|
on Risk Management |
| By: | Thomas J.Flavin (Department of Economics Finance and Accounting, National University of Ireland, Maynooth); Mardi Dungey (Tasmanian School of Business and Economics, University of Tasmania, Hobart, TAS 7001, Australia); Thomas O'Connor (Department of Economics Finance and Accounting, National University of Ireland, Maynooth); Michael Wosser (Financial Stability Division, Central Bank of Ireland, Dublin, Ireland.) |
| Abstract: | We investigate the systemic importance of U.S. industrial firms and analyse the firm-specific characteristics that identify systemically important industrials. We compute two firm-specific measures of systemic risk for 367 non-financial corporations and confirm that industrial firms are both vulnerable to systemic shocks and contribute to system-wide risk. Systemic risk measures exhibit substantial variation across firms and over time. Debt and trade credit are related to both dimensions of systemic risk, while a range of other firm characteristics are associated with systemic risk in at least one direction. The differences between the dimensions of risk and their associated characteristics underline the importance of analysing both measures of risk. Finally, we report some striking differences vis-Ã -vis the extant literature on banks and non-bank financials. |
| Keywords: | Systemic risk; MES; ∆CoVaR; industrial firms; financial crises. |
| JEL: | G32 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:may:mayecw:n298-20.pdf&r=all |
| By: | Liu,Jinjing |
| Abstract: | The co-dependence between assets tends to increase when the market declines. This paper develops a correlation measure focusing on market declines using the expected shortfall (ES), referred to as the ES-implied correlation, to improve the existing value at risk (VaR)-implied correlation. Simulations which define period-by-period true correlations show that the ES-implied correlation is much closer to true correlations than is the VaR-implied correlation with respect to average bias and root-mean-square error. More importantly, this paper develops a series of test statistics to measure and test correlation asymmetries, as well as to evaluate the impact of weights on the VaR-implied correlation and the ES-implied correlation. The test statistics indicate that the linear correlation significantly underestimates correlations between the US and the other G7 countries during market downturns, and the choice of weights does not have significant impact on the VaR-implied correlation or the ES-implied correlation. |
| Keywords: | Capital Markets and Capital Flows,Securities Markets Policy&Regulation,Capital Flows |
| Date: | 2019–01–17 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:wbrwps:8709&r=all |
| By: | Osman Gulseven; Kasirga Yildirak |
| Abstract: | This study estimates the risk contributions of individual European countries regarding the indemnity payments in agricultural insurance. We model the total risk exposure as an insurance portfolio where each country is unique in terms of its risk characteristics. The data has been collected from the recent surveys conducted by the European Commission and the World Bank. Farm Accountancy Data Network is used as well. 22 out of 26 member states are included in the study. The results suggest that the EuroMediterranean countries are the major risk contributors. These countries not only have the highest expected loss but also high volatility of indemnity payments. Nordic countries have the lowest indemnity payments and risk exposure. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.05726&r=all |
| By: | Raphael A Espinoza; Miguel A. Segoviano; Ji Yan |
| Abstract: | We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire sales, and a “Minsky" cycle of optimism. The empirical model uses stock market and CDS spreads data to estimate a multivariate density of equity returns and to compute the expected equity return for each bank, conditional on a bad macro-outcome. Theses “cross-sectional" moments are used to re-calibrate the theoretical model and estimate the importance of the Minsky cycle of optimism in driving systemic risk. |
| Date: | 2020–03–13 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:20/54&r=all |
| By: | Ruenzi, Stefan; Ungeheuer, Michael; Weigert, Florian |
| Abstract: | We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a stock's return (liquidity) is lowest at the same time when the market liquidity (return) is lowest. This effect is not driven by linear or downside liquidity risk or extreme downside return risk and is mainly driven by more recent years. There is no premium for stocks whose liquidity is lowest when market liquidity is lowest. |
| Keywords: | Asset Pricing,Crash Aversion,Downside Risk,Liquidity Risk,Tail Risk |
| JEL: | C12 C13 G01 G11 G12 G17 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cfrwps:2001&r=all |
| By: | Cheng Cai; Tiziano De Angelis; Jan Palczewski |
