Turbulent Period Research Articles

Implementing circular economy through bricolage, frugal innovation and technological turbulence

AbstractScholars, practitioners, and policymakers are considering a circular economy (CE) to optimise resource utilisation and tackle issues linked to economic and environmental growth. This research investigates the association between entrepreneurial bricolage, frugal innovation (FI), technological turbulence, and the implementation of CE in Malaysia, an emerging market. The authors tested the hypothesised relationships using legged multi‐source data and analysed them using the Smart‐PLS‐SEM technique. Data revealed that entrepreneurial bricolage is important in encouraging FI and CE. Meanwhile, the mediating role of FI amplified the link between entrepreneurial bricolage and CE. Furthermore, the moderation of technological turbulence amplified the link between entrepreneurial bricolage, FI, and CE. The findings indicate that firms employing a bricolage approach, characterised by accessing, storing, combining, and utilising readily available resources, exhibit enhanced performance during periods of technological turbulence through the implementation of CE and FI.

Knowledge can wait? The epistemic conversion of new beat reporters

This study shows how, during the turbulent period of their initial months on the job, new beat reporters experience a shift in their basic approach to knowledge. This new epistemic approach encompasses two interconnected shifts: From seeing self-knowledge as a necessity to reliance on sources’ knowledge, and from prioritizing content knowledge to prioritizing journalistic knowledge. Findings suggest that reporting without knowledge isn’t a bug, but rather a major feature of news reporting; that at least during reporters’ first years, the main epistemic challenge is reporting despite the lack of beat knowledge; and that the foundations of source-reporter relations are laid down when the latter are at their weakest point in terms of power and knowledge, enabling sources’ to gain a dominant position in shaping the reported realities.

Exploring the Dynamic Behavior of Crude Oil Prices in Times of Crisis: Quantifying the Aftershock Sequence of the COVID-19 Pandemic

Crude oil prices crashed and dropped into negative territory at the onset of the COVID-19 pandemic. This extreme event triggered a series of great-magnitude aftershocks. We seek to investigate the cascading dynamics and the characteristics of the series immediately following the oil market crash. Utilizing a robust method named the Omori law, we quantify the correlations of these events. This research presents empirical regularity concerning the number of times that the absolute value of the percentage change in the oil index exceeds a given threshold value. During the COVID-19 crisis, the West Texas Intermediate (WTI) oil prices exhibit greater volatility compared to the Brent oil prices, with higher relaxation values at all threshold levels. This indicates that larger aftershocks decay more rapidly, and the period of turbulence for the WTI is shorter than that of Brent and the stock market indices. We also demonstrate that the power law’s exponent value increases with the threshold value’s magnitude. By proposing this alternative method of modeling extreme events, we add to the current body of literature, and the findings demonstrate its practical use for decision-making authorities—particularly financial traders who model high-volatility products like derivatives.

The Impact of Organizational Resources on Organizational Agility in Hospitality Industry: A Dynamic Capabilities Approach

ABSTRACTThe present study investigates the relationship between organizational resources (financial, social, and technological capital) and dynamic capabilities development in crises periods. Through quantitative research, a theoretical framework that is based on resource‐based view and dynamic capabilities view is validated for the first time in the hospitality industry. In practice, it is explored whether the hospitality firms—based on their own resources—can develop the dynamic capability of organizational agility that enables them to cope with turbulent and unstable environments. The empirical research was conducted with the sample of 502 hospitality firms in Greece during the COVID‐19 era. The findings confirm that financial and technological capital have a positive influence on the development of agility‐related dynamic capabilities, and specifically market capitalizing agility and operational adjustment agility, for the hospitality industry during turbulent periods. Instead, social capital has a negative and no effect respectively on these two dynamic capabilities.

Ottoman Jewish Feminism in Print and Practice: The Paradoxical Life and Ideas of Graziella Benghiat

Abstract: Few traces remain of the life and work of the Ottoman Jewish author and thinker Graziella Benghiat. Though she served as a contributor to and, later, editor of different journals in late Ottoman Izmir, most of her writing appears to have been lost in the turbulent period of nearly uninterrupted war that ravaged the region between 1912 and 1922. The words of a speech she gave in March 1913 as well as various personal details preserved by family members are among what is left. Viewed together, they present a picture of a life and body of thought that is difficult to pin down, characterized by paradoxes and perpetual motion.

