nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒11‒05
nineteen papers chosen by



  1. On the solution uniqueness in portfolio optimization and risk analysis By Bogdan Grechuk; Andrzej Palczewski; Jan Palczewski
  2. Optimal hedging under fast-varying stochastic volatility By Josselin Garnier; Knut Solna
  3. New Evidence on Procyclical Bank Capital Regulation: The Role of Bank Loan Commitments By Ki Young Park
  4. Tenure Choice, Portfolio Structure and Long-term Care - Optimal Risk Management in Retirement By Hofmann, Maurice; Fehr, Hans
  5. Forecasting Financial Stress Indices in Korea: A Factor Model Approach By Hyeongwoo Kim; Wen Shi; Hyun Hak Kim
  6. Forecasting Financial Vulnerability in the US: A Factor Model Approach By Hyeongwoo Kim; Wen Shi
  7. Asset allocation: new evidence through network approaches By Gian Paolo Clemente; Rosanna Grassi; Asmerilda Hitaj
  8. On the ranking consistency of global systemic risk measures: empirical evidence By Abendschein, Michael; Grundke, Peter
  9. Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach By Kim, Hyeongwoo; Ko, Kyunghwan
  10. Time consistency for scalar multivariate risk measures By Zachary Feinstein; Birgit Rudloff
  11. Effects of Brexit on Corporate Yield Spreads: Evidence from UK and Eurozone Corporate Bond Markets By Arthur Korus; Samir Kadiric
  12. Measurement of Volatility Spillovers and Asymmetric Connectedness on Commodity and Equity Markets By Tereza Palanska
  13. Tail-dependent Rainfall Risk and Demand for Index based Crop Insurance By Negi, Digvijay S.
  14. Quantifying the Model Risk Inherent in the Calibration and Recalibration of Option Pricing Models By Yu Feng; Ralph Rudd; Christopher Baker; Qaphela Mashalaba; Melusi Mavuso; Erik Schl\"ogl
  15. Determinants of Business Risks With Impact on SMEs in V4 countries By Zuzana Virglerova
  16. The Relationship between Macroeconomic Overheating and Financial Vulnerability : A Narrative Investigation By Elena Afanasyeva; Seung Jung Lee; Michele Modugno; Francisco J. Palomino
  17. Portfolio Construction Matters By Stefano Ciliberti; Stanislao Gualdi
  18. Funding Options from the Market By Bell, Peter
  19. Multilinear Superhedging of Lookback Options By Alex Garivaltis

  1. By: Bogdan Grechuk; Andrzej Palczewski; Jan Palczewski
    Abstract: We consider the issue of solution uniqueness for portfolio optimization problem and its inverse for asset returns with a finite number of possible scenarios. The risk is assessed by deviation measures introduced by Rockafellar et al. (2006) instead of variance as in the Markowitz optimization problem. We prove that in general one can expect uniqueness neither in forward nor in inverse problems. We discuss consequences of that non-uniqueness for several problems in risk analysis and portfolio optimization, including capital allocation, risk sharing, cooperative investment, and the Black-Litterman methodology. In all cases, the issue with non-uniqueness is closely related to the fact that subgradient of a convex function is non-unique at the points of non-differentiability. We suggest methodology to resolve this issue by identifying a unique "special" subgradient satisfying some natural axioms. This "special" subgradient happens to be the Stainer point of the subdifferential set.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.11299&r=rmg
  2. By: Josselin Garnier; Knut Solna
    Abstract: In a market with a rough or Markovian mean-reverting stochastic volatility there is no perfect hedge. Here it is shown how various delta-type hedging strategies perform and can be evaluated in such markets. A precise characterization of the hedging cost, the replication cost caused by the volatility fluctuations, is presented in an asymptotic regime of rapid mean reversion for the volatility fluctuations. The optimal dynamic asset based hedging strategy in the considered regime is identified as the so-called `practitioners' delta hedging scheme. It is moreover shown that the performances of the delta-type hedging schemes are essentially independent of the regularity of the volatility paths in the considered regime and that the hedging costs are related to a vega risk martingale whose magnitude is proportional to a new market risk parameter.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.08337&r=rmg
  3. By: Ki Young Park (Yonsei University)
    Abstract: Previous research on procyclical bank capital regulation has largely focused on the role of increased loan losses and deteriorated credit ratings in economic downturns. We focus on the role of bank loan commitments, which have been increasingly popular from the 2000s, on the procyclicality of bank capital regulation. Using the bank-level data of U.S. commercial banks, we present another independent source of procyclicality working through bank loan commitments, which we call "loan commitments channel." We find that, as firms draw down more from their pre-existing credit lines when credit market conditions are tighter, this increased takedown raises bank risk-weighted assets via involuntary lending and thus lowers capital adequacy ratios of commercial banks, making them more procyclical. Our empirical results suggest that this loan commitments channel is quantitatively important and needs to be addressed in designing the regulatory framework for reducing credit procyclicality.
