Market Crash Research Articles

The impact of social financing structures on different industry sectors: A new perspective based on time-varying and high-dimensional methods

<abstract> <p>With the continuous innovation of financial instruments, the financing structure presents a diversified development trend, and the proportion of direct financing in Aggregate Financing to the Real Economy (AFRE) has been increasing. We utilized monthly data from January 2002 to March 2023 to establish a time-varying spillover index model and a large TVP-VAR model in order to investigate the dynamic impact of the social financing structure on various industry sectors. The empirical results suggested that the impact of financing structure on different industry sectors varies. Direct financing had the least impact on the industry compared to on-balance-sheet financing and off-balance-sheet financing. Lagging effects had the most significant influence on all industries. Furthermore, since 2015, the impact of different industries on the proportion of direct financing has significantly changed, indicating that the impact of direct financing on different industries became apparent during the 'stock crash'. Moreover, the impact of different financing methods on the economic development of various industry sectors was susceptible to external events, and the degree of impact varied. Our results are useful in helping policy makers better understand the changes in different industries affected by the financing structure, which can inform their policy formulation.</p> </abstract>

The Implications of A Recessionary Trend in An Economy and The Role That Monetary Policy, Through Government Intervention, Helps Rectify The Same

This paper delves into the different consequences of a recession and economic downturns through different case studies such as the lost decades in Japan and the Stock market crash in the USA in 2007. Moreover through these case studies the paper establishes a link between financial markets and monetary policy as most recent recession have either been caused by financial crisis or have been preceded by them."As such it explores how the prevalent theoretical framework of monetary policy during the times of Friedman, which tasked monetary policy with fluctuating short term interest rates to meet inflation targets and further be stable in the long term to foster economic growth and feed consumer expectation, has now been usurped by governments to act as a stabiliser of economic downturns such as a recession. Through these case studies it offers a critique of recent expansionary policies undertaken in Japan that have often ignored the long time gap inconsistency problem of Japan which has lead to unconventional yet inconsistent monetary actions in Japan being unable to solve the recession. This critique is furthered through its comparison tot he actions of the FED that suggest monetary policy is best used aggressively over the long term to foster consumer expectations and thus return confidence in the economy and the credit system after a recession. This is supported by different IMF investigations discussed in the paper which reveal the importance of aggressive monetary policy with the support of fiscal stimulus to best solve a recession. Finally this paper then seeks to determine the implications of a recessionary trend in an economy and the role that Monetary policy, through government intervention, helps rectify the same.

IVESA - Visual Analysis of Time-Stamped Event Sequences.

Time-stamped event sequences (TSEQs) are time-oriented data without value information, shifting the focus of users to the exploration of temporal event occurrences. TSEQs exist in application domains, such as sleeping behavior, earthquake aftershocks, and stock market crashes. Domain experts face four challenges, for which they could use interactive and visual data analysis methods. First, TSEQs can be large with respect to both the number of sequences and events, often leading to millions of events. Second, domain experts need validated metrics and features to identify interesting patterns. Third, after identifying interesting patterns, domain experts contextualize the patterns to foster sensemaking. Finally, domain experts seek to reduce data complexity by data simplification and machine learning support. We present IVESA, a visual analytics approach for TSEQs. It supports the analysis of TSEQs at the granularities of sequences and events, supported with metrics and feature analysis tools. IVESA has multiple linked views that support overview, sort+filter, comparison, details-on-demand, and metadata relation-seeking tasks, as well as data simplification through feature analysis, interactive clustering, filtering, and motif detection and simplification. We evaluated IVESA with three case studies and a user study with six domain experts working with six different datasets and applications. Results demonstrate the usability and generalizability of IVESA across applications and cases that had up to 1,000,000 events.

The Impact of Covid -19 Pandemic in Development Banks’ Stock Performance Evidence from Nepal

Propose: This study explores the relationship between COVID-19 and the stock market in Nepal from February 15th, 2020, to February 15th, 2023, with a focus on the impact on development banks. Adopting a descriptive research design, the study analyzes the risk and fluctuation in stock prices of development banks during the pandemic. The first half of 2020 witnessed a significant stock market crash due to the global spread of COVID-19 and subsequent economic disruptions caused by lockdowns. Methods: The study examines how different sectors within the stock market reacted to COVID-19, with sectors like natural gas and healthcare showing positive returns, while others like petroleum and entertainment experienced declines. It emphasizes the tradeoff between risk and return in inancial management, highlighting investors' demand for compensation for bearing risk. Findings: The findings suggest that development banks in Nepal faced increased risk and fluctuation in stock prices during the pandemic. However, the study also reveals opportunities for investors, as economic crises can create investment prospects. Contrary to some literature, the study indicates that the market index in Nepal showed positive correlations with the number of COVID-19 cases, deaths, recoveries, and active cases, suggesting no significant impact of COVID-19 on the stock market index. Values: This study contributes to understanding the dynamics of the stock market during crises like COVID-19 and provides insights for investors and financial analysts. Keywords: COVID-19, Development banks, Stock market, Stock market capitalization, Impact.

