Financial Market Crisis Research Articles

Forecasting the Crisis of Vietnam's Financial Market by Markov Switching VAR Model

The global economy and financial markets have experienced "The most adverse shock in a century" due to the impact of the Covid-19 epidemic but are also transforming enormously in the digital era. Besides, Vietnam's financial system has been making vital development steps, increasing its resilience. Still, its development prospects depend mainly on the recovery of the global economy and financial markets, the Stability of the economy, and the Stability of the economic stability and sustainability of investor confidence in the market. The Markov Switching Var (MSVAR) model will measure the crisis in the Vietnamese financial system. The research goals reveal that the volatility of macro variables such as the exchange rate (ER), foreign exchange reserves (FR), and the domestic interest rate differential (ID) affects the financial market crisis in Vietnam from 2010 to 2020. According to MSVAR estimation, establishing the time of the financial market crisis correlates with the period of higher volatility in the foreign currency market. Thus, the article's novelty is to proactively seize opportunities development prospects and prevent risks towards sustainable development, and strategic solutions are needed.

Forecasting Stock Exchange Data using Group Method of Data Handling Neural Network Approach

The increasing uncertainty of the natural world has motivated computer scientists to seek out the best approach to technological problems. Nature-inspired problem-solving approaches include meta-heuristic methods that are focused on evolutionary computation and swarm intelligence. One of these problems significantly impacting information is forecasting exchange index, which is a serious concern with the growth and decline of stock as there are many reports on loss of financial resources or profitability. When the exchange includes an extensive set of diverse stock, particular concepts and mechanisms for physical security, network security, encryption, and permissions should guarantee and predict its future needs. This study aimed to show it is efficient to use the group method of data handling (GMDH)-type neural networks and their application for the classification of numerical results. Such modeling serves to display the precision of GMDH-type neural networks. Following the US withdrawal from the Joint Comprehensive Plan of Action in April 2018, the behavior of the stock exchange data stream and commend algorithms has not been able to predict correctly and fit in the network satisfactorily. This paper demonstrated that Group Method Data Handling is most likely to improve inductive self-organizing approaches for addressing realistic severe problems such as the Iranian financial market crisis. A new trajectory would be used to verify the consistency of the obtained equations hence the models' validity.

401(k) Plan Asset Allocation, Account Balances, and Loan Activity in 2018

The bulk of 401(k) assets were invested in stocks. On average, at year-end 2018, 63 percent of 401(k) participants’ assets were invested in equity securities through equity funds, the equity portion of balanced funds, and company stock. Twenty-eight percent of assets were in fixed-income securities such as stable value investments, bond funds, money funds, and the fixed-income portion of balanced funds. More 401(k) plan participants held equities at year-end 2018 than before the financial market crisis (year-end 2007), and most had the majority of their accounts invested in equities. For example, about three-quarters of participants in their twenties had more than 80 percent of their 401(k) plan accounts invested in equities at year-end 2018, up from less than half of participants in their twenties at year-end 2007. Overall, more than 90 percent of 401(k) participants had at least some investment in equities at year-end 2018. More than three-quarters of 401(k) plans, covering more than three-quarters of 401(k) plan participants, included target date funds in their investment lineup at year-end 2018. At year-end 2018, 27 percent of the assets in the EBRI/ICI 401(k) database were invested in target date funds and more than half of 401(k) participants in the database held target date funds. Also known as lifecycle funds, these funds are designed to offer a diversified portfolio that automatically rebalances to be more focused on income over time. In an ongoing collaborative effort, the Employee Benefit Research Institute (EBRI) and the Investment Company Institute (ICI) collect annual data on millions of 401(k) plan participants as a means to examine how these participants manage their 401(k) plan accounts. This report is an update of EBRI and ICI’s ongoing research into 401(k) plan participants’ activity through year-end 2018. The report is divided into four sections: the first describes the EBRI/ICI 401(k) database; the second presents a snapshot of participant account balances at year-end 2018; the third looks at participants’ asset allocations, including analysis of 401(k) participants’ use of target date, or lifecycle, funds; and the fourth focuses on participants’ 401(k) loan activity.

