nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒07‒08
twenty papers chosen by
Stan Miles
Thompson Rivers University

  1. Systemic Risk and Collateral Adequacy By Radoslav Raykov
  2. Hedging climate change news By Robert Engle; Stefano Giglio; Heebum Lee; Bryan Kelly; Johannes Stroebel
  3. From Halfspace M-Depth to Multiple-output Expectile Regression By Daouia, Abdelaati; Paindaveine, Davy
  4. Bank risk dynamics and distance to default By Stefan Nagel; Amiyatosh Purnanandam
  5. Pricing Financial Derivatives Subject to Multilateral Credit Risk and Collateralization By Xiao, Tim
  6. Do Portfolio Investors Need To Consider The Asymmetry Of Returns On The Russian Stock Market? By Valeria V. Lakshina
  7. Lower bank capital requirements as a policy tool to support credit to SMEs: evidence from a policy experiment By Sandrine Lecarpentier; Mathias Lé; Henri Fraisse; Michel Dietsch
  8. Resaleable debt and systemic risk By Donaldson, Jason, Roderick; Micheler, Eva
  9. Are cryptocurrency traders pioneers or just risk-seekers? Evidence from brokerage accounts By Matthias Pelster; Bastian Breitmayer; Tim Hasso
  10. Analyzing credit risk transmission to the non-financial sector in Europe: A network approach By Christian Gross; Pierre L. Siklos
  11. Forecasting Volatility and Co-volatility of Crude Oil and Gold Futures: Effects of Leverage, Jumps, Spillovers, and Geopolitical Risks By Manabu Asai; Rangan Gupta; Michael McAleer
  12. Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol By Darjus Hosszejni; Gregor Kastner
  13. Predictability concentrates in bad times. And so does disagreement By de Oliveira Souza, Thiago
  14. Business tax policy under default risk By Nicola Comincioli; Sergio Vergalli; Paolo Panteghini
  15. The Dark Side of Prudential Measures By PAulo Roberto Scalco; Benjamin M. Tabak; Anderson Mutter Teixeira
  16. The Systematic Risk of Gold at Different Timescales By Antonis A. Michis
  17. A portfolio choice problem in the framework of expected utility operators By Irina Georgescu; Louis Aim\'e Fono
  18. Threshold Ages for the Relation between Lifetime Entropy and Mortality Risk By Patrick Meyer; Grégory Ponthiere
  19. Impact of higher capital buffers on banks’ lending and risk-taking: evidence from the euro area experiments By Cappelletti, Giuseppe; Peeters, Jonas; Budrys, Žymantas; Varraso, Paolo; Marques, Aurea Ponte
  20. Oil price volatility forecasts: What do investors need to know? By Degiannakis, Stavros; Filis, George

  1. By: Radoslav Raykov
    Abstract: Many derivatives markets use collateral requirements calculated with industry-standard but dated methods that are not designed with systemic risk in mind. This paper explores whether the conservative nature of conventional collateral requirements outweighs their lack of consideration of systemic risk. To investigate this issue, we calculate a new systemic risk metric: the expected systemic market shortfall. We analyze the composition of systemic risk across firms both before and after applying conventional collateral requirements. Our results show that the conservative nature of conventional collateral levels does buffer systemic risk adequately and results in only small risk spillovers above collateral. These spillovers do not meaningfully add to banks' pre-existing systemic risk. We verify the robustness of this result by exploring alternative systemic risk measures, allowing for an implausibly large margin of error. Even under the most extreme scenario, the maximum market-wide shortfall in excess of collateral barely reaches 1 per cent of banks' market capitalization. This maximum shortfall therefore does not exceed the effect of a 1 per cent decline in stock price.
    Keywords: Financial Institutions; Financial markets
    JEL: G10 G20
    Date: 2019–06
  2. By: Robert Engle; Stefano Giglio; Heebum Lee; Bryan Kelly; Johannes Stroebel
    Abstract: We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk exposures. We show that this approach yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample. We discuss multiple directions for future research on financial approaches to managing climate risk.
