Turbulent Period Research Articles

Parish transformations and revolution, or Reformation of the Unreformable

The author examines the monograph by A.L. Beglov, dedicated to the evolution of the church parish in the history of Russia, and focuses primarily on the turbulent period of the early 20th century. At that time, the issue of parish reform acquired an acute political character. Two points of view emerged, essentially diametrically opposed: public and synodal. According to the author of the article, the politicization of the issue blocked a constructive discussion of ways to resolve the problem.

ESG Meets DeFi: Exploring Time‐Varying Linkages and Portfolio Implications

ABSTRACTThis study delves into the connection between Environmental, Social and Governance (ESG) indices and emerging Decentralised Finance (DeFi) assets. Specifically, it explores the ever‐changing, frequency‐based linkage between these ESG indices and innovative DeFi assets. Employing the wavelet coherence technique, we analyse a broad range of ESG indices, spanning emerging, developed and US indices, alongside various DeFi assets. This examination covers a period encompassing the COVID‐19 pandemic and the Russian‐Ukrainian conflict to assess market linkages during extreme events. We then calculate optimal weights and hedge ratios for ESG‐DeFi asset pairs to evaluate portfolio implications. Wavelet analysis results frequently show no connection between ESG indices and DeFi assets, underscoring the diversification benefits of adding DeFi to an ESG portfolio. However, this relationship notably strengthens at the pandemic crisis's onset, indicating DeFi assets lose diversification potential during turbulent times. Portfolio allocation should mainly favour ESG indices during normal periods, with minimal variations in optimal weights pre‐ and post‐COVID. Meanwhile, hedge ratio analysis suggests DeFi assets make sound investments during crises, although hedging costs increase during turbulent periods. These findings hold relevance for investors, portfolio managers and policymakers.

Economic development and foreign trade: a сomparative analysis of the United States and China

The article presents a comparative analysis of socio-economic and foreign trade relationships between the United States and the People's Republic of China, two leading countries of the world economy, which exert maximum influence on global processes in economics and politicsas well as in world trade, investment activities and scientific and technical sphere. Today, the rivalry between the two powers has also intensified in the monetary and financial aspect due to the growing importance and share of the yuan in international settlements and government reserves of many countries. This situation continues to worsen smoothly, often having a negative impact on other countries, including the Russian Federation. The purpose of the article is to explore the current state of the demographic situation, the dynamics of GDP and trade turnover of the two countries, to characterize the current situation and identify trends in its development in the medium term, which will make it possible to form the positions and policies of other subjects of the world economy to ensure their stability and balance their actions. The article concludes that both countries are currently experiencing a period of socio-economic and foreign trade turbulence, and its range has not yet shown a tendency to decrease. It is often the United States that acts as the source of this turbulence, trying to overcome the negative processes in its own economy. Therefore, it is important for third countries, for example, Russia, to take consistent measures to ensure national, including foreign economic, security. The methodological basis of the research is statistical, comparative, graphical analysis, the study of reports and archives, calculations based on data from open international statistical databases and official websites of international economic organizations, the main purpose of which is to study the economic indicators of the United States and the People's Republic of China. The study period covers 2012–2023.

Importance of geopolitical risk in volatility structure: New evidence from biofuels, crude oil, and grains commodity markets

This paper aims to explore the complex linkages and evolving structure of price volatility in the global oil, biofuels, and grain commodity markets during periods of global turbulence. With the growing urgency for energy stability amid climate change, biofuels are gaining traction as a viable alternative energy source. However, their production can significantly impact essential commodities like grains and vegetable oils, increasing food prices and heightened market volatility. We introduced a TVP-VAR frequency connectedness method to address this, analyzing data from January 1, 2013, to September 29, 2023. Our approach offers a fresh perspective on market dynamics and geopolitical risks.The study underscores the growing influence of agricultural shocks on energy markets, particularly within the ethanol sector. It confirms that the Russia-Ukraine war, a significant geopolitical event, has had a profound and enduring impact on the interconnectedness of these markets across various timeframes and frequencies. We offer concrete, actionable policy recommendations to mitigate the transmission of market shocks within the energy and food sectors, thereby bolstering investor and policymaker confidence and facilitating informed decision-making.

Living on a low income during the cost-of-living crisis: Exploring experiences and perceptions

Drawing upon data from Changing Realities, an online participatory research project collected between September-October 2022 and March-April 2023, this article generates new knowledge on the lived experiences of low-income families in the UK during this turbulent political period and particularly through the (ongoing) cost-of-living crisis. Utilising the work of Wright and McIntosh, we articulate the ‘shared typical’ discernible of lived experiences of life on a low income during this tumultuous period. Findings provide new insights into how participants describe themselves as part of a collective, comprising parents and carers who shared similar experiences of life on a low income. However, in contrast they differentiated between themselves and those in positions of power and disconnected from their reality. In our discussion, we examine the implications of this and consider the broader understandings and realisations of poverty.

Spillover between investor sentiment and volatility: The role of social media

We examine the spillover effects between social media sentiments and market-implied volatilities among stock, bond, foreign exchange, and commodity markets. We find that information mainly spillovers from volatility to sentiment indices, with the VIX being the most significant net transmitter. Within each asset class, there is a more pronounced spillover from volatility to sentiment compared to the reverse, implying that a significant portion of investor sentiment is volatility-driven. This relationship intensifies in turbulent economic periods, such as during the Global Financial Crisis, Brexit, the US-China trade war, and the COVID-19 pandemic. Our analysis also reveals that sentiment indices can transition from net receivers to net transmitters of shocks during turbulent periods. This can be explained by the echo chamber effect, where social media echo prevailing news signals, and some investors interpret repeated signals as genuinely new information.