The Value of Registered Investment Advisors during the COVID-19 Financial Market Crash - Evidence from 13F and Twitter

The ongoing public health crisis associated with the COVID-19 pandemic has had a significant impact on business activities, government at large, financial markets, and individual households. This study is the first to our knowledge that seeks to examine the 2020 financial market crisis using manually downloaded data, which combined 13F filing with ADV forms with tweets from Registered Investment Advisors. We find that even during extremely negative return days, financial advisors communicate frequently and positively with their clients. Clients working with financial advisors tend to sell less and buy more during a market downturn as compared with self-discretionary clients.

Limits of resolution tools under the BRRD and the Czech act on recovery procedures and the financial market crisis resolution

Given the unique position of credit institutions and their systemic importance for the financial stability, their resolution has been traditionally entrusted to supervisory authorities rather than courts. As a result, credit institutions are essentially excluded from the scope of “traditional” insolvency procedure and fall under the resolution regime constituting specific form of administrative proceedings. Directive 2014/59/EU of the European Parliament and of the Council (known as the BRRD) is of a particular consequence here as it harmonized the resolution process at the level of the European Union and the European Economic Area, inter alia through the implementation of specific resolution tools. This article deals with conditions for applicability of such resolution tools, their fundamental mechanics as well as legal implications arising thereunder, considering also the Act on Recovery Procedures and the Financial Market Crisis Resolution under which the BRRD has been implemented into Czech law.

Developing the methodology of early diagnosis of financial crises using a system of signaling economic indicators

Subject. This article discusses new possibilities for diagnosing the state of the country's financial and economic system and monitoring the true signs of crisis phenomena. Objectives. The article aims to develop effective methods of diagnosing and predicting financial crises in Russia using a special system of economic indicators and digital analytical tools. Methods. For the study, we used the signaling approach, non-parametric and mathematical statistics, and econometric modeling. Results. The article proposes a developed methodology for diagnosing crisis events, and tested on the basis of a sample of official data of the Federal State Statistics Service, the Ministry of Finance of the Russian Federation, the Central Bank of the Russian Federation, and the exchange information of the world financial markets for 1998–2019. Conclusions. The study confirmed the prospects for using a signaling approach in combination with the binary choice model and econometric modeling methods to predict the onset of crisis events in the Russian economy. The proposed methodology for diagnosing financial market crises contributes to the development of scientific approaches to the analysis and forecasting of the price dynamics of financial markets and periods of their increased volatility. Its practical implementation provides information on emerging trends in financial and economic instability and assesses the likelihood of a financial crisis.

The Impact of the Covid-19 Crisis on Financial Markets: The Case of Turkey

The main purpose of this study, the example of Turkey Covid-19 is analyzing the effects of the financial market crisis. In this way, it has been tried to contribute to the literature on the effects of Covid-19 on the markets. Daily data for the period 16.03.2020-21.08.2020 were taken into account in the analyzes. In analyzing the relationships between variables, besides ADF Unit Root Test, Zivot-Andrews Unit Root Test with structural break and Toda-Yamamoto Causality Test were used. According to the ADF unit root test results, all variables were found to be stationary at the first level. According to the Zivot-Andrews test, although the degree of stability of the GOLD series is 2, when the correlogram of the series is examined, it is determined that the first difference is stationary. Bivariate VAR models, one of which is the CASE (VAKA) variable and the other the financial variable, were created to determine the causality relationships between Covid-19 daily case numbers (VAKA) and other financial indicators. Schwarz Information Criterion (SIC) was used to determine lag lengths related to Toda-Yamamoto causality tests. According to the Toda-Yamamoto causality test results, a statistically significant causality was determined from the number of cases to the Euro and USD (Dollar) exchange rate.

