nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒06‒13
fourteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Robust Distortion Risk Measures By Carole Bernard; Silvana M. Pesenti; Steven Vanduffel
  2. Eine empirische Analyse der Skalierung von Value-at-Risk Schaetzungen By Marita Kuhlmann
  3. Failure of Gold, Bitcoin and Ethereum as safe havens during the Ukraine-Russia war By Alhonita Yatie
  4. Bitcoin Prices and the Realized Volatility of US Sectoral Stock Returns By Elie Bouri; Afees A. Salisu; Rangan Gupta
  5. Dynamics of Subjective Risk Premia By Stefan Nagel; Zhengyang Xu
  6. Portfolio Diversification Revisited By Charles Shaw
  7. Implications of Cyber Risk for Financial Stability By Danny Brando; Antonis Kotidis; Anna Kovner; Michael Junho Lee; Stacey L. Schreft
  8. Taxes, Risk Taking, and Financial Stability By Kogler, Michael
  9. Hot off the press: News-implied sovereign default risk By Dim, Chukwuma; Koerner, Kevin; Wolski, Marcin; Zwart, Sanne
  10. Risk Through the Looking-Glass the pursuit of a return without the risk! From wealth creation to wealth extraction By Savvakis C. Savvides
  11. Russia's Ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention By \v{S}tefan Ly\'ocsa; Tom\'a\v{s} Pl\'ihal
  12. What Drives Credit Risk? Empirical Evidence from Southeast Europe By Nikola Fabris; Nina Vujanović
  13. Optimal bank capital requirements: What do the macroeconomic models say? By Gulan, Adam; Jokivuolle, Esa; Verona, Fabio
  14. Quantile return and volatility connectedness among Non-Fungible Tokens (NFTs) and (un)conventional assets By Urom, Christian; Ndubuisi, Gideon; Guesmi, Khaled

  1. By: Carole Bernard; Silvana M. Pesenti; Steven Vanduffel
    Abstract: The robustness of risk measures to changes in underlying loss distributions (distributional uncertainty) is of crucial importance in making well-informed decisions. In this paper, we quantify, for the class of distortion risk measures with an absolutely continuous distortion function, its robustness to distributional uncertainty by deriving its largest (smallest) value when the underlying loss distribution has a known mean and variance and, furthermore, lies within a ball - specified through the Wasserstein distance - around a reference distribution. We employ the technique of isotonic projections to provide for these distortion risk measures a complete characterisation of sharp bounds on their value, and we obtain quasi-explicit bounds in the case of Value-at-Risk and Range-Value-at-Risk. We extend our results to account for uncertainty in the first two moments and provide applications to portfolio optimisation and to model risk assessment.
    Date: 2022–05
  2. By: Marita Kuhlmann
    Abstract: In practice, the value-at-risk (VaR) for a longer holding period is often scaled using the 'square root of time rule'. The VaR is determined for a shorter holding period and then scaled up according to the desired holding period. For example, the Basel rules allow banks to scale up the 1-day VaR by the square root of ten to determine the 10-day VaR. It can be seen from the results of this thesis that scaling can also provide good and accurate estimates of VaR. However, it is probably much more important to consider that, depending on the methods or data set involved, there may also be significant consequences for risk provisioning. Particularly, since scaling does not always avoid the occurrence of losses that exceed the VaR estimate on a frequent basis over a period of time. Overall, the permission to use the square root of time rule in the regulatory framework should be reconsidered.
    Date: 2022–05
  3. By: Alhonita Yatie (BSE - Bordeaux Sciences Economiques - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper studies the impact of fear, uncertainty and market volatility caused by the Ukraine-Russia war on crypto-assets returns (Bitcoin and Ethereum) and Gold returns. We use the searches on Wikipedia trends as proxies of uncertainty and fear and two volatility indices: S&P500 VIX and the Russian VIX (RVIX). The results show that Bitcoin, Ethereum and Gold failed as safe havens during this war.
    Keywords: H56,Safe haven,Gold,crypto-assets,Russia,Ukraine,G15 War,G12,G32
    Date: 2022–03–23
  4. By: Elie Bouri (Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon); Afees A. Salisu (Centre for Econometrics & Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)
    Abstract: Recent research suggests stronger ties between Bitcoin and US stock markets. In this paper, we examine the predictive power of Bitcoin prices for the realized volatility of the US stock market index and its various sectoral indices. Using data over the period 22 November 2017 and 30 December 2021, we conduct in-sample and out-of-sample analyses over multiple forecast horizons and evidence that Bitcoin prices contain significant predictive power for the volatility of US stocks. Specifically, an inverse relationship exists between Bitcoin prices and the realized volatility of US stock sector indices. The model that includes Bitcoin prices consistent outperforms the benchmark historical average model, irrespective of the various stock sectors and multiple of forecast horizons. The use of Bitcoin prices as a predictor yields higher economic gains. These findings highlight the power and utility of observing Bitcoin prices when forecasting the realized volatility of US stock sectors, which matter to practitioners, and academics, and policymakers.