The advantages of CBOE credit VIXs for corporate bond investors in North America: A sectoral analysis

This paper examines the safe-haven role of the recently introduced CBOE credit VIXs for investment-grade and high-yield corporate bonds, at both aggregate and sectoral levels. Using a time-varying quantile-based framework and daily data from June 5, 2014 to December 10, 2023, the safe-haven role of credit VIX is confirmed irrespective of bond sector. The safe-haven property of credit VIX is pronounced for high-yield bonds which embed a high credit risk-premium. This result stands when taking into account interest rate volatility, as measured by the MOVE index. A time-varying analysis shows the persistence of credit VIX as a safe-haven for all bond sectors after the COVID-19 pandemic and during a high US interest-rate regime. Corporate bond investors and traders can use these findings to refine their investment and trading decisions and offset credit risk during both normal and turbulent periods.

Echoes of violence: experiences of Palestinian Arab students in Israeli academia during the violent events of May 2021

AbstractThis paper investigates the challenges faced by Palestinian Arab citizens of Israel (PAI) who are students in Israeli higher education institutions amidst periods of national turbulence and violence, particularly focusing on the violent events of May 2021. Using interviews with students, academics, and members of civil society organisations, the paper puts forth a constructivist grounded theory model that charts the impact of the violent events of May 2021 on PAI students. It reveals that students’ experiences of violence, in various forms, give rise to a host of emotional, social, and political processes that heighten their awareness of the structural violence of the broader Israeli-Palestinian struggle. In response, PAI students withdraw both physically and mentally from their campuses and concurrently mobilise within their communities to address unmet needs neglected by official authorities. The perceptions of PAI students regarding their institutions’ responses to political issues are marked by intense cynicism—a sentiment that is mitigated by individual supportive initiatives by faculty members. Based on the findings, the paper argues that periods of political escalation are not to be viewed as fleeting events that heighten emotions but rather as critical junctures where identities and perceptions are formed, leaving an impact that lasts long after the immediate turbulence subsides.

Investing during a Fintech revolution: The hedge and safe haven properties of Bitcoin and Ethereum

Global financial markets have witnessed significant transformations in response to the worldwide spread of the Covid-19 pandemic, resulting in heightened risk and alterations in inter-market relationships. Both cryptocurrency markets and conventional equity markets have been influenced by these changes. This study aims to investigate the potential hedging and safe haven benefits of Bitcoin and Ethereum against risks in Asian emerging stock markets under various Covid-19 pandemic contexts including the onset of the pandemic, varying levels of panic, the extent of media attention, and sentiment analysis. Utilizing the dynamic correlation coefficients derived from the DCC-GARCH methodology, our analysis indicates that, both Bitcoin and Ethereum do not effectively serve as hedges or safe havens for major Asian emerging stock markets during the Covid-19 outbreak. These results remain robust during more extreme periods characterized by high panic, intense media attention, and negative sentiment. Nevertheless, an noteworthy exception is the case where Ethereum exhibits strong hedging properties specifically in the context of the Pakistan equity market. Recognizing these unique hedge and safe haven potential of cryptocurrencies can contribute to enhancing the effectiveness of investment strategies and risk management practices during periods of market turbulence.

Evaluating Volatility Using an ANFIS Model for Financial Time Series Prediction

This paper develops and implements an Autoregressive Integrated Moving Average model with an Adaptive Neuro-Fuzzy Inference System (ARIMA-ANFIS) for BTCUSD price prediction and risk assessment. The goal of these forecasts is to identify patterns from past data and achieve an understanding of the future behavior of the price and its volatility. The proposed ARIMA-ANFIS model is compared with a benchmark ARIMA-GARCH model. To evaluated the adequacy of the models in terms of risk assessment, we compare the confidence intervals of the price and accuracy measures for the testing sample. Additionally, we implement the diebold and Mariano test to compare the accuracy of the two volatility forecasts. The results revealed that each volatility model focuses on different aspects of the data dynamics. The ANFIS model, while effective in certain scenarios, may expose one to unexpected risks due to its underestimation of volatility during turbulent periods. On the other hand, the GARCH(1,1) model, by producing higher volatility estimates, may lead to excessive caution, potentially reducing returns.

DYNAMIC LINKS BETWEEN COMMODITY MARKETS & PAKISTANI SECTORAL INDICES: IMPLICATIONS FOR PORTFOLIO DIVERSIFICATION

This research aimed to examine the inter-connections among international commodities markets and sectoral indices of Pakistan over the most recent period ranging from July 19, 2016, to December 29, 2023. This time period is selected based on recent important events of global significance including COVID-19 pandemics and recent geopolitical crisis emerged due to Russia-Ukraine war in Feb, 2022. This study is utilizing Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model for the deeper inquiry of interplay among the variables. The findings of the study indicate significant spillovers among variables with varying degrees of significance. The results show that various sectors of Pakistan economy showed asymmetric behavior indicating that some sectors were the risk transmitters while other were risk recipients. Moreover, volatility linkages are time-varying with heightened transmissions during turbulent periods. The results provide the significant information in reaching the desired conclusion and making decisions. The findings of study thus had important implications for investors (individual & institutional), fund managers and policy makers while devising strategies for diversification and risk mitigation in the Pakistani context especially in stressful periods.

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.

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.