Dynamics of the Global Stock Market Networks Generated by DCCA Methodology

A group of stock markets can be treated as a complex system. We tried to find the financial market crisis by constructing a global 24 stock market network while using detrended cross-correlation analysis. The community structures by the Girvan-Newman method are observed and other network properties, such as the average degree, clustering coefficient, efficiency, and modularity, are quantified. The criterion of correlation between any two markets on the detrended cross-correlation analysis was considered to be 0.7. We used the return (rt) and volatility (|rt|) time series for the periods of 1, 4, 10, and 20-year of composite stock price indices during 1997–2016. Europe (France, Germany, Netherland, UK), USA (USA1, USA2, USA3, USA4) and Oceania (Australia1, Australia2) have been confirmed to make a solid community. This approach also detected the signal of financial crisis, such as Asian liquidity crisis in 1997, world-wide dot-com bubble collapse in 2001, the global financial crisis triggered by the USA in 2008, European sovereign debt crisis in 2010, and the Chinese stock price plunge in 2015 by capturing the local maxima of average degree and efficiency.

Empirical Credit Spread Components of Banks and their Coverage in Structural Models – An Integrated Analysis

During the global financial crisis and euro crisis, credit spreads of European banks have increased sharply, which has not only been attributed to default risk. Credit spreads can be estimated empirically or using structural models. In the KMV model, a firm defaults if the market value of assets falls below the Default Point (DP) based on liabilities. The Distance-to-Default (DD) measures how many standard deviations the asset value is away from DP. Based on DD, Moody's Analytics calculates a physical probability of default, the Expected Default Frequency (EDF). The paper analyzes the relation between the KMV structural model and empirical credit spread components. In addition to default risk, empirical credit default swap (CDS) spreads compensate risk-averse investors for liquidity risk and common spread risk. Default risk can generally be divided into a diffusion and jump component. Fundamental structural models cover default by a continuous decrease in the asset value below the default barrier, while unexpected jumps or (liquidity) shocks – such as bank runs – are not captured. Comparing model-based bank EDFs and empirical CDS-implied default probabilities, with a special focus on financial market and liquidity crises, the residual risks are derived. In contrast, previous studies primarily consider non-financial firms and phases of low financial market volatility. The present empirical study is the first integrated analysis of the determinants of one-year CDS spreads and the EDF of European banks from 2004 to mid-2015. Using a panel regression with time fixed effects, the residual impact on the logarithmized CDS-implied default probability, that cannot be explained by the logarithmized EDF, is decomposed into a systematic and idiosyncratic component. Since the global financial crisis and especially during the euro crisis, the EDF structural model assesses the default probabilities of European banks to be lower than the CDS market does – due to market-wide risks. The systematic residual impact increases substantially at the outbreak of both financial market and liquidity crises. At the onset of the global financial crisis and euro crisis, in particular market-wide liquidity risks imply a stronger increase in CDS spreads compared to EDFs. Combining market-based signals from European bank CDS spreads with model-based signals in an integrated analysis, the risk of a financial market crisis is derived. Market-wide indicators of funding and liquidity risk provide a statistically significant and economically important explanatory power for the systematic residual impact. Moreover, the risk premium is an essential determinant. Compared to alternative crisis indicators, the systematic residual impact achieves an equally good and during the euro crisis even better performance.