    Keywords: Bitcoin prices, S&P 500 index, US stock sector indices, realized volatility prediction, economic gains
    Date: 2022–05
  5. By: Stefan Nagel; Zhengyang Xu
    Abstract: We examine subjective risk premia implied by return expectations of individual investors and professionals for aggregate portfolios of stocks, bonds, currencies, and commodity futures. While in-sample predictive regressions with realized excess returns suggest that objective risk premia vary countercyclically with business cycle variables and aggregate asset valuation measures, subjective risk premia extracted from survey data do not comove much with these variables. This lack of cyclicality of subjective risk premia is a pervasive property that holds in expectations of different groups of market participants and in different asset classes. A similar lack of cyclicality appears in out-of-sample forecasts of excess returns, which suggests that investors’ learning of forecasting relationships in real time may explain much of the cyclicality gap. These findings cast doubt on models that explain time-varying objective risk premia inferred from in-sample regressions with countercyclical variation in perceived risk or risk aversion. We further find a link between subjective perceptions of risk and subjective risk premia, which points toward a positive risk-return tradeoff in subjective beliefs.
    Date: 2022
  6. By: Charles Shaw
    Abstract: We relax a number of assumptions in Alexeev and Tapon (2012) in order to account for non-normally distributed, skewed, multi-regime, and leptokurtic asset return distributions. We calibrate a Markov-modulated Levy process model to equity market data to demonstrate the merits of our approach, and show that the calibrated models do a good job of matching the empirical moments. Finally, we argue that much of the related literature on portfolio diversification relies on assumptions that are in tension with certain observable regularities and which, if ignored, may lead to underestimation of risk.
    Date: 2022–04
  7. By: Danny Brando; Antonis Kotidis; Anna Kovner; Michael Junho Lee; Stacey L. Schreft
    Abstract: Cyber risk, defined as the risk of loss from dependence on computer systems and digital technologies, has grown in the financial system. Cyber events, especially cyberattacks, are among the top risks cited in financial stability surveys in the United States and globally.
    Date: 2022–05–12
  8. By: Kogler, Michael
    Abstract: After the global financial crisis, the use of taxes to enhance financial stability received new attention. This paper compares two ways of taxing bank leverage, namely, an allowance for corporate equity (ACE), which addresses the debt bias in corporate taxation, and a Pigovian tax on bank debt (bank levy). We emphasize financial stability gains driven by lower bank asset risk and develop a principal-agent model, in which risk taking depends on the bank's capital structure and, by extension, on the tax treatment of debt and equity because of moral hazard. We find that (i) the ACE unambiguously reduces risk taking, (ii) bank levies reduce risk taking if they are independent of bank performance but may be counterproductive otherwise, (iii) high corporate tax rates render the bank levies less effective, and (iv) taxes are especially effective if capital requirements are low.
    Keywords: Pigovian taxes, corporate tax reform, bank risk taking, financial stability
    JEL: G21 G28 H25
    Date: 2022–05
  9. By: Dim, Chukwuma; Koerner, Kevin; Wolski, Marcin; Zwart, Sanne
    Abstract: We develop a sovereign default risk index using natural language processing techniques and 10 million news articles covering over 100 countries. The index is a highfrequency measure of countries' default risk, particularly for those lacking marketbased measures: it correlates with sovereign CDS spreads, predicts rating downgrades, and reflects default risk information not fully captured by CDS spreads. We assess the influence of sovereign default concerns on equity markets and find that spikes in the index are negatively associated with same-week market returns, which reverses over the next week, indicating that investors might overreact to default concerns. Equity markets' reaction to default concerns is more pronounced and persistent for countries with tight fiscal constraints. The response to global, compared to country-specific, default concerns is much stronger, underlining the relevance of global "push" factors for local asset prices.
    Keywords: Sovereign default,Credit risk,Equity returns,Machine learning,Naturallanguage processing,Early warning indicators
    JEL: F30 G12 G15
    Date: 2022
  10. By: Savvakis C. Savvides (Visiting Lecturer, John Deutsch Institute for the Study of Economic Policy, Queen’s University, Canada)
    Abstract: The question of what is really risk in capital investments is posed and discussed. It suggests that the almost total acceptance of the concept that volatility constitutes a good measure of risk is wrong and leads towards a misallocation of economic resources. It is argued that that the Expected Loss of a capital investment project should be used as a measure of risk. It is further illustrated how the risk aversion attitudes of potential investors can be taken into consideration in the decision to invest or not. The pursuit of return without risk inevitably leads to the transfer of wealth through a failing banking system which collaborates with an unregulated financial market who constantly seek low risk and relatively safe returns for the benefit of their wealthy clients. It is further argued that wasteful finance impairs the real economy and inevitably brings about financial crises and economic recessions. The promise of a “return without the risk†leads financial intermediaries in the direction of an elusive quest whereby the only way to attain this is through directing funding towards the capture of existing assets rather than investing in the real economy to create new wealth.
