nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒02‒04
twenty-one papers chosen by
Stan Miles
Thompson Rivers University

  1. The Interest Rate Sensitivity of Institutional Real Estate Investments By Michael Heinrich; Thomas Schreck
  2. Effects of Solvency II on Portfolio Efficiency, The Case of Real Estate and Infrastructure Investments By Michael Heinrich; Thomas Schreck
  3. Is gold a hedge against equity risk? Malaysian experience based on NARDL approach By Sabry, Saajid; Masih, Mansur
  4. Macro and Micro Prudential Policies: Sweet and Lowdown in a Credit Network Agent Based Model By Ermanno Catullo; Federico Giri; Mauro Gallegati
  5. Willingness to take risk: The role of risk conception and optimism By Thomas Dohmen; Simone Quercia; Jana Willrodt
  6. Global Evidence on Economic Preferences By Armin Falk; Thomas Dohmen; David Huffman; Uwe Sunde
  7. Financial Portfolios based on Tsallis Relative Entropy as the Risk Measure By Devi, Sandhya
  8. A Coupled Component GARCH Model for Intraday and Overnight Volatility By Linton, O.; Wu, J.
  9. Conditional Risk-Based Portfolio By Olessia CaillÉ; Daria Onori
  10. The Leverage Ratio and Its Impact on Capital Regulation By Lukas Pfeifer; Martin Hodula; Libor Holub; Zdenek Pikhart
  11. Superhedging prices of European and American options in a non-linear incomplete market with default By Grigorova, Miryana; Quenez, Marie-Claire; Sulem, Agnès
  12. Lost in Diversification By Marco Bardoscia; Daniele d'Arienzo; Matteo Marsili; Valerio Volpati
  13. The Insurance is the Lemon: Failing to Index Contracts By Barney Hartman-Glaser; Benjamin M. Hébert
  14. Adapted Wasserstein Distances and Stability in Mathematical Finance By Julio Backhoff-Veraguas; Daniel Bartl; Mathias Beiglb\"ock; Manu Eder
  15. Foreign expansion, competition and bank risk By Faia, Ester; Laffitte, Sebastien; Ottaviano, Gianmarco I. P.
  16. Changing Risk Preferences at Older Ages By James Banks; Elena Bassoli; Irene Mammi
  17. Wrong-way Risk in Credit Valuation Adjustment of Credit Default Swap with Copulas By Tetsuya Adachi; Takumi Sueshige; Toshinao Yoshiba
  18. Dynamics of a Well-Diversified Equity Index By Eckhard Platen; Renata Rendek
  19. Deep Learning Volatility By Blanka Horvath; Aitor Muguruza; Mehdi Tomas
  20. Bootstrap Procedures for Detecting Multiple Persistance4 Shifts in a heteroskedastic Time Series By Mohitosh Kejriwal; Xuewen Yu
  21. Transportation Project Evaluation Methods/Approaches By M. Rouhani, Omid

  1. By: Michael Heinrich; Thomas Schreck
    Abstract: Real estate is known for high risk-adjusted returns and its diversification qualities. However, apart from traditional volatility-based risk measures, institutional investors also have to manage the interest rate risk of their portfolios. In practice, the interest rate sensitivity of the assets must be matched with the interest rate sensitivity of the companies’ liabilities. Regulation standards like Solvency II incentivize life insurance companies to minimize their interest rate risk exposure by requiring large amounts of economic capital to cover remaining interest rate risk. Furthermore, the current low interest environment raises the question of how sensitively real estate assets react to positive interest rate shocks. We estimate the interest rate sensitivity of real estate empirically, using a panel regression model. We find a strong link between the level and the term structure of market interest rates and the valuation of real estate. By dividing our sample into different subsamples, we identify both interest shock sensitive and interest shock robust submarkets. To the best of our knowledge, this is the first study analyzing the influence of interest rate shocks on real estate valuations based on actual portfolio data of a major life insurance company.