| Abstract: | It is well-known that using delta hedging to hedge financial options is not feasible in practice. Traders often rely on discrete-time hedging strategies based on fixed trading times or fixed trading prices (i.e., trades only occur if the underlying asset's price reaches some predetermined values). Motivated by this insight and with the aim of obtaining explicit solutions, we consider the seller of a perpetual American put option who can hedge her portfolio once until the underlying stock price leaves a certain range of values $(a,b)$. We determine optimal trading boundaries as functions of the initial stock holding, and an optimal hedging strategy for a bond/stock portfolio. Optimality here refers to the variance of the hedging error at the (random) time when the stock leaves the interval $(a,b)$. Our study leads to analytical expressions for both the optimal boundaries and the optimal stock holding, which can be evaluated numerically with no effort. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.06249&r=all |
| By: | Alexander J. McNeil |
| Abstract: | An approach to the modelling of financial return series using a class of uniformity-preserving transforms for uniform random variables is proposed. V-transforms describe the relationship between quantiles of the return distribution and quantiles of the distribution of a predictable volatility proxy variable constructed as a function of the return. V-transforms can be represented as copulas and permit the construction and estimation of models that combine arbitrary marginal distributions with linear or non-linear time series models for the dynamics of the volatility proxy. The idea is illustrated using a transformed Gaussian ARMA process for volatility, yielding the class of VT-ARMA copula models. These can replicate many of the stylized facts of financial return series and facilitate the calculation of marginal and conditional characteristics of the model including quantile measures of risk. Estimation of models is carried out by adapting the exact maximum likelihood approach to the estimation of ARMA processes. |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2002.10135&r=all |
| By: | Raphaël Douady (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Question of the day: how to manage a large (or small) portfolio in low interest rate conditions, while equity markets bear significant draw-down risk? More generally, how to build an "antifragile" portfolio that can weather the most extreme market scenarios without impacting long-term performances? Do active strategies systematically create or increase already existing market instabilities? By analyzing in depth markets behavior during past speculative bubbles and credit crises, we aim at addressing these questions. Our goal is to describe as faithfully as possible the major mechanisms at stake, avoiding the trap of mapping the complexity of financial markets into a single mathematical model, which would necessarily be wrong at some point. Starting from Minsky's "Financial Instability Hypothesis", we try to disentangle the complex relation between dynamics and randomness, including the presence of "fat tails". We provide methods to monitor the evolving probability of a forthcoming crisis through the measurement of "market instability". Scalable investment strategies result from the application of these methods. 2 |
| Date: | 2019–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:hal-02488589&r=all |
| By: | Kiss, Tamás (Örebro University School of Business); Österholm, Pär (Örebro University School of Business) |
| Abstract: | In this paper, we illustrate the macroeconomic risk associated with the early stage of the corona-virus outbreak. Using monthly data ranging from July 1991 to March 2020 on a recently developed coincidence indicator of global output growth, we estimate an autoregressive model with GARCH effects and non-Gaussian disturbances. Our results indicate that i) accounting for conditional heteroscedasticity is important and ii) risk, measured as the volatility of the shocks to the process, is at a very high level – largely on par with that experienced around the financial crisis of 2008-2009. |
| Keywords: | GARCH; Non-Gaussianity |
| JEL: | C22 E32 E37 |
| Date: | 2020–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:oruesi:2020_002&r=all |
| By: | Marcelo Brutti Righi |
| Abstract: | The inf-convolution of risk measures is directly related to risk sharing and general equilibrium, and it has attracted considerable attention in mathematical finance and insurance problems. However, the theory is restricted to finite (or at most countable in rare cases) sets of risk measures. In this study, we extend the inf-convolution of risk measures in its convex-combination form to an arbitrary (not necessarily finite or even countable) set of alternatives. The intuitive principle of this approach is to regard a probability measure as a generalization of convex weights in the finite case. Subsequently, we extensively generalize known properties and results to this framework. Specifically, we investigate the preservation of properties, dual representations, optimal allocations, and self-convolution. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.05797&r=all |