Bitcoin returns and YouTube news: a behavioural time series analysis

ABSTRACT This study investigates whether investor’s sentiment and attention information collected via YouTube can improve bitcoin return forecasts. Accordingly, we collected daily data over the period 2017–2023, covering calm and turbulent periods marked by different types and episodes of emotions. Unlike previous studies, we used YouTube videos to propose two sentiment proxies: investor attention to YouTube (daily number of YouTube video views) and investor sentiment on YouTube (number of positive and negative videos on YouTube). Interestingly, we break down both attention and sentiment per subject. Econometrically, we assess lead-lag effects between sentiment/attention and bitcoin return using causality tests and Vector Auto-regressive (VAR) model. We also evaluate the forecasting power of YouTube attention/sentiment data using a deep learning LSTM model. Our study shows two main results. First, we find lead-lag effects between bitcoin returns and per subject investor’s attention and sentiment proxies. Second, we show that our deep learning LSTM model relying on the information provided by attention and sentiment supplants benchmark Buy and Hold Strategy to forecast future bitcoin returns.

Twitter-based market uncertainty and global stock volatility predictability

This study integrates Twitter-based market uncertainty (TMU) into the predictive framework of daily volatility in twenty international equity markets. The study reveals that TMU has a strong predictive ability for stock volatility from both in- and out-of-sample perspectives. Interestingly, despite Twitter being inaccessible in China, the interconnectedness of global financial markets allows it to indirectly impact China’s stock market volatility. The research also highlights that TMU plays a particularly significant role in forecasting stock market volatility during turbulent periods, such as the COVID-19 epidemic. Furthermore, integrating TMU into the volatility prediction framework leads to an improvement in economic value. These findings are essential for policymakers to develop effective market-stabilizing policies and for investors to enhance the management of their investment portfolios.

Sanctions and Russian online prices

This study leverages daily web-scraped data to evaluate the impact of economic sanctions following Russia’s invasion of Ukraine on consumer prices and product availability across different goods categories. We find that international sanctions significantly disrupted Russian price dynamics, with the exchange rate serving as the primary transmission mechanism. Utilizing granular online data allows us to circumvent potential misreporting and track real-time economic indicators at high frequency. Our analysis uncovers heterogeneous effects across product groups, with sanctions associated with an average increase of 11.7 percentage points in the Russian CPI. The results highlight how trade policies and geopolitical events can rapidly propagate through retail markets, underscoring the importance of timely price monitoring during periods of economic turbulence. More broadly, we demonstrate the value of online data for evaluating policy shocks, paving the way for similar applications in other contexts.

The impact of COVID-19 uncertainties on energy market volatility: Evidence from the US markets

This research investigates the influence of the COVID-19 on the returns of energy indexes in the US using daily time series data of WTI and Brent markets for the January 2020 – March 2022 period. The findings reveal compelling evidence of the effects of the COVID-19 on the volatility of energy commodity indexes in the US. Nevertheless, the magnitude of this impact varies across different volatility regimes. Notably, the WTI crude oil exhibits more substantial effects during periods of lower volatility characterised by fewer COVID-19 cases, potentially attributed to market control measures. In contrast, the Brent crude oil displays a more pronounced impact of the COVID-19 during turbulent periods, attributed to the market's openness and the prevalence of speculative participants. The study suggests that participants in the Brent market, driven by a desire to capitalise on price differentials, intensify their activities during turbulent periods, contributing to increased volatility during successive waves of high COVID-19 cases. The observed structural differences between the WTI and Brent commodity markets carry significant policy implications for investors in the energy sector.

