nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒03‒11
seventeen papers chosen by
Stan Miles
Thompson Rivers University

  1. The Risk Exposures of Safe Havens to Global and Regional Stock Market Shocks: A Novel Approach By Mehmet Balcilar; Riza Demirer; Rangan Gupta; Mark E. Wohar
  2. Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index By Escribano Sáez, Álvaro; Blazsek, Szabolcs Istvan; Ayala, Astrid
  3. Lapse tables for lapse risk management in insurance: a competing risk approach By Xavier Milhaud; Christophe Dutang
  4. Republic of Armenia; Detailed Assessment of Observance of the Basel Core Principles for Effective Banking Supervision By International Monetary Fund
  5. Systemic Risk and Centrality Revisited: The Role of Interactions By Asgharian, Hossein; Krygier, Dominika; Vilhelmsson, Anders
  6. Australia; Financial Sector Assessment Program-Technical Note-Stress Testing the Banking Sector and Systemic Risk Analysis By International Monetary Fund
  7. Should Portfolio Model Inputs Be Estimated Using One or Two Economic Regimes? By Emmanouil Platanakis; Athanasios Sakkas; Charles Sutcliffe
  8. An innovative feature selection method for support vector machines and its test on the estimation of the credit risk of default By Sariev, Eduard; Germano, Guido
  9. Non-Parametric Robust Model Risk Measurement with Path-Dependent Loss Functions By Yu Feng
  10. Gaussian Process Regression for Pricing Variable Annuities with Stochastic Volatility and Interest Rate By Ludovic Gouden\`ege; Andrea Molent; Antonino Zanette
  11. Gold-Oil Dependence Dynamics and the Role of Geopolitical Risks: Evidence from a Markov-Switching Time-Varying Copula Model By Aviral Kumar Tiwari; Goodness C. Aye; Rangan Gupta; Konstantinos Gkillas
  12. Asymptotics for volatility derivatives in multi-factor rough volatility models By Chloe Lacombe; Aitor Muguruza; Henry Stone
  13. Exact Solution for the Portfolio Diversification Problem Based on Maximizing the Risk Adjusted Return By Abdulnasser Hatemi-J; Mohamed Ali Hajji; Youssef El-Khatib
  14. The Impact of ESG on Stocks’ Downside Risk and Risk Adjusted Return By Lööf, Hans; Stephan, Andreas
  15. A critique of momentum anomalies By de Oliveira Souza, Thiago
  16. Measuring Multivariate Risk Preferences in the Health Domain By Arthur Attema; Olivier L’haridon; Gijs Van de Kuilen
  17. At Your Service! Liquidity Provision and Risk Management in 19th Century France By Avaro, Maylis; Bignon, Vincent

  1. By: Mehmet Balcilar (Department of Economics, Eastern Mediterranean University, Famagusta, via Mersin 10, Northern Cyprus, Turkey; Department of Economics, University of Pretoria, Pretoria, 0002, South Africa; Montpellier Business School, Montpellier, France.); Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026- 1102, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Mark E. Wohar (College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE 68182, USA and School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)
    Abstract: This paper examines the fundamental linkages between stock markets and safe haven assets by developing a two-factor, regime-based volatility spillover model with global and regional stock market shocks as risk factors. The risk exposures of safe havens with respect to global and regional shocks are found to display significant time variation and regime-specific features, with the exception of VIX for which consistent negative risk exposures are observed with respect to both global and regional shocks. While traditional safe havens like precious metals exhibit positive risk exposures to both regional and global shocks during high volatility periods, Swiss Francs, Japanese Yen and U.S. Treasuries are found to display either insignificant or negative risk exposures during market stress periods to equity market shocks, implying these assets would serve as more effective hedges or safe havens for equity investors. Our findings highlight the importance of dynamic models in assessing the linkages between safe haven assets and stock returns as static models would introduce large biases in diversification measures and optimal hedge ratios.
    Keywords: Safe haven assets, Multivariate regime-switching, Equity market shocks
    JEL: C32 G11 G15
    Date: 2019–02
  2. By: Escribano Sáez, Álvaro; Blazsek, Szabolcs Istvan; Ayala, Astrid
    Abstract: We introduce new dynamic conditional score (DCS) volatility models with dynamic scale and shape parameters for the effective measurement of volatility. In the new models, we use the EGB2 (exponential generalized beta of the second kind), NIG (normal-inverse Gaussian) and Skew-Gen-t (skewed generalized-t) probability distributions. Those distributions involve several shape parameters that control the dynamic skewness, tail shape and peakedness of financial returns. We use daily return data from the Standard & Poor's 500 (S&P 500) index for the period of January 4, 1950 to December 30, 2017. We estimate all models by using the maximum likelihood (ML) method, and we present the conditions of consistency and asymptotic normality of the ML estimates. We study those conditions for the S&P 500 and we also perform diagnostic tests for the residuals. The statistical performances of several DCS specifications with dynamic shape are superior to the statistical performance of the DCS specification with constant shape. Outliers in the shape parameters are associated with important announcements that affected the United States (US) stock market. Our results motivate the application of the new DCS models to volatility measurement, pricing financial derivatives, or estimation of the value-at-risk (VaR) and expected shortfall (ES) metrics.