| By: | Reichlin, Lucrezia; Ricco, Giovanni; Hasenzagl, Thomas |
| Abstract: | We evaluate the role of financial conditions as predictors of macroeconomic risk first in the quantile regression framework of Adrian et al. (2019b), which allows for non-linearities, and then in a novel linear semi-structural model as proposed by Hasenzagl et al. (2018). We distinguish between price variables such as credit spreads and stock variables such as leverage. We find that (i) although the spreads correlate with the left tail of the conditional distribution of GDP growth, they provide limited advanced information on growth vulnerability; (ii) nonfinancial leverage provides a leading signal for the left quantile of the GDP growth distribution in the 2008 recession; (iii) measures of excess leverage conceptually similar to the Basel gap, but cleaned from business cycle dynamics via the lenses of the semi-structural model, point to two peaks of accumulation of risks - the eighties and the first eight years of the new millennium, with an unstable relationship with business cycle chronology. |
| Keywords: | financial cycle,business cycle,credit,financial crises,downside risk,entropy,quantile regressions |
| JEL: | E32 E44 C32 C53 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:052020&r=all |
| By: | Claudiu Albulescu (CRIEF); Aviral Tiwari; Qiang Ji |
| Abstract: | This paper studies the extreme dependencies between energy, agriculture and metal commodity markets, with a focus on local co-movements, allowing the identification of asymmetries and changing trend in the degree of co-movements. More precisely, starting from a non-parametric mixture copula, we use a novel copula-based local Kendall's tau approach to measure nonlinear local dependence in regions. In all pairs of commodity indexes, we find increased co-movements in extreme situations, a stronger dependence between energy and other commodity markets at lower tails, and a 'V-type' local dependence for the energy-metal pairs. The three-dimensional Kendall's tau plot for upper tails in quantiles shows asymmetric co-movements in the energy-metal pairs, which tend to become negative at peak returns. Therefore, we show that the energy market can offer diversification solutions for risk management in the case of extreme bull market events. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.04007&r=all |
| By: | Ralph Chami; Thomas F. Cosimano; Celine Rochon; Julieta Yung |
| Abstract: | Investors seek to hedge against interest rate risk by taking long or short positions on bonds of different maturities. We study changes in risk taking behavior in a low interest rate environment by estimating a market stochastic discount factor that is non-linear and therefore consistent with the empirical properties of cashflow valuations identified in the literature. We provide evidence that non-linearities arise from hedging strategies of investors exposed to interest rate risk. Capital losses are amplified when interest rates increase and risk averse investors have taken positions on instruments with longer maturity, expecting instead interest rates to revert back to their historical average. |
| Date: | 2020–03–13 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:20/53&r=all |
| By: | Xingxing Ye; Raphaël Douady (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | The global financial market has become extremely interconnected as it demonstrates strong nonlinear contagion in times of crisis. As a result, it is necessary to measure financial systemic risk in a comprehensive and nonlinear approach. By establishing a large set of risk factors as the main bones of the financial market network and applying nonlinear factor analysis in the form of so-called PolyModel, this paper proposes two systemic risk indicators that can prognosticate the advent and trace the development of financial crises. Through financial network analysis, theoretical simulation, empirical data analysis and final validation, we argue that the indicators suggested in this paper are proved to be very effective in forecasting and tracing the financial crises from 1998 to 2017. The economic benefit of the indicator is evidenced by the enhancement of a protective put/covered call strategy on major stock markets. |
| Keywords: | validation,PolyModel,nonlinear regression,network,financial indicator,systemic risk crisis,Indicators,Poly-Model,Systemic Risk,Nonlinear |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:hal-02488592&r=all |
| By: | Thomas R. Cook; Taeyoung Doh |