    Keywords: Duration; Interest Rate Sensitivity; Life Insurance; Pension funds; Risk Management
    JEL: R3
    Date: 2018–09–01
  2. By: Michael Heinrich; Thomas Schreck
    Abstract: We examine the potential effects of Solvency II on general portfolio efficiency, and specifically on the allocation of alternative assets by European insurers. The paper starts with a brief intro- duction to the Solvency II Directive, focusing on the rules for calculating the Solvency capital requirements (SCR), according to the standard formula. The following empirical analysis en- tails several portfolio optimizations considering six relevant asset classes for the time period from 1993-2013. We derive optimal portfolios with respect to portfolio risk and capital require- ments, and finally combine both optimization problems. Our results suggest that, although the capital charges for real estate and infrastructure assets are not adequately calibrated, a signifi- cant shift of portfolio weights is not expected for the majority of European insurers. However, after Solvency II comes into effect, undercapitalized insurers may often not be capable of hold- ing risk-optimal allocations of alternative assets.
    Keywords: Financial Crisis; Infrastructure; Life Insurance; real estate; Risk Based Regulation
    JEL: R3
    Date: 2017–09–01
  3. By: Sabry, Saajid; Masih, Mansur
    Abstract: The chain of financial crises that had been occurring raised a serious concern among the investors regarding its equity risk. There is a need to rethink about gold as a hedge against its equity risk in the long run. Hence, the question is whether gold is a good hedge against equity risk? We use a recently developed time series technique namely, nonlinear ARDL (NARDL) to test the long term asymmetric relationship between gold price and Kuala Lumpur Composite Index. To the best of our knowledge, this would be the first attempt to use NARDL to look into the long run asymmetric relationship between these variables. Our results tend to suggest that gold price in the Malaysian context is determined by external factors, specifically cultural preferences. Also, it has a negative relationship making gold a good hedge against equity risk. This finding would be important for the investors to consider to have gold in their portfolio to hedge against equity risk in Malaysia.
    Keywords: Malaysia, Emerging markets, Gold, Investments, Stock markets, Gold investment, NARDL
    JEL: C22 C58 G11
    Date: 2018–12–30
  4. By: Ermanno Catullo (Department of Economics and Social Sciences, Universita' Politecnica delle Marche); Federico Giri (Department of Economics and Social Sciences, Universita' Politecnica delle Marche); Mauro Gallegati (Department of Economics and Social Sciences, Universita' Politecnica delle Marche)
    Abstract: The paper presents an agent based model reproducing a stylized credit network that evolves endogenously through the individual choices of rms and banks. We introduce in this framework a anancial stability authority in order to test the e ects of different prudential policy measures designed to improve the resilience of the economic system. Simulations show that a combination of micro and macro prudential policies reduces systemic risk, but at the cost of increasing banks' capital volatility. Moreover, agent based methodology allows us to implement an alternative meso regulatory framework that takes into consideration the connections between firms and banks. This policy targets only the more connected banks, increasing their capital requirement in order to reduce the di usion of local shocks. Our results support the idea that the meso prudential policy is able to reduce systemic risk without a ecting the stability of banks'capital structure.
    Keywords: Micro prudential policy; Macro prudential policy; Credit Network; Meso prudential policy; Agent based model
    JEL: E50 E58 G18 G28 C63
    Date: 2019–01
  5. By: Thomas Dohmen; Simone Quercia; Jana Willrodt
    Abstract: We show that the disposition to focus on favorable or unfavorable outcomes of risky situations affects willingness to take risk as measured by the general risk question. We demonstrate that this disposition, which we call risk conception, is strongly associated with optimism, a stable facet of personality and that it predicts real-life risk taking. The general risk question captures this disposition alongside pure risk preference. This enlightens why the general risk question is a better predictor of behavior under risk across different domains than measures of pure risk preference. Our results also rationalize why risk taking is related to optimism.
