Could a CAMELS downgrade model improve off-site surveillance?

The Federal Reserve’s off-site surveillance system includes two econometric models that are collectively known as the System for Estimating Examination Ratings (SEER). One model, the SEER risk rank model, uses the latest financial statements to estimate the probability that each Fed-supervised bank will fail in the next two years. The other component, the SEER rating model, uses the latest financial statements to produce a “shadow” CAMELS rating for each supervised bank. Banks identified as risky by either model receive closer supervisory scrutiny than other state-member banks.> Because many of the banks flagged by the SEER models have already tumbled into poor condition and, hence, would already be receiving considerable supervisory attention, we developed an alternative model to identify safe-and-sound banks that potentially are headed for financial distress. Such a model could help supervisors allocate scarce on- and off-site resources by pointing out banks not currently under scrutiny that need watching.> It is possible, however, that our alternative model improves little over the current SEER framework. All three models—the SEER risk rank model, the SEER rating model, and our downgrade model—produce ordinal rankings based on overall risk. If the financial factors that explain CAMELS downgrades differ little from the financial factors that explain failures or CAMELS ratings, then all three models will produce similar risk ratings and, hence, similar watch lists of one- and two-rated banks.> We find only slight differences in the ability of the three models to spot emerging financial distress among safe-and-sound banks. In out-of-sample tests for 1992 through 1998, the watch lists produced by the downgrade model outperform the watch lists produced by the SEER models by only a small margin. We conclude that, in relatively tranquil banking environments like the 1990s, a downgrade model adds little value in off-site surveillance. We caution, however, that a downgrade model might prove useful in more turbulent banking times.Bank supervision

Can feedback from the jumbo-CD market improve bank surveillance?

We examine the value of jumbo certificate-of-deposit (CD) signals in bank surveillance. To do so, we first construct proxies for default premiums and deposit runoffs and then rank banks based on these risk proxies. Next, we rank banks based on the output of a logit model typical of the econometric models used in off-site surveillance. Finally, we compare jumbo-CD rankings and surveillance-model rankings as tools for predicting financial distress. Our comparisons include eight out-of-sample test windows during the 1990s. We find that rankings obtained from jumbo-CD data would not have improved on rankings obtained from conventional surveillance tools. More importantly, we find that jumbo-CD rankings would not have improved materially over random rankings of the sample banks. These findings validate current surveillance practices and, when viewed with other recent empirical tests, raise questions about the value of market signals in bank surveillance.Finance ; Banks and banking ; Bank supervision

The role of a CAMEL downgrade model in bank surveillance

This article examines the potential contribution to bank supervision of a model designed to predict which banks will have their supervisory ratings downgraded in future periods. Bank supervisors rely on various tools of off-site surveillance to track the condition of banks under their jurisdiction between on-site examinations, including econometric models. One of the models that the Federal Reserve System uses for surveillance was estimated to predict bank failures. Because bank failures have been so rare during the last decade, the coefficients on this model have been "frozen" since 1991. Each quarter the surveillance staff at the Board of Governors provide the supervision staff in the Reserve Banks the probabilities of failure by the banks subject to Fed supervision, based on the coefficients of this bank failure model and the latest call report data for each bank. The number of banks downgraded to problem status in recent years has been substantially larger than the number of bank failures. During a period of few bank failures, the relevance of this bank failure model for surveillance depends to some extent on the accuracy of the model in predicting which banks will have their supervisory ratings downgraded to problem status in future periods. This paper compares the ability of two models to predict downgrades of supervisory ratings to problem status: the Board staff model, which was estimated to predict bank failures, and a model estimated to predict downgrades of supervisory ratings. We find that both models do about as well in predicting downgrades of supervisory ratings for the early 1990s. Over time, however, the ability of the downgrade model to predict downgrades improves relative to that of the model estimated to predict failures. This pattern reflects the value of using a model for surveillance that can be re-estimated frequently. We conclude that the downgrade model may prove to be a useful supplement to the Board's model for estimating failures during periods when most banks are healthy, but that the downgrade model should not be considered a replacement for the current surveillance framework.Bank supervision

Can feedback from the jumbo-CD market improve off-site surveillance of community banks?

We examine the value of feedback from the jumbo-certificate-of-deposit (CD) market in the off-site surveillance of community banks. Using accounting data, we construct proxies for default premiums on jumbo CDs. Then, we produce rank orderings of community banks -- defined as institutions holding less than $500 million in assets (constant 1999 dollars) -- based on these proxies. Next, we use an econometric surveillance model to generate rank orderings based on the probability of encountering financial distress. Finally, we compare these rank orderings as tools for flagging emerging problems. Our comparisons include eight out-of-sample test windows during the 1990s. We find that feedback from the jumbo-CD market would have added little value in community-bank surveillance during our sample period. Specifically, rank orderings based on output from the econometric model significantly outperformed rank orderings based on jumbo-CD default premiums. More important, the jumbo-CD orderings improved little over a random ordering. Other attempts to extract risk signals from the jumbo-CD data yielded similar results. Taken together, our findings validate current surveillance practices. We conclude by arguing that the robust economic environment of the 1990s probably plays a large role in our results.Community banks ; Bank supervision

Can feedback from the jumbo CD market improve bank surveillance?