| Abstract: | We use a large set of economic and financial indicators to assess tail risks of the three macroeconomic variables: real GDP, unemployment, and inflation. When applied to U.S. data, we find evidence that a dense model using principal components (PC) as predictors might be misspecified by imposing the “common slope” assumption on the set of predictors across multiple quantiles. The common slope assumption ignores the heterogeneous informativeness of individual predictors on different quantiles. However, the parsimony of the PC-based approach improves the accuracy of out-of-sample forecasts when combined with a sparse model using the dynamic model averaging method. Out-of-sample analysis of U.S. data suggests that the downside risk for real macro variables spiked to by the end of the Great Recession but subsequently declined to a negligible level. On the other hand, the downside tail risk for inflation fluctuated around a non-negligible level even after the end of the Great Recession. The disconnect between the downside risk of inflation and that of real activities can be in line with the evidence for the reduced role of the output gap for inflation during the recent period. |
| Keywords: | Quantile Regressions; Tail Risks; Variable Selection; Dynamic Model Averaging |
| JEL: | C22 C55 E27 E37 |
| Date: | 2019–11–20 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedkrw:87675&r=all |
| By: | Claudiu Albulescu (CRIEF - Centre de Recherche sur l'Intégration Economique et Financière - Université de Poitiers); Aviral Tiwari (ICFAI University Tripura - ICFAI University Tripura); Qiang Ji |
| Abstract: | This paper studies the extreme dependencies between energy, agriculture and metal commodity markets, with a focus on local co-movements, allowing the identification of asymmetries and changing trend in the degree of co-movements. More precisely, starting from a non-parametric mixture copula, we use a novel copula-based local Kendall's tau approach to measure nonlinear local dependence in regions. In all pairs of commodity indexes, we find increased co-movements in extreme situations, a stronger dependence between energy and other commodity markets at lower tails, and a 'V-type' local dependence for the energy-metal pairs. The three-dimensional Kendall's tau plot for upper tails in quantiles shows asymmetric co-movements in the energy-metal pairs, which tend to become negative at peak returns. Therefore, we show that the energy market can offer diversification solutions for risk management in the case of extreme bull market events. |
| Keywords: | energy prices,commodity markets,local dependence,co-movements and contagion,mixture copula,local Kendall's tau JEL Classification: C22 |
| Date: | 2020–03–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02501815&r=all |
| By: | Walther, Ansgar |
| Abstract: | This paper studies optimal financial policy in a world where the financial sector can become excessively optimistic. I decompose the welfare effects of bank capital regulation to demonstrate the effects of exuberance and its interaction with incentive problems in banking. The optimal policy depends not only on the extent, but also on the type of optimism. For example, it is markedly different when the exuberance of banks focuses on neglected downside risk, as opposed to overstated upside opportunities. A central normative conclusion is that “leaning against the wind”, by tightening capital requirements in exuberant times, can be counterproductive. I show that two natural metrics, describing the distortion in perceived upside and downside risk, are sufficient statistics for the policy implications of exuberance. My results shed light on the diverse empirical evidence on the relationship between bank capital and risk-taking. Finally, I investigate the sensitivity of these insights under different assumptions about government rationality and paternalism. JEL Classification: G01, G21, G40 |
| Keywords: | banking, behavioral finance, financial crises, macroprudential policy |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20202380&r=all |
| By: | Shane Barratt; Jonathan Tuck; Stephen Boyd |
| Abstract: | We consider a collection of derivatives that depend on the price of an underlying asset at expiration or maturity. The absence of arbitrage is equivalent to the existence of a risk-neutral probability distribution on the price; in particular, any risk neutral distribution can be interpreted as a certificate establishing that no arbitrage exists. We are interested in the case when there are multiple risk-neutral probabilities. We describe a number of convex optimization problems over the convex set of risk neutral price probabilities. These include computation of bounds on the cumulative distribution, VaR, CVaR, and other quantities, over the set of risk-neutral probabilities. After discretizing the underlying price, these problems become finite dimensional convex or quasiconvex optimization problems, and therefore are tractable. We illustrate our approach using real options and futures pricing data for the S&P 500 index and Bitcoin. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.02878&r=all |
| By: | Christian Bongiorno (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec); Damien Challet (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec) |
