On Pushing Multilingual Query Operators into Relational Engines

To effectively support today’s global economy, database systems need to manage data in multiple languages simultaneously. While current database systems do support the storage and management of multilingual data, they are not capable of querying across different natural languages. To address this lacuna, we have recently proposed two cross-lingual functionalities, LexEQUAL[13] and SemEQUAL[14], for matching multilingual names and concepts, respectively. In this paper, we investigate the native implementation of these multilingual functionalities as first-class operators on relational engines. Specifically, we propose a new multilingual storage datatype, and an associated algebra of the multilingual operators on this datatype. These components have been successfully implemented in the PostgreSQL database system, including integration of the algebra with the query optimizer and inclusion of a metric index in the access layer. Our experiments demonstrate that the performance of the native implementation is up to two orders-of-magnitude faster than the corresponding outsidethe- server implementation. Further, these multilingual additions do not adversely impact the existing functionality and performance. To the best of our knowledge, our prototype represents the first practical implementation of a crosslingual database query engine.

Pricing credit derivatives

The financial crisis set off by the default of Lehman Brothers in 2008 leading to disastrous consequences for the global economy has focused attention on regulation and pricing issues related to credit derivatives. Credit risk refers to the potential losses that can arise due to the changes in the credit quality of financial instruments. These changes could be due to changes in the ratings, market price (spread) or default on contractual obligations. Credit derivatives are financial instruments designed to mitigate the adverse impact that may arise due to credit risks. However, they also allow the investors to take up purely speculative positions. In this article we provide a succinct introduction to the notions of credit risk, the credit derivatives market and describe some of the important credit derivative products. There are two approaches to pricing credit derivatives, namely the structural and the reduced form or intensity-based models. A crucial aspect of the modelling that we touch upon briefly in this article is the problem of calibration of these models. We hope to convey through this article the challenges that are inherent in credit risk modelling, the elegant mathematics and concepts that underlie some of the models and the importance of understanding the limitations of the models.

Optimal allocation of carbon credits to emitting agents in a carbon economy

Reduction of carbon emissions is of paramount importance in the context of global warming. Countries and global companies are now engaged in understanding systematic ways of achieving well defined emission targets. In fact, carbon credits have become significant and strategic instruments of finance for countries and global companies. In this paper, we formulate and suggest a solution to the carbon allocation problem, which involves determining a cost minimizing allocation of carbon credits among different emitting agents. We address this challenge in the context of a global company which is faced with the challenge of determining an allocation of carbon credit caps among its divisions in a cost effective way. The problem is formulated as a reverse auction problem where the company plays the role of a buyer or carbon planning authority and the different divisions within the company are the emitting agents that specify cost curves for carbon credit reductions. Two natural variants of the problem: (a) with unlimited budget and (b) with limited budget are considered. Suitable assumptions are made on the cost curves and in each of the two cases we show that the resulting problem formulation is a knapsack problem that can be solved optimally using a greedy heuristic. The solution of the allocation problem provides critical decision support to global companies engaged seriously in green programs.