nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒11‒01
thirteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Star-shaped acceptability indexes By Marcelo Brutti Righi
  2. Long Run Risk Model and Equity Premium Puzzle in Thailand By Sartja Duangchaiyoosook; Weerachart Kilenthong
  3. MAD Risk Parity Portfolios By \c{C}a\u{g}{\i}n Ararat; Francesco Cesarone; Mustafa \c{C}elebi P{\i}nar; Jacopo Maria Ricci
  4. Revisiting the Case for a Fiscal Union: the Federal Fiscal Channel of Downside-Risk Sharing in the United States By Luca Rossi
  5. Forecasting Financial Market Structure from Network Features using Machine Learning By Douglas Castilho; Tharsis T. P. Souza; Soong Moon Kang; Jo\~ao Gama; Andr\'e C. P. L. F. de Carvalho
  6. When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance By Yacine Aït-Sahalia; Felix Matthys; Emilio Osambela; Ronnie Sircar
  7. Forecasting International REITs Volatility: The Role of Oil-Price Uncertainty By Jiqian Wang; Rangan Gupta; Oguzhan Cepni; Feng Ma
  8. Pricing Poseidon: Extreme Weather Uncertainty and Firm Return Dynamics By Mathias S. Kruttli; Brigitte Roth Tran; Sumudu W. Watugala
  9. Mean-Variance Portfolio Selection in Contagious Markets By Yang Shen; Bin Zou
  10. Cyber contagion: impact of the network structure on the losses of an insurance portfolio By Caroline Hillairet; Olivier Lopez; Louise d'Oultremont; Brieuc Spoorenberg
  11. Liquidity-free implied volatilities: an approach using conic finance By Matteo Michielon; Asma Khedher; Peter Spreij
  12. Inflation at Risk in Thailand By Maneerat Gongsiang; Pongpitch Amatyakul
  13. The Real Consequences of Macroprudential FX Regulations By Hyeyoon Jung

  1. By: Marcelo Brutti Righi
    Abstract: We propose the star-shaped acceptability indexes as generalizations of both the approaches of Cherny and Madan (2009) and Rosazza Gianin and Sgarra (2013) in the same vein as star-shaped risk measures generalize both the classes of coherent and convex risk measures. We characterize acceptability indexes through star-shaped risk measures, star-shaped acceptance sets, and as the minimum of some family of quasi-concave acceptability indexes. Further, we introduce concrete examples under our approach linked to Value at Risk, risk-adjusted reward on capital, reward-based gain-loss ratio, monotone reward-deviation ratio, and robust acceptability indexes. We also expose an application regarding optimization of performance.
    Date: 2021–10
  2. By: Sartja Duangchaiyoosook; Weerachart Kilenthong
    Abstract: This paper shows that the long-run risk model of Bansal and Yaron (2004) can potentially solve the equity premium and risk-free rate puzzles in Thailand. In particular, the calibrated values of the risk aversion and the elasticity of intertemporal substitution are empirically plausible. Risk decomposition results indicate that long-run risk is the most important risk component relevant to asset prices; that is, asset prices in Thai financial markets are most sensitive to small changes in news regarding long-term expected growth rates. Volatility risk also has an impact on asset prices but its impact is just about a quarter of the impact of the long-run risk.
    Keywords: Equity Premium Puzzle; Long-run Risk Model; Long-run Component Risk; Asset Pricing; Generalized Method of Moments
    JEL: G12
    Date: 2021–04
  3. By: \c{C}a\u{g}{\i}n Ararat; Francesco Cesarone; Mustafa \c{C}elebi P{\i}nar; Jacopo Maria Ricci
    Abstract: In this paper, we investigate the features and the performance of the Risk Parity (RP) portfolios using the Mean Absolute Deviation (MAD) as a risk measure. The RP model is a recent strategy for asset allocation that aims at equally sharing the global portfolio risk among all the assets of an investment universe. We discuss here some existing and new results about the properties of MAD that are useful for the RP approach. We propose several formulations for finding MAD-RP portfolios computationally, and compare them in terms of accuracy and efficiency. Furthermore, we provide extensive empirical analysis based on five real-world datasets, showing that the performances of the RP approaches generally tend to place both in terms of risk and profitability between those obtained from the minimum risk and the Equally Weighted strategies.