    Keywords: Economic development, repayment capability, project evaluation, corporate lending, credit risk.
    JEL: D61 G17 G21 G32 G33 H43
    Date: 2022–04–18
  11. By: \v{S}tefan Ly\'ocsa; Tom\'a\v{s} Pl\'ihal
    Abstract: The onset of the Russo-Ukrainian crisis has led to the rapid depreciation of the Russian ruble. In this study, we model intraday price fluctuations of the USD/RUB and the EUR/RUB exchange rates from the $1^{st}$ of December 2021 to the $7^{th}$ of March 2022. Our approach is novel in that instead of using daily (low-frequency) measures of attention and investor's expectations, we use intraday (high-frequency) data: google searches and implied volatility to proxy investor's attention and expectations. We show that both approaches are useful in predicting intraday price fluctuations of the two exchange rates, although implied volatility encompasses intraday attention.
    Date: 2022–05
  12. By: Nikola Fabris; Nina Vujanović (The Vienna Institute for International Economic Studies, wiiw)
    Abstract: Bank stability is an important aspect of financial stability, especially in bank-centric systems such as those in Southeast Europe. The financial crisis has shown that there is a particular need to monitor credit and other similar risks. Hence, it is important to analyse risks affecting the stability of both the banking sector and the financial system as a whole. To that end, central banks have developed macroprudential policies aiming to safeguard financial stability. However, little is known about the drivers of some financial risks. In that context, this study analyses the determinants of credit risk, which is the most prominent risk in the banking sectors of three selected Southeast European economies – Montenegro, Kosovo* and Bosnia and Herzegovina. Dynamic panel data techniques were applied to 48 banks, which represent almost the entire banking sectors in the respective countries. The empirical evidence has shown that both macroeconomic and bank-specific determinants represent influential factors driving credit risk in Southeast Europe. Particularly important macroeconomic factors affecting credit risk are business cycle and sovereign debt. On the other hand, bank size, capital levels, credit activity and profitability are the most prominent factors influencing credit risk in the region.
    Keywords: Credit Risk, Financial Stability, Southeast Europe, Banking
    JEL: G21 E37
    Date: 2022–05
  13. By: Gulan, Adam; Jokivuolle, Esa; Verona, Fabio
    Abstract: The optimal level of banks' capital requirements has been a key research topic since at least the introduction of the Basel rules in the late 1980s. In this paper, we review the literature, focusing on recent findings from quantitative structural macroeconomic models. While dynamic stochastic general equilibrium models capture second-round (general equilibrium) effects such as the feedback effects from macroeconomic outcomes back to financial intermediation and the dynamic evolution of the economy following regulatory changes, they suffer from tractability issues, including treatment of nonlinear effects, that typically force modeling simplifications. Additionally, studies tend to be concerned with determining the optimal level of fixed capital requirements. Only a handful offer estimates of the optimal size of the dynamic buffers. Since optimal dynamic macroprudential policies depend heavily on the nature of the underlying shocks, questions arise regarding the robustness and potential side effects of such plicies. Despite progress, the optimal level of bank capital requirements - in either fixed or dynamic form - remains largely an open research question.
    Date: 2022
  14. By: Urom, Christian (Paris School of Business, Paris); Ndubuisi, Gideon (UNU-MERIT, Maastricht University, and German Development Institute, Bonn); Guesmi, Khaled (Paris School of Business, Paris)
    Abstract: This paper uses the Quantile Vector-Autoregressive (Q-VAR) connectedness technique to examine the return and volatility connectedness among NFTs and (un)conventional assets including cryptocurrency, energy, technology, equity, precious metals, and fixed income financial assets across three quantiles corresponding to the normal, bearish, and bullish market conditions. It also explores the predictive powers of major macroeconomic and geopolitical indicators on the return and volatility connectedness across these three market conditions using a linear regression model. The main findings are as follows. First, the return and volatility connectedness vary across the market conditions, with the levels during the bearish and bullish market conditions being higher. Second, except under the bullish market condition, the total return connectedness is higher than those of total volatility connectedness. Third, NFTs are, at best, decoupled from (un)conventional assets during the normal market condition. Fourth, NFTs is a net return shock receivers except under the bullish market condition where it is a net transmitters. However, it is a net volatility shock receiver irrespective of the market condition. Fifth, during periods of economic crisis the total return and volatility connectedness rise (decreases) under the normal and bearish (bullish) market conditions. Finally, geopolitical risks, business environment conditions, and market and economic policy uncertainty are important predictors of return and volatility connectedness, although the predictive strength and direction vary across market conditions. We discuss the implications of our findings.
    Keywords: Non-Fungible Tokens, Green energy, Grey energy, Spillovers, Quantile connectedness
    JEL: G12 G14 G40 C58 G11
    Date: 2022–05–03

This nep-rmg issue is ©2022 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.