| Abstract: | Cleaning covariance matrices is a highly non-trivial problem, yet of central importance in the statistical inference of dependence between objects. We propose here a probabilistic hierarchical clustering method, named Bootstrapped Average Hierarchical Clustering (BAHC) that is particularly effective in the high-dimensional case, i.e., when there are more objects than features. When applied to DNA microarray, our method yields distinct hierarchical structures that cannot be accounted for by usual hierarchical clustering. We then use global minimum-variance risk management to test our method and find that BAHC leads to significantly smaller realized risk compared to state-of-the-art linear and nonlinear filtering methods in the high-dimensional case. Spectral decomposition shows that BAHC better captures the persistence of the dependence structure between asset price returns in the calibration and the test periods. |
| Date: | 2020–03–12 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02506848&r=all |
| By: | Christian Bongiorno; Damien Challet |
| Abstract: | Statistical inference of the dependence between objects often relies on covariance matrices. Unless the number of features (e.g. data points) is much larger than the number of objects, covariance matrix cleaning is necessary to reduce estimation noise. We propose a method that is robust yet flexible enough to account for fine details of the structure covariance matrix. Robustness comes from using a hierarchical ansatz and dependence averaging between clusters; flexibility comes from a bootstrap procedure. This method finds several possible hierarchical structures in DNA microarray gene expression data, and leads to lower realized risk in global minimum variance portfolios than current filtering methods when the number of data points is relatively small. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.05807&r=all |
| By: | Taurai Muvunza |
| Abstract: | We investigate the behaviour of cryptocurrencies' return data. Using return data for bitcoin, ethereum and ripple which account for over 70% of the cyrptocurrency market, we demonstrate that $\alpha$-stable distribution models highly speculative cryptocurrencies more robustly compared to other heavy tailed distributions that are used in financial econometrics. We find that the Maximum Likelihood Method proposed by DuMouchel (1971) produces estimates that fit the cryptocurrency return data much better than the quantile based approach of McCulloch (1986) and sample characteristic method by Koutrouvelis (1980). The empirical results show that the leptokurtic feature presented in cryptocurrencies' return data can be captured by an ${\alpha}$-stable distribution. This papers covers predominant literature in cryptocurrencies and stable distributions. |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2002.09881&r=all |
| By: | Claudiu Albulescu (CRIEF - Centre de Recherche sur l'Intégration Economique et Financière - Université de Poitiers) |
| Abstract: | 40 days after the start of the international monitoring of COVID-19, we search for the effect of official announcements regarding new cases of infection and death ratio on the financial markets volatility index (VIX). Whereas the new cases reported in China and outside China have a mixed effect on financial volatility, the death ratio positively influences VIX, that outside China triggering a more important impact. In addition, the higher the number of affected countries, the higher the financial volatility is. |
| Keywords: | coronavirus,financial volatility,VIX,announcement effect |
| Date: | 2020–03–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02501814&r=all |
| By: | Hirdesh K. Pharasi; Eduard Seligman; Thomas H. Seligman |
| Abstract: | We present the clustering analysis of the financial markets of S&P 500 (USA) and Nikkei 225 (JPN) markets over a period of 2006-2019 as an example of a complex system. We investigate the statistical properties of correlation matrices constructed from the sliding epochs. The correlation matrices can be classified into different clusters, named as market states based on the similarity of correlation structures. We cluster the S&P 500 market into four and Nikkei 225 into six market states by optimizing the value of intracluster distances. The market shows transitions between these market states and the statistical properties of the transitions to critical market states can indicate likely precursors to the catastrophic events. We also analyze the same clustering technique on surrogate data constructed from average correlations of market states and the fluctuations arise due to the white noise of short time series. We use the correlated Wishart orthogonal ensemble for the construction of surrogate data whose average correlation equals the average of the real data. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.07058&r=all |
| By: | Paolo Mauro; Jing Zhou |