    Keywords: bank loan commitments, capital adequacy ratio (CAR), procyclical bank, capital regulation
    JEL: E44 G21 G32
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:yon:wpaper:2018rwp-130&r=rmg
  4. By: Hofmann, Maurice; Fehr, Hans
    Abstract: Our study analyzes the savings behavior of elderly and highlights the interplay between tenure decisions, stock market investment and long-term care risk. Housing equity serves a dual purpose as a consumption good and as an asset, consequently it is important for the optimal risk structure of the financial portfolio. In addition, recent contributions also point out its implicit insurance provision to buffer long-term care shocks. Our stylized life cycle model captures these links and indicates that in Germany long-term care risks may be an important driver for homeownership. In our preferred set-up housing equity is a rather low-risky investment that even encourages stockmarket participation among elderly homeowners.
    Keywords: Homeownership,Life-cycle models,Stock market participation,Long-term care insurance provision
    JEL: C61 G11 H55
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:zbw:vfsc18:181517&r=rmg
  5. By: Hyeongwoo Kim; Wen Shi; Hyun Hak Kim
    Abstract: We propose factor-based out-of-sample forecast models for Korea's financial stress index and its 4 sub-indices that are developed by the Bank of Korea. We extract latent common factors by employing the method of the principal components for a panel of 198 monthly frequency macroeconomic data after differencing them. We augment an autoregressive-type model of the financial stress index with estimated common factors to formulate out-of-sample forecasts of the index. Our models overall outperform both the stationary and the nonstationary benchmark models in forecasting the financial stress indices for up to 12-month forecast horizons. The first common factor that represents not only financial market but also real activity variables seems to play a dominantly important role in predicting the vulnerability in the financial markets in Korea.
    Keywords: Financial Stress Index; Principal Component Analysis; PANIC; In-Sample Fit; Out-of-Sample Forecast; Diebold-Mariano-West Statistic
    JEL: E44 E47 G01 G17
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:abn:wpaper:auwp2018-06&r=rmg
  6. By: Hyeongwoo Kim; Wen Shi
    Abstract: This paper presents a factor-based forecasting model for the financial market vulnerability, measured by changes in the Cleveland Financial Stress Index (CFSI). We estimate latent common factors via the method of the principal components from 170 monthly frequency macroeconomic data in order to out-of-sample forecast the CFSI. Our factor models outperform both the random walk and the autoregressive benchmark models in out-of-sample predictability at least for the short-term forecast horizons, which is a desirable feature since financial crises often come to a surprise realization. Interestingly, the first common factor, which plays a key role in predicting the financial vulnerability index, seems to be more closely related with real activity variables rather than nominal variables. We also present a binary choice version factor model that estimates the probability of the high stress regime successfully.