Risk spillovers and extreme risk between e-commerce and logistics markets in China

<p>We first utilized the Bayes positive diagonal BEKK generalized autoregressive conditional heteroskedasticity (Bayes-pdBEKK-GARCH) model to evaluate the risk spillovers between the e-commerce and logistics, then applied the adaptive Fourier decomposition method to measure the extent of these spillovers and detect structural changes. The results showed that there were structural breaks in both markets, which may lead to extreme risks. At last, we applied the GARCH-copula quantile regression model to analyze the extreme risks. We found that: (1) there were asymmetric volatility spillovers and positive correlations between them. (2) The dynamic risk spillovers exhibited heterogeneity over time. The logistics market had a smaller downside risk spillover, while the e-commerce market had a stronger upside risk spillover. (3) The study indicated that important events, such as the Chinese stock market crash, the Sino-U.S. trade friction, the COVID-19 epidemic, and the "either-or choice" monopoly policy of e-commerce platforms, had a significant influence on them, resulting in dramatic risk spillovers.</p>

Oil market crashes: from the subprime crisis to the COVID-19 pandemic

Oil market crashes: from the subprime crisis to the COVID-19 pandemic

A Micro-Level Evidence of how Investor and Manager Herding Behavior Influence the Firm Financial Performance

Using the investor-herding index (IHRB) and manager-herding index (MHRB), the emergence of investors’ and managers’ herding behavior at the corporate-level and its potential impact on firm financial performance (FFP) is analyzed in the entire study. The study utilizes the micro-level data of 296 listed firms of Pakistan stock exchange (PSX) from 2013 to 2017. Empirical findings show that the investors’ and managers’ herding significantly affect FFP. The results are robust under alternative measurements of FFP. This study has a unique contribution to the literature on behavioral finance by addressing the astonishingly overlooked phenomena of firm-level biases and their potential impact on FFP. For prospective investor’s decision, the findings are significant in such way that the market index is irrelevant than the firm-level financial evidence. Explicitly, the study concludes that positive herding behavior is elucidated by the bullish trend and inverse herding behavior of investors with respective to firm value leads toward bearish trend of stock market index. The likelihood of market crash may become more stringent in circumstances once managers and investors interactively exhibit negative herding behavior. Thus, the study offers useful policy and strategy implications for the associated stakeholders to the device the policies accordingly. JEL Code: D9, D21, D91, G11.

Gambling for Recovery? Exploring the Credit Risk of European Insurers’ Bond Portfolios during the Covid-19 Market Crash

Gambling for Recovery? Exploring the Credit Risk of European Insurers’ Bond Portfolios during the Covid-19 Market Crash

The moderating effect of financial constraints on the relationship between stock price crash risk and managerial ability

PurposeThis study aims to empirically explore the influence of managerial ability on crash risk and the moderating effect of financial constraints on this interrelationship.Design/methodology/approachUsing a sample of listed corporations in the Egyptian Stock Exchange during 2018–2021, the authors test the hypotheses by using the measures and methods well established in prior literature. The authors also conduct multiple robustness analyses to ensure the validity of the empirical results.FindingsThe findings suggest that managerial ability can effectively inhibit crash risk. In addition, the authors report that financial constraints significantly dampen this relationship. Thus, financial restrictions play a striking role in hampering the managerial ability to prevent stock crashes. Furthermore, the authors document that the moderating role of severe financing constraints is more prominent during the Covid-19 pandemic period.Originality/valueThe originality of this study stems from the following considerations. First, this study enriches relevant studies on crash risk by providing evidence from one of the emerging markets in the Middle East; thereby, contrasting with those in developed economies. Second, to the best of the authors’ knowledge, this is the first study investigating the moderating impact of financing constraints on the managerial ability and crash risk nexus. Therefore, this work adds value to the extant knowledge by scrutinizing this important issue and providing novel empirical evidence.

