Risk transfer in project finance loans for toll road using credit default swaps

Purpose The purpose of this paper is to demonstrate the applicability of the Credit Default Swaps (CDS), as a financial instrument, for transferring of risk in project finance loans. Also, an equation has been derived for pricing of CDS spreads. Design/methodology/approach The debt service cover ratio (DSCR) is modeled as a Brownian Motion (BM) with a power-law model fitted to the mean and half-variance of the existing data set of DSCRs. The survival probability of DSCR is calculated during the operational phase of the project finance deal, using a closed-form analytical method, and the results are verified by Monte Carlo simulation (MCS). Findings It is found that using the power-law model yields higher CDS premiums. This in turn confirms the necessity of conducting rigorous statistical analysis in fitting the best performing model as uninformed reliance on constant time-invariant drift and diffusion model can erroneously result in smaller CDS spreads. A sensitivity analysis also shows that the results are very sensitive to the recovery rate and cost of debt values. Originality/value Insufficiency of free cash flow is a major risk in the toll road project finance and hence there is a need to develop innovative financial instruments for risk management. In this paper, a novel valuation method of CDS is proposed assuming that DSCR follows the BM stochastic process.

Consumers’ Perception of The Cost of Credit Default in The Vehicle Finance Industry in South Africa

The risk that a borrower may not fulfil his/her borrowing obligation presents credit owner (lender) a default risk management opportunity to maximize the risk-adjusted rate of return and to maintain minimum exposure to default associated cost. This paper investigated respondents’ perception of the cost of credit default and examines requirements for default risk management (DRM) in the vehicle finance industry in South Africa. It is noted that with an increased level of consumer indebtedness, unstable economy, high unemployment, opportunistic risks like health pandemics, vehicle financing faces a higher probability of default from borrowers. This descriptive investigation utilised quantitative approach using a survey method to collect data from 381 purposive randomly selected respondents who are vehicle finance customers in South Africa, Cape Town specifically. Data collection took place in the Western Cape over a nine-month period, utilising personal interview, and emails to administer questionnaires to vehicle finances’ customers as data collection instruments. Responses received were codified and quantitative data were analysed using the Statistical Packages for Social Sciences (SPSS version 25) The paper found mixed and variable respondents’ perception of the cost of credit default. In conclusion, it is perceived that South Africa debt would become more costly with credit default. It can be recommended that a default risk management intervention be applied to manage credit default risk within the context of the unified credit assessment policy in South Africa.

Determinants of Russia’s Sovereign Risk

This paper presents an empirical analysis of the determinants of Russia’s sovereign risk. The spreads on sovereign Russian credit default swaps (CDS) were used as a measure of risk. Based on the accuracy of out-of-sample forecasts, the factors that influence Russian CDS were selected: the implied volatility of the rouble exchange rate, the size of foreign exchange reserves relative to GDP, and the average spread on other emerging market CDS as a proxy for global factors. In turn, the CDS of emerging market countries are determined by the volatility of their currencies, the slope of the US government bond curve, and also by the increments of the dollar index.