How do risk shocks reshape the spillovers among the oil, gold, emerging, and developed markets? Evidence from a new TVP-VAR-based wavelet coherence framework

ABSTRACT To quantify the impacts of risk shocks on time-domain and frequency-domain spillovers, we propose a new empirical framework based on TVP-VAR and wavelet coherence analysis. We illustrate the methodology by analysing the spillovers among the gold, oil, emerging, and developed markets from 10 February 2011 to 2 April 2024 and obtain intriguing findings. First, the dynamic spillovers among markets rise significantly during turbulent periods. The dynamic net spillover results show that the gold and emerging markets are mainly the spillover receivers, developed markets are spillover emitters, and the oil market plays a switching role over time. Second, risk shocks have frequency-dependent impacts on the spillovers among markets. The effects are concentrated in the medium- to long-term ranges of 2015, 2018, and 2020–2021, and the relationship between risk volatility and dynamic total connectedness is positive. The impact of risk volatility on net market dynamic spillovers is heterogeneous in the time and frequency domains and the lead-lag relationship. Our findings have important implications for policymakers and investors.

Comparative Analysis of GARCH-Based Volatility Models of Financial Market Volatility: A Case of Nairobi Security Market PLC, Kenya

This paper conducted a comprehensive comparative analysis of various GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models to forecast financial market volatility, with a specific focus on the Nairobi Stock Exchange Market. The examined models include symmetric and asymmetric GARCH types, such as sGARCH, GJR-GARCH, AR (1) GJG-GARCH, among others. The primary objective is to identify the most suitable model for capturing the complex dynamics of financial market volatility. The study employs rigorous evaluation criteria, including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Error (ME), and Root Mean Absolute Error (RMAE), to assess the performance of each model. These criteria facilitate the selection of the optimal model for volatility forecasting. The analysis reveals that the GJR-GARCH (1,1) model emerges as the best-fit model, with AIC and BIC values of −5.5008 and −5.4902, respectively. This selection aligns with the consensus in the literature, highlighting the superiority of asymmetric GARCH models in capturing volatility dynamics. The comparison also involves symmetric GARCH models, such as sGARCH (1,1), and other asymmetric models like AR (1) GJG-GARCH. While these models were considered, the GJR-GARCH (1,1) model demonstrated superior forecasting capabilities. The study emphasizes the importance of accurate model selection and the incorporation of asymmetry in volatility modeling. The research provides essential insights into financial market volatility modeling and forecasting using both asymmetric and symmetric GARCH models. These findings have significant implications for government policymakers, financial institutions, and investors, offering improved tools for risk assessment and decision-making during periods of market turbulence.

Announcement effect of tender offer share buyback around turmoil period – evidence from India

The announcement of a buyback informs the market about the company’s decision to repurchase its own shares. This announcement highlights the company’s price valuation and the inefficiencies that exist in the market. This study examines the share buyback announcement effect during the COVID-19 period. The study considered the stocks listed in the National Stock Exchange (NSE) that offered share buyback under tender offer mode during the pre-pandemic period between April 2016 and February 2020 and the post-pandemic period between March 2020 and March 2022. 75 firms in the pre-pandemic period and 43 in the post-pandemic period that announced share buyback under the tender offer method were analyzed. The event study methodology using a market model was employed to determine the presence of abnormal returns during the event period, which consisted of –21 days and +21 days. The findings of the study revealed the existence of abnormal returns in and around the announcement date. Besides, statistically significant cumulative abnormal average returns (CAAR) were also found on the event day, i.e., on Day 0. The study found that the impact of buyback announcements on stock returns significantly differed before and after COVID-19 for 10 and 21-day periods, with no significant differences for shorter periods. These insights can help traders and fund managers make informed portfolio adjustments during turbulent market periods surrounding buyback announcements. AcknowledgementThe authors express their sincere gratitude and special thanks to Dr. Krishna T.A., Assistant Professor, Department of Professional Studies, School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Bangalore, India, for encouraging, motivating and providing all the required support throughout this empirical investigation and to accomplish this research task.

