Subprime Crisis Research Articles

Investment Strategies in Turbulent Times: A Comparative Analysis of Developed and Emerging Markets

ABSTRACT This study examines portfolio diversification between emerging (China, Malaysia, the Philippines, and Thailand) and developed markets (the USA, UK, Singapore, Hong Kong, and Australia) from January 2006 to August 2022 using MGARCH-DCC analysis. Malaysia’s stock index shows low volatility but a declining trend. The USA index offers the lowest volatility and correlation, making it ideal for diversification with Asian markets. The Philippine index also provides diversification benefits. However, China’s and Thailand’s indices pose risks due to high volatility. Correlations spiked during the 2007 subprime crisis but later stabilized. The findings guide investors on diversification strategies and highlight caution with volatile markets.

Financial Connectedness and Contagion Risk in a Dual Banking System

The 2008 subprime mortgage crisis laid bare the vulnerabilities inherent in financial interdependencies, where shocks originating from one sector and entity rapidly disseminated through complex networks, engendering a contagion effect that reverberated across the banking system. The present paper offers a comprehensive exploration of systemic risk, financial interconnectedness, and contagion within the context of a dual banking system. This appears to be a particular problem because of the heterogeneous market structure, which raises major questions about financial stability. Recognizing the profound implications of the interplay between Islamic and conventional banks, this study employs a comprehensive framework to dissect the intricate dynamics at play. The results reveal the existence of significant interconnectivity, which experiences a notable augmentation during periods of turmoil. Additionally, we provide an analysis of the topological structure of the interlinkage between Islamic and conventional banks, indicating substantial transmission of volatility, both unidirectionally and bidirectionally, across intersectoral and intrasectoral domains. However, our findings indicate that both incoming and outgoing connectivities are primarily influenced by the conventional banking sector.

CAUSES OF THE GLOBAL FINANCIAL CRISIS: POTENTIAL IMPACTS ON THE WORLD AND TURKISH ECONOMY

The global-scale crisis that quickly affected the entire world, originating in the United States, resulted in a dramatic increase in housing prices due to the widespread issuance of home (mortgage) loans to the public without much consideration for repayment capacity, fueled by the surge in demand. Subsequently, problems arose uncontrollably, especially for individuals with low incomes using variable interest rate mortgage loans, as the Federal Reserve (FED) also increased interest rates. The difficulties stemmed from the inability of these individuals to repay the loans, particularly those with variable interest rates, leading to what can be called "subprime mortgages." The securitization of these troubled loans and their grounding in derivative financial instruments, coupled with numerous banks transferring these contracts to each other, resulted in troubled stocks and derivative contracts experiencing significant global crisis due to excessive value losses. As the banking sector forms the cornerstone of financial markets and economies worldwide, the crisis that began in the banking sector rapidly and negatively impacted not only global banks but also developing and even developed country economies through a domino effect. This study aims to analyze the effects of the global crisis on the world countries and Turkey, along with the causes and consequences, based on the U.S. mortgage market.

Are risk disclosures in financial reports informative? A text mining-based perspective

This paper studies whether the risk factors disclosed in financial reports are as informative as SEC requires. The subprime crisis is used as a typical real-risk event to test their informativeness by text mining methods. By analyzing the textual attributes and specific contents of the risk disclosures in 14089 Form 10-K statements of 1,685 financial firms from 2006 to 2022, the results show that firms tend to disclose risks in more specific and negative language and significantly reduce stickiness and boilerplate during the subprime crisis. This paper also finds that the changes of risk factors are consistent with the actual risk profile before, during and after the subprime crisis. The failed institutions during the crisis have disclosed more risks related to the subprime crisis using a more negative tone than the survived institutions. These findings all provide evidence that the risk factors in Form 10-K are informative and not invariable boilerplate.

