Showing papers on "Financial risk published in 2014"

Systemic Risk and Stability in Financial Networks

Abstract: We provide a framework for studying the relationship between the financial network architecture and the likelihood of systemic failures due to contagion of counterparty risk. We show that financial contagion exhibits a form of phase transition as interbank connections increase: as long as the magnitude and the number of negative shocks affecting financial institutions are sufficiently small, more "complete" interbank claims enhance the stability of the system. However, beyond a certain point, such interconnections start to serve as a mechanism for propagation of shocks and lead to a more fragile financial system. We also show that, under natural contracting assumptions, financial networks that emerge in equilibrium may be socially inefficient due to the presence of a network externality: even though banks take the effects of their lending, risk-taking and failure on their immediate creditors into account, they do not internalize the consequences of their actions on the rest of the network.

A macroeconomic model with a financial sector

Abstract: This paper studies a macroeconomic model in which financial experts borrow from less productive agents. We pursue four sets of results: (i) The economy is prone to instability and occasionally enters volatile episodes. As volatility spikes agents precautionary motive increases depressing prices even further. Log-linear approximations fail to capture these non-linear effects that can cause economies to be significantly depressed for long periods of time. (ii) Endogenous risk during volatile episodes increases asset price correlations. (iii) Financial experts impose a negative externality on each other and on the labor sector by not maintaining adequate capital cushion, and funding structure. (iv) While risk sharing within the financial sector (through securitization and derivatives contracts) reduces many inefficiencies, it can also amlify systemic risks.

Consumer Financial Capability and Financial Satisfaction

Abstract: The purpose of this study was to examine associations between consumer financial capability and financial satisfaction. Consumer financial capability was measured by three sets of variables, perceived financial capability, financial literacy, and financial behavior. Using data from the 2009 US State-by-State Survey of Financial Capability, the results indicated the positive association between perceived financial capability and financial satisfaction. The findings suggested that desirable financial behavior increases while risky financial behavior decreases financial satisfaction. Subjective financial literacy was also found to contribute positively to financial satisfaction. The positive association between objective financial literacy and financial satisfaction was found in bivariate analyses but not in multivariate analyses. The results imply that to enhance consumer financial well-being, consumer financial education programs should emphasize action taking and encourage consumers to avoid risky financial behavior, engage in desirable financial behavior, and improve financial self-efficacy.

Can You Help Someone Become Financially Capable? A Meta-Analysis of the Literature

Abstract: This paper presents a systematic and comprehensive meta-analysis of the literature on financial education interventions. The analysis focuses on financial education studies designed to strengthen the financial knowledge and behaviors of consumers. The analysis identifies 188 papers and articles that present impact results of interventions designed to increase consumers' financial knowledge (financial literacy) or skills, attitudes, and behaviors (financial capability). These papers are diverse across a number of dimensions, including objectives of the program intervention, expected outcomes, intensity and duration of the intervention, delivery channel used, and type of population targeted. However, there are a few key outcome indicators where a subset of papers are comparable, including those that address savings behavior, defaults on loans, and financial skills, such as record keeping. The results from the meta analysis indicate that financial literacy and capability interventions can have a positive impact in some areas (increasing savings and promoting financial skills such as record keeping) but not in others (credit default).

The Relationship between Liquidity Risk and Credit Risk in Banks

Abstract: This paper investigates the relationship between the two major sources of bank default risk: liquidity risk and credit risk. We use a sample of virtually all U.S. commercial banks during the period 1998 to 2010 to analyze the relationship between these two risk sources on the bank institutional-level and how this relationship influences banks’ probabilities of default (PD). Our results show that both risk categories do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship. However, they do influence banks’ probability of default. This effect is twofold: whereas both risks separately increase the PD, the influence of their interaction depends on the overall level of bank risk and can either aggravate or mitigate default risk. These results provide new insights into the understanding of bank risk, as developed by the body of literature on bank stability risk in general and credit and liquidity risk in particular. They also serve as an underpinning for recent regulatory efforts aimed at strengthening banks (joint) risk management of liquidity and credit risks, such as the Basel III and Dodd-Frank frameworks.

