Economy-wide Risk Research Articles

Risk Dynamics with Heterogeneous Borrowers and Intermediaries

This paper studies the effects of borrowers' balance sheet heterogeneity on economywide risks and fragility, together with effects from intermediary balance sheet channel. We build a continuous time heterogeneous agents model with financial frictions and analytically characterize the transition dynamics. Once the economy moves to high leverage states, it tends to stay there — a leverage trap. Transition speed increases (decreases) when the economy is leveraging up (deleveraging) and when interest rate is lower. Tail uncertainty lasts longer during transition. Intermediary failure risk can lead to severe decline in borrowing/lending activities that could further slow the recovery process.

Deep Learning and Financial Stability

The financial sector is entering a new era of rapidly advancing data analytics as deep learning models are adopted into its technology stack. A subset of Artificial Intelligence, deep learning represents a fundamental discontinuity from prior analytical techniques, providing previously unseen predictive powers enabling significant opportunities for efficiency, financial inclusion, and risk mitigation. Broad adoption of deep learning, though, may over time increase uniformity, interconnectedness, and regulatory gaps. This paper maps deep learning’s key characteristics across five possible transmission pathways exploring how, as it moves to a mature stage of broad adoption, it may lead to financial system fragility and economy-wide risks. Existing financial sector regulatory regimes - built in an earlier era of data analytics technology - are likely to fall short in addressing the systemic risks posed by broad adoption of deep learning in finance. The authors close by considering policy tools that might mitigate these systemic risks.

Firm-Level Policy Risk in China: The Effects on Corporate Leverage Target Following Behaviour

This study proposes a new approach that bridges the asset pricing implications of economic policy uncertainty (EPU) and the dynamic debt-financing decisions of Chinese firms. The approach introduces a new variable, firm-level policy risk (FLPR), in empirical tests. FLPR embraces two elements, the exposure of a firm’s stocks to EPU shocks and the change of EPU as economy-wide policy risk. Our approach rectifies the defect that all firms respond homogeneously to EPU innovations and underpins the connection between EPU and capital structure with established theories. We show firms with positive (negative) EPU betas have their FLPRs impact negatively (positively) the leverage target, supporting the prediction derived from trade-off theory that rising economy-wide risk leads to falling optimum debt ratios. We also find that over-levered firms adjust towards the leverage target faster than under-levered firms.

Do China’s Non-Financial Firms Affect Systemic Risk?

ABSTRACT This article investigates the contribution of non-financial firms to systemic risk in the entire financial system and the corresponding firm-specific determinants. Thus, we develop a new measure of systemic risk with a test of our hypothesis that separates systemic risk from systematic risk. We also consider the firm-level determinants of contributions to systemic risk using a fixed-effects model and a logit model. Using data on companies in the CSI 300 index from 2008 to 2016, we find that our extreme value theory (EVT)-copula method is a good fit for testing the joint probability distribution of extreme returns as well as diverse dependence patterns with asymmetry and non-linearity characteristics. The empirical results provide evidence against the marginal expected shortfall (MES) method without a mechanism to test the statistical significance of determination. Several non-financial firms, though not all financial institutions, can generate significant spillover effects on the financial system. Our regression results suggest that, among firms with a significantly positive contribution to systemic risk, smaller firms have greater spillover effects on the financial system in China. Moreover, economy-wide systemic risk information and dynamic identification on systemically important firms deserve more attention in terms of macro-prudential regulation.

What’s in Your Benchmark? A Factor Analysis of Major Market Indexes

The authors examine the factor exposures of several popular market-capitalization indexes and how they vary over time. The authors find that most market-capitalization-weight indexes are effectively exposed to only two or three factors, with value and momentum being increasingly dominant. They find that the proportion of index movements explained by factors has materially increased in recent years, which is consistent with a more top-down, macro-driven environment or the increasing importance of economy-wide risks for financial markets.