    Keywords: risk taking behavior, optimism, preference measures, risk conception
    JEL: D91 C91 D81 D01
    Date: 2018–06
  6. By: Armin Falk; Thomas Dohmen; David Huffman; Uwe Sunde
    Abstract: This paper discusses the recent literature on the relationship between cognitive ability and decision making under risk and uncertainty. After clarifying some important distinctions between concepts and measurement of risk preference and cognitive ability, we take stock of what is known empirically on the connections between cognitive ability and measured risk preferences. We conclude by discussing perspectives for future research.
    JEL: D81 D91 D89
    Date: 2018–03
  7. By: Devi, Sandhya
    Abstract: Tsallis relative entropy, which is the generalization of Kullback-Leibler relative entropy to non-extensive systems, is investigated as a possible risk measure in constructing risk optimal portfolios whose returns beat market returns. The results are compared with those from three other risk measures: 1) the commonly used ‘beta’ of the Capital Asset Pricing Model (CAPM), 2) Kullback-Leibler relative entropy, and 3) the relative standard deviation. Portfolios are constructed by binning the securities according to their risk values. The mean risk value and the mean return in excess of market returns for each bin is calculated to get the risk-return patterns of the portfolios. The investigations have been carried out for both long (~18 years) and shorter (~9 years) terms that include the dot-com bubble and the 2008 crash periods. In all cases, a linear fit can be obtained for the risk and excess return profiles, both for long and shorter periods. For longer periods, the linear fits have a positive slope, with Tsallis relative entropy giving the best goodness of fit. For shorter periods, the risk-return profiles from Tsallis relative entropy show a more consistent behavior in terms of goodness of fit than the other three risk measures.
    Keywords: Non-extensive statistics, Tsallis relative entropy, Kullback-Leibler relative entropy, q-Gaussian distribution, Capital Asset Pricing Model, Beta, Risk optimal portfolio, Econophysics
    JEL: C10
    Date: 2018–01–18
  8. By: Linton, O.; Wu, J.
    Abstract: We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility that allows the two return series to have different properties. We adopt a dynamic conditional score model with t-distributed innovations that captures the very heavy tails of overnight returns. We propose a several-step estimation procedure that captures the nonparametric slowly moving components by kernel estimation and the dynamic parameters by estimated maximum likelihood. We establish the consistency, asymptotic normality, and semiparametric efficiency of our semiparametric estimation procedures. We extend the modelling to the multivariate case where we allow time varying correlation between stocks. We apply our model to the study of Dow Jones industrial average component stocks, CRSP size-based portfolios, and size-based portfolios in four large international markets over the period 1993-2017. We show that the ratio of overnight to intraday volatility has actually increased in importance for Dow Jones stocks during the last two decades. This ratio has also increased for large stocks in the CRSP database, but decreased for small stocks in CRSP. Notably, the slope increases monotonically from the smallest-cap decile to the largest-cap decile. This pattern also exists in other international markets. The multivariate model shows that overnight and intraday correlations have both increased, but overnight correlations have increased more substantially during recent crises than intraday correlations.
    Keywords: DCS, GAS, GARCH, size-based portfolios, Testing
    JEL: C12 C13
    Date: 2018–09–14
  9. By: Olessia CaillÉ (LEO - Laboratoire d'économie d'Orleans - UO - Université d'Orléans - Université de Tours - CNRS - Centre National de la Recherche Scientifique); Daria Onori (LEO - Laboratoire d'économie d'Orleans - UO - Université d'Orléans - Université de Tours - CNRS - Centre National de la Recherche Scientifique)
    Date: 2018
  10. By: Lukas Pfeifer; Martin Hodula; Libor Holub; Zdenek Pikhart
    Abstract: The capital regulation reform package proposed for the EU banking sector envisages the introduction of a minimum leverage ratio as a (non-risk-weighted) prudential backstop. In this paper, we use Czech bank-level data to explore the implications of introducing a leverage ratio into the capital regulatory framework. Our results confirm that the capital and leverage ratios complement each other. On the other hand, if a minimum leverage ratio is binding on some institutions, the increase in macroprudential capital buffers does not necessarily lead to a real increase in the capital and resilience of those institutions. We therefore describe possible settings of the macroprudential leverage ratio that would maintain the effectiveness of macroprudential policy. Furthermore, we derive channels through which the capital and leverage ratios might be affected and test the functionality of those channels. We find that the leverage ratio is far less procyclical than the capital ratio.
