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The purpose of this study is to determine distributional properties of the accumulated rate of interest when the instantaneous rate of interest evolves in terms of the Cox et al. (1985) square root process.

The law of iterated (or double) expectations is used to determine the mean and variance of the accumulated rate of interest on a cash management (or loan) account when interest accumulates at the instantaneous rates of interest implied by the square root process.

This study demonstrates how the accumulated rate of interest does not satisfy the strong mixing conditions necessary for convergence in distribution to the normal density function.

This study has strong educational value in determining distributional properties of the accumulated rate of interest when the instantaneous rate of interest evolves in terms of the Cox et al. (1985) square root process and demonstrating how the accumulated rate of interest does not satisfy the strong mixing conditions necessary for convergence in distribution to the normal density function.

The purpose of this study is to analyze the overnight and intraday returns of the most traded American Depositary Receipts (ADRs) of Asian companies, understand the different levels of volatilities realized in these asynchronous markets and develop trading strategies based on empirical findings.

This study presents an empirical analysis on the overnight and intraday returns of Asian ADRs. The authors propose a measure to quantify the relative contributions of the intraday and overnight returns to the ADR's total volatility. Furthermore, the return difference between S&P500 index and each ADR is fitted to an Ornstein–Uhlenbeck model via maximum-likelihood estimation.

This study finds that ADRs' overnight returns are more volatile, whereas the intraday returns are significantly more strongly correlated with the US market returns. The return spreads between the S&P500 and ADRs are found to be a mean-reverting time series and motivate a pairs trading strategy.

The methodology used in this study is not limited to Asian ADRs and can be adapted to analyze the overnight and intraday returns of other non-Asian ADRs and stocks.

Investors should be aware of the overnight price fluctuations while intraday traders may consider strategies that capture the mean-reverting return spread between an ADR (or an Exchange-Traded Funds [ETF] of Asian stocks) and the S&P500 index ETF (SPY).

ADRs are among the most popular securities for investing in foreign (non-US) companies. The total global investments in ADRs are estimated to be close to US$1tn. Understanding the risks of ADRs is important to not only individual/institutional investors but also regulators.

This study provides a new measure to quantify and compare the relative contributions of volatility by overnight and intraday returns. Optimized pairs trading strategies involving ADRs and ETFs are developed and backtested.

The main purpose of this paper is to estimate the resistance and inductor in the RL electrical circuit when these are unavailable or missing data that it is a concern in electrical engineering. The input voltage is assumed to be corrupted by the noise and the current is observed at discrete time points.

The authors propose a computationally efficient framework for parameters estimation using least square estimator and Bayesian Monte Carlo scheme.

The explicit formulas for least square estimator are derived and the strong consistency of resistance estimator is verified when inductor is a known parameter, then Bayesian estimation of parameters governed by using Markov chain Monte Carlo methods. The applicability of the results is demonstrated by using numerical examples. Several numerical results and figures are presented via Matlab and R programming to illustrate the performance of the estimators.

The paper can be used in various types of electrical engineering real time projects. The projects include electrical circuits, electrical machines theory and drives, especially when the parameters are uncertain that it is a worry in electrical engineering.

To the author's best knowledge, least square and Bayesian estimation of resistance and inductor have not been studied before. The proposed model is nonlinear with respect to inductor (L); therefore the present work has fundamental difference in comparison with the similar models.

The volatility of a financial asset is an important input for financial decision‐making in the context of asset allocation, option pricing, and risk management. The authors compare and contrast four approaches to stochastic volatility to determine which is most appropriate to each of these various needs.

The depth and breadth of the market for contingent claims, including exotic options, has expanded dramatically. Regulators have expressed concern regarding the risks of exotics to the financial system, due to the difficulty of hedging these instruments. Recent literature focuses on the difficulties in hedging exotic options, e.g., liquidity risk and other violations of the standard Black‐Scholes model. This article provides insight into hedging problems associated with exotic options: 1) hedging in discrete versus continuous time, 2) transaction costs, 3) stochastic volatility, and 4) non‐constant correlation. The author applies simulation analysis of these problems to a variety of exotics, including Asian options, barrier options, look‐back options, and quanto options.

I. INTRODUCTION A typical shortcoming of most current credit portfolio models is the lack of a stochastic modeling of risk factors, such as interest rates or credit spreads, during the revaluation process at the risk horizon. For example, fixed income instruments, such as bonds or loans, are revalued at the risk horizon using the current forward rates and (rating class specific) forward credit spreads for discounting future cash flows. Hence, the stochastic nature of the instrument's value in the future which results from changes in factors other than credit quality is ignored, and the riskiness of the credit portfolio at the risk horizon is underestimated. A further consequence is that correlations between changes of the debtor's default probability and changes of market risk factors and, hence, the exposure at default cannot be integrated into the credit portfolio model. This drawback is especially relevant for portfolios of defaultable market‐driven derivatives. One reason why risk factors not directly related to credit risk are neglected in most current credit portfolio models is that there is still no commonly accepted approach for modeling the credit quality of a debtor and the dependencies between the credit quality changes of different debtors. Hence, it might be over‐ambitious to incorporate correlations between market risk factors and credit quality changes. Even empirical evidence on the sign of the correlation remains inconclusive. Additionally, introducing stochastic market risk factors and modeling the correlation between these risk factors and credit quality changes would significantly increase the computational burden for calculating robust risk measures of credit portfolios.

The aim of this work is to explain the final negotiated prices for some of the most famous transfers of football players over the last twelve years (2007–2018).

The article analyses different values for forwards taken from the sports website Transfermarkt, developing a statistical model based on personal, performance, risk, environmental and popularity variables. From those values, the article finds an explanation for the final prices paid for 20 superstar players based on a combination of real option valuations, incorporating the players' life cycles and game theory.

The authors find that in a large percentage (70%) of the analysed cases, the price paid was higher than the intrinsic market value resulting from Transfermarkt, implying the existence of monopolistic rents, paid as “growth options” on prices from different negotiating conditions. On occasions, the final prices also exceed the value of the growth option, calculated under neutral bargaining conditions, highlighting the lack of economic viability of important transfers, leading to financial difficulties for the clubs involved.

The algorithm provides more flexibility and realism than previous proposals, based on the life cycle of football players, introducing the uncertainty and volatility of projections through Monte Carlo simulation, the capacity of clubs to bargain a price at any point of the contract and finally, the buyer's ability to transfer the player if his subsequent performance is not as expected.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.