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This study attempts to examine the time-varying volatility spillovers between environmentally sustainable assets and quantify the value-at-risk of the portfolios across various frequencies.

To accomplish these objectives, this paper utilizes a connectedness index-based TVP-VAR model and applies the wavelet-based VaR ratio to daily data spanning from January 2018 to September 2023.

The empirical findings reveal a notable increase in the connectedness index between green stocks and green bonds during the COVID-19 crisis, signifying evidence of a contagion effect. The portfolio’s risk ratio also exhibited a sharp rise amid the pandemic, particularly over medium and long-term horizons, driven by increased spillover among green assets. Notably, our analysis indicates that green bonds influence the connectedness system between green stocks and the value-at-risk ratio, reducing volatility spillover and portfolio risk ratios across various investment horizons. These results highlight the role of green bonds as an effective diversification asset against the risks associated with green equities.

This research investigates the dynamic connectedness and value-at-risk ratio between eight green sectoral renewable energy and non-energy equities and green bonds. We put forward some portfolio implications for green investors with an environmental consciousness who desire to decarbonize their portfolios and mitigate environmental issues.

This chapter tries to hedge extreme financial risk of entrepreneurs who work with wheat by combining wheat with four stock indices of developed and emerging European markets in a portfolio. Extreme risk of the portfolios is measured by the parametric and historical value-at-risk (VaR) metrics. Portfolios that target maximum return-to-VaR ratio are also constructed because different market participants prefer different goals. Preliminary equicorrelation results indicate that integration between wheat and emerging markets is lower (0.218) vis-á-vis the combination of wheat and developed markets (0.307), which gives preliminary advantage to emerging markets in diversification efforts. The results show that portfolios with emerging stock indices have significantly lower parametric (–0.816) and historical (–0.831) VaR than portfolios with developed indices, –1.080 and –1.295, respectively. As for optimal portfolios, the portfolios with developed indices have a slight upper hand. This chapter shows that parametric VaR is not a good measure of extreme risk, because it neglects the third and fourth moments.

This paper examines the impact of macroeconomic volatility on stock volatility, both under normal conditions and during the COVID-19 pandemic in Vietnam.

We extend the existing Exponential Generalized Autoregressive Conditional Heteroskedasticity model by adding a new component: the thresholds – the levels of macroeconomic volatility at which the market may respond differently. These thresholds are estimated for both positive and negative volatility.

The impact of macroeconomic volatility on stock volatility is asymmetric: there are thresholds of macroeconomic volatility at which its pattern changes. These thresholds are higher in the case of positive volatility compared with negative volatility. The thresholds were also higher during the COVID-19 pandemic. Macroeconomic variables influence stock volatility differently depending on market conditions. While GDP is more significant in normal periods, interest rates affect it in both normal and unstable phases.

Our models consider only two variables representing macroeconomic variables: interest rate and GDP. Furthermore, only one lag period of the variables is included in the analysis. In the future, more macrovariables and longer lags could be included when computational techniques advance.

Policymakers should consider the impact of macroeconomic volatility on the stock market when designing policies, especially at thresholds. Similarly, investors should pay more attention to macroeconomic volatility when constructing and managing their portfolios, particularly when such volatility is close to thresholds.

The inclusion of thresholds as parameters to be estimated into the model provides more insights into the impact of macroeconomic variables on stock volatility.

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 study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

We propose an alternative rationale for why some firms employ veterans, driven not solely by benevolence but also by the prospect of enhanced outcomes. Financially, hiring veterans could correlate with improved stock market performance for the hiring company while aligning with corporate social responsibility (CSR) initiatives. Our study centers on the stock market performance of companies hiring veterans. It aims to underscore a lesser-known facet of the veteran employment discourse and its connection to the hiring firm's financial performance.

This paper evaluates the stock market performance of three VETS portfolios (made of companies that hire veterans) compared to the benchmark SPDR S&P 500 ETF. Using a modular approach, we create three VETS passive indices: VETSEW (equal-weighted index), VETSPW (price-weighted index) and VETSVW (value-weighted index). The study analyzes the annual returns, portfolio allocations, risk-adjusted performance metrics and style analysis of the portfolios from January 1, 2020, to December 31, 2022.

The findings indicate that all three VETS portfolios outperformed the benchmark, with higher ending balances and superior risk-adjusted ratios such as the Sharpe and Sortino ratios. Notably, the portfolios demonstrated resilience during challenging periods, including the COVID-19 pandemic, subsequent recovery and an inflationary period.

