Do Correlated Exposures Influence Intermediary Decision-making? Evidence from Trading Behavior of Equity Dealers

This paper investigates whether dealers’ trading and pricing decisions are governed by their equivalent inventories (based on total returns as in Ho and Stoll, 1983 or on unhedgeable returns as in Froot and Stein, 1998) or by their ordinary inventories, as would be the case in a decentralized market-making organizational structure. It finds that ordinary inventories, and not equivalent inventories best explain dealers’ quote placement strategy, which dealer executes trades and the quality of execution offered to the trades. This finding is consistent with decentralized market making where, due to information sharing difficulties or the nature of compensation contracts, individual dealers care only about risk of stocks managed by them, and not the positions of other dealers within the firm

Risk Management with Derivatives by Dealers and Market Quality in Government Bond Markets

This paper examines how bond dealers use futures markets to manage the hedgeable market risk component of their core business risk exposure, and whether market quality is adversely affected by their selective risk taking activity. It also investigates the efficiency of market risk sharing within a decentralized semi-transparent market structure. We find that dealers engage in duration targeting, behaving as if they have a comparative advantage in bearing interest rate risk. They make significant directional bets often by holding futures that are in the same direction as the spot. They actively use futures to hedge changes in the spot exposure. They hedge changes in their spot exposure more when the potential costs of regulatory distress are high, when the cost of such hedging is low, and during periods of greater uncertainty. We find that duration targeting by dealers has adverse price effects due to capital constraints as predicted by Froot and Stein (1998). Finally, we find that trades in the spot market are not executed by dealers with extreme exposures. In this context, we recommend market reforms such as introduction of central quote posting or limit order book that will enable more efficient matching of liquidity demanders and suppliers, reduce trading costs, and improve the quality of risk sharing

Risk Management with Derivatives by Dealers and Market Quality in Government Bond Markets

This paper examines how bond dealers use futures markets to manage the hedgeable market risk component of their core business risk exposure, and whether market quality is adversely affected by their selective risk taking activity. It also investigates the efficiency of market risk sharing within a decentralized semi-transparent market structure. We find that dealers engage in duration targeting, behaving as if they have a comparative advantage in bearing interest rate risk. They make significant directional bets often by holding futures that are in the same direction as the spot. They actively use futures to hedge changes in the spot exposure. They hedge changes in their spot exposure more when the potential costs of regulatory distress are high, when the cost of such hedging is low, and during periods of greater uncertainty. We find that duration targeting by dealers has adverse price effects due to capital constraints as predicted by Froot and Stein (1998). Finally, we find that trades in the spot market are not executed by dealers with extreme exposures. In this context, we recommend market reforms such as introduction of central quote posting or limit order book that will enable more efficient matching of liquidity demanders and suppliers, reduce trading costs, and improve the quality of risk sharing

See Through the Fog: Curriculum Learning with Progressive Occlusion in Medical Imaging

In recent years, deep learning models have revolutionized medical image interpretation, offering substantial improvements in diagnostic accuracy. However, these models often struggle with challenging images where critical features are partially or fully occluded, which is a common scenario in clinical practice. In this paper, we propose a novel curriculum learning-based approach to train deep learning models to handle occluded medical images effectively. Our method progressively introduces occlusion, starting from clear, unobstructed images and gradually moving to images with increasing occlusion levels. This ordered learning process, akin to human learning, allows the model to first grasp simple, discernable patterns and subsequently build upon this knowledge to understand more complicated, occluded scenarios. Furthermore, we present three novel occlusion synthesis methods, namely Wasserstein Curriculum Learning (WCL), Information Adaptive Learning (IAL), and Geodesic Curriculum Learning (GCL). Our extensive experiments on diverse medical image datasets demonstrate substantial improvements in model robustness and diagnostic accuracy over conventional training methodologies.Comment: 20 pages, 3 figures, 1 tabl

Risk Management with Derivatives by Dealers and Market Quality in Government Bond Markets

This paper examines how bond dealers use futures markets to manage the hedgeable market risk component of their core business risk exposure, and whether market quality is adversely affected by their selective risk taking activity. It also investigates the efficiency of market risk sharing within a decentralized semi-transparent market structure. We find that dealers engage in duration targeting, behaving as if they have a comparative advantage in bearing interest rate risk. They make significant directional bets often by holding futures that are in the same direction as the spot. They actively use futures to hedge changes in the spot exposure. They hedge changes in their spot exposure more when the potential costs of regulatory distress are high, when the cost of such hedging is low, and during periods of greater uncertainty. We find that duration targeting by dealers has adverse price effects due to capital constraints as predicted by Froot and Stein (1998). Finally, we find that trades in the spot market are not executed by dealers with extreme exposures. In this context, we recommend market reforms such as introduction of central quote posting or limit order book that will enable more efficient matching of liquidity demanders and suppliers, reduce trading costs, and improve the quality of risk sharing

Do Correlated Exposures Influence Intermediary Decision-making? Evidence from Trading Behavior of Equity Dealers

This paper investigates whether dealers’ trading and pricing decisions are governed by their equivalent inventories (based on total returns as in Ho and Stoll, 1983 or on unhedgeable returns as in Froot and Stein, 1998) or by their ordinary inventories, as would be the case in a decentralized market-making organizational structure. It finds that ordinary inventories, and not equivalent inventories best explain dealers’ quote placement strategy, which dealer executes trades and the quality of execution offered to the trades. This finding is consistent with decentralized market making where, due to information sharing difficulties or the nature of compensation contracts, individual dealers care only about risk of stocks managed by them, and not the positions of other dealers within the firm

Type A aortic dissection: Has surgical outcome improved with time?

