The Effect of Financial Stress on Bitcoin Volatility

What are the effects of financial stress on economic activity and government debt? An empirical examination in an emerging economy

This study employs the vector autoregression (VAR) analysis to empirically report the impulse response functions of economic policy certainty and financial stress. A causality test of these two variables is also performed. The analysis of the monthly changes in the economic policy uncertainty index and the Federal Reserve Bank of St. Louis Financial Stress Index from 1994:1 to 2012:5 including up 9 lags shows that the financial stress jumps in the first, fifth, and eighth through twelfth months following economic policy shocks. In addition, economic policy uncertainty jumps in the first, third, fourth, sixth, seventh, and ninth months following financial stress shocks. The Granger causality test shows that financial stress and economic policy uncertainty Granger-cause each other. The time-series OLS regression analysis shows a statistically significant positive coefficient (b = 24.16609; t = 6.56) when monthly changes of financial stress is the independent variable.

The importance of a sound and stable financial system and by extension economic stability was brought to the fore by the global financial crisis (GFC). The economic and social costs of the GFC have renewed the commitment of stakeholders in the financial sector including central banks to develop instruments and methodologies that will be useful in monitoring financial stress within the financial system and the real economy. This study contributes to the growing literature by developing a financial stress indicator for the South African financial market. The financial stress indicator (FSI) is a single aggregate indicator that is constructed to reflect the systemic nature of financial instability and also to measure the vulnerability of the financial system to both internal and external shocks. Using the principal component analysis (PCA), the results show that financial stress can be identified by the financial stress indicator. Furthermore, using a recursive Vector Autoregression (VAR) model to estimate the impact of financial stress on output and investment, the result shows that financial stress has a negative impact on economic growth and investment, though not immediately. FSI is very useful for gauging the effectiveness of government measures to mitigate the impact of financial stress. Concerted effort to stimulate investment and domestic production by relevant stakeholders is necessary to mitigate the impact of financial stress. This will go a long way to alleviating the impact of the financial stress on industrial production, employment and the economy at large.

Purpose This study aims to investigate the impact of climate change on financial system stress in ASEAN-5 countries: Indonesia, Malaysia, the Philippines, Singapore and Thailand. Design/methodology/approach The authors construct a Financial Stress Index (FSI) from multiple financial indicators and assess physical climate risks using six indicators grouped into weather- and disaster-related proxies. Using first-difference generalised methods of moments estimation, this study analyses the dynamic relationships between these variables from the first quarter of 2008 to the first quarter of 2017. Findings The findings reveal significant positive relationships between disaster-related variables and the FSI, indicating that extreme climate events exacerbate financial system stress. While weather-related factors show no direct correlation with the FSI, they act as precursors to climate-related disasters, indirectly contributing to financial stress. Specifically, interbank lending rates exhibit the most pronounced associations with physical risk variables. Practical implications This study emphasises the urgent need for policymakers to address the multi-faceted impact of climate change on financial stability. This includes enhancing physical resilience and implementing macroprudential policies to safeguard the financial system from climate risks. Social implications Understanding the broader impact of climate change on financial stress can help societies prepare for and mitigate the adverse effects of extreme climate events on economic stability, promoting more resilient and sustainable economies and communities. Originality/value To the best of the authors’ knowledge, this study is the first comprehensive analysis examining the role of climate change risk on financial system stress in developing economies, specifically focusing on ASEAN-5 countries.

The recent global financial crisis 2008-2009 has posed great impacts on the global economy. Since then, there are many researches on financial stress: what it is, how to construct financial stress index and how it affects the real economy. In this paper, the author first reviews literature on financial stress, then constructs the financial stress index (FSI) by identifying the stress sub index for different market: monetary market, stock market, foreign exchange market and the banking system, then use the equal variance weight method to determine the financial stress period in Vietnam. The result shows that the Vietnam financial stress index reached its highest peak in 2011 and sur passed the long term trend of FSI during 2011- 2012, implying that Vietnam financial sector experienced stress period during this time. By using VAR model, the author assesses the impact of FSI to Vietnam economy by reduc ing the investment and GDP growth in Vietnam. The result shows a negative impact of FSI on real economy.

