Complex Network of Aviation E-Services in the Belt and Road Initiative: A Heuristic Study of Small Data based on Block Modeling

ABSTRACT

The aviation e-service system is an important part of support for business communication in regions covered by Belt and Road initiative. In exploring the role of airline companies in this system, we examine the structure of the network, which consists of airlines interconnections based on small data of individual attributes of aviation companies in aviation e-services, and study these interconnections across different groups using block modeling. The heuristic solution of airline companies in development of international communication and cooperation is further discussed. Among our policy implications for global managers, we suggest the enhancement of cross-regional cooperation among airlines.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Addressing the sustainable development through sustainable procurement: What factors resist the implementation of sustainable procurement in Pakistan?

Sustainable Public Procurement is an integral part of sustainable development because of ever increasing government expenditures. Most of the developing countries lack the required infrastructure which may support public sector sustainability. The aim of this study is to assess the critical factors which resist the implementation of sustainable procurement in public sector of Pakistan. We used Interpretive Structural Model to investigate and rank the interrelationships among different factors of sustainable procurement. With the help of literature and Likert scale instrument, we found twelve key barriers that resist sustainable procurement implementation. We also examined tender documents of 75 different public sector universities of Pakistan but found absence of sustainability element in the documents. External factors namely government legislation and stakeholders' pressure are found most critical barriers as compared to inter organizational factors. The study is also important to highlight the hurdles in the way of sustainable development. First, the government must introduce rules and regulations to implement the sustainable procurement. Stakeholders and donors must put pressure on organizations for adopting sustainable procurement. Sustainability education should be made mandatory part of curriculum and employees should be given regular training on sustainability. Further, public procurement policies at government and institutional levels are required to be revisited towards a circular economy.     

From rationality to hyperreality: paradigm poker

This paper, following McGoun's (1997) seminal article comparing the economy of financial securities to a hyperreal poker game, argues that finance and accounting researchers should take the “linguistic turn” that has rejuvenated theory and research in many, if not most, of the social science and humanities in recent decades. In general terms, this means following Ludwig Wittgenstein's language game paradigm rather than Karl Popper's scientific deductive hypothesis testing methodology. The paper illustrates this by drawing on some of Jean Baudrillard's' ideas, particularly his concept of hyperreality and his phases of the image theoretic.The paper presents a poststructuralist genealogical analysis of the radical ruptures and reformulation of the meaning attributed to the accounting sign of earnings over the feudal, counterfeit, production, and simulation eras. It concludes that, as with many other signs in contemporary society, the earnings sign no longer has any relationship with, nor does it any longer refer to, any real or intrinsic profit but instead floats ungrounded in today's financial economy.The paper recommends that researchers in finance and accounting adopt paradigms from literary theory, semiotics, linguistics, and semiology rather than continue to rely on economics-based theory, which has lost its power for explaining and predicting happenings in today's financial economy of self-referencing models and images.     

THE CHANGING VOLATILITY OF THE SOUTH AFRICAN ECONOMY

During the last decade economic literature explored the presence of and reasons for what became known as “the great moderation” in the US and other G7 countries. “The great moderation” describes the decrease in economic volatility experienced in many of the G7 countries. This paper finds that in South Africa volatility is also not constant (it even finds that there are autoregressive conditional heteroskedastic effects present) and that volatility also decreased, particularly since 1994. Following the literature, the paper explores several reasons for this decrease and finds that smaller shocks, better monetary policy and improvements in the financial sector that place less liquidity constraints on individuals and allow them to manage their debt better are some of the main reasons for the reduction in the volatility of the South African economy. The literature on the G7 also suggests that better inventory management contributed to the lower volatility. However, this seems not to be true for South Africa.     

Diffusion of Products with Limited Supply and Known Expiration Date

In this paper, we provide a model for diffusion of products, which are available in limited quantity until a known expiration date, after which the unsold products have no value. We consider the case of a performing arts company. The model development is built on the foundation of classical product diffusion model by Bass (1969) and the psychological effect known as the scarcity principle (Cialdini, 1985). Our empirical analysis results show that the proposed model can provide significant improvement in prediction of the products characterized by the scarcity effect.     

物流合理配送问题的多阶段建模优化求解方法

简述了现有货物配装问题在实际应用中的缺陷,并针对货物配送问题,提出了多阶段建模优化求解方法,并应用于实例中。实例证明该方法所求得的最优解更具合理性和实际意义。