nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒01‒22
25 papers chosen by

  1. Regression Based Expected Shortfall Backtesting By Sebastian Bayer; Timo Dimitriadis
  2. Firm-Level Political Risk: Measurement and Effects By Tarek A. Hassan; Stephan Hollander; Laurence van Lent; Ahmed Tahoun
  3. Optimal Dynamic Capital Requirements By Kalin Nikolov; Javier Suarez; Dominik Supera; Caterina Mendicino
  4. The Fragility of Market Risk Insurance By Ralph Koijen; Motohiro Yogo
  5. A Multivariate Model of Strategic Asset Allocation with Longevity Risk By Emilio Bisetti; Carlo A. Favero; Giacomo Nocera; Claudio Tebaldi
  6. The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the Global Financial Crisis By Danilo Delpini; Stefano Battiston; Guido Caldarelli; Massimo Riccaboni
  7. A time change strategy to model reporting delay dynamics in claims reserving By Jonas Crevecoeur; Katrien Antonio; Roel Verbelen
  8. Default Cycles By Leo Kaas; Wei Cui
  9. News and narratives in financial systems: exploiting big data for systemic risk assessment By Nyman, Rickard; Kapadia, Sujit; Tuckett, David; Gregory, David; Ormerod, Paul; Smith, Robert
  10. Asymptotic Analysis for Spectral Risk Measures Parameterized by Confidence Level By Takashi Kato
  11. Which Precious metal shines brightest for international investors? : A Vine Copula approach By Marwa Talbi; Rihab Bedoui; Lotfi Belkacem; Christian De Peretti
  12. Rational expectations and stochastic systems By Jorgen-Vitting Andersen; Roy Cerqueti; Giulia Rotundo
  13. Focusing and framing of risky alternatives By Dertwinkel-Kalt, Markus; Wenzel, Tobias
  14. Notes on Fano Ratio and Portfolio Optimization By Zura Kakushadze; Willie Yu
  15. Risk adjusted momentum strategies: a comparison between constant and dynamic volatility scaling approaches By Fan, Minyou; Li, Youwei; Liu, Jiadong
  16. Price Optimisation for New Business By Maissa Tamraz; Yaming Yang
  17. Asymptotic Static Hedge via Symmetrization By Jiro Akahori; Flavia Barsotti; Yuri Imamura
  18. Monitoring Banking System Fragility with Big Data By Hale, Galina; Lopez, Jose A.
  19. Investor Concentration, Flows, and Cash Holdings : Evidence from Hedge Funds By Mathias S. Kruttli; Phillip J. Monin; Sumudu W. Watugala
  20. Bubbles and Bluffs: Risk Lovers Can Survive Economically By Harashima, Taiji
  21. Fund Tradeoffs By Pástor, Luboš; Stambaugh, Robert F.; Taylor, Lucian
  22. Incorporating Macro-Financial Linkages into Forecasts Using Financial Conditions Indices: The Case of France By Piyabha Kongsamut; Christian Mumssen; Anne-Charlotte Paret; Thierry Tressel
  23. RBC LiONS™ S&P 500 Buffered Protection Securities (USD) Series 4 Analysis Option Pricing Analysis, Issuing Company Risk-hedging Analysis, and Recommended Investment Strategy By Tan, Zekuang
  24. The zero risk fallacy? Banks' sovereign exposure and sovereign risk spillovers By Kirschenmann, Karolin; Korte, Josef; Steffen, Sascha
  25. Transition probability of Brownian motion in the octant and its application to default modeling By Vadim Kaushansky; Alexander Lipton; Christoph Reisinger

  1. By: Sebastian Bayer; Timo Dimitriadis
    Abstract: In this article, we introduce a regression based backtest for the risk measure Expected Shortfall (ES) which is based on a joint regression framework for the quantile and the ES. We also introduce a second variant of this ES backtest which allows for testing one-sided hypotheses by only testing an intercept parameter. These two backtests are the first backtests in the literature which solely backtest the risk measure ES as they only require ES forecasts as input parameters. In contrast, the existing ES backtesting techniques require forecasts for further quantities such as the Value at Risk, the volatility or even the entire (tail) distribution. As the regulatory authorities only receive forecasts for the ES, backtests including further input parameters are not applicable in practice. We compare the empirical performance of our new backtests to existing approaches in terms of their empirical size and power through several different simulation studies. We find that our backtests clearly outperform the existing backtesting procedures in the literature in terms of their size and (size-adjusted) power properties throughout all considered simulation experiments. We provide an R package for these ES backtests which is easily applicable for practitioners.