    Keywords: climate risk
    JEL: G11 G18 Q54
    Date: 2019
  3. By: Daouia, Abdelaati; Paindaveine, Davy
    Abstract: Despite the importance of expectiles in fields such as econometrics, risk management, and extreme value theory, expectile regression—or, more generally, M-quantile regression—unfortunately remains limited to single-output problems. To improve on this, we define hyperplane-valued multivariate M-quantiles that show strong advantages over their point-valued competitors. Our M-quantiles are directional in nature and provide centrality regions when all directions are considered. These regions define new statistical depths, the halfspace M-depths, that include the celebrated Tukey depth as a particular case. We study thoroughly the proposed M-quantiles, halfspace M-depths, and corresponding regions. M-depths not only provide a general framework to consider Tukey depth, expectile depth, Lr-depths, etc., but are also of interest on their own. However, since our original motivation was to consider multiple-output expectile regression, we pay more attention to the expectile case and show that expectile depth and multivariate expectiles enjoy distinctive properties that will be of primary interest to practitioners: expectile depth is maximized at the mean vector, is smoother than the Tukey depth, and exhibits surprising monotonicity properties that are key for computational purposes. Finally, our multivariate expectiles allow defining multiple-output expectile regression methods, that, in riskoriented applications in particular, are preferable to their analogs based on standard quantiles.
    Keywords: Centrality regions; Multivariate expectiles; Multivariate M-quantiles;; Multiple-output regression; Statistical depth
    Date: 2019–07–02
  4. By: Stefan Nagel; Amiyatosh Purnanandam
    Abstract: We adapt structural models of default risk to take into account the special nature of bank assets. The usual assumption of log-normally distributed asset values is not appropriate for banks. Typical bank assets are risky debt claims, which implies that they embed a short put option on the borrowers' assets, leading to a concave payoff. This has important consequences for banks’ risk dynamics and distance to default estimation. Due to the payoff non-linearity, bank asset volatility rises following negative shocks to borrower asset values. As a result, standard structural models in which the asset volatility is assumed to be constant can severely understate banks’ default risk in good times when asset values are high. Bank equity payoffs resemble a mezzanine claim rather than a call option. Bank equity return volatility is therefore much more sensitive to big negative shocks to asset values than in standard structural models.
    Date: 2019
  5. By: Xiao, Tim
    Abstract: This article presents a new model for valuing financial contracts subject to credit risk and collateralization. Examples include the valuation of a credit default swap (CDS) contract that is affected by the trilateral credit risk of the buyer, seller and reference entity. We show that default dependency has a significant impact on asset pricing. In fact, correlated default risk is one of the most pervasive threats in financial markets. We also show that a fully collateralized CDS is not equivalent to a risk-free one. In other words, full collateralization cannot eliminate counterparty risk completely in the CDS market.
    Keywords: asset pricing; credit risk modeling; collateralization; comvariance; comrelation; correlation, CDS.
    JEL: G12 G13 M21 P45
    Date: 2019–03–09
  6. By: Valeria V. Lakshina (National Research University Higher School of Economics)
    Abstract: This paper uses the parsimonious method of embedding skewness in asset allocation based on the Taylor expansion of the investor utility function up to the third term and maximizing it by portfolio weights. This approach also enables us to consider investor risk aversion. Time-dependent multivariate asset moments are obtained via the GOGARCH volatility model with a normal-inverse Gaussian distribution for the error term. We explore the performance of the usual 2 moment utility and its 3 moment counterpart for a portfolio consisted of twenty assets traded on the Russian stock market. The results demonstrate that the 3 moment utility significantly outperforms the 2 moment utility by SD, MAD and CVaR for low levels of absolute risk aversion and by portfolio returns and investor utility level during the whole forecast period.
    Keywords: portfolio optimization, asymmetry of returns, risk aversion, GO-GARCH, normal-inverse Gaussian distribution, utility approach.
