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A Real Estate Investment Trust (REIT) is a fund or trust that owns and manages commercial real estate and generates revenue. After two years of the COVID-19 pandemic, the whole REITs sector suffered from lockdown, diminishing revenue from office and shopping mall rentals. Hence, investors may lose more than expected on invested capital without further analysing this situation. This highlights the importance of investors knowing the risk of investing in REITs to plan their investment strategies appropriately. The Value at Risk (VaR) is widely employed to calculate the investment risk under a mathematical model to achieve this. A past review suggested that two approaches had been utilised for modelling, i.e., parametric and non-parametric methods. The methods under non-parametric include historical simulation, Monte Carlo simulation, and bootstrapping simulation. Thus, comparing parametric methods, historical simulation, Monte Carlo simulation, and bootstrapping simulation is essential in determining the best method to analyse the VaR in the Malaysia REITs (M-REITs) sector, which particularly focuses on Malaysia. Actual previous five-year history raw price data for each REIT in Malaysia are extracted from Yahoo Finance, Refinitiv Eikon, and DataStream via University Utara Malaysia’s (UUM) e-resources database. The result of VaR from those methods is compared and validated using backtesting. Other than that, the result reveals that the parametric method and Monte Carlo simulation are good methods for REIT’s VaR calculations in Malaysia, which are close to the current value for 12 from 17 M-REITs companies.

In moving towards Industrial Revolution 4.0, healthcare and medicine are one of the biggest areas of concern which is beneficial to maintaining healthy living. This study seeks to identify the potential problems and risks related to high-technology medical approaches, namely the da Vinci robotic surgical systems, specifically used for thyroidectomy surgery. In particular, the risks embedded in robotic surgeries in terms of health and economy are investigated. Furthermore, a probabilistic risk analysis was conducted to assess the risk among surgeons of the da Vinci robotic surgery using event tree analysis and Bayesian network. This research revealed that the probability of success for surgeons without prior robotic surgery experience was 0.10. It highlights the importance of proper training for medical practitioners in handling advanced medical equipment by considering the related risk involved in patients

This study aims to further analyze the factors that contribute to the adoption of Financial Technology (FINTECH) among Malaysians during the COVID-19 pandemic. Financial institutions all over the world have been grappling with the consequences of the COVID-19 pandemic and striving to understand the immediate challenges to society, economies, and the long-term implications on the interconnected financial system during this time of crisis. As a result, this study will provide light on society's desire to adopt FINTECH in the face of the epidemic. A total of 402 surveys were distributed and gathered from FINTECH users between the ages of 18 and 60. SPSS was then used to examine the data. Consumers' intentions to use e-wallets during the COVID-19 pandemic are heavily influenced by performance expectations, effort expectations, social influence, and government support, as per the research findings. During the COVID-19 epidemic in Malaysia, researchers discovered that trust variants had no impact on customers' willingness to use e-wallets.

Previous studies revealed that most local researchers frequently used the Black Scholes model to price equity warrants. However, the Black Scholes model was perceived of possessing too many drawbacks, such as big errors of estimation and mispricing of equity warrants. In this work, we consider the problem of pricing hybrid equity warrants based on a hybrid model of stochastic volatility and stochastic interest rate. The integration of stochastic interest rate using the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility of the Heston model was first developed as a hybrid model. We solved the governing stochastic equations and come up with analytical pricing formulas for hybrid equity warrants. This provides an alternative method for valuation of equity warrants, compared to the usual practice of utilizing the Black Scholes pricing formula.

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

Prior literature's revealed that most researchers tend to employ the Black Scholes model to price equity warrants. However, the Black Scholes model was found deficient by contributing to large estimation errors and mispricing of equity warrants. Therefore( issues revolving equity warrants are discussed in this paper, by focusing on specific topics and respective stochastic models to provide a basis for improvements in future research. In recent years, stochastic approaches had been used to a great extent among researchers due to the expansive applications in both theoretical and practical sense. Subsequently, this paper provides the results of a comprehensive literature review on various stochastic modelling methods and its applications for pricing financial derivatives in terms of applications, modifications of methods, comparisons with other methods, and general related researches. Focus is given on two types of stochastic mod~ls namely stochastic volatility and stochastic interest rate models; along with the discussions associating these two types of models. This paper acts as a valuable source of information for academic researchers and practitioners not only for pricing financial instruments, but also in various other fields involving stochastic techniques.

—A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Variance swaps have gained an immense recognition in the financial market based on the tremendous spike in its trading volume since late 1990s. Being categorized under volatility derivatives, the substance of variance swaps can be related to the vital role of volatility in making investment decisions. In this paper, the price of discretely-sampled forward-start variance swaps is evaluated using an equity-interest rate hybrid model. The modeling framework involves an extension of the Heston stochastic volatility model, which is combined with the dynamics of the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. Focus is given on the forward-start nature, identified by the starting time of the sampling period being a future date. Previous studies on variance swaps were mainly focusing on instantaneous-start variance swaps, whereas in reality, most of traded variance swaps

The problem of pricing discretely-sampled variance swaps under stochastic volatility, stochastic interest rate and regimeswitchin" e is beine considered in this oaoer. An extension of the Heston stochastic volatiliw model structure is done bv adding the - . . . Cox-lngersoll-Row (CIR) ctochawc intereel rare modcl In add~uon[,h e parameme of the mndel are perm~rtedlo have uan.uvcrable lh~shb bnd model cdn be uced lo tllusunre ccrrlrn macmec~nomicc onditions.-for example the changing phases of business stages. The outcome of our regime-switching hybrid model is presented in lerms of analytical pricing formulas for variance swaps.

Recently, market players have been exposed to the astounding increase in the trading volume of variance swaps. In this paper, the forward-start nature of a variance swap is king inspected. where hybridizations or equity and interest rate models are used to evaluate the price of discretely-sampled forward-start variance swaps . The Hc~ton~ tmhasticv olatiliry model 1s being extended to incorporate the dynamic5 of the Cox-Tngersoll-Ross (CIR)s tochast~cln teresr rate model. This is essential since previous studies on variance swaps were mainly focusing on instantaneous-start variance swaps without considering the interest rate effects. This hybrid mcdc! pmduccp an cfficicnt scmi-closcd form pricing Formula through the dcvclopmen~ of tijnvnrd characteristic functions. The performance of this formula is investigated via simulations to demonstrate how the formula performs for different sampling times and again the real market scenario. Comparison done with the Monte Car1o simulation which was set as our main reference point reveals that our pricing formula gains almost the same precision in a shorter execution time.

In this paper, we evaluate the price of discretely-sampled variance swaps using a equity-interest rate hybrid model. Our modeling framework extends the Heston stochastic volatility model by including the Cox-Ingersoll-Ross stochastic interest rates and imposes correlation between the stochastic interest rate and volatility. It is known that one limitation of the hybrid models is that the analytical pricing formula is often unavailable due to the non-affinity property of hybrid models. An efficient semi-closed form pricing formula is derived for an approximation of the fully correlated hybrid model. Our pricing formula which involves solving two phases of three-dimensional partial differential equations is evaluated through numerical implementations to confirm its accuracy