    Keywords: Financial Stress Index; Method of the Principal Component; Out-of-Sample Forecast; Ratio of Root Mean Square Prediction Error; Diebold-Mariano-West Statistic; Ordered Probit Model
    JEL: E44 E47 G01 G17
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:abn:wpaper:auwp2018-07&r=rmg
  7. By: Gian Paolo Clemente; Rosanna Grassi; Asmerilda Hitaj
    Abstract: The main contribution of the paper is to employ the financial market network as a useful tool to improve the portfolio selection process, where nodes indicate securities and edges capture the dependence structure of the system. Three different methods are proposed in order to extract the dependence structure between assets in a network context. Starting from this modified structure, we formulate and then we solve the asset allocation problem. We find that the portfolios obtained through a network-based approach are composed mainly of peripheral assets, which are poorly connected with the others. These portfolios, in the majority of cases, are characterized by an higher trade-off between performance and risk with respect to the traditional Global Minimum Variance (GMV) portfolio. Additionally, this methodology benefits of a graphical visualization of the selected portfolio directly over the graphic layout of the network, which helps in improving our understanding of the optimal strategy.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.09825&r=rmg
  8. By: Abendschein, Michael; Grundke, Peter
    Abstract: We empirically analyze to which extent popular global systemic risk measures (SRMs) yield comparable results with respect to the systemic importance of a financial institution and, in particular, from which determinants the degree of consistency of the classification by the various SRMs depends. In this study, we investigate the rank correlations of SRMs in order to detect common drivers that might explain (in-)consistent ranking outcomes. This could allow to facilitate the interpretation of the outcome of SRMs and to increase the reliability of their usage in academic and practical applications. Our results show that rank correlations are particularly sensitive towards a bank’s leverage and towards tightening economic conditions. This finding holds across various different specifications.
    Keywords: systemic risk,risk rankings,financial regulation
    JEL: G01 G21 G28 G32
    Date: 2018
    URL: http://d.repec.org/n?u=RePEc:zbw:vfsc18:181623&r=rmg
  9. By: Kim, Hyeongwoo; Ko, Kyunghwan
    Abstract: We present a factor augmented forecasting model for assessing the financial vulnerability in Korea. Dynamic factor models often extract latent common factors from a large panel of time series data via the method of the principal components (PC). Instead, we employ the partial least squares (PLS) method that estimates target specific common factors, utilizing covariances between predictors and the target variable. Applying PLS to 198 monthly frequency macroeconomic time series variables and the Bank of Korea's Financial Stress Index (KFSTI), our PLS factor augmented forecasting models consistently outperformed the random walk benchmark model in out-of-sample prediction exercises in all forecast horizons we considered. Our models also outperformed the autoregressive benchmark model in short-term forecast horizons. We expect our models would provide useful early warning signs of the emergence of systemic risks in Korea's financial markets.
    Keywords: Partial Least Squares; Principal Component Analysis; Financial Stress Index; Out-of-Sample Forecast; RRMSPE
    JEL: C38 C53 E44 E47 G00 G17
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:89449&r=rmg
  10. By: Zachary Feinstein; Birgit Rudloff
    Abstract: In this paper we present results on dynamic multivariate scalar risk measures, which arise in markets with transaction costs and systemic risk. Dual representations of such risk measures are presented. These are then used to obtain the main results of this paper on time consistency; namely, an equivalent recursive formulation of multivariate scalar risk measures to multiportfolio time consistency. We are motivated to study time consistency of multivariate scalar risk measures as the superhedging risk measure in markets with transaction costs (with a single eligible asset) (Jouini and Kallal (1995), Roux and Zastawniak (2016), Loehne and Rudloff (2014)) does not satisfy the usual scalar concept of time consistency. In fact, as demonstrated in (Feinstein and Rudloff (2018)), scalar risk measures with the same scalarization weight at all times would not be time consistent in general. The deduced recursive relation for the scalarizations of multiportfolio time consistent set-valued risk measures provided in this paper requires consideration of the entire family of scalarizations. In this way we develop a direct notion of a "moving scalarization" for scalar time consistency that corroborates recent research on scalarizations of dynamic multi-objective problems (Karnam, Ma, and Zhang (2017), Kovacova and Rudloff (2018)).