ObjectiveThe study objective was to determine whether developments in surgical, anesthetic, and perfusion techniques in the treatment of type A aortic dissection have resulted in improved clinical outcome.MethodsA consecutive series of 165 patients undergoing surgical repair of type A aortic dissection performed between April of 1992 and March of 2006 in a single center were analyzed. Operations were grouped in 2 time frames of equal length (before April of 1999 vs from April of 1999 onward).ResultsThere were 30 in-hospital deaths (18.2%), and the death rate was similar in the 2 time periods. Patients who underwent operation in the recent era compared with the earlier era were older (median 62 years [interquartile range 51–68] vs 59 years [45–68], P = .18), with a significantly higher incidence of concomitant coronary artery disease (13 [18%] vs 5 [7%], P = .03]) and significantly worse (moderate to poor) left ventricular function (33 [40%] vs 13 [18%], P = .002). The duration of circulatory arrest was shorter in the recent era (median 31 minutes [interquartile range 26.5–39] vs 37.5 minutes [31–45], P = .009), with a higher incidence of concomitant procedures (19 [21%] vs 10 [14%], P = .22). Except for total hospital stay, which increased over time, there were no significant differences in postoperative outcome.ConclusionDespite the adoption of techniques to improve outcome for patients with type A dissection, mortality remains unchanged. A deteriorating risk profile and factors relating to the disease process itself may explain this observation

Trend and early outcomes in isolated surgical aortic valve replacement in the United Kingdom

ObjectiveSurgical aortic valve replacement (SAVR) is traditionally the gold-standard treatment in patients with aortic valve disease. The advancement of transcatheter aortic valve replacement (TAVR) provides an alternative treatment to patients with high surgical risks and those who had previous cardiac surgery. We aim to evaluate the trend, early clinical outcomes, and the choice of prosthesis use in isolated SAVR in the United Kingdom.MethodsAll patients (n = 79,173) who underwent elective or urgent isolated surgical aortic valve replacement (SAVR) from 1996 to 2018 were extracted from the National Adult Cardiac Surgery Audit database. Patients who underwent additional procedures and emergency or salvage SAVR were excluded from the study. Trend and clinical outcomes were investigated in the whole cohort. Patients who had previous cardiac surgery, high-risk groups (EuroSCORE II >4%), and predicted/observed mortality were evaluated. Furthermore, the use of biological prostheses in five different age groups, that are <50, 50–59, 60–69, 70–79, and >80, was investigated. Clinical outcomes between the use of mechanical and biological aortic valve prostheses in patients <65 years old were analyzed.ResultsThe number of isolated SAVR increased across the study period with an average of 4,661 cases performed annually after 2010. The in-hospital/30-day mortality rate decreased from 5.28% (1996) to 1.06% (2018), despite an increasing trend in EuroSCORE II. The number of isolated SAVR performed in octogenarians increased from 596 to 2007 (the first year when TAVR was introduced in the UK) to 872 in 2015 and then progressively decreased to 681 in 2018. Biological prosthesis usage increased across all age groups, particularly in the 60–69 group, from 24.59% (1996) to 81.87% (2018). There were no differences in short-term outcomes in patients <65 years old who received biological or mechanical prostheses.ConclusionSurgical aortic valve replacement remains an effective treatment for patients with isolated aortic valve disease with a low in-hospital/30-day mortality rate. The number of patients with high-risk and octogenarians who underwent isolated SAVR and those requiring redo surgery has reduced since 2016, likely due to the advancement in TAVR. The use of biological aortic prostheses has increased significantly in recent years in all age groups

Transcending Grids: Point Clouds and Surface Representations Powering Neurological Processing

In healthcare, accurately classifying medical images is vital, but conventional methods often hinge on medical data with a consistent grid structure, which may restrict their overall performance. Recent medical research has been focused on tweaking the architectures to attain better performance without giving due consideration to the representation of data. In this paper, we present a novel approach for transforming grid based data into its higher dimensional representations, leveraging unstructured point cloud data structures. We first generate a sparse point cloud from an image by integrating pixel color information as spatial coordinates. Next, we construct a hypersurface composed of points based on the image dimensions, with each smooth section within this hypersurface symbolizing a specific pixel location. Polygonal face construction is achieved using an adjacency tensor. Finally, a dense point cloud is generated by densely sampling the constructed hypersurface, with a focus on regions of higher detail. The effectiveness of our approach is demonstrated on a publicly accessible brain tumor dataset, achieving significant improvements over existing classification techniques. This methodology allows the extraction of intricate details from the original image, opening up new possibilities for advanced image analysis and processing tasks