Rethinking predation under financialisation through the history of subprime mortgages: a case of raiding finance

ABSTRACT The ‘rentier’ model provides an influential framework for conceptualising the predatory traits of financialisation. It asserts that financialisation has empowered a class of rentiers who wield influence by controlling scarce money and charging others for its use. The development of subprime mortgages is often cited as a prime example of rentier exploitation, wherein banks capitalised on historically marginalised borrowers. This article revisits this history to argue that predation under financialisation has historically deviated from rentierisation. Specifically, subprime mortgages were not developed by entities fitting the rentier model, but rather by real estate actors operating outside the established financial system. The latter developed predatory capabilities by virtue of their ability to secure substantial funds through debt, thus reducing reliance on their own capital. This led to the creation of subprime mortgages, loans focused on home-equity stripping, which were crucial to sustain their funding model. Building on these insights, this study introduces the concept of ‘raiding’ as a form of predation that emphasises practices centred on the rapid extraction of money, alongside more traditional forms of rentierism.

The Impact of the US Subprime Mortgage Crisis

The subprime mortgage crisis has a huge impact on American society, it makes a lot of countries get into financial crisis too. A lot of countries economy goes downturn. It is due to the lack of supervision of the U.S. financial industry, and with the need for rapid economic recovery, led to the financial crisis in the later years, and the U.S. economy fell into negative growth. Subsequently, the U.S. strengthened the supervision of the financial market in order to restore the U.S. economy. The significance of this article is to analyze the economic impact of subprime mortgages on the United States and to study some wrong policies behind the prosperous U.S. economy. The policy which commended by this article are that the national economic development should not focus on the short-term, but on longterm development. Loans should be given to small and medium-sized enterprises to promote the progress of social and economic development.

Exploring the impact of loans on credit risk management in Spanish systemic banks

PurposeThis research analyses the solvency behaviour of systemically important (or systemic) Spanish banks, focusing on their credit risk management during the subprime mortgage crisis and the COVID-19 pandemic.Design/methodology/approachThe top three Spanish banks (BBVA, Banco Santander and Caixabank) were selected as a representative sample. Key indicators, such as the volume of assets, amount of financing or loans to clients, non-performing loan (NPL) ratio, reported volume of write-offs, equity and share capital, were analysed to assess their solvency and credit risk management. Furthermore, from the variables evaluated, a structural equation model has been proposed to evaluate the structural relationships among the variables.FindingsThe results indicate a significant reorganisation of these institutions after the subprime crisis. This reorganisation was crucial for providing the necessary room to manoeuvre to overcome the challenges posed by the COVID-19 crisis. However, the study highlights the importance of implementing preventive management policies to handle future crises effectively.Originality/valueThis study provides valuable insights into the solvency and credit risk management of systemic Spanish banks during two major financial crises. The evidence presented is particularly relevant for bank managers and policymakers, offering guidance on effective credit risk treatment and crisis management strategies.

Impact of crisis events on stock market volatility and risks

The COVID-19 crisis, which occurred in 2020, brought crisis events back to the attention of scholars. With the increasing frequency of crisis events, the influence of crisis events on stock markets has become more obvious. This paper focuses on the impact of the subprime crisis, the Chinese stock market crash crisis and the COVID-19 crisis on the volatility and risk of the world’s major stock markets. In this paper, we first fit the volatility using EGARCH model and detect asymmetry of volatility. After that, a VaR model is calculated on the basis of EGARCH to measure the impact of the crisis event on the risk of stock markets. This paper finds that the subprime crisis has a significant influence on the risk of the stock market in China, US, South Korea, and Japan. During the COVID-19 crisis, there was little change in the average risk of each country. But at the beginning of the COVID-19 crisis, there was a significant increase in the risk of each country’s stock market. The Chinese stock market crash crisis had a more pronounced effect on the Chinese and Japanese stock markets and a lesser effect on the US and Korean stock markets.