    JEL: C13 C22 C58 G11 G17
    Date: 2019
  7. By: Sandrine Lecarpentier; Mathias Lé; Henri Fraisse; Michel Dietsch
    Abstract: Starting in 2014 with the implementation of the European Commission Capital Requirement Directive, banks operating in the Euro area were benefiting from a 25% reduction (the Supporting Factor or "SF" hereafter) in their own funds requirements against Small and Medium-sized enterprises ("SMEs" hereafter) loans. We investigate empirically whether this reduction has supported SME financing and to which extent it is consistent with SME credit risk. Economic capital computations based on multifactor models do confirm that capital requirements should be lower for SMEs. Taking into account the uncertainty surrounding their estimates and adopting a conservative approach, we show that the SF is consistent with the difference in economic capital between SMEs and large corporates. As for the impact on credit distribution, our differences-in-differences specification enables us to find a positive and significant impact of the SF on the credit supply.
    Keywords: SME finance, Credit supply, Basel III, Credit risk modelling, SME Supporting Factor
    JEL: C13 G21 G33
    Date: 2019
  8. By: Donaldson, Jason, Roderick; Micheler, Eva
    Abstract: Many debt claims, such as bonds, are resaleable, whereas others, such as repos, are not. There was a fivefold increase in repo borrowing before the 2008 crisis. Why? Did banks’ dependence on non-resaleable debt precipitate the crisis? In this paper, we develop a model of bank lending with credit frictions. The key feature of the model is that debt claims are heterogeneous in their resaleability. We find that decreasing credit market frictions leads to an increase in borrowing via non-resaleable debt. Borrowing via non-resaleable debt has a dark side: it causes credit chains to form, since if a bank makes a loan via non-resaleable debt and needs liquidity, it cannot sell the loan but must borrow via a new contract. These credit chains are a source of systemic risk, since one bank’s default harms not only its creditors but also its creditors’ creditors. Overall, our model suggests that reducing credit market frictions may have an adverse effect on the financial system and may even lead to the failures of financial institutions.
    Keywords: resaleable debt; systemic risk; bankruptcy; repos; securities law
    JEL: G21 G28 G33 K12 K22
    Date: 2017–12–20
  9. By: Matthias Pelster; Bastian Breitmayer; Tim Hasso
    Abstract: Are cryptocurrency traders driven by a desire to invest in a new asset class to diversify their portfolio or are they merely seeking to increase their levels of risk? To answer this question, we use individual-level brokerage data and study their behavior in stock trading around the time they engage in their first cryptocurrency trade. We find that when engaging in cryptocurrency trading investors simultaneously increase their risk-seeking behavior in stock trading as they increase their trading intensity and use of leverage. The increase in risk-seeking in stocks is particularly pronounced when volatility in cryptocurrency returns is low, suggesting that their overall behavior is driven by excitement-seeking.
    Date: 2019–06
  10. By: Christian Gross; Pierre L. Siklos
    Abstract: We use a factor model and elastic net shrinkage to model a high-dimensional network of European CDS spreads. Our empirical approach allows us to assess the joint transmission of bank and sovereign risk to the non-financial corporate sector. Our findings identify a sectoral clustering in the CDS network, where financial institutions are in the center and non-financial entities as well as sovereigns are grouped around the financial center. The network has a geographical component reflected in different patterns of real-sector risk transmission across countries. Our framework also provides dynamic estimates of risk transmission, a useful tool for systemic risk monitoring.
    Keywords: networks, financial-real linkages, connectedness, systemic risk, credit risk, contagion, large datasets
    JEL: C32 C38 F3 G01 G15
    Date: 2019–06
  11. By: Manabu Asai (Faculty of Economics, Soka University, Japan); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Michael McAleer (Department of Finance, Asia University, Taiwan; Discipline of Business Analytics, University of Sydney Business School, Australia; Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands; Department of Economic Analysis and ICAE Complutense University of Madrid, Spain and Institute of Advanced Sciences, Yokohama National University, Japan)
    Abstract: For purposes of forecasting the covariance matrix for the returns of crude oil and gold futures, this paper examines the effects of leverage, jumps, spillovers, and geopolitical risks, using their respective realized covariance matrices. In order to guarantee the positive definiteness of the forecasts, we consider the full BEKK structure on the conditional Wishart model. By the specification, we can divide flexibly the direct and spillover effects of volatility feedback, negative returns, and jumps. The empirical analysis indicates the benefits in accommodating the spillover effects of negative returns and the geopolitical risks indicator for modelling and forecasting the future covariance matrix.
