Bargaining and sustainability: the Argentine debt swap of 2005

When Argentine sovereign default in December 2001 led to a collapse of the peso, the burden of dollar debt became demonstrably unsustainable. But it was not clear what restructuring was feasible, nor when. Eventually, in 2005 after a delay of more than three years, a supermajority of creditors accepted a swap implying a recovery rate of around 37 cents in the dollar. In this paper a bargaining approach is used to explain both the settlement and the delay. We conclude that the agreed swap broadly corresponds to a bargaining outcome where the Argentine government had “first mover” advantage: and that substantial delay occurred as negotiators seeking a sustainable settlement waited for economic recovery. Factors not explicit in the formal framework are also considered -- heterogeneity of creditors, for example, and the role of third parties in promoting “good faith” bargaining

Searching for nova shells around cataclysmic variables

We present the results of a search for nova shells around 101 cataclysmic variables (CVs), using Halpha images taken with the 4.2-m William Herschel Telescope (WHT) and the 2.5-m Isaac Newton Telescope Photometric Halpha Survey of the Northern Galactic Plane (IPHAS). Both telescopes are located on La Palma. We concentrated our WHT search on nova-like variables, whilst our IPHAS search covered all CVs in the IPHAS footprint. We found one shell out of the 24 nova-like variables we examined. The newly discovered shell is around V1315 Aql and has a radius of approx.2.5 arcmin, indicative of a nova eruption approximately 120 years ago. This result is consistent with the idea that the high mass-transfer rate exhibited by nova-like variables is due to enhanced irradiation of the secondary by the hot white dwarf following a recent nova eruption. The implications of our observations for the lifetime of the nova-like variable phase are discussed. We also examined 4 asynchronous polars, but found no new shells around any of them, so we are unable to confirm that a recent nova eruption is the cause of the asynchronicity in the white dwarf spin. We find tentative evidence of a faint shell around the dwarf nova V1363 Cyg. In addition, we find evidence for a light echo around the nova V2275 Cyg, which erupted in 2001, indicative of an earlier nova eruption approx.300 years ago, making V2275 Cyg a possible recurrent nova.Comment: 14 pages, 50 figures, 3 Table

Constructing packings in Grassmannian manifolds via alternating projection

This paper describes a numerical method for finding good packings in Grassmannian manifolds equipped with various metrics. This investigation also encompasses packing in projective spaces. In each case, producing a good packing is equivalent to constructing a matrix that has certain structural and spectral properties. By alternately enforcing the structural condition and then the spectral condition, it is often possible to reach a matrix that satisfies both. One may then extract a packing from this matrix. This approach is both powerful and versatile. In cases where experiments have been performed, the alternating projection method yields packings that compete with the best packings recorded. It also extends to problems that have not been studied numerically. For example, it can be used to produce packings of subspaces in real and complex Grassmannian spaces equipped with the Fubini--Study distance; these packings are valuable in wireless communications. One can prove that some of the novel configurations constructed by the algorithm have packing diameters that are nearly optimal.Comment: 41 pages, 7 tables, 4 figure

Treatment of Acute Sciatica

In patients with acute sciatica, bed rest and advice to stay active have similar outcomes on their functional status and perceived improvement. (Strength of Recommendation [SOR]: A) Spinal manipulation increases improvement compared with placebo; also, specific spinal pulling and turning manipulation techniques are more effective than traction. (SOR: A) Nonsteroidal anti-inflammatory drugs (NSAIDs) are similar to placebo in overall improvement. (SOR: A) Epidural steroid injections are unlikely to be beneficial. (SOR: A

Sovereign debt default: the impact of creditor composition

The main motivation of this paper is to study the impact of the composition of creditors on the probability of default and the risk premium on sovereign bonds, when there is debtor moral hazard. In the absence of any legal enforcement, relational contracts work only when there are creditors who have a repeated relationship with the borrower. We show that ownership structures with a larger fraction of long term lenders are associated with a lower default probability and lower risk premia. Moreover, competitive markets structures lead to loss in efficiency as well when there is moral hazard, in contrast to the case with perfect enforceability and information

Scalable Semidefinite Programming using Convex Perturbations

Several important machine learning problems can be modeled and solved via semidefinite programs. Often, researchers invoke off-the-shelf software for the associated optimization, which can be inappropriate for many applications due to computational and storage requirements. In this paper, we introduce the use of convex perturbations for semidefinite programs (SDPs). Using a particular perturbation function, we arrive at an algorithm for SDPs that has several advantages over existing techniques: a) it is simple, requiring only a few lines of MATLAB, b) it is a first-order method which makes it scalable, c) it can easily exploit the structure of a particular SDP to gain efficiency (e.g., when the constraint matrices are low-rank). We demonstrate on several machine learning applications that the proposed algorithm is effective in finding fast approximations to large-scale SDPs

Learning from eXtreme Bandit Feedback

We study the problem of batch learning from bandit feedback in the setting of extremely large action spaces. Learning from extreme bandit feedback is ubiquitous in recommendation systems, in which billions of decisions are made over sets consisting of millions of choices in a single day, yielding massive observational data. In these large-scale real-world applications, supervised learning frameworks such as eXtreme Multi-label Classification (XMC) are widely used despite the fact that they incur significant biases due to the mismatch between bandit feedback and supervised labels. Such biases can be mitigated by importance sampling techniques, but these techniques suffer from impractical variance when dealing with a large number of actions. In this paper, we introduce a selective importance sampling estimator (sIS) that operates in a significantly more favorable bias-variance regime. The sIS estimator is obtained by performing importance sampling on the conditional expectation of the reward with respect to a small subset of actions for each instance (a form of Rao-Blackwellization). We employ this estimator in a novel algorithmic procedure -- named Policy Optimization for eXtreme Models (POXM) -- for learning from bandit feedback on XMC tasks. In POXM, the selected actions for the sIS estimator are the top-p actions of the logging policy, where p is adjusted from the data and is significantly smaller than the size of the action space. We use a supervised-to-bandit conversion on three XMC datasets to benchmark our POXM method against three competing methods: BanditNet, a previously applied partial matching pruning strategy, and a supervised learning baseline. Whereas BanditNet sometimes improves marginally over the logging policy, our experiments show that POXM systematically and significantly improves over all baselines