    Keywords: score-driven shape parameters; Dynamic conditional score (DCS) models
    JEL: C58 C52 C22
    Date: 2019–01–28
  3. By: Xavier Milhaud (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon); Christophe Dutang (LMM - Laboratoire Manceau de Mathématiques - UM - Le Mans Université)
    Abstract: This paper deals with the crucial problem of modeling policyholders' behaviours in life insurance. We focus here on the surrender behaviours and model the contract lifetime through the use of survival regression models. Standard models fail at giving acceptable forecasts for the timing of surrenders because of too much heterogeneity, whereas the competing risk framework provides interesting insights and more accurate predictions. Numerical results follow from using Fine & Gray model ([13]) on an insurance portfolio embedding Whole Life contracts. Through backtests, this framework reveals to be quite efficient and recovers the empirical lapse rate trajectory by aggregating individual predicted lifetimes. These results could be particularly useful to design future insurance product. Moreover, this setting allows to calibrate experimental lapse tables, simplifying the lapse risk management for operational teams.
    Date: 2018–03–09
  4. By: International Monetary Fund
    Abstract: The Central Bank of Armenia (CBA) has made significant progress in its approach to banking supervision with adoption of the RBS framework and addressing gaps in the regulatory framework identified in the 2012 Basel Core Principles (BCP) assessment. The recently adopted RBS framework provides a forward-looking assessment of the risk profile of individual banks and groups and assigns supervisory resources more proportionate to the risk in the system, and to the risks within individual banks. The use of risk teams to take ownership of individual risk across the banking system also contributes to identification and monitoring of risks emanating from banks and the banking system as a whole. In addition, improvements have been made in the regulatory regime regarding requirements for risk management, stress testing, corporate governance, country risk and consolidated supervision.
    Keywords: Armenia;Middle East;
    Date: 2019–02–05
  5. By: Asgharian, Hossein (Department of Economics, Lund University); Krygier, Dominika (Department of Economics, Lund University); Vilhelmsson, Anders (Department of Economics, Lund University)
    Abstract: We suggest that banks contribute extensively to systemic risk only if they are both "risky" and centrally placed in the financial network. To calculate systemic risk we apply the CoVaR measure of Adrian and Brunnermeier (2016) and measure centrality using detailed US loan syndication data. In agreement with our conjecture our main finding is that centrality is an important determinant of systemic risk but primarily not by its direct effect. Rather, its main influence is to make other firm specific risk measures more important for highly connected banks. A bank's contribution to systemic risk from a fixed level of Value-at-Risk is about four times higher for a bank with two standard deviations above average centrality compared to a bank with average network centrality. Neglecting this indirect moderation effect of centrality severely underestimates the importance of centrality for "risky" banks and overestimates the effect for "safer" banks.
    Keywords: systemic risk; network centrality; loan syndication; CoVaR
    JEL: G18 G21
    Date: 2019–03–05
  6. By: International Monetary Fund
    Abstract: This Technical Note on Stress Testing the Banking Sector and Systemic Risk Analysis for Australia was prepared by a staff team of the International Monetary Fund as background documentation for the periodic consultation with the member country. It is based on the information available at the time it was completed on September 14, 2018.
    Date: 2019–02–21
  7. By: Emmanouil Platanakis (School of Management, University of Bath); Athanasios Sakkas (Southampton Business School, University of Southampton); Charles Sutcliffe (ICMA Centre, Henley Business School, University of Reading)
    Abstract: Estimation errors in the inputs are the main problem when applying portfolio analysis. Markov regime switching models are used to reduce these errors, but they do not always improve out-of-sample portfolio performance. We investigate the levels of transaction costs and risk aversion below which the use of two regimes is superior to one regime for an investor with a CRRA utility function, allowing for skewed and kurtic returns. Our results suggest that, due to differences in risk and transactions costs, most retail investors should use one regime models, while investment banks should use two regime models.