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.04978&r=rmg
  11. By: Arthur Korus (Europäisches Institut für Internationale Wirtschaftsbeziehungen (EIIW)); Samir Kadiric (Europäisches Institut für Internationale Wirtschaftsbeziehungen (EIIW))
    Abstract: Using event-study techniques we investigate the impact of Brexit-related events on the corporate bond yield spreads in the United Kingdom and euro area, respectively. We want to find out whether Brexit-related news, including the Brexit referendum itself, had an impact on the risk conditions in those two corporate bond markets. Our estimation results indicate that the announcement of the referendum result is associated with increasing credit spreads in the UK and EA. However, only the actual announcement of the UK referendum result itself had an influence on the credit spreads. Furthermore, we distinguish between the financial and the non-financial economic sectors in order to analyze more specific sector-related effects of the referendum event. Our estimation results suggest that UK credit spreads were more strongly influenced by the announcement of the results of the Brexit referendum than credit bond spreads in the euro area were. Finally, we split our sample into pre-referendum and post-referendum periods to consider the potential changing evaluation of the determinants of corporate bond spreads due to altering risk pricing triggered by the Brexit referendum result. We find that the effect of credit default risk is far stronger and plays a significant role in the post-referendum period in UK and EA, respectively.
    Keywords: corporate bond yield spreads, credit risk, Brexit, event-study
    JEL: C32 G12 G14 G32
    Date: 2018–09
    URL: http://d.repec.org/n?u=RePEc:bwu:eiiwdp:disbei251&r=rmg
  12. By: Tereza Palanska (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic)
    Abstract: We study volatility spillovers among commodity and equity markets by employing a recently developed approach based on realized measures and forecast error variance decomposition invariant to the variable ordering from vector-autoregressions. This enables us to measure total, directional and net volatility spillovers as well as the asymmetry of responses to positive and negative shocks. We exploit high-frequency data on the prices of Crude oil, Corn, Cotton and Gold futures, and the S&P 500 Index and use a sample which spans from January 2002 to December 2015 to cover the entire period around the global financial crisis of 2008. Our empirical analysis reveals that on average, the volatility shocks related to other markets account for around one fifth of the volatility forecast error variance. We find that shocks to the stock markets play the most important role as the S&P 500 Index dominates all commodities in terms of general volatility spillover transmission. Our results further suggest that volatility spillovers across the analyzed assets were rather limited before the global financial crisis, which then boosted the connectedness between commodity and stock markets. Furthermore, the volatility due to positive and negative shocks is transmitted between markets at different magnitudes and the prevailing effect has varied. In the pre-crisis period, the positive spillovers dominated the negative ones, however, in several years following the crisis, the negative shocks have had a significantly higher impact on the volatility spillovers across the markets, pointing to an overall increase in uncertainty in the commodity and equity markets following a major crisis. In recent years, the asymmetric measures seem to have returned to their pre-crises directions and magnitudes.
    Keywords: Volatility, Spillovers, Relized Semivariance, Asymmetric effects, Commodity markets, Equity markets
    JEL: C18 C58 G01 G15 Q02
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp2018_27&r=rmg
  13. By: Negi, Digvijay S.
    Keywords: Risk and Uncertainty, Food and Agricultural Policy Analysis, International Development
    Date: 2018–06–20
    URL: http://d.repec.org/n?u=RePEc:ags:aaea18:274481&r=rmg
  14. By: Yu Feng; Ralph Rudd; Christopher Baker; Qaphela Mashalaba; Melusi Mavuso; Erik Schl\"ogl
    Abstract: We focus on two particular aspects of model risk: the inability of a chosen model to fit observed market prices at a given point in time (calibration error) and the model risk due to recalibration of model parameters (in contradiction to the model assumptions). In this context, we follow the approach of Glasserman and Xu (2014) and use relative entropy as a pre-metric in order to quantify these two sources of model risk in a common framework, and consider the trade-offs between them when choosing a model and the frequency with which to recalibrate to the market. We illustrate this approach applied to the models of Black and Scholes (1973) and Heston (1993), using option data for Apple (AAPL) and Google (GOOG). We find that recalibrating a model more frequently simply shifts model risk from one type to another, without any substantial reduction of aggregate model risk. Furthermore, moving to a more complicated stochastic model is seen to be counterproductive if one requires a high degree of robustness, for example as quantified by a 99 percent quantile of aggregate model risk.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.09112&r=rmg
  15. By: Zuzana Virglerova (Tomas Bata University in Zlín, Facutly of Management and Economics)
    Abstract: Many enterprises fight with various risks and it can be a reason of lack of success for their business. The first step towards successful risk management is a risk identification. Entrepreneurs use different methods for risk identification and they also detect diverse risks. The aim of the article is to identify determinants of business risks in SMEs in Visegrad Four. The article deals with the partial results of the empirical questionnaire survey, which was completed in 2018 at the Tomas Bata University in Zlín in the Czech Republic. Questionnaires from the owners of micro and SME enterprises in Hungary (388), Poland (498), Slovakia (487) and Czech Republic (408) were collected. Entrepreneurs were asked for the ability to identify risks, importance of risks and methods used for risk management in their companies. 3 research questions were set in this context. In process of solving the formulated research questions the following statistical tools such as tables, descriptive characteristics, and Person coefficient of contingency were used. Finally, the results indicate that there are differences in risk identification among countries. Also the importance of each risk is different. The similarity of results in Czech Republic and Slovakia was proved. The article concludes with a discussion which explains possible couse of differences and similarities of results.
