Price bias and common practice in option pricing

Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump intensity. A popular practice is to use an estimate of these latent factors to compute the option price. However, in many situations this plug-and-play approximation does not yield the appropriate price. This article examines this bias and quantifies its impacts. We decompose the bias into terms that are related to the bias on the unobservable factors and to the precision of their point estimators. The approximated price is found to be highly biased when only the history of the stock price is used to recover the latent states. This bias is corrected when option prices are added to the sample used to recover the states' best estimate. We also show numerically that such a bias is propagated on calibrated parameters, leading to erroneous values. The Canadian Journal of Statistics 48: 8–35; 2020 © 2019 Statistical Society of Canada     

Australia and the Global South: Knowledge and the Ambiguities of Place and Identity

Australia was settled as a colony of Britain from the 17th century, and its early history of violent occupation has gradually given way to a relatively peaceful, wealthy, multicultural society. As a post-colonial country, its people share characteristics with those of Britain, but, as a multicultural society, national identity is increasingly influenced by the cultures of many countries, from both the global North and South. In this paper, the question of Australia's placement as a country of the global North or South is explored. Considerations of geography, the economy, political regimes and national identity are the backdrop to an investigation of Australian scholarship and the attitudes of scholars to the inclusion of Australia as a country of the global South.     

The Measurement of Multidimensional Poverty

Many authors have insisted on the necessity of defining poverty as a multidimensional concept rather than relying on income or consumption expenditures per capita. Yet, not much has actually been done to include the various dimensions of deprivation into the practical definition and measurement of poverty. Existing attempts along that direction consist of aggregating various attributes into a single index through some arbitrary function and defining a poverty line and associated poverty measures on the basis of that index. This is merely redefining more generally the concept of poverty, which then essentially remains a one dimensional concept. The present paper suggests that an alternative way to take into account the multi-dimensionality of poverty is to specify a poverty line for each dimension of poverty and to consider that a person is poor if he/she falls below at least one of these various lines. The paper then explores how to combine these various poverty lines and associated one-dimensional gaps into multidimensional poverty measures. An application of these measures to the rural population in Brazil is also given with poverty defined on income and education.     

The Chinese-speaking Muslims (Dungans) of Central Asia: A Case of Multiple Identities in a Changing Context

Chinese-speaking Muslims, called Dungans in Central Asia and Huizu in China, were forced to migrate to present-day Kazakhstan, Kyrgyzstan and Uzbekistan at the end of the nineteenth century. They reconstructed their identity through interrelations with local populations and the soviet categorisation of nationality. But after 1991, their status has being gradually destabilised owing to the changes in economic, social and political rules as well as citizenship regulations in these countries. They have to readapt to the new situation created by the independence of the three former Soviet Republics, which has challenged their unity.     

Local dependence estimation using semiparametric archimedean copulas

The authors define a new semiparametric Archimedean copula family which has a flexible dependence structure. The generator of the family is a local interpolation of existing generators. It has locally‐defined dependence parameters. The authors present a penalized constrained least‐squares method to estimate and smooth these parameters. They illustrate the flexibility of their dependence model in a bi‐variate survival example.     

Analyse biographique du travail féminin

Cet article montre comment l'application d'une méthode d'analyse biographique d'interaction à un domaine où l'interaction paraît évidente — activité féminine et fécondite — ouvre des perspectives nouvelles. En effet, les limites qui apparaissent lors de cette analyse conduisent les auteurs à conclure que ce n'est pas en raffinant les méthodes mais plutôt la collecte que l'on parviendra à progresser dans ce domaine. Le problème des interactions de l'activité et de la fécondité semble mal posé avant même le recours à la méthode. Cela justifie la nécessité de saisir le travail féminin comme concept unifié ne dissociant pas la sphère domestique et la sphère rémunérée. Cela conduit les auteurs à dégager quelques principes de collecte mieux adaptés aux préoccupations récentes dans ce domaine: des données biographiques sur le travail féminin. L'interaction collectée à sa source se prêterait alors à une analyse biographique plus révélatrice que celle qui confronte deux processus sans en évaluer les modalités changeantes.This article demonstrates how life event history analysis applied to the interaction between fertility and female economic activity can lead to new perspectives in the analysis of this complicated relationship. The authors identify limits to the analysis of the interaction given the anticipatory nature of behaviour. They conclude that progress in this field requires not the refinement of methods but rather a fundamental change in the approach to the data collected. If fertility and employment are considered separately, a problem is created even before the methods of analysis are applied. They recommend a conception of women's work as a whole, a conception that does not dissociate domestic and paid work. The authors go on to identify ways of improving the relevance of data collection to contemporary issues in the life history analysis of women's work. They argue that data on the interaction, collected at its source, would yield a more revealing life history than that which sees domestic work and paid work as separate spheres, and fails to take account of changes in their relationship.     

The Access/Impact Problem and the Green and Gold Roads to Open Access

The research access/impact problem arises because journal articles are not accessible to all of their would-be users; hence, they are losing potential research impact. The solution is to make all articles Open Access (OA; i.e., accessible online, free for all). OA articles have significantly higher citation impact than non-OA articles. There are two roads to OA: the “golden” road (publish your article in an OA journal) and the “green” road (publish your article in a non-OA journal but also self-archive it in an OA archive). Only 5% of journals are gold, but over 90% are already green (i.e., they have given their authors the green light to self-archive); yet only about 10–20% of articles have been self-archived. To reach 100% OA, self-archiving needs to be mandated by researchers' employers and funders, as the United Kingdom and the United States have recently recommended, and universities need to implement that mandate.     

Optimal scaling of Metropolis algorithms: Heading toward general target distributions

The authors provide an overview of optimal scaling results for the Metropolis algorithm with Gaussian proposal distribution. They address in more depth the case of high‐dimensional target distributions formed of independent, but not identically distributed components. They attempt to give an intuitive explanation as to why the well‐known optimal acceptance rate of 0.234 is not always suitable. They show how to find the asymptotically optimal acceptance rate when needed, and they explain why it is sometimes necessary to turn to inhomogeneous proposal distributions. Their results are illustrated with a simple example.     

A bayesian estimator for the dependence function of a bivariate extreme‐value distribution

Any continuous bivariate distribution can be expressed in terms of its margins and a unique copula. In the case of extreme‐value distributions, the copula is characterized by a dependence function while each margin depends on three parameters. The authors propose a Bayesian approach for the simultaneous estimation of the dependence function and the parameters defining the margins. They describe a nonparametric model for the dependence function and a reversible jump Markov chain Monte Carlo algorithm for the computation of the Bayesian estimator. They show through simulations that their estimator has a smaller mean integrated squared error than classical nonparametric estimators, especially in small samples. They illustrate their approach on a hydrological data set.     

Almost Consistent Estimation of Panel Probit Models with “Small” Fixed Effects

We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel probit models with fixed effects for the case of small Tand large N. The moments used are derived for each period from a first order approximation of the mean of the dependent variable conditional on explanatory variables and on the fixed effect. The estimators differ w.r.t. the choice of instruments and whether they use trimming to reduce the bias or not. In a Monte Carlo study, we compare these estimators with pooled probit and conditional logit estimators for different data generating processes. The results show that the proposed estimators outperform these competitors in several situations.