Tail dependence analysis of stock markets using extreme value theory

Financial risk modelling frequently uses the assumption of a normal distribution when considering the return series which is inefficient if the data is not normally distributed or if it exhibits extreme tails. Estimation of tail dependence between financial assets plays a vital role in various aspects of financial risk modelling including portfolio theory and hedging amongst applications. Extreme Value Theory (EVT) provides well established methods for considering univariate and multivariate tail distributions which are useful for forecasting financial risk or modelling the tail dependence of risky assets. The empirical analysis in this article uses nonparametric measures based on bivariate EVT to investigate asymptotic dependence and estimate the degree of tail dependence of the ASX-All Ordinaries daily returns with four other international markets, viz., the S&P-500, Nikkei-225, DAX-30 and Heng-Seng for both extreme right and left tails of the return distribution. It is investigated whether the asymptotic dependence between these markets is related to the heteroscedasticity present in the logarithmic return series using GARCH filters. The empirical evidence shows that the asymptotic extreme tail dependence between stock markets does not necessarily exist and rather can be associated with the heteroscedasticity present in the financial time series of the various stock markets.     

Objective estimation versus subjective perceptions of earnings patterns and post‐earnings‐announcement drift

We investigate how the market's subjective estimates of autocorrelation in quarterly earnings vary with objective time‐series estimates. Our results suggest that investors increasingly underestimate the correlation as the autocorrelation level increases, and as a result, the post‐earnings‐announcement drift (PEAD) increases with the level of autocorrelation. We further show that the ability of autocorrelation to explain variation in the PEAD is robust to alternative explanations based on risk and institutional factors. Additional analysis indicates that the market's inefficiency in assessing the existence and magnitude of autocorrelation (and the related impact on PEAD) is inversely related to the richness of the information environment.     

SPACE AND TIME: A COMPETING RISKS ANALYSIS OF THE IMPACT OF PROPERTY TAXES AND ZONING RESTRICTIONS ON RESIDENTIAL DEVELOPMENT

Property taxes and zoning restrictions are prevalent tools for managing land use. We combine microlevel data on residential subdivision development from the Baltimore, Maryland, metro area from 1994 to 2007 with a competing risks model to examine how both policies influence the density and timing of residential development. Consistent with theory, we demonstrate that the impact of both policies on optimal density and timing depends on whether density and time are substitutes or complements in the profit function. Our results have important implications as they provide key empirical insights into how property taxes and zoning interact to influence development patterns.     

CEO compensation and performance in US private foundations

In a large sample of US private foundations, we examine the association between CEO compensation and an accounting‐based measure of performance, administrative efficiency. We document a positive pay–performance association across time within foundations, but a negative association across foundations. We interpret our evidence as follows: some foundation boards reward CEOs for high administrative efficiency, which results in a positive pay–performance association. However, some foundations are poorly monitored relative than others, resulting in higher CEO compensation and lower efficiency.     

Growth outside the core

Growth in an adjacent market is tougher than it looks; three-quarters of the time, the effort fails. But companies can change those odds dramatically. Results from a five-year study of corporate growth conducted by Bain & Company reveal that adjacency expansion succeeds only when built around strong core businesses that have the potential to become market leaders. And the best place to look for adjacency opportunities is inside a company's strongest customers. The study also found that the most successful companies were able to consistently, profitably outgrow their rivals by developing a formula for pushing out the boundaries of their core businesses in predictable, repeatable ways. Companies use their repeatability formulas to expand into any number of adjacencies. Some companies make repeated geographic moves, as Vodafone has done in expanding from one geographic market to another over the past 13 years, building revenues from $1 billion in 1990 to $48 billion in 2003. Others apply a superior business model to new segments. Dell, for example, has repeatedly adapted its direct-to-customer model to new customer segments and new product categories. In other cases, companies develop hybrid approaches. Nike executed a series of different types of adjacency moves: it expanded into adjacent customer segments, introduced new products, developed new distribution channels, and then moved into adjacent geographic markets. The successful repeaters in the study had two common characteristics. First, they were extraordinarily disciplined, applying rigorous screens before they made an adjacency move. This discipline paid off in the form of learning curve benefits, increased speed, and lower complexity. And second, in almost all cases, they developed their repeatable formulas by studying their customers and their customers' economics very, very carefully.     

The Newspaper Can Be an Effective Teaching Tool

The effective use of newspapers as a supplement to economic instruction is a challenge to most instructors. The author details a method of bringing real-world problems to the classroom by creating a newspaper for classroom use. Students are reported to be motivated and encouraged to think and to talk about economics.     

Managerial time constraints and young worker productivity: Natural experiments with NFL rookies

The 2011 National Football League lockout and movement of the 2014 draft to a later date compressed the off‐seasons preceding the 2011 and 2014 seasons, exogenously tightening time constraints within which managers—head coaches and their staffs—engage in short‐run training of players. We exploit these natural experiments to investigate how this impacted the productivity of young workers (National Football League rookies). Results estimated for a sample of over 1,500 rookies support hypotheses emanating from an economic model of worker training time allocation and indicate reduced productivity along several dimensions. Survival analysis shows evidence of shorter player career durations along certain lines, suggesting longer term consequences.     

Experimental errors in predictions of thermal hazards

Predictions of critical conditions for thermal runaways are generally based on heat balance models using experimentally generated heat and kinetic data. The accuracy of the predictions depends on the fit of the models and the quality of the thermal data. The relative importance of these factors to the calculated critical reaction conditions are discussed. Some additional procedures for evaluating and improving results are recommended.