Lkw-Verkehrsdaten in der Konjunkturanalyse: Eine Anwendung für die bayerische Wirtschaft

Gross domestic product (GDP) figures for Germany's 16 federal states are currently only published twice a year, with no quarterly figures available. This makes it impossible to pinpoint the exact timing of turning points in the economies of individual states. However, industrial production provides a practical alternative. To reduce the delay in identifying macroeconomic turning points at state level, the authors examine more promptly available road haulage data, taking Bavaria as an example. Data from the Bundesanstalt fur Strasenwesen and the Zentralstelle Verkehrsmanagement in Bavaria are used to compare truck traffic during the financial market crisis in 2008 and 2009 and during the current corona crisis. For the entire period under review, data on the volume of road transport provides a meaningful indicator with which to identify turning points in manufacturing, and thus in overall production, in the Bavarian economy. However, they show the decline in overall economic output only in very rough terms. Road haulage data provided early signs of an increasing decline in real GDP in Bavaria in the first quarter of 2020, in April and in May. In contrast to the financial crisis of 2008/2009, in the current corona crisis road transport data is responding more strongly than industrial production, which may be explained by the broader sectoral impact of the pandemic.

The Role of Speculators in the Market Crash of 1929

90 years ago – in October 1929 – the crash on Wall Street created chaos in the financial markets. The Great Crash of 1929 led to the Great Depression the longest period of unemployment and contraction in modern history. The market crash of 1929 is considered a unique, five sigma event, occurring only once-in–a-lifetime. Seventy nine years after the Great Crash of 1929 (GC), the financial markets collapsed again in the Global Financial Crisis of 2008 (GFC) and threatened the financial stability of the world like in 1929. Explanations for the causes of a market crash can range from overindebtedness, asset bubbles, speculation to massive leverage in the system. Crises can have different forms ranging from classic hunger crises to modern forms of demand crises, corporate crises and financial market crises. While the causes of a hunger crisis is often the result of a series of poor harvest, the causes of a financial market crisis can be complex and are not always easy to identify. In this paper I focus on the worst financial market crisis in history the GC in the USA. It was argued that funds and short sellers were the culprits of the crisis, and that they benefited from it. This paper covers the speculators in the GC by analysing their role, their strategies and their returns. I introduce an analysis of the role of speculators in their function as either liquidity providers or liquidity takers. As far as the theory of speculation is concerned I use Minsky’s Financial Instability Hypothesis. The analysis shows that in a systematic crisis there are no winners and there is no place to hide.

Threshold cointegration, nonlinearity, and frequency domain causality relationship between stock price and Turkish Lira

Modelling complex asymmetric effects and non-linear relationships between exchange rate and stock prices has challenged classical econometric methods. This study contributes to the relative literature in the following distinct ways. First, we follow a variety of econometric approaches in order to characterize the complex dynamic co-movements between Turkish stock market and exchange rate from January 2003 to December 2018. Secondly, we show that the evidence for asymmetric threshold cointegration in Turkey’s financial market can be hidden by following linear time series methodologies. Thirdly, it is also worth noting that the real effective exchange rate, USD-Turkish lira exchange rates, money supply and interest rates have large predictive power for stock price fluctuations at various frequencies. Building on these insights, we claim that asymmetry (nonlinearity) is particularly important in Turkey’s financial market because it shows the need for a new pattern of policy measures to prevent financial market crisis risk in Turkey.

Labor Market Uncertainty and Pension System Performance

The financial market crisis has prompted policymakers to devote substantial attention to ways in which capital market risks shape pension performance, but few analysts have asked how shocks to human capital shape retirement wellbeing. Yet human capital risks due to fluctuations in labor earnings, employment volatility, and survival, can have a profound influence on pension accumulations and payouts. This paper reviews existing studies and offers a framework to think about how human capital risk can influence pension outcomes. We conclude with thoughts on how future analysts can better assess sensitivity of pension plan outcomes to a labor income uncertainty.