Heterogeneous impact of economic and political uncertainty on green bond volatility: Evidence from the MRS-GARCH-MIDAS-Skewed T model

Green bonds attract increasing attention as a new eco-friendly investment product. We explore the heterogeneous impact of low-frequency economic and political uncertainty across high or low uncertainty states on green bond volatility in order to accurately analyze the green bond market risk. To this end, we propose a new Markov regime switching GARCH-MIDAS-Skewed T model, in which the regime switching behavior occurs on the low-frequency long-term volatility. An effective filtering estimation method is put forth by introducing the likelihood of the low-frequency sub-sample set. The evidence supports that there are significant time-varying and state-dependent impacts from uncertainty shocks on the volatility of green bonds, including monetary policy, inflation, and crude oil prices as well as global economic policy and political environment. In addition, we find the counter-cyclical behavior of green bond volatility, which increases in the period of economic recession or financial turbulence with expanding uncertainty. Improving the hedging ability of green bonds against uncertainty risks effectively contributes to low-carbon economic development.

Conventional and unconventional shadow rates and the US state-level stock returns: Evidence from non-stationary heterogeneous panels

This study analyzes how monthly stock returns in the United States react to conventional and unconventional shadow rates from February 1994 to April 2023. The study uses a nonstationary heterogeneous panel data technique appropriate for analyzing large cross-sections and long periods. The analysis is separated into turbulent and tranquil periods. The findings suggest that, although the shadow rate is expected to align with the long-term rate, its ability to boost economic activity in the stock markets is only applicable in the short term. Despite the Federal Funds Rate (FFR) being unable to be lowered below zero bounds, the study shows results that support the effectiveness of the FFR in stimulating stock returns in the long run, particularly during crisis periods. The study also reveals that both conventional and unconventional shadow rates share a common feature, which is that they demonstrate how the stock markets can be downward-sticky in the long run with a rising shadow rate in virtually all 50 states in the U.S. The findings provide sturdy insights into the usefulness of unconventional monetary policy measures for stock market performance during crises and normal periods.

Is style drift informative? Evidence from mutual funds in China

In this study, we investigate whether the style drift of portfolio managers is informative. We establish that style drift is based on public information rather than the imitation of peers. Fund managers are found to adjust their portfolios to align with market expectations, particularly in normal market conditions. However, we observe a pronounced shift towards irrational herd behavior during market turbulence and style rotation periods. While style drift can offer benefits in contemporary periods, such as positive risk-adjusted returns, the funds that exhibit excessive drift can hardly beat their peers in subsequent periods. More notably, sophisticated investors tend to abandon funds with more considerable style drift in favor of those adhering to a consistent investment strategy. Our findings indicate that while style drift may be a strategic response to market conditions, its advantages are transient and often unaligned with the preferences of sophisticated investors.

THE HISTORY OF SINO-RUSSIAN COMMUNICATIONS ON ANTHROPOLOGY: WITH THE EXAMPLE OF DONG TICHEN, THE FIRST CHINESE ANTHROPOLOGIST WHO STUDIED IN THE SOVIET UNION

Introduction. The centennial development of physical anthropology in China can be divided into three periods: 1) the initial period fr om the end of the 19th century to the founding of New China in 1949, when anthropology was imported from the West and gradually localized; 2) the unstable development period from 1949 to 1976, which was faced with a major restructuring of the discipline, the epoch of Sino-Soviet friendship, and a ten-year period of turbulence of the Cultural Revolution; 3) the period of rapid development after the reform and opening up of the country at the end of the 1970s. Materials and methods. The author presents the history of anthropological exchanges between China and Russia over the past hundred years through the study of literature and photographic sources. Results. Before the founding of New China, communications of anthropology between China and Russia was represented by S.M. Shirokogorov; after the founding of New China, it was represented by N.N. Cheboksarov; during the period of Sino-Soviet friendship, China adopted the suggestions of Soviet scientists and launched journals, translated and published monographs, and dispatched international students, Dong Tichen and Cui Chengyao, to study in the Soviet Union. Conclusion. In this article, for the first time, a large number of old photographs from private collections have been released to show the life story of Dong Tichen, the first anthropologist who went to the Soviet Union to study and returned to China. After graduating from Beijing Normal University, Dong Tichen went to Moscow University to study anthropology and obtained his Ph.D. in biology in 1961. He became a lecturer in the Department of Anthropology at Fudan University, wh ere he was one of the earliest teachers of anthropology in New China. His research was pioneering and prospective, for example, his proposed taxonomic position of the Gigantopithecus was very forward-looking; he created a precedent in the study of dermatoglyphics in China and contributed to the foundations of anthropometrics. His return solidified the discipline of anthropology at Fudan University, and during his short life he trained several students who would become the mainstay of anthropology in the new China in the future. Unfortunately, he died in 1966, as a result of social unrest and change.