Convective Risk Flows in Commodity Futures Markets

Abstract: We study the joint responses of commodity futures prices and positions of various trader groups to changes of the CBOE Volatility Index (VIX) before and after the recent financial crisis. Financial traders reduced their net long positions during the crisis in response to market distress, while hedgers facilitated this by reducing their net short positions as prices fell. This convective risk flow induced by the greater distress of financial institutions led to a change in the allocation of risk with hedgers holding more risk than they did previously. The presence of such a risk flow confirms the market impact of financial traders conditional on trades they initiate.

Risk-Taking Differences Across the Adult Life Span: A Question of Age and Domain

Abstract: Background. Older adults face important risky decisions about their health, their financial future, and their social environment. We examine age differences in risk-taking behaviors in multiple risk domains across the adult life span. Methods. A cross-sectional study was conducted in which 528 participants from 18 to 93 years of age completed the Domain-Specific Risk-Taking (DOSPERT) scale, a survey measuring risk taking in 5 different domains. Results. Our findings reveal that risk-taking tendencies in the financial domain reduce steeply in older age (at least for men). Risk taking in the social domain instead increases slightly from young to middle age, before reducing sharply in later life, whereas recreational risk taking reduces more steeply from young to middle age than in later life. Ethical and health risk taking reduce relatively smoothly with age. Our findings also reveal gender differences in risk taking with age. Financial risk taking reduced steeply in later life for men but not for women, and risk taking in the social domain reduced more sharply for women than for men. Discussion. We discuss possible underlying causes of the domain-specific nature of risk taking and age.

Financial Risk Protection and Universal Health Coverage: Evidence and Measurement Challenges

Abstract: Financial risk protection is a key component of universal health coverage (UHC), which is defined as access to all needed quality health services without financial hardship. As part of the PLOS Medicine Collection on measurement of UHC, the aim of this paper is to examine and to compare and contrast existing measures of financial risk protection. The paper presents the rationale behind the methodologies for measuring financial risk protection and how this relates to UHC as well as some empirical examples of the types of measures. Additionally, the specific challenges related to monitoring inequalities in financial risk protection are discussed. The paper then goes on to examine and document the practical challenges associated with measurement of financial risk protection. This paper summarizes current thinking on the area of financial risk protection, provides novel insights, and suggests future developments that could be valuable in the context of monitoring progress towards UHC.

Cortisol shifts financial risk preferences

Abstract: Risk taking is central to human activity. Consequently, it lies at the focal point of behavioral sciences such as neuroscience, economics, and finance. Many influential models from these sciences assume that financial risk preferences form a stable trait. Is this assumption justified and, if not, what causes the appetite for risk to fluctuate? We have previously found that traders experience a sustained increase in the stress hormone cortisol when the amount of uncertainty, in the form of market volatility, increases. Here we ask whether these elevated cortisol levels shift risk preferences. Using a double-blind, placebo-controlled, cross-over protocol we raised cortisol levels in volunteers over 8 d to the same extent previously observed in traders. We then tested for the utility and probability weighting functions underlying their risk taking and found that participants became more risk-averse. We also observed that the weighting of probabilities became more distorted among men relative to women. These results suggest that risk preferences are highly dynamic. Specifically, the stress response calibrates risk taking to our circumstances, reducing it in times of prolonged uncertainty, such as a financial crisis. Physiology-induced shifts in risk preferences may thus be an underappreciated cause of market instability.

Robust risk measurement and model risk

Abstract: Financial risk measurement relies on models of prices and other market variables, but models inevitably rely on imperfect assumptions and estimates, creating model risk. Moreover, optimization decisions, such as portfolio selection, amplify the effect of model error. In this work, we develop a framework for quantifying the impact of model error and for measuring and minimizing risk in a way that is robust to model error. This robust approach starts from a baseline model and finds the worst-case error in risk measurement that would be incurred through a deviation from the baseline model, given a precise constraint on the plausibility of the deviation. Using relative entropy to constrain model distance leads to an explicit characterization of worst-case model errors; this characterization lends itself to Monte Carlo simulation, allowing straightforward calculation of bounds on model error with very little computational effort beyond that required to evaluate performance under the baseline nominal model. Thi...