    Date: 2018–01
  2. By: Tarek A. Hassan; Stephan Hollander; Laurence van Lent; Ahmed Tahoun
    Abstract: We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual US firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm's actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. Interestingly, we find that the incidence of political risk across firms is far more heterogeneous and volatile than previously thought. The vast majority of the variation in our measure is at the firm-level rather than at the aggregate or sector-level, in the sense that it is neither captured by time fixed effects and the interaction of sector and time fixed effects, nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.
    JEL: D8 E22 E24 E32 E6 G18 G32 G38 H32
    Date: 2017–11
  3. By: Kalin Nikolov (European Central Bank); Javier Suarez (CEMFI); Dominik Supera (European Central Bank); Caterina Mendicino (European Central Bank)
    Abstract: We characterize welfare maximizing capital requirement policies in a macroeconomic model with household, firm and bank defaults calibrated to Euro Area data. We optimize on the level of the capital requirements applied to each loan class and their sensitivity to changes in default risk. We find that getting the level right (so that bank failure risk remains small) is of foremost importance, while the optimal sensitivity to default risk is positive but typically smaller than under Basel IRB formulas. When starting from low levels, initially both savers and borrowers benefit from higher capital requirements. At higher levels, only savers are in favour of tighter and more time-varying capital charges.
    Date: 2017
  4. By: Ralph Koijen; Motohiro Yogo
    Abstract: Insurers sell retail financial products called variable annuities that package mutual funds with minimum return guarantees over long horizons. Variable annuities accounted for $1.5 trillion or 34 percent of U.S. life insurer liabilities in 2015. Sales fell and fees increased after the 2008 financial crisis as the higher valuation of existing liabilities stressed risk-based capital. Insurers also made guarantees less generous or stopped offering guarantees entirely to reduce risk exposure. We develop an equilibrium model of insurance markets in which financial frictions and market power are important determinants of pricing, contract characteristics, and the degree of market incompleteness.
    JEL: G22 G32
    Date: 2018–01
  5. By: Emilio Bisetti; Carlo A. Favero; Giacomo Nocera (Audencia Business School - Audencia Business School); Claudio Tebaldi
    Abstract: Population-wide increase in life expectancy is a source of aggregate risk. Longevity-linked securities are a natural instrument to reallocate that risk. This paper extends the standard Campbell–Viceira (2005) strategic asset allocation model by including a longevity-linked investment possibility. Model estimation, based on prices for standardized annuities publicly offered by U.S. insurance companies, shows that aggregate shocks to survival probabilities are predictors for long-term returns of the longevity-linked securities, and reveals an unexpected predictability pattern. Valuation of longevity risk premium confirms that longevity-linked securities offer inexpensive funding opportunities to asset managers.
    Date: 2017–10
  6. By: Danilo Delpini; Stefano Battiston; Guido Caldarelli; Massimo Riccaboni
    Abstract: Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk diversification by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and analyse the interplay between diversification, as understood in classical portfolio theory, and similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from models of random allocation of investments. This indicates the existence of strong correlations between fund portfolio strategies. We introduce a simplified model of propagation of financial shocks, that we exploit to show that a systemic risk component origins from the similarity of portfolios. The network is still vulnerable after crisis because of this effect, despite the increase in the diversification of portfolios. Our results indicate that diversification may even increase systemic risk when funds diversify in the same way. Diversification and similarity can play antagonistic roles and the trade-off between the two should be taken into account to properly assess systemic risk.