    Keywords: Capital ratio, leverage ratio, macroprudential policy, regulation
    JEL: G21 G28
    Date: 2018–12
  11. By: Grigorova, Miryana (Center for Mathematical Economics, Bielefeld University); Quenez, Marie-Claire (Center for Mathematical Economics, Bielefeld University); Sulem, Agnès (Center for Mathematical Economics, Bielefeld University)
    Abstract: This paper studies the superhedging prices and the associated superhedging strategies for European and American options in a non-linear incomplete market with default. We present the seller's and the buyer's point of view. The underlying market model consists of a risk-free asset and a risky asset driven by a Brownian motion and a compensated default martingale. The portfolio process follows non-linear dynamics with a non-linear driver ƒ. By using a dynamic programming approach, we first provide a dual formulation of the seller's (superhedging) price for the European option as the supremum over a suitable set of equivalent probability measures *Q* ∈ $\mathcal{Q}$ of the ƒ-evaluation/expectation under *Q* of the payoff. We also provide an infinitesimal characterization of this price as the minimal supersolution of a constrained BSDE with default. By a form of symmetry, we derive corresponding results for the buyer. We also give a dual representation of the seller's (superhedging) price for the American option associated with an irregular payoff (ξ *t* ) (not necessarily cà dlà g) in terms of the value of a non-linear mixed control/stopping problem. We also provide an infinitesimal characterization of this price in terms of a constrained reflected BSDE. When ξ is cà dlà g, we show a duality result for the buyer's price. These results rely on first establishing a non-linear optional decomposition for processes which are $\mathcal{E}$ ƒ -strong supermartingales under *Q*, for all *Q* ∈ $\mathcal{Q}$ .
    Keywords: European options, American options, incomplete markets, non-linear pricing, BSDEs with constraints, constrained re ected BSDEs, Æ’-expectation, control problems with non-linear expectation, optimal stopping with non-linear expectation, non-linear optional decomposition, pricing-hedging duality
    Date: 2019–01–18
  12. By: Marco Bardoscia; Daniele d'Arienzo; Matteo Marsili; Valerio Volpati
    Abstract: As financial instruments grow in complexity more and more information is neglected by risk optimization practices. This brings down a curtain of opacity on the origination of risk, that has been one of the main culprits in the 2007-2008 global financial crisis. We discuss how the loss of transparency may be quantified in bits, using information theoretic concepts. We find that {\em i)} financial transformations imply large information losses, {\em ii)} portfolios are more information sensitive than individual stocks only if fundamental analysis is sufficiently informative on the co-movement of assets, that {\em iii)} securitisation, in the relevant range of parameters, yields assets that are less information sensitive than the original stocks and that {\em iv)} when diversification (or securitisation) is at its best (i.e. when assets are uncorrelated) information losses are maximal. We also address the issue of whether pricing schemes can be introduced to deal with information losses. This is relevant for the transmission of incentives to gather information on the risk origination side. Within a simple mean variance scheme, we find that market incentives are not generally sufficient to make information harvesting sustainable.
    Date: 2019–01
  13. By: Barney Hartman-Glaser; Benjamin M. Hébert
    Abstract: We model the widespread failure of contracts to share risk using available indices. A borrower and lender can share risk by conditioning repayments on an index. The lender has private information about the ability of this index to measure the true state the borrower would like to hedge. The lender is risk averse, and thus requires a premium to insure the borrower. The borrower, however, might be paying something for nothing, if the index is a poor measure of the true state. We provide sufficient conditions for this effect to cause the borrower to choose a non-indexed contract instead.