| Abstract: | Contrary to the traditional assumption of interest rates on government debt exceeding economic growth, negative interest-growth differentials have become prevalent since the global financial crisis. As these differentials are a key determinant of public debt dynamics, can we sleep more soundly, despite high government debts? Our paper undertakes an empirical analysis of interestgrowth differentials, using the largest historical database on average effective government borrowing costs for 55 countries over up to 200 years. We document that negative differentials have occurred more often than not, in both advanced and emerging economies, and have often persisted for long historical stretches. Moreover, differentials are no higher prior to sovereign defaults than in normal times. Marginal (rather than average) government borrowing costs often rise abruptly and sharply, but just prior to default. Based on these results, our answer is: not really. |
| Date: | 2020–03–13 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:20/52&r=all |
| By: | Boot, Arnoud W. A.; Carletti, Elena; Kotz, Hans-Helmut; Krahnen, Jan Pieter; Pelizzon, Loriana; Subrahmanyam, Marti G. |
| Abstract: | In this SAFE Policy letter on the implications of the Coronavirus for financial stability in Europe, we address how to mitigate a systemic financial crisis that is propagating in slow motion, as we speak, and which we identified and diagnosed in the SAFE policy letter 782. This second letter emphasizes the speed at which the underlying unprecedented real sector cash drains and how asymmetric national solutions may be destabilizing in the longer run. Our main conclusion: A coordinated fiscal plan at the pan-European level, complementing national measures, is crucial for financial stability in Europe. The plan has to be substantial in size, implemented immediately, and backed by a common fiscal backstop. While today's policy actions have to be undertaken inevitably at a quickened pace, it is paramount to also account for the longer-term implications of the chosen policies and instruments for a post-crisis Europe now. (...) |
| Keywords: | coronavirus,financial stability,systemic risk |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:safepl:79&r=all |
| By: | Edge, Rochelle M.; Liang, Jean Nellie |
| Abstract: | Multi-agency financial stability committees (FSCs) have grown dramatically since the global financial crisis. However, most cannot direct actions or recommend to other agencies that they take actions, and most would influence policy actions only through convening and discussing risks. We evaluate whether the significant variation in FSCs and other financial regulatory structures across countries affect decisions to use the countercyclical capital buffer (CCyB). After controlling for credit growth and the severity of the financial crisis, we find that countries with stronger FSCs are more likely to use the CCyB, especially relative to countries where a bank regulator or the central bank has the authority to set the CCyB. While the experience with the CCyB is still limited, these results are consistent with some countries creating FSCs with strong governance to take actions, but most countries instead creating weak FSCs without mechanisms to promote actions, consistent more with a symbolic political delegation motive and raising questions about accountability for financial stability. |
| Keywords: | Financial stability committees,Bank regulators,Delegation,Macroprudential policy,Countercyclical capital buffer,Credit growth |
| JEL: | H11 G21 G28 P16 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:042020&r=all |
| By: | Flagmeier, Vanessa; Gawehn, Vanessa |
| Abstract: | We assess the investor reaction to a potential introduction of public country-by-country reporting (CbCR) into the European Capital Requirements Directive IV. Estimating cumulative abnormal returns with the help of a multivariate regression model, we find weak significant evidence around our event date (February 20th, 2013) that investors perceive the introduction of CbCR as beneficial. In additional tests, we assess investor perceptions relative to different control groups (domestic institutions and non-EU institutions) and in the cross-section (splitting across size, systemically relevant, pre-event level of GAAP ETR and pre-event level of geographic disclosure). The only significant outcome is a negative reaction for large international EU institutions. |
| Keywords: | Country-by-country reporting,CbCR,financial institutions,investor reactions,eventstudy,multivariate regression model |
| JEL: | H25 H26 G21 G28 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:arqudp:254&r=all |
| By: | Perez-Quiros, Gabriel; Rots, Eyno; Leiva-Leon, Danilo |
| Abstract: | We propose an empirical framework to measure the degree of weakness of the global economy in real-time. It relies on nonlinear factor models designed to infer recessionary episodes of heterogeneous deepness, and fitted to the largest advanced economies (U.S., Euro Area, Japan, U.K., Canada and Australia) and emerging markets (China, India, Russia, Brazil, Mexico and South Africa). Based on such inferences, we construct a Global Weakness Index that has three main features. First, it can be updated as soon as new regional data is released, as we show by measuring the economic effects of coronavirus. Second, it provides a consistent narrative of the main regional contributors of world economy's weakness. Third, it allows to perform robust risk assessments based on the probability that the level of global weakness would exceed a certain threshold of interest in every period of time. JEL Classification: E32, C22, E27 |
