Modeling the Repayment Capacity of Mauritian Firms: In Quest of a Credit Risk Model

-- Indranarain Ramlall

This paper proposes an innovative approach for bankers by assessing the impact of the attributes of corporate firms on their repayment capacity in the case of Mauritian firms. Results show that profitability and leverage constitute the underlying forces that influence the Debt Service Coverage Ratio (DSCR) and the Interest Coverage Ratio (ICR). Findings further suggest the need for specificity of leverage analysis since Mauritian firms prefer short-term financing strategies relative to long-term financing. Besides, it also transpires that local companies heavily cling to leases. Long-term loan, Cash Conversion Cycle (CCC), size, growth, liquidity, age, investment, and the presence of foreign currency risk are not found to influence the repayment capacity of Mauritian firms. From the perspective of financial stability, the findings suggest that policy should be mainly geared toward import-substitution strategies so that local firms are able to maintain a sound debt servicing capacity with a view to alleviate the negative effects of the worst financial crisis, the US subprime crisis, since the Great Depression.

© 2010 IUP. All Rights Reserved.

The FX Smile

-- Daniel Bloch

The study considers a stochastic local volatility model with domestic and foreign stochastic interest rates and identifies a bias with respect to the deterministic local volatility with deterministic rates. Relating the local volatility of the model to that of the forward price, the study quantifies the bias by equating the variance swap contract under the risk-neutral measure with that under the forward probability measure. Assuming a collapse process for the variance with the same random variable for all time and deterministic zero-coupon bond volatility functions, the bias term simplifies and can easily be computed. A simple implementation of the model is also described. In the discretized dynamics, the local volatility function being piecewise constant, the bootstrapping technique is applied to calculate its value by solving a quadratic equation at each maturity and strike. As a result, a fast and robust way of calibrating a stochastic local volatility model with stochastic rates to market prices is obtained.

© 2010 IUP. All Rights Reserved.

Risk Analysis of Infrastructure Projects: A Case Study on Build-Operate-Transfer Projects in India

-- Hiren Maniar

The growth of the infrastructure sector in India has been relatively slow compared to that of the industrial and manufacturing sectors. Energy shortage, inadequate transportation network, and insufficient water supply system have caused a bottleneck in the country's economic growth. The Build-Operate-Transfer (BOT) scheme is now becoming one of the prevailing ways for infrastructure development in India to meet the needs of India's future economic growth and development. There are tremendous opportunities for foreign investors in this field. However, undertaking infrastructure business in India involves many risks and problems that are mainly due to differences in legal systems, market conditions and culture. It is crucial for foreign investors to identify and manage the critical risks associated with investments in India's BOT infrastructure projects. The main purpose of this paper is to investigate the critical risks associated with BOT projects in India. Based on a survey, the following critical risks, in descending order of criticality, are identified: delay in approval, change in law, cost overrun, dispatch constraint, land acquisition and compensation, enforceability of contracts, construction schedule, financial closing, tariff adjustment and environmental risk. The measures for mitigating each of these risks are also discussed. Finally, a risk management framework for India's BOT infrastructure projects is developed.

© 2010 IUP. All Rights Reserved.

Do Company-Specific Factors Influence the Extent of Usage of Risk Analysis Techniques in Strategic Investment Decisions?

-- Kannadhasan M and Nandagopal R

This study empirically examines the extent of usage of risk analysis approaches and techniques and the influence of company-specific factors on the extent of usage of risk analysis approaches and techniques in Strategic Investment Decisions (SIDs). Based on the responses obtained through a single cross-sectional mailed survey, from 36 senior finance professionals representing 36 automotive companies operating in India, this study gives four important conclusions. First, the respondent companies are using formal risk analysis techniques equally to the subjective/intuitive risk assessment techniques. Second, the selected firm-specific characteristics do not have a significant relationship with the overall scope of risk analysis in SIDs. Third, sensitivity analysis is the most preferred formal risk measurement technique used by the respondents, followed by probability distribution. Finally, shortening payback period is the most preferred formal risk adjustment method used by the respondents, followed by raising the discount rate.

© 2010 IUP. All Rights Reserved.

Estimating LGD Correlation

-- Jiøí Witzany

The paper proposes a new method to estimate correlation of account-level Basel II Loss Given Default (LGD). The correlation determines the probability distribution of portfolio level LGD in the context of a copula model which is used to stress the LGD parameter as well as to estimate the LGD discount rate and other parameters. Given historical LGD observations, the maximum likelihood method is applied to estimate the best correlation parameter. The method is applied and analyzed on a real large dataset of unsecured retail account-level LGDs and the corresponding monthly series of the average LGDs. The correlation estimate obtained is relatively close to the PD regulatory correlation. It is also tested for stability using the bootstrapping method and used in an efficient formula to estimate the ex ante one-year stressed LGD, i.e., one-year LGD quantiles on any reasonable probability level.

© 2010 IUP. All Rights Reserved.