Relevance. The interconnectedness of global financial markets implies that shocks in one region can have widespread implications. The recent geopolitical tensions in the Middle East and Western Europe, have significantly heightened Geopolitical Risk (GPR) and Economic Policy Uncertainty (EPU). Country-specific financial stability can experience ripple effects from these external sources of risk, indicating a direct link between geopolitical events and economic policy uncertainties that contribute to financial stress. Research Objective. This study examines the risk spillovers from Global Geopolitical Risk (GLGPR) and Economic Policy Uncertainty (GLEPU) to the country-wise Financial Stress Index (FSI) of the USA, China, and Russia. Our goal is to determine which of these giants demonstrates superior resilience in terms of financial stability against these external sources of risks. Data and Methods. Using Cross-Quantilogram (CQ), Partial-CQ and Recursive-CQ (R-CQ), we evaluate a weekly high-frequency data from 2000 to 2023 to identify patterns of these spillover effects. Results. Our findings indicate that GLGPR has mixed spillover effects on the USA's FSI under varying market conditions, while the FSI shows long-term resilience to GLEPU. For China, GLGPR only boosts the FSI during long-term bullish markets, and GLEPU demonstrates pronounced adverse impact at the bullish market. In contrast, the Russian FSI reacts unevenly to both GLGPR and GLEPU, experiencing greater severity. Overall, the USA's financial market exhibits the highest resilience to GLEPU, while the Chinese market demonstrates the greatest resilience to GLGPR. In contrast, the Russian financial market shows the highest exposure to these global risks. Conclusions. No previous empirical study has examined the financial stress response of these three globally powerful economies to external sources of risk such as GLGPR and GLEPU. Most of the previous research focuses solely on stock market returns or their volatility in relation to these risks, whereas we focus on a composite measure of stability that encompasses all four sectors of a financial market. Our research fills this gap, particularly in the context of current geopolitical tensions among these global players, making it highly relevant for both academics and policymakers.

بازارهای مالی با کاهش هزینه‌های مبادله‌ای و عدم تقارن‌های اطلاعاتی در اقتصاد سبب ارتقای سطح پس انداز، انباشت سرمایه و رشد اقتصادی می‎شوند. اگرچه رشد بازارهای مالی کارا نقش تعیین کننده‎ای در رشد اقتصادی دارد، ولی باید توجه داشت که وقوع بحران در بازار‌های مالی نیز به نوبه خود می‎تواند به تنش مالی و در برخی شرایط به رکود اقتصادی بیانجامد. هدف این مقاله برآورد شاخص تنش مالی در بازارهای دارایی و تامین مالی در اقتصاد ایران از سال ۱۳۸۰ تا ۱۳۹6 است. برای محاسبه‌ی شاخص تنش مالی ابتدا پنج بخش اصلی مالی کشور شامل بخش پولی و بانکی، ارز، سهام، مستغلات، و بازار اعتبارات انتخاب شد. با استفاده از روش تکنیک مؤلفه های اصلی (PCA) متغیرهای مربوط به تنش در اجزای نظام مالی کشور تجمیع شده و شاخص تنش مالی پیشنهادی برای اقتصاد ایران استخراج شده است. نتایج مطالعه حاکی از نقش تاثیرگذار تنش در بازار اعتبارات در تنش مالی در اقتصاد ایران دارد.

Information flow between global financial market stress and African equity markets: An EEMD-based transfer entropy analysis

In recent years, the volatility of cryptocurrency markets has been a major concern for investors, policymakers, and researchers. This study examines the impact of Economic Policy Uncertainty (EPU) on cryptocurrency volatility, focusing on Bitcoin as a representative digital asset. Utilizing a daily dataset from 2014 to 2023, we employ GARCH(1,1) and GARCH-X models to assess volatility persistence and the influence of EPU on price fluctuations. Additionally, a Vector Autoregression (VAR) model and Granger causality tests are applied to analyze the dynamic interdependencies between EPU and Bitcoin returns. The findings reveal that higher economic policy uncertainty significantly increases Bitcoin volatility, indicating that investors react strongly to policy-related risks. The GARCH-X model confirms that EPU is a significant determinant of cryptocurrency price swings, while VAR analysis and impulse response functions (IRFs) suggest that policy uncertainty shocks lead to heightened Bitcoin volatility over a short-term horizon. However, Bitcoin price movements do not significantly influence economic policy uncertainty, reinforcing the view that cryptocurrencies behave as speculative rather than safe-haven assets during periods of policy instability. These results have crucial implications for portfolio risk management, regulatory policies, and investment strategies. Policymakers should consider the spillover effects of economic uncertainty on crypto markets, while investors may use EPU as a predictive indicator for volatility trading strategies. Future research can extend this study by incorporating alternative cryptocurrencies, machine learning-based forecasting models, and global uncertainty indices.

This study investigates the predictive power of the financial stress on the dynamic of the Middle East and North Africa (MENA) financial market returns from 2007 to 2021. Based on a Quantile Regression, we show that financial stress has highest predictive abilities at the lower quantiles when the market is bearish. Then, we propose a Hidden Markov Model (HMM) based on the transition matrix to understand the relationship between financial stress index and the MENA stock market dynamics. We find that the effect of financial stress on stock market return reveals the persistence of regimes: Bullish state exists and persists, and has the longest conditional expected duration for the majority of MENA markets, except Bahrain, Qatar and Jordan. However, the transition probability from the bullish to the calm regime is too low for the financial market of Bahrain, United Arab Emirates and Egypt. Besides, the estimated mean returns for each regime divulge that the bearish and calm states are more attractive destination for both portfolio managers and investors.