Cortisol shifts financial risk preferences

Abstract: * Freely available online through the PNAS open access option. Risk taking is central to human activity. Consequently, it lies at the focal point of behavioral sciences such as neuroscience, economics, and finance. Many influential models from these sciences assume that financial risk preferences form a stable trait. Is this assumption justified and, if not, what causes the appetite for risk to fluctuate? We have previously found that traders experience a sustained increase in the stress hormone cortisol when the amount of uncertainty, in the form of market volatility, increases. Here we ask whether these elevated cortisol levels shift risk preferences. Using a double-blind, placebo-controlled, cross-over protocol we raised cortisol levels in volunteers over eight days to the same extent previously observed in traders. We then tested for the utility and probability weighting functions underlying their risk taking, and found that participants became more risk averse. We also observed that the weighting of probabilities became more distorted among men relative to women. These results suggest that risk preferences are highly dynamic. Specifically, the stress response calibrates risk taking to our circumstances, reducing it in times of prolonged uncertainty, such as a financial crisis. Physiology-induced shifts in risk preferences may thus be an under-appreciated cause of market instability.

Financial Stability and Financial Inclusion

Abstract: Developing economies are seeking to promote financial inclusion, i.e., greater access to financial services for low-income households and firms, as part of their overall strategies for economic and financial development. This raises the question of whether financial stability and financial inclusion are, broadly speaking, substitutes or complements. In other words, does the move toward greater financial inclusion tend to increase or decrease financial stability? A number of studies have suggested both positive and negative ways in which financial inclusion could affect financial stability, but very few empirical studies have been made of their relationship. This partly reflects the scarcity and relative newness of data on financial inclusion. This study contributes to the literature on this subject by estimating the effects of various measures of financial inclusion (together with some control variables) on some measures of financial stability, including bank non-performing loans and bank Z scores. We find some evidence that an increased share of lending to small and medium sized enterprises (SMEs) aids financial stability, mainly by reducing non-performing loans (NPLs) and the probability of default by financial institutions. This suggests that policy measures to increase financial inclusion, at least by SMEs, would have the side-benefit of contributing to financial stability as well.

Assessing the Contribution of Banks, Insurance and Other Financial Services to Systemic Risk

Abstract: The aim of this paper is to contribute to the debate on systemic risk by assessing the extent to which distress within the main different financial sectors, namely, the banking, insurance and other financial services industries contribute to systemic risk. To this end, we rely on the ∆CoVaR systemic risk measure introduced by Adrian and Brunnermeier (2011). In order to provide a formal ranking of the financial sectors with respect to their contribution to systemic risk, the original ∆CoVaR approach is extended here to include the Kolmogorov-Smirnov test developed by Abadie (2002), based on bootstrapping. Our empirical results reveal that in the Eurozone, for the period ranging from 2004 to 2012, the other financial services sector contributes relatively the most to systemic risk at times of distress affecting this sector. In turn, the banking sector appears to contribute more to systemic risk than the insurance sector. By contrast, the insurance industry is the most systemically risky financial sector in the United States for the same period, while the banking sector contributes the least to systemic risk in this area. Beyond this ranking, the three financial sectors of interest are found to contribute significantly to systemic risk, both in the Eurozone and in the United States.

Cost and Schedule Risk Analysis of Bridge Construction in Pakistan: Establishing Risk Guidelines

Abstract: The construction process is inherently prone to risks. Risk management is an essential and integral part of project management on virtually all construction projects. Risk analysis is one of the core components of risk management that enables professionals to quantify and analyze risks that may pose potential threats to project performance in terms of cost, quality, safety, and time. This research was conducted to identify and analyze risks associated with bridge construction in Pakistan. A questionnaire was conducted to collect data. Risks affecting bridge construction project performance were identified through interviews conducted with engineers and managers involved with various bridge projects. Cost and schedule impacts of project risks were supplemented by conducting a case study using the Monte Carlo simulation. The key findings indicate that financial risks were a major factor that affected cost and schedule objectives. The highest ranked factor identified was unavailability of funds with ...