    Date: 2018–01
  7. By: Jonas Crevecoeur; Katrien Antonio; Roel Verbelen
    Abstract: This paper considers the problem of predicting the number of claims that have already incurred in past exposure years, but which have not yet been reported to the insurer. This is an important building block in the risk management strategy of an insurer since the company should be able to fulfill its liabilities with respect to such claims. Our approach puts emphasis on modeling the time between the occurrence and reporting of claims, the so-called reporting delay. Using data at a daily level we propose a micro-level model for the heterogeneity in reporting delay caused by calendar day effects in the reporting process, such as the weekday pattern and holidays. A simulation study identifies the strengths and weaknesses of our approach in several scenarios compared to traditional methods to predict the number of incurred but not reported claims from aggregated data (i.e. the chain ladder method). We also illustrate our model on a European general liability insurance data set and conclude that the granular approach compared to the chain ladder method is more robust with respect to volatility in the occurrence process. Our framework can be extended to other predictive problems where interest goes to events that incurred in the past but which are subject to an observation delay (e.g. the number of infections during an epidemic).
    Date: 2018–01
  8. By: Leo Kaas (University of Konstanz); Wei Cui (University College London)
    Abstract: Corporate default rates are counter-cyclical and are often accompanied by declines of business credit over prolonged episodes. This paper develops a tractable macroeconomic model in which persistent credit and default cycles are the outcome of variations in self-fulfilling beliefs about credit market conditions. Interest spreads and leverage ratios are determined in optimal credit contracts that reflect the expected default risk of borrowing firms. Next to sunspot shocks, the model also features shocks to recovery rates and to financial intermediation costs. We calibrate the model to evaluate the impact of these different financial shocks on the credit market and on output dynamics. Self-fulfilling changes in credit market expectations trigger sizable reactions in default rates and generate endogenously persistent credit and output cycles. All credit market shocks together account for over 50% of the variation of U.S. GDP growth during 1982-2015.
    Date: 2017
  9. By: Nyman, Rickard (University College London, Centre for the Study of Decision-Making Uncertainty); Kapadia, Sujit (Bank of England); Tuckett, David (University College London, Centre for the Study of Decision-Making Uncertainty); Gregory, David (Bank of England); Ormerod, Paul (University College London, Centre for the Study of Decision-Making Uncertainty); Smith, Robert (University College London, Centre for the Study of Decision-Making Uncertainty)
    Abstract: This paper applies algorithmic analysis to large amounts of financial market text-based data to assess how narratives and sentiment play a role in driving developments in the financial system. We find that changes in the emotional content in market narratives are highly correlated across data sources. They show clearly the formation (and subsequent collapse) of very high levels of sentiment — high excitement relative to anxiety — prior to the global financial crisis. Our metrics also have predictive power for other commonly used measures of sentiment and volatility and appear to influence economic and financial variables. And we develop a new methodology that attempts to capture the emergence of narrative topic consensus which gives an intuitive representation of increasing homogeneity of beliefs prior to the crisis. With increasing consensus around narratives high in excitement and lacking anxiety likely to be an important warning sign of impending financial system distress, the quantitative metrics we develop may complement other indicators and analysis in helping to gauge systemic risk.
    Keywords: Systemic risk; text mining; big data; sentiment; uncertainty; narratives; forecasting; early warning indicators
    JEL: C53 D83 E32 G01 G17
    Date: 2018–01–05
  10. By: Takashi Kato
    Abstract: We study the asymptotic behavior of the difference $\Delta \rho ^{X, Y}_\alpha := \rho _\alpha (X + Y) - \rho _\alpha (X)$ as $\alpha \rightarrow 1$, where $\rho_\alpha $ is a risk measure equipped with a confidence level parameter $0
    Date: 2017–11
  11. By: Marwa Talbi (ISFA - Institut des Science Financière et d'Assurances - Université de Lyon, IHEC Sousse - IHEC); Rihab Bedoui (IHEC Sousse - IHEC); Lotfi Belkacem (IHEC Sousse - IHEC); Christian De Peretti (ISFA - Institut des Science Financière et d'Assurances - Université de Lyon)
    Abstract: This paper investigates the role of precious metals (Gold, Silver and Platinum) as hedge and/or safe haven assets against the G-7 stock markets that represents the most developed economies, by characterizing the multivariate dependence structure using vine copulas, mainly the C-vine and the D-vine, to capture more flexibly the dependencies between the three precious metals and each stock market index. Therefore, by the information about the dependence on average and the dependence in extreme market conditions provided by the vine copulas, we find that all precious metals under study serve as hedge and safe haven assets in almost all countries with different degrees. These results are crucial for both investors and risk managers to understand portfolio diversification and risk reduction by including these precious metals in their investment portfolios.