This study delves into an exploration of volatility spillover between financial stress, investor sentiment, and stock market index returns in the Gulf Cooperation Council (GCC) countries using the DCC-GARCH, wavelet coherence, and BEKK-GARCH models. A robustness check, applying Diebold and Yilmaz’s (2012, 2014) methodology, verifies network measures across markets. Significant patterns in financial stress index were observed during crises, with strong co-movement between financial stress, investor sentiment, and stock returns, especially during COVID-19 pandemic. Volatility transmission from stock returns to investor sentiment and the financial stress index was notable in some markets. Additionally, we found a significant volatility transmission from the financial stress index to market returns during periods of bearish stress in Bahrain and Kuwait and bullish stress across all countries. These findings offer insights for investors and fund managers optimizing portfolios and managing risk exposure.

In recent years, there is increasing attention to examining the relationship between oil prices, financial markets, and the economy. Relatively little is known about the dynamic relationship between structural oil shocks and financial market stress of countries, which are majorly dependent on oil price fluctuations. This paper examines the impact of structural oil shocks (oil supply shocks, global aggregate demand shocks, speculative shocks, and other oil shocks) on the financial stress of major oil-exporting and-importing economies. In this study, we construct a financial stress index and using a structural vector autoregression model, we investigate the effects of oil price shocks on the financial stress of major oil-exporting and importing economies. We find evidence that global demand shocks, followed by speculative demand shocks, have significant impacts on financial stress. Furthermore, the US subprime crisis has a significant bearing on the response of the financial stress index to structural oil shocks. The magnitude of oil price shocks on financial stress has subdued during the post-crisis period.

The objective of this paper4 is to develop a methodology for the Latvian financial stress index (FSI). To this effect, the particular methodologies widely used in international practice for composite indicators applied in financial stability monitoring and the experience of selected countries were examined. The authors analyse the nature of financial stress and the related symptoms and offer their interpretation of the financial stress concept. The paper provides the rationale behind the selection of the individual indicators (components) comprised in the FSI and evaluates various options for aggregating FSI components. The main conclusion presented in the paper is that the dynamics of the FSI developed on the basis of the methodology proposed by the authors of the paper is quite an accurate measure of changes in Latvian financial system stress levels. It signals periods of elevated stress as well as periods of an excessively vigorous and imbalanced development of the financial system. The Bank of Latvia has been using the FSI as one of the elements of Latvia’s financial system stability monitoring framework since 2010.

Interactions between financial stress and economic activity for the U.S.: A time- and frequency-varying analysis using wavelets

PurposeWith the globalization and liberalization in terms of increasing financial flows across the countries, the policy makers around the world are not independent in the context of monetary and fiscal policy initiatives. In this regard, this paper aims to attempt to quantify and capture long run, short run as well as time-varying linkages among the two financial stress indices, namely, Kansas City Financial Stress Index (KCFSI) and Indian Financial Stress Index (IFSI) across the monthly period (2004 to 2014).Design/methodology/approachOwing to the non-existence of a standardized financial stress index with regards to the Indian financial system, the study has developed an index/stress indicator using principal component analysis. Furthermore, to comprehend the linkages, the study uses bivariate Johansen cointegration model, vector error correction model, impulse response functions (IRF), variance decomposition analysis (VDA), Toda-Yamamoto’s Granger causality test and, finally, bivariate generalized autoregressive conditional heteroskedastic (BVGARCH) (1,1) model under constant conditional correlation (CCC) framework.FindingsThe results report a stochastic trend among the two indices wherein the US financial system acts as a source of a shock causing disequilibrium in the long run co-movement. About 40 per cent of the adjustments take place in one month and rest in the coming months. Both the IRF and VDA report a greater degree impact of the US financial stress on the Indian financial system. Moreover, there is a uni-directional short run causality running from the stress in the US financial system to the Indian financial stress. Furthermore, the co-movement between the US and Indian financial stress reached to its maximum significant level during the sub-prime crisis even confirmed by the Markov switching model results.Practical implicationsOverall, the results provide an insight to the financial market investors both domestic as well as international in their act of risk management. The financial stress prevailing in an economy further has an impact on different economic factors like foreign exchange rates, interest rates, yield curves, equity market returns and volatility. So, the empirical results support strong implications for the Indian policy makers as well as investors in the Indian financial markets.Originality/valueThe present study contributes to the literature in three senses. First, the study considers indices reflecting financial stress in the Indian as well as US financial system. Second, the study captures long run as well as short run linkages among the financial stress indices relating to a developed and an emerging market. Finally, the study uses CCC-BVGARCH (1,1) model to account for the time-varying co-movement among the financial stress indices. This helps in comprehending time-varying nature of the co-movement of the stress in the financial system prevalent in the respective markets.