    Keywords: Commodity Markets, Co-volatility, Forecasting, Geopolitical Risks, Jumps, Leverage Effects, Spillover Effects, Realized Covariance
    JEL: C32 C33 C58 Q02
    Date: 2019–07
  12. By: Darjus Hosszejni; Gregor Kastner
    Abstract: Stochastic volatility (SV) models are nonlinear state-space models that enjoy increasing popularity for fitting and predicting heteroskedastic time series. However, due to the large number of latent quantities, their efficient estimation is non-trivial and software that allows to easily fit SV models to data is rare. We aim to alleviate this issue by presenting novel implementations of four SV models delivered in two R packages. Several unique features are included and documented. As opposed to previous versions, stochvol is now capable of handling linear mean models, heavy-tailed SV, and SV with leverage. Moreover, we newly introduce factorstochvol which caters for multivariate SV. Both packages offer a user-friendly interface through the conventional R generics and a range of tailor-made methods. Computational efficiency is achieved via interfacing R to C++ and doing the heavy work in the latter. In the paper at hand, we provide a detailed discussion on Bayesian SV estimation and showcase the use of the new software through various examples.
    Date: 2019–06
  13. By: de Oliveira Souza, Thiago (Department of Business and Economics)
    Abstract: Within a standard risk-based asset pricing framework with rational expectations, realized returns have two components: Predictable risk premiums and unpredictable shocks. In bad times, the price of risk increases. Hence, the predictable fraction of returns – and predictability – increases. “Disagreement” (dispersion in analyst forecasts) also intensifies in bad times if (i) analysts report (close to) risk-neutral expectations weighted by state prices, which become more volatile, or (ii) dividend volatility changes with the price of risk – for example, because consumption volatility changes. In both cases, individual analysts produce unbiased forecasts based on partial information.
    Keywords: Predictability; bad times; efficient market hypothesis; disagreement; rational expectations
    JEL: G11 G12 G14
    Date: 2019–06–26
  14. By: Nicola Comincioli; Sergio Vergalli; Paolo Panteghini
    Abstract: In this article we use a stochastic model with one representative firm to study business tax policy under default risk. We will show that, for a given tax rate, the government has an incentive to reduce (increase) financial instability and default costs if its objective function is welfare (tax revenue).
    Keywords: capital structure, default risk, business taxation and welfare
    JEL: H25 G33 G38
    Date: 2019
  15. By: PAulo Roberto Scalco (FACE-UFG); Benjamin M. Tabak; Anderson Mutter Teixeira (FACE/UFG)
    Abstract: In the aftermath of the financial crisis of 2008 and 2009, there is a series of changes in the scenario of financial regulation. Globally, several macroprudential measures that seek to limit systemic risk are currently in use. We evaluated the e ect of these measures on the market power of banks in the Brazilian case, in which there was a process of great banking concentration that coexists with high bank spreads. Using an innovative methodology, we show that the e ect of macroprudential measures is to reduce bank competition by increasing the market power of banks. It is essential that financial regulators consider this adverse effect in the design of a financial regulation that not only aims at financial stability but also a more competitive banking system.
    Keywords: Bank Regulation, Prudential Measures, Market Power, Lerner Index, Stochastic Frontier.
    Date: 2019–06
  16. By: Antonis A. Michis (Central Bank of Cyprus)
    Abstract: Gold is frequently cited by investors as a financial asset that can be associated with a negative beta coefficient. I investigate this hypothesis by estimating the beta coefficient of gold at different timescales and examining the associated implications for investors with different planning horizons. Estimation is performed using maximal overlap discrete wavelet transforms of gold and stock market returns in four major currencies. The results suggest that gold tends to be associated with a negative beta coefficient when considering long-term investment horizons, and this finding is consistent across markets and currencies.
