nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒08‒06
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Back to the Future: Backtesting Systemic Risk Measures during Historical Bank Runs and the Great Depression By Brownlees, Christian; Chabot, Ben; Ghysels, Eric; Kurz, Christopher
  2. The "Size Premium" in Equity Markets: Where is the Risk? By Stefano Ciliberti; Emmanuel S\'eri\'e; Guillaume Simon; Yves Lemp\'eri\`ere; Jean-Philippe Bouchaud
  3. Extreme Risk Value and Dependence Structure of the China Securities Index 300 By Chong, Terence Tai Leung; Ding, Yue; Pang, Tianxiao
  4. On Biased Correlation Estimation By Thomas Sch\"urmann; Ingo Hoffmann
  5. Banks' Liquidity Management and Systemic Risk By E. Panetti; LG Deidda
  6. A ternary-state early warning system for the European Union By Savas Papadopoulos; Pantelis Stavroulias; Thomas Sager; Etti Baranoff
  7. Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries By Boldanov, Rustam; Degiannakis, Stavros; Filis, George
  8. A risk measure that optimally balances capital determination errors By Marcelo Brutti Righi
  9. Sparse Structural Approach for Rating Transitions By Volodymyr Perederiy
  10. Theoretical and Empirical Differences Between Diagonal and Full Bekk for Risk Management By David Allen; Michael McAleer
  11. Political Distribution Risk and Aggregate Fluctuations By Drautzburg, Thorsten; Fernández-Villaverde, Jesús; Guerron-Quintana, Pablo A.
  12. A top-down stress testing framework for the Dutch banking sector By Tijmen Daniëls; Patty Duijm; Franka Liedorp; Dimitris Mokas
  13. Downside Risk in the Chinese Stock Market - Has it Fundamentally Changed? By Ghysels, Eric; Liu, Hanwei

  1. By: Brownlees, Christian; Chabot, Ben; Ghysels, Eric; Kurz, Christopher
    Abstract: We evaluate the performance of two popular systemic risk measures, CoVaR and SRISK, during eight financial panics in the era before FDIC insurance. Bank stock price and balance sheet data were not readily available for this time period. We rectify this shortcoming by constructing a novel dataset for the New York banking system before 1933. Our evaluation exercise focuses on assessing whether systemic risk measures were able to detect systemically important financial institutions and to provide early warning signals of aggregate financial sector turbulence. The predictive ability of CoVaR and SRISK is measured controlling for a set of commonly employed market risk measures and bank ratios. We find that CoVaR and SRISK help identifying systemic institutions in periods of distress beyond what is explained by standard risk measures up to six months prior to the panic events. Increases in aggregate CoVaR and SRISK precede worsening conditions in the financial system; however, the evidence of predictability is weaker.
    Keywords: Financial crises; Risk Measures; systemic risk
    JEL: G01 G21 G28 N21
    Date: 2017–07
  2. By: Stefano Ciliberti; Emmanuel S\'eri\'e; Guillaume Simon; Yves Lemp\'eri\`ere; Jean-Philippe Bouchaud
    Abstract: We find that when measured in terms of dollar-turnover, and once $\beta$-neutralised and Low-Vol neutralised, the Size Effect is alive and well. With a long term t-stat of $5.1$, the "Cold-Minus-Hot" (CMH) anomaly is certainly not less significant than other well-known factors such as Value or Quality. As compared to market-cap based SMB, CMH portfolios are much less anti-correlated to the Low-Vol anomaly. In contrast with standard risk premia, size-based portfolios are found to be virtually unskewed. In fact, the extreme risk of these portfolios is dominated by the large cap leg; small caps actually have a positive (rather than negative) skewness. The only argument that favours a risk premium interpretation at the individual stock level is that the extreme drawdowns are more frequent for small cap/turnover stocks, even after accounting for volatility. This idiosyncratic risk is however clearly diversifiable.
    Date: 2017–08
  3. By: Chong, Terence Tai Leung; Ding, Yue; Pang, Tianxiao
    Abstract: A time-varying copulas–conditional value at risk (CVaR) model is estimated to analyze the extreme risk value and dependence structure of the China Securities Index 300 (CSI 300) and index futures portfolios. The goodness-of-fit test as well as the in-sample and out-of-sample tests show that time-varying copulas outperform constant copulas. Specifically, the Student’s t, normal, Plackett, and the rotated Gumbel copulas outperform the rotated Clayton copulas.
    Keywords: CVaR model; Time-varying copulas.
    JEL: C2 C22 G1
    Date: 2017–03–06
  4. By: Thomas Sch\"urmann; Ingo Hoffmann
    Abstract: In general, underestimation of risk is something which should be avoided as far as possible. Especially in financial asset management, equity risk is typically characterized by the measure of portfolio variance, or indirectly by quantities which are derived from it. Since there is a linear dependency of the variance and the empirical correlation between asset classes, one is compelled to control or to avoid the possibility of underestimating correlation coefficients. In the present approach, we formalize common practice and classify these approaches by computing their probability of underestimation. In addition, we introduce a new estimator which is characterized by having the advantage of a constant and controllable probability of underestimation. We prove that the new estimator is statistically consistent.
