Realized Volatility: A Review

This article reviews the exciting and rapidly expanding literature on realized volatility. After presenting a general univariate framework for estimating realized volatilities, a simple discrete time model is presented in order to motivate the main results. A continuous time specification provides the theoretical foundation for the main results in this literature. Cases with and without microstructure noise are considered, and it is shown how microstructure noise can cause severe problems in terms of consistent estimation of the daily realized volatility. Independent and dependent noise processes are examined. The most important methods for providing consistent estimators are presented, and a critical exposition of different techniques is given. The finite sample properties are discussed in comparison with their asymptotic properties. A multivariate model is presented to discuss estimation of the realized covariances. Various issues relating to modelling and forecasting realized volatilities are considered. The main empirical findings using univariate and multivariate methods are summarized.     

Semiparametric Estimation of Risk–Return Relationships

This article proposes semiparametric generalized least-squares estimation of parametric restrictions between the conditional mean and the conditional variance of excess returns given a set of parametric factors. A distinctive feature of our estimator is that it does not require a fully parametric model for the conditional mean and variance. We establish consistency and asymptotic normality of the estimates. The theory is nonstandard due to the presence of estimated factors. We provide sufficient conditions for the estimated factors not to have an impact in the asymptotic standard error of estimators. A simulation study investigates the finite sample performance of the estimates. Finally, an application to the CRSP value-weighted excess returns highlights the merits of our approach. In contrast to most previous studies using nonparametric estimates, we find a positive and significant price of risk in our semiparametric setting.     

Estimating the Risk of a Down's Syndrome Term Pregnancy Using Age and Serum Markers: Comparison of Various Methods

The risk of an individual woman having a pregnancy associated with Down's syndrome is estimated given her age, α-fetoprotein, human chorionic gonadotropin, and pregnancy-specific β1-glycoprotein levels. The classical estimation method is based on discriminant analysis under the assumption of lognormality of the marker values, but logistic regression is also applied for data classification. In the present work, we compare the performance of the two methods using a dataset containing the data of almost 89,000 unaffected and 333 affected pregnancies. Assuming lognormality of the marker values, we also calculate the theoretical detection and false positive rates for both the methods.     

On Markov-Pólya Distribution and the Katz Family of Distributions

This article is concerned with the Markov-Pólya distribution and its links with the Katz family of distributions. The Katz family is defined through a first-order recursion of remarkable form; it (only) covers the Poisson, negative binomial and binomial distributions. The Markov-Pólya distribution arises in the study of certain urn or population models that incorporate (anti)contagion effects. The present work is motivated by questions and applications in actuarial sciences. First, the Markov-Pólya distribution is presented as a claim frequency model. This distribution is then shown to satisfy a Katz-like recursion. As a consequence, a simple recursion is derived for computing a compound sum distribution that generalizes the Panjer algorithm in risk theory. The Katz family is also obtained as a limit of the Markov-Pólya distribution. Finally, an observed frequency of car accidents is fitted by a Markov-Pólya distribution.     

Bayesian estimation of mean and square of mean of normal distribution using linex loss function

In this paper, the Bayes estimators for mean and square of mean ol a normal distribution with mean μ and vaiiance σ r2 (known), relative to LINEX loss function are obtained Comparisons in terms of risk functions and Bayes risks of those under LINEX loss and squared error loss functions with their respective alternative estimators viz, UMVUE and Bayes estimators relative to squared error loss function, are made. It is found that Bayes estimators relative to LINEX loss function dominate the alternative estimators m terms of risk function snd Bayes risk. It is also found that if t2 is unknown the Bayes estimators are still preferable over alternative estimators.     

Estimating the Parameters of Stochastic Volatility Models Using Option Price Data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.     

Faith's wager: How religion deters gambling

The relationship between religion and gambling has only rarely been investigated in sociology and related fields. Prior studies have found that religion, broadly defined, deters gambling, with different religious traditions exhibiting varying degrees of deterrence. Our study, a quantitative analysis of a recent representative sample of U.S. adults, theorizes and tests how three different dimensions of religion affect three distinct forms of gambling. Religious tradition and religious service attendance are found to reduce the likelihood of casino gambling and lottery play; while religious salience is the only dimension that constrains online gambling. We argue that these findings reflect variation in the social visibility, time intensity, and broader legitimacy associated with gambling forms, and that this variation is crucial for understanding the deterring effects of faith.     

Gynecologic age is an important risk factor for obstetric and perinatal outcomes in adolescent pregnancies

BackgroundAdolescent pregnancy is an important public health problem. Physiological maturity affects obstetric and perinatal outcomes. Almost all assessments of adolescent pregnancies are based on chronological age. Gynecologic age (GA) is defined as age in years at conception minus age at menarche and it is an indicator of physiological maturity.AimTo compare obstetric and perinatal outcomes between adult and adolescent pregnancies as categorized according to GA.MethodsIn this retrospective study, 233 adolescent pregnant women were divided into two groups based on GA ≤ 3 years (101 women) and GA > 3 years (132 women). Their obstetric and perinatal results were compared with 202 adult pregnancies who gave birth in the same period.FindingsGestational age at delivery, APGAR scores, birth weight, and incidence of preterm birth, admission to neonatal intensive care unit (NICU), intrauterine growth restriction, low birth weight, and premature rupture of membranes were significantly different between the study groups. Compared to adolescent pregnancies with GA > 3 years, adolescent pregnancies with GA ≤ 3 years had significantly lower birth weight, gestational age, APGAR scores, and significantly higher incidence of intrauterine growth restriction, low birth weight and admission to NICU.ConclusionLow GA is associated with an increased rate of obstetric and perinatal complications in adolescent pregnancies. Although the main aim is the prevention of adolescent pregnancies, a detailed evaluation of such pregnancies including determination of the gynecological age together with a multidisciplinary approach may decrease potential complications.     

Stigma mitigation and the importance of redundant treatments

Disgust can evoke strong behavioral responses. Sometimes these extreme visceral responses can lead to stigmatization—an overreaction to a risk. In fact, disgust may be so inhibiting that it leads people to refuse to consume completely safe items, such as treated drinking water, leading to important economic and policy implications. Using economic experiments, we provide a measure of the behavioral response to disgust. Our findings suggest that when monetary incentives are provided, the behavioral response may have been exaggerated by previous studies that have relied on survey methods. Furthermore, mitigation steps successfully reduce the stigma behavior. In fact, the results suggest that stigma is primarily reduced not by a specific mitigation step taken but by how many steps are taken consecutively. These results have important implications for policies addressing issues such as the global shortage of drinking water. Some efforts to resolve the shortage have involved recycled water that is completely safe to drink but is often rejected because of reactions of disgust.     

Common fate motivates cooperation: The influence of risks on contributions to public goods

In order to study whether common fate induced by shared risk can promote cooperation, I introduce two types of risks into a public goods game: risk that is common among all group members (the COM treatment), and risk that is independent across individuals (the IND treatment). In both treatments, zero contributions is the only equilibrium. In contrast to the equilibrium analysis, contributions to the public goods in the experiment approach zero under the independent risk but remain at high levels when the common risk is present. Analysis of the data reveals that different reactions to beliefs are fundamental to this treatment effect. While beliefs and contributions in the first periods, as well as the belief formation processes, are similar across treatments, subjects in the IND treatment are significantly less cooperative than those in the COM treatment with the same beliefs. A large variation in group contributions is observed in the COM treatment. Further analysis shows that initial beliefs can explain most of the variation in the long-run contribution level, implying the importance of beliefs in shaping the players’ experience and establishing group norms.