    Keywords: finance, portfolio theory, regime shifting, transaction costs, risk aversion, constant relative risk aversion
    JEL: G11
    Date: 2017–09
  8. By: Sariev, Eduard; Germano, Guido
    Abstract: Support vector machines (SVM) have been extensively used for classification problems in many areas such as gene, text and image recognition. However, SVM have been rarely used to estimate the probability of default (PD) in credit risk. In this paper, we advocate the application of SVM, rather than the popular logistic regression (LR) method, for the estimation of both corporate and retail PD. Our results indicate that most of the time SVM outperforms LR in terms of classification accuracy for the corporate and retail segments. We propose a new wrapper feature selection based on maximizing the distance of the support vectors from the separating hyperplane and apply it to identify the main PD drivers. We used three datasets to test the PD estimation, containing (1) retail obligors from Germany, (2) corporate obligors from Eastern Europe, and (3) corporate obligors from Poland. Total assets, total liabilities, and sales are identified as frequent default drivers for the corporate datasets, whereas current account status and duration of the current account are frequent default drivers for the retail dataset.
    Keywords: default risk; logistic regression; support vector machines; ES/ K002309/1
    JEL: C10 C13
    Date: 2018–11–28
  9. By: Yu Feng
    Abstract: Understanding and measuring model risk is important to financial practitioners. However, there lacks a non-parametric approach to model risk quantification in a dynamic setting and with path-dependent losses. We propose a complete theory generalizing the relative-entropic approach by Glasserman and Xu to the dynamic case under any $f$-divergence. It provides an unified treatment for measuring both the worst-case risk and the $f$-divergence budget that originate from the model uncertainty of an underlying state process.
    Date: 2019–03
  10. By: Ludovic Gouden\`ege; Andrea Molent; Antonino Zanette
    Abstract: In this paper we develop an efficient approach based on a Machine Learning technique which allows one to quickly evaluate insurance products considering stochastic volatility and interest rate. Specifically, following De Spiegeleer et al., we apply Gaussian Process Regression to compute the price and the Greeks of a GMWB Variable Annuity. Starting from observed prices previously computed by means of a Hybrid Tree PDE approach for some known combinations of model parameters, it is possible to approximate the whole target function on a bounded domain. The regression algorithm consists of two main steps: algorithm training and evaluation. In particular, the first step is the most time demanding, but it needs to be performed only once, while the prediction step is very fast and requires to be performed only when evaluating the function. The developed method, as well as for the calculation of prices and Greeks, can also be employed to compute the no-arbitrage fee, which is a common practice in the Variable Annuities sector. We consider three increasing complexity models, namely the Black-Scholes, the Heston and the Heston Hull-White models, which extend the sources of randomness up to consider stochastic volatility and stochastic interest rate together. Numerical experiments show that the accuracy of the estimated values is high, while the computational cost is much lower than the one required by a direct calculation with standard approaches. Finally, we stress out that the analysis is carried out for a GMWB annuity but it could be generalized to other insurance products. Machine Learning seems to be a very promising and interesting tool for insurance risk management.
    Date: 2019–03
  11. By: Aviral Kumar Tiwari (Montpellier Business School, 2300, Avenue des Moulins, 34185, Montpellier Cedex 4 0002, France); Goodness C. Aye (Department of Economics, University of Pretoria, Pretoria, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Konstantinos Gkillas (Department of Business Administration , University of Patras, University Campus, Rio, P.O. Box 1391, 26500 Patras, Greece)
    Abstract: This paper examined the dependence structure and dynamics between gold and oil prices. Specifically, we examined the hedge and safe haven ability of gold for oil prices using the time-varying Markov switching copula models and daily gold prices and West Texas Intermediate Institute (WTI) crude oil spot prices from 2 January 1985 to 30 November 2017. The heterogeneity of market agents is captured by decomposing the raw original series into different multi-resolution analysis (MRA) investment horizons (D1-S9). Further, we examined the effect of geopolitical risks on the dynamic dependence between gold and oil. We provide evidence of time-varying Markov tail dependence structure and dynamics between gold and oil. While our results showed that gold is a good hedge for oil returns and for short- and medium-term investors, it cannot protect long-term investors against losses arising from increasing oil prices. We also provide evidence in support of the safe haven ability of gold for oil. Further, we show that the inclusion of geopolitical risks in a pure gold and oil asset portfolio provides diversification benefits since the former has mostly negative effect on the dependence structure between gold and oil.
    Keywords: Time-Varying Dependence, Gold and Oil Markets, Copula Models, Geopolitical Risks.