Limitations include the paper's focus solely on stock returns, suggesting a need for broader financial and management ratios. Moreover, a deeper exploration into how veterans contribute during turbulent times is suggested for further investigation. Although the study touches upon the financial performance of veteran-focused companies during challenging economic times, it does not extensively delve into the specific ways in which veterans add value under such circumstances, presenting an opportunity for further exploration.

Firms that employ veterans amid the COVID-19 pandemic demonstrate favorable risk-adjusted returns, underscoring the potential of veterans as valuable crisis-time assets. Our research further underscores the correlation between veteran hiring and enhanced financial prowess. These insights carry significant policy implications, including CSR initiatives for hiring veterans, skill translation and training and collaboration with veteran organizations.

The paper's findings suggest significant implications: (1) Policymakers could incentivize firms to hire veterans through tax benefits or grants, leveraging their skills for organizational resilience. (2) Collaborative efforts between policymakers and firms can promote responsible hiring, boosting a company's reputation through diversity and inclusion, positively impacting society. (3) Support for skill translation from military to civilian jobs is crucial. Programs certifying skills and tailored education aid veterans' successful transition into the workforce. (4) Collaborations between policymakers, veteran organizations and private sector entities can create networks, job placements and support systems for veterans' employment.

Numerous prior studies within the domain of corporate social responsibility have predominantly neglected the contributions veterans offer to businesses and the underlying reasons behind firms' decisions to employ them. Our research uniquely concentrates on the stock market performance of companies that choose to hire veterans.

This study aims to examine information (stock return, volatility and extreme risk) spillovers and interconnectedness within dual-banking systems.

Using multilayer information spillover networks, this paper conduct a deep analysis of contagion dynamics among 24 Islamic and 46 conventional banks from 2006 to 2022.

The findings show the network’s rapid response to financial shocks. Through cross-sector analysis, this paper identify information spillovers between and within Islamic and conventional banking systems. Furthermore, this research illustrates distinct roles played by Islamic and conventional banks within the multilayer network structure, contingent upon the nature of the financial shock.

Understanding the differential roles of Islamic and conventional banks in information transmission can aid policymakers and financial institutions in devising more effective risk management strategies, thereby enhancing financial stability within dual-banking systems.

This study contributes to the literature by emphasizing the necessity of examining contagion mechanisms beyond traditional single-layer network structures, shedding light on the shadow dynamics of information transmission in dual-banking systems.

The purpose of this study is to evaluate whether the classification of the equity mutual fund depends on the performance measure used.

The sample for this study includes stock mutual funds for the USA, Europe and emerging market economies covering the period 2010 to 2020. Using more than 20 performance measures the results are compared using the Sharpe ratio as the reference.

The results show that performance measures based on absolute reward–risk ratios like Sortino, Treynor, etc. have similar rankings, because in general the numerator (mean excess return) is the same. However, when the authors employ other types of performance measures, results may be significantly different, especially in the case of metrics for “incremental returns”, i.e. alphas. Focussing on markets, their results show that choosing performance measures is more relevant for emerging markets.

The sample is only limited to the USA, Europe and the emerging market, and there are other performance metrics in the literature which have not been covered in this work.

The ordering of equity mutual funds depends on the measure used, specially if investors employ factor models to measure excess returns (alphas). Hence, policy formulation on disclosure of mutual fund performance should encourage the use of several metrics from different families. Investors must be aware of the different rankings made and the most appropriate metrics based on their preferences.

This paper focusses specifically on the effect that performance metrics have on relative fund performance. Previous studies have ignored alpha metrics to rank funds, which are commonly employed by investors. The authors’ study performs an analysis for three different markets considering the two main developed ones (the American and European equity markets), as well as the emerging one, largely ignored until now.

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.

The purpose of this paper is to test the invulnerability of the guarantee network at the equilibrium point.

This paper introduces a tractable guarantee network model that captures the invulnerability of the network in terms of cascade-based attack. Furthermore, the equilibrium points are introduced for banks to determine loan origination.

The proposed approach not only develops equilibrium analysis as an extended perspective in the guarantee network, but also applies cascading failure method to construct the guarantee network. The equilibrium points are examined by simulating experiment. The invulnerability of the guarantee network is quantified by the survival of firms in the simulating progress.

There is less study in equilibrium analysis of the guarantee network. Additionally, cascading failure model is expressed in the presented approach. Moreover, agent-based model can be extended in generating the guarantee network in the future study.

The approach of this paper presents a framework to analyze the equilibrium of the guarantee network. For this, the systemic risk of the whole guarantee network and each node's contribution are measured to predict the probability of default on cascading failure. Focusing on cascade failure process based on equilibrium point, the invulnerability of the guarantee network can be quantified.