    Keywords: gold returns; systematic risk; timescales; wavelets
    JEL: G11 G12 G15
    Date: 2018–03
  17. By: Irina Georgescu; Louis Aim\'e Fono
    Abstract: Possibilistic risk theory starts from the hypothesis that risk is modelled by fuzzy numbers. In particular, in a possibilistic portfolio choice problem, the return of a risky asset will be a fuzzy number. The expected utility operators have been introduced in a previous paper to build an abstract theory of possibilistic risk aversion. To each expected utility operator one can associate a notion of possibilistic expected utility. Using this notion, we will formulate in this very general context a possibilistic choice problem. The main results of the paper are two approximate calculation formulas for corresponding optimization problem. The first formula approximates the optimal allocation with respect to risk aversion and investor's prudence, as well as the first three possibilistic moments. Besides these parameters, in the second formula the temperance index of the utility function and the fourth possibilistic moment appear.
    Date: 2019–06
  18. By: Patrick Meyer; Grégory Ponthiere
    Date: 2019
  19. By: Cappelletti, Giuseppe; Peeters, Jonas; Budrys, Žymantas; Varraso, Paolo; Marques, Aurea Ponte
    Abstract: We study the impact of higher bank capital buffers, namely of the Other Systemically Important Institutions (O-SII) buffer, on banks' lending and risk-taking behaviour. The O-SII buffer is a macroprudential policy aiming to increase banks' resilience. However, higher capital requirements associated with the policy may likely constrain lending. While this may be a desired effect of the policy, it could, at least in the short-term, pose costs for economic activity. Moreover, by changing the relative attractiveness of different asset classes, a higher capital requirement could also lead to risk-shifting and therefore promote the build-up (or deleverage) of banks' risk-taking. Since the end of 2015, national authorities, under the EBA framework, started to identify banks as O-SII and impose additional capital buffers. The identification of the O-SII is mainly based on a cutoff rule, ie. banks whose score is above a certain threshold are automatically designated as systemically important. This feature allows studying the effects of higher capital requirements by comparing banks whose score was close to the threshold. Relying on confidential granular supervisory data, between 2014 and 2017, we find that banks identified as O-SII reduced, in the short-term, their credit supply to households and financial sectors and shifted their lending to less risky counterparts within the non-financial corporations. In the medium-term, the impact on credit supply is defused and banks shift their lending to less risky counterparts within the financial and household sectors. Our findings suggest that the discontinuous policy change had limited effects on the overall supply of credit although we find evidence of a reduction in the credit supply at the inception of the macroprudential policy. This result supports the hypothesis that the implementation of the O-SII's framework could have a positive disciplining effect by reducing banks' risk-taking while having only a reduced adverse impact JEL Classification: E44, E51, E58, G21, G28
    Keywords: bank capital-based measures, bank risk-shifting, credit supply, macroprudential policy, systemic risk
    Date: 2019–06
  20. By: Degiannakis, Stavros; Filis, George
    Abstract: Contrary to the current practice that mainly considers stand-alone statistical loss functions, the aim of the paper is to assess oil price volatility forecasts based on objective-based evaluation criteria, given that different forecasting models may exhibit superior performance at different applications. To do so, we forecast implied and several intraday volatilities and we evaluate them based on financial decisions for which these forecasts are used. In this study we confine our interest on the use of such forecasts from financial investors. More specifically, we consider four well established trading strategies, which are based on volatility forecasts, namely (i) trading the implied volatility based on the implied volatility forecasts, (ii) trading implied volatility based on intraday volatility forecasts, (iii) trading straddles in the United States Oil Fund ETF and finally (iv) trading the United States Oil Fund ETF based on implied and intraday volatility forecasts. We evaluate the after-cost profitability of each forecasting model for 1-day up to 66-days ahead. Our results convincingly show that our forecasting framework is economically useful, since different models provide superior after-cost profits depending on the economic use of the volatility forecasts. Should investors evaluate the forecasting models based on statistical loss functions, then their financial decisions would be sub-optimal. Thus, we maintain that volatility forecasts should be evaluated based on their economic use, rather than statistical loss functions. Several robustness tests confirm these findings.
    Keywords: Volatility forecasting, implied volatility, intraday volatility, WTI crude oil futures, objective-based evaluation criteria.
    JEL: C22 C53 G11 G17 Q47
    Date: 2019–06–11

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