    Keywords: Precious metals, G-7 Stock markets, vine copulas, hedge, safe haven, diversification
    Date: 2017–12–14
  12. By: Jorgen-Vitting Andersen (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Roy Cerqueti (University of Macerata); Giulia Rotundo (Sapienza University [Rome])
    Abstract: This paper proposes a stochastic model for describing rational expectations. The context is systemic risk, with interconnected components of a unified system. The evolution dynamics leading to the failure of the system is explored either under a theoretical point of view as well as through an extensive scenario analysis.
    Keywords: Rational expectation,stochastic system,systemic risk,evolutionary economics
    Date: 2017–12
  13. By: Dertwinkel-Kalt, Markus; Wenzel, Tobias
    Abstract: This paper develops a theory of focusing and framing in an intertemporal context with risky choices. We provide a selection criterion between existing theories of fo- cusing by allowing a decision maker to choose her frame such that her attention is either drawn to salient events associated with an option or to the expected utilities an option yields in different time periods. Our key assumption is that a decision maker can choose her frame in a self-serving manner. We predict that the selected frame induces overoptimistic actions in the sense that subjects underrate downside risk but overrate upside risk and accordingly reveal overoptimistic choices. Hence, our theory can explain phenomena such as excessive harmful consumption (smoking, unhealthy diet) and risky investments (entrepreneurship, lotteries, gambling) in one coherent framework. Notably, overoptimistic actions are not universal, but have plausible limits. We characterize under which situations overoptimistic actions are most likely to occur and under which circumstances choices should be rational or even pessimistic.
    Keywords: Focusing,Salience,Framing,Overoptimism
    JEL: D03 D11 D90
    Date: 2017
  14. By: Zura Kakushadze; Willie Yu
    Abstract: We discuss - in what is intended to be a pedagogical fashion - generalized "mean-to-risk" ratios for portfolio optimization. The Sharpe ratio is only one example of such generalized "mean-to-risk" ratios. Another example is what we term the Fano ratio (which, unlike the Sharpe ratio, is independent of the time horizon). Thus, for long-only portfolios optimizing the Fano ratio generally results in a more diversified and less skewed portfolio (compared with optimizing the Sharpe ratio). We give an explicit algorithm for such optimization. We also discuss (Fano-ratio-inspired) long-short strategies that outperform those based on optimizing the Sharpe ratio in our backtests.
    Date: 2017–11
  15. By: Fan, Minyou; Li, Youwei; Liu, Jiadong
    Abstract: We compare the performance of two volatility scaling methods in momentum strategies: (i) the constant volatility scaling approach of Barroso and Santa-Clara (2015), and (ii) the dynamic volatility scaling method of Daniel and Moskowitz (2016). We perform momentum strategies based on these two approaches in a diversified portfolio consisting of 55 global liquid futures contracts, and further compare these results to the time series momentum and buy-and-hold strategies. We find that the momentum strategy based on the constant volatility scaling method is the most efficient approach with an annual return of 15.3%.
    Keywords: Cross-sectional momentum; Time series momentum; Momentum crashes; Volatility scaling
    JEL: G02 G12
    Date: 2017–12–20
  16. By: Maissa Tamraz; Yaming Yang
    Abstract: This contribution is concerned with price optimisation of the new business for a non-life product. Due to high competition in the insurance market, non-life insurers are interested in increasing their conversion rates on new business based on some profit level. In this respect, we consider the competition in the market to model the probability of accepting an offer for a specific customer. We study two optimisation problems relevant for the insurer and present some algorithmic solutions for both continuous and discrete case. Finally, we provide some applications to a motor insurance dataset.