    JEL: D82 D86 G21
    Date: 2019–01
  14. By: Julio Backhoff-Veraguas; Daniel Bartl; Mathias Beiglb\"ock; Manu Eder
    Abstract: Assume that an agent models a financial asset through a measure Q with the goal to price / hedge some derivative or optimize some expected utility. Even if the model Q is chosen in the most skilful and sophisticated way, she is left with the possibility that Q does not provide an exact description of reality. This leads us the following question: will the hedge still be somewhat meaningful for models in the proximity of Q? If we measure proximity with the usual Wasserstein distance (say), the answer is NO. Models which are similar wrt Wasserstein distance may provide dramatically different information on which to base a hedging strategy. Remarkably, this can be overcome by considering a suitable adapted version of the Wasserstein distance which takes the temporal structure of pricing models into account. This adapted Wasserstein distance is most closely related to the nested distance as pioneered by Pflug and Pichler. It allows us to establish Lipschitz properties of hedging strategies for semimartingale models in discrete and continuous time. Notably, these abstract results are sharp already for Brownian motion and European call options.
    Date: 2019–01
  15. By: Faia, Ester; Laffitte, Sebastien; Ottaviano, Gianmarco I. P.
    Abstract: Using a novel dataset on the 15 European banks classified as G-SIBs from 2005 to 2014, we find that the impact of foreign expansion on risk is always negative and significant for most individual and systemic risk metrics. In the case of individual metrics, we also find that foreign expansion affects risk through a competition channel as the estimated impact of openings differs between host countries that are more or less competitive than the source country. The systemic risk metrics also decline with respect to expansion, though results for the competition channel are more mixed, suggesting that systemic risk is more likely to be affected by country or business models characteristics that go beyond and above the differential intensity of competition between source and host markets. Empirical results can be rationalized through a simple model with oligopolistic/oligopsonistic banks and endogenous assets/liabilities risk.
    Keywords: banks’ risk-taking; systemic risk; geographical expansion; gravity; diversification; competition; regulatory arbitrage
    JEL: G21 G32 L13
    Date: 2018–08
  16. By: James Banks (Institute for Fiscal Studies and University of Manchester); Elena Bassoli (Department of Economics, University Of Venice Cà Foscari); Irene Mammi (Department of Economics, University Of Venice Cà Foscari)
    Abstract: This paper investigates risk preference at older ages in 14 European countries. Older individuals report greater risk aversion. Using the longitudinal nature of the data we are able to show this relationship between risk preferences and age is not due to cohort effects or selective mortality. We also show, however, that on average roughly forty percent of this overall age effect is actually due to life events such as retirement, health shocks and widowhood or marital change that occur increasingly as individuals age. These life events are a particularly important explanation of the age `effect' for women and for the age group 50-64.
    Keywords: Risk attitude, ageing, health status, life-related events, SHARE
    JEL: D90 D91 D81
    Date: 2019
  17. By: Tetsuya Adachi (Economist, Institute for Monetary and Economic Studies, Bank of Japan (currently, PwC Consulting LLC, E-mail: tetsuya.; Takumi Sueshige (Senior, EY Shinnihon LLC (currently, School of Computing, Tokyo Institute of Technology, E-mail:; Toshinao Yoshiba (Director and Senior Economist, Institute for Monetary and Economic Studies (currently, Financial System and Bank Examination Department), Bank of Japan (E-mail:
    Abstract: We compare several wrong-way risk models for the credit valuation adjustment of a credit default swap under a copula approach with stochastic default intensities. We show that the tail dependent copulas well capture the wrong-way risk for the credit valuation adjustment. To that end, we employ an affine jump diffusion process for the default intensity to derive the distribution function of the cumulative intensity, based on the copula approach. To reduce computing time, we propose an approximation method using the fractional fast Fourier transform and numerical integration to the characteristic function of the cumulative intensity.
