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     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

Twinning Rates in Developed Countries: Trends and Explanations

The twinning rate has increased dramatically over the last four decades in developed countries. Two main factors account for this increase: delayed childbearing, as older women tend to have twins more frequently than younger ones, and the expansion of medically assisted reproduction (MAR), which carries an increased probability of multiple births. Using civil registration data, we estimate the share of the increase in twinning rates attributable to the rise in the age at childbearing and to MAR. The effect of MAR is estimated to be about three times as important as the effect of delayed childbearing. Negative health outcomes associated with multiple births and the cost of MAR have raised concerns. We find that in one‐quarter of developed countries with the relevant data, the twinning rate reached a plateau around the early 2000s and decreased thereafter. We examine the reasons for this reversal, in particular changes in MAR policies and practices.     

(Un)ethical practices: intimacy and Internet in the media coverage of the Ashley Madison hack

In the summer of 2015, the “cheating website” known as Ashley Madison came under scrutiny, as a group calling itself the Impact Team revealed users’ private information. This case study explores the controversy’s Canadian media coverage and sheds light on the main discourses about intimacy and the Internet that were made visible during this event. It interrogates how cheaters, hackers, and the company were represented. To varying degrees, the mainstream press condemns the cheaters, the hackers, and the company for their behaviour. The article also addresses the ways intimate practices are politicized and commercialized in the digital context, including a discussion of the emphasis on “privacy.” To conclude the article, I discuss the transparency and privacy issues implicated in digital intimacies and the power–knowledge (im)balance implied by hackers’ online anonymity.     

Corporate communications managers in large firms: new challenges

The new organisational form of large corporations (horizontal organisation), is affecting the communications job. This corporate transformation leads to new challenges for the corporate communications manager and his team. On the one hand, he has to develop a fully integrated strategy which enables the different forms of communication to contribute to the success of the firm's mission (a common goal). On the other hand, he has to provide small business units, led by strong front-line managers, with professional services. The analysis of several companies will show that the position of the corporate communications department is subject to various pressures and that the development of the `communications function' is calling into question the corporate communications manager's `profession'.     

Parenting as a Dynamic Process: A Test of the Resource Dilution Hypothesis

In this paper, we tested the resource dilution hypothesis, which posits that, because parenting resources are finite, the addition of a new sibling depletes parenting resources for other children in the household. We estimated growth curve models on the self‐reported parenting practices of mothers using four waves of data collected biennially between 1994 and 2000 on a nationally representative sample of 2,082 Canadian children aged 2 to 5 at initial interview and in continuously intact, two‐biological‐parent households. Results showed that when new children were added to the household, mothers exhibited declines in positive interaction, but increased their levels of consistent parenting. Taken together, these findings suggested that parenting resources were reallocated, rather than diluted, when family size increased.     

Inference in model-based cluster analysis

A new approach to cluster analysis has been introduced based on parsimonious geometric modelling of the within-group covariance matrices in a mixture of multivariate normal distributions, using hierarchical agglomeration and iterative relocation. It works well and is widely used via the MCLUST software available in S-PLUS and StatLib. However, it has several limitations: there is no assessment of the uncertainty about the classification, the partition can be suboptimal, parameter estimates are biased, the shape matrix has to be specified by the user, prior group probabilities are assumed to be equal, the method for choosing the number of groups is based on a crude approximation, and no formal way of choosing between the various possible models is included. Here, we propose a new approach which overcomes all these difficulties. It consists of exact Bayesian inference via Gibbs sampling, and the calculation of Bayes factors (for choosing the model and the number of groups) from the output using the Laplace–Metropolis estimator. It works well in several real and simulated examples.     

ECONOMIC SCIENCE AND POLITICAL INFLUENCE

When policymakers and private agents use models, the economists who design the model have an incentive to alter it in order to influence outcomes in a fashion consistent with their own preferences. I discuss some consequences of the existence of such ideological bias. In particular, I analyze the role of measurement infrastructures such as national statistical institutes, the extent to which intellectual competition between different schools of thought may lead to polarization of views over some parameters and at the same time to consensus over other parameters, and finally how the attempt to preserve influence can lead to degenerative research programs.     

Vector correlation for elliptical distributions

A measure of multivariate correlation between two sets of vectors is considered when the underlying joint distribution is a member of the class of elliptical distributions. Its asymptotic distribution is derived under different situations and these results are used to test hypotheses on vector correlation when the underlying joint distribution is non-normal.