    Keywords: business risks, SME, entrepreneurship, risk identification
    JEL: G32 M21 L26
    Date: 2018–07
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:6509314&r=rmg
  16. By: Elena Afanasyeva; Seung Jung Lee; Michele Modugno; Francisco J. Palomino
    Abstract: In this note, we follow a narrative approach to review historical episodes of significant financial imbalances and examine whether these episodes were linked to macroeconomic overheating.
    Date: 2018–10–12
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfn:2018-10-12-2&r=rmg
  17. By: Stefano Ciliberti; Stanislao Gualdi
    Abstract: The role of portfolio construction in the implementation of equity market neutral factors is often underestimated. Taking the classical momentum strategy as an example, we show that one can significantly improve the main strategy's features by properly taking care of this key step. More precisely, an optimized portfolio construction algorithm allows one to significantly improve the Sharpe Ratio, reduce sector exposures and volatility fluctuations, and mitigate the strategy's skewness and tail correlation with the market. These results are supported by long-term, world-wide simulations and will be shown to be universal. Our findings are quite general and hold true for a number of other "equity factors". Finally, we discuss the details of a more realistic set-up where we also deal with transaction costs.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.08384&r=rmg
  18. By: Bell, Peter
    Abstract: Investors face many different versions of The Portfolio Problem. Consider, for example, holding shares and call options on a publicly-traded equity. The options are in-the-money and live. How best should the investor go about exercising those options? They could fund from capital or use the secondary market to fund the options, as follows. When market price is above strike price, it may be possible to sell shares into market in advance of exercising the call options. This operation can yield residual cash or shares. How much should an investor do this and when? This paper presents a specific numerical example where we trade out of options when the market price breaches a 2:1 ratio to strike price and provides descriptive statistics for investors’ wealth in simulation with standard Gaussian motion for share price and specific trading rule.
    Keywords: Finance, Trading, Derivatives,
    JEL: C00 G00
    Date: 2018–10–05
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:89360&r=rmg
  19. By: Alex Garivaltis
    Abstract: In a pathbreaking paper, Cover and Ordentlich (1998) solved a max-min portfolio game between a trader (who picks an entire trading algorithm, $\theta(\cdot)$) and "nature," who picks the matrix $X$ of gross-returns of all stocks in all periods. Their (zero-sum) game has the payoff kernel $W_\theta(X)/D(X)$, where $W_\theta(X)$ is the trader's final wealth and $D(X)$ is the final wealth that would have accrued to a $\$1$ deposit into the best constant-rebalanced portfolio (or fixed-fraction betting scheme) determined in hindsight. The resulting "universal portfolio" compounds its money at the same asymptotic rate as the best rebalancing rule in hindsight, thereby beating the market asymptotically under extremely general conditions. Smitten with this (1998) result, the present paper solves the most general tractable version of Cover and Ordentlich's (1998) max-min game. This obtains for performance benchmarks (read: derivatives) that are separately convex and homogeneous in each period's gross-return vector. For completely arbitrary (even non-measurable) performance benchmarks, we show how the axiom of choice can be used to "find" an exact maximin strategy for the trader.
    Date: 2018–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1810.02447&r=rmg

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