    Date: 2017–11
  17. By: Jiro Akahori; Flavia Barsotti; Yuri Imamura
    Abstract: This paper is a continuation of Akahori-Barsotti-Imamura (2017) and where the authors i) showed that a payment at a random time, which we call timing risk, is decomposed into an integral of static positions of knock-in type barrier options, ii) proposed an iteration of static hedge of a timing risk by regarding the hedging error by a static hedge strategy of Bowie-Carr type with respect to a barrier option as a timing risk, and iii) showed that the error converges to zero by infinitely many times of iteration under a condition on the integrability of a relevant function. Even though many diffusion models including generic 1-dimensional ones satisfy the required condition, a construction of the iterated static hedge that is applicable to any uniformly elliptic diffusions is postponed to the present paper because of its mathematical difficulty. We solve the problem in this paper by relying on the symmetrization, a technique first introduced in Imamura-Ishigaki-Okumura (2014) and generalized in Akahori-Imamura (2014), and also work on parametrix, a classical technique from perturbation theory to construct a fundamental solution of a partial differential equation. Due to a lack of continuity in the diffusion coefficient, however, a careful study of the integrability of the relevant functions is required. The long lines of proof itself could be a contribution to the parametrix analysis.
    Date: 2018–01
  18. By: Hale, Galina (Federal Reserve Bank of San Francisco); Lopez, Jose A. (Federal Reserve Bank of San Francisco)
    Abstract: The need to monitor aggregate financial stability was made clear during the global financial crisis of 2008-2009, and, of course, the need to monitor individual financial firms from a microprudential standpoint remains. In this paper, we propose a procedure based on mixed-frequency models and network analysis to help address both of these policy concerns. We decompose firm-specific stock returns into two components: one that is explained by observed covariates (or fitted values), the other unexplained (or residuals). We construct networks based on the co-movement of these components. Analysis of these networks allows us to identify time periods of increased risk concentration in the banking sector and determine which firms pose high systemic risk. Our results illustrate the efficacy of such modeling techniques for monitoring and potentially enhancing national financial stability.
    JEL: C32 G21 G28
    Date: 2017–09–15
  19. By: Mathias S. Kruttli; Phillip J. Monin; Sumudu W. Watugala
    Abstract: We show that when only a few investors own a substantial portion of a hedge fund's net asset value, flow volatility increases because investors' exogenous, idiosyncratic liquidity shocks are not diversified away. Using confidential regulatory filings, we confirm that high investor concentration hedge funds experience more volatile flows. These hedge funds hold more cash and liquid assets, which help absorb large, unexpected outflows. Such funds have to pay a liquidity premium and generate lower risk-adjusted returns. Investor concentration does not affect flow-performance sensitivity. These results are robust to including lock-up and redemption periods, strategy, manager ownership, and other controls.
    Keywords: Investor concentration ; Hedge funds ; Flows ; Portfolio liquidity ; Precautionary cash
    JEL: G11 G20 G23
    Date: 2017–12–15
  20. By: Harashima, Taiji
    Abstract: In economics, risk lovers have been generally ignored, most likely because it has generally been thought that they cannot survive economically. In this paper, I examine the possibility that risk lovers can exist continuously in the framework of an economic growth model. A bubble-like phenomenon (a so-called “bubble economy”) can be generated if risk lovers undertake a very risky financial “bluff”—for example, if they purposely raise some important asset prices. I conclude that because risk-loving and risk-averse households can coexist at a state of sustainable heterogeneity, risk lovers can exist continuously in an economy. Therefore, it is likely that a bluff will be undertaken by risk lovers and a bubble-like phenomenon can be generated.