Testimony of Erik F. Gerding Before the U.S. House of Representatives Subcommittee on Consumer Protection and Financial Institutions on 'Emerging Threats to Stability: Considering the Systemic Risk of Leveraged Lending'

Risk is building in the leveraged loan and collateralized loan obligation (“CLO”) markets. These two markets are connected: leveraged loans are being repackaged into CLOs just as mortgages and mortgage-backed securities were used to create collateralized debt obligations (“CDOs”), the financial products at the heart of the financial crisis 11 years ago. There are important differences but also troubling parallels between the leveraged loan/CLO markets and the earlier mortgage/CDO markets. One alarming similarity is the decline in leveraged loan underwriting standards: the market is now dominated by “covenant-lite loans.” Covenant-lite loans permit greater leverage by borrowers and remove an early warning system for lenders. Purchases of CLOs by banks and other regulated financial institutions made in order to game crucial regulatory capital requirements (“regulatory capital arbitrage”) remain a significant concern . Like mortgages and CDOs, leveraged loans and CLOs form a pipeline or system. Disruptions at either end of the system can cause financial havoc on the other end and then ricochet back. This is akin to a coiled spring or “crisis accordion.” Losses or disruptions in the leveraged loan/CLO markets, even if they do not approach the levels of mortgages/CDOs in the global financial crisis could still be significant, e.g., amplifying a recession. We should be humble about our ability to predict the upper bound of financial market disruptions or crises. Some tranches of CLO securities appear not to trade actively. Many CLO securities trade on opaque markets lacking transparent prices. A lack of trading of CLO securities undermines the economic rationale of these securities, as well as their safety and favorable regulatory treatment. A lack of transparent prices means that neither the marketplace nor regulators can rely on prices to police risk-taking in the CLO market. Regulators must monitor and analyze data on leveraged loans and CLO markets. The OFR needs cooperation from other financial regulators in assessing risk in these markets. Lack of data sharing among financial regulators remains a crucial weakness. The OFR needs an independent source of funding. Regulators need minimum standards in their examinations with respect to assessing bank exposure to leveraged loans. I also recommend: - Stress testing of financial markets, not just individual institutions; - Requiring financial regulators to conduct war games to prepare for market disruptions; - Underscoring that the burden is on financial institutions to prove that leveraged loans and CLOs are safe rather than on regulators to prove that they are unsafe. If data gathering reveals significant systemic risk in leveraged lending/CLO markets, regulators should use a mix of tools, including limiting bank investments in CLOs, enhanced and countercyclical capital requirements, and the Volcker Rule “covered funds” provisions.

Dynamic behaviors and measurements of financial market crash rate

This paper proposes the conditional crash rate (CCR) to study the degree of financial market crisis and evaluate the risk of financial market crash, based on maximum drawdown and escape rate. It is found that the CCR of stock price in financial market is equivalent to the escape rate of the drawdown time series corresponding to price series. Based on the mean escape rate, the analytical solution of CCR of financial market of stock price described by Black–Scholes model is obtained. For the CCR, empirical researches show that the theoretical results of the Heston model are in good agreement with the results of the real financial data of the S&P 500. The parameters of Heston model are estimated based on the least square estimation of the mean square error of probability density of return between the proposed model and S&P 500 data set. Then, we discuss the dynamic behaviors of CCR and the results indicate that (i) the monotonic and non-monotonic features are observed in the behaviors of CCR as a function of system parameters; (ii) we can find critical phenomena, resonance and inverse resonance behaviors in the function of CCR vs. mean reversion of volatility; (ii) the parameter variation induces the appearance of noise enhancement stability in the function of CCR vs. amplitude of volatility fluctuation.

Modern approaches to the crisis management of hotel enterprises, used in world practice