| Keywords: | business cycles, factor model, international, nonlinear |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20202381&r=all |
| By: | Patrick Bolton; Neng Wang; Jinqiang Yang |
| Abstract: | We develop a q theory of investment with endogenous leverage, payout, hedging, and risk-taking dynamics. The key frictions are costly equity issuance and incomplete markets. We show that the marginal source of external financing on an on-going basis is debt. The firm lowers its debt when making a profit, increases its debt in response to losses and induced higher interest payments, and even taps external equity markets at a cost before exhausting its endogenous debt capacity. The firm seeks to preserve its financial flexibility by prudently managing its leverage and investment. Paradoxically, it is the high cost of equity issuance that causes the firm to keep leverage low, in contrast to the predictions of static Modigliani-Miller tradeoff and Myers-Majluf pecking-order theories. Our model generates leverage and investment dynamics that are consistent with the empirical evidence. |
| JEL: | G11 G31 G32 G35 |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26802&r=all |
| By: | Masaaki Fukasawa |
| Abstract: | First, we give an asymptotic expansion of short-dated at-the-money implied volatility that refines the preceding works and proves in particular that non-rough volatility models are inconsistent to a power law of volatility skew. Second, we show that given a power law of volatility skew in an option market, a continuous price dynamics of the underlying asset with non-rough volatility admits an arbitrage opportunity. The volatility therefore has to be rough in a viable market of the underlying asset of which the volatility skew obeys a power law. |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2002.09215&r=all |
| By: | Shan Luo (Federal Reserve Bank of Chicago); Anthony Murphy |
| Abstract: | We study and model the determinants of exposure at default (EAD) for large U.S. construction and land development loans from 2010 to 2017. EAD is an important component of credit risk, and commercial real estate (CRE) construction loans are more risky than income producing loans. This is the first study modeling the EAD of construction loans. The underlying EAD data come from a large, confidential supervisory dataset used in the U.S. Federal Reserve’s annual Comprehensive Capital Assessment Review (CCAR) stress tests. EAD reflects the relative bargaining ability and information sets of banks and obligors. We construct OLS and Tobit regression models, as well as several other machine-learning models, of EAD conversion measures, using a four-quarter horizon. The popular LEQ and CCF conversion measure is unstable, so we focus on EADF and AUF measures. Property type, the lagged utilization rate and loan size are important drivers of EAD. Changing local and national economic conditions also matter, so EAD is sensitive to macro-economic conditions. Even though default and EAD risk are negatively correlated, a conservative assumption is that all undrawn construction commitments will be fully drawn in default. |
| Keywords: | Credit Risk; Commercial Real Estate (CRE); Construction; Exposure at Default; EAD Conversion Measures; Macro-sensitivity; Machine Learning |
| JEL: | G21 G28 |
| Date: | 2020–03–17 |
| URL: | http://d.repec.org/n?u=RePEc:fip:feddwp:87677&r=all |
| By: | Jose Cruz; Daniel Sevcovic |
| Abstract: | In this paper we focus on qualitative properties of solutions to a nonlocal nonlinear partial integro-differential equation (PIDE). Using the theory of abstract semilinear parabolic equations we prove existence and uniqueness of a solution in the scale of Bessel potential spaces. Our aim is to generalize known existence results for a wide class of L\'evy measures including with a strong singular kernel. As an application we consider a class of PIDEs arising in the financial mathematics. The classical linear Black-Scholes model relies on several restrictive assumptions such as liquidity and completeness of the market. Relaxing the complete market hypothesis and assuming a Levy stochastic process dynamics for the underlying stock price process we obtain a model for pricing options by means of a PIDE. We investigate a model for pricing call and put options on underlying assets following a Levy stochastic process with jumps. We prove existence and uniqueness of solutions to the penalized PIDE representing approximation of the linear complementarity problem arising in pricing American style of options under Levy stochastic processes. We also present numerical results and comparison of option prices for various Levy stochastic processes modelling underlying asset dynamics. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2003.03851&r=all |