    JEL: C22 Q02
    Date: 2019–03
  12. By: Chloe Lacombe; Aitor Muguruza; Henry Stone
    Abstract: We present small-time implied volatility asymptotics for Realised Variance (RV) and VIX options for a number of (rough) stochastic volatility models via large deviations principle. We provide numerical results along with efficient and robust numerical recipes to compute the rate function; the backbone of our theoretical framework. Based on our results, we further develop approximation schemes for the density of RV, which in turn allows to express the volatility swap in close-form. Lastly, we investigate different constructions of multi-factor models and how each of them affects the convexity of the implied volatility smile. Interestingly, we identify the class of models that generate non-linear smiles around-the-money.
    Date: 2019–03
  13. By: Abdulnasser Hatemi-J; Mohamed Ali Hajji; Youssef El-Khatib
    Abstract: The potential benefits of portfolio diversification have been known to investors for a long time. Markowitz (1952) suggested the seminal approach for optimizing the portfolio problem based on finding the weights as budget shares that minimize the variance of the underlying portfolio. Hatemi-J and El-Khatib (2015) suggested finding the weights that will result in maximizing the risk adjusted return of the portfolio. This approach seems to be preferred by the rational investors since it combines risk and return when the optimal budget shares are sought for. The current paper provides a general solution for this risk adjusted return problem that can be utilized for any potential number of assets that are included in the portfolio.
    Date: 2019–03
  14. By: Lööf, Hans (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology); Stephan, Andreas (Jönköping International Business School, Jönköping University & Centre of Excellence for Science and Innovation Studies (CESIS))
    Abstract: Investments considering corporate social responsibility continue to expand. Are companies pursuing a CSR agenda benefiting shareholders by reducing their financial downside risk? This paper investigates the relationship between a firm’s environmental, social and corporate governance (ESG) scores and its downside risk on the stock market. We study this link using a panel of 887 stocks listed in five European countries over the period 2005-2017. Our empirical results show that higher ESG scores are associated with reduced downside risk of stock returns. Based on the Fama-French three factor model, we found no systematic relationship between ESG and the level of risk-adjusted return.
    Keywords: ESG; Value at Risk; Risk-adjusted return; stock market; panel data
    JEL: D22 G11 G14 G32
    Date: 2019–03–06
  15. By: de Oliveira Souza, Thiago (Department of Business and Economics)
    Abstract: This paper offers theoretical, empirical, and simulated evidence that momentum regularities in asset prices are not anomalies. Within a general, frictionless, rational expectations, risk-based asset pricing framework, riskier assets tend to be in the loser portfolios after (large) increases in the price of risk. Hence, the risk of momentum portfolios usually decreases with the prevailing price of risk, and their risk premiums are approximately negative quadratic functions of the price of risk (and the market premium) theoretically truncated at zero. The best linear (CAPM) function describing this relation unconditionally has exactly the negative slope and positive intercept documented empirically.
    Keywords: Momentum; risk; puzzle; ranking; conditional
    JEL: G11 G12 G14
    Date: 2019–02–20
  16. By: Arthur Attema (Erasmus School of Economics - Erasmus University Rotterdam); Olivier L’haridon (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - CNRS - Centre National de la Recherche Scientifique); Gijs Van de Kuilen (TiSEM - Tilburg School of Economics and Management - Tilburg University [Netherlands])
    Abstract: We investigate univariate and multivariate risk preferences for health (longevity) and wealth. We measure attitudes toward correlation and attitudes toward higher order dependence structures such as cross-prudence and cross-temperance, making use of the risk apportionment technique proposed by Eeckhoudt et al. (2007). For multivariate gains, we find correlation aversion and cross-prudence in longevity and wealth. For losses, we observe correlation seeking and cross-imprudence. We do not find clear evidence for cross-temperance. Our results indicate that longevity and wealth are considered to be substitutes for gains, but not for losses. Second, univariate (higher order) risk preferences are comparable for longevity and wealth, although somewhat closer to linearity for wealth. Third, we find evidence that attitudes toward dependence structures in the health domain are sign-dependent.
    Keywords: multivariate risk attitudes,health,prudence,temperance
    Date: 2019–03
  17. By: Avaro, Maylis; Bignon, Vincent
    Abstract: This paper uses a historical study to show a solution to the trade-off faced by central banks between providing liquidity to a broad group of financial intermediaries and the risk that this easy access may fuel moral hazard. In late 19th century the Bank of France operated a very wide discount window and used a variety of risk management techniques to effectively subdue risk-taking behaviors and to protect its balance sheet from taking any loss. This allowed agents to monetize a very diverse set of capital while limiting the risk of bail-out. We show that this effectively helped the central bank to stabilize the economy from the consequences of negative income shocks.
    Keywords: central bank; discount window; lender of last resort; Retail and shadow banks
    JEL: E51 G23 N13
    Date: 2019–02

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