Global risk factors in the returns of listed private equity

PurposeThe purpose of this paper is, to study macroeconomic risk factors driving the expected stock returns of listed private equity (LPE). The authors use LPE indices divided into different styles and regions from January 2004 to December 2016 and a set of country stock indices to estimate the macroeconomic risk profiles and corresponding risk premiums. Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market βs that are greater than 1. A one-factor asset pricing model using world stock market returns as the only possible risk factor is rejected on the basis of generalized method of moments (GMM) orthogonality conditions. In contrast, using the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of economic policy uncertainty as additional risk factors, this multifactor model is able to price a cross-section of expected LPE returns. The risk-return profile of LPE differs from country equity indices. Consequently, LPE should be treated as a separate asset class.Design/methodology/approachFollowing Ferson and Harvey (1994), the authors use an unconditional asset pricing model to capture the structure of returns across LPE. The authors use 11 LPE indices divided into different styles and regions from January 2004 to December 2016, and a set of country stock indices as spanning assets to estimate the macroeconomic risk profiles and corresponding risk premiums.FindingsUsing a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market ßs that are greater than 1. The authors estimate a one-factor asset pricing model using world stock market returns as the only possible risk factor by GMM. This model is rejected on the basis of the GMM orthogonality conditions. By contrast, a multifactor model built on the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of global economic policy uncertainty as additional risk factors is able to price a cross-section of expected LPE returns.Research limitations/implicationsGiven data availability, the authors’ sample is strongly influenced by the financial crisis and its aftermath.Practical implicationsInformation about the risk profile of LPE is important for asset allocation decisions. In particular, it may help to optimally react to contemporaneous changes in economy-wide risk factors.Originality/valueTo the best of authors’ knowledge, this is the first LPE study which investigates whether a set of macroeconomic factors is actually priced and, therefore, associated with a non-zero risk premium in the cross-section of returns.

What’s in Your Benchmark? A Factor Analysis of Major Market Indexes

The authors examine the factor exposures of several popular market-capitalization indexes and how they vary over time. The authors find that most market-capitalization-weight indexes are effectively exposed to only two or three factors, with value and momentum being increasingly dominant. They find that the proportion of index movements explained by factors has materially increased in recent years, which is consistent with a more top-down, macro-driven environment or the increasing importance of economy-wide risks for financial markets.

Mind the denominator: towards a more effective measurement system for cybersecurity

ABSTRACTCrime statistics in the physical world are routinely normalised around the population of a city or country. Such normalisations are essential, as they provide both a propensity-based perspective on crime (e.g. the odds of being murdered are 1 in 100,000) and correct for the simple fact that a larger population should have more crimes. Unfortunately, many cybersecurity metrics tend to be uncorrected counts of malicious phenomena such as the number of phishing websites. While normalisation cannot make bad measures good, a failure to normalise even the best cybersecurity metrics can lead to bias. A failure to normalise count statistics around the size of the ecosystem, sensor density or risk mitigation personnel has implications for the observed trends, often making the state of cybersecurity seem worse than it actually is. In short, normalisation of malicious count data is a crucial measurement step and has significant impacts for both firm- and economy-wide risk management strategies and policy assessment.

Basel III and perceived resilience of banks in the BRICS economies

ABSTRACTThis study investigates how the additional capital and liquidity requirements of Basel III would increase the resilience of banks. In particular, using panel data from 2007 to 2014, we examine the resilience of banks in the BRICS economies. Our results suggest that a 10% increase in capital adequacy ratio (CAR), Tier 1 capital ratio (TRA), and leverage ratio (LEV), the resilience (as measured by Z-Score of banks) increases by about 2.18, 0.89 and 1.31%, respectively. Similarly, for a 100% increase in liquidity coverage ratio (LCR), the resilience of banks increases by 0.51%, 1.10% and 1.19%, respectively, in the models associated with CAR, TRA, and LEV. Hence, our findings suggest that the CAR is robust to increase the resilience of banks. Our study also reveals that the LCR and LEV are the most effective to increase the resilience of banks if implemented simultaneously. We also find that the stage of economic development does not matter in formulating policies for the BRICS economies, and finally, we provide empirical evidence that economy-wide risk, such as a financial crisis, does not affect the resilience of banks and it influences the resilience of banks in the BRICS economies in the same way before and after the crisis.

What's in Your Benchmark? A Factor Analysis of Major Market Indexes

We examine the factor exposures of several popular market capitalization indexes and how they vary over time. We find that most market capitalization weight indexes are effectively exposed to only two or three factors, with value and momentum being increasingly dominant. We find that the proportion of the index movements explained by factors has materially increased in recent years, which is consistent with a more top-down, macro-driven environment or the increasing importance of economy-wide risks for financial markets.