    Keywords: Risk lover; Bluff; Bubble; Sustainable heterogeneity; Risk averse
    JEL: D81 E32 E44 G11
    Date: 2018–01–05
  21. By: Pástor, Luboš; Stambaugh, Robert F.; Taylor, Lucian
    Abstract: We derive equilibrium relations among active mutual funds' key characteristics: fund size, expense ratio, turnover, and portfolio liquidity. As our model predicts, funds with smaller size, higher expense ratios, and lower turnover hold less liquid portfolios. A portfolio's liquidity, a concept introduced here, depends not only on the liquidity of the portfolio's holdings but also on the portfolio's diversification. We derive simple, theoretically motivated measures of portfolio liquidity and diversification. Both measures have trended up over time. We also find larger funds are cheaper, funds trading less are larger and cheaper, and excessively large funds underperform, as our model predicts.
    Keywords: Diversification; Mutual funds; portfolio liquidity
    JEL: G11 G23
    Date: 2017–12
  22. By: Piyabha Kongsamut; Christian Mumssen; Anne-Charlotte Paret; Thierry Tressel
    Abstract: How can information on financial conditions be used to better understand macroeconomic developments and improve macroeconomic projections? We investigate this question for France by constructing country-specific financial conditions indices (FCIs) that are tailored to movements in GDP, investment, private consumption and exports respectively. We rely on a VAR approach to estimate the weights of the financial components of each FCI, including equity market returns (which turn out having a relatively strong weight across all FCIs), private sector risk premiums, long-term interest rates, and banks’ credit standards. We find that the tailored FCIs are useful as leading indicators of GDP, investment, and exports, and as a contemporaneous indicator of private consumption. Credit volumes turn out to be lagging indicators of growth. The indices inform us on macro-financial linkages in France and are used to improve the accuracy of quarterly forecasting models and high-frequency “nowcast” models. We show that FCI-augmented models could have significantly improved forecasts during and after the global financial crisis.
    Date: 2017–12–01
  23. By: Tan, Zekuang
    Abstract: This paper will compute the value of the RBC financial derivative-RBC LiONS™ S&P 500 Buffered Protection Securities (USD), Series 4 by utilizing the Black-Scholes Option Pricing Model. In order conduct a thorough analysis of the securities, the paper will compare the model value with the actual price at which the security was issued and the price at which it was traded. This model will help establish a recommended strategy for the issuing company to hedge the liability incurred by the security issued, and provide a possible hedging strategy for the investors.
    Keywords: Black-Scholes Model, Delta Hedging, Geometric Brownian Motion, risk-less arbitrage
    JEL: C51 G11 G12
    Date: 2017–12–16
  24. By: Kirschenmann, Karolin; Korte, Josef; Steffen, Sascha
    Abstract: European banks are exposed to a substantial amount of risky sovereign debt. The "missing bank capital" resulting from the zero-risk weight exemption for European banks for European sovereign debt amplifies the co-movement between sovereign CDS spreads and facilitates cross-border financial-crisis spillovers. Risks spill over from risky periphery sovereigns to safer core countries, but not in the opposite direction nor for exposures to countries not exempted from risk-weighting. We consider the trade-off of benefits of sovereign debt (for banks and sovereigns) and spillover risk when applying risk-weights. More bank capital as well as positive risk-weighting for sovereign exposures mitigates spillovers.
    Keywords: sovereign debt,sovereign risk,bank risk,CDS,contagion,zero risk weight,Basel III,CRD,EBA capital exercise
    JEL: G01 G21 G28 G14 G15 F23
    Date: 2017
  25. By: Vadim Kaushansky; Alexander Lipton; Christoph Reisinger
    Abstract: We derive a semi-analytic formula for the transition probability of three-dimensional Brownian motion in the positive octant with absorption at the boundaries. Separation of variables in spherical coordinates leads to an eigenvalue problem for the resulting boundary value problem in the two angular components. The main theoretical result is a solution to the original problem expressed as an expansion into special functions and an eigenvalue which has to be chosen to allow a matching of the boundary condition. We discuss and test several computational methods to solve a finite-dimensional approximation to this nonlinear eigenvalue problem. Finally, we apply our results to the computation of default probabilities and credit valuation adjustments in a structural credit model with mutual liabilities.
    Date: 2017–12

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