Banks and banking

Experimental Demonstration of Post-Selection based Continuous Variable Quantum Key Distribution in the Presence of Gaussian Noise

In realistic continuous variable quantum key distribution protocols, an eavesdropper may exploit the additional Gaussian noise generated during transmission to mask her presence. We present a theoretical framework for a post-selection based protocol which explicitly takes into account excess Gaussian noise. We derive a quantitative expression of the secret key rates based on the Levitin and Holevo bounds. We experimentally demonstrate that the post-selection based scheme is still secure against both individual and collective Gaussian attacks in the presence of this excess noise.Comment: 4 pages, 4 figure

Event Tracker: a Text Analytics Platform for Use During Disasters

Emergency management organisations currently rely on a wide range of disparate tools and technologies to support the monitoring and management of events during crisis situations. This has a number of disadvantages, in terms of training time for new staff members, reliance on external services, and a lack of integration (and hence poor transfer of information) between those services. On the other hand, Event Tracker is a new solution that aims to provide a unified view of an event, integrating information from emergency response officers, the public (via social media) and also volunteers from around the world. In particular, Event Tracker provides a series of novel functionalities to realise this unified view of the event, namely: real-time identification of critical information, automatic grouping of content by the information needs of response officers, as well as real-time volunteers management and communication. This is supported by an efficient and scalable back-end infrastructure designed to ingest and process high-volumes of real-time streaming data with low latency

Impact of T2R38 receptor polymorphisms on Pseudomonas aeruginosa infection in cystic fibrosis

The T2R38 (taste receptor 2 member 38) bitter taste receptor on respiratory epithelia detects Pseudomonas aeruginosa N-acyl-l-homoserine lactones (AHLs). In vitro, T2R38 activation by AHLs initiates calcium-mediated increases in nitric oxide production and ciliary beat frequency, dependent on polymorphisms in the TAS2R38 gene (1). In patients with chronic rhinosinusitis, the TAS2R38 genotype is proposed to modify mucosal responses to P. aeruginosa (1). Polymorphisms in the TAS2R38 gene result in two high-frequency haplotypes associated with taste perception of the bitter compound phenylthiocarbamide (2). The “taster” haplotype codes proline-alanine-valine (PAV), and the “nontaster” haplotype codes alanine-valine-isoleucine (AVI) at positions 49, 262, and 296 in the receptor protein. Responses to AHLs in vitro are greatest in PAV/PAV epithelial cells, and this genotype is reported to be protective against P. aeruginosa in the sinonasal airway (1). P. aeruginosa is the most frequently isolated respiratory pathogen in cystic fibrosis (CF), and chronic infection is associated with accelerated rates of disease progression. Determining the impact of TAS2R38 polymorphisms on P. aeruginosa infection in CF could have implications for patient risk stratification and, as naturally occurring and synthetic agonists to T2R38 are already in clinical use (3), could identify promising therapeutic targets. We characterized T2R38 localization in the CF airway and investigated the hypothesis that TAS2R38 polymorphisms would modify the prevalence and impact of P. aeruginosa infection in CF. Some of the results of these studies have previously been reported in the form of abstracts

A new tyrannosaurid (Dinosauria: Theropoda) from the Upper Cretaceous Menefee Formation of New Mexico

The giant tyrannosaurids were the apex predators of western North America and Asia during the close of the Cretaceous Period. Although many tyrannosaurid species are known from numerous skeletons representing multiple growth stages, the early evolution of Tyrannosauridae remains poorly known, with the well-known species temporally restricted to the middle Campanian-latest Maastrichtian (∼77–66 Ma). The recent discovery of a new tyrannosaurid, Lythronax argestes, from the Wahweap Formation of Utah provided new data on early Campanian (∼80 Ma) tyrannosaurids. Nevertheless, the early evolution of Tyrannosauridae is still largely unsampled. We report a new tyrannosaurid represented by an associated skeleton from the lower Campanian Allison Member of the Menefee Formation of New Mexico. Despite fragmentation of much of the axial and appendicular skeleton prior to discovery, the frontals, a metacarpal, and two pedal phalanges are well-preserved. The frontals exhibit an unambiguous autapomorphy and a second potential autapomorphy that distinguish this specimen from all other tyrannosaurids. Therefore, the specimen is made the holotype of the new genus and species Dynamoterror dynastes. A phylogenetic analysis places Dynamoterror dynastes in the tyrannosaurid subclade Tyrannosaurinae. Laser-scanning the frontals and creation of a composite 3-D digital model allows the frontal region of the skull roof of Dynamoterror to be reconstructed