An Analysis of Romania’s Energy Strategy: Perspectives and Developments since 2020

Earth’s climate cannot be ignored any longer. Policies are vital in order to mitigate the negative effects of climate change. The energy crisis created by the Russo-Ukrainian war in Europe and COVID-19 pandemic affected the EU and its member states. The focus is more than ever on its energy policies and independence. The EU revised the energy strategy in response to the regional conflict, and it sped up all the processes for energetic independence from other countries outside of the EU. This benefited the climate change policies the most, as all the measures involved reducing energy consumption and increasing renewables, thus contributing to reducing greenhouse gas emissions. As a member state of the EU, Romania is committed to complying with EU regulations. With a high degree of energy independence compared with the other EU members, Romania plans to become a regional energy provider and modernize the energy infrastructure internally as a response to the regional conflict. The measures that the EU and Romania implemented after the conflict started in 2022 have come to fruition, and the effects are becoming visible a year later. This study aims to study the energy strategy of Romania in correlation with the EU strategy in the turbulent period of pandemics and conflict between 2019 and 2023, with the latest available data.

Predictive analytics on artificial intelligence in supply chain optimization

AI-powered predictive analytics is among the most important ways of optimizing supply chains. This paper on AI-powered predictive analytics will address improving the competitiveness and effectiveness of supply chain operations. Nevertheless, current methods are not always scalable or adaptable to complex supply networks and changing market environments. Therefore, this paper posits that Supply Chain Optimization using Artificial Intelligence (SCO-AI) systems can help with these concerns. SCO-AI employs real-time data analysis and advanced machine learning algorithms which results to reduced response time, enhanced logistics route optimization, improved demand planning as well as real-time inventory control. Thus, the idea herein suggested fits smoothly into existing supply chain frameworks for data-driven decisions that make companies remain agile in ever-changing market dynamics. SCO-AI implementation has seen significant improvements in inventory turnover rate, rates of on-time delivery as well as overall supply chain costs. In this period of high business turbulence, such kind of research builds up the robustness of a given supply chain while at the same time minimizing operational risks by means of simulations and case studies

Skew–Brownian processes for estimating the volatility of crude oil Brent

To predict the volatility of crude oil Brent price, we propose a novel econometric model 11The numerical results presented in this manuscript were reproduced by the Editor-in-Chief on 30 June 2024. where the explanatory variables are a combination of macroeconomic variables (i.e. price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distributed quantities; alternatively, we consider the potential presence of skewness and adopt a Skew–Brownian process. We show that the suggested approach outperforms the selected baseline model as well as other models proposed in the literature, especially when turbulent periods occur.

Organisational change and transformational strategies for enhancing a bank’s change and transformation during periods of turbulence

This study offers a critical analysis of the organisational change and transformation strategies for enhancing a bank’s change and transformation during periods of turbulence. As banks devise and apply different turnaround strategies to get the bank out of the crisis, the challenge often arises from the difficulties of applying the required accompanying change management strategies to enhance the bank’s transition from the crisis to the desired new state of operation and performance. To respond to such difficulties, this study used systematic review as one of the techniques for qualitative content analysis to evaluate and highlight the types of the accompanying organisational change and transformation strategies that banks can use during crisis management. In crisis situations where the bank has to make some radical and incremental changes to survive, systematic review suggests that process change and transformation must be integrated with cultural change and transformation in order to influence the bank’s seamless transition into the desired new state. In addition to radical or incremental organisational change and transformation, findings imply that if the nature of the bank crisis requires, these strategies must also be accompanied with the application of the organisational-wide/subsystem change and transformation. Though the use of a combination of such organisational change and transformation strategies may influence the bank’s seamless transition from the old system to the new state, future studies must still explore the challenges of managing organisational change and transformation during a bank crisis.