    Date: 2021–10
  4. By: Luca Rossi (Bank of Italy)
    Abstract: Differentiating between standard risk measures and downside risk has a longstanding tradition in finance. Interestingly, this fundamental distinction has been neglected in the literature on risk sharing. Drawing on a simple definition in Markowitz (1959), we translate downside-risk metrics appropriate for stock returns into ones that can be used in our macro-forecasting setting, and propose a new methodology to estimate channels of downside-risk sharing, with an application to the federal fiscal channel in the United States. Our work reinstates some discarded arguments as to why a fiscal union could be desirable, as our findings suggest that public risk sharing is considerably higher than was previously thought. We also show that the great importance long attributed to the capital market channel estimated with popular income smoothing methodologies is instead entirely driven by the neglect of the effect of capital depreciation. Therefore, our paper argues that the relative importance of the fiscal channel as compared to the capital market one has been substantially underestimated.
    Keywords: downside risk, risk sharing, fiscal unions
    JEL: C80 E01 E17 E64 H29
    Date: 2021–10
  5. By: Douglas Castilho; Tharsis T. P. Souza; Soong Moon Kang; Jo\~ao Gama; Andr\'e C. P. L. F. de Carvalho
    Abstract: We propose a model that forecasts market correlation structure from link- and node-based financial network features using machine learning. For such, market structure is modeled as a dynamic asset network by quantifying time-dependent co-movement of asset price returns across company constituents of major global market indices. We provide empirical evidence using three different network filtering methods to estimate market structure, namely Dynamic Asset Graph (DAG), Dynamic Minimal Spanning Tree (DMST) and Dynamic Threshold Networks (DTN). Experimental results show that the proposed model can forecast market structure with high predictive performance with up to $40\%$ improvement over a time-invariant correlation-based benchmark. Non-pair-wise correlation features showed to be important compared to traditionally used pair-wise correlation measures for all markets studied, particularly in the long-term forecasting of stock market structure. Evidence is provided for stock constituents of the DAX30, EUROSTOXX50, FTSE100, HANGSENG50, NASDAQ100 and NIFTY50 market indices. Findings can be useful to improve portfolio selection and risk management methods, which commonly rely on a backward-looking covariance matrix to estimate portfolio risk.
    Date: 2021–10
  6. By: Yacine Aït-Sahalia; Felix Matthys; Emilio Osambela; Ronnie Sircar
    Abstract: We analyze an environment where the uncertainty in the equity market return and its volatility are both stochastic and may be potentially disconnected. We solve a representative investor's optimal asset allocation and derive the resulting conditional equity premium and risk-free rate in equilibrium. Our empirical analysis shows that the equity premium appears to be earned for facing uncertainty, especially high uncertainty that is disconnected from lower volatility, rather than for facing volatility as traditionally assumed. Incorporating the possibility of a disconnect between volatility and uncertainty significantly improves portfolio performance, over and above the performance obtained by conditioning on volatility only.
    Keywords: Risk Aversion; Stochastic Uncertainty; Stochastic Volatility; Uncertainty Aversion; Volatility and Uncertainty Disconnect
    JEL: G11 G12
    Date: 2021–09–30
  7. By: Jiqian Wang (School of Economics and Management, Southwest Jiaotong University, Chengdu, China); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Oguzhan Cepni (Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark; Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050, Ankara, Turkey); Feng Ma (School of Economics and Management, Southwest Jiaotong University, Chengdu, China)
    Abstract: We forecast realized variance (RV) of Real Estate Investment Trusts (REITs) for ten leading markets and regions, derived from 5-minutes-interval intraday data, based on the information content of two alternative metrics of daily oil-price uncertainty. Based on the period of the analysis covering January 2008 to July 2020, and using variants of the popular MIDAS-RV model, augmented to include oil market uncertainties, captured by its RV (also derived from 5-minute intraday data) and implied volatility (i.e., the oil VIX), we report evidence of significant statistical and economic gains in the forecasting performance. The result is robust to the size of the forecasting samples, including that of the COVID-19 period, jump risks, lag-length, nonlinearities, and asymmetric effects, and forecast horizon. Our results have important implications for investors and policymakers.
    Keywords: REITs, International data, Realized volatility, Oil-Price Uncertainty, Forecasting
    JEL: C22 C53 G15 Q02
    Date: 2021–10
  8. By: Mathias S. Kruttli; Brigitte Roth Tran; Sumudu W. Watugala
    Abstract: We present a framework to identify market responses to uncertainty faced by firms regarding both the potential incidence of extreme weather events and subsequent economic impact. Stock options of firms with establishments in forecast and realized hurricane landfall regions exhibit large increases in implied volatility, reflecting significant incidence uncertainty and long-lasting impact uncertainty. Comparing ex ante expected volatility to ex post realized volatility by analyzing volatility risk premia changes shows that investors significantly underestimate extreme weather uncertainty. After Hurricane Sandy, this underreaction diminishes and, consistent with Merton (1987), these increases in idiosyncratic volatility are associated with positive expected stock returns.