Currency power as a medium: Revisiting international cost transfer mechanisms in the U.S. subprime crisis

This paper endeavors to meticulously examine the disparities in developmental trajectories between industrialized and emerging economies, employing the nuanced concept of cost transfer within the theoretical framework of the "core-periphery" paradigm. We propose an intricate conceptual model to delve into the mechanisms through which economic crises are systematically shifted from the developed core to the peripheral developing regions, with particular emphasis on the pivotal roles of monetary hegemony and geopolitical dominance. Utilizing the U.S. subprime mortgage crisis as a seminal case study, we scrutinize the intricate dynamics of cost transfer, elucidating how the developed nations leverage their monetary supremacy and geopolitical prowess, often bolstered by military might and neo-liberal ideologies, to facilitate the offloading of inflationary pressures and commodity price hikes onto developing nations, notably China. Our findings contribute to the ongoing discourse on the entrenched inequalities between the Global North and South, emphasizing the asymmetrical power relations that underpin the process of cost transfer. Furthermore, this study enhances the research framework of cost-transfer theory and offers insights into the development of inequalities between developed and developing countries, aiding in the formulation of response strategies for developing countries facing cost transfer and mitigating the adverse impacts of cost transfers, thereby fostering more equitable and sustainable development trajectories.

Tail risk spillovers in the stock and forex markets at the major emergencies: Evidence from the G20 countries

We explore the tail risk spillover in the stock and foreign exchange (forex) markets along the G20 countries based on the tail-event driven network (TENET) method. To effectively capture the risk spillover mechanism from the tail-dependence perspective, we analyze the network connectedness in four aspects (namely system, market, region, and country) and explore it at the major emergencies. We find that (i) the system-level risk spillover peaks at the US subprime crisis, and subsequently undergoes several cyclical volatility in relatively high level in the period of major emergencies; (ii) the cross-market risk spillover from the stock markets to the forex markets plays a dominant role, while that from the forex markets to the stock markets is small; and (iii) the stock and forex markets in Europe and America transmit the large tail risk spillovers to other regions, and the forex markets in these regions are sensitive to the major emergencies.

The Impact of Financial Crises on Financial Markets: Case Studies of Three Historical Crises

Abstract: The recurring occurrences of financial crises have profound impacts on the global economic system. Insights gained from in-depth discussions on financial crises can effectively respond to future shocks, thereby ensuring the steady development of the world economy. This paper uses comparative analysis to examine the similar and different impacts of three financial crises on financial markets: the Dutch Tulip Mania of 1637, the Asian Financial Crisis of 1997, and the Subprime Mortgage Crisis of 2008. The research findings indicate that all three financial crises caused significant volatility in financial product trading markets. At the same time, these crises provided different lessons for the development of financial markets: the 1637 Dutch Tulip Mania underscored the importance of regulating exchanges, the 1997 Asian Financial Crisis highlighted the importance of foreign exchange reserves, and the 2008 Subprime Mortgage Crisis emphasized the necessity of controlling the banking industry, especially lending.

Corporate risk‐taking, economic policy uncertainty and ESG performance: International evidence

AbstractCorporate risk‐taking, which aims to maximize shareholders' profits, has raised concerns regarding potential conflicts with Environmental, social and governance (ESG) investments. We address this gap by investigating the relationship between corporate risk‐taking and ESG performance using an international sample from 20 economies spanning 2000 to 2022, while carefully accounting for endogeneity based on GMM, Heckman sample selection bias and simultaneous equations. Our findings reveal a significantly negative relationship, suggesting a trade‐off between the two, which aligns with the conservation of resources (COR) theory. Furthermore, the COR theory is integrated with agency theory and stakeholder theory when examining subsamples of high and low corporate governance scores. Additionally, we find that economic policy uncertainty (EPU) positively moderates this relationship, particularly in high‐income economies and for large firms. This effect is evident during the post‐2008 subprime crisis period but dissipates in the post‐COVID‐19 era. The overall findings have several important theoretical and practical implications for the literature.

