A Study of Credit Guarantee Fund Trust for Micro and Small Enterprises with particular reference to Bank of Baroda in state of Kerala

While the quantum of advances from the public sector banks (PSBs) to the MSEs has increased over the years in absolute terms, from Rs.46, 045 crore in March 2000 to Rs.1, 85,208 crore in March 2009, the share of the 7credit to the MSE sector in the Net Bank Credit (NBC) has declined from 12.5 per cent to 10.9 per cent. Similarly, there has been a decline in the share of micro sector as a percentage of Net Bank Credit (NBC) from 7.8 per cent in March 2000 to 4.9% in March 2009. (TKA.Nair, 2010)9.The major reasons for low availability of bank finance to this sector are high risk perception of the banks in lending to MSEs and high transaction costs in processing of loan applications of MSEs. The problem is more serious for micro enterprises requiring small loans and the first generation entrepreneursThe thesis studies the divergence in guidelines by, CGTMSE, RBI & Bank of Baroda on collateral free lending and analyses the awareness of MSE about CGTMSE lending. The researcher tries to assess the problems faced by borrowers in availing advance under CGTMSE from Bank of Baroda, Kerala.

Foreign perception of sovereign risk : an event study of the colombian armed conflict

Este paper estudia la relación entre algunos de los eventos más importantes del conflicto colombiano con la percepción extranjera de riesgo soberano, medido por los Credit Default Swaps (CDS) de los bonos del Gobierno Colombiano. Usando dos metodologías relativamente recientes, yo estimo el efecto causal de los eventos de conflicto ampliamente cubierto por los medios internacionales. En primer lugar construyo un grupo de control sintético que funciona como contra factual de la serie real de los CDS colombianos pero en ausencia de eventos de conflicto. Segundo, estimo el efecto acumulado del evento bajo la metodología de retornos anormales acumulados. Los resultados sugieren que los efectos de los eventos de conflicto sobre la percepción extranjera de riesgo soberano dependen de las especificaciones de cada evento.

Los conceptos de salud financiera, riesgo y epidemiología en los estados financieros de las compañías del sector de extracción de petróleo crudo y gas natural en Colombia

El presente proyecto tiene como objeto identificar cuáles son los conceptos de salud, enfermedad, epidemiología y riesgo aplicables a las empresas del sector de extracción de petróleo y gas natural en Colombia. Dado, el bajo nivel de predicción de los análisis financieros tradicionales y su insuficiencia, en términos de inversión y toma de decisiones a largo plazo, además de no considerar variables como el riesgo y las expectativas de futuro, surge la necesidad de abordar diferentes perspectivas y modelos integradores. Esta apreciación es pertinente dentro del sector de extracción de petróleo y gas natural, debido a la creciente inversión extranjera que ha reportado, US$2.862 millones en el 2010, cifra mayor a diez veces su valor en el año 2003. Así pues, se podrían desarrollar modelos multi-dimensional, con base en los conceptos de salud financiera, epidemiológicos y estadísticos. El termino de salud y su adopción en el sector empresarial, resulta útil y mantiene una coherencia conceptual, evidenciando una presencia de diferentes subsistemas o factores interactuantes e interconectados. Es necesario mencionar también, que un modelo multidimensional (multi-stage) debe tener en cuenta el riesgo y el análisis epidemiológico ha demostrado ser útil al momento de determinarlo e integrarlo en el sistema junto a otros conceptos, como la razón de riesgo y riesgo relativo. Esto se analizará mediante un estudio teórico-conceptual, que complementa un estudio previo, para contribuir al proyecto de finanzas corporativas de la línea de investigación en Gerencia.

Transfer of knowledge of the structural components of the model Q400 and Global Express: the case of Aerospace Bombardier, Querétaro

The aim of this paper is to analyze the knowledge transfer in the production of structural components of two aircraft:Q400 and Global Express of Bombardier Aerospace Company, Querétaro. Bombardier Aerospace is a pioneer company in the aviation sector in Mexico, and the third largest civil aircraft manufacturer. In 2005, Bombardier decided to invest in Mexico, creating Bombardier Aerospace de Mexico S. A. C. V. and transferring production lines from Japan and Toronto to Queretaro. The relocation strategy of both plants aims to reduce modular and general production costs facing other competitors. The relocation has been supported by the State Government funds, through a trust and the creation of Queretaro aerospace cluster. Among various benefits, the State of Queretaro donated seventy-eight acres of land where the Queretaro International Airport (QIA) and a training centre will be built to promote the development of this sector. The interest in this research is to analyze and describe the transfer of knowledge to the production of structural components of both aircraft models, thanks to the results of productivity and internal and external factors which have contributed along with this transfer

A Network model of systemic risk : identifying the sources of dependence across institutions

We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.