Risk aversion vs. individualism: what drives risk taking in household finance?

Abstract: Despite a considerable premium on equity with respect to risk-free assets, many households do not own stocks. We ask why the prevalence of stockholding is so limited. We focus on individuals’ attitudes toward risk and identify relevant factors that affect the willingness to take financial risks. Our empirical evidence contradicts standard portfolio theory, as it does not indicate a significant relationship between risk aversion and financial risk taking. However, our analysis supports the behavioral view that psychological factors rooted in national culture affect portfolio choice. Individualism, which is linked to overconfidence and overoptimism, has a significantly positive effect on financial risk taking. In microdata from Germany and Singapore, as well as in cross-country data, we find evidence consistent with low levels of individualism being an important factor in explaining the limited participation puzzle.

A Macroeconomic Framework for Quantifying Systemic Risk

Abstract: Systemic risk arises when shocks lead to states where a disruption in financial intermediation adversely affects the economy and feeds back into further disrupting financial intermediation. We present a macroeconomic model with a financial intermediary sector subject to an equity capital constraint. The novel aspect of our analysis is that the model produces a stochastic steady state distribution for the economy, in which only some of the states correspond to systemic risk states. The model allows us to examine the transition from “normal” states to systemic risk states. We calibrate our model and use it to match the systemic risk apparent during the 2007/2008 financial crisis. We also use the model to compute the conditional probabilities of arriving at a systemic risk state, such as 2007/2008. Finally, we show how the model can be used to conduct a macroeconomic “stress test” linking a stress scenario to the probability of systemic risk states.

What Factors Drive Systemic Risk during International Financial Crises

Abstract: We analyze the determinants of the contribution of international banks to both global and local systemic risk during prominent financial crises. We find no empirical evidence supporting the hypotheses that bank size, leverage, non-interest income or the quality of the bank’s credit portfolio are persistent determinants of systemic risk across financial crises. In contrast, our results show that global systemic risk in particular is predominantly driven by characteristics of the regulatory regime. We also confirm, for the subprime crisis, the hypothesis that the banks’ contribution to moderately bad tail events in the past predicts the financial sector’s crash risk.

Corporate Governance and Risk Taking: Evidence from the U.K. and German Insurance Markets

Abstract: We analyze the impact of factors related to corporate governance (i.e., compensation, monitoring, and ownership structure) on risk taking in the insurance industry. We measure asset, product, and financial risk in insurance companies and employ a structural equation model in which corporate governance is modeled as a latent factor. Based on this model, we present empirical evidence on the link between corporate governance and risk taking, considering insurers from two large European insurance markets. Higher levels of compensation, increased monitoring (more independent boards with more meetings), and more blockholders are associated with lower risk taking. Our empirical results provide justification for including factors related to corporate governance in insurance regulation.

Flood insurance schemes and climate adaptation in developing countries

Abstract: Risk transfer, including insurance, is widely recognized as a tool for increasing financial resilience to severe weather events such as floods. The application of this mechanism varies widely across countries, with a range of different types and schemes in operation. While most of the analytical focus has so far been on those markets that have a long tradition of insurance, there is still a clear gap in our understanding of how this mechanism works in a developing country context. This paper assesses 27 insurance schemes that transfer the risk of economic losses arising from floods in low—and middle income countries, focusing on the linkages between financial risk transfer and risk reduction. This aspect is important to avoid the effect of moral hazard and has gained particular relevance in the context of the climate change adaptation discourse, where some scholars and practitioners view insurance as a potential tool not just for current risks, but also to address projected future impacts of a changing climate by incentivizing risk reduction. We therefore look beyond the pure financial risk transfer nature of those 27 insurance schemes and investigate any prevention and risk reduction elements. Our analysis suggests that the potential for utilizing risk transfer for risk reduction is far from exhausted, with only very few schemes showing an operational link between risk transfer and risk reduction, while the effectiveness and implementation on the ground remains unclear. The dearth of linkages between risk reduction and insurance is a missed opportunity in the efforts to address rising risk levels, particularly in the context of climate change. Rising risk levels pose a threat to the insurability of floods, and insurance without risk reduction elements could lead to moral hazard. Therefore a closer linkage between risk transfer and risk reduction could make this a more sustainable and robust tool.