Subprime Crisis Shockwaves: Impacts On Capital Structure In Non-Financial Corporations

Based upon a dataset spanning about 2,780 non-financial firms in France over the period 2007- 2019, we explore the impact of the subprime crisis on their leverage ratio and capital structure, comparing the experience of the largest listed and unlisted non-financial corporates. Our results highlight that both listed and unlisted corporates tend to reduce their overall indebtedness ratios during the subprime crisis period and its aftermath, generalizing a significant corporate deleveraging for listed and unlisted firms especially during the post-crisis period. In addition, our findings show that listed corporates become more dependable on short- and medium-term credits than the long-term which may increase the exposure of these corporates to credit and liquidity shocks. While our outcomes reveal a clear preference to long-term debt for unlisted firms by expanding their debt maturities, relying on long-term credits and reducing their dependence on short- and medium-term debt which burden these corporates with short-term charges and payments that cannot afford during the crisis and post-crisis periods.

Risk Analysis of Mortgage Loan Default for Bank Customers and AI Machine Learning

Abstract Risk Analysis of Mortgage Loan Default for Banks is a crucial issue. On one hand, it concerns the quality of the bank's credit decisions, and on the other hand, it affects the rights of homebuyers to obtain financial support. In 2008, the U.S. subprime mortgage crisis sparked a global financial meltdown. What began with the collapse of the housing market quickly spread throughout the global financial system, resulting in the failure of numerous banks and a widespread economic recession. Recently, the banking sector has increasingly leveraged Artificial Intelligence (AI) and Machine Learning (ML) to enhance decision-making processes, particularly in assessing the risk of mortgage loan defaults. This paper aims to explore the application of ML techniques to predict and analyze the risk of default among bank customers, thereby enabling financial institutions to make more accurate and informed lending decisions. Keywords: Mortgage Loan Default Risk Analysis AI ML K-MANS LTV.

Technology-Driven Financial Risk Management: Exploring the Benefits of Machine Learning for Non-Profit Organizations

This study explores how machine learning can optimize financial risk management for non-profit organizations by evaluating various algorithms aimed at mitigating loan default risks. The findings indicate that ensemble learning models, such as random forest and LightGBM, significantly improve prediction accuracy, thereby enabling non-profits to better manage financial risk. In the context of the 2008 subprime mortgage crisis, which underscored the volatility of financial markets, this research assesses a range of risks—credit, operational, liquidity, and market risks—while exploring both traditional machine learning and advanced ensemble techniques, with a particular focus on stacking fusion to enhance model performance. Emphasizing the importance of privacy and adaptive methods, this study advocates for interdisciplinary approaches to overcome limitations such as stress testing, data analysis rule formulation, and regulatory collaboration. The research underscores machine learning’s crucial role in financial risk control and calls on regulatory authorities to reassess existing frameworks to accommodate evolving risks. Additionally, it highlights the need for accurate data type identification and the potential for machine learning to strengthen financial risk management amid uncertainty, promoting interdisciplinary efforts that address broader issues like environmental sustainability and economic development.

Impact of Sharia‐Based Screening on Equity Risk: International Evidence

ABSTRACTThis paper investigates the impact of mainstream Sharia‐based screening methodologies on equity risk. The study is based on the daily returns of 23 pairs of stock indices belonging to different index providers, namely Dow Jones, FTSE, and S&P. For risk measurement, the study uses five Value at Risk (VaR) methods. Moreover, the conditional VaR (CVaR) is used to analyze the tail behavior of return distributions. The results show that Sharia‐based screening is a source of significant differences in risk. There is strong evidence that Islamic stock indices (ISIs) tend to be less risky than their conventional peers. Also, the screening process allows for keeping extreme negative returns at a lower level relative to unscreened indices. The analysis during the Dotcom and Subprime crises shows that, globally, the results are time‐invariant. In sum, Islamic screening is tantamount to prudential rules that lead to low‐risk portfolios; it is, in its essence, a risk‐reduction strategy. Findings suggest that Sharia‐compliant stocks would be of great attractiveness to risk‐averse investors. They will find their claim in this asset class, as its riskiness is relatively low. For banks, a lower VaR of Islamic investing implies fewer capital requirements for market risk when holding portfolios that include Sharia‐compliant stocks. Fewer capital requirements will enhance the banks' ability to invest and make profits, which will, in turn, result in reducing the cost of capital.

