmaceutical markets using data for 25 countries, six years and a comprehensive list of products from the MIDAS IMS database. We show that market power and the quality of the product has a significantly positive impact of prices. The nationality of the producer appears to have a small and often insignificant impact on prices, which suggests that countries which regulates prices have relatively little power to do it in a way that advances narrow national interest. We produce a theoretical explanation for this phenomenon based on the fact that low negotiated prices in a country would have a knock-on effect in other markets, and is thus strongly resisted by producers. Another key finding is that the U.S. has prices that are not significantly higher than those of countries with similar income levels. This, together with the former observation on the effect of the nationality of producers casts doubt on the ability of countries to purs

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We study a retail benchmarking approach to determine access prices for interconnected networks. Instead of considering fixed access charges as in the existing literature, we study access pricing rules that determine the access price that network i pays to network j as a linear function of the marginal costs and the retail prices set by both networks. In the case of competition in linear prices, we show that there is a unique linear rule that implements the Ramsey outcome as the unique equilibrium, independently of the underlying demand conditions. In the case of competition in two-part tariffs, we consider a class of access pricing rules, similar to the optimal one under linear prices but based on average retail prices. We show that firms choose the variable price equal to the marginal cost under this class of rules. Therefore, the regulator (or the competition authority) can choose one among the rules to pursue additional objectives such as consumer surplus, network covera.

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This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

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In this paper, we investigate whether evidence of discriminatory treatment against immigrants in the Spanish mortgage market exists. More specifically, we test whether, ceteris paribus, immigrant borrowers tend to be charged with higher interest rates on their mortgages than their Spanish born counterparts. To do so, we use a unique dataset on granted mortgages that contains information not only regarding the conditions of the loan but also the socio-economic characteristics of the mortgagors. We observe that immigrants are systematically charged with higher interest rates. We apply the well known Oaxaca-Blinder decomposition to measure the extent to which this disparate treatment of lenders in mortgage pricing against immigrants is due to discrimination. Our results indicate that approximately two thirds of the gap in the interest rate between Spanish born and immigrant borrowers can be attributed to discriminatory treatment. Key words: Immigration, discrimination, mortgage pricing, housing market. JEL codes: R21, G21, J14

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La morfina es l’opioid majoritàriament utilitzat en dolor oncològic, però existeix elevada variabilitat de resposta. Vam intentar correlacionar aquesta variabilitat amb polimorfismes genètics (Opmr-1, Beta-arrestina2, Stat6 i COMT, relacionats amb mecanismes d’acció opioids). Hem estudiat 29 pacients amb dolor (EVA superior o igual a 6) que van iniciar tractament amb morfina i vam avaluar eficacia i tolerancia a la morfina correlacionant-ho amb els polimorfismos que presentaven. Vam observar que els genotips CC/TC per β-arrestina2 i AA/GA per COMT i Oprm1 es podrien associar a millor resposta i menor toxicitat a la morfina, i els genotips AA/GA per STAT6 s’associaven significativament a menor toxicitat

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A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

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The biplot has proved to be a powerful descriptive and analytical tool in many areasof applications of statistics. For compositional data the necessary theoreticaladaptation has been provided, with illustrative applications, by Aitchison (1990) andAitchison and Greenacre (2002). These papers were restricted to the interpretation ofsimple compositional data sets. In many situations the problem has to be described insome form of conditional modelling. For example, in a clinical trial where interest isin how patients’ steroid metabolite compositions may change as a result of differenttreatment regimes, interest is in relating the compositions after treatment to thecompositions before treatment and the nature of the treatments applied. To study thisthrough a biplot technique requires the development of some form of conditionalcompositional biplot. This is the purpose of this paper. We choose as a motivatingapplication an analysis of the 1992 US President ial Election, where interest may be inhow the three-part composition, the percentage division among the three candidates -Bush, Clinton and Perot - of the presidential vote in each state, depends on the ethniccomposition and on the urban-rural composition of the state. The methodology ofconditional compositional biplots is first developed and a detailed interpretation of the1992 US Presidential Election provided. We use a second application involving theconditional variability of tektite mineral compositions with respect to major oxidecompositions to demonstrate some hazards of simplistic interpretation of biplots.Finally we conjecture on further possible applications of conditional compositionalbiplots

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In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.