    Date: 2017–07
  5. By: E. Panetti; LG Deidda
    Abstract: We study a novel mechanism to explain the interaction between banks' liquidity management and the emergence of systemic financial crises, in the form of self-fulfilling runs. To this end, we develop an environment where banks offer insurance to their depositors against both idiosyncratic and aggregate real shocks, by holding a portfolio of liquidity and illiquid productive assets. Moreover, banks' asset portfolios and the probability of a depositors' self-fulfilling run are jointly determined via a "global game". We characterize the sufficient conditions under which there exists a unique threshold recovery rate, associated with the early liquidation of the productive assets, below which the banks first employ liquidity and then liquidate, in order to finance depositors' early withdrawals. Ex ante, the banks hold more liquidity than in a full-information economy, where there are no self-fulfilling runs and risk is only due to idiosyncratic and aggregate real shocks.
    Keywords: systemic risk;global games;excess liquidity;bank runs
    Date: 2017
  6. By: Savas Papadopoulos (Bank of Greece); Pantelis Stavroulias (Democritus University of Thrace); Thomas Sager (University of Texas); Etti Baranoff (Virginia Commonwealth University)
    Abstract: The global financial crisis of 2007-2008 focused the attention of financial authorities on developing methods to forecast and avoid future financial crises of similar magnitude. We contribute to the literature on crisis prediction in several important ways. First, we develop an early warning system (EWS) that provides 7-12 quarters advance warning with high accuracy in out-of-sample testing. Second, the EWS applies region-wide to the leading economies in the European Union. Third, the methodology is transparent – utilizing only publicly available macro-level data and standard statistical classification methodology (multinomial logistic regression, discriminant analysis, and neural networks). Fourth, we employ two relatively novel methodological innovations in EWS modeling: ternary state classification to guarantee a minimum advance warning period, and a fitting and evaluation criterion (the total harmonic mean) that prioritizes avoiding classification errors for the relatively infrequent events of most interest. As a consequence, a policymaker who uses these methods will enjoy a high probability that future crises will be signaled well in advance and that warnings of crisis will not be false alarms.
    Keywords: Banking crisis; financial stability; macroprudential policy; classification methods; goodness-of-fit measures
    JEL: C53 E58 G28
    Date: 2017–04
  7. By: Boldanov, Rustam; Degiannakis, Stavros; Filis, George
    Abstract: This paper investigates the time-varying conditional correlation between oil price and stock market volatility for six major oil-importing and oil-exporting countries. The period of the study runs from January 2000 until December 2014 and a Diag-BEKK model is employed. Our findings report the following regularities. (i) The correlation between the oil and stock market volatilities changes over time fluctuating at both positive and negative values. (ii). Heterogeneous patterns in the time-varying correlations are evident between the oil-importing and oil-exporting countries. (iii) Correlations are responsive to major economic and geopolitical events, such as the early-2000 recession, the 9/11 terrorist attacks and the global financial crisis of 2007-2009. These findings are important for risk management practices, derivative pricing and portfolio rebalancing.
    Keywords: conditional volatility, realized volatility, time-varying correlation, Diag-BEKK, GARCH, oil-importing countries, oil-exporting countries.
    JEL: C32 C51 G15 Q40
    Date: 2017
  8. By: Marcelo Brutti Righi
    Abstract: In this paper, we propose a risk measurement approach that minimizes the expectation of sum between costs from capital determination overestimation and underestimation. We develop results that guarantee the existence of a solution, indicate properties that our risk measure fulfills, and characterize the resulting minimum cost as a deviation measure. We generalize this approach to a robust framework, where the minimization is over a supremum of expectations, based on a convex set of probability measures. We relate this robust approach with the dual representation of coherent risk measures. In a numerical example, we illustrate our approach for simulated and real financial data. Results indicate our approach leads to more parsimonious capital requirement determinations and reduces the mentioned costs.
    Date: 2017–07
  9. By: Volodymyr Perederiy
    Abstract: In banking practice, rating transition matrices have become the standard approach of deriving multi-year probabilities of default (PDs) from one-year PDs, with the latter normally being available from Basel ratings. Rating transition matrices have gained in importance with the newly adopted IFRS 9 accounting standard. Here, the multi-year PDs can be used to calculate the so-called expected credit losses (ECL) over the entire lifetime of relevant credit assets. A typical approach for estimating the rating transition matrices relies on calculating empirical rating migration counts and frequencies from rating history data. However, for small portfolios this approach often leads to zero counts and high count volatility, which makes the estimations unreliable and volatile, and can also produce counter-intuitive prediction patterns. This paper proposes a structural model which overcomes these problems. We retort to a plausible assumption of an autoregressive mean-reverting specification for the underlying ability-to-pay process. With only three parameters, this sparse process can describe well an entire typical rating transition matrix, provided the one-year PDs of the rating classes are specified (e.g. in the rating master scale). The transition probabilities produced by the structural approach are well-behaved. The approach reduces significantly the statistical degrees of freedom of the estimated transition probabilities, which makes the rating transition matrix significantly more reliable for small portfolios. The approach can be applied to data with as few as 50 observed rating transitions. Moreover, the approach can be efficiently applied for data consisting of continuous (undiscretized) PDs. In the IFRS9 context, the approach offers an additional merit of an easy way to account for the macroeconomic adjustments, which are required by the IFRS 9 accounting standard.
