Interpreting Value at Risk (VaR) forecasts

Value at Risk (VaR) forecasts have been increasingly accepted globally by both risk managers and regulators as a tool to identify and control exposure to financial market risk. However, modern portfolios are characterized by a constantly changing composition of security holdings that reflect portfolio managers’ strategies, expected prices, and net cash flows into the portfolio. As a result of these factors, portfolio returns are time-varying mixtures of distributions which are unlikely to be well approximated by conventional methods.     

Are Sunk Costs a Barrier to Entry?

The received wisdom is that sunk costs create a barrier to entry—if entry fails, then the entrant, unable to recover sunk costs, incurs greater losses. In a strategic context where an incumbent may prey on the entrant, sunk entry costs have a countervailing effect: they may effectively commit the entrant to stay in the market. By providing the entrant with commitment power, sunk investments may soften the reactions of incumbents. The net effect may imply that entry is more profitable when sunk costs are greater.     

Anomalies in the Foundations of Ridge Regression

Errors persist in ridge regression, its foundations, and its usage, as set forth in Hoerl & Kennard (1970) and elsewhere. Ridge estimators need not be minimizing, nor a prospective ridge parameter be admissible. Conventional estimators are not LaGrange's solutions constrained to fixed lengths, as claimed, since such solutions are singular. Of a massive literature on estimation, prediction, cross–validation, choice of ridge parameter, and related issues, little emanates from constrained optimization to include inequality constraints. The problem traces to a misapplication of LaGrange's Principle, unrecognized singularities, and misplaced links between constraints and ridge parameters. Alternative principles, based on condition numbers, are seen to validate both conventional ridge and surrogate ridge regression to be defined. Numerical studies illustrate that ridge regression as practiced often exhibits pathologies it is intended to redress.     

Can the Timing of Negotiations Impact the Consequences of Mergers?

This paper uses a theoretical model to examine whether variation in the timing of negotiations between buyers and sellers can alter the effects of mergers between sellers. The model shows that mergers between horizontally overlapping firms lead to price increases regardless of how negotiations take place. In contrast, mergers between firms in different markets can only lead to higher compensation for the combined firm when negotiations occur sequentially. However, any price effects from out‐of‐market mergers stem from a mechanical redistribution of existing market power and not from a loss in competition. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.     

摒弃文档低效率节约纳税人资金

2007年国际团队卓越竞赛(International Team Excellence Competition)的三位银奖获得者之一,来自佛罗里达州的一个团队,他们创造了一项绝佳的解决方案,该方案可以节约佛罗里达州纳税人1800万美元的资金.     

Least-squares forecast averaging

This paper proposes forecast combination based on the method of Mallows Model Averaging (MMA). The method selects forecast weights by minimizing a Mallows criterion. This criterion is an asymptotically unbiased estimate of both the in-sample mean-squared error (MSE) and the out-of-sample one-step-ahead mean-squared forecast error (MSFE). Furthermore, the MMA weights are asymptotically mean-square optimal in the absence of time-series dependence. We show how to compute MMA weights in forecasting settings, and investigate the performance of the method in simple but illustrative simulation environments. We find that the MMA forecasts have low MSFE and have much lower maximum regret than other feasible forecasting methods, including equal weighting, BIC selection, weighted BIC, AIC selection, weighted AIC, Bates–Granger combination, predictive least squares, and Granger–Ramanathan combination.     

Rater source factors represent important subcomponents of the criterion construct space, not rater bias

We contrast normative accuracy and ecological perspectives on applications of the multitrait–multimethod methodology to multisource performance ratings and review existing research that provides critical tests of these perspectives. Existing research supports the ecological perspective which proposes that the rater source effects that are typically found in analysis of multisource performance ratings do not represent mere halo biases but alternative, perhaps equally valid perspectives on ratee performance. We suggest that future research view multifaceted research designs in the broader context of a prototype multidimensional data relational system such as that proposed by Lance, Baranik, Lau, and Scharlau (Lance, C. E., Baranik, L. E., Lau, A. R., & Scharlau, E. A. (in press). If it's not trait it must be method: (Mis)application of the multitrait–multimethod design in organizational research. In C. E. Lance & R. J. Vandenberg (Eds.), Statistical and methodological myths and urban legends: Received doctrine, verity, and fable in the organizational and social sciences. Mahwah, NJ: Erlbaum).     

The Mendacity of Reconciliation in an Age of Resentment

The political ideal of reconciliation has gained increased prominence in recent decades, in part due to political experiments such as the South African Truth and Reconciliation Commission and other formal or informal truth or reconciliation processes. Here, I argue that there is a fundamental mendacity to reconciliation, given stubborn asymmetries of social power and disrespect. Reconciliation as an ideal carries an impetus towards resolution that covers over the necessary role that conflict plays in political struggles—including the role that conflict plays within struggles for reconciliation. Nevertheless, despite the mendacity of reconciliation, its meaning still holds political value. Reconciliation implies an orientation towards social repair, which even the strongest critics of reconciliation cannot bring themselves to reject. Some lies are worse than others, and some lies might be noble or necessary. Reconciliation is the latter—a fiction that is less pernicious than its absence. In this light, the task is to locate means of political reconciliation that do not obscure the conflicts and asymmetries of social life but enable social actors to face up to these conflicts and to discover novel ways to repair the damage that they can do.     

Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of start‐ups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a nonemployer to employer firm among start‐ups. Several interesting patterns emerge regarding the dynamics of nonemployer start‐ups hiring their first employee. Hiring rates among the universe of nonemployer start‐ups are very low, but increase when the population of nonemployers is focused on more growth‐oriented businesses such as incorporated and employer identification number businesses. If nonemployer start‐ups hire, the bulk of hiring occurs in the first few years of existence. After this point in time, relatively few nonemployer start‐ups hire an employee. Focusing on more growth‐ and employment‐oriented start‐ups in the KFS, we find that Asian‐owned and Hispanic‐owned start‐ups have higher rates of hiring their first employee than white‐owned start‐ups. Female‐owned start‐ups are roughly 10 percentage points less likely to hire their first employee by the first, second, and seventh years after start‐up. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that nonemployers hire their first employee.