Momentum Origin and Investor Behaviors on Wall Street

The Efficient Market Hypothesis (EMH) asserts that consistently outperforming the market is implausible because market prices promptly incorporate all available information. However, the momentum strategy has demonstrated consistent profitability, which poses a significant challenge to the EMH and suggests the presence of factors that extend beyond existing theoretical frameworks in influencing price movements. Here we present a model attributing changes in asset return to behavior interactions between liquidity takers and providers that directly impact price formation and discovery processes. The analysis of the measured behavior of liquidity takers and inferred market microstructure due to behaviors of liquidity providers generates signals relating to the forming, terminating, and reversal of price momentums. Applying these signals to the 1987 market crash yields warning flags about the looming crisis weeks before the sudden market plunge on Black Monday. As market crises always correspond with substantial negative price momentum, our model can serve to mitigate or avoid catastrophic investment losses during such events.

Assessing the linkage of energy cryptocurrency with clean and dirty energy markets

The primary objective of this study is to explore the dynamic connectedness that exists among energy cryptocurrencies, clean energy metals, and conventional dirty energies. Moreover, we aim to investigate the time-varying effects of uncertainties on the connectedness that exists among these asset classes. We uncover heterogeneous reactions among energy cryptocurrencies and other assets. Common positive co-movement clustering is revealed mostly during the periods of the cryptocurrency crash and boom in 2018 and 2020, and the oil market crash, respectively. However, a constant weak and strong co-movement over shorter and longer horizons is observed throughout the sample period for all pairs analysed, with varying outcomes for longer horizons. Combining VIX and US EPU as measures of financial and economic uncertainty, we contend that uncertainty significantly affects energy cryptocurrencies, clean and dirty energies, and clean energy metals, with relatively weak impacts or influences observed for longer investment horizons. Our findings are highly beneficial to cryptocurrency investors, alternative asset investors, and policy makers, especially during periods of market turmoil.

Price monotonicity violations during stock market crashes: Evidence from the SSE 50 ETF options market

AbstractThis study empirically tests whether price violations, as defined by Bakshi, Cao, and Chen (2000), show different patterns in response to market shocks. Specifically, we analyze the Chinese options market during a period covering a stock market crash and a series of trading restrictions in the Chinese derivatives markets. Our results confirm the significant changes of the defined violations in the face of unexpected shocks, and more importantly, we interpret such variations from the perspective of information spillovers. Our findings suggest that the stock market crash prompts informed traders in the Chinese options market to frequently adjust their positions on put options, exacerbating the misunderstandings and overreactions to new information. Further, the regulatory shock in the derivatives markets diminishes the efficiency of information incorporation for both options and spot markets but does not affect the dominance of the Chinese options market in price discovery.

Market return spillover from the US to the Asia-Pacific Countries: The Role of Geopolitical Risk and the Information & Communication Technologies.

This study examines the market return spillovers from the US market to 10 Asia-Pacific stock markets, accounting for approximately 91 per cent of the region's GDP from 1991 to 2022. Our findings indicate an increased return spillover from the US stock market to the Asia-Pacific stock market over time, particularly after major global events such as the 1997 Asian and the 2008 global financial crises, the 2015 China stock market crash, and the COVID-19 pandemic. The 2008 global financial crisis had the most substantial impact on these events. In addition, the findings also indicate that US economic policy uncertainty and US geopolitical risk significantly affect spillovers from the US to the Asia-Pacific markets. In contrast, the geopolitical risk of Asia-Pacific countries reduces these spillovers. The study also highlights the significant impact of information and communication technologies (ICT) on these spillovers. Given the increasing integration of global financial markets, the findings of this research are expected to provide valuable policy implications for investors and policymakers.

Minority state ownership and firm performance: Evidence from the Chinese stock market crash in 2015

AbstractWe examine the effect of minority state ownership on firm performance using the Chinese stock market crash in 2015. We find that treatment firms with minority state ownership accumulated from governmental purchases of equities experience significant reductions in operating performance. The negative impact is more severe in firms with higher riskiness and firms with less powerful large shareholders. We also find that treatment firms’ risk decreases and their employment increases after minority state shareholders step in, providing supportive evidence on the government's motives of reducing risk and preventing mass layoffs. Further tests reveal the channels through which minority state ownership impedes investment efficiency, productivity, and innovation. The negative impact diminishes when government institutions divest their shares in a timely manner. Overall, our results suggest there are unintended negative consequences of minority state ownership arising from the governmental rescue package in a market crisis.

Real estate investment trusts during market shocks: Impact and resilience

The market value of a stock is a function of firm performance and market sentiment. Specific events can alter returns and present several challenges to market performances. Through an event study design, this study examines five real estate investment trusts (REITs) market indices’ responses to market shock from the initial COVID-19 outbreak. The results revealed negative cumulative abnormal returns for lodging, health care, and retail REITs over the 20-day trading window. Considering their lower drawdown losses, the remaining REIT sectors showed greater resilience than their counterparts. Block bootstrapping confirmed the returns were significantly worse for all sectors, with retail and lodging sectors having the poorest returns. This study advances the literature on pandemic-related market crashes along with how COVID-19 affected cross-sector REIT equities compared to other market indices. REIT firms can use the findings to develop more effective policy measures as responses to pandemic market conditions.

TESTING MARKET EFFICIENCY: THE ROAD TO INTRINSIC VALUATION

The paradigm of market equilibrium and the “efficient-market hypothesis” tied to it, dealing specifically with the behavior of capital markets, has no explanation for financial bubbles and their bursting that is leading to stock market crashes. Accordingly, the main goal of this paper is to discuss the inefficiency of markets, with examples of corporate decisions that directly abuse such inefficiency to psychologically motivate desired behavior of potential customers. To test the efficiency market hypothesis, we have used Stoxx Europe 600 index historical closing daily prices, for the period from 2012–2022. Using both non-parametric and parametric tests, such as the Kolmogorov–Smirnov test, run–test for random order, and ARIMA regression, we reject the hypothesis that the market is efficient in a weak form because it doesn’t follow a random walk. Also, basic-level problems of economic theory were analyzed, emphasizing the view that perhaps the time has come to align the fundamentals of economic theory with basic concepts that have been used in practice for years.

Convergence Rate of the Diffused Split-Step Truncated Euler–Maruyama Method for Stochastic Pantograph Models with Lévy Leaps

This paper studies the stochastic pantograph model, which is considered a subcategory of stochastic delay differential equations. A more general jump process, which is called the Lévy process, is added to the model for better performance and modeling situations, having sudden changes and extreme events such as market crashes in finance. By utilizing the truncation technique, we propose the diffused split-step truncated Euler–Maruyama method, which is considered as an explicit scheme, and apply it to the addressed model. By applying the Khasminskii-type condition, the convergence rate of the proposed scheme is attained in Lp(p≥2) sense where the non-jump coefficients grow super-linearly while the jump coefficient acts linearly. Also, the rate of convergence of the proposed scheme in Lp(0<p<2) sense is addressed where all the three coefficients grow beyond linearly. Finally, theoretical findings are manifested via some numerical examples.

Hearding during COVID-19 pandemic: An empirical study in Vietnamese stock market

This paper investigates herd behavior in the Vietnam stock market under the impacts of the COVID-19 pandemic. Using Chang et al.’s (2000) method on two sets of daily and weekly trading data ranging from January 2018 to December 2021, we provide evidence about the presence of herd behavior during the global health crisis but not in the period prior to the outbreak of COVID-19. In addition, the regression analysis of a modified model implies that the tendency of herding among investors in the Vietnam stock market became more prevalent as the pandemic became more severe and the government measures to mitigate the pandemic turned out to be more stringent. These findings suggest that Vietnamese regulators may help to stop or mitigate the impact of any potential stock market crashes and that new investors need to acquire more knowledge about the market and skills for investing.

Research on the Efficacy of the iVIX Index Based on VIX Pricing

ABSTRACT Amidst rising trading volumes, there’s evident demand for volatility trading. This study assists Chinese stakeholders in understanding the iVIX’s functionality, offering insights for investments and policy-making. Building on the VIX option pricing model, the research introduces a novel approach: the mean-reverting logarithmic stochastic volatility Hawkes jump model (MLSVHJ). Using VIX call option data from March 9, 2020, to March 18, 2021, the MLSVHJ model outperformed four others during 2020’s three US market crashes. Additionally, this model’s parameters aligned well with theoretical expectations. However, the positive correlation observed between the iVIX and the Shanghai Composite Index prompts a reevaluation of applying global VIX standards directly to China.

The global spillovers of unconventional monetary policies on tail risks

This article analyzes the risk spillovers of UMPs of four major central banks on the expectations of a market crash in foreign equity markets. The empirical findings show that forward guidance measures exhibit a significant cross-border impact on tail risks. Other expansionary UMPs are innocuous on inducing risk spillovers to other economies. A classification of reversal UMPs into contractionary and tapering provides opposite conclusions: contractionary UMPs shocks exhibit a strong and negative cross-border impact on the tail risks of other economic areas, contrary to tapering announcements. Both the Fed and ECB unconventional policies induce significant risk spillovers with similar magnitudes.