    Keywords: Credit valuation adjustment, Credit default swap, Affine jump diffusion, Fractional fast Fourier transform, Characteristic function
    JEL: G13
    Date: 2019–01
  18. By: Eckhard Platen (Finance Discipline Group, UTS Business School, University of Technology Sydney); Renata Rendek
    Abstract: The paper derives a parsimonious model for the long-term dynamics of a well-diversified stock index, the S&P500. The index is modeled as growth optimal portfolio. Its normalized value evolves, in some market time, as a square root process. The derivative of market time is a linear function of the squared derivative of a smoothed proxy of the single driving Brownian motion. The model explains the feedback effects from index moves typically observed for monthly and daily S&P500 values. It is highly tractable, permits almost exact simulation and leads beyond classical assumptions in finance.
    Keywords: long-term index model; growth optimal portfolio; square root process; market time; leverage effect puzzle; benchmark approach
    JEL: G10 C10 C15
    Date: 2019–01–01
  19. By: Blanka Horvath; Aitor Muguruza; Mehdi Tomas
    Abstract: We present a consistent neural network based calibration method for a number of volatility models -- including the rough volatility family -- that performs the calibration task within a few milliseconds for the full implied volatility surface. The aim of neural networks in this work is an off-line approximation of complex pricing functions, which are difficult to represent or time-consuming to evaluate by other means. We highlight how this perspective opens new horizons for quantitative modelling: The calibration bottleneck posed by a slow pricing of derivative contracts is lifted. This brings several model families (such as rough volatility models) within the scope of applicability in industry practice. As customary for machine learning, the form in which information from available data is extracted and stored is crucial for network performance. With this in mind, we discuss how our approach addresses the usual challenges of machine learning solutions in a financial context (availability of training data, interpretability of results for regulators, control over generalisation errors). We present specific architectures for price approximation and calibration and optimize these with respect to different objectives regarding accuracy, speed and robustness. We also find that including the intermediate step of learning pricing functions of (classical or rough) models before calibration significantly improves network performance compared to direct calibration to data.
    Date: 2019–01
  20. By: Mohitosh Kejriwal; Xuewen Yu
    Abstract: This paper proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by nonstationary volatility. The assumed volatility process can accommodate discrete breaks, smooth transition variation as well as trending volatility. We develop wild bootstrap sup-Wald tests of the null hypothesis that the process is either stationary [I(0)] or has a unit root [I(1)] throughout the sample. We also propose a sequential procedure to estimate the number of persistence breaks based on ordering the regime-specific bootstrap p-values. The asymptotic validity of the advocated procedures is established both under the null of stability and a variety of persistence change alternatives. Monte Carlo simulations support the use of a non-recursive scheme for generating the I(0) bootstrap samples and a partially recursive scheme for generating the I(1) bootstrap samples, especially when the data generating process contains an I(1) segment. A comparison with existing tests illustrates the finite sample improvements offered by our methods in terms of both size and power. An application to OECD inflation rates is included.
    Keywords: heteroskedasticity, multiple structural changes,
    JEL: C22
    Date: 2018–12
  21. By: M. Rouhani, Omid
    Abstract: In this paper, I briefly review the key methods to evaluate transportation projects. These methods are: Financial analysis; Cost benefit (economic analysis); Multi-criteria analysis; Cost-effectiveness analysis; Social welfare analysis; and Risk analysis (Monte Carlo simulation). The importance of understanding these methods lies in the fact that transportation projects offer huge social benefits and costs; some are impossible or very complex to measure in monetary terms.
    Keywords: Project evaluation methods, Transport projects, Social cost benefit analysis, Multi-criteria analysis, and Social welfare analysis.
    JEL: H43 R42 R58
    Date: 2019–01–07

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