Estimation methods for expected shortfall

Abstract: Introduced in the 1980s, value at risk has been a popular measure of financial risk. However, value at risk suffers from a number of drawbacks as measure of financial risk. An alternative measure referred to as expected shortfall was introduced in late 1990s to circumvent these drawbacks. Much theory have been developed since then. The developments have been most intensive in recent years.However, we are not aware of any comprehensive review of known estimation methods for expected shortfall. We feel it is timely that such a review is written. This paper (containing six sections and over 140 references) attempts that task with emphasis on recent developments. We expect this review to serve as a source of reference and encourage further research with respect to measures of financial risk.

AdaBoost based bankruptcy forecasting of Korean construction companies

Abstract: AdaBoost (adaptive boosting) is an appropriate model to judge the financial risk of Korean construction companies.We classified construction companies into three groups - large, middle, and small based on the capital of a company.We analyzed the predictive ability of the AdaBoost and other algorithms for each group of companies.The AdaBoost has more predictive power than others, especially for the large group of companies that has the capital more than 50 billion won. A lot of bankruptcy forecasting model has been studied. Most of them uses corporate finance data and is intended for general companies. It may not appropriate for forecasting bankruptcy of construction companies which has big liquidity. It has a different capital structure, and the model to judge the financial risk of general companies can be difficult to apply the construction companies. The existing studies such as traditional Z-score and bankruptcy prediction using machine learning focus on the companies of non-specific industries. The characteristics of companies are not considered at all. In this paper, we showed that AdaBoost (adaptive boosting) is an appropriate model to judge the financial risk of Korean construction companies. We classified construction companies into three groups - large, middle, and small based on the capital of a company. We analyzed the predictive ability of the AdaBoost and other algorithms for each group of companies. The experimental results showed that the AdaBoost has more predictive power than others, especially for the large group of companies that has the capital more than 50 billion won.

A Semiparametric Gaussian Copula Regression Model for Predicting Financial Risks from Earnings Calls

Abstract: Earnings call summarizes the financial performance of a company, and it is an important indicator of the future financial risks of the company. We quantitatively study how earnings calls are correlated with the financial risks, with a special focus on the financial crisis of 2009. In particular, we perform a text regression task: given the transcript of an earnings call, we predict the volatility of stock prices from the week after the call is made. We propose the use of copula: a powerful statistical framework that separately models the uniform marginals and their complex multivariate stochastic dependencies, while not requiring any prior assumptions on the distributions of the covariate and the dependent variable. By performing probability integral transform, our approach moves beyond the standard count-based bag-ofwords models in NLP, and improves previous work on text regression by incorporating the correlation among local features in the form of semiparametric Gaussian copula. In experiments, we show that our model significantly outperforms strong linear and non-linear discriminative baselines on three datasets under various settings.

Risk models-at-risk

Abstract: The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risks. A key reason for this is that risk measures are subject to a model risk due, e.g. to specification and estimation uncertainty. While regulators have proposed that financial institutions assess the model risk, there is no accepted approach for computing such a risk. We propose a remedy for this by a general framework for the computation of risk measures robust to model risk by empirically adjusting the imperfect risk forecasts by outcomes from backtesting frameworks, considering the desirable quality of VaR models such as the frequency, independence and magnitude of violations. We also provide a fair comparison between the main risk models using the same metric that corresponds to model risk required corrections.