    Keywords: extreme weather; uncertainty; implied volatility; expected returns; climate risks
    JEL: G12 G14 Q54
    Date: 2021–03–01
  9. By: Yang Shen; Bin Zou
    Abstract: We consider a mean-variance portfolio selection problem in a financial market with contagion risk. The risky assets follow a jump-diffusion model, in which jumps are driven by a multivariate Hawkes process with mutual-excitation effect. The mutual-excitation feature of the Hawkes process captures the contagion risk in the sense that each price jump of an asset increases the likelihood of future jumps not only in the same asset but also in other assets. We apply the stochastic maximum principle, backward stochastic differential equation theory, and linear-quadratic control technique to solve the problem and obtain the efficient strategy and efficient frontier in semi-closed form, subject to a non-local partial differential equation. Numerical examples are provided to illustrate our results.
    Date: 2021–10
  10. By: Caroline Hillairet (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique); Olivier Lopez (LPSM (UMR_8001) - Laboratoire de Probabilités, Statistiques et Modélisations - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique - UP - Université de Paris); Louise d'Oultremont; Brieuc Spoorenberg
    Abstract: In this paper, we provide a model that aims to describe the impact of a massive cyber attack on an insurance portfolio, taking into account the structure of the network. Due to the contagion, such an event can rapidly generate consequent damages, and mutualization of the losses may not hold anymore. The composition of the portfolio should therefore be diversified enough to prevent or reduce the impact of such events, with the difficulty that the relationships between actor is difficult to assess. Our approach consists in introducing a multi-group epidemiological model which, apart from its ability to describe the intensity of connections between actors, can be calibrated from a relatively small amount of data, and through fast numerical procedures. We show how this model can be used to generate reasonable scenarios of cyber events, and investigate the response to different types of attacks or behavior of the actors, allowing to quantify the benefit of an efficient prevention policy.
    Keywords: Cyber insurance,cyber risk,compartmental models,multi-SIR,network structures
    Date: 2021–10–20
  11. By: Matteo Michielon; Asma Khedher; Peter Spreij
    Abstract: We consider the problem of calculating risk-neutral implied volatilities of European options without relying on option mid prices but solely on bid and ask prices. We provide an approach, based on the conic finance paradigm, that allows to uniquely strip risk-neutral implied volatilities from bid and ask quotes, and that does not require restrictive assumptions. Our methodology also allows to jointly calculate the implied liquidity of the market. The idea outlined in this paper can be applied to calculate other implied parameters from bid and ask security prices as soon as their theoretical risk-neutral counterparts are strictly increasing with respect to the former.
    Date: 2021–10
  12. By: Maneerat Gongsiang; Pongpitch Amatyakul
    Abstract: Using monthly Thai data from 2003–2020, we examine the determinants of the future distribution of inflation. We evaluate how different risk factors predict 1-year- ahead future distributions of CPI inflation and its components. Risk factors come from 5 different groups of variables: inflation expectations, domestic economic activity, global economic activity, financial conditions, and component-specific factors. We obtain points on the future distributions of inflation through quantile regressions and fitting those points with skewed-t distributions. Our focus is on the outlook in the tails of the distribution, which recent literature referred to as `inflation-at-risk.' We find, as expected, that the whole inflation distribution has shifted lower, and thus the probability of negative inflation has increased markedly in recent years. There is a structural break around 2015 that affects both the distributions of inflation and their determinants. This structural break makes it challenging to make out-of-sample forecasts, thus, we focus on in-sample evaluation and explanations. For risk factors, we observe that the tightening of financial conditions and the decreasing world production are prominent sources of downside risks to inflation. Inflation expectations also play a smaller role in the lower quantiles, signaling its lower effectiveness in anchoring actual inflation during disinflationary periods. Finally, high global and domestic economic activity can be effective in decreasing downside risks in the lower tail, providing policy makers a way to counter these risks by stimulating the economy.
    Keywords: Inflation Determinants; Central Bank Policies
    JEL: E31 E52
    Date: 2021–04
  13. By: Hyeyoon Jung
    Abstract: I exploit a natural experiment in South Korea to examine the real effects of macroprudential foreign exchange (FX) regulations designed to reduce risk-taking by financial intermediaries. By using crossbank variation in the regulation's tightness, I show that it causes a reduction in the supply of FX derivatives (FXD) and results in a substantial decline in exports for the firms that were heavily relying on FXD hedging. I offer a mechanism in which imbalances in hedging demand, banks' costly equity financing, and firms' costly switching of banking relationships play a central role in explaining the empirical findings.
    Keywords: real effects; macroprudential policy; international finance; derivatives hedging; FX risk management
    JEL: D14 E44 G15 G28 G32
    Date: 2021–10–01

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