Cyber Attacks: Preliminary Evidence from the Bank of Italy's Business Surveys

This paper presents preliminary evidence on cyber risk in the Italian private sector based on the Bank of Italy’s annual surveys of Italian industrial and service firms. The information collected, albeit only covering the incidence of cyber attacks and some aspects of security governance, is the first of its kind for Italy. The results are striking: even though a mere 1.5 per cent of businesses do not deploy any cybersecurity measures, 30.3 per cent – corresponding to 35.6 per cent of total employees – report at least some damage from a cyber attack between September 2015 and September 2016. Once data are corrected to account for unwillingness to report or inability to detect attacks on the part of some respondents, these figures climb to 45.2 and 56 per cent respectively, with large, high-tech and internationally exposed businesses faring worse than average. The economy-wide risk level is likely to be higher still; the financial sector, healthcare, education and social care are excluded from the sample, but they are known from other sources to be particularly appealing to attackers. Further research is needed on the correlation between firm-level vulnerability and investment in cyber defence, and on the cost of cyber breaches.

Banking competition and welfare

We develop a simple general equilibrium model in which investment in a risky technology is subject to moral hazard and banks can extract market power rents. We show that more bank competition results in lower economy-wide risk, higher social welfare, lower bank capital ratios, more efficient production plans and Pareto-ranked real allocations. Perfect competition supports a second best allocation and optimal levels of bank risk and capitalization. These results are at variance with those obtained by a large literature that has studied a similar environment in partial equilibrium, they are empirically relevant, and carry significant implications for policy guidance.

Economic Fluctuations and the Role of Monetary Policy: An Investigation of an Agent-based Model

AbstractThe merit of ABM comes directly from removing set of unreal assumptions that are commonly assumed in standard models. Not only can ABM regenerates macroeconomics regularities at the same level as the traditional models without introducing any exogenous process but also displays the ability to capture microeconomics dynamics. Simulation results conform to standard monetary economics theory—expansionary monetary policy can be used as a stabilization tool and leave no permanent impacts to real variables. When an economy experiences growth, an increase in money supply is required to stabilize price level, otherwise, severe deflation is expected as well as high fluctuations in unemployment level. Simple monetary policy can be used to stabilize such fluctuations and would reduced economy-wide default risk, which may have positive economic impacts in the long run. Provided that agents do not hold assets in this model setup, the study supports Friedman’s K-percent rule as it performs the best in term of output improvement. The asymmetric effects of monetary policy are found in number of aspects: impact to GDP, impact duration, and impact to unemployment level. Less flexibility in downward price adjustment is the reason behind such asymmetric responses.

Macroeconomic Risk and Residential Rate Design

If financial markets manage risk to personal consumption efficiently, it should be the case that energy bills that vary directly with aggregate personal consumption can be made both lower and less volatile at cost, since doing so is effectively making payments when aggregate consumption is high, and receiving payments when it is low. However, if energy bills vary directly with household personal consumption, making them less volatile will make household consumption more volatile. We develop a rate design that optimizes household consumption when there are macroeconomic surprises, as well as those in energy price and load. Households are heterogeneous in personal consumption, and that of energy. The rate design is embedded in a model of an economy-wide market for management of risk. Customers pay positive or negative risk premia that increase in the sensitivity of their consumption to macroeconomic surprises, and in the correlations of their loads with spot prices. Risk premia also increase in systematic risk and economy-wide risk aversion.

Are Capital Requirements on Small Business Loans Flawed?

This paper addresses issues related to industry heterogeneity, default clustering and parameter uncertainty of capital requirements in US retail loan portfolios. Using a multi-factor model of credit risk, we show that the Basel II capital requirements overstate the riskiness of small businesses. Retail exposures are a much safer investment than the regulator would suggest. We find that sensitivity to the common risk factors is low and that small business risk is predominantly a reflection of idiosyncratic risk. Our results show that only 0.00-3.39% of the asset variability is explained by economy-wide risk factors. The remaining 96.61%-100.00% of small business risk is due to changes in the firm-specific characteristics. Moreover, both expected and unexpected losses are time dependent. Their shifts over the course of financial crisis cause uncertainty in the provisions level and capital requirements. Importantly, our estimates of asset correlations are significantly lower than any available estimates for corporate firms. Our results are based on a new, representative dataset of US retail businesses from 2005 to 2011 and give fundamental insights into the US economy.

