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This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios.

The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metrics.

The paper finds cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) and Litecoin (LTC), and the corresponding trading strategies are shown to be profitable under different configurations.

The main contributions of the study are the use of multiple altcoins in addition to bitcoin to construct a cointegrated portfolio, and the detailed comparison of the performance of different trading strategies with and without stop-loss constraints.

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 purpose of this study is to understand the tracking errors of leveraged exchange-traded funds (LETFs) on gold and demonstrate improved tracking performance by dynamic portfolios of gold futures.

The author formulates and solves a constrained quadratic minimization problem to construct static replicating portfolios of both leveraged and unleveraged benchmarks in gold; a dynamic constant leveraged portfolio using gold futures is used to track the path of the leveraged gold benchmark.

The results suggest that market-traded LETFs do not track a leveraged position in gold effectively over a long horizon, and the dynamic leveraged futures portfolio achieves lower tracking errors over multiple years.

The research informs us that investors should consider alternative portfolios with gold futures, rather than holding a leveraged gold exchange-traded funds to achieve a desired leveraged exposure in spot gold.

The main contribution of the study is the use of gold futures to dynamically replicate a gold benchmark with any given leverage ratio and the detailed comparison of the tracking performance of LETFs versus optimal static and dynamic futures portfolios.

We discuss the valuation of credit derivatives in extreme regimes such as when the time-to-maturity is short, or when payoff is contingent upon a large number of defaults, as with senior tranches of collateralized debt obligations. In these cases, risk aversion may play an important role, especially when there is little liquidity, and utility-indifference valuation may apply. Specifically, we analyze how short-term yield spreads from defaultable bonds in a structural model may be raised due to investor risk aversion.

This paper aims to explore the theory of technology adoption using a system‐application approach to facilitate PMA innovation span across multiple organisations to enhance overall production network effectiveness.

The survey on technology available and forecast future trends, design a workable prototype for test in real‐world airline operation under a three‐layer analysis model. Data is taken to validate the concept and correlate performance factors in PMA adoption.

The findings highlight greater operational efficiency and higher process value maintenance to be achieved through communication paths. The value process‐to‐shop concept is validated, next to value network.

This research supports maintenance business, especially with high contents of information and knowledge driven tasks for outsource service providers, can make use of the wireless system adoption rules for assets and maintenance performance management.

The paper presents organisations with a tool such that portable maintenance device can be identified as contribution in different levels, focus and functional effects. Within a critical process, airlines can better manage their dynamic operation process for higher revenue generation.

A regression kink design (RKD or RK design) can be used to identify casual effects in settings where the regressor of interest is a kinked function of an assignment variable. In this chapter, we apply an RKD approach to study the effect of unemployment benefits on the duration of joblessness in Austria, and discuss implementation issues that may arise in similar settings, including the use of bandwidth selection algorithms and bias-correction procedures. Although recent developments in nonparametric estimation (Calonico, Cattaneo, & Farrell, 2014; Imbens & Kalyanaraman, 2012) are sometimes interpreted by practitioners as pointing to a default estimation procedure, we show that in any given application different procedures may perform better or worse. In particular, Monte Carlo simulations based on data-generating processes that closely resemble the data from our application show that some asymptotically dominant procedures may actually perform worse than “sub-optimal” alternatives in a given empirical application.

The main theme of this volume is credit risk and credit derivatives. Recent developments in financial markets show that appropriate modeling and quantification of credit risk is fundamental in the context of modern complex structured financial products. Moreover, there is a need for further developments in our understanding of this important area. In particular modeling defaults and their correlation has been a real challenge in recent years, and still is. This problem is even more relevant after the so-called subprime crisis that hit in the summer of 2007. This makes the volume very timely and hopefully useful for researchers in the area of credit risk and credit derivatives.

The purpose of this paper is to investigate the relationship between gender and the individual and social aspects of expatriate work, emphasising how issues external to the organisation impact on the experience of female expatriates.

In total, 102 male respondents and 44 female respondents were surveyed in order to test the perceived organisational support, career satisfaction, and expatriate social support.

Significant gender‐related differences were identified in all three areas with notable contradiction in the perception and practice of how multinational corporations (MNCs) manage their expatriates. While earlier research suggested that organisations perceived their treatment of female expatriates to be equivalent to that of men, the results indicate that female international managers do not perceive equal treatment on international assignments.

Although based on a smaller sample than other international studies, the gender breakdown was sufficient for moderated regression testing.

As the expatriate social support construct is largely exploratory in nature, future research could examine the effect of perceived expatriate social support on other related workplace behaviours, both domestically and internationally, including work‐life balance and diversity management.

While other studies have provided a rich descriptive picture of the gendered nature of expatriation, little research has attempted to quantify the reasons behind the phenomenon. This paper addresses this gap in the literature through exploration of the issues, which impact upon the experience of female expatriates in foreign MNCs in China.

In parallel with the rising importance of innovation and digital technologies, research on platform ecosystems is rapidly accumulating. This study aims to summarize the current research published in leading technical and innovation management (TIM) journals and provide recommendation for future research.

In this paper, the authors combine multiple quantitative literature review methods (social network analysis, citation analysis and co-citation analysis) with a systematic literature review of articles published in the 13 most influential TIM journals over a 15-year period.

The citation network of 168 selected papers is sparse, with low network density indicating the emerging nature of the field. Using network centrality values, the authors identified the 33 most influential articles. The review of methodologies in these articles found that conceptual and case study research dominate, suggesting the need for additional confirmatory and quantitative analysis. Co-citation analysis of the references identified six research clusters: foundation, network-centric innovation, complementor management, platform competition, ecosystemsand product platforms.

This analysis is among the first to examine the knowledge structure of platform ecosystem research in the TIM domain by using multiple evidence-based analysis methods. The authors also apply the theory, context, characteristics and methodology framework to suggest areas for future research.