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In this research, arbitrage opportunity is tested between the yield rates computed by the NSS model, and the computed forward rates between conventional and Islamic finance to see any arbitrage opportunity. The research questions are the conventional and Islamic finance yields at the same level and equal to each other to avoid arbitrage? Whether conventional and Islamic forward rates differ significantly and thus create any arbitrage opportunity. This study aims to find the presence or absence of arbitrage between conventional and Islamic finance yield rates.

The NSS model is the latest model in calculating yield and forward rates. In the method the error level is minimized so expected yield rate and given yield rate both converged (Vahidin and Anastasios, 2020). When they converged it gives the researchers all six months’ yield rates. For the Nelson Siegal method, all the six months’ yield rates are available and these yield rates can be used to compute the forward rates.

The authors concluded there is a significant difference between the conventional yield rate and the Islamic yield rate. It suggests that because there are significant differences, its suggest arbitrage is possible. So anyone interested in making a guaranteed profit. The conventional yield rates are lower; hence, anyone can borrow from the conventional finance system and invest the money in the Islamic financial system because investments are getting higher rates of income in the form of yield rate in Islamic Finance. So, one can make money because of this difference. Statistically, it is possible to make money, but practically, the authors observed the difference, however it is very meager. The arbitrage opportunity between Islamic finance and conventional finance will not affect the economy because the significant difference is too small. The disturbance in the arbitrage opportunity due to the values is very meager and insignificant.

This research does not address the derivative contracts’ role in risk management; future researchers could take up this as another research.

This research will be beneficial for financial institutions, especially institutional investors. Besides, this research will help the regulators and investment bankers in assisting where and future losses especially bond portfolios in conventional finance and Islamic finance. This study will also contribute and help the asset manager of mutual funds in the mutual fund industries.

In effect, this research will strengthen the financial system, capital market and bond market, derivative contracts such as options contracts, futures contracts, swap contracts and forward contracts will use computed forward rates for assessing future losses (value at risk [VaR]) and to hedge them (Balakrishnan, 2020).

As this topic is rarely studied it will increase the literature present in this domain.

This paper investigates the relationship between climate finance and climate ergodicity. More specifically the paper examines how climate ergodicity as measured by a mean-reverting Ornstein–Uhlenbeck process affects the value of climate-linked bonds.

Bond valuation is evaluated using Monte Carlo methods of the Ornstein–Uhlenbeck process. The paper describes climate risk in terms of the Hurst coefficient and derives a direct linkage between the Ornstein–Uhlenbeck process and the Hurst measure.

We use the Ornstein–Uhlenbeck mean reversion relationship in its OLS form to estimate Hurst coefficients for 5 × 5° grids across the US for monthly temperature and precipitation. We find that the ergodic property holds with Hurst coefficients between 0.025 and 0.01 which implies increases in climate standard deviation in the range of 25%–50%.

The approach provides a means to stress-test the bond prices to uncover the probability distribution about the issue value of bonds. The methods can be used to price or stress-test bonds issued by firms in climate sensitive industries. This will be of particular interest to the Farm Credit System and the Farm Credit Funding Corporation with agricultural loan portfolios subject to spatial climate risks.

This paper examines bond issues under conditions of rising climate risks using Hurst coefficients derived from an Ornstein–Uhlenbeck process.

This paper offers a bibliometric analysis of the scientific literature on social finance. It provides an overview of the research field by identifying gaps in the existing academic literature and presenting future research directions.

The study uses co-word analysis and visualization mapping techniques.

This study's findings show that the social finance research field comprises five main research clusters and four main research hotspots—impact investing, social entrepreneurship, social impact bonds, and social innovation—which represent the core of this research domain. The authors also identify the researchers and the research institutions that have contributed to the development of social finance. In addition, emerging research areas are mapped and discussed.

Compared with most previous literature reviews, this work provides a more complete and objective analysis of the entire social finance landscape by revealing the trends and evolving dynamics that characterize its development. To this end, clear terminological boundaries have not yet been established in social finance. The field appears immature because only a few researchers have contributed to it, and papers have yet to be published by top finance journals. Finally, the findings of this research provide directions for future studies.