Lean construction: Arenas of enactment, models of diffusion and the meaning of 'leanness'

The existing literature on lean construction is overwhelmingly prescriptive with little recognition of the social and politicised nature of the diffusion process. The prevailing production-engineering perspective too often assumes that organizations are unitary entities where all parties strive for the common goal of 'improved performance'. An alternative perspective is developed that considers the diffusion of lean construction across contested pluralistic arenas. Different actors mobilize different storylines to suit their own localized political agendas. Multiple storylines of lean construction continuously compete for attention with other management fashions. The conceptualization and enactment of lean construction therefore differs across contexts, often taking on different manifestations from those envisaged. However, such localized enactments of lean construction are patterned and conditioned by pre-existing social and economic structures over which individual managers have limited influence. Taking a broader view, 'leanness' can be conceptualized in terms of a quest for structural flexibility involving restructuring, downsizing and outsourcing. From this perspective, the UK construction industry can be seen to have embarked upon leaner ways of working in the mid-1970s, long before the terminology of lean thinking came into vogue. Semi-structured interviews with construction sector policy-makers provide empirical support for the view that lean construction is a multifaceted concept that defies universal definition.

A review of climate risk information for adaptation and development planning

Although the use of climate scenarios for impact assessment has grown steadily since the 1990s, uptake of such information for adaptation is lagging by nearly a decade in terms of scientific output. Nonetheless, integration of climate risk information in development planning is now a priority for donor agencies because of the need to prepare for climate change impacts across different sectors and countries. This urgency stems from concerns that progress made against Millennium Development Goals (MDGs) could be threatened by anthropogenic climate change beyond 2015. Up to this time the human signal, though detectable and growing, will be a relatively small component of climate variability and change. This implies the need for a twin-track approach: on the one hand, vulnerability assessments of social and economic strategies for coping with present climate extremes and variability, and, on the other hand, development of climate forecast tools and scenarios to evaluate sector-specific, incremental changes in risk over the next few decades. This review starts by describing the climate outlook for the next couple of decades and the implications for adaptation assessments. We then review ways in which climate risk information is already being used in adaptation assessments and evaluate the strengths and weaknesses of three groups of techniques. Next we identify knowledge gaps and opportunities for improving the production and uptake of climate risk information for the 2020s. We assert that climate change scenarios can meet some, but not all, of the needs of adaptation planning. Even then, the choice of scenario technique must be matched to the intended application, taking into account local constraints of time, resources, human capacity and supporting infrastructure. We also show that much greater attention should be given to improving and critiquing models used for climate impact assessment, as standard practice. Finally, we highlight the over-arching need for the scientific community to provide more information and guidance on adapting to the risks of climate variability and change over nearer time horizons (i.e. the 2020s). Although the focus of the review is on information provision and uptake in developing regions, it is clear that many developed countries are facing the same challenges. Copyright © 2009 Royal Meteorological Society

Stress testing credit risk: the Great Depression scenario

By employing Moody’s corporate default and rating transition data spanning the last 90 years we explore how much capital banks should hold against their corporate loan portfolios to withstand historical stress scenarios. Specifically, we will focus on the worst case scenario over the observation period, the Great Depression. We find that migration risk and the length of the investment horizon are critical factors when determining bank capital needs in a crisis. We show that capital may need to rise more than three times when the horizon is increased from 1 year, as required by current and future regulation, to 3 years. Increases are still important but of a lower magnitude when migration risk is introduced in the analysis. Further, we find that the new bank capital requirements under the so-called Basel 3 agreement would enable banks to absorb Great Depression-style losses. But, such losses would dent regulatory capital considerably and far beyond the capital buffers that have been proposed to ensure that banks survive crisis periods without government support.

Predicting metal-binding site residues in low-resolution structural models

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.

Predicting protein structures and structural annotation of proteomes

Protein structure prediction methods aim to predict the structures of proteins from their amino acid sequences, utilizing various computational algorithms. Structural genome annotation is the process of attaching biological information to every protein encoded within a genome via the production of three-dimensional protein models.

Credit risk in covered bonds

Covered bonds are a promising alternative for prime mortgage securitization. In this paper, we explore risk premia in the covered bond market and particularly investigate whether and how credit risk is priced. In extant literature, yield spreads between high-quality covered bonds and government bonds are often interpreted as pure liquidity premia. In contrast, we show that although liquidity is important, it is not the exclusive risk factor. Using a hand-collected data set of cover pool information, we find that the credit quality of the cover assets is an important determinant of covered bond yield spreads. This effect is particularly strong in times of financial turmoil and has a significant influence on the issuer's refinancing cost.

Connecting mean field models of neural activity to EEG and fMRI data

Progress in functional neuroimaging of the brain increasingly relies on the integration of data from complementary imaging modalities in order to improve spatiotemporal resolution and interpretability. However, the usefulness of merely statistical combinations is limited, since neural signal sources differ between modalities and are related non-trivially. We demonstrate here that a mean field model of brain activity can simultaneously predict EEG and fMRI BOLD with proper signal generation and expression. Simulations are shown using a realistic head model based on structural MRI, which includes both dense short-range background connectivity and long-range specific connectivity between brain regions. The distribution of modeled neural masses is comparable to the spatial resolution of fMRI BOLD, and the temporal resolution of the modeled dynamics, importantly including activity conduction, matches the fastest known EEG phenomena. The creation of a cortical mean field model with anatomically sound geometry, extensive connectivity, and proper signal expression is an important first step towards the model-based integration of multimodal neuroimages.