Testing for explosive bubbles in the South African-US exchange rate using the sequential ADF procedures

The objective of the research carried out is to understand the impact of selected economic variables (such as Crude Oil Price, GDP, Industrial Production, Exchange Rates, and Inflation) on credit rating of Indian companies.
The sample comprises of 120 rating observations during the period 2012–2016 for a total of 24 companies of India.
Measurement of central tendency – descriptive statistics is used where credit rating is used as dependent variable and five economic factors viz. Crude Oil Price, GDP, Industrial Production, Exchange Rates, and Inflation as the independent variables.
Results from the analysis indicate that the credit rating responds in both linear, as well as nonlinear manner, to selected economic factors. Economic factors such as GDP, Industrial Production, and Exchange Rates have a linear relationship to credit rating, whereas Crude Oil price and Inflation have a non-linear impact upon the credit rating.

In this study, the RiskMetrics method is used to estimate Value at Risk for two exchange rates: BitCoin/dollar and the South African Rand/dollar. Value at Risk is used to compare the riskiness of the two currencies. This is to help South Africans and investors understand the risk they are taking by converting their savings/investments to BitCoin instead of the South African currency, the Rand. The Maximum Likelihood Estimation method is used to estimate the parameters of the models. Seven statistical error distributions, namely Normal Distribution, skewed Normal Distribution, Student’s T-Distribution, skewed Student’s T-Distribution, Generalized Error Distribution, skewed Generalized Error Distribution, and the Generalized Hyperbolic Distributions, were considered when modelling and estimating model parameters. Value at Risk estimates suggest that the BitCoin/dollar return averaging 0.035 and 0.055 per dollar invested at 95% and 99%, respectively, is riskier than the Rand/dollar return averaging 0.012 and 0.019 per dollar invested at 95% and 99%, respectively. Using the Kupiec test, RiskMetrics with Generalized Error Distribution (p > 0.07) and skewed Generalized Error Distribution (p > 0.62) gave the best fitting model in the estimation of Value at Risk for BitCoin/dollar and Rand/dollar, respectively. The RiskMetrics approach seems to perform better at higher than lower confidence levels, as evidenced by higher p-values from backtesting using the Kupiec test at 99% than at 95% levels of significance. These findings are also helpful for risk managers in estimating adequate risk-based capital requirements for the two currencies.

In the Nigerian context, there is a gap in the literature on the structural attributes of firms and the extent to which corporate investments are irreversible. Thus, this study was to empirically examine the structural attributes of firms, irreversibility, and uncertainty of corporate investment using the real options theory of investment. The study is based on annual data series of firms listed on the Nigerian Stock Exchange from 2005 to 2019. The study measured structural attributes using competitiveness and monopoly/oligopoly of a firm, macroeconomic uncertainty, inflation, interest, and exchange rates, and examines their association with corporate investments. The study was conducted using a panel dataset adopting a fixed-effect estimation technique that takes into account potential endogeneity and firm specific-effects. The result showed that the macroeconomic uncertainty measure of exchange rate volatility is strongly detrimental to corporate investment decisions. Furthermore, interest rate and inflation volatilities are not detrimental to investment growth, while exchange rate uncertainty has a substantial negative influence on corporate investment. Besides, macroeconomic uncertainty was found to be a greater disincentive for firms with irreversible investments than for firms with more easily reversible investment projects.