    Date: 2017–07
  10. By: David Allen (Department of Mathematics, University of Sydney, Australia); Michael McAleer (Department of Quantitative Finance, National Tsing Hua University, Taiwan; Discipline of Business Analytics, University of Sydney Business School, Australia; Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands)
    Abstract: The purpose of the paper is to explore the relative biases in the estimation of the Full BEKK model as compared with the Diagonal BEKK model, which is used as a theoretical and empirical benchmark. Chang and McAleer [4] show that univariate GARCH is not a special case of multivariate ARCH, specifically, the Full BEKK model, and demonstrate that Full BEKK which, in practice, is estimated almost exclusively, has no underlying stochastic process, regularity conditions, or asymptotic properties. Diagonal BEKK (DBEKK) does not suffer from these limitations, and hence provides a suitable benchmark. We use simulated financial returns series to contrast estimates of the conditional variances and covariances from DBEKK and BEKK. The results of non-parametric tests suggest evidence of considerable bias in the Full BEKK estimates. The results of quantile regression analysis show there is a systematic relationship between the two sets of estimates as we move across the quantiles. Estimates of conditional variances from Full BEKK, relative to those from DBEKK, are lower in the left tail and higher in the right tail.
    Keywords: DBEKK; BEKK; Regularity Conditions; Asymptotic Properties; Non-Parametric; Bias; Quantile regression.
    JEL: C13 C21 C58
    Date: 2017–07–31
  11. By: Drautzburg, Thorsten; Fernández-Villaverde, Jesús; Guerron-Quintana, Pablo A.
    Abstract: We argue that political distribution risk is an important driver of aggregate fluctuations. To that end, we document significant changes in the capital share after large political events, such as political realignments, modifications in collective bargaining rules, or the end of dictatorships, in a sample of developed and emerging economies. These policy changes are associated with significant fluctuations in output and asset prices. Using a Bayesian proxy-VAR estimated with U.S. data, we show how distribution shocks cause movements in output, unemployment, and sectoral asset prices. To quantify the importance of these political shocks for the U.S. as a whole, we extend an otherwise standard neoclassical growth model. We model political shocks as exogenous changes in the bargaining power of workers in a labor market with search and matching. We calibrate the model to the U.S. corporate non-financial business sector and we back up the evolution of the bargaining power of workers over time using a new methodological approach, the partial filter. We show how the estimated shocks agree with the historical narrative evidence. We document that bargaining shocks account for 34% of aggregate fluctuations.
    Keywords: Aggregate fluctuations; bargaining shocks; historical narrative.; partial filter; Political redistribution risk
    JEL: E32 E37 E44 J20
    Date: 2017–07
  12. By: Tijmen Daniëls; Patty Duijm; Franka Liedorp; Dimitris Mokas
    Abstract: Stress tests have become an increasingly important tool for macroprudential policy makers and micro-prudential supervisors. DNB has developed an extensive top-down stress test framework to support its macro- and micro-prudential responsibilities. It is used to quantify financial stability assessments, to challenge calculations that banks provide in supervisory stress tests and to reinforce the link between macro risk assessment and micro-prudential actions. This paper explains DNB's topdown stress test framework with a focus on the characteristics of the Dutch banking sector.
    Date: 2017–07
  13. By: Ghysels, Eric; Liu, Hanwei
    Abstract: The Chinese economy has gained a more significant role on the world stage. As a consequence, a wide range of investors, both domestic and foreign, have paid more attention to the Chinese stock market. One focal point has been the downside risk, in particular in light of the large price movements and the regulatory changes which took place over time. In this paper we study the pattern of downside risks using the 1\% and 5\% conditional quantiles of the equity index returns. One of our ultimate goals is to provide an objective assessment of the regulatory policy changes and government actions in the Chinese market. We discover several break dates linked to major financial crises and trading reforms put forth by the China Securities Regulatory Commission. Furthermore, our findings indicate that breaks in the B shares and the H shares downside risk tend to appear earlier than those corresponding to the A shares returns. Lastly, the revised Qualified Foreign Institutional Investor (QFII) program in 2006 and government share purchasing actions in 2015 have shown to be effective at alleviating downside risks in the Shanghai A shares.
    Date: 2017–07

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