Dynamic risk, accounting-based valuation and firm fundamentals

This study extends the accounting-based valuation framework of Ohlson (Contemp Acc Res 11(2):661–687, 1995) and Feltham and Ohlson (Acc Rev 74(2):165–183, 1999) to incorporate dynamic expectations about the level of systematic risk in the economy. Our model explains recent empirical findings documenting a strong negative association between changes in economy-wide risk and future stock returns. Importantly, the model also generates costs of capital that are solely a linear function of accounting variables and other firm fundamentals, including the book-to-market ratio, the earnings-to-price ratio, the forward earnings-to-price ratio, size and the dividend yield. This result provides a theoretical rationale for the inclusion of these popular variables in cost of capital (expected return) computations by the accounting and finance literatures and obviates the need to estimate costs of capital from unobservable (future) covariances. The model also generates an accounting return decomposition in the spirit of Vuolteenaho (J Finance 57(1):233–264, 2002). Empirically, we find that costs of capital generated by our model are significantly associated with future returns both in and out of sample in contrast to standard benchmark models. We further obtain significantly lower valuation errors in out-of-sample tests than traditional models that ignore dynamic risk expectations.

Momentum and Aggregate Default Risk

In this paper, we explain momentum profits using innovations in aggregate economy-wide default risk. First, we show that momentum returns are positive only during high default shocks and nonexistent otherwise. Second, we present evidence suggesting that a conditional default shock factor is priced in the cross-section and can explain a large portion of the total momentum returns. According to our results, winners have potentially higher risk than losers during periods of high default shocks. We confirm this finding in alternate sub-periods where momentum is generally not observed and as well as in international data. We also provide an explanation for this finding by linking momentum profits to potential shareholder recovery during financial distress. We find that winners tend to have relatively higher risk in worsening aggregate default conditions due to lower shareholder bargaining power. These results indicate that momentum profits contain a systematic component related to aggregate default and can be explained in a rational framework.

Diversity Among Banks May Increase Systemic Risk

The problem of how to stabilize the financial system has attracted considerable attention since the global financial crisis of 2007-2009. Recently, Beal et al. (2011, gIndividual versus systemic risk and the regulator fs dilemma h, Proc Natl Acad Sci USA 108: 12647-12652) demonstrated that higher portfolio diversity among banks would reduce systemic risk by decreasing the likelihood of simultaneous defaults. Here, I show that this result is overturned once a financial network comes into play. In a networked financial system, the failure of one bank can bring about a contagion of failure. The optimality of individual risk diversification, as opposed to economy-wide risk diversification, is thus restored. I also present a new method to quantify how the diversity of bank size affects the stability of a financial system. It is shown that a higher diversity of bank size itself makes the financial system more fragile even if external risk exposure is controlled for. The main reason for this is that larger banks are more likely to become a gsuper spreader h of infectious defaults. In this situation the social cost of letting a bank fail is not uniform and depends on the size of the failing bank. This strongly implies that larger banks are systemically more important than smaller banks, and preventing large banks from being exposed to high external risks would therefore be the most effective vaccine against financial crisis.

Measuring Residential Real Estate Risk and Return

This article explains how common misconceptions about residential real estate returns contribute to unrealistic expectations about house price appreciation. The article evaluates several comprehensive ways of computing residential real estate returns and discusses the relation between real estate return and risk. We review the role of real estate in household portfolios, the overall economy, and the financial crisis and discuss why decline in the real estate market imposes economy-wide risks.

Dynamic Risk, Accounting-Based Valuation and Firm Fundamentals

This study extends the accounting-based valuation framework of Ohlson (1995) and Feltham and Ohlson (1999) to incorporate dynamic expectations about the level of systematic risk in the economy. Our model explains recent empirical findings documenting a strong negative association between changes in economy-wide risk and future stock returns. Importantly, the model also generates costs of capital that are solely a linear function of accounting variables and other firm fundamentals including the book-to-market ratio, the earnings-to-price ratio, the forward earnings-to-price ratio, size and the dividend yield. This result provides a theoretical rationale for the inclusion of these popular variables in cost of capital (expected return) computations by the accounting and finance literatures and obviates the need to estimate costs of capital from unobservable (future) covariances. The model also generates an accounting return decomposition in the spirit of Vuolteenaho (2002). Empirically, we find that costs of capital generated by our model are significantly associated with future returns both in and out of sample in contrast to standard benchmark models. We further obtain significantly lower valuation errors in out-of-sample tests than traditional models that ignore dynamic risk expectations.