The concept of "crisis management" entered into everyday use among the managers of hotel enterprises relatively recently. As a practical discipline, crisis management began to actively develop in the 1990s. It was at this time that the objects and subjects of crisis management were determined, different approaches to definition were outlined, tasks, methods, and methods for solving them were formed. The article considers the existing approaches to the definition of crisis management, proposed by Russian and foreign scientists. The most interesting definitions of crisis management, which are used in the hotel business, are indicated. In the framework of the above definitions, examples are given on the implementation of crisis management in practice (in Russia and in foreign countries). Particular attention is paid to the classification of crises that affect the activities of hotel enterprises. Internal and external factors influencing the development of the hotel business are highlighted, and their ranking has been carried out. According to the results of the study, the shortcomings of the approaches to crisis management are presented, and a personal interpretation of the definition is proposed. World experience shows that crisis management was interested in scientists and practitioners from various fields: management, economics, finance, law, mathematical modeling, econometrics, programming, etc. Moreover, interest in crisis management arose most often at times when the world economy underwent a number of negative impacts. Currently, these phenomena have become quite frequent. Due to the fact that the markets and industries of the world have become interconnected, the financial market crisis leads to a decline in the development of the tourism industry, which in turn affects the hotel business.

Reinforcement of pension financialisation as a response to financial crises in Germany, the Netherlands and the United Kingdom

ABSTRACTThe financial market crises of 2001/02 and 2007/08 and the sovereign debt crisis that started in 2011 had adverse effects on financialised pensions such as pension funds. In general, moments of crises are major shocks to existing equilibriums and policies and open windows of opportunity for policy change. Did these crises trigger a slowdown or reversal of pension financialisation? This article finds that Germany, the Netherlands and the United Kingdom took similar steps along the pension financialisation path by intensifying the reliance of pension funds on financial markets despite the occurrence of three financial crises. The reinforcement of pension financialisation can be explained by the entrenched interests of several actors in finance, employers, the state, and trade unions, who have no interest in the collapse of pension funds.

A dynamic target volatility strategy for asset allocation using artificial neural networks

ABSTRACTA challenge to developing data-driven approaches in finance and trading is the limited availability of data because periods of instability, such as during financial market crises, are relatively rare. This study applies a stability-oriented approach (SOA) based on statistical tests to compare data for the current period to a past set of data for a stable period, providing higher reliability due to a more abundant source of data. Based on an SOA, this study uses an artificial neural network (ANN), which is one of the commonly applied machine learning algorithms, for simultaneously forecasting the volatility and classifying the level of market stability. In addition, this study develops a dynamic target volatility strategy for asset allocation using an ANN to enhance the ability of a target volatility strategy that is established for automatically allocating capital between a risky asset and a risk-free cash position. In order to examine the impact of the proposed strategy, the results are compared to the buy-and-hold strategy, the static asset allocation strategy, and the conventional target volatility strategy using different volatility forecasting methodologies. An empirical case study of the proposed strategy is simulated in both the Korean and U.S. stock markets.

Economic growth, financial market, and twin crises

ABSTRACTIn this study, we look not only to provide empirical evidence to investigate the direct impact of financial crises on economic growth, but also to examine the roles of insurance development, financial liberalization, financial institution, and crisis intervention policies on the relationship between the two. We employ a panel data framework from 50 countries by applying the dynamic panel generalized method of moments model. Our main empirical results show that financial crises do have a significantly negative impact on economic growth. In addition, governments or authorities are encouraged to further enhance their insurance sector in order to help spur economic growth when financial crises arise. The government intervention policy choice is also an important factor influencing economic growth during crises.

Effects of Monetary Policy during Financial Market Crises and Regime Changes: An Empirical Evaluation Using a Nonlinear Vector Autoregression Model

Using monthly data for Korea, this study examines nonlinear effects of monetary policy in association with financial market distress. The study uses a nonlinear vector autoregression model and finds that monetary policy becomes ineffective for addressing huge demand contractions in times of financial market turmoil or severe economic downturn, implying a structural change from a non‐Keynesian to a Keynesian regime, such as a liquidity trap. Monetary contractions have stronger output effects than monetary expansions, particularly in times of financial distress. We found no evidence in favor of asymmetric effects of monetary shocks of different sizes. Finally, we also found financial shocks to have stronger effects on the real economy in times of financial distress than in normal times. The results have important policy implications for periods of financial turmoil or economic crisis.