Analysis of financial contagion among economic sectors through Dynamic Bayesian Networks

Crises severely impact economies and may spread across regions or sectors in a process called contagion. Understanding this process is crucial for anticipating crises’ effects and implementing mitigative strategies. Specific economic sectors may be major crisis propagators: banking and insurance are often considered decisive in this context. This study employs Dynamic Bayesian Networks to model sectoral interdependencies within the U.S. economy, utilizing daily data from nine Dow Jones industrial indices over the period 2000–2020. As a secondary objective, we evaluate whether the insurance industry plays a central role in spreading crises. Several crisis periods are analyzed, from dot-com bubble to Covid-19 pandemic. The results reveal the subprime crisis, European debt crisis and the 2016 presidential election as the main contagious periods. The last analyzed period – Covid-19 pandemic – was divided in two phases, showing, on phase 1, an interconnected economic system with three main spreaders (Oil & Gas, Real Estate and Pharmaceutical) and, on phase 2, the same configuration of the post-subprime. Furthermore, although the insurance sector was somehow relevant during subprime crisis, it primarily acts as a contagion receptor, specially from the banking sector, with the correlation between them being the highest of all, reaching 0.49 at the last period.

Corporate Cash Holdings and Advertising Spending After the Financial Crises

This paper examines the link between a firm’s characteristics and advertising budget allocation. It also shows the firm’s behavior after the Asian financial crisis and the American subprime mortgage crisis. Results show that crises can significantly impact management decisions. They can influence how multinational companies plan for their future. The study also identifies the macroeconomic factors that can influence a firm’s decision to allocate funds.

Pure contagion vs. financial interconnection in the subprime crisis context: Short- and long-term dynamics

This paper examines the difference between pure contagion and financial interconnection by studying the U.S. and some American and Asian markets in the subprime crisis context. These markets are affected by the mortgage crisis, with data available from January 1, 2003 to December 30, 2011. The paper first identifies the turmoil period via the wavelet technique and adopts cointegration and Granger causality approaches by estimating vector autoregressive (VAR) and vector error correction models (VECM) models. Based on daily returns from stock market indices in five American countries (Mexico, Brazil, Canada, Argentina, and the U.S.) and eight Asian ones (Hong Kong, Japan, India, Indonesia, Malaysia, Singapore, Korea, and China), the results show eight cases of pure contagion and 10 cases of financial interconnection. In addition, there were high co-movements in the short term and low co-movements in the long term for financial interconnection cases. These findings have several implications for investors looking to diversify their portfolios internationally and for portfolio managers to expect and limit market risk. The results provide additional guidance to regulators and policymakers.

Analyzing the Selective Stock Price Index Using Fractionally Integrated and Heteroskedastic Models

Stock market indices are important tools to measure and compare stock market performance. The Selective Stock Price (SSP) index reflects fluctuations in a set value of financial instruments of Santiago de Chile’s stock exchange. Stock indices also reflect volatility linked to high uncertainty or potential investment risk. However, economic shocks are altering volatility. Evidence of long memory in SSP time series also exists, which implies long-term persistence. In this paper, we studied the volatility of SSP time series from January 2010 to September 2023 using fractionally heteroskedastic models. We considered the Autoregressive Fractionally Integrated Moving Average (ARFIMA) process with Generalized Autoregressive Conditional Heteroskedasticity (GARCH) innovations—the ARFIMA-GARCH model—for SSP log returns, and the fractionally integrated GARCH, or FIGARCH model, was compared with a classical GARCH one. The results show that the ARFIMA-GARCH model performs best in terms of volatility fit and predictive quality. This model allows us to obtain a better understanding of the observed volatility and its behavior, which contributes to more effective investment risk management in the stock market. Moreover, the proposed model detects the influence volatility increments of the SSP index linked to external factors that impact the economic outlook